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Record W3106619594 · doi:10.3354/meps13603

Preliminary estimate of post-release survival of immature porbeagles caught with rod-and-reel in the Northwest Atlantic Ocean

2020· article· en· W3106619594 on OpenAlexaff
BN Anderson, HD Bowlby, LJ Natanson, Rui Coelho, Enric Cortés, Andrés Domingo, JA Sulikowski

Bibliographic record

VenueMarine Ecology Progress Series · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsFisheryPopulationReelPacific oceanOceanographyEnvironmental scienceBiologyGeographyZoologyDemographyGeologyArt

Abstract

fetched live from OpenAlex

The Northwest Atlantic (NWA) population of porbeagles Lamna nasus is susceptible to capture in rod-and-reel fisheries and most individuals are discarded alive due to catch and size limits. To estimate post-release survival, pop-off satellite archival tags were attached to porbeagles captured with rod-and-reel. Fourteen tags were deployed, of which 13 transmitted. All sharks for which we had data survived, giving a post-release survival rate of 100%. Following release, 6 individuals remained in surface waters for several hours to days, while 2 individuals immediately resumed normal diving behaviors. For the remaining sharks (n = 5), low tag transmission resolution precluded the detection of fine scale post-release behavior. The duration of initial depth-holding behavior was characterized using a break-point analysis of dive track variance, which suggests porbeagles exhibited a median post-release recovery period of 116 h (10th and 90th percentiles = 68.8 and 280.1 h) following capture and handling. Our preliminary study suggests immature porbeagles are resilient to capture and handling, although more data would provide stronger support for management recommendations.

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)0.001
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.005
GPT teacher head0.206
Teacher spread0.201 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueMarine Ecology Progress SeriesSame topicIchthyology and Marine BiologyFrench-language works237,207