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Record W2726168146 · doi:10.54846/jshap/972

Determining feeder space allowance across feed forms and water availability in the feeder for growing-finishing pigs

2017· article· en· W2726168146 on OpenAlexaff
Yuzhi Li, Kimberly McDonald, H. W. Gonyou

Bibliographic record

VenueJournal of Swine Health and Production · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsGenome Prairie
Fundersnot available
KeywordsAllowance (engineering)Animal scienceFeed conversion ratioProductivityEating behaviorBody weightEnvironmental scienceMathematicsBiologyOperations managementObesityEngineeringEndocrinology

Abstract

fetched live from OpenAlex

Objectives: To evaluate a method of determining the optimal feeder space allowance for pigs. Materials and methods: Trial 1 used eight pens of 12 pigs to determine total eating time in pigs to estimate occupancy rates of a single-space feeder. Feed was provided in four combinations of feed form (mash versus pelleted) and water availability in the feeder (dry versus wet-dry). Eating behavior of pigs was video-recorded during both growing and finishing phases. Trial 2 used 560 pigs for the growing phase and 454 pigs for the finishing phase. Effects of feeder occupancy rate (< 80%, 95%, 110%, and 125% for the growing phase; 80%, 103%, and 125% for the finishing phase) on total eating time and growth performance were determined. Results: Both feed form (P < .01) and water availability in the feeder (P < .001) affected total eating time and, consequently, feeder occupancy rate. Pigs spent more time eating a dry mash diet than any other diet by water combination during both growing (P < .001) and finishing (P < .01) phases. As feeder occupancy rate increased to above 80%, either eating time (P < .05) or growth performance (P < .05) decreased. Implications: When testing levels of feeder space allowance and identifying the optimum, the designated number of pigs per feeder space should be determined according to feeder occupancy rates under different production settings. Optimal feeder space allowance should maintain both productivity and eating time of pigs.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.053
GPT teacher head0.320
Teacher spread0.267 · 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 teacher head, 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

Citations7
Published2017
Admission routes1
Has abstractyes

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