{"id":"W4404023725","doi":"10.3390/cancers16213716","title":"Progress in Precision Medicine for Head and Neck Cancer","year":2024,"lang":"en","type":"review","venue":"Cancers","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"CancerCare Manitoba; University of Guelph; Research Institute in Oncology and Hematology; University of Manitoba","funders":"Fundação para a Ciência e a Tecnologia","keywords":"microRNA; Precision medicine; MMP1; Head and neck cancer; Medicine; Head and neck; Gene; Bioinformatics; Computational biology; Cancer; Cancer research; Oncology; Internal medicine; Biology; Pathology; Genetics; Gene expression; Surgery","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":[0.002018283,0.0009541397,0.001420918,0.002245279,0.0004193677,0.001594948,0.0009507042,0.001857485,0.004142208],"category_scores_gemma":[0.001956982,0.0003149522,0.0009470314,0.001700625,0.001108341,0.002058274,0.001196614,0.003709931,0.002077473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00151173,"about_ca_system_score_gemma":0.002150069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001297781,"about_ca_topic_score_gemma":0.001761013,"domain_scores_codex":[0.9993678,0.0001657074,0.000061325,0.0001098491,0.0002399536,0.00005539164],"domain_scores_gemma":[0.9986476,0.0008420911,0.00007927907,0.00005898783,0.0002995147,0.00007253746],"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":[0.00007537127,0.00005786764,0.0002066328,0.01332146,0.0001916268,0.0002000143,0.00008878975,0.0006121036,0.001988135,0.01978662,0.04817124,0.9153002],"study_design_scores_gemma":[0.00001441256,0.00007465857,0.00034915,0.001888853,0.00007183926,0.0005914177,0.00003842896,0.0001231664,0.0005134412,0.006492576,0.9898223,0.00001984161],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006729911,0.9968463,0.0005827067,0.0009331424,0.0005136871,0.000005050197,0.00001879503,0.0000156517,0.001017428],"genre_scores_gemma":[0.001047387,0.9957274,0.0008031997,0.0008643025,0.0006638169,0.00001310222,0.00004915209,0.000004824286,0.0008268338],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004142208,"threshold_uncertainty_score":0.01385701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05346057248229868,"score_gpt":0.4134668526527447,"score_spread":0.360006280170446,"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."}}