Corrigendum: Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds
Bibliographic record
Abstract
Corrigendum on: Rasmussen P, Barkema HW, Hall DC. Effectiveness andEconomic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds. Front. Vet. Sci. (2021) 7. doi:10.3389/fvets.2020.614727. In the original article, there was a typographical error. A correction has been made to the exponent on the final bracket of Materials and Methods, Testing and Culling, Paragraph 1, Equation (1). The corrected paragraph appears below."In this control scenario, animals aged 1-7 years are tested annually using a combination of pooled and individual fecal PCR tests. They are first tested at time zero, and then retested after each transition period (year) along with purchased replacements aged 1-3 years, which are tested only at the individual level. For all testing periods, the probability of a pooled test containing samples from an number of MAP-positive animals given the pool size , or ( ) | ( , ), is determined using the following equation: where: equals the number of true positive animals aged 1-7 years in a shedding state and (1−7) equals the number of animals aged 1-7 years in the herd. A testing pool size of five animals is assumed, or = 5. Pooled tests and individual tests are assumed to share the same sensitivities and specificities, or that = and = ."The authors apologize for this error and state that this does not change the scientific results or conclusions of the article in any way. The original article has been updated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.098 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.063 | 0.031 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".