{"id":"W2595526824","doi":"10.1117/12.2253879","title":"Registration pipeline for pulmonary free-breathing <sup>1</sup>H MRI ventilation measurements","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Intraclass correlation; Correlation coefficient; Nuclear medicine; Reproducibility; Coefficient of variation; Magnetic resonance imaging; Computer science; Nuclear magnetic resonance; Breathing; Image registration; Algorithm; Medicine; Physics; Artificial intelligence; Mathematics; Radiology; Statistics; Machine learning","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":[0.001577689,0.0008833273,0.0006206891,0.001085672,0.0004271185,0.001299843,0.001395607,0.001027702,0.005825422],"category_scores_gemma":[0.003365146,0.0007480497,0.001022913,0.0006588707,0.0003955188,0.0008761633,0.001322078,0.001363918,0.003533382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005447306,"about_ca_system_score_gemma":0.001573321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002182763,"about_ca_topic_score_gemma":0.003521219,"domain_scores_codex":[0.9992643,0.0001291492,0.00005717031,0.0002058933,0.0002832843,0.00006018709],"domain_scores_gemma":[0.9992906,0.0002311391,0.0001004719,0.0001291374,0.0002106838,0.00003792152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007480528,0.0002626788,0.005186149,0.0004823596,0.0001787842,0.0005111947,0.0004756292,0.06170724,0.3038962,0.005633389,0.008472387,0.6124459],"study_design_scores_gemma":[0.00007784317,0.0004262427,0.009610966,0.00005569205,0.0001026005,0.001349893,0.0001348946,0.791586,0.1701887,0.006025087,0.02034146,0.0001005378],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01015077,0.00009066789,0.9851233,0.000109888,0.00002531671,0.0001856947,0.0002135652,0.003475531,0.0006251871],"genre_scores_gemma":[0.079611,0.0001515963,0.9166209,0.0001026239,0.00002881885,0.0003732752,0.0007573661,0.0008335109,0.001520888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005825422,"threshold_uncertainty_score":0.01948798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695918483444232,"score_gpt":0.2724767516182864,"score_spread":0.2455175667838441,"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."}}