A COMPREHENSIVE STUDY ON TPI CLASSIFICATIONS IN BULLS AND GLOBALHERD QUALITY INDICATORS
Bibliographic record
Abstract
The Total Performance Index (TPI) is a key genetic evaluation tool developed to rank Holstein bulls based on their ability to enhance herd productivity, health, and longevity. Widely used in the United States and beyond, TPI integrates traits like milk production, fertility, and conformation into a single score, guiding dairy farmers in selecting bulls that can genetically improve their herds. This project aims to delve deeply into the TPI classification system, exploring its methodology, significance, and impact on global dairy farming. Additionally, it will compare TPI with other herd quality indicators, such as the Profitable Lifetime Index (PLI) in the UK and the Lifetime Profit Index (LPI) in Canada, to highlight the diversity in genetic evaluation systems across different countries. The future of dairy farm sustainability lies in genomic testing and knowledge of the performance indices of bulls and cows, combining them in new generations of animals through reproductive biotechnologies such as embryo transfer.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".