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Record W2961332982 · doi:10.3390/ani9070434

Gilt Management for Fertility and Longevity

2019· review· en· W2961332982 on OpenAlex

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

VenueAnimals · 2019
Typereview
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFertilityLongevityHerdProductivityProduction (economics)BiologyBusinessBiotechnologyAgricultural scienceAnimal scienceDemographyEconomicsPopulationEconomic growth

Abstract

fetched live from OpenAlex

Substantial evidence supports successful management of gilts as an absolutely necessary component of breeding herd management and the pivotal starting point for the future fertility and longevity of the breeding herd. Therefore, gilt management practices from birth have the potential to influence the future reproductive performance of the sow herd. A good gilt management program will address several key components such as birth traits that determine the efficiency of replacement gilt production; effective selection of the most fertile gilts for entry to the breeding herd; effective management programs that provide a consistent supply of service eligible gilts; and appropriate management of weight, physiological maturity, and a positive metabolic state at breeding. Good gilt management can largely resolve the existing gap between excellent genetic potential and the more modest sow lifetime productivity typically achieved in the industry. Investment in good gilt development programs from birth represents a foundational opportunity for improving the efficiency of the pork production industry.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.306
GPT teacher head0.462
Teacher spread0.156 · 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