A rubric for assessing conformance to the Ten Rules for credible practice of modeling and simulation in healthcare Article Swipe
Alexandra Manchel
,
Ahmet Erdemir
,
Lealem Mulugeta
,
Joy P. Ku
,
Bruno V. Rego
,
Marc Horner
,
William W. Lytton
,
Jerry G. Myers
,
Rajanikanth Vadigepalli
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.10.31.24316520
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.10.31.24316520
The power of computational modeling and simulation (M&S) is realized when the results are credible, and the workflow generates evidence that supports credibility for the context of use. The Committee on Credible Practice of Modeling & Simulation in Healthcare was established to help address the need for processes and procedures to support the credible use of M&S in healthcare and biomedical research. Our community efforts have led to the Ten Rules (TR) for Credible Practice of M&S in life sciences and healthcare. This framework is an outcome of a multidisciplinary investigation from a wide range of stakeholders beginning in 2012. Here, we present a pragmatic rubric for assessing the conformance of an M&S activity to the TR. This rubric considers the ability of the M&S to facilitate outreach of the results to a wide range of stakeholders from context-specific M&S practitioners to policymakers. It uses an ordinal scale ranging from Insufficient (zero) to Comprehensive (four) that is applicable to each rule, providing a uniform approach for comparing assessments across different reviewers and different models. We used the rubric to evaluate the conformance of two computational modeling activities: 1. six viral disease (COVID-19) propagation models, and 2. a model of hepatic glycogenolysis with neural innervation and calcium signaling. These examples were used to evaluate the applicability of the rubric and illustrate rubric usage in real-world M&S scenarios including those that bridge scientific M&S with policymaking. The COVID-19 M&S studies were of particular interest because they needed to be quickly operationalized by government and private decision-makers early in the COVID-19 pandemic and were accessible as open-source tools. Our findings demonstrate that the TR rubric represents a systematic tool for assessing the conformance of an M&S activity to codified good practices and enhances the value of the TR for supporting real-world decision-making.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.10.31.24316520
- https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdf
- OA Status
- green
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403999103
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4403999103Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2024.10.31.24316520Digital Object Identifier
- Title
-
A rubric for assessing conformance to the Ten Rules for credible practice of modeling and simulation in healthcareWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-02Full publication date if available
- Authors
-
Alexandra Manchel, Ahmet Erdemir, Lealem Mulugeta, Joy P. Ku, Bruno V. Rego, Marc Horner, William W. Lytton, Jerry G. Myers, Rajanikanth VadigepalliList of authors in order
- Landing page
-
https://doi.org/10.1101/2024.10.31.24316520Publisher landing page
- PDF URL
-
https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdfDirect OA link when available
- Concepts
-
Rubric, Health care, Computer science, Process management, Accounting, Engineering management, Business, Engineering, Psychology, Political science, Mathematics education, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4403999103 |
|---|---|
| doi | https://doi.org/10.1101/2024.10.31.24316520 |
| ids.doi | https://doi.org/10.1101/2024.10.31.24316520 |
| ids.openalex | https://openalex.org/W4403999103 |
| fwci | 0.0 |
| type | preprint |
| title | A rubric for assessing conformance to the Ten Rules for credible practice of modeling and simulation in healthcare |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10350 |
| topics[0].field.id | https://openalex.org/fields/36 |
| topics[0].field.display_name | Health Professions |
| topics[0].score | 0.9627000093460083 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3605 |
| topics[0].subfield.display_name | Health Information Management |
| topics[0].display_name | Electronic Health Records Systems |
| topics[1].id | https://openalex.org/T11773 |
| topics[1].field.id | https://openalex.org/fields/36 |
| topics[1].field.display_name | Health Professions |
| topics[1].score | 0.9101999998092651 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/3604 |
| topics[1].subfield.display_name | Emergency Medical Services |
| topics[1].display_name | Healthcare Operations and Scheduling Optimization |
