Bibliographic record
Abstract
This study was performed to introduce the application method of increasing reliability by comparison between national proof, MACE(Multiple Across Country Evaluation) proof and deregressed MACE proof using 973 dairy sires in Korea. International genetic evaluation by Interbull was conducted by joining 31 groups of 32 countries with 134,533 sires for milk production traits. Correlation between national proof and MACE proof was 0.925 and the correlations by nationality were 0.917, 0.910 and 0.996 for Canadian, American(USA) and Korean, respectively. In case of sires with high reliabilities as they have plenty number of daughters, changes of reliabilities was low for both of Korean and foreign sires, however, in case of sires with low EDC(Effective Daughter Contribution) in Korea and high EDC in foreign countries, reliability was increased in MACE proof as maximum of 43. Average reliability of MACE proof was 87.16±10.62 with range of 51~99 and correlation between MACE proof and deregressed MACE proof was high as 0.945
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".