{"id":"W4403420021","doi":"10.1016/j.jtho.2024.09.107","title":"MA02.12 UC Screen California: A Statewide Participatory Informatics Approach to Lung Cancer Screening","year":2024,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Lung cancer; Informatics; Citizen journalism; Lung cancer screening; Health informatics; Medical physics; Oncology; Nursing; World Wide Web; Public health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01035014,0.0004806638,0.0005807558,0.001920997,0.001575973,0.001538261,0.001549437,0.0005669548,0.01147486],"category_scores_gemma":[0.01411439,0.0006568425,0.0003911183,0.002899356,0.000332826,0.0004328176,0.001934669,0.0007151609,0.001763257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003088259,"about_ca_system_score_gemma":0.01274781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2241125,"about_ca_topic_score_gemma":0.3291489,"domain_scores_codex":[0.9931028,0.004928065,0.0002045779,0.0008859623,0.0005499315,0.0003287304],"domain_scores_gemma":[0.9933218,0.00236783,0.0007055137,0.0009286273,0.001767451,0.0009087019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001402729,0.002216462,0.4324338,0.0009011735,0.0004720762,0.0003363742,0.005500164,0.003272769,0.001337464,0.005939953,0.2948967,0.2512904],"study_design_scores_gemma":[0.00164159,0.001050177,0.7271362,0.0004273555,0.0003132975,0.0001458106,0.00277703,0.01477371,0.0008430707,0.002648911,0.2481471,0.00009576453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4368241,0.00196979,0.0881153,0.01429065,0.0005316777,0.05185255,0.1358826,0.007074319,0.263459],"genre_scores_gemma":[0.6782044,0.0009836361,0.1769495,0.002439394,0.0003898399,0.06583712,0.03008248,0.0003828638,0.04473082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2241125,"threshold_uncertainty_score":0.4456161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1738862808594694,"score_gpt":0.5420492569862319,"score_spread":0.3681629761267624,"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."}}