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Record W7072226772

Visserijdata en de toestand van onze visbestanden

2023· article· nl· W7072226772 on OpenAlexaboutno aff

Bibliographic record

VenueFlanders Marine Institute (Flanders Marine Institute) · 2023
Typearticle
Languagenl
FieldSocial Sciences
TopicHistorical Influence and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative analysisQuarter (Canadian coin)Bridge (graph theory)
DOInot available

Abstract

fetched live from OpenAlex

Vis is gezond, dat weten we.Maar hoe is het gesteld met de gezondheid van onze visbestanden?Decennialang hebben visserijwetenschappers gewaarschuwd dat veel visbestanden te hard worden bevist.Soms is het advies opgevolgd, andere keren niet.Hele visserijen zijn ingestort -zoals gebeurde met de haringvisserij in de Noordzee eind jaren zeventig en aan de andere kant van de Atlantische Oceaan met de kabeljauwvisserij op de Grote Banken aan het begin van de jaren 1990.Gelukkig hebben een aantal visbestanden zich kunnen herstellen door de verminderde visserij in de afgelopen jaren.Dat zeggen wetenschappers op basis van duizenden data die ze verzamelen en analyseren.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0030.002
Scholarly communication0.0010.004
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.009

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 head0.031
GPT teacher head0.323
Teacher spread0.292 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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