{"id":"W4388828753","doi":"10.2196/46402","title":"Acceptance of Medical Artificial Intelligence in Skin Cancer Screening: Choice-Based Conjoint Survey","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Preprint; Conjoint analysis; Skin cancer; Cancer; Medicine; Computer science; World Wide Web; Preference; Mathematics; Internal medicine; Statistics","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":[0.009426863,0.0003065776,0.0005079589,0.001139395,0.0005431644,0.001011743,0.0003841353,0.0007512957,0.002222004],"category_scores_gemma":[0.01517432,0.0002385804,0.001177834,0.001280976,0.0008356352,0.0008349153,0.001056399,0.000893012,0.0003886854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008731905,"about_ca_system_score_gemma":0.0006085305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001500421,"about_ca_topic_score_gemma":0.001370016,"domain_scores_codex":[0.9924335,0.004977566,0.0007444766,0.0003837107,0.001081715,0.0003789991],"domain_scores_gemma":[0.9827031,0.009586423,0.004354833,0.0006732442,0.001232408,0.001449972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001365401,0.001468517,0.9800893,0.000136886,0.0002736414,0.0001132458,0.002753299,0.001252355,0.0005445015,0.0001826649,0.0002930418,0.01152714],"study_design_scores_gemma":[0.0001968209,0.005494951,0.9688554,0.00007519763,0.0001474634,0.0005265669,0.008415096,0.01326572,0.00124409,0.0006666225,0.001007615,0.0001043673],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991049,0.00004076051,0.0003604161,0.00005531178,0.000002801927,0.00009756803,0.000127908,0.00000251816,0.0002077679],"genre_scores_gemma":[0.9989471,0.00004332812,0.0007049699,0.00003967077,0.000003178212,0.0001081034,0.00007306054,0.000001112782,0.00007950525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009426863,"threshold_uncertainty_score":0.04985464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1925254959671268,"score_gpt":0.481041524265968,"score_spread":0.2885160282988412,"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."}}