Bibliographic record
Abstract
Widespread human-to-human transmission of the severe acute respiratory syndrome coronavirus two (SARS-CoV-2) stems from a strong affinity for the cellular receptor angiotensin converting enzyme two (ACE2). We investigate the relationship between a patient’s nasopharyngeal <i>ACE2</i> transcription and secondary transmission within a series of concurrent hospital associated SARS-CoV-2 outbreaks in British Columbia, Canada.<i>Methods</i>: Epidemiological case data from the outbreak investigations was merged with public health laboratory records and viral lineage calls, from whole genome sequencing, to reconstruct the concurrent outbreaks using infection tracing transmission network analysis. <i>ACE2</i> transcription and RNA viral load were measured by quantitative real-time polymerase chain reaction. The transmission network was resolved to calculate the number of potential secondary cases. Bivariate and multivariable analyses using Poisson and Negative Binomial regression models was performed to estimate the association between <i>ACE2</i> transcription the number of SARS-CoV-2 secondary cases.<br><br>Data Dictionary:<br><b>Unit_of_Transmission:</b> Hospital Unit where a infection prevention and control epidemiologist identified a possible transmission event.<br><b>Unit_Acquisition:</b> Hospital Unit where a infection prevention and control epidemiologist identified a possible acquisition event.<br><b>Collection Date (yyyy-mm-dd, UTC):</b> date at which a nasopharyngeal specimen was collected from a symptomatic case for SARS-CoV-2 molecular diagnostic testing using qRT-PCR.<br><b>log_GE: </b> Logarithmic base ten genome-equivalents per millilitre of SARS-CoV-2 detected by envelope gene target using qRT-PCR.<br><b>Fold.Change.ace3: </b> Relative gene expression data of <i>ACE2</i> expression (full-length/ transmembrane transcript variant).<br><b>Linearge: </b>SARS-CoV-2 viral lineage as classified by the PANGOLIN tool (Version 1.15.1), viral genome alignments are available on GISAID. <br>
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.497 | 0.572 |
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".