MétaCan
Menu
Back to cohort
Record W7134994281

Required dietary digestible lysine content for maximum growth performance in weaned piglets

2025· other· en· W7134994281 on OpenAlexfundno aff
N.E. Manzke, P. Pluk, A.J.M. Jansman, P. Bikker

Bibliographic record

VenueSocio-Environmental Systems Modeling · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersLandbrugsstyrelsenNatural Sciences and Engineering Research Council of CanadaElanco Animal HealthGrønt Udviklings- og Demonstrations ProgramEuropean Agricultural Fund for Rural DevelopmentMinisterie van Landbouw, Natuur en VoedselkwaliteitCHIST-ERAH. Wilhelm Schaumann StiftungRoyal De HeusJunta de AndalucíaCanada First Research Excellence FundBundesamt für LandwirtschaftEvonik OperationsUniversité François-RabelaisBundesministerium für Ernährung und LandwirtschaftVereniging Diervoederonderzoek NederlandU.S. Department of AgricultureMitacsUniversity of AlbertaEuropean CommissionMinisterio de Ciencia e InnovaciónNarodowym Centrum NaukiNational Institute of Food and AgricultureNovo NordiskUniversità degli Studi di MilanoGeneralitat de CatalunyaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São PauloAgentschap Innoveren en OndernemenAarhus UniversitetDeutsche ForschungsgemeinschaftJapan Society for the Promotion of ScienceNovalaitConselho Nacional de Desenvolvimento Científico e TecnológicoVlaamse regeringBeef Farmers of OntarioSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungBeef Cattle Research CouncilTexas Tech UniversityAgriculture and Agri-Food CanadaNational Science Foundation
KeywordsLysineComposition (language)Feed conversion ratioBody weightAnimal production
DOInot available

Abstract

fetched live from OpenAlex

highfat milk replacer.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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)0.0040.000

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 head0.043
GPT teacher head0.237
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 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
Published2025
Admission routes1
Has abstractno

Explore more

Same venueSocio-Environmental Systems ModelingFrench-language works237,207