Biosafety measures for preventing infection from COVID-19 in clinical laboratories: IFCC Taskforce Recommendations
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) is the third coronavirus outbreak that has emerged in the past 20 years, after severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). One important aspect, highlighted by many global health organizations, is that this novel coronavirus outbreak may be especially hazardous to healthcare personnel, including laboratory professionals. Therefore, the aim of this document, prepared by the COVID-19 taskforce of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC), is to provide a set of recommendations, adapted from official documents of international and national health agencies, on biosafety measures for routine clinical chemistry laboratories that operate at biosafety levels 1 (BSL-1; work with agents posing minimal threat to laboratory workers) and 2 (BSL-2; work with agents associated with human disease which pose moderate hazard). We believe that the interim measures proposed in this document for best practice will help minimazing the risk of developing COVID-19 while working in clinical laboratories.
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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 | 0.099 | 0.159 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.026 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 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".