{"id":"W2156628517","doi":"10.1503/cmaj.091641","title":"Modelling mitigation strategies for pandemic (H1N1) 2009","year":2009,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; University Health Network","funders":"Ontario Ministry of Research and Innovation; Canadian Institutes of Health Research","keywords":"Attack rate; Pandemic; Vaccination; Population; Outbreak; Medicine; Influenza pandemic; Pandemic influenza; Environmental health; Public health; Closure (psychology); H1n1 pandemic; Coronavirus disease 2019 (COVID-19); Virology; Infectious disease (medical specialty); Disease; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003515771,0.0001366847,0.000323437,0.00009953923,0.0004302481,0.00009811037,0.0002012843,0.0003947765,0.0003665492],"category_scores_gemma":[0.01131076,0.0001140917,0.0001531097,0.0001413577,0.00002694922,0.0001691445,0.000006806828,0.0006143731,0.0000205834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138426,"about_ca_system_score_gemma":0.001481472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006575165,"about_ca_topic_score_gemma":0.006135769,"domain_scores_codex":[0.9978193,0.0001668121,0.0005973097,0.0001691071,0.0006962013,0.0005512461],"domain_scores_gemma":[0.9963368,0.002084112,0.0003213241,0.0000785928,0.0003853595,0.0007937817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003092418,0.00009839444,0.01731157,0.00005192052,0.0002725896,0.00008311026,0.001319496,0.005638809,0.00002699968,0.1635463,0.7473174,0.06430247],"study_design_scores_gemma":[0.0006683675,0.0001068225,0.002205268,0.00007763523,0.00004331155,0.00003400868,0.0005579705,0.03426016,0.000002381131,0.8563134,0.1055181,0.0002125868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2231333,0.001153274,0.5816522,0.1859774,0.001151028,0.0007935449,0.00009590168,0.000227755,0.00581564],"genre_scores_gemma":[0.9649816,0.0003103356,0.00893971,0.02306773,0.002262515,0.00001813819,0.00001013767,0.0000168535,0.0003929378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7418483,"threshold_uncertainty_score":0.9970174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1350363999823951,"score_gpt":0.378014440172851,"score_spread":0.2429780401904559,"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."}}