{"id":"W2121352103","doi":"10.1093/jnci/djq385","title":"Re: Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use?","year":2010,"lang":"en","type":"letter","venue":"JNCI Journal of the National Cancer Institute","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Ontario Institute for Cancer Research","funders":"","keywords":"Lung cancer; Gene expression; Computational biology; Cancer; Medicine; Gene; Oncology; Expression (computer science); Cancer research; Internal medicine; Biology; Bioinformatics; Computer science; Genetics","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":[0.006111985,0.0009215465,0.002829914,0.0008324463,0.00166022,0.003236288,0.002202452,0.02769101,0.006666562],"category_scores_gemma":[0.03095302,0.000648762,0.00108164,0.0008112654,0.001944674,0.003974691,0.001181873,0.03126994,0.01125375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002578004,"about_ca_system_score_gemma":0.002934081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002840645,"about_ca_topic_score_gemma":0.00699668,"domain_scores_codex":[0.9968413,0.001017369,0.0005978597,0.0002979909,0.001013914,0.0002315889],"domain_scores_gemma":[0.980481,0.01066238,0.0007143412,0.0008151904,0.005594651,0.001732388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001626803,0.00004158436,0.00132615,0.00008290191,0.00002227443,0.0007237784,0.00004240463,0.00007543425,0.0004397837,0.001331117,0.9664601,0.02929169],"study_design_scores_gemma":[0.0004357586,0.0002158713,0.004988163,0.0005255528,0.0001194844,0.003303354,0.0003986582,0.00195093,0.0008866386,0.01502445,0.9720041,0.0001469807],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003717347,0.002309014,0.0003204043,0.9781067,0.0167133,0.00001411649,0.0001135554,0.00006309272,0.001988077],"genre_scores_gemma":[0.006553126,0.003937351,0.001655594,0.8777373,0.09702806,0.00008901644,0.0002286922,0.00006409927,0.01270665],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02769101,"threshold_uncertainty_score":0.0323236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1168513198355868,"score_gpt":0.4364818628233884,"score_spread":0.3196305429878015,"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."}}