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DIAGNOSIS AND TREATMENT OF POSTPARTUM UTERINE DISEASES IN DAIRY COWS: A REVIEW WITH EMPHASIS ON SUBCLINICAL ENDOMETRITIS

2017· review· en· W2765740200 on OpenAlexaff
Osvaldo Bogado Pascottini, Geert Opsomer

Bibliographic record

VenueCompendio de ciencias veterinarias · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEndometritisGynecologyMedicineHumanitiesBiologyPhilosophyPregnancy

Abstract

fetched live from OpenAlex

In this review, updated and precise definitions of the most common postpartum uterine diseases in dairy cows are provided.An aberrant uterine environment at inappropriate stages of the reproductive cycle inflicts damage to gametes and zygotes, impairing the reproductive performance of dairy cows.This involves major economic losses for the milk production unit.Consequently, an accurate diagnosis of postpartum uterine diseases is indispensable for practitioners to set up a prompt and efficient treatment.This review furthermore emphasizes on the new perspectives regarding diagnosis and treatment of subclinical endometritis, a highly prevalent uterine disease that is often overlooked by practitioners while causing major reproductive problems.Based on a more profound clinical understanding of the postpartum uterine disease complex, practitioners will be able to better use the available diagnostic tools and therefore apply a more efficient therapeutic approach.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.184
GPT teacher head0.393
Teacher spread0.208 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2017
Admission routes1
Has abstractyes

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