MétaCan
Menu
Back to cohort
Record W2000203665 · doi:10.1126/science.1233246

Comment on “Bateman in Nature: Predation on Offspring Reduces the Potential for Sexual Selection”

2013· letter· en· W2000203665 on OpenAlexaff
Patrick Bergeron, Alexandre M. Martin, Dany Garant, Fanie Pelletier

Bibliographic record

VenueScience · 2013
Typeletter
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsOffspringSelection (genetic algorithm)PredationSexual selectionBiologyReproductive successMetric (unit)ZoologyEcologyDemographyComputer sciencePopulationMachine learningEngineeringPregnancyGenetics

Abstract

fetched live from OpenAlex

Byers and Dunn (Reports, 9 November 2012, p. 802) claimed that predation on offspring reduced the potential for sexual selection in pronghorn. We argue that the potential for sexual selection is not affected by random offspring mortality when relative reproductive success is considered and increases when measured with the opportunity for selection, a metric that describes the potential for selection.

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)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.065
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0650.055
Insufficient payload (model declined to judge)0.0070.010

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 head0.015
GPT teacher head0.273
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations6
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueScienceSame topicAnimal Ecology and Behavior StudiesFrench-language works237,207