Additional file 1 of Time trends in social contacts before and during the COVID-19 pandemic: the CONNECT study
Bibliographic record
Abstract
Additional file 1: Table S1. Overview of the different phases of CONNECT. Table S2. Weighting procedure. Table S3. Time trends in the number of social contacts, by location of contacts A mean number of contacts, B median number of contacts. Table S4. Association between the mean number of social contacts and the stringency index. Table S5. Time trends in the total number of social contacts by key socio-demographic characteristics. Table S6. Time trends in the number of social contacts at school/daycare among children-students according to school level. Table S7. Time trends in social contacts at work among workers and according to the type of employment (2016 National occupation classification). Table S8. Time trends in the proportion of workers who reported working remotely, according to the type of employment (2016 National occupation classification). Fig. S1. Example of the social contact diary. Fig. S2. Quebec COVID-19 epidemiology, related physical distancing measures, and CONNECT data periods. Fig. S3. Flowchart of participant identification for CONNECT 1, CONNECT 2, and CONNECT 3,4,5. Fig. S4. Mean number of social contacts according to the intensity of public health measures in Quebec as summarized by the stringency index.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.621 | 0.046 |
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".