{"id":"W4409595737","doi":"10.1016/j.oraloncology.2025.107304","title":"Development of a patient reported outcomes based machine learning model to predict recurrences in head and neck cancer","year":2025,"lang":"en","type":"article","venue":"Oral Oncology","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre","funders":"Sophiahemmet Högskola; Princess Margaret Cancer Foundation","keywords":"Head and neck cancer; Medicine; Head and neck; Head (geology); Cancer; Medical physics; Oncology; Computer science; Surgery; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002034031,0.0006548698,0.0007480069,0.0009893186,0.0002946269,0.00098634,0.00108127,0.0007472432,0.001431108],"category_scores_gemma":[0.004910382,0.0002909575,0.000843311,0.0005081326,0.0001447844,0.0006342696,0.0004658221,0.001532361,0.0006005401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006889888,"about_ca_system_score_gemma":0.001141833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01023078,"about_ca_topic_score_gemma":0.009473105,"domain_scores_codex":[0.9996101,0.0001341341,0.0000451294,0.00008935596,0.00006743179,0.00005376418],"domain_scores_gemma":[0.9976502,0.00162248,0.0001473901,0.00006946988,0.0004319981,0.00007851657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006463141,0.002046276,0.2309719,0.0001326226,0.0008314864,0.0003813883,0.0001341168,0.4282758,0.00188267,0.001728677,0.00905154,0.3239172],"study_design_scores_gemma":[0.00001749825,0.0001158123,0.006761646,0.00001193484,0.00006524626,0.00004149085,0.00001946199,0.9914327,0.0004048793,0.0006931642,0.0004270518,0.000009158986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6724397,0.001075835,0.3124634,0.003214798,0.0003379163,0.0004169206,0.004430204,0.001735381,0.003885792],"genre_scores_gemma":[0.9533387,0.0002560866,0.04018788,0.00022535,0.00009867002,0.000254374,0.003081295,0.00003399547,0.002523575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01023078,"threshold_uncertainty_score":0.02034247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06215681418154072,"score_gpt":0.3937863657484333,"score_spread":0.3316295515668926,"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."}}