An entropy model of decision uncertainty Article Swipe
Studying metacognition, the introspection of one’s own decisions, can provide insights into the mechanisms underlying the decisions. Here we show that observers’ uncertainty about their decisions incorporates both the entropy of the stimuli and the entropy of their response probabilities across the psychometric function. Describing uncertainty data with a functional form permits the measurement of internal parameters not measurable from the decision responses alone. To test and demonstrate the utility of this novel model, we measured uncertainty in 11 participants as they judged the relative contrast appearance of two stimuli in several experiments employing explicit bias or attentional cues. The entropy model enabled an otherwise intractable quantitative analysis of participants’ uncertainty, which in one case distinguished two comparative judgments that produced nearly identical psychometric functions. In contrast, comparative and equality judgments with different behavioral reports, yielded uncertainty reports that were not significantly different. The entropy model was able to successfully account for uncertainty in these two different types of decisions that resulted in differently shaped psychometric functions, and the entropy contribution from the stimuli, which were identical across experiments, was consistent. An observer’s uncertainty could therefore be measured as the total entropy of the inputs and outputs of the stimulus-response system, i.e. the entropy of the stimuli plus the entropy of the observer’s responses.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31234/osf.io/hveac_v2
- https://osf.io/hveac_v2/download
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413009342
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4413009342Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.31234/osf.io/hveac_v2Digital Object Identifier
- Title
-
An entropy model of decision uncertaintyWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-08-06Full publication date if available
- Authors
-
Keith A. SchneiderList of authors in order
- Landing page
-
https://doi.org/10.31234/osf.io/hveac_v2Publisher landing page
- PDF URL
-
https://osf.io/hveac_v2/downloadDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://osf.io/hveac_v2/downloadDirect OA link when available
- Concepts
-
Entropy (arrow of time), Econometrics, Statistical physics, Computer science, Mathematics, Physics, ThermodynamicsTop 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/W4413009342 |
|---|---|
| doi | https://doi.org/10.31234/osf.io/hveac_v2 |
| ids.doi | https://doi.org/10.31234/osf.io/hveac_v2 |
| ids.openalex | https://openalex.org/W4413009342 |
| fwci | 0.0 |
| type | preprint |
| title | An entropy model of decision uncertainty |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10042 |
| topics[0].field.id | https://openalex.org/fields/28 |
| topics[0].field.display_name | Neuroscience |
| topics[0].score | 0.9695000052452087 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2805 |
| topics[0].subfield.display_name | Cognitive Neuroscience |
| topics[0].display_name | Neural and Behavioral Psychology Studies |
| topics[1].id | https://openalex.org/T10315 |
| topics[1].field.id | https://openalex.org/fields/18 |
| topics[1].field.display_name | Decision Sciences |
| topics[1].score | 0.9510999917984009 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1800 |
| topics[1].subfield.display_name | General Decision Sciences |
| topics[1].display_name | Decision-Making and Behavioral Economics |
| topics[2].id | https://openalex.org/T11542 |
| topics[2].field.id | https://openalex.org/fields/32 |
| topics[2].field.display_name | Psychology |
| topics[2].score | 0.9251999855041504 |
| topics[2].domain.id | https://openalex.org/domains/2 |
| topics[2].domain.display_name | Social Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3202 |
| topics[2].subfield.display_name | Applied Psychology |
| topics[2].display_name | Behavioral Health and Interventions |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C106301342 |
| concepts[0].level | 2 |
| concepts[0].score | 0.43617239594459534 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q4117933 |
| concepts[0].display_name | Entropy (arrow of time) |
| concepts[1].id | https://openalex.org/C149782125 |
| concepts[1].level | 1 |
| concepts[1].score | 0.40120819211006165 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q160039 |
| concepts[1].display_name | Econometrics |
| concepts[2].id | https://openalex.org/C121864883 |
| concepts[2].level | 1 |
| concepts[2].score | 0.35743236541748047 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q677916 |
| concepts[2].display_name | Statistical physics |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.32540249824523926 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C33923547 |
