Characterization of Enterovirus Activity, Including That of
Bibliographic record
Abstract
In the late summer and fall of 2014, the province of Alberta,Canada (4.1 million people), was in the midst of peak entero-rhinovirus (ERV) activity, as descriptions of enterovirusD68 (EV-D68) activity were being publicized (1, 2). This analysis was un-dertaken with several goals: (i) to understand the burden of respiratory illness in emergency department (ED) visits on 18-year-old Albertans in the periods from 14 August to 10 September in both 2013 and 2014; (ii) to understand the impact of enterovi-ruses, including EV-D68, on pediatric hospital patients (from 14 August to 10 September 2014, when rates of ERV activity were increasing); and (iii) to determine whether those infected with EV-D68 aremore likely to have asthma or other respiratory illness than those with EV of a strain other than D68. This analysis was initiated as a public health investigation and did not require ethics approval, and all clinical specimens and datawere collected for the purposes of routine ongoing diagnostics and surveillance.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".