MétaCan
Menu
Back to cohort
Record W7026773647

Assessing the status of the cod (Gadus morhua) stock in NAFO Subdivision 3Ps in 2015

2016· article· en· W7026773647 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Archive of Ifremer (French Research Institute for Exploitation of the Sea) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsStock (firearms)Research vesselStock assessmentScophthalmusFishingSubdivisionSpawn (biology)
DOInot available

Abstract

fetched live from OpenAlex

The status of the cod stock in the Northwest Atlantic Fisheries Organization (NAFO) Subdivision 3Ps was assessed during a Fisheries and Oceans Canada (DFO) Regional Peer Review Process meeting held October 20-22, 2015. Stock status was updated based upon information collected up to spring 2015. Principal sources of information available for the assessment were: a time series of abundance and biomass indices from Canadian winter/spring research vessel (RV) bottom trawl surveys, inshore sentinel surveys, science logbooks from vessels < 35 ft., logbooks from vessels > 35 ft., reported landings from commercial fisheries, oceanographic data, and tagging studies.\nDespite short-term projections for stock growth, there is reason for concern for 3Ps cod going forward. Although recruitment has recently been good, mortality is very high and hence the long-term contribution of these year classes to the fishery and spawning biomass is still uncertain. The spawning biomass is composed almost entirely of young fish, with the current age at maturity being the lowest recorded in the time series. Recent biological data suggest fish growth rates are low and that fish condition is poor. In recent years, cod in 3Ps have been feeding heavily on lipid-poor prey such as snow crab and other invertebrates. The combination of these biological data with the recent rise of warm-water species such as white hake is suggestive of broad changes in the 3Ps ecosystem and perhaps reduced cod productivity.\n

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.097
GPT teacher head0.379
Teacher spread0.282 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInstitutional Archive of Ifremer (French Research Institute for Exploitation of the Sea)Same topicMarine and fisheries researchFrench-language works237,207