{"id":"W4291002222","doi":"10.51731/cjht.2022.414","title":"An Overview of Comprehensive Genomic Profiling Technologies to Inform Cancer Care","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":"Profiling (computer programming); Emerging technologies; Clinical trial; Health care; Medicine; Data science; Computer science; Pathology; 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":[0.0001752006,0.0001336059,0.0003147656,0.0004076886,0.0003084744,0.00001714109,0.0006941276,0.0001075727,0.000009691732],"category_scores_gemma":[0.0001128106,0.0001366169,0.00007652896,0.000317256,0.0001298859,0.000006032627,0.0001767166,0.0002711206,5.001621e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004222424,"about_ca_system_score_gemma":0.003365005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003036305,"about_ca_topic_score_gemma":0.005243522,"domain_scores_codex":[0.9988374,0.00002848871,0.0004814019,0.0001729708,0.0001206023,0.0003591405],"domain_scores_gemma":[0.9988322,0.00001295721,0.0004079524,0.0003842041,0.0002905713,0.00007211284],"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":[0.0001240243,0.00003997312,0.01983994,0.0005512803,0.0001516191,0.00005063106,0.001269542,0.01718318,0.06563652,0.002982325,0.004717782,0.8874532],"study_design_scores_gemma":[0.0006158291,0.003638962,0.004774406,0.0001235134,0.00002521015,0.0001213938,0.06134687,0.00001925047,0.08381768,0.0008624636,0.8442621,0.0003923447],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7226253,0.2723053,0.00005784143,0.00403124,0.0003117782,0.000277417,0.0003437567,0.00002541193,0.00002190322],"genre_scores_gemma":[0.9920667,0.005888269,0.001357196,0.0005884724,0.00001401688,0.00004061953,0.00002185479,0.00001811428,0.000004742508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8870608,"threshold_uncertainty_score":0.5969375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0449433329869874,"score_gpt":0.3327109231258695,"score_spread":0.2877675901388821,"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."}}