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Record W4251782270 · doi:10.1139/z00-019

Food-anticipatory activity of groups of golden shiners during both day and night

2000· article· en· W4251782270 on OpenAlexfundvenueno aff
Martin Lägue, Stéphan G. Reebs

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyAnticipation (artificial intelligence)MidnightAnimal scienceZoology

Abstract

fetched live from OpenAlex

For 12 days, captive groups each containing four golden shiners (Notemigonus crysoleucas) were fed by automatic feeders at two diametrically opposed daily times. These two times could be midday and midnight, late day and late night, or early day and early night. As measured by interruptions of an infrared beam underneath the feeder, golden shiners almost always expressed food-anticipatory activity. Beam interruptions started to increase a few hours before mealtime, reaching a peak within 1.5 h of food delivery. In at least half of the groups tested, food-anticipatory activity developed for both daily times simultaneously. This double anticipation was maintained for at least 5 days after food was withheld. These results show that golden shiner groups (though not necessarily individuals) can express two peaks of food anticipation at widely separated daily times, even if one occurs during the day and the other at night, providing further evidence for the great variability that fishes can display in their activity patterns.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.212
Teacher spread0.191 · 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

Citations11
Published2000
Admission routes2
Has abstractyes

Explore more

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