Culture Collections in Japan and their Services
Bibliographic record
Abstract
Culture collections (CCs) are organizations that mainly collect strains of microorganisms to stably preserve or maintain them and distribute them to users. There are 23 CCs in Japan ; these are mainly established in universities and national institutes, and contain a total of 411 183 strains of preserved microorganisms (191 692 bacteria, 50 799 yeasts, 49 380 fungi and others), accounting for 20 % of strains preserved in CCs around the world. CCs also store information on their microorganism collections (species, location and origin of isolation, and growth conditions) in databases. These primary data for the identification of strains are open to the public via the Internet, and users can retrieve the data using searching systems offered by the CCs instead of using paper-based catalogs. In CCs, deposited microorganisms are cultured and, depending on the microbial group, freeze-drying or other freezing methods are used to prepare the microorganisms for distribution. At regular intervals, survival tests are carried out to check the quality of the preparations. In addition, CCs offer services other than distribution of their collections, such as e-mail newsletters, workshops on the handling of microorganisms, booklets on the microorganisms, and safety-deposit services for users’ collections.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.023 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.139 | 0.127 |
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".