Additional file 5 of Understanding contextual and practical factors to inform WHO recommendations on using chest imaging to monitor COVID-19 pulmonary sequelae: a qualitative study exploring stakeholders’ perspective
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
Additional file 5: Appendix 5. Valuation of outcomes associated with using chest imaging to monitor COVID-19 pulmonary sequelae, with exemplary quotes. Appendix 6. Preferences for each chest imaging modality used to monitor COVID-19 pulmonary sequelae, by indication, pros and cons, with exemplary quotes. Appendix 7. Acceptability of using chest imaging to monitor COVID-19 pulmonary sequelae, by providers and patients respectively, its determinants, with exemplary quotes. Appendix 8. Determinants of equity of using chest imaging to monitor COVID-19 pulmonary sequelae and exemplary quotes. Appendix 9. Feasibility of using chest imaging to monitor COVID-19 pulmonary sequelae by facilitators and barriers, with exemplary quotes. Appendix 10. Practical issues that patients might consider when using chest imaging to monitor COVID-19 pulmonary sequelae, with exemplary quotes.
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 | 0.000 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.518 | 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