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Record W4321444039 · doi:10.22621/cfn.v136i3.2949

Salmon Shark (<i>Lamna ditropis</i>) scratching behaviour using floating anthropogenic debris

2023· article· en· W4321444039 on OpenAlexafffundvenue
Cherisse Du Preez, Heidi Gartner, Joshua Watts, Lindsay Clark, Shelton Du Preez, Tammy Norgard

Bibliographic record

VenueThe Canadian Field-Naturalist · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of VictoriaNuu Chah Nulth Tribal CouncilFisheries and Oceans Canada
FundersFisheries and Oceans Canada
KeywordsDebrisScratchingScratchFisheryEnvironmental scienceUnderwaterOceanographyBiologyGeologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

Observations of animal behaviour in the open ocean are relatively rare. However, while conducting surveys in the Northeast Pacific in the summers of 2019 and 2021, we encountered two Salmon Shark (Lamna ditropis) using floating anthropogenic debris to scratch their bodies. We captured the activity with aerial (drone) and underwater cameras. We document and describe this novel behaviour as high energy, high impact, repetitive, fast, and long lasting (e.g., every ~15 s for >20 minutes). We explore these observations in light of traditional ecological knowledge and scientific literature.

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 score0.061
Threshold uncertainty score0.121

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.242
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

Citations0
Published2023
Admission routes3
Has abstractyes

Explore more

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