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Diving and ranging behaviour of odontocetes: a methodological review and critique

2001· review· en· W2127016162 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMammal Review · 2001
Typereview
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRangingSampling (signal processing)Computer scienceRemote sensingEnvironmental scienceGeologyTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT Movements can be analysed in terms of horizontal or vertical dimensions, but cetacean movement is ultimately three‐dimensional, and it is the integration of analyses of both horizontal and vertical movements that will provide the most insight about an animal's behaviour. Current field techniques can provide simultaneous information on both diving (vertical movements) and ranging (horizontal movements). We discuss the considerations, techniques and analyses for diving and ranging studies, together with the advantages and disadvantages of each technique. Ranging studies using VHF or satellite‐linked radio‐transmitters have evolved alongside studies of diving behaviour using time–depth recorders, and problems associated with deployment and attachment techniques apply to both. The diving (and concurrent ranging behaviour) of 13 species of odontocetes has been studied using time–depth recorders or acoustic transponders with VHF‐or satellite‐transmitters. However, differences in sampling techniques used, and summary statistics presented, have made comparisons difficult. We review these issues and suggest parameters that should be presented in future studies of diving and ranging. In general, studies should be consistent in their presentation of the basic parameters and statistics, and provide enough information for the reader to assess the limitations of the data.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.147
GPT teacher head0.402
Teacher spread0.254 · 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