{"id":"W2612729833","doi":"10.1093/annonc/mdx195.002","title":"Establishment of a diagnostic algorithm for ROS1 testing in Canada","year":2017,"lang":"en","type":"article","venue":"Annals of Oncology","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency; Institut universitaire de cardiologie et de pneumologie de Québec; Capital District Health Authority; University Health Network; CancerCare Manitoba; Health Sciences Centre; McGill University; Jewish General Hospital; Queen Elizabeth II Health Sciences Centre; University of Alberta; William Osler Health System; Princess Margaret Cancer Centre","funders":"","keywords":"ROS1; Crizotinib; Medicine; Immunohistochemistry; Lung cancer; Fluorescence in situ hybridization; Adenocarcinoma; Oncology; Fish <Actinopterygii>; Pathology; Internal medicine; Cancer; Algorithm; Biology; Gene; Computer science; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001690304,0.0004319559,0.0004294829,0.004147941,0.002207424,0.002185367,0.002084401,0.0008039755,0.004672033],"category_scores_gemma":[0.009812299,0.0003576272,0.000766016,0.003182574,0.0005986126,0.0006960881,0.00123941,0.001362299,0.0006958449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03503877,"about_ca_system_score_gemma":0.09794156,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.952522,"about_ca_topic_score_gemma":0.9638053,"domain_scores_codex":[0.9980044,0.0002426579,0.0002904065,0.0002832171,0.0006941019,0.0004852618],"domain_scores_gemma":[0.9927419,0.0005481853,0.0003775334,0.0001092766,0.005353232,0.0008699069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002584573,0.0001987839,0.5282215,0.0002894098,0.0001677666,0.002439944,0.0009577519,0.01248744,0.00160879,0.01528298,0.194846,0.2432412],"study_design_scores_gemma":[0.0002788741,0.0002201067,0.67727,0.001727864,0.0003671143,0.004390566,0.004704031,0.08451569,0.005382129,0.008340891,0.2125909,0.0002117917],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4720844,0.007942002,0.08487175,0.1331454,0.002215073,0.005557235,0.03807255,0.002490177,0.2536214],"genre_scores_gemma":[0.8793083,0.004218595,0.08466254,0.006936352,0.0002558255,0.0006452076,0.008423144,0.0003015917,0.01524847],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04747796,"threshold_uncertainty_score":0.2542253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08863118656972734,"score_gpt":0.4340051304527683,"score_spread":0.345373943883041,"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."}}