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SPERM WHALES IN THE GULF OF CALIFORNIA: RESIDENCY, MOVEMENTS, BEHAVIOR, AND THE POSSIBLE INFLUENCE OF VARIATION IN FOOD SUPPLY

2003· article· en· W1972401204 on OpenAlexaff
Nathalie Jaquet, Diane Gendron, Amanda Coakes

Bibliographic record

VenueMarine Mammal Science · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCephalopods and Marine Biology
Canadian institutionsDalhousie University
FundersWildlife Conservation Society
KeywordsSperm whaleForagingAbundance (ecology)PredationFisherySpermPopulationWhaleBiologyCetaceaSquidEcologyGeographyOceanographyDemographyGeology

Abstract

fetched live from OpenAlex

A bstract Sperm whale movements, residency, population structure, and behavior were investigated in the Gulf of California in 1998 and 1999. Variations in sperm whale movement patterns and behavior were related to changes in prey abundance (jumbo squid, Dosidicus gigas ) determined by fishery statistics. Photo‐identification data revealed that seven female sperm whales moved into the Gulf of California from the Galapagos Islands, traveling up to 3,803 km. These are among the longest documented movements for female sperm whales. There were significant differences in speed and distance traveled during a dive cycle between 1998 and 1999 (low and high squid abundance). In 1999 there were also significant differences in small‐scale movements and behavior between the northern and the southern part of the study area (high and low prey abundance). These results suggest that when food resources are low, sperm whales travel in straighter lines, dive for longer periods, travel larger distances during dive cycles, and at higher speed. In 1999 there were significant differences in time spent socializing in areas of high prey abundance versus areas of low abundance. All of these changes in behavior were consistent with increased foraging effort when squid abundance was low. A high proportion of mature males and first‐year calves were observed in the Gulf of California, suggesting that it is an important sperm whale breeding ground.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.217
Teacher spread0.207 · 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.

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

Citations55
Published2003
Admission routes1
Has abstractyes

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