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Record W778692421 · doi:10.1163/1568539x-00003296

Time-sensitive neophobic responses to risk

2015· article· en· W778692421 on OpenAlexafffund
Maud C. O. Ferrari, G. E. Brown, Douglas P. Chivers

Bibliographic record

VenueBehaviour · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsConcordia UniversityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsPredatorPredationALARMEveningNeophobiaSensory cueStimulus (psychology)BiologyPsychologyEcologyCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Prey animals that experience a high background level of risk are known to exhibit considerable phenotypic plasticity in their responses to unknown predators. When background risk is high, prey exhibit neophobic responses to unknown odours, i.e. they show a fear response to any new stimulus. Here, we examine whether temporal variation in the pattern of risk to which prey are exposed influences neophobic responses. To establish prey groups with different temporal patterns of risk, embryonic woodfrogs (Lithobates sylvaticus) were exposed to conspecific alarm cues each morning and control cues in the evening, or conspecific alarm cues each evening and control cues in the morning, for their entire embryonic period. After the tadpoles hatched they were tested at both times of day for known risk cues (alarm cues), unknown predator odours or water control. Tadpoles responded to alarm cues at any time of day, but showed neophobic responses to predator odours only if their test time matched their embryonic risk exposure time. These results demonstrate a high level of sophistication of neophobic responses and points to temporal variation in risk as a key driver of antipredator decision making.

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 score0.001
Threshold uncertainty score0.005

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 head0.040
GPT teacher head0.258
Teacher spread0.218 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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