MétaCan
Menu
Back to cohort
Record W4225743450 · doi:10.1093/icesjms/fsac089

Comment on “Five centuries of cod catches in eastern Canada,” by Schijns <i>et al</i>

2022· article· en· W4225743450 on OpenAlexaboutno aff
Poul Holm, Patrick Hayes, John Nicholls

Bibliographic record

VenueICES Journal of Marine Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsGadusFishingFisheryDocumentationStock (firearms)GeographyBiologyArchaeologyFish <Actinopterygii>Computer science

Abstract

fetched live from OpenAlex

Abstract Schijns et al. use a historical time series to inform a stock assessment model for the northern Atlantic cod (Gadus morhua) fishery from 1508 to 2019. They find that catches from the sixteenth century to the 1950s did not exceed 200000 t per annum and could have been sustained today “if fishing effort and mortality had been stabilized in the 1980s”. Had Schijns et al. used a more complete and representative time series (as identified below), they would have found that catches were substantially higher during much of the time period, possibly affecting their conclusions regarding the timing and onset of unsustainable exploitation. In an earlier paper, based on original archival documentation, we have argued that total landings in the Newfoundland fishery averaged 400000 t in the eighteenth century and peaked at 600000 t in 1788. We contend that pre-industrial technology was sufficient to have a significant impact on marine life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.649
Threshold uncertainty score0.699

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.005
Scholarly communication0.0040.003
Open science0.0050.002
Research integrity0.0270.025
Insufficient payload (model declined to judge)0.0060.005

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueICES Journal of Marine ScienceSame topicMarine and fisheries researchFrench-language works237,207