MétaCan
Menu
Back to cohort
Record W2945297055 · doi:10.2960/j.v50.m719

Diverse migratory behaviors of Atlantic halibut (<i>Hippoglossus hippoglossus</i>, L.) based on the 2000–2017 Maine halibut tagging program

2019· article· en· W2945297055 on OpenAlexaboutno aff
Michael Kersula, Andrew C. Seitz

Bibliographic record

VenueJournal of Northwest Atlantic Fishery Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceState of Maine Department of Marine Resources
KeywordsHalibutHippoglossus hippoglossusFisheryBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Accurately delineating the spatial extent of fish stocks and the degree to which stocks mix is important for understanding the effects of fisheries management and environmental change. This paper describes migratory behaviors of Atlantic halibut (Hippoglossus hippoglossus L.) tagged with conventional wire tags in the U.S. portion of the Gulf of Maine between 2000 and 2017. There were 412 recaptures reported out of 2 573 releases, a return rate of 16.0%. These returns illustrate that although most fish are recaptured close to the release point with a median distance at recapture of 38 km, Gulf of Maine Atlantic halibut also engage in dispersive behavior with some fish travelling at least 1 564 km. Returns from Canadian waters accounted for 43.2% of total recaptures. A generalized linear model found greater distances at recapture related to greater days at liberty and during winter. Fish size explained a negligible proportion (<1%) of the variability in recapture distance. Most (76%) recaptures were from waters of the Gulf of Maine and the Western Scotian Shelf off Canada, suggesting a higher level of mixing within this transnational boundary area than to elsewhere. This contrasts common assumptions about stock structure made for assessment and management purposes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

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 studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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.

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

Citations9
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Northwest Atlantic Fishery ScienceSame topicFish Ecology and Management StudiesFrench-language works237,207