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Record W2148915901 · doi:10.4141/a02-034

Hormonal, behavioural and performance characteristics of Meishan sows during pregnancy and lactation

2003· article· en· W2148915901 on OpenAlexaffvenue
C. Farmer and S. Robert

Bibliographic record

VenueCanadian Journal of Animal Science · 2003
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsLactationLitterBreedBiologyPregnancyGestationEndocrine systemAnimal scienceHormoneEndocrinologyPhysiologyEcology

Abstract

fetched live from OpenAlex

Meishan sows are known for their high prolificity and great lactational performances. Specific breed characteristics in terms of their embryonic, foetal and placental developments as well as their differences in mammary development at the end of gestation are covered. The various known metabolic, physiological and endocrine factors related to the decreased embryonic mortality and increased placental vascularity, which are largely responsible for the greater litter size of Meishans, are discussed. An overview of published data on the endocrine status of the sow and foetuses throughout pregnancy is also presented. The superiority of Meishan sows during lactation is described in terms of its various components (i.e., piglet growth and development, sow and litter behaviour, milk composition) and the breed differences pertaining to sow metabolism and endocrinology during lactation are covered in order to provide an insight as to the possible mechanisms responsible for these superior performances. This review illustrates how a better understanding of the biological differences between Meishan sows and sows from European breeds could benefit the development of new management schemes to further improve reproductive potential of sows from traditional breeds. Key words: Meishan, gestation, lactation, hormones, behaviour, performance

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.049
GPT teacher head0.279
Teacher spread0.230 · 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

Citations29
Published2003
Admission routes2
Has abstractyes

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