Regulation of in vitro diagnostics (IVDs) for use in clinical diagnostic laboratories: towards the light or dark in clinical laboratory testing?
Bibliographic record
Abstract
A revised framework for the regulation of in vitro diagnostic devices (IVDs) came into force in Australia on July 1, 2010 that aims to 'ensure that public and personal health are adequately protected', but which instead may lead to adverse outcomes in clinical diagnosis and management. The regulatory process aims to regulate all IVDs, including those used by clinical diagnostic laboratories, which are already subject to scrutiny as part of the current laboratory accreditation process. The IVD regulatory process initiated in Australia is similar to that used in Canada, but different to that currently operating in the USA and Europe. However, it is feasible that other countries will in time adopt a similar regulatory framework, given that many countries are involved in the development process. In this opinion paper, the regulatory process for IVDs across several geographies are outlined, as are some benefits and weaknesses of the new regulatory process now applied to Australia, as potentially planned for other regions of the world.
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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 | 0.078 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".