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Record W2167329009 · doi:10.5539/jas.v4n9p269

Rearing of Burbot, Lota lota (Pisces, Teleostei), Larvae with Zooplankton and Formulated Microdiets

2012· article· en· W2167329009 on OpenAlexvenueno aff
Franz Lahnsteiner, Manfred Kletzl, T. Weismann

Bibliographic record

VenueJournal of Agricultural Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsZooplanktonBiologyLive foodLarvaAnimal scienceFisheryTeleosteiIchthyoplanktonAquacultureEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Different feeding methods were tested for burbot, Lota lota, larvae. In small scale experiments with 300 larvae per treatment grinded artemia flakes, enriched artemia flakes, artemia flakes supplemented with dried algae (Chlorella sp., Spirulina sp.) and formulated microdiets consisting of different combinations of fishmeal, fish oil, soybean lecithin, casein, dextran, and artemia flakes were fed over a period of 30 days. These foods were compared to live zooplankton food collected from the nature. After 30 days, only feeding with live zooplankton resulted in high survival rates > 80%. No survival was observed with artificial microdiets. The 15 d survival of larvae was significantly lowest with agar agar bound microparticles and with formulated diets containing > 7% soya lecithin and > 3 % fish oil. The live zooplankton feeding method was also tested in a large scale experiment with 25,000 larvae per tank for a period of 100 d. After 100 d the larvae survival rate was > 65 %, and the body length had increased for circa 6-fold.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.206
Teacher spread0.194 · 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 designBench or experimental
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

Citations11
Published2012
Admission routes1
Has abstractyes

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