{"id":"W4390618902","doi":"10.1016/j.suronc.2024.102033","title":"Improving accuracy in nodal staging of oral cancer: Proposal of a new system","year":2024,"lang":"en","type":"article","venue":"Surgical Oncology","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Medicine; AJCC staging system; TNM staging system; Hazard ratio; Lymph node; Staging system; Oncology; Cohort; Cancer staging; Cancer; Stage (stratigraphy); Proportional hazards model; Survival analysis; Retrospective cohort study; Internal medicine; Basal cell; 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":[0.02048984,0.001002657,0.002125816,0.007098559,0.001982978,0.00494053,0.002949709,0.002124274,0.003088485],"category_scores_gemma":[0.03298466,0.0005965843,0.001862373,0.003134754,0.002443361,0.006347482,0.003502263,0.001830698,0.001011429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003153045,"about_ca_system_score_gemma":0.005602463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007964063,"about_ca_topic_score_gemma":0.009588975,"domain_scores_codex":[0.9929708,0.002699592,0.001142696,0.0009854354,0.001760076,0.0004414968],"domain_scores_gemma":[0.9742089,0.01188239,0.001614201,0.002207092,0.009301561,0.0007858591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001759837,0.000563236,0.3579482,0.001159345,0.0008458897,0.0002404161,0.001361374,0.008039461,0.007508278,0.02881181,0.01667345,0.5750887],"study_design_scores_gemma":[0.001598202,0.01098238,0.4979837,0.001573375,0.006832481,0.003650168,0.00383376,0.2709945,0.0178524,0.0957638,0.08793512,0.00100015],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3897237,0.02340706,0.5034176,0.03599023,0.00341026,0.002645052,0.003913548,0.004293255,0.03319947],"genre_scores_gemma":[0.622269,0.002414047,0.3674061,0.001796029,0.001449447,0.0009281621,0.001563991,0.0002085044,0.001964726],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02048984,"threshold_uncertainty_score":0.108362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03384610861087645,"score_gpt":0.3836053644779985,"score_spread":0.349759255867122,"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."}}