| topics[2].id | https://openalex.org/T10629 |
| topics[2].field.id | https://openalex.org/fields/36 |
| topics[2].field.display_name | Health Professions |
| topics[2].score | 0.9093000292778015 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3600 |
| topics[2].subfield.display_name | General Health Professions |
| topics[2].display_name | Health Policy Implementation Science |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C111640148 |
| concepts[0].level | 2 |
| concepts[0].score | 0.9518630504608154 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q847349 |
| concepts[0].display_name | Rubric |
| concepts[1].id | https://openalex.org/C160735492 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6270486116409302 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q31207 |
| concepts[1].display_name | Health care |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.4886777698993683 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C195094911 |
| concepts[3].level | 1 |
| concepts[3].score | 0.38692519068717957 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q14167904 |
| concepts[3].display_name | Process management |
| concepts[4].id | https://openalex.org/C121955636 |
| concepts[4].level | 1 |
| concepts[4].score | 0.32679110765457153 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q4116214 |
| concepts[4].display_name | Accounting |
| concepts[5].id | https://openalex.org/C110354214 |
| concepts[5].level | 1 |
| concepts[5].score | 0.32609057426452637 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q6314146 |
| concepts[5].display_name | Engineering management |
| concepts[6].id | https://openalex.org/C144133560 |
| concepts[6].level | 0 |
| concepts[6].score | 0.29981106519699097 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q4830453 |
| concepts[6].display_name | Business |
| concepts[7].id | https://openalex.org/C127413603 |
| concepts[7].level | 0 |
| concepts[7].score | 0.2705497145652771 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[7].display_name | Engineering |
| concepts[8].id | https://openalex.org/C15744967 |
| concepts[8].level | 0 |
| concepts[8].score | 0.23296406865119934 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[8].display_name | Psychology |
| concepts[9].id | https://openalex.org/C17744445 |
| concepts[9].level | 0 |
| concepts[9].score | 0.21159574389457703 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[9].display_name | Political science |
| concepts[10].id | https://openalex.org/C145420912 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0817980170249939 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q853077 |
| concepts[10].display_name | Mathematics education |
| concepts[11].id | https://openalex.org/C199539241 |
| concepts[11].level | 1 |
| concepts[11].score | 0.06817948818206787 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[11].display_name | Law |
| keywords[0].id | https://openalex.org/keywords/rubric |
| keywords[0].score | 0.9518630504608154 |
| keywords[0].display_name | Rubric |
| keywords[1].id | https://openalex.org/keywords/health-care |
| keywords[1].score | 0.6270486116409302 |
| keywords[1].display_name | Health care |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.4886777698993683 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/process-management |
| keywords[3].score | 0.38692519068717957 |
| keywords[3].display_name | Process management |
| keywords[4].id | https://openalex.org/keywords/accounting |
| keywords[4].score | 0.32679110765457153 |
| keywords[4].display_name | Accounting |
| keywords[5].id | https://openalex.org/keywords/engineering-management |
| keywords[5].score | 0.32609057426452637 |
| keywords[5].display_name | Engineering management |
| keywords[6].id | https://openalex.org/keywords/business |
| keywords[6].score | 0.29981106519699097 |
| keywords[6].display_name | Business |
| keywords[7].id | https://openalex.org/keywords/engineering |
| keywords[7].score | 0.2705497145652771 |
| keywords[7].display_name | Engineering |
| keywords[8].id | https://openalex.org/keywords/psychology |
| keywords[8].score | 0.23296406865119934 |
| keywords[8].display_name | Psychology |
| keywords[9].id | https://openalex.org/keywords/political-science |
| keywords[9].score | 0.21159574389457703 |
| keywords[9].display_name | Political science |
| keywords[10].id | https://openalex.org/keywords/mathematics-education |
| keywords[10].score | 0.0817980170249939 |
| keywords[10].display_name | Mathematics education |
| keywords[11].id | https://openalex.org/keywords/law |
| keywords[11].score | 0.06817948818206787 |
| keywords[11].display_name | Law |
| language | en |
