{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005359671,0.00007171028,0.0002898088,0.0001036694,0.00005296406,0.00001418328,0.000155981,0.00007307233,0.000003730749],"category_scores_gemma":[0.0001335927,0.00004748285,0.0001162224,0.00002021687,0.0002488387,0.00007006489,0.00002493717,0.0001202517,4.827978e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001120569,"about_ca_system_score_gemma":0.000144833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003263732,"about_ca_topic_score_gemma":0.000002288647,"domain_scores_codex":[0.9992077,0.00005599948,0.0004035779,0.00008881064,0.0001854615,0.00005849453],"domain_scores_gemma":[0.9986615,0.00009116715,0.0007645702,0.0001482202,0.0002972183,0.0000373808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005470169,0.000157466,0.9770179,0.0002078753,0.000514683,0.00009163555,0.0001208017,0.00130815,0.002055879,0.0009380226,0.00386394,0.0131766],"study_design_scores_gemma":[0.0006209164,0.0001187187,0.9743108,0.0003477927,0.00007520321,0.001094055,0.000006933587,0.02238931,0.0003257669,0.0002807548,0.0003873798,0.00004236825],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782313,0.0003011396,0.01410841,0.006985886,0.0002063094,0.00006657091,8.371854e-7,0.000002416793,0.00009709891],"genre_scores_gemma":[0.9967766,0.0001524548,0.001900795,0.0009333253,0.0001749959,8.09798e-7,0.000002487116,0.000003978551,0.00005450979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02108116,"threshold_uncertainty_score":0.1936294,"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."}}