Development of a Profitability Analysis Prototype with Multidimensional Benchmarks for Dairy Herds
Bibliographic record
Abstract
The prototype of an information visualisation tool was developed using combined information from the Que´bec and Atlantic Provinces Dairy Production Centre of Expertise (Valacta Inc.) and the Quebec Animal Health Records (DSAHR Inc.), with the objective of presenting cumulative lifetime-profit results, and the factors that affect them, thereby facilitating the process of analysing and comparing results at the dairy-herd and individual-cow levels. The information visualisation prototype created benchmarking curves with the possibility to evaluate current profitability at the herd and individual-cow level, and also to monitor the effect of historical decisions and events on the future components of profit. The user is presented with a herd analysis that compares its profit evolution to those of selected cohorts. These values are calculated from the accumulation of average daily profit estimates by herd or cohort. At the individual-cow level, lifetime profit curves are presents that include the effects of health and breeding-service costs among others. It is hoped that this prototype may demonstrate the value, to Dairy Herd Improvement agencies, of analysing and visualizing existing and potential profitability at the herd level, and lifetime analysis at the individualcow level.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".