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A factorial model to predict phosphorus waste output of rainbow trout (Oncorhynchus mykiss)

2008· article· en· W2140667373 on OpenAlex
Katheline Hua, C. F. M. de Lange, A. J. Niimi, G O Cole, Richard D. Moccia, Ming Fan, Dominique Bureau

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAquaculture Research · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsFisheries and Oceans CanadaUniversity of Guelph
Fundersnot available
KeywordsRainbow troutFactorial experimentBiologyAquacultureFisheryBioenergeticsPhosphorusRecirculating aquaculture systemFactorialSalmonidaeAnimal scienceOncorhynchusFish <Actinopterygii>StatisticsMathematicsBiochemistry

Abstract

fetched live from OpenAlex

Minimizing phosphorus (P) wastes is considered to be a key factor for environmental sustainability of freshwater aquaculture operations in many parts of the world. A factorial P model, consisting of digestibility, whole-body P deposition, P waste output and limnological transformation sub-models, was constructed to simulate the effects of different dietary P sources and levels on P utilization in salmonids. This factorial P model was developed based on information from the literature for rainbow trout (Oncorhynchus mykiss). This factorial model runs on the platform of a fish bioenergetics model that provides dynamic estimates of feed intake of salmonids based on diet composition and growth rate. Simulations suggest that this model can potentially be a useful tool for waste output management of salmonid culture operations.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

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

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 head0.099
GPT teacher head0.316
Teacher spread0.217 · 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