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Record W2152133526 · doi:10.3168/jds.2015-9610

Factors affecting management changes on farms participating in a Johne’s disease control program

2015· article· en· W2152133526 on OpenAlexaffabout
Robert Wolf, Herman W. Barkema, Jeroen De Buck, Karin Orsel

Bibliographic record

VenueJournal of Dairy Science · 2015
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsParatuberculosisHerdAuditMycobacterium avium subsp. paratuberculosisOddsOdds ratioEnvironmental healthDisease managementDisease controlRisk managementMedicineTransmission (telecommunications)DiseaseAgricultural scienceVeterinary medicineLogistic regressionBusinessBiologyMycobacteriumPathology

Abstract

fetched live from OpenAlex

Modern Johne's disease programs aim to control Mycobacterium avium ssp. paratuberculosis (MAP) infection through implementation of management practices that reduce the probability of MAP introduction and within-herd transmission on dairy farms. Success of these programs depends on whether weaknesses in management are corrected through implementation of management improvements. The objectives of this study were, therefore, to (1) assess whether scores in risk-assessment (RA) questions predicted suggestions for management changes for the upcoming year; and (2) determine factors as assessed in an RA that motivated producers to make management improvements and assess whether management improvements were influenced by previously received test results. The RA determining on-farm management related to MAP introduction and transmission were conducted annually by herd veterinarians on 370 dairy farms participating in the Alberta Johne's Disease Initiative. A maximum of 3 management changes that the farmer and the veterinarian agreed upon were recorded in a management plan. The MAP infection status of the herds was assessed through culture of 6 environmental samples. Whereas a management change was proposed for only 4% of questions with scores 1 or 2 (low risk), a change was proposed for 19% of questions with scores >2 [high risk; odds ratio (OR)=11.4]. Improvement in RA question scores was more likely between the first and second annual RA than between the second and third RA (OR=1.6). Farms with >3 culture-positive environmental samples collected in the previous year were more likely to improve their management than environmental sample culture-negative farms (OR=1.3). In conclusion, proposed management changes were oriented toward previously identified weaknesses in management practices, suggesting that the RA was properly used to design targeted management suggestions. Furthermore, improvements in management were not randomly distributed among farms participating in the control program. Instead, knowledge of MAP infection status of a herd, suggestions for management improvements, and duration of participation all influenced implementation of management improvements.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.053
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.099
GPT teacher head0.385
Teacher spread0.286 · 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

Citations18
Published2015
Admission routes2
Has abstractyes

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