{"id":"W1980012993","doi":"10.1118/1.4734931","title":"SU‐E‐J‐95: Towards Optimum Boundary Conditions for Biomechanical Model Based Deformable Registration Using Intensity Based Image Matching for Prostate Correlative Pathology","year":2012,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Toronto General Hospital; University of Toronto","funders":"","keywords":"Image registration; Magnetic resonance imaging; Ex vivo; Artificial intelligence; Computer science; Computer vision; Nuclear medicine; Biomedical engineering; In vivo; Medicine; Radiology; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001594891,0.0006739233,0.0007444932,0.0008902767,0.0002909515,0.0009525017,0.001531806,0.001295985,0.003481371],"category_scores_gemma":[0.003215165,0.0006595448,0.0008041062,0.0004869614,0.0005044451,0.0006896727,0.001039815,0.0009382805,0.001546457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00054262,"about_ca_system_score_gemma":0.0009963955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001535148,"about_ca_topic_score_gemma":0.001985771,"domain_scores_codex":[0.9993219,0.0001364326,0.00003845006,0.00009914617,0.0003575381,0.00004654693],"domain_scores_gemma":[0.9994045,0.0002443161,0.00008944244,0.00009750259,0.0001344715,0.0000296639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005094077,0.0003882184,0.00141403,0.0004925985,0.0001021087,0.0001626405,0.0002189716,0.3833392,0.2641044,0.01209566,0.003370785,0.3338019],"study_design_scores_gemma":[0.00001984182,0.00007923011,0.0004455664,0.00001631285,0.00001173896,0.00007938009,0.00001501114,0.9611022,0.03433113,0.001548511,0.002326209,0.00002486279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0159374,0.0001667234,0.9811956,0.00005505782,0.00002609988,0.0000656785,0.00006167489,0.001348876,0.001142835],"genre_scores_gemma":[0.1999743,0.000184774,0.7964172,0.00009039428,0.00001674339,0.0002196469,0.0003955553,0.0009142476,0.001787123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003481371,"threshold_uncertainty_score":0.01164633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04456014033257506,"score_gpt":0.3391828645894667,"score_spread":0.2946227242568917,"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."}}