Quality of early evidence on the pathogenesis, diagnosis, prognosis and treatment of COVID-19
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
Since the initial description of the SARS-CoV-2 outbreak and its declaration as a worldwide pandemic, the number of publications on the novel virus has increased rapidly. We studied the trends and quality of evidence in early SARS-CoV-2 publications. A comprehensive search of MEDLINE and EMBASE was performed for papers published between 1 January 2020 and 21 April 2020. Two reviewers independently screened titles and abstracts and subsequently full texts for eligibility in this systematic review. The search yielded 2504 citations published between January and February 2020 or an unspecified date, 109 of which remained for extraction after screening. Data extracted included study design, year of publication, country of basis, journal of publication, impact factor of publishing journal, study sample size, number of citations and topic of investigation. Study design-specific critical appraisal tools were used to evaluate the scientific rigour of all included papers: the Joanna Briggs Institute checklist was used for case series, Scale for the Assessment of Narrative Review Articles scale for narrative reviews, Newcastle-Ottawa scale for cohort studies and AMSTAR 2 for systematic reviews. The overall quality of the literature was low-moderate. Of 541 papers that reported clinical characteristics, 295 were commentaries/expert opinions and 36 were case reports. There were no randomised clinical trials, 45 case series studies, 58 narrative reviews, 1 cohort study and 5 systematic reviews. We encourage clinicians to be attentive to these findings when utilising early SARS-CoV-2 evidence in their practices.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
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 | 0.008 | 0.414 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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