{"id":"W2611207416","doi":"10.3747/co.24.3495","title":"Improving Molecular Testing and Personalized Medicine in Non-Small-Cell Lung Cancer in Ontario","year":2017,"lang":"en","type":"article","venue":"Current Oncology","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; Mount Sinai Hospital; Trillium Health Centre; University of Toronto; University Health Network; University of Ottawa; Princess Margaret Cancer Centre; Cancer Care Ontario; Barrie Urology Group; Women's College Hospital; McMaster University","funders":"Government of Ontario; Ontario Institute for Cancer Research; Cancer Care Ontario","keywords":"Medicine; Lung cancer; Context (archaeology); Medical physics; Personalized medicine; Cancer; Specialty; Pathology; Intensive care medicine; Bioinformatics; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001402489,0.0001207911,0.0003258736,0.0000831451,0.00008593397,0.00001127622,0.00006983233,0.00006754106,0.00009148612],"category_scores_gemma":[0.0001527655,0.00009903654,0.00002134163,0.00005164542,0.0001121592,0.00004931322,0.00005742141,0.0002774493,0.000001102963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041266,"about_ca_system_score_gemma":0.0006492814,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1254737,"about_ca_topic_score_gemma":0.1606139,"domain_scores_codex":[0.9992032,0.00002195774,0.0002075599,0.0002619304,0.00007931916,0.0002259994],"domain_scores_gemma":[0.9994634,0.00006770153,0.0001415467,0.0001785172,0.00005746097,0.00009133203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004641086,0.0001801817,0.9060019,0.0001539776,0.00002181461,0.0001810192,0.003186614,0.000005686469,0.00316517,0.0000196653,0.00004797555,0.08698963],"study_design_scores_gemma":[0.01338105,0.0003786879,0.9785712,0.0008156098,0.0003321228,0.00002485564,0.0003167029,0.00307223,0.0001295133,0.00004685115,0.002794581,0.0001366084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858929,0.00473365,0.00007872831,0.001125968,0.0005009988,0.0005503846,0.000002523724,0.000009287684,0.007105563],"genre_scores_gemma":[0.9984921,0.0001295855,0.0006505594,0.0001104857,0.00008499434,0.0001585841,0.000008189118,0.00001238,0.000353154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08685303,"threshold_uncertainty_score":0.8803498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06377226674774933,"score_gpt":0.4212138699542191,"score_spread":0.3574416032064697,"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."}}