| locations[0].id | doi:10.1101/2024.10.31.24316520 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306402567 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| locations[0].source.host_organization | https://openalex.org/I2750212522 |
| locations[0].source.host_organization_name | Cold Spring Harbor Laboratory |
| locations[0].source.host_organization_lineage | https://openalex.org/I2750212522 |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/2024.10.31.24316520 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5087059029 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-6946-3829 |
| authorships[0].author.display_name | Alexandra Manchel |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I149251103 |
| authorships[0].affiliations[0].raw_affiliation_string | Thomas Jefferson University |
| authorships[0].institutions[0].id | https://openalex.org/I149251103 |
| authorships[0].institutions[0].ror | https://ror.org/00ysqcn41 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I149251103 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Thomas Jefferson University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Alexandra Manchel |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Thomas Jefferson University |
| authorships[1].author.id | https://openalex.org/A5026010532 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-4629-8055 |
| authorships[1].author.display_name | Ahmet Erdemir |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I36373038 |
| authorships[1].affiliations[0].raw_affiliation_string | Cleveland Clinic Lerner Research Institute |
| authorships[1].institutions[0].id | https://openalex.org/I36373038 |
| authorships[1].institutions[0].ror | https://ror.org/02x4b0932 |
| authorships[1].institutions[0].type | healthcare |
| authorships[1].institutions[0].lineage | https://openalex.org/I1316902750, https://openalex.org/I36373038 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | Cleveland Clinic Lerner College of Medicine |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Ahmet Erdemir |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Cleveland Clinic Lerner Research Institute |
| authorships[2].author.id | https://openalex.org/A5039031909 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-2978-0114 |
| authorships[2].author.display_name | Lealem Mulugeta |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210118119 |
| authorships[2].affiliations[0].raw_affiliation_string | InSilico Labs LLC |
| authorships[2].institutions[0].id | https://openalex.org/I4210118119 |
| authorships[2].institutions[0].ror | https://ror.org/02p5qdz58 |
| authorships[2].institutions[0].type | company |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210118119 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | Insilicos (United States) |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Lealem Mulugeta |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | InSilico Labs LLC |
| authorships[3].author.id | https://openalex.org/A5005101585 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-4785-6044 |
| authorships[3].author.display_name | Joy P. Ku |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I97018004 |
| authorships[3].affiliations[0].raw_affiliation_string | Stanford University |
| authorships[3].institutions[0].id | https://openalex.org/I97018004 |
| authorships[3].institutions[0].ror | https://ror.org/00f54p054 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I97018004 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Stanford University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Joy P. Ku |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Stanford University |
| authorships[4].author.id | https://openalex.org/A5035877104 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-6315-693X |
| authorships[4].author.display_name | Bruno V. Rego |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I121820613 |
| authorships[4].affiliations[0].raw_affiliation_string | Louisiana State University |
| authorships[4].institutions[0].id | https://openalex.org/I121820613 |
| authorships[4].institutions[0].ror | https://ror.org/05ect4e57 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I121820613 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | Louisiana State University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Bruno V. Rego |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Louisiana State University |
| authorships[5].author.id | https://openalex.org/A5011836743 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-2483-5796 |
| authorships[5].author.display_name | Marc Horner |
| authorships[5].countries | US |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I21160419 |
| authorships[5].affiliations[0].raw_affiliation_string | Ansys Inc |
