{"id":"W2012879746","doi":"10.1503/cmaj.1041734","title":"Media Doctor prognosis for health journalism","year":2005,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Journalism; Public health; Medicine; News media; Family medicine; Selection (genetic algorithm); Alternative medicine; Medical education; Computer science; Media studies; Nursing; Pathology; Sociology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01400225,0.0003920532,0.0003840068,0.006206952,0.007131979,0.01112788,0.001200262,0.00520008,0.08250782],"category_scores_gemma":[0.1488795,0.0004679001,0.0004989433,0.004856756,0.002865666,0.01217111,0.004735839,0.005618715,0.01240596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006009344,"about_ca_system_score_gemma":0.01031528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00928994,"about_ca_topic_score_gemma":0.01429751,"domain_scores_codex":[0.9845501,0.005797577,0.001058698,0.0009057177,0.005028824,0.00265907],"domain_scores_gemma":[0.809763,0.05756551,0.04305584,0.008085089,0.03378236,0.04774829],"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":[0.0004491953,0.0002662143,0.08774634,0.0004313982,0.00003046371,0.0006165946,0.002852074,0.00004113818,0.0001460335,0.0285018,0.7772107,0.101708],"study_design_scores_gemma":[0.0001756338,0.0003571672,0.1539018,0.003118075,0.00009872689,0.002454925,0.01262952,0.0004875755,0.0006478744,0.01713155,0.8088652,0.0001320406],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.03297578,0.02105872,0.0005080398,0.8035926,0.01537421,0.00009832758,0.002726849,0.0002005267,0.123465],"genre_scores_gemma":[0.720399,0.0346898,0.002327019,0.1068902,0.04221501,0.0002590963,0.003506855,0.0004061705,0.08930673],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.08250782,"threshold_uncertainty_score":0.2760162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05799108668748533,"score_gpt":0.3965327664431761,"score_spread":0.3385416797556908,"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."}}