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Record W4312846811 · doi:10.46867/c49k52

Simultaneous Pattern Discriminations by Pigeons Reveal Absence of Mirror-Image and Left-Right Confusions

2002· article· en· W4312846811 on OpenAlexafffund
France Landry, Catherine Plowright

Bibliographic record

VenueInternational Journal of Comparative Psychology · 2002
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTask (project management)PsychologyImage (mathematics)Position (finance)CommunicationArtificial intelligencePattern recognition (psychology)Cognitive psychologyComputer science

Abstract

fetched live from OpenAlex

In a simultaneous discrimination task, pigeons were first trained with two patterns: one rewarding (A+) and the other unrewarding (B-) that contained the same components (the symbols: c, d, ■ and <) but displayed in a different spatial layout. They were then tested for their choices of patterns: (1) A+ vs. its mirror image (MI); (2) A+ vs. its left-right reversal (LR); (3) MI vs. other layouts (OL) of the symbols; (4) LR vs. OL. In the first two conditions, A+ was chosen over its MI and LR reversal (i.e., no MI or LR confusions were found). In the last two conditions, MI and LR were not chosen over the OL, that is, they were not treated as substitutes for the A+. On the contrary, the OL stimuli were chosen over the transformations of A+. In all cases, the discriminations revealed a failure to confuse the A+ with its transformations, as predicted from work showing that the position of pattern components is important in pattern recognition.

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.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.094
GPT teacher head0.414
Teacher spread0.320 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2002
Admission routes2
Has abstractyes

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