Table S1 from Pattern and process in hominin brain size evolution are scale-dependent Article Swipe
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.6084/m9.figshare.5873232
Excel spreadsheet with the raw data used for all analyses. Each row is a separate specimen along with its ID. Columns include the “lumper's” and “splitter's” taxonomy used in the random effects ANOVA to get inter-observer error (“lump.taxon” and “split.taxon”), the less and more speciose lineages used in the lower-taxonomic additive partitioning analyses (“lump.part” and “split.part”), region where each specimen comes from which aided in the allocation of specimens to lineages (“region”), grade for coding points in fig. 2 (“grade”), which specimens were excluded for the damaged specimens sensitivity analysis (“reliab.sens”), ECV replicate measurements from different researchers (“ecv1” to “ecv6”), and the various dates for each specimen (“min.date”, “max.date”, “mean.date”, and “sd.date”) and their respective age error distribution (“date.dist”).
Related Topics
- Type
- dataset
- Language
- en
- Landing Page
- https://doi.org/10.6084/m9.figshare.5873232
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394461782
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4394461782Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.6084/m9.figshare.5873232Digital Object Identifier
- Title
-
Table S1 from Pattern and process in hominin brain size evolution are scale-dependentWork title
- Type
-
datasetOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-01-01Full publication date if available
- Authors
-
Andrew Du, Andrew M. Zipkin, Kevin G. Hatala, Elizabeth Renner, Jennifer L. Baker, Serena Bianchi, Kallista H. Bernal, Bernard WoodList of authors in order
- Landing page
-
https://doi.org/10.6084/m9.figshare.5873232Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.6084/m9.figshare.5873232Direct OA link when available
- Concepts
-
Table (database), Scale (ratio), Process (computing), Geology, Evolutionary biology, Computer science, Geography, Biology, Data mining, Cartography, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4394461782 |
|---|---|
| doi | https://doi.org/10.6084/m9.figshare.5873232 |
| ids.doi | https://doi.org/10.6084/m9.figshare.5873232 |
| ids.openalex | https://openalex.org/W4394461782 |
| fwci | |
| type | dataset |
| title | Table S1 from Pattern and process in hominin brain size evolution are scale-dependent |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10676 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.8587999939918518 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1302 |
| topics[0].subfield.display_name | Aging |
| topics[0].display_name | Genetics, Aging, and Longevity in Model Organisms |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C45235069 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7091753482818604 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q278425 |
| concepts[0].display_name | Table (database) |
| concepts[1].id | https://openalex.org/C2778755073 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6020163297653198 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q10858537 |
| concepts[1].display_name | Scale (ratio) |
| concepts[2].id | https://openalex.org/C98045186 |
| concepts[2].level | 2 |
| concepts[2].score | 0.48111647367477417 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q205663 |
| concepts[2].display_name | Process (computing) |
| concepts[3].id | https://openalex.org/C127313418 |
| concepts[3].level | 0 |
| concepts[3].score | 0.32543933391571045 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[3].display_name | Geology |
| concepts[4].id | https://openalex.org/C78458016 |
| concepts[4].level | 1 |
| concepts[4].score | 0.3224707841873169 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q840400 |
| concepts[4].display_name | Evolutionary biology |
| concepts[5].id | https://openalex.org/C41008148 |
| concepts[5].level | 0 |
| concepts[5].score | 0.31985414028167725 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[5].display_name | Computer science |
| concepts[6].id | https://openalex.org/C205649164 |
| concepts[6].level | 0 |
| concepts[6].score | 0.22779381275177002 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1071 |
| concepts[6].display_name | Geography |
| concepts[7].id | https://openalex.org/C86803240 |
| concepts[7].level | 0 |
| concepts[7].score | 0.1908472776412964 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[7].display_name | Biology |
| concepts[8].id | https://openalex.org/C124101348 |
| concepts[8].level | 1 |
| concepts[8].score | 0.1902972161769867 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[8].display_name | Data mining |
| concepts[9].id | https://openalex.org/C58640448 |
| concepts[9].level | 1 |
