{"id":"W4391883953","doi":"10.1002/mp.16972","title":"RADCURE: An open‐source head and neck cancer CT dataset for clinical radiation therapy insights","year":2024,"lang":"en","type":"article","venue":"Medical Physics","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; Artificial Intelligence in Medicine (Canada); Princess Margaret Cancer Centre","funders":"","keywords":"Head and neck cancer; Radiation therapy; Medicine; Head and neck; Radiology; 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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001002909,0.001773393,0.001063739,0.002752285,0.0004414151,0.001499743,0.003453563,0.00219008,0.01693799],"category_scores_gemma":[0.005848477,0.000630949,0.001511531,0.003640175,0.0003681883,0.0009205578,0.001810855,0.001534336,0.02006656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001477866,"about_ca_system_score_gemma":0.002164264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01475168,"about_ca_topic_score_gemma":0.02850108,"domain_scores_codex":[0.9992969,0.0001238711,0.0001028618,0.0002059851,0.00019003,0.00008046516],"domain_scores_gemma":[0.9986395,0.0003704847,0.0001764418,0.0003546895,0.0003410323,0.0001177666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00051183,0.0001704236,0.01090891,0.001708782,0.0002246358,0.0003871614,0.0001232504,0.008504922,0.001661491,0.001411943,0.938486,0.03590066],"study_design_scores_gemma":[0.0008049978,0.0001503017,0.04033905,0.0006848073,0.0001854304,0.001325396,0.0002802125,0.02773592,0.005117268,0.005110216,0.9180543,0.0002121644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004263466,0.0005900309,0.00329921,0.0003679146,0.00007876976,0.0002067626,0.9835252,0.005538933,0.002129773],"genre_scores_gemma":[0.008065582,0.0002309874,0.005689206,0.0001349278,0.00003216684,0.0004341464,0.9842764,0.0004799082,0.0006565722],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9965464,"threshold_uncertainty_score":0.05666327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1225048021030885,"score_gpt":0.4638454143419308,"score_spread":0.3413406122388424,"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."}}