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Record W4244980136 · doi:10.1002/naaq.10100

Issue Information

2020· paratext· en· W4244980136 on OpenAlexfundno aff
Scott A. Bonar, Brian R. Murphy, April Croxton, Leanne Roulson, Jesse Trushenski, Douglas Austen, Michelle Mick, ⁄ Walsh

Bibliographic record

VenueNorth American Journal of Aquaculture · 2020
Typeparatext
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
FundersCalifornia Department of Fish and WildlifeDalhousie UniversityPukyong National UniversityWashington Department of Fish and WildlifeUniversidad del AtlánticoFlorida Atlantic UniversityMississippi State UniversityU.S. Department of Agriculture
KeywordsCitationLibrary scienceWorld Wide WebInformation retrievalComputer scienceBiology

Abstract

fetched live from OpenAlex

The American Fisheries Society, organized in 1870, is the world's oldest and largest professional fisheries society.Its objectives are conservation, development, and wise use of recreational and commercial fisheries; promotion of all branches of fisheries science and practice; and exchange and dissemination of knowledge about fish, fisheries, and related subjects.Persons interested in the Society and its objectives are eligible for membership. Editorial policyThe North American Journal of Aquaculture (published as The Progressive Fish-Culturist from 1934 to 1998; ISSN 0033-0779) publishes papers on all aspects of aquaculture, including broodstock selection and spawning, nutrition and feeding, health and water quality, facilities and production technology, and management of ponds, pens, and raceways.Papers dealing with ways to improve the husbandry of any aquatic species-marine or freshwater, vertebrate or invertebrate-raised for commercial, scientific, recreational, enhancement, or restoration purposes that may be of importance to North Americans will be considered.

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)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.142
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.8580.813

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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