Papers Celebrating the 25th Anniversary of Biometric Society of Japan Contribution to Human Society: Experience of a Quarter of a Century and the Future Prospects Major Activities of Biometric Society of Japan and Japanese Biostatisticians —Past, Present and Future—
Bibliographic record
Abstract
At the end of 2005 Biometric Society of Japan (BSJ) cerebrated a quarter of a century of its establishment, a 25-year period over which the number of BSJ members has increased to about 450 from 220 and it has engaged a wide range of research and education. In this report, I reviewed the major activities of BSJ and the achievements that BSJ members have made by investigating the temporal trend of published papers in such journals as Japanese Journal of Biometrics, Biometrics and Statistics in Medicine. I further investigated the Japanese achievements published in the Encyclopedia of Statistical Sciences and the Cambridge Dictionary of Statistics. Based on these investigations, I discussed the key conditions that, I think, could improve the present situation and infuence the future activities and status of Japanese Biostatisticians.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".