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Record W3045013281 · doi:10.1111/tops.12517

Editor's Introduction: Best of Papers From the 17th International Conference on Cognitive Modeling

2020· editorial· en· W3045013281 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTopics in Cognitive Science · 2020
Typeeditorial
Languageen
FieldComputer Science
TopicCognitive Science and Mapping
Canadian institutionsNational Research Council CanadaUniversity of Waterloo
Fundersnot available
KeywordsCognitionSimilarity (geometry)Set (abstract data type)Computer scienceDiversity (politics)Cognitive scienceCognitive modelArtificial intelligenceData sciencePsychologyManagement scienceCognitive psychologyPolitical scienceEngineeringLawProgramming languageNeuroscience

Abstract

fetched live from OpenAlex

Cognitive modeling involves the creation of computer simulations that emulate the internal processes of the mind. This set of papers are the five best representatives of the papers presented at the 17th International Conference on Cognitive Modeling, ICCM 2019. While they represent a diversity of techniques and tasks, they all also share a striking similarity: They make strong statements about the importance of accounting for individual differences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.303
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.325
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it