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Record W3140213901 · doi:10.21423/aabppro20114053

Temporal Repeatability of Positive Test Results of Mycobacterium avium subspecies paratuberculosis-antibody Milk ELISA-positive Cows

2011· article· en· W3140213901 on OpenAlexaff
U.S. Sorge, D.F. Kelton, A. Godkin, S. Wells, S. Hendrick, K. Lissemore

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2011
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of SaskatchewanUniversity of Guelph
Fundersnot available
KeywordsMycobacterium avium subspecies paratuberculosisParatuberculosisHerdSubclinical infectionDairy cattleAntibodyVeterinary medicineBiologyAnimal scienceMilk productionMycobacteriumMedicineImmunologyVirologyBacteria

Abstract

fetched live from OpenAlex

Johne’s disease (JD) of dairy cows is caused by Mycobacterium avium subspecies paratuberculosis (MAP). Although the majority of infected cows are subclinical, the infection causes production losses which lead to economic losses for the farm. Available tests do not identify all subclinically infected cows, and anecdotal reports from producers indicate that some cows can test positive for Johne’s disease or MAP antibodies at one test, and the same cow can test negative at a following test. These contradictory results often lead to frustration and uncertainty among producers about the interpretation of test results and their implication for JD control on their farm. Therefore, the objective of this study was to identify characteristics of the cow and her Dairy Herd Improvement (DHI) milk test at the time of a positive MAP-antibody milk ELISA (MAP milk ELISA) result that is followed by a different milk ELISA result, i.e. negative or suspect, compared to a cow’s milk test where cows tested positive at both the initial and subsequent MAP milk ELISA.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.294
Teacher spread0.272 · 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
Published2011
Admission routes1
Has abstractyes

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