| concepts[4].level | 0 |
| concepts[4].score | 0.3242245316505432 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[4].display_name | Mathematics |
| concepts[5].id | https://openalex.org/C121332964 |
| concepts[5].level | 0 |
| concepts[5].score | 0.15496015548706055 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[5].display_name | Physics |
| concepts[6].id | https://openalex.org/C97355855 |
| concepts[6].level | 1 |
| concepts[6].score | 0.11701017618179321 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11473 |
| concepts[6].display_name | Thermodynamics |
| keywords[0].id | https://openalex.org/keywords/entropy |
| keywords[0].score | 0.43617239594459534 |
| keywords[0].display_name | Entropy (arrow of time) |
| keywords[1].id | https://openalex.org/keywords/econometrics |
| keywords[1].score | 0.40120819211006165 |
| keywords[1].display_name | Econometrics |
| keywords[2].id | https://openalex.org/keywords/statistical-physics |
| keywords[2].score | 0.35743236541748047 |
| keywords[2].display_name | Statistical physics |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.32540249824523926 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/mathematics |
| keywords[4].score | 0.3242245316505432 |
| keywords[4].display_name | Mathematics |
| keywords[5].id | https://openalex.org/keywords/physics |
| keywords[5].score | 0.15496015548706055 |
| keywords[5].display_name | Physics |
| keywords[6].id | https://openalex.org/keywords/thermodynamics |
| keywords[6].score | 0.11701017618179321 |
| keywords[6].display_name | Thermodynamics |
| language | en |
| locations[0].id | doi:10.31234/osf.io/hveac_v2 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://osf.io/hveac_v2/download |
| 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/10.31234/osf.io/hveac_v2 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5071929477 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7120-3380 |
| authorships[0].author.display_name | Keith A. Schneider |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Keith A Schneider |
| authorships[0].is_corresponding | True |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://osf.io/hveac_v2/download |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | An entropy model of decision uncertainty |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10042 |
| primary_topic.field.id | https://openalex.org/fields/28 |
| primary_topic.field.display_name | Neuroscience |
| primary_topic.score | 0.9695000052452087 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2805 |
| primary_topic.subfield.display_name | Cognitive Neuroscience |
| primary_topic.display_name | Neural and Behavioral Psychology Studies |
| related_works | https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W4391375266, https://openalex.org/W1979597421, https://openalex.org/W2007980826, https://openalex.org/W2061531152, https://openalex.org/W3002753104, https://openalex.org/W2077600819, https://openalex.org/W2142036596, https://openalex.org/W2180033908 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.31234/osf.io/hveac_v2 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://osf.io/hveac_v2/download |
| 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/10.31234/osf.io/hveac_v2 |
| primary_location.id | doi:10.31234/osf.io/hveac_v2 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://osf.io/hveac_v2/download |
| 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/10.31234/osf.io/hveac_v2 |
| publication_date | 2025-08-06 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 48 |
| abstract_inverted_index.11 | 78 |
| abstract_inverted_index.An | 181 |
| abstract_inverted_index.In | 125 |
| abstract_inverted_index.To | 64 |
| abstract_inverted_index.an | 103 |
| abstract_inverted_index.as | 80, 188 |
| abstract_inverted_index.be | 186 |
| abstract_inverted_index.in | 77, 90, 112, 153, 162 |
| abstract_inverted_index.of | 4, 30, 36, 54, 70, 87, 108, 158, 192, 197, 204, 210 |
| abstract_inverted_index.or | 96 |
| abstract_inverted_index.to | 148 |
| abstract_inverted_index.we | 18, 74 |
| abstract_inverted_index.The | 99, 143 |
| abstract_inverted_index.and | 33, 66, 128, 167, 195 |
| abstract_inverted_index.can | 8 |
| abstract_inverted_index.for | 151 |
| abstract_inverted_index.not | 57, 140 |
| abstract_inverted_index.one | 113 |
| abstract_inverted_index.own | 6 |
| abstract_inverted_index.the | 2, 12, 15, 28, 31, 34, 41, 52, 60, 68, 83, 168, 172, 189, 193, 198, 202, 205, 208, 211 |
| abstract_inverted_index.two | 88, 116, 155 |
| abstract_inverted_index.was | 146, 179 |
| abstract_inverted_index.Here | 17 |
| abstract_inverted_index.able | 147 |
| abstract_inverted_index.bias | 95 |
| abstract_inverted_index.both | 27 |
| abstract_inverted_index.case | 114 |
| abstract_inverted_index.data | 46 |
| abstract_inverted_index.form | 50 |
