Report of an International Survey of Molecular Genetic Testing Laboratories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To collect data on the practices of molecular genetic testing (MGT) laboratories for the development of national and international policies for quality assurance (QA). METHODS: A web-based survey of MGT laboratory directors (n = 827; response rate 63%) in 18 countries on 3 continents. QA and reporting indices were developed and calculated for each responding laboratory. RESULTS: Laboratory setting varied among and within countries, as did qualifications of the directors. Respondents in every country indicated that their laboratory receives specimens from outside their national borders (64%, n = 529). Pair-wise comparisons of the QA index revealed a significant association with the director having formal training in molecular genetics (p < 0.005), affiliation with a genetics unit (p = 0.003), accreditation of the laboratory (p < 0.005) and participation in proficiency testing (p < 0.005). Research labs had a lower mean report score compared to all other settings (p < 0.05) as did laboratories accessioning <150 samples per year. CONCLUSION: MGT is provided under widely varying conditions and regulatory frameworks. The data provided here may be a useful guide for policy action at both governmental and professional levels.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it