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10.1016/s0967-0653(98)80697-2

2000· article· en· W153387503 on OpenAlexvenueno aff
V D Deshmukh, Mohammad Zafar Khan

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFisheryMaximum sustainable yieldShrimpYield (engineering)PrawnBiologyResource (disambiguation)Sustainable yieldGeographyFisheries managementFishingEcology

Abstract

fetched live from OpenAlex

The growth, mortality, recruitment pattern and MSY of important fishery resources of Maharashtra \nwere estimated. The investigation revealed that out of 18 fish resources 11 are optimally exploited. The \npenaeid prawn resources which are the target species of shrimp trawlers are underexploited. \nCephalopods appear to be optimally exploited. The present yield of fishes, prawns and cephalopods are \n65083, 38404 and 11373 tons while the estimated MSY are 83025, 72460 and 10475 tons. The study \nindicates that additional yield of 62,926 ton can be obtained by increasing the efforts to the extent of \n25% without any adverse effects on the total resource

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0040.007
Open science0.0040.004
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.9920.994

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 head0.009
GPT teacher head0.161
Teacher spread0.152 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations31
Published2000
Admission routes1
Has abstractyes

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