The delights and perils of publishing, knowledge-sharing and critique during a pandemic: Observations from COVID-19 coagulopathies
Bibliographic record
Abstract
The COronaVIrus Disease 2019 (COVID-19) pandemic is a major global concern with 4,369,410 confirmed infections and 297,569 total deaths since the first reported outbreak of the infection (https://coronavirus.jhu.edu/map.html, accessed 14th May 2020) [1,2]. It is caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019-nCoV [3]. SARS-CoV-2 belongs to the β-coronavirus family, and shares 80% similarity to known SARS-CoV according to genome sequencing [4]. While COVID-19 is primarily a viral respiratory illness, it is proven to have systemic manifestations, most notably coagulation complications, in those with severe disease.
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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 | 0.006 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.019 | 0.026 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".