| concepts[9].score | 0.18731191754341125 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q42515 |
| concepts[9].display_name | Cartography |
| concepts[10].id | https://openalex.org/C111919701 |
| concepts[10].level | 1 |
| concepts[10].score | 0.047543495893478394 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[10].display_name | Operating system |
| keywords[0].id | https://openalex.org/keywords/table |
| keywords[0].score | 0.7091753482818604 |
| keywords[0].display_name | Table (database) |
| keywords[1].id | https://openalex.org/keywords/scale |
| keywords[1].score | 0.6020163297653198 |
| keywords[1].display_name | Scale (ratio) |
| keywords[2].id | https://openalex.org/keywords/process |
| keywords[2].score | 0.48111647367477417 |
| keywords[2].display_name | Process (computing) |
| keywords[3].id | https://openalex.org/keywords/geology |
| keywords[3].score | 0.32543933391571045 |
| keywords[3].display_name | Geology |
| keywords[4].id | https://openalex.org/keywords/evolutionary-biology |
| keywords[4].score | 0.3224707841873169 |
| keywords[4].display_name | Evolutionary biology |
| keywords[5].id | https://openalex.org/keywords/computer-science |
| keywords[5].score | 0.31985414028167725 |
| keywords[5].display_name | Computer science |
| keywords[6].id | https://openalex.org/keywords/geography |
| keywords[6].score | 0.22779381275177002 |
| keywords[6].display_name | Geography |
| keywords[7].id | https://openalex.org/keywords/biology |
| keywords[7].score | 0.1908472776412964 |
| keywords[7].display_name | Biology |
| keywords[8].id | https://openalex.org/keywords/data-mining |
| keywords[8].score | 0.1902972161769867 |
| keywords[8].display_name | Data mining |
| keywords[9].id | https://openalex.org/keywords/cartography |
| keywords[9].score | 0.18731191754341125 |
| keywords[9].display_name | Cartography |
| keywords[10].id | https://openalex.org/keywords/operating-system |
| keywords[10].score | 0.047543495893478394 |
| keywords[10].display_name | Operating system |
| language | en |
| locations[0].id | doi:10.6084/m9.figshare.5873232 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | |
| locations[0].raw_type | dataset |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | False |
| locations[0].is_published | |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.6084/m9.figshare.5873232 |
| indexed_in | datacite |
| authorships[0].author.id | https://openalex.org/A5030613783 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-7381-5089 |
| authorships[0].author.display_name | Andrew Du |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Andrew Du |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5090231540 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-3813-8051 |
| authorships[1].author.display_name | Andrew M. Zipkin |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Andrew M. Zipkin |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5081329294 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-9131-5304 |
| authorships[2].author.display_name | Kevin G. Hatala |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Kevin G. Hatala |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5065348636 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-3363-4347 |
| authorships[3].author.display_name | Elizabeth Renner |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Elizabeth Renner |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5102862612 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-5192-2377 |
| authorships[4].author.display_name | Jennifer L. Baker |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Jennifer L. Baker |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5031607316 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-3731-5463 |
| authorships[5].author.display_name | Serena Bianchi |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Serena Bianchi |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5019729850 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Kallista H. Bernal |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Kallista H. Bernal |
| authorships[6].is_corresponding | False |
| authorships[7].author.id | https://openalex.org/A5026510296 |
| authorships[7].author.orcid | https://orcid.org/0000-0003-0273-7332 |
| authorships[7].author.display_name | Bernard Wood |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Bernard A. Wood |
| authorships[7].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.6084/m9.figshare.5873232 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Table S1 from Pattern and process in hominin brain size evolution are scale-dependent |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10676 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.8587999939918518 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1302 |
