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Record W2117202811 · doi:10.15406/jamb.2015.02.00034

Distribution and Overlap of Five Coastal Indo-Pacific Cetacean Species

2015· article· en· W2117202811 on OpenAlexaff
Jennifer Alexa Cheznowski

Bibliographic record

VenueJournal of Aquaculture & Marine Biology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsResearch Canada
Fundersnot available
KeywordsIndo-PacificFisheryOceanographyGeographyDistribution (mathematics)Fisheries scienceEcologyBiologyGeologyFisheries managementFishing

Abstract

fetched live from OpenAlex

There are many cetaceans that exist in the Indo-Pacific region, however precise distributional locations are difficult to come across.The purpose of this study was to examine reliable literature in order to generate the distributional properties of five cetaceans.Individual spatial locations were combined to reveal where the five species overlapped.The habitat preferences of each species were also gathered in attempt to suggest possible correlations between specific cetacean overlap.Geographical barriers were observed for their distributional effects on the five species.There was a correlation between cetaceans with similar habitats and overlapping distribution.Biogeographical barriers, the Wallace and Lydekker line seemed to play a significant role in isolating certain species.Some cetaceans were permanently separated from other populations due to barriers of the Wallace and Lydekker line.It is possible that new species have diverged as a result of population isolation.

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)0.001
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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