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Record W2982037991 · doi:10.12681/mms.20671

An approximate assessment of the production levels of the Italian fishing fleet in the Mediterranean Sea during selected years in comparison with the analogous previous estimates

2020· article· en· W2982037991 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMediterranean Marine Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsDiscardsFishingFisheryMediterranean seaTonneGeographyMediterranean climateMarine fisheriesCommercial fishingEnvironmental scienceOceanographyBiologyGeologyArchaeology

Abstract

fetched live from OpenAlex

During the past two decades, the organization Sea Around Us (based at the Fisheries Centre in British Columbia, Canada) has been carrying out the relevant task of reconstructing national statistics on marine fisheries for almost all countries and territories to fill information gaps and correct the general trend of severe underestimation of the “true” level of catches, discards and landings.A recent reconstruction of this kind showed that the annual catches by the Italian fleet fishing in the Mediterranean Sea had been presumably underestimated during most of the 1950-2010; in the 1970-1995 sub-period, they would have ranged from 0.7-1.1 million metric tons per year. However, comparisons with the landings for the few years for which there are “independent” estimates (i.e., not based on official statistics) show that many more bivalve molluscs and fewer “small pelagics” were caught and that the highest annual outputs reported by Sea Around Us should be presumably cut by 25%-35%.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.034
GPT teacher head0.291
Teacher spread0.257 · 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