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Record W2105676013 · doi:10.1139/z02-050

Male mate choice and male-male competition coexist in the humpback whale (<i>Megaptera novaeangliae</i>)

2002· article· en· W2105676013 on OpenAlexvenueno aff
Alison S. Craig, Louis M. Herman, Adam A. Pack

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyHumpback whaleSeasonal breederIce calvingMatingReproductionCompetition (biology)ZoologyFisheryPregnancyEcologyWhale

Abstract

fetched live from OpenAlex

Male humpback whales (Megaptera novaeangliae) outnumber females on the winter grounds and compete physically for proximity to females. Analyses of identification photographs collected in Hawai'i from 1976 through 1995 and scan samples collected in 1998 showed that (i) reproductive potential (calving rate) for the following winter was greater for females without a calf than females with a calf, (ii) females without a calf were less likely to be found alone and more likely to be found in large pods than females with a calf, (iii) individual females were found in larger pods when without a calf than when with a calf, (iv) the probability of females with a calf being escorted by one or more males increased as the reproductive season progressed, and (v) head lunges occurred more commonly in all-adult pods than in pods containing a calf. We concluded that male humpback whales associate preferentially with females with high reproductive potential, that the attractiveness of individual females varies with their status (with a calf versus without a calf), that males become progressively less choosy over the course of the reproductive season as females without a calf become increasingly rare on the winter grounds, and that males expend more energy in competition over females without a calf than females with a calf.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.023
GPT teacher head0.217
Teacher spread0.194 · 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

Citations77
Published2002
Admission routes1
Has abstractyes

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