{"id":"W3172219840","doi":"10.1007/978-3-030-63234-2_24","title":"Innovation and Advances in Precision Medicine in Head and Neck Cancer","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Salivary Gland Tumors Diagnosis and Treatment","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"American Association for Cancer Research","keywords":"HRAS; Druggability; Precision medicine; Head and neck squamous-cell carcinoma; Tumor microenvironment; Cancer research; Cancer; Medicine; Personalized medicine; Head and neck cancer; Bioinformatics; Oncology; Biology; Gene; Internal medicine; Pathology; KRAS; 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":[0.01994558,0.0008532355,0.001779131,0.002996128,0.0008341376,0.004391252,0.002130396,0.004235063,0.006658907],"category_scores_gemma":[0.0155031,0.0004103483,0.001727973,0.001817537,0.004772388,0.005249518,0.00333419,0.006512718,0.002210028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003451437,"about_ca_system_score_gemma":0.004778503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001735307,"about_ca_topic_score_gemma":0.00137554,"domain_scores_codex":[0.9941502,0.002643385,0.0003876054,0.0008790759,0.001515018,0.0004247233],"domain_scores_gemma":[0.9731938,0.01779699,0.001271312,0.002051711,0.004486565,0.001199705],"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":[0.0004160336,0.0001884332,0.002869246,0.006418059,0.0003227909,0.0006824779,0.0005368256,0.004410169,0.006472833,0.1832423,0.05506483,0.739376],"study_design_scores_gemma":[0.0001019998,0.0006126681,0.002784552,0.004245487,0.0001471001,0.001719153,0.000508467,0.003275069,0.004261768,0.2208069,0.7613614,0.0001755708],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003993419,0.8439835,0.0348963,0.09418135,0.005150608,0.00008981457,0.0003960398,0.0004088399,0.01690003],"genre_scores_gemma":[0.1192692,0.758383,0.05228858,0.04293874,0.0201437,0.0003011234,0.0007199482,0.000148323,0.005807342],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01994558,"threshold_uncertainty_score":0.1054835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.032063759438609,"score_gpt":0.3316401505540871,"score_spread":0.2995763911154781,"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."}}