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Record W2113833417 · doi:10.1017/s003060530400081x

Biology, fishery and trade of sea moths (Pisces: Pegasidae) in the central Philippines

2004· article· en· W2113833417 on OpenAlexaff
Marivic Pajaro, Jessica J. Meeuwig, Brian G. Giles, Amanda C. J. Vincent

Bibliographic record

VenueOryx · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsFisheryGeographyFishingPopulationAbundance (ecology)BiologyDemography

Abstract

fetched live from OpenAlex

Sea moths (family Pegasidae) are little-studied benthic fish, found throughout the Indo-Pacific. Two species of sea moths, Pegasus volitans and Eurypegasus draconis, are caught incidentally in illegal trawl gear in the Philippines and sold into the dried fish trade. Approximately 130,000–620,000 P. volitans and 130,000 E. draconis were landed off north-western Bohol alone in 1996. An additional 43,000–62,000 sea moths (predominantly P. volitans) were caught live for the aquarium trade. Catch per unit effort for P. volitans was double that of E. draconis, probably because of its occurrence in shallower waters where fishing effort was concentrated. Sea moths may be unsuited for heavy exploitation as they occur at low densities. Moreover, a female-biased catch could lower the effective population size, given the reported monogamy amongst sea moths. No population data were available for a complete conservation assessment, although divers surveyed did report declines in their abundance.

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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.204
Teacher spread0.188 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

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