Comparative transcriptomic analysis of nasopharyngeal swabs from individuals with and without COVID-19
Bibliographic record
Abstract
This dataset contains the results of a transcriptomic (RNA-seq) analysis of nasopharyngeal swabs collected from 50 individuals with COVID-19 and 13 individuals without COVID-19 based on clinical qPCR testing. COVID-19 positive individuals included 16 outpatients, 16 hospitalized, non-ICU patients, and 18 hospitalized ICU patients. Samples were collected from a clinical cohort in Greater Toronto Area hospitals and outpatient assessment centres between October 2020 and October 2021. Four comparative analyses were performed using DESeq2: all COVID-19 positive individual versus negatives, COVID-19 ICU individuals versus negatives, non-ICU COVID-19 positive individuals versus negatives, and COVID-19 positive outpatients versus negatives. The analysis was performed with DESeq2 v1.30.1 using the Gencode human reference transcriptome v37.<br>
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 0.016 |
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; both teacher heads agree on what is shown here.
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".