{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01122513,0.0008867863,0.001243506,0.005607882,0.0007711502,0.003868037,0.002943791,0.002089609,0.01558057],"category_scores_gemma":[0.01566131,0.0005385646,0.001300131,0.004496119,0.001089794,0.002680022,0.002880611,0.002479008,0.003442642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009413754,"about_ca_system_score_gemma":0.01347179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08118926,"about_ca_topic_score_gemma":0.1121612,"domain_scores_codex":[0.9929883,0.001429567,0.0003517106,0.0006849801,0.00392894,0.0006165836],"domain_scores_gemma":[0.9784534,0.007912383,0.001567899,0.0009823648,0.00970831,0.001375554],"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":[0.0007556746,0.0001788652,0.0118941,0.0039784,0.0001802847,0.00047817,0.000328568,0.002602879,0.006690968,0.03126115,0.09690374,0.8447472],"study_design_scores_gemma":[0.0002491539,0.0008436618,0.01509369,0.004851219,0.0005725935,0.002637916,0.0005750256,0.009926621,0.02147654,0.02733314,0.9161729,0.0002675857],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02957435,0.4857132,0.1789987,0.086099,0.005790757,0.002087982,0.02386493,0.005798507,0.1820725],"genre_scores_gemma":[0.2615861,0.3215846,0.2937931,0.03577747,0.002945577,0.001520049,0.01816909,0.0007007867,0.06392325],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.08118926,"threshold_uncertainty_score":0.1614334,"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."}}