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Record W4298960048 · doi:10.47886/9781934874271.ch10

Advances in Fish Tagging and Marking Technology

2012· book-chapter· en· W4298960048 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2012
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGadusStock (firearms)FisheryAtlantic codStock assessmentFish stockGeographyRecreationEnvironmental resource managementOceanographyEnvironmental scienceFishingEcologyFish <Actinopterygii>Biology

Abstract

fetched live from OpenAlex

&lt;i&gt;Abstract&lt;/i&gt;.—In the Gulf of Maine region, Atlantic cod &lt;i&gt;Gadus morhua&lt;/i&gt;, are managed as three separate stocks: in U.S. waters, the Gulf of Maine (5Y) and Georges Bank (5Z) stocks and in Canadian waters, the Bay of Fundy stock (4X). The Northeast Regional Cod Tagging Program (NRCTP), a large-scale, international collaborative tagging program, was initiated in 2003 and provides the first region-wide, international snapshot of cod movements, mixing, and growth across all three management areas. As the 2008 stock assessment of Atlantic cod was approaching, these mark–recapture data (114,473 tag releases and &gt;6,500 recaptures) were being analyzed for stock identification purposes. Analysis of raw and weighted data indicate exchanges between different areas which are likely related to spawning behavior, maturation, and environmental conditions. Two core assumptions when defining a stock are that (1) the stock is self-sustaining and that (2) neighboring stocks exist in isolation; the migration patterns observed in the current study may substantially violate both assumptions. With additional ongoing assessments into spatial variation in key life history characteristics of growth and natural mortality, the NRCTP exemplifies the role of conventional mark–recapture data in the complex process of stock identification. The geographic scale and quality of data collected during the NRCTP also confirm the value of international, industry-science collaborative research initiatives; involving this data in both stock assessments and future management initiatives is rewarding to the ~250 commercial and recreational fishermen who tagged cod for this program.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2012
Admission routes1
Has abstractyes

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