Bibliographic record
Abstract
The International Commission on Microbiological Specifications for Foods (ICMSF) has been requested to contribute by proposing risk-based microbiological criteria as one of the control measures, and the proposal currently annexed in the revised draft code is presented in this chapter. The main stumbling blocks identified during the preparation of the initial drafts certainly is the scope of the new code, i.e., the types of products to be included in relation to the existing definitions of infants and the definitions of infant formulae, which may vary depending on the country. The European Commission has, established microbiological criteria for formulae for special medical purposes and for infant formulae that include two food safety parameters (Salmonella and E. sakazakii), with detection of other Enterobacteriaceae as a process hygiene parameter. The importance of the adherence to good hygiene practices during preparation has been stressed in all assessments performed. While the establishment of microbiological criteria has progressed rapidly and has led to the creation and even the implementation of very similar stringent criteria throughout the world, the establishment of guidelines for the safe preparation, handling, and storage of infant feeds has lagged behind. It is evident that, as far as regulatory approaches to control E. sakazakii are concerned, a multipronged approach is the best one. This will require continued cooperation and collaboration between hospitals, industry, and governments.
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.
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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.014 | 0.008 |
| Insufficient payload (model declined to judge) | 0.101 | 0.070 |
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".