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Record W2910454983 · doi:10.1111/jav.02003

Some important overlooked aspects of odors in avian nesting ecology

2019· article· en· W2910454983 on OpenAlexaff
Dave Shutler

Bibliographic record

VenueJournal of Avian Biology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsAcadia University
Fundersnot available
KeywordsCrypsisBiologyNest (protein structural motif)EcologyCamouflagePredationOlfactionMimicryAttractivenessNesting (process)BitingZoologyPsychology

Abstract

fetched live from OpenAlex

Although outdated opinions about poor avian olfaction have largely disappeared in recent decades, there has been inadequate attention paid to olfaction of other organisms that interact with birds and their nests. In particular, olfaction is likely more important than vision for many biting arthropods and for many reptilian, mammalian, and likely even some bird predators of nests (e.g. some procellariiforms, piciforms, and corvids), but crypsis (or attractiveness) of nest odors has largely been ignored in the literature. Given the pivotal importance of nest success to a bird's fitness, there has likely been strong selection to conceal inadvertent cues to nest locations, including odors. Here, I summarize what is known about this, and discuss a few important topics I deem worthy of deeper investigation.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.005
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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