| authorships[5].institutions[0].id | https://openalex.org/I21160419 |
| authorships[5].institutions[0].ror | https://ror.org/05cf5b117 |
| authorships[5].institutions[0].type | company |
| authorships[5].institutions[0].lineage | https://openalex.org/I21160419 |
| authorships[5].institutions[0].country_code | US |
| authorships[5].institutions[0].display_name | Ansys (United States) |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Marc Horner |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Ansys Inc |
| authorships[6].author.id | https://openalex.org/A5082122443 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-3727-2849 |
| authorships[6].author.display_name | William W. Lytton |
| authorships[6].countries | US |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I181697535 |
| authorships[6].affiliations[0].raw_affiliation_string | SUNY Downstate Health Sciences University |
| authorships[6].institutions[0].id | https://openalex.org/I181697535 |
| authorships[6].institutions[0].ror | https://ror.org/0041qmd21 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I181697535 |
| authorships[6].institutions[0].country_code | US |
| authorships[6].institutions[0].display_name | SUNY Downstate Health Sciences University |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | William W Lytton |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | SUNY Downstate Health Sciences University |
| authorships[7].author.id | https://openalex.org/A5070129549 |
| authorships[7].author.orcid | https://orcid.org/0000-0001-9775-4850 |
| authorships[7].author.display_name | Jerry G. Myers |
| authorships[7].countries | US |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I2799786008 |
| authorships[7].affiliations[0].raw_affiliation_string | NASA John H Glenn Research Center |
| authorships[7].institutions[0].id | https://openalex.org/I2799786008 |
| authorships[7].institutions[0].ror | https://ror.org/059fqnc42 |
| authorships[7].institutions[0].type | facility |
| authorships[7].institutions[0].lineage | https://openalex.org/I2799786008, https://openalex.org/I4210124779 |
| authorships[7].institutions[0].country_code | US |
| authorships[7].institutions[0].display_name | Glenn Research Center |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Jerry G. Myers |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | NASA John H Glenn Research Center |
| authorships[8].author.id | https://openalex.org/A5039987858 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-8405-1037 |
| authorships[8].author.display_name | Rajanikanth Vadigepalli |
| authorships[8].countries | US |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I149251103 |
| authorships[8].affiliations[0].raw_affiliation_string | Thomas Jefferson University Sidney Kimmel Medical College |
| authorships[8].institutions[0].id | https://openalex.org/I149251103 |
| authorships[8].institutions[0].ror | https://ror.org/00ysqcn41 |
| authorships[8].institutions[0].type | education |
| authorships[8].institutions[0].lineage | https://openalex.org/I149251103 |
| authorships[8].institutions[0].country_code | US |
| authorships[8].institutions[0].display_name | Thomas Jefferson University |
| authorships[8].author_position | last |
| authorships[8].raw_author_name | Rajanikanth Vadigepalli |
| authorships[8].is_corresponding | True |
| authorships[8].raw_affiliation_strings | Thomas Jefferson University Sidney Kimmel Medical College |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | A rubric for assessing conformance to the Ten Rules for credible practice of modeling and simulation in healthcare |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10350 |
| primary_topic.field.id | https://openalex.org/fields/36 |
| primary_topic.field.display_name | Health Professions |
| primary_topic.score | 0.9627000093460083 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3605 |
| primary_topic.subfield.display_name | Health Information Management |
| primary_topic.display_name | Electronic Health Records Systems |
| related_works | https://openalex.org/W2748952813, https://openalex.org/W1987813225, https://openalex.org/W4390610055, https://openalex.org/W4379053243, https://openalex.org/W3021020626, https://openalex.org/W2955201676, https://openalex.org/W2153005530, https://openalex.org/W3199392376, https://openalex.org/W4321385307, https://openalex.org/W2330342969 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1101/2024.10.31.24316520 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306402567 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| best_oa_location.source.host_organization | https://openalex.org/I2750212522 |
| best_oa_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.1101/2024.10.31.24316520 |
