Retrospective analysis of risk and timing of death from right heart failure in United States and Canadian feedlot necropsied cattle
Bibliographic record
Abstract
OBJECTIVE: To evaluate the risk and timing of right heart failure (RHF) in feedlot cattle. ANIMALS: Study population consisted of 1,717,356 cattle (5,527 cohorts) in 13 US and Canadian feedlots. There were 1,336 RHF diagnosed at necropsy. PROCEDURES: Multivariable models were utilized to evaluate risk and timing of RHF death. RESULTS: Arrival year was associated with RHF and was influenced by arrival quarter on the magnitude of risk of RHF (P < .01), but no linear increase over years was identified. The impact of feedlot elevation on RHF was modified by breed (beef, dairy, or dairy-cross; P < .01) with beef cattle in the highest elevation category having 0.54 times the risk of RHF as dairy cattle in the same elevation category (LCL = 0.31; UCL = 0.962). Cattle that died due to RHF and were treated for bovine respiratory disease died 11 days (LCL = 1.33, UCL = 20.2 days) sooner than cattle never treated for bovine respiratory disease (P = .03). Cattle breed was associated with RHF timing (P = .01), and dairy-cross cattle RHF cases died approximately 37 days earlier (SE = 13.0 days; P = .01) compared to beef cattle. CLINICAL RELEVANCE: This research showed demographic factors associated with RHF and their respective influence on risk and timing of RHF. Risk rates of RHF were similar to previous research. This could allow for comparisons across different feedlot populations, using different diagnoses at necropsy and RHF risk/rates do not appear to be increasing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".