{"id":"W2035003270","doi":"10.1016/j.jmir.2014.10.005","title":"An Investigation of the Feasibility and Utility of a Low-dose Cone-beam Computed Tomography Scan Protocol for Head and Neck Cancer Patients","year":2015,"lang":"en","type":"article","venue":"Journal of medical imaging and radiation sciences","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sunnybrook Health Science Centre","funders":"","keywords":"Imaging phantom; Cone beam computed tomography; Medicine; Nuclear medicine; Protocol (science); Image registration; Radiation therapy; Radiation treatment planning; Head and neck cancer; Medical physics; Radiology; Computed tomography; Computer science; Artificial intelligence; Image (mathematics)","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":[0.003085041,0.0002400468,0.0002275008,0.000459179,0.0004461792,0.000572614,0.0007246555,0.0004952467,0.002708557],"category_scores_gemma":[0.007883607,0.0001882993,0.0002645063,0.0003841467,0.0002929941,0.0004449032,0.0002895013,0.0004645107,0.0002837537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008903294,"about_ca_system_score_gemma":0.001750933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003799834,"about_ca_topic_score_gemma":0.005379179,"domain_scores_codex":[0.9989815,0.0005682205,0.00009632559,0.0001123898,0.0001850502,0.00005639004],"domain_scores_gemma":[0.9970915,0.001368703,0.0002695671,0.0002899227,0.0007659812,0.000214265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.05561045,0.02075553,0.4029411,0.0007638401,0.0002545512,0.001538466,0.001593619,0.01614887,0.130061,0.001441276,0.003086002,0.3658052],"study_design_scores_gemma":[0.005522177,0.1277125,0.7079737,0.0001923453,0.001113387,0.003551512,0.002120256,0.06092631,0.07583842,0.0007684709,0.0140871,0.0001937628],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886088,0.0002362213,0.004619192,0.0003881708,0.0000501534,0.001568244,0.0002356021,0.0000963656,0.004197151],"genre_scores_gemma":[0.984867,0.0001121728,0.01313443,0.0001849883,0.00002498068,0.0007814926,0.0001868764,0.00002587951,0.0006821346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003799834,"threshold_uncertainty_score":0.01631546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03740323663853706,"score_gpt":0.3875976208737621,"score_spread":0.350194384235225,"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."}}