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Record W2065723728 · doi:10.1037/0735-7036.114.3.232

Flexible search behavior in domestic cats (Felis catus): A case study of predator–prey interaction.

2000· article· en· W2065723728 on OpenAlexaff
Claude Dumas

Bibliographic record

VenueJournal of comparative psychology · 2000
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsFelis catusCATSFlexibility (engineering)FelisPredationObject (grammar)PsychologyPredatorTask (project management)Artificial intelligenceCognitive psychologyComputer scienceStatisticsMathematicsBiologyEcology

Abstract

fetched live from OpenAlex

Domestic cats (Felis catus) were administered an object permanence task in a novel and a familiar situation to investigate flexibility (i.e., pause behavior and searching by following a path opposite of that taken by the object when it disappeared) in search behavior. Pause and opposite search were assumed to be independent, equiprobable, and randomly exhibited (i.e., random model). The random model predicted that cats would exhibit flexible behavior on 75% of the trials. The results revealed that flexible behavior occurred on 69% of the trials in the novel situation, but only on 52% of the trials in the familiar setting in which pauses were less frequent and shorter than in the novel situation. Thus, the random model provided a good fit of the data in the novel but not in the familiar situation. It is argued that pause and opposite search reflect decision processes when cats are dealing with the behavior of prey that has disappeared while being pursued.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.156
GPT teacher head0.511
Teacher spread0.355 · 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 designObservational
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

Citations9
Published2000
Admission routes1
Has abstractyes

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