MétaCan
Menu
Back to cohort
Record W4298849082 · doi:10.47886/9781934874110.ch45

Pacific Salmon: Ecology and Management of Western Alaska’s Populations

2009· book-chapter· en· W4298849082 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2009
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinook windOncorhynchusFisheryFishingStock (firearms)Fisheries managementGeographyStock assessmentBiologyFish <Actinopterygii>Archaeology

Abstract

fetched live from OpenAlex

&lt;em&gt;Abstract.&lt;/em&gt;—Fisheries and Oceans Canada has managed the northern British Columbia troll fishery since 1995 to reduce fishing mortality on Chinook salmon &lt;em&gt;Oncorhynchus tshawytscha &lt;/em&gt;stocks from the West Coast of Vancouver Island (WCVI). This paper describes the fishery and the use of genetic data in mixed-stock analyses for in-season management of Chinook salmon. Microsatellite DNA based stock identification was used in 2006 to regulate the mixed-stock fishery to address WCVI stock specific harvest. Chinook salmon stock compositions were estimated in-season for the 2006 troll fishery harvest and the fishery was managed based on this information to meet catch targets for WCVI Chinook salmon. The best opportunities for the troll fishery to avoid WCVI Chinook salmon stocks were defined spatially (in northern portions of the fishing area) and temporally (in late June and July). The application of stock-specific management allowed the internationally negotiated catch allocation between Canada and the U.S. (Pacific Salmon Treaty) to be reached while reducing the exploitation of WCVI Chinook salmon stocks.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.218
Teacher spread0.202 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Fisheries Society eBooksSame topicFish Ecology and Management StudiesFrench-language works237,207