{"id":"W4292462669","doi":"","title":"On how COVID-19 mitigation measures can reshuffle the risk of infection: a case study from Montreal, Canada","year":2022,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Coronavirus Infections; Computer science; Environmental health; Virology; Medicine; Internal medicine; Outbreak; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001663226,0.0005053756,0.000310825,0.001064406,0.007855985,0.002686378,0.001634571,0.001332353,0.006633844],"category_scores_gemma":[0.003819834,0.0002139863,0.0005904014,0.00161761,0.002272138,0.0005607792,0.001566247,0.001394553,0.0002642925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05749988,"about_ca_system_score_gemma":0.07185859,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946964,"about_ca_topic_score_gemma":0.9968004,"domain_scores_codex":[0.9981657,0.0005061851,0.00002786552,0.00009009232,0.000302225,0.0009079663],"domain_scores_gemma":[0.998042,0.0004343784,0.0001247072,0.00007003081,0.0007765585,0.0005523273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006938059,0.0007262866,0.3841437,0.0007574835,0.0004594238,0.02591681,0.031939,0.03053127,0.004592313,0.1847317,0.1704526,0.1650557],"study_design_scores_gemma":[0.0002751451,0.0005950663,0.4393675,0.001063222,0.0005629296,0.003942177,0.131857,0.02628708,0.002926411,0.02168529,0.3710485,0.0003895999],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7337374,0.005495957,0.01016342,0.05977299,0.0004054249,0.0004992857,0.003130217,0.0001428271,0.1866525],"genre_scores_gemma":[0.9699164,0.001701359,0.002820212,0.001351213,0.00004263065,0.00004308667,0.0002823302,0.00002580401,0.02381695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05749988,"threshold_uncertainty_score":0.4171928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0986070041289642,"score_gpt":0.3359485277640416,"score_spread":0.2373415236350774,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}