{"id":"W3044868839","doi":"10.1136/bmjgh-2020-002672","title":"Integrating the social sciences into the COVID-19 response in Alberta, Canada","year":2020,"lang":"en","type":"review","venue":"BMJ Global Health","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Alberta; University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; Genome Canada; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; International Development Research Centre; Government of Canada","keywords":"Software deployment; Leverage (statistics); Public health; Public relations; Pandemic; Psychological intervention; Situated; Health care; Implementation; Coronavirus disease 2019 (COVID-19); Sociology; Political science; Medicine; Nursing; Engineering; Computer science; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01474598,0.0007468986,0.001134543,0.007148432,0.004578087,0.005322586,0.001695329,0.001670179,0.00311101],"category_scores_gemma":[0.01406051,0.0004382544,0.0008857218,0.008595756,0.00417173,0.001346212,0.003957348,0.002703997,0.000219647],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1113955,"about_ca_system_score_gemma":0.3999644,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9826961,"about_ca_topic_score_gemma":0.9900283,"domain_scores_codex":[0.9926258,0.002603828,0.0002941846,0.0002727486,0.003268913,0.000934611],"domain_scores_gemma":[0.9880691,0.005232283,0.0004544146,0.0002321627,0.004745923,0.001266136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001889336,0.0001492678,0.005259559,0.04777114,0.0004794858,0.0006183168,0.01257434,0.002341727,0.0007275012,0.05923782,0.04703245,0.8236194],"study_design_scores_gemma":[0.00008275736,0.0001770213,0.03131038,0.04385733,0.0004020685,0.0001781506,0.01232264,0.0004481575,0.0004587941,0.007072152,0.9035554,0.0001351534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004359261,0.9507475,0.0006488789,0.02209736,0.001178679,0.0002410835,0.0001882078,0.00002775953,0.0205112],"genre_scores_gemma":[0.08847356,0.8949811,0.004212419,0.008054418,0.0003705393,0.000253006,0.0001792736,0.00002194685,0.003453839],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8886045,"threshold_uncertainty_score":0.8082345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6583891356210727,"score_gpt":0.7532925870467938,"score_spread":0.0949034514257211,"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."}}