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Record W4301882073 · doi:10.47886/9781934874073.ch28

Biology and Management of Dogfish Sharks

2009· book-chapter· en· W4301882073 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2009
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsGroundfishBycatchFisherySqualus acanthiasFisheries managementFishingSpiny dogfishBusinessExclusive economic zoneGeographyBiology

Abstract

fetched live from OpenAlex

Abstract.—The fishery for spiny dogfish <em>Squalus acanthias </em>within British Columbia (B.C.) has fluctuated greatly over the past 150 years. During the 1930s and 1940s it was one of the most valuable fisheries on the West Coast. Active management of this fishery began in 1977 after Canada extended its exclusive economic zone to 200 mi. The management of Pacific groundfish fisheries, including dogfish, is complex, and is further complicated by serious conservation concerns. Bycatch issues and the lack of full catch monitoring have been of particular concern. As a result, Fisheries and Oceans Canada (DFO) approached groundfish industry representatives to develop a plan to address these key issues. A program to make individual fishers more accountable for their harvest, to improve compliance with the DFO’s selective fishing and fishery monitoring policies, and to be consistent with Pacific fisheries reform was developed. This integration program was implemented in 2006 for commercial groundfish fisheries within B.C. As a result, at-sea monitoring was maximized to 100% and individual transferable quotas within each fishery allow fishermen to account for their groundfish bycatch on an annual basis. This new management system could help pave the way for other fisheries around the world to learn, adjust accordingly, and implement similar regimes.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.957
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 studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.241
Teacher spread0.226 · 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

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