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Record W2943908141 · doi:10.1093/beheco/arz067

Innovative consumers: ecological, behavioral, and physiological predictors of responses to novel food

2019· article· en· W2943908141 on OpenAlexaff
Sanjay Prasher, M. J. Thompson, Julian Evans, Michael El-Nachef, Frances Bonier, Julie Morand‐Ferron

Bibliographic record

VenueBehavioral Ecology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsQueen's UniversityUniversity of Ottawa
Fundersnot available
KeywordsNeophobiaForagingBiologyUrbanizationEcologyDominance (genetics)Affect (linguistics)PersonalityBehavioral ecologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Consumer innovation, that is, the acquisition and consumption of novel food types, has received little attention, despite its predominance among animal innovations and its potential implications for the ecology and evolution of species in a changing world. Results of the few studies that have investigated individual responses to novel foods suggest that various ecological, behavioral, and physiological variables may affect individual propensity for consumer innovation, but further work is needed to clarify these relationships. We investigated whether urbanization, social rank, exploratory personality, and baseline levels of corticosterone predict food neophobia and consumer innovation responses of wild-caught black-capped chickadees (N = 170) from 14 sites along an urbanization gradient. Our analyses do not support a link between food neophobia or consumer innovation and urbanization, dominance, or exploratory personality. However, birds with higher levels of baseline corticosterone were quicker to contact novel food types, and more likely to consume novel foods than individuals with lower levels of the hormone. This finding suggests that physiological states that promote foraging behavior might drive individual responses to novel food. Additionally, we found that chickadees tested later in autumn were less neophobic than those tested earlier in the season, perhaps reflecting seasonal changes in food availability. Together, the ability of baseline corticosterone and date of capture to predict responses to novel food suggest that necessity may drive consumer innovation in chickadees.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.081
GPT teacher head0.305
Teacher spread0.224 · 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 teacher head, not a consensus.

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

Citations23
Published2019
Admission routes1
Has abstractyes

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