| abstract_inverted_index.from | 59, 171 |
| abstract_inverted_index.i.e. | 201 |
| abstract_inverted_index.into | 11 |
| abstract_inverted_index.plus | 207 |
| abstract_inverted_index.show | 19 |
| abstract_inverted_index.test | 65 |
| abstract_inverted_index.that | 20, 119, 138, 160 |
| abstract_inverted_index.they | 81 |
| abstract_inverted_index.this | 71 |
| abstract_inverted_index.were | 139, 175 |
| abstract_inverted_index.with | 47, 131 |
| abstract_inverted_index.about | 23 |
| abstract_inverted_index.could | 184 |
| abstract_inverted_index.cues. | 98 |
| abstract_inverted_index.model | 101, 145 |
| abstract_inverted_index.novel | 72 |
| abstract_inverted_index.their | 24, 37 |
| abstract_inverted_index.these | 154 |
| abstract_inverted_index.total | 190 |
| abstract_inverted_index.types | 157 |
| abstract_inverted_index.which | 111, 174 |
| abstract_inverted_index.across | 40, 177 |
| abstract_inverted_index.alone. | 63 |
| abstract_inverted_index.inputs | 194 |
| abstract_inverted_index.judged | 82 |
| abstract_inverted_index.model, | 73 |
| abstract_inverted_index.nearly | 121 |
| abstract_inverted_index.shaped | 164 |
| abstract_inverted_index.account | 150 |
| abstract_inverted_index.enabled | 102 |
| abstract_inverted_index.entropy | 29, 35, 100, 144, 169, 191, 203, 209 |
| abstract_inverted_index.one’s | 5 |
| abstract_inverted_index.outputs | 196 |
| abstract_inverted_index.permits | 51 |
| abstract_inverted_index.provide | 9 |
| abstract_inverted_index.reports | 137 |
| abstract_inverted_index.several | 91 |
| abstract_inverted_index.stimuli | 32, 89, 206 |
| abstract_inverted_index.system, | 200 |
| abstract_inverted_index.utility | 69 |
| abstract_inverted_index.yielded | 135 |
| abstract_inverted_index.Studying | 0 |
| abstract_inverted_index.analysis | 107 |
| abstract_inverted_index.contrast | 85 |
| abstract_inverted_index.decision | 61 |
| abstract_inverted_index.equality | 129 |
| abstract_inverted_index.explicit | 94 |
| abstract_inverted_index.insights | 10 |
| abstract_inverted_index.internal | 55 |
| abstract_inverted_index.measured | 75, 187 |
| abstract_inverted_index.produced | 120 |
| abstract_inverted_index.relative | 84 |
| abstract_inverted_index.reports, | 134 |
| abstract_inverted_index.response | 38 |
| abstract_inverted_index.resulted | 161 |
| abstract_inverted_index.stimuli, | 173 |
| abstract_inverted_index.contrast, | 126 |
| abstract_inverted_index.decisions | 25, 159 |
| abstract_inverted_index.different | 132, 156 |
| abstract_inverted_index.employing | 93 |
| abstract_inverted_index.function. | 43 |
| abstract_inverted_index.identical | 122, 176 |
| abstract_inverted_index.judgments | 118, 130 |
| abstract_inverted_index.otherwise | 104 |
| abstract_inverted_index.responses | 62 |
| abstract_inverted_index.therefore | 185 |
| abstract_inverted_index.Describing | 44 |
| abstract_inverted_index.appearance | 86 |
| abstract_inverted_index.behavioral | 133 |
| abstract_inverted_index.decisions, | 7 |
| abstract_inverted_index.decisions. | 16 |
| abstract_inverted_index.different. | 142 |
| abstract_inverted_index.functional | 49 |
| abstract_inverted_index.functions, | 166 |
| abstract_inverted_index.functions. | 124 |
| abstract_inverted_index.measurable | 58 |
| abstract_inverted_index.mechanisms | 13 |
| abstract_inverted_index.parameters | 56 |
| abstract_inverted_index.responses. | 213 |
| abstract_inverted_index.underlying | 14 |
| abstract_inverted_index.attentional | 97 |
| abstract_inverted_index.comparative | 117, 127 |
| abstract_inverted_index.consistent. | 180 |
| abstract_inverted_index.demonstrate | 67 |
| abstract_inverted_index.differently | 163 |
| abstract_inverted_index.experiments | 92 |
| abstract_inverted_index.intractable | 105 |
| abstract_inverted_index.measurement | 53 |
| abstract_inverted_index.uncertainty | 22, 45, 76, 136, 152, 183 |
| abstract_inverted_index.contribution | 170 |
| abstract_inverted_index.experiments, | 178 |
| abstract_inverted_index.incorporates | 26 |
| abstract_inverted_index.observers’ | 21 |
| abstract_inverted_index.observer’s | 182, 212 |
| abstract_inverted_index.participants | 79 |
| abstract_inverted_index.psychometric | 42, 123, 165 |
| abstract_inverted_index.quantitative | 106 |
| abstract_inverted_index.successfully | 149 |
| abstract_inverted_index.uncertainty, | 110 |
| abstract_inverted_index.distinguished | 115 |
| abstract_inverted_index.introspection | 3 |
| abstract_inverted_index.probabilities | 39 |
| abstract_inverted_index.significantly | 141 |
| abstract_inverted_index.metacognition, | 1 |
| abstract_inverted_index.participants’ | 109 |
| abstract_inverted_index.stimulus-response | 199 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5071929477 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| citation_normalized_percentile.value | 0.35010678 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |