Bibliographic record
Abstract
The novel coronavirus (severe acute respiratory syndrome; SARS-CoV-2) pandemic has spread rapidly throughout the planet. It is believed to have originated in the Wuhan province of China, but this highly contagious respiratory virus has spread to over 140 countries on 6 continents as of mid-March 2020, according to the World Health Organization. Worldwide, there have been over 164,000 cases identified and over 6500 deaths attributed to the viral infection. As of mid-March 2020, there are over 3700 confirmed cases and 68 deaths ascribed to the coronavirus disease 2019 (COVID-19; the disease caused by SARS-CoV-2) in the United States (www.livescience.com/coronavirus-updates-united-states.html). These numbers will only continue to grow globally. Based primarily on data out of China, about 80% of those infected with SARS-CoV-2 experience a relatively mild “cold,” as is seen with more common coronavirus infections. However, 20% of those infected require hospitalization, with 5–15% overall necessitating intensive care1. As the true denominator of those infected is not yet known, it remains unclear what the overall mortality rate is associated with COVID-19, but estimates range between 1% and 4%2. Although the mortality rate is lower than that reported for previous coronavirus epidemics such as SARS and MERS (Middle East respiratory syndrome), the much larger absolute number of infected individuals with SARS-CoV-2 will result in substantially more total deaths worldwide. Those at highest risk of dying from COVID-19 are elderly (> 60 yrs and increasing with age), those with immunodeficiencies, and those with underlying chronic medical conditions (e.g., diabetes, heart disease). Although children tend to experience only mild symptoms, younger previously healthy adults have also succumbed to COVID-19. Once hospitalized, for some patients, death can occur within a few days, many with adult respiratory distress syndrome, and some with multiorgan dysfunction syndrome3. In those critically ill patients, … Address correspondence to Dr. R.Q. Cron, Children’s of Alabama, Division of Rheumatology, 1600 7th Ave. S., CPPN, Suite G10, Birmingham, Alabama 35233-1711, USA. E-mail: rcron{at}peds.uab.edu
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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.053 | 0.018 |
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".