MétaCan
Menu
Back to cohort
Record W3164119290 · doi:10.1093/jas/skab035

Factors affecting performance response of pigs exposed to different challenge models: a multivariate approach

2021· article· en· W3164119290 on OpenAlexaff
Lucas Alves Rodrigues, F. Ferreira, Matheus O. Costa, Michael O Wellington, Daniel A Columbus

Bibliographic record

VenueJournal of Animal Science · 2021
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsGenome PrairieUniversity of Saskatchewan
Fundersnot available
KeywordsAnimal scienceBiologyMultivariate statisticsPlateau (mathematics)Feed conversion ratioLipopolysaccharideVeterinary medicineBody weightImmunologyMedicineMathematicsEndocrinologyStatistics

Abstract

fetched live from OpenAlex

Factors associated with the severity with which different challenge models (CMs) compromise growth performance in pigs were investigated using hierarchical clustering on principal components (HCPC) analysis. One hundred seventy-eight studies reporting growth performance variables (average daily gain [ADG], average daily feed intake [ADFI], gain:feed [GF], and final body weight [FBW]) of a Control (Ct) vs. a Challenged (Ch) group of pigs using different CMs (enteric [ENT], environmental [ENV], lipopolysaccharide [LPS], respiratory [RES], or sanitary condition [SAN] challenges) were included. Studies were grouped by similarity in performance in three clusters (C1, C2, and C3) by HCPC. The effects of CM, cluster, and sex (males [M], females [F], mixed [Mi]) were investigated. Linear (LRP) and quadratic (QRP) response plateau models were fitted to assess the interrelationships between the change in ADG (∆ADG) and ADFI (∆ADFI) and the duration of challenge. All variables increased from C1 through C3, except for GF, which decreased (P < 0.05). LPS was more detrimental to ADG than ENV, RES, and SAN models (P < 0.05). Furthermore, LPS also lowered GF more than all the other CMs (P < 0.05). The ∆ADG independent of ∆ADFI was significant in LPS and SAN (P < 0.05), showed a trend toward the significance in ENT and RES (P < 0.10), and was not significant in ENV (P > 0.10), while the ∆ADG dependent on ∆ADFI was significant in ENT, ENV, and LPS only (P < 0.05). The critical value of ∆ADFI influencing the ∆ADG was significant in pigs belonging to C1 (P < 0.05) but not C2 or C3 (P > 0.10). The ∆ADG independent of duration post-Ch (irreparable portion of growth) was significant in C1 and C2 pigs, whereas the ∆ADFI independent of duration post-Ch (irreparable portion of feed intake) was significant in C1 pigs only (P < 0.05). Moreover, the time for recovery of ADG and ADFI after Ch was significant in pigs belonging to C1 and C2 (P < 0.05). Control F showed reduced ADG compared with Ct-M, and Ch-F showed reduced ADFI compared with Ch-M (P < 0.05). Moreover, the irreparable portion of ΔADG was 4.8 higher in F (-187.7; P < 0.05) compared with M (-39.1; P < 0.05). There are significant differences in growth performance response to CM based on cluster and sex. Furthermore, bacterial lipopolysaccharide appears to be an appropriate noninfectious model for immune stimulation and growth impairment in 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 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)0.005
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.209
GPT teacher head0.361
Teacher spread0.152 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Animal ScienceSame topicAnimal Behavior and Welfare StudiesFrench-language works237,207