{"id":"W6893683668","doi":"10.5281/zenodo.4573154","title":"HEad and neCK TumOR segmentation and outcome prediction in PET/CT images","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radiomics; Segmentation; Head and neck; Radiation treatment planning; Positron emission tomography; Radiation therapy; Head and neck cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003167144,0.0001470923,0.0001588011,0.0004081647,0.0004368866,0.0007869651,0.0003417891,0.00002031425,0.003463776],"category_scores_gemma":[0.00008948499,0.0001590906,0.00002584864,0.0004327157,0.00006978364,0.0002356614,0.0006782972,0.0002088944,0.0003966466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007604012,"about_ca_system_score_gemma":0.000002936301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006726782,"about_ca_topic_score_gemma":0.000005065083,"domain_scores_codex":[0.9985499,0.000250134,0.000231833,0.0005125941,0.0002598149,0.0001957242],"domain_scores_gemma":[0.9994221,0.000008162477,0.0001111051,0.0002675996,0.00009341426,0.00009765908],"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":[0.00005341233,0.0006262224,0.001526258,0.001367078,0.0001594079,0.0008850038,0.001570925,0.00002942803,0.00815531,0.008071504,0.650009,0.3275465],"study_design_scores_gemma":[0.001102753,0.0002826779,0.01210885,0.0002386163,0.00001434661,0.001473099,0.000241804,0.002994665,0.000198845,0.0001229915,0.980893,0.0003284211],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.05256897,0.001828098,0.06694807,0.001720254,0.001352042,0.002404722,0.0004423109,0.004489152,0.8682464],"genre_scores_gemma":[0.4545265,0.002303413,0.01496305,0.001139023,0.0007804403,0.000001268736,0.004608249,0.01097439,0.5107037],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4019575,"threshold_uncertainty_score":0.9974472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0338681134965464,"score_gpt":0.2884823471455012,"score_spread":0.2546142336489548,"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."}}