Technical Note: Software for Calculation of the Inverse Numerator Relationship Matrix
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Software was developed to compute the non-zero elements of the inverse of the numerator relationship matrix used in estimation of (co)variances and breeding values. The program was written to be flexible with regard to format of the input pedigree file and integration with existing software packages for genetic evaluation. The program was further designed to be highly portable, with a minimum of compiler dependence, and to use dynamic rather than static memory allocation. Real time required to read and sort input pedigrees containing 5,000 to 100,000 animals with varying levels of inbreeding and to compute the non-zero elements of the matrix was < 9.5 min and increased as the numbers of animals in the pedigree file increased beyond 20,000 animals. Increased numbers of inbred animals in large (≥20,000 animals) pedigrees increased the time required to complete computations. Although a combination of alphanumeric animal identification codes were allowed, the time required to initially read pedigrees and, therefore, total run time was significantly decreased (P < 0.001) for large pedigrees when identification codes were strictly numeric for all animals.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it