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Record W4313453623 · doi:10.3758/s13428-022-02050-9

The timing database: An open-access, live repository for interval timing studies

2023· article· en· W4313453623 on OpenAlexafffund
Turaç Aydoğan, Hakan Karşılar, Yalçın Akın Duyan, Başak Akdoğan, Alessia Baccarani, Renaud Brochard, Benjamin J. De Corte, Jonathon D. Crystal, Bilgehan Çavdaroğlu, C. R. Gallistel, Simon Grondin, Ezgi Gür, Quentin Hallez, Joost de Jong, Leendert van Maanen, Matthew S. Matell, Nandakumar S. Narayanan, Ezgi Özoğlu, Tutku Öztel, Argiro Vatakis, David Freestone, Fuat Balcı

Bibliographic record

VenueBehavior Research Methods · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité LavalThe Scarborough HospitalUniversity of TorontoUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceDatabaseTask (project management)Interval (graph theory)Range (aeronautics)Data mining

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.010
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0050.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2290.128

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 head0.873
GPT teacher head0.720
Teacher spread0.153 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreSoftware

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2023
Admission routes2
Has abstractno

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