Life at the Editorial “COVID Frontline”. The American Thoracic Society Journal Family
Bibliographic record
Abstract
We live in extraordinary times, facing the greatest medical crisis of the last century and potentially of all time.The growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic affects each of us, our families, and our very way of life.Our core American Thoracic Society (ATS) journal readership, making up a significant number of individuals on the clinical and research frontlines, places us in a privileged position: the "editorial frontline" tasked to provide timely, robust, and scientifically sound information to inform clinical practice and research.With this role comes great responsibility and during a global pandemic requires real-time responses, accelerated peer review processes, and a timely, agile governance cadence.Although this is a challenge, the digital era of publication accelerates information availability at speeds inaccessible in past pandemics. Putting Safety FirstOur priority as editors is first safeguarding patient and physician safety by ensuring the scientific accuracy of submitted work: publishing stringently peer-reviewed data using accurate, responsible, and ethical approaches, while ensuring timely publication to facilitate advancements in knowledge and clinical care.Charged by the ATS with the responsibility of transitioning data into the public domain, our role requires time, focus, and a meticulous approach, in reality, working at the "editorial frontline."During a global pandemic, we face a set of unique issues where publishing data at speed must be balanced against maintaining standards and rigor.Here we provide a view from that frontline for our international readership.
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.
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 | 0.005 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.193 | 0.156 |
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".