[Current status of ISO 15189 accreditation system].
Bibliographic record
Abstract
The Japan Accreditation Board (JAB) mainly involves the ISO 15189 accreditation system with support from the Japanese Committee for Clinical Laboratory Standards (JCCLS). The currently available procedure to obtain accreditation is as below. Firstly, it is necessary for applicants to prepare ISO 15189 and related documents in each laboratory. Then a JAB assessor will conduct a preliminary assessment to check if the applicant is ready to be accredited. Subsequently, a team consisting of one to five JAB assessors and/or technical experts will conduct the initial assessment, usually for two days. Finally, the team will make a recommendation to the JAB Accreditation Committee for Medical Laboratory on its evaluation for accreditation. If the Accreditation Committee approves the recommendation of the assessment team, the applicant will be granted accreditation and issued with a certificate of accreditation. According to EU data in February 2011, about 1,300 medical laboratories obtained the ISO 15189 accreditation. The numbers of accredited laboratories are 482 in Germany, 276 in England, 209 in France, 100 in Czechoslovakia etc. Similarly, the data for the Asia-Pacific region in June 2011 showed that the numbers of accredited laboratories are 638 in Australia, 287 in India, 220 in Canada, 160 in Taiwan etc. Although 59 laboratories are accredited in Japan, the ISO 15189 accreditation is not so widespread compared with other countries. It is now expected that the government and/or related bodies will have sufficient understanding of this accreditation system to further its development in Japan. [Rinsho Byori 60: 653-659, 2012]
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.043 |
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".