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Marginal Marine Crustacean Fisheries

2020· book-chapter· en· W3157576277 on OpenAlexaboutno aff
Boris A. López

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsOverexploitationFisheryFishingFisheries managementGeographyCrustaceanBiologyEcology

Abstract

fetched live from OpenAlex

A review of small-scale fisheries of marine crustacean is here presented, indicating the main biological traits of the target species, levels and methods of capture, prices and markets, as well as fishing regulations. Edible barnacles are exploited in Spain, Japan, and Chile with low levels of capture (<500 t per year) and can be sold at high prices in the Iberian market. Stomatopods (mantis shrimps) are captured in the vicinity of the river mouths through trawl fisheries in Mediterranean Sea and in the western Indo-Pacific. Their landings fluctuate between 4,000 and 7,000 t per year, with levels of overexploitation reported for some Asian fisheries. A recent harvesting of sandhoppers (amphipods) has been reported from sandy beaches of Chile for aquarium food, with annual yields of 10–15 t dry mass. Other amphipod species (lysianassoids) are exploited in Canada mainly for fish food. These fisheries are characterized by a lack of biological and fishing parameters, management measurements, and regulations of the exploitation of their natural populations. However, in the cases of the European fisheries (stalked barnacles and stomatopods), some regulations have been implemented, such as closing periods, extraction quotas, and minimum legal sizes. Ecological studies are necessary to evaluate the possible impacts on biological interactions and food webs on the populations of the commercial extraction in these fisheries.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.018
GPT teacher head0.176
Teacher spread0.158 · 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
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

Citations6
Published2020
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicCrustacean biology and ecologyFrench-language works237,207