| primary_location.id | doi:10.1101/2024.10.31.24316520 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306402567 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| primary_location.source.host_organization | https://openalex.org/I2750212522 |
| primary_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| primary_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.medrxiv.org/content/medrxiv/early/2024/11/02/2024.10.31.24316520.full.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/2024.10.31.24316520 |
| publication_date | 2024-11-02 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W4401418803, https://openalex.org/W4385295938, https://openalex.org/W3091749330, https://openalex.org/W1969397196, https://openalex.org/W2508693207, https://openalex.org/W3048821551, https://openalex.org/W3018741847, https://openalex.org/W3021995053, https://openalex.org/W3046527520, https://openalex.org/W3135185765, https://openalex.org/W4384926244, https://openalex.org/W4281766215, https://openalex.org/W3093610264, https://openalex.org/W3012284084, https://openalex.org/W3010131837, https://openalex.org/W3032971139, https://openalex.org/W3014687595, https://openalex.org/W3216475342, https://openalex.org/W2131966673, https://openalex.org/W3214383379 |
| referenced_works_count | 20 |
| abstract_inverted_index.a | 89, 93, 104, 133, 163, 197, 274 |
| abstract_inverted_index.1. | 188 |
| abstract_inverted_index.2. | 196 |
| abstract_inverted_index.It | 144 |
| abstract_inverted_index.TR | 271, 295 |
| abstract_inverted_index.We | 175 |
| abstract_inverted_index.an | 86, 112, 146, 282 |
| abstract_inverted_index.as | 263 |
| abstract_inverted_index.be | 247 |
| abstract_inverted_index.by | 250 |
| abstract_inverted_index.in | 38, 58, 78, 99, 223, 256 |
| abstract_inverted_index.is | 9, 85, 157 |
| abstract_inverted_index.of | 3, 27, 34, 56, 76, 88, 96, 111, 123, 129, 136, 183, 199, 216, 240, 281, 293 |
| abstract_inverted_index.on | 31 |
| abstract_inverted_index.to | 42, 51, 68, 115, 126, 132, 142, 153, 159, 179, 212, 246, 285 |
| abstract_inverted_index.we | 102 |
| abstract_inverted_index.Our | 63, 266 |
| abstract_inverted_index.TR. | 117 |
| abstract_inverted_index.Ten | 70 |
| abstract_inverted_index.The | 1, 29, 235 |
| abstract_inverted_index.and | 6, 16, 49, 60, 81, 172, 195, 205, 219, 252, 260, 289 |
| abstract_inverted_index.are | 14 |
| abstract_inverted_index.for | 24, 47, 73, 107, 166, 277, 296 |
| abstract_inverted_index.led | 67 |
| abstract_inverted_index.six | 189 |
| abstract_inverted_index.the | 12, 17, 25, 45, 53, 69, 109, 116, 121, 124, 130, 177, 181, 214, 217, 257, 270, 279, 291, 294 |
| abstract_inverted_index.two | 184 |
| abstract_inverted_index.use | 55 |
| abstract_inverted_index.was | 40 |
| abstract_inverted_index.(TR) | 72 |
| abstract_inverted_index.This | 83, 118 |
| abstract_inverted_index.each | 160 |
| abstract_inverted_index.from | 92, 138, 150 |
| abstract_inverted_index.good | 287 |
| abstract_inverted_index.have | 66 |
| abstract_inverted_index.help | 43 |
| abstract_inverted_index.life | 79 |
| abstract_inverted_index.need | 46 |
| abstract_inverted_index.that | 21, 156, 229, 269 |
| abstract_inverted_index.they | 244 |
| abstract_inverted_index.tool | 276 |
| abstract_inverted_index.use. | 28 |
| abstract_inverted_index.used | 176, 211 |
| abstract_inverted_index.uses | 145 |
| abstract_inverted_index.were | 210, 239, 261 |
| abstract_inverted_index.when | 11 |
| abstract_inverted_index.wide | 94, 134 |
| abstract_inverted_index.with | 202, 233 |
| abstract_inverted_index.& | 36 |
| abstract_inverted_index.2012. | 100 |
| abstract_inverted_index.Here, | 101 |
| abstract_inverted_index.Rules | 71 |
| abstract_inverted_index.These | 208 |
| abstract_inverted_index.early | 255 |
| abstract_inverted_index.model | 198 |
| abstract_inverted_index.power | 2 |
| abstract_inverted_index.range | 95, 135 |
| abstract_inverted_index.rule, | 161 |
| abstract_inverted_index.scale | 148 |
| abstract_inverted_index.those | 228 |
| abstract_inverted_index.usage | 222 |
| abstract_inverted_index.value | 292 |
| abstract_inverted_index.viral | 190 |
| abstract_inverted_index.(four) | 155 |
| abstract_inverted_index.(zero) | 152 |
| abstract_inverted_index.across | 169 |
| abstract_inverted_index.bridge | 230 |
| abstract_inverted_index.needed | 245 |
| abstract_inverted_index.neural | 203 |
| abstract_inverted_index.rubric | 106, 119, 178, 218, 221, 272 |
| abstract_inverted_index.tools. | 265 |
| abstract_inverted_index.M&S | 57, 77, 113, 125, 140, 225, 232, 237, 283 |
| abstract_inverted_index.ability | 122 |
| abstract_inverted_index.address | 44 |
| abstract_inverted_index.because | 243 |
| abstract_inverted_index.calcium | 206 |
