{"id":"W1973452909","doi":"10.1118/1.2961650","title":"SU‐GG‐J‐100: Guidelines for Optimizing Image Quality and Minimizing Technique‐Specific Uncertainties in 3D Ultrasound Imaging for Online Image Guided Radiotherapy of the Prostate","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Image-guided radiation therapy; Visualization; Ultrasound; Prostate; Image quality; Medicine; Medical physics; Medical imaging; Modality (human–computer interaction); Prostate gland; Computer science; Radiology; Nuclear medicine; Artificial intelligence; Image (mathematics); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02133023,0.002432097,0.001845259,0.007789022,0.001003457,0.003304328,0.005622902,0.004925606,0.006041045],"category_scores_gemma":[0.03187826,0.002345344,0.001532697,0.003383287,0.001463836,0.00191141,0.001946046,0.002721247,0.006390607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001224755,"about_ca_system_score_gemma":0.002977019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003135767,"about_ca_topic_score_gemma":0.008325835,"domain_scores_codex":[0.9882409,0.004651068,0.002034564,0.0003981334,0.004402166,0.0002732787],"domain_scores_gemma":[0.9792621,0.008445925,0.002149309,0.001438599,0.008198255,0.0005058388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001214224,0.0006789549,0.01037527,0.005517659,0.0003040776,0.001016835,0.0009135235,0.01031436,0.0640263,0.006564002,0.1185795,0.7804952],"study_design_scores_gemma":[0.0007930318,0.002558862,0.07472569,0.006918877,0.0007634365,0.01438649,0.0008069065,0.07434291,0.1817863,0.01489857,0.6269174,0.00110141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03485008,0.07407483,0.8268649,0.005920982,0.001204983,0.003276602,0.004760745,0.02051609,0.02853088],"genre_scores_gemma":[0.03272918,0.008481137,0.9440534,0.0007867932,0.0001160592,0.001700397,0.002975232,0.004130616,0.005027211],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02133023,"threshold_uncertainty_score":0.1128064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05876709251329833,"score_gpt":0.3798479559787716,"score_spread":0.3210808634654733,"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."}}