{"id":"W2899037941","doi":"10.2196/11073","title":"How to Optimize Health Messages About Cancer on Facebook: Mixed-Methods Study","year":2018,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Operationalization; Life expectancy; Solidarity; Theme (computing); Health communication; Health promotion; Cancer prevention; Social media; Psychology; Cancer; Medicine; Computer science; Public relations; World Wide Web; Public health; Political science; Nursing; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001882863,0.0001915089,0.0003582418,0.000135089,0.001070461,0.0001576315,0.0003895235,0.0001305819,0.00104459],"category_scores_gemma":[0.00102161,0.0001867724,0.00005615992,0.0007051381,0.0002598865,0.0001640343,0.00005061558,0.0002366012,0.0000929287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001788192,"about_ca_system_score_gemma":0.002014206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05128058,"about_ca_topic_score_gemma":0.09548101,"domain_scores_codex":[0.9964857,0.001296007,0.0002786093,0.0005151241,0.000654675,0.0007699421],"domain_scores_gemma":[0.9977558,0.0008093544,0.0002343616,0.0003308521,0.000316437,0.0005531547],"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":[0.00005196647,0.0001801462,0.0139777,0.00003052018,0.00002839832,4.460227e-7,0.2265286,0.0000165019,0.0000217978,0.000449299,0.04178135,0.7169333],"study_design_scores_gemma":[0.0003967314,0.0004853956,0.1298247,0.0001226779,0.00001321595,4.819825e-8,0.05262434,0.00001024539,0.0001877822,0.00009543771,0.815963,0.0002764131],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5985915,0.002788598,0.00110489,0.2920614,0.06481913,0.02788071,0.00006911733,0.0005809935,0.01210371],"genre_scores_gemma":[0.8852775,0.001530336,0.009437477,0.01155642,0.01769012,0.06784111,0.000003219687,0.00009930651,0.00656454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7741816,"threshold_uncertainty_score":0.9998686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1496515641765934,"score_gpt":0.5687355756485787,"score_spread":0.4190840114719853,"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."}}