MétaCan
Menu
Back to cohort
Record W6981745471

Exploring the economic viability of Dol net Fishery off the coast of Gujarat

2024· article· en· W6981745471 on OpenAlexaboutno aff

Bibliographic record

VenueEprints@CMFRI Open Access Institutional Repository (Central Marine Fisheries Research Institute) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFisheries and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFishingProductivityCraftOrder (exchange)Value (mathematics)Fisheries managementProduction (economics)Quarter (Canadian coin)Prime (order theory)
DOInot available

Abstract

fetched live from OpenAlex

Dol-net fishing is a very popular traditional fishing method carried out along the Gujarat coast. Dol nets have evolved over time with innovations in craft and gear, in order to enhance the efficiency of operation as well facilitate the ease of catch of the targeted species. Economics of operation of Dol-netters is a prime factor governing its deployment by fishers, provision of credit assistance by financial institutions and decision making on sustainable fisheries management by the Government. The following study, framed with the above said objectives, revealed that, during 2023, mechanised multi-day doll netters from Jaffarabad, a major Dol-net operating centre, operated with a capital productivity of 0.69, labour productivity of 1631 Kg/crew/trip, Input-Output ratio of 0.28 and Gross Value added to the tune of 187338.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.123
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.215
GPT teacher head0.366
Teacher spread0.151 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueEprints@CMFRI Open Access Institutional Repository (Central Marine Fisheries Research Institute)Same topicFisheries and Aquaculture StudiesFrench-language works237,207