| abstract_inverted_index.context | 26 |
| abstract_inverted_index.disease | 191 |
| abstract_inverted_index.efforts | 65 |
| abstract_inverted_index.hepatic | 200 |
| abstract_inverted_index.models, | 194 |
| abstract_inverted_index.models. | 174 |
| abstract_inverted_index.ordinal | 147 |
| abstract_inverted_index.outcome | 87 |
| abstract_inverted_index.present | 103 |
| abstract_inverted_index.private | 253 |
| abstract_inverted_index.quickly | 248 |
| abstract_inverted_index.ranging | 149 |
| abstract_inverted_index.results | 13, 131 |
| abstract_inverted_index.studies | 238 |
| abstract_inverted_index.support | 52 |
| abstract_inverted_index.uniform | 164 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.COVID-19 | 236, 258 |
| abstract_inverted_index.Credible | 32, 74 |
| abstract_inverted_index.Modeling | 35 |
| abstract_inverted_index.Practice | 33, 75 |
| abstract_inverted_index.activity | 114, 284 |
| abstract_inverted_index.approach | 165 |
| abstract_inverted_index.codified | 286 |
| abstract_inverted_index.credible | 54 |
| abstract_inverted_index.enhances | 290 |
| abstract_inverted_index.evaluate | 180, 213 |
| abstract_inverted_index.evidence | 20 |
| abstract_inverted_index.examples | 209 |
| abstract_inverted_index.findings | 267 |
| abstract_inverted_index.interest | 242 |
| abstract_inverted_index.modeling | 5, 186 |
| abstract_inverted_index.outreach | 128 |
| abstract_inverted_index.pandemic | 259 |
| abstract_inverted_index.realized | 10 |
| abstract_inverted_index.sciences | 80 |
| abstract_inverted_index.supports | 22 |
| abstract_inverted_index.workflow | 18 |
| abstract_inverted_index.(M&S) | 8 |
| abstract_inverted_index.Committee | 30 |
| abstract_inverted_index.assessing | 108, 278 |
| abstract_inverted_index.beginning | 98 |
| abstract_inverted_index.community | 64 |
| abstract_inverted_index.comparing | 167 |
| abstract_inverted_index.considers | 120 |
| abstract_inverted_index.credible, | 15 |
| abstract_inverted_index.different | 170, 173 |
| abstract_inverted_index.framework | 84 |
| abstract_inverted_index.generates | 19 |
| abstract_inverted_index.including | 227 |
| abstract_inverted_index.practices | 288 |
| abstract_inverted_index.pragmatic | 105 |
| abstract_inverted_index.processes | 48 |
| abstract_inverted_index.providing | 162 |
| abstract_inverted_index.research. | 62 |
| abstract_inverted_index.reviewers | 171 |
| abstract_inverted_index.scenarios | 226 |
| abstract_inverted_index.(COVID-19) | 192 |
| abstract_inverted_index.Healthcare | 39 |
| abstract_inverted_index.Simulation | 37 |
| abstract_inverted_index.accessible | 262 |
| abstract_inverted_index.applicable | 158 |
| abstract_inverted_index.biomedical | 61 |
| abstract_inverted_index.facilitate | 127 |
| abstract_inverted_index.government | 251 |
| abstract_inverted_index.healthcare | 59 |
| abstract_inverted_index.illustrate | 220 |
| abstract_inverted_index.particular | 241 |
| abstract_inverted_index.procedures | 50 |
| abstract_inverted_index.real-world | 224, 298 |
| abstract_inverted_index.represents | 273 |
| abstract_inverted_index.scientific | 231 |
| abstract_inverted_index.signaling. | 207 |
| abstract_inverted_index.simulation | 7 |
| abstract_inverted_index.supporting | 297 |
| abstract_inverted_index.systematic | 275 |
| abstract_inverted_index.activities: | 187 |
| abstract_inverted_index.assessments | 168 |
| abstract_inverted_index.conformance | 110, 182, 280 |
| abstract_inverted_index.credibility | 23 |
| abstract_inverted_index.demonstrate | 268 |
| abstract_inverted_index.established | 41 |
| abstract_inverted_index.healthcare. | 82 |
| abstract_inverted_index.innervation | 204 |
| abstract_inverted_index.open-source | 264 |
| abstract_inverted_index.propagation | 193 |
| abstract_inverted_index.Insufficient | 151 |
| abstract_inverted_index.stakeholders | 97, 137 |
| abstract_inverted_index.Comprehensive | 154 |
| abstract_inverted_index.applicability | 215 |
| abstract_inverted_index.computational | 4, 185 |
| abstract_inverted_index.investigation | 91 |
| abstract_inverted_index.policymakers. | 143 |
| abstract_inverted_index.policymaking. | 234 |
| abstract_inverted_index.practitioners | 141 |
| abstract_inverted_index.glycogenolysis | 201 |
| abstract_inverted_index.decision-makers | 254 |
| abstract_inverted_index.operationalized | 249 |
| abstract_inverted_index.context-specific | 139 |
| abstract_inverted_index.decision-making. | 299 |
| abstract_inverted_index.multidisciplinary | 90 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5039987858 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I149251103 |
| citation_normalized_percentile.value | 0.29724697 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |