{"id":"W4283765531","doi":"10.3390/jpm12071092","title":"Prediction of Incomplete Response of Primary Tumour Based on Clinical and Radiomics Features in Inoperable Head and Neck Cancers after Definitive Treatment","year":2022,"lang":"en","type":"article","venue":"Journal of Personalized Medicine","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Uniwersytet Medyczny im. Karola Marcinkowskiego w Poznaniu","keywords":"Medicine; Radiomics; Stage (stratigraphy); Head and neck; Radiation therapy; Radiology; Head and neck cancer; Radiation treatment planning; Retrospective cohort study; Internal medicine; 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":[0.001822708,0.0006832291,0.0008328378,0.001075787,0.0001738713,0.001319639,0.0005240411,0.0006891773,0.0006639194],"category_scores_gemma":[0.005015341,0.0002744225,0.001040908,0.0003841613,0.0001963943,0.0004288891,0.0004927966,0.0006417438,0.0003001662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000532679,"about_ca_system_score_gemma":0.0004722061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003583386,"about_ca_topic_score_gemma":0.003547929,"domain_scores_codex":[0.9994476,0.0002190032,0.0000510572,0.0001222134,0.00009411297,0.00006592752],"domain_scores_gemma":[0.9973403,0.00181237,0.0003551545,0.000138751,0.0002117196,0.0001417505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001321056,0.0003632851,0.767208,0.0001491894,0.0004023364,0.0003370449,0.0001269934,0.1628367,0.002497259,0.0001376767,0.001098249,0.06352215],"study_design_scores_gemma":[0.00003257723,0.00100348,0.2043692,0.0000691781,0.0003156637,0.0005920614,0.0001696854,0.7895268,0.002128064,0.000791483,0.0009556803,0.00004625462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827647,0.001584556,0.01330747,0.0003653984,0.00005319454,0.00005893638,0.0007803957,0.0001813624,0.0009041252],"genre_scores_gemma":[0.9972966,0.000169773,0.001563072,0.00003368459,0.00001814237,0.00001980887,0.0006577087,0.000009502062,0.0002315672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003583386,"threshold_uncertainty_score":0.009639502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03613203817168795,"score_gpt":0.3318843217355877,"score_spread":0.2957522835638997,"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."}}