{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.02628911,0.0004561974,0.00152279,0.0001147626,0.008595403,0.0000624168,0.002092026,0.0002489461,0.0001566347],"category_scores_gemma":[0.02681442,0.0002418921,0.0001599772,0.004133147,0.0005796453,0.0001050778,0.0005553705,0.001869698,0.0001973081],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.0176027,"about_ca_system_score_gemma":0.3381152,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9817461,"about_ca_topic_score_gemma":0.9948167,"domain_scores_codex":[0.9662542,0.02661764,0.00312441,0.0007916505,0.001385149,0.001826969],"domain_scores_gemma":[0.971921,0.02434442,0.00229154,0.0005316679,0.0001082519,0.0008031407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006361859,0.000007516351,0.0002729875,0.00858863,0.000012107,0.00001393814,0.03653493,0.00000207539,2.327385e-9,0.01478136,0.5429955,0.3967274],"study_design_scores_gemma":[0.0002114549,0.00007989038,0.0002273537,0.001718711,0.0000146117,0.0000178981,0.0133668,0.00002589579,8.98476e-10,0.0003057876,0.983836,0.000195597],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.00003351947,0.3351025,0.00006023884,0.6548158,0.001171749,0.006666723,0.0004010991,0.00003979101,0.001708594],"genre_scores_gemma":[0.0002535757,0.5144052,0.0002068263,0.4823527,0.0008812682,0.001605128,0.00002236626,0.00002765964,0.0002452701],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.4408406,"threshold_uncertainty_score":0.9926953,"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."}}