{"id":"W4403214090","doi":"10.3390/curroncol31100449","title":"Implementation of Liquid Biopsy in Non-Small-Cell Lung Cancer: An Ontario Perspective","year":2024,"lang":"en","type":"article","venue":"Current Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Southlake Regional Health Center; Fluidigm (Canada); William Osler Health System; University of Ottawa; Ottawa Hospital; University Health Network; Health Sciences Centre; Juravinski Cancer Centre; Sunnybrook Health Science Centre; University of Toronto; McMaster University; London Health Sciences Centre","funders":"AstraZeneca Canada; AstraZeneca","keywords":"Liquid biopsy; Medicine; Reimbursement; Lung cancer; Biopsy; Profiling (computer programming); Biomarker; Oncology; Intensive care medicine; Internal medicine; Pathology; Bioinformatics; Cancer; Health care","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.00736919,0.0004770156,0.0003851829,0.0012172,0.004990763,0.005735348,0.002721007,0.002969465,0.007233391],"category_scores_gemma":[0.01689824,0.0004048308,0.0008920111,0.0018951,0.003328803,0.002117289,0.003255419,0.002138333,0.0006022083],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.14503,"about_ca_system_score_gemma":0.3693572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9737231,"about_ca_topic_score_gemma":0.9875613,"domain_scores_codex":[0.9888826,0.001804258,0.0005149852,0.0004863394,0.004643698,0.003668112],"domain_scores_gemma":[0.9614381,0.004107615,0.003349362,0.0006353035,0.01671189,0.01375781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0007418321,0.0007203143,0.249733,0.003023255,0.0002863945,0.002976077,0.008029584,0.004558763,0.005088645,0.0777638,0.3698324,0.2772458],"study_design_scores_gemma":[0.0002367904,0.0006327646,0.3455096,0.002738443,0.0002481262,0.0007442576,0.01357065,0.003067542,0.001470233,0.007137551,0.6243943,0.000249715],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07841189,0.01884099,0.003259555,0.8007283,0.002015542,0.000531993,0.002152453,0.0001759049,0.09388336],"genre_scores_gemma":[0.7661841,0.04533296,0.0135572,0.1291946,0.00238018,0.0004141718,0.001867781,0.0001931863,0.04087581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.14503,"threshold_uncertainty_score":0.9916441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02851001337604529,"score_gpt":0.3866814172502055,"score_spread":0.3581714038741602,"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."}}