{"id":"W4312114052","doi":"10.7554/elife.73288","title":"Predicting progression-free survival after systemic therapy in advanced head and neck cancer: Bayesian regression and model development","year":2022,"lang":"en","type":"article","venue":"eLife","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Guy's and St Thomas' NHS Foundation Trust; Engineering and Physical Sciences Research Council; Institute of Cancer Research; Medical Research Council; Daiichi Sankyo Europe; Rosetrees Trust; University College London Hospitals NHS Foundation Trust; King's Health Partners; University College London; King's College London; Cancer Research Institute; Department of Health and Social Care; Innovative Health Initiative; National Institute for Health and Care Research; Imperial Experimental Cancer Medicine Centre; Cancer Research UK","keywords":"Oncology; Internal medicine; Medicine; Head and neck squamous-cell carcinoma; Covariate; Cetuximab; Proportional hazards model; Cohort; Head and neck cancer; Cancer; Colorectal cancer; Machine learning","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":[0.007386693,0.001088505,0.001348028,0.0009869256,0.0004173914,0.001084056,0.001297298,0.001078221,0.001184556],"category_scores_gemma":[0.01133752,0.0007200433,0.001373277,0.0005452727,0.0005743057,0.0006511906,0.00115839,0.001940198,0.0003250594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0015268,"about_ca_system_score_gemma":0.001609415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02290866,"about_ca_topic_score_gemma":0.01222738,"domain_scores_codex":[0.9984148,0.001070962,0.00005338219,0.0002249202,0.0001209165,0.0001149622],"domain_scores_gemma":[0.9918604,0.00696563,0.0005226689,0.0001226267,0.0004006379,0.0001281119],"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":[0.0002052555,0.00007222428,0.008523164,0.00004425715,0.000119052,0.00003187546,0.00003707371,0.974678,0.0002976487,0.001437728,0.0003917906,0.01416188],"study_design_scores_gemma":[0.000008903023,0.00002323493,0.00059239,0.000005170135,0.000009072137,0.000005791231,0.000002891864,0.9984004,0.00004347285,0.0008385996,0.00006621199,0.000003901357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4083563,0.001984694,0.5834183,0.00205624,0.00005717411,0.0003368645,0.001033433,0.0007009032,0.002056118],"genre_scores_gemma":[0.9310387,0.0007308688,0.06406631,0.0002311126,0.00007693183,0.0005132588,0.00142885,0.00006630389,0.001847669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02290866,"threshold_uncertainty_score":0.04555064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02230101066856162,"score_gpt":0.3189407816257751,"score_spread":0.2966397709572135,"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."}}