{"id":"W2395228578","doi":"10.1186/s41199-016-0004-y","title":"Genomically personalized therapy in head and neck cancer","year":2016,"lang":"en","type":"review","venue":"Cancers of the Head & Neck","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Head and neck squamous-cell carcinoma; Head and neck cancer; Precision medicine; Personalized medicine; Malignancy; Clinical trial; Genomics; Oncology; Medicine; Cancer; Biomarker; Biomarker discovery; Bioinformatics; Internal medicine; Computational biology; Genome; Pathology; Biology; Proteomics; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021298,0.0005470293,0.003079027,0.0001448007,0.00009682195,0.00001167979,0.0003432537,0.0002975918,0.0002203491],"category_scores_gemma":[0.00006678065,0.000293132,0.0006182669,0.0003525295,0.0004746613,0.00004671733,0.0001461534,0.000496564,0.00001219553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001257258,"about_ca_system_score_gemma":0.002289917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001116805,"about_ca_topic_score_gemma":0.0009680605,"domain_scores_codex":[0.997628,0.0001400027,0.0007644804,0.0005980683,0.0003356696,0.0005337535],"domain_scores_gemma":[0.998533,0.0001528865,0.0003922506,0.0006423728,0.00009962337,0.000179829],"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":[0.0003386418,0.00004715359,0.001105714,0.00683291,0.0004379316,0.00001095394,0.0004185244,2.553141e-7,0.00003581389,0.00005272019,0.004440514,0.9862789],"study_design_scores_gemma":[0.003073821,0.0002875413,0.001674914,0.06258347,0.0002111448,0.0000267824,0.00002022074,0.000001335473,0.00001250352,0.00002692626,0.9317838,0.0002975202],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01280603,0.981476,4.163355e-7,0.001861172,0.0006219596,0.001552731,0.0001451293,0.00002542944,0.001511149],"genre_scores_gemma":[0.0002580623,0.9954615,0.00006927278,0.000949955,0.0004555068,0.0004149577,0.000005413729,0.00009081383,0.002294525],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9859813,"threshold_uncertainty_score":0.9999521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07357988163979376,"score_gpt":0.3827926424840124,"score_spread":0.3092127608442187,"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."}}