{"id":"W4296502312","doi":"10.1177/17588359221126151","title":"Plasma-first: accelerating lung cancer diagnosis and molecular profiling through liquid biopsy","year":2022,"lang":"en","type":"article","venue":"Therapeutic Advances in Medical Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Medicine; Cohort; Lung cancer; Internal medicine; Biopsy; Referral; Liquid biopsy; Cancer; Oncology; Clinical endpoint; Cohort study; Pathology; Clinical trial","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002405568,0.0005226244,0.0005898185,0.001168788,0.0003244906,0.001557415,0.00124754,0.0006786107,0.004911715],"category_scores_gemma":[0.002835554,0.0003809782,0.0004115359,0.0005703486,0.0003793245,0.001087234,0.001513242,0.0009345159,0.001846557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008510147,"about_ca_system_score_gemma":0.001058395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002158447,"about_ca_topic_score_gemma":0.002609528,"domain_scores_codex":[0.9986857,0.0004262348,0.00004487994,0.0003117449,0.0004408719,0.00009062643],"domain_scores_gemma":[0.9984888,0.0005636634,0.0003061234,0.0001438502,0.0003072302,0.0001903035],"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":[0.004769658,0.0007593093,0.1577941,0.001033474,0.000298968,0.0008222592,0.0002757567,0.003878026,0.1393374,0.001661923,0.02230358,0.6670656],"study_design_scores_gemma":[0.002332198,0.01349902,0.3424445,0.001132926,0.0008853119,0.02342436,0.0007722115,0.1644398,0.2998903,0.007192705,0.1435156,0.0004710765],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.6412547,0.0287048,0.2872308,0.006908712,0.001136064,0.001412714,0.004468762,0.01329855,0.01558499],"genre_scores_gemma":[0.8044612,0.00400676,0.1810537,0.001963253,0.0005900324,0.0005063285,0.003018059,0.0004118199,0.003988713],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004911715,"threshold_uncertainty_score":0.01643133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814273573074241,"score_gpt":0.3462831243431265,"score_spread":0.3281403886123841,"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."}}