{"id":"W4224317855","doi":"10.51731/cjht.2022.315","title":"Emerging Multi-Cancer Early Detection Technologies","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Emerging technologies; Test (biology); Risk analysis (engineering); Cancer; Cancer screening; Clinical decision support system; Computer science; Medicine; Data science; Decision support system; Artificial intelligence; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003583765,0.0001185407,0.0001931464,0.0004037449,0.0005321127,0.00002772048,0.0004691739,0.0001138876,0.00001345167],"category_scores_gemma":[0.0003195094,0.0001236963,0.00008152102,0.0002694589,0.0001376602,0.000005616966,0.0001268338,0.0003980828,0.000001028491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003145757,"about_ca_system_score_gemma":0.001376232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003327178,"about_ca_topic_score_gemma":0.007304848,"domain_scores_codex":[0.9989297,0.00003593254,0.0003629373,0.0001756902,0.00010642,0.0003892914],"domain_scores_gemma":[0.9992233,0.00001143356,0.0003607833,0.0002561846,0.0001052733,0.00004305631],"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":[0.00003044614,0.00002639806,0.008203819,0.00002768521,0.00006525416,0.00003764944,0.0001599134,0.001193503,0.0144775,0.0001567139,0.004199804,0.9714213],"study_design_scores_gemma":[0.0006441916,0.001146338,0.003906461,0.00003099171,0.00001435353,0.0001787381,0.007417192,0.0000524989,0.04224605,0.0008935537,0.9432006,0.0002690541],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7980363,0.184247,0.003787268,0.01229608,0.001106189,0.0002592393,0.0001137226,0.0001150984,0.00003902684],"genre_scores_gemma":[0.9961566,0.002860737,0.0006033181,0.0002400391,0.00002021177,0.00004009101,0.000003826188,0.00001921,0.00005596012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9711522,"threshold_uncertainty_score":0.504419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01654254130916333,"score_gpt":0.2713022902753495,"score_spread":0.2547597489661861,"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."}}