{"id":"W2807016910","doi":"10.1177/1179554918779581","title":"Precision Medicine in Head and Neck Cancer: Myth or Reality?","year":2018,"lang":"en","type":"article","venue":"Clinical Medicine Insights Oncology","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Head and neck squamous-cell carcinoma; Head and neck cancer; Precision medicine; Personalized medicine; Clinical trial; Medicine; Cancer; Medical physics; Bioinformatics; Internal medicine; Biology; Pathology","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":[0.03391386,0.0008827939,0.003067837,0.0016184,0.002025315,0.008296905,0.002406226,0.006114137,0.004760863],"category_scores_gemma":[0.0290677,0.0004321981,0.001164135,0.001426704,0.01884101,0.01721394,0.004917232,0.01292729,0.001350505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003758812,"about_ca_system_score_gemma":0.00765625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002059995,"about_ca_topic_score_gemma":0.002564465,"domain_scores_codex":[0.99184,0.004202039,0.0005116065,0.0008922056,0.002085903,0.0004682455],"domain_scores_gemma":[0.9582392,0.03088808,0.001649027,0.003463879,0.003999848,0.001760058],"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":[0.0005805933,0.000216478,0.004106073,0.007380959,0.0005790229,0.0005999546,0.001965549,0.002329868,0.002855928,0.3718351,0.1337889,0.4737615],"study_design_scores_gemma":[0.0001161863,0.0005741718,0.002267613,0.00592964,0.0002086322,0.001103302,0.002260874,0.001231758,0.001335723,0.6083223,0.3764793,0.0001705985],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002069698,0.4495307,0.01454225,0.5221533,0.005834956,0.00002797642,0.0002082544,0.0001568354,0.00547605],"genre_scores_gemma":[0.1116214,0.6713277,0.02965415,0.1596383,0.02416695,0.0002110089,0.000310345,0.0001285908,0.002941566],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03391386,"threshold_uncertainty_score":0.1793558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1975468661358666,"score_gpt":0.5213579928452671,"score_spread":0.3238111267094005,"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."}}