| primary_topic.subfield.display_name | Aging |
| primary_topic.display_name | Genetics, Aging, and Longevity in Model Organisms |
| related_works | https://openalex.org/W2324615561, https://openalex.org/W2086120259, https://openalex.org/W2245170124, https://openalex.org/W2076393078, https://openalex.org/W3186982001, https://openalex.org/W1984402782, https://openalex.org/W2137941439, https://openalex.org/W2004200960, https://openalex.org/W1999891779, https://openalex.org/W2029513011 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.6084/m9.figshare.5873232 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | |
| best_oa_location.raw_type | dataset |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.6084/m9.figshare.5873232 |
| primary_location.id | doi:10.6084/m9.figshare.5873232 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | |
| primary_location.raw_type | dataset |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.6084/m9.figshare.5873232 |
| publication_date | 2018-01-01 |
| publication_year | 2018 |
| referenced_works_count | 0 |
| abstract_inverted_index.2 | 78 |
| abstract_inverted_index.a | 13 |
| abstract_inverted_index.in | 28, 47, 64, 76 |
| abstract_inverted_index.is | 12 |
| abstract_inverted_index.of | 67 |
| abstract_inverted_index.to | 33, 69, 98 |
| abstract_inverted_index.ECV | 91 |
| abstract_inverted_index.ID. | 19 |
| abstract_inverted_index.age | 115 |
| abstract_inverted_index.all | 8 |
| abstract_inverted_index.and | 24, 38, 42, 54, 100, 110, 112 |
| abstract_inverted_index.for | 7, 73, 84, 104 |
| abstract_inverted_index.get | 34 |
| abstract_inverted_index.its | 18 |
| abstract_inverted_index.raw | 4 |
| abstract_inverted_index.row | 11 |
| abstract_inverted_index.the | 3, 22, 29, 40, 48, 65, 85, 101 |
| abstract_inverted_index.Each | 10 |
| abstract_inverted_index.data | 5 |
| abstract_inverted_index.each | 58, 105 |
| abstract_inverted_index.fig. | 77 |
| abstract_inverted_index.from | 61, 94 |
| abstract_inverted_index.less | 41 |
| abstract_inverted_index.more | 43 |
| abstract_inverted_index.used | 6, 27, 46 |
| abstract_inverted_index.were | 82 |
| abstract_inverted_index.with | 2, 17 |
| abstract_inverted_index.ANOVA | 32 |
| abstract_inverted_index.Excel | 0 |
| abstract_inverted_index.aided | 63 |
| abstract_inverted_index.along | 16 |
| abstract_inverted_index.comes | 60 |
| abstract_inverted_index.dates | 103 |
| abstract_inverted_index.error | 36, 116 |
| abstract_inverted_index.grade | 72 |
| abstract_inverted_index.their | 113 |
| abstract_inverted_index.where | 57 |
| abstract_inverted_index.which | 62, 80 |
| abstract_inverted_index.coding | 74 |
| abstract_inverted_index.points | 75 |
| abstract_inverted_index.random | 30 |
| abstract_inverted_index.region | 56 |
| abstract_inverted_index.Columns | 20 |
| abstract_inverted_index.damaged | 86 |
| abstract_inverted_index.effects | 31 |
| abstract_inverted_index.include | 21 |
| abstract_inverted_index.various | 102 |
| abstract_inverted_index.additive | 50 |
| abstract_inverted_index.analyses | 52 |
| abstract_inverted_index.analysis | 89 |
| abstract_inverted_index.excluded | 83 |
| abstract_inverted_index.lineages | 45, 70 |
| abstract_inverted_index.separate | 14 |
| abstract_inverted_index.specimen | 15, 59, 106 |
| abstract_inverted_index.speciose | 44 |
| abstract_inverted_index.taxonomy | 26 |
| abstract_inverted_index.analyses. | 9 |
| abstract_inverted_index.different | 95 |
| abstract_inverted_index.replicate | 92 |
| abstract_inverted_index.specimens | 68, 81, 87 |
| abstract_inverted_index.allocation | 66 |
| abstract_inverted_index.respective | 114 |
| abstract_inverted_index.(“ecv1” | 97 |
| abstract_inverted_index.researchers | 96 |
| abstract_inverted_index.sensitivity | 88 |
| abstract_inverted_index.spreadsheet | 1 |
| abstract_inverted_index.distribution | 117 |
| abstract_inverted_index.measurements | 93 |
| abstract_inverted_index.partitioning | 51 |
| abstract_inverted_index.“ecv6”), | 99 |
| abstract_inverted_index.(“grade”), | 79 |
| abstract_inverted_index.inter-observer | 35 |
| abstract_inverted_index.“lumper's” | 23 |
| abstract_inverted_index.“sd.date”) | 111 |
| abstract_inverted_index.(“region”), | 71 |
| abstract_inverted_index.lower-taxonomic | 49 |
| abstract_inverted_index.“max.date”, | 108 |
| abstract_inverted_index.(“lump.part” | 53 |
| abstract_inverted_index.(“min.date”, | 107 |
| abstract_inverted_index.“mean.date”, | 109 |
| abstract_inverted_index.“splitter's” | 25 |
| abstract_inverted_index.(“lump.taxon” | 37 |
| abstract_inverted_index.(“date.dist”). | 118 |
| abstract_inverted_index.“split.part”), | 55 |
| abstract_inverted_index.“split.taxon”), | 39 |
| abstract_inverted_index.(“reliab.sens”), | 90 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |