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Record W3135088133 · doi:10.21423/aabppro20173391

Effect of prepartum energy balance on neutrophil function following pegbovigrastim treatment in periparturient cows

2017· article· en· W3135088133 on OpenAlexaff
S McDougall, Paul Rapnicki, S.J. LeBlanc, Axel Heiser

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Guelph
FundersInstitute of Veterinary, Animal and Biomedical Sciences, Massey UniversityElanco Animal HealthMassey University
KeywordsGranulocyteIce calvingGranulocyte colony-stimulating factorRecombinant DNAInternal medicineEndocrinologyMedicineAnimal scienceImmunologyBiologyBiochemistryLactationPregnancyChemotherapy

Abstract

fetched live from OpenAlex

Treatment with granulocyte colony stimulating factor (GCSF) increases neutrophil (PMN) count and enhances PMN function in the periparturient cow. It was hypothesized that prepartum undernutrition might reduce the effect of a commercial recombinant bovine G-CSF product (pegbovigrastim; Imrestor (IMR), Elanco) on PMN count and function. Hence the objective of this study was to test the effect of undernutrition for 1 month prior to calving on the response to IMR.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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
Published2017
Admission routes1
Has abstractyes

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