{"id":"W2597163714","doi":"10.1007/s11548-017-1552-2","title":"Model-based registration of preprocedure MR and intraprocedure US of the lumbar spine","year":2017,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Anesthesia and Pain Management","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Paul's Hospital; Kingston General Hospital; B.C. Women's Hospital & Health Centre; Queen's University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Modality (human–computer interaction); Computer science; Magnetic resonance imaging; Lumbar; Modalities; Artificial intelligence; Facet (psychology); Facet joint; Metric (unit); Medicine; Computer vision; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007856479,0.0005281632,0.0007441442,0.001341469,0.0003190947,0.00204073,0.0006998525,0.001206847,0.001568296],"category_scores_gemma":[0.003438132,0.0005317889,0.0013329,0.0012079,0.0003240161,0.0007359564,0.0008515595,0.0009246379,0.001157322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005363851,"about_ca_system_score_gemma":0.001629006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007282645,"about_ca_topic_score_gemma":0.008004581,"domain_scores_codex":[0.9995426,0.0001138935,0.00003925779,0.00009431177,0.0001446092,0.0000653511],"domain_scores_gemma":[0.9994525,0.000167492,0.00008024179,0.000128794,0.0001449128,0.00002606486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001888119,0.0005953569,0.02027201,0.0005782588,0.0005241659,0.0007616924,0.0006140254,0.321861,0.1282993,0.005052352,0.008756419,0.5107974],"study_design_scores_gemma":[0.00005325098,0.0002884932,0.01075364,0.0000451949,0.0001806648,0.001154131,0.0001202731,0.9366076,0.04163807,0.003000729,0.006050434,0.0001076005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1684674,0.001295277,0.8204535,0.0004561255,0.0002439774,0.0001634541,0.000872494,0.004675529,0.003372279],"genre_scores_gemma":[0.8453823,0.0007894168,0.1479616,0.0002436941,0.00007740798,0.0001777514,0.001523557,0.0008287681,0.003015485],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007282645,"threshold_uncertainty_score":0.01448053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221316117225118,"score_gpt":0.2730484713942243,"score_spread":0.2508353102219731,"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."}}