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THE DIET OF GALÁPAGOS SPERM WHALES <i>PHYSETER MACROCEPHALUS</i> AS INDICATED BY FECAL SAMPLE ANALYSIS

2000· article· en· W2139275369 on OpenAlexaff
Sean Smith, Hal Whitehead

Bibliographic record

VenueMarine Mammal Science · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSperm whaleBiologyBeakSpermCetaceaWhaleFecesFisheryZoologyEcologyBotany

Abstract

fetched live from OpenAlex

A bstract Fecal samples were collected while following sperm whales ( Physeter macrocephalus ) off the Galápagos Islands, Ecuador. They contained 133 upper beaks and 164 lower beaks of cephalopods. Analysis of the lower beaks suggests that the sperm whales fed primarily on three genera of cephalopods; Histioteutbis (62%), Ancistrocbeirus (16%), and Octopoteutbis (7%). The beak dimensions indicate that the cephalopods ranged in mantle length from 5 to 54 cm and in mass from 12 to 650 g. Fecal samples varied significantly between five study years and over different parts of the study area, but the number of beaks collected per sample did not correlate significantly with defecation rate (a measure of feeding success). Using beak material from fecal samples gives a biased estimate of sperm whale diet, reducing the frequencies of very small and very large cephalopods. However, all other available methods of assessing sperm whale diet also possess biases.

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 score0.009
Threshold uncertainty score0.017

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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

Citations70
Published2000
Admission routes1
Has abstractyes

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