{"id":"W2898201119","doi":"10.1002/mrm.27527","title":"A framework for Fourier‐decomposition free‐breathing pulmonary <sup>1</sup>H MRI ventilation measurements","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Reproducibility; Segmentation; Image registration; Correlation coefficient; Coefficient of variation; Nuclear medicine; Similarity (geometry); Fiducial marker; Artificial intelligence; Ventilation (architecture); Pearson product-moment correlation coefficient; Concordance correlation coefficient; Mathematics; Computer science; Biomedical engineering; Pattern recognition (psychology); Medicine; Physics; Statistics; Image (mathematics)","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":[0.0007222113,0.0002048037,0.0003280826,0.0001284769,0.0001895247,0.00002782502,0.0003671281,0.00007988543,0.0007058013],"category_scores_gemma":[0.00007997866,0.0001873457,0.00007178956,0.000332286,0.0002349494,0.000146662,0.0000864293,0.0002819707,0.00003743504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001151054,"about_ca_system_score_gemma":0.00009042497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002376179,"about_ca_topic_score_gemma":0.000002806102,"domain_scores_codex":[0.998068,0.00008635177,0.0004255283,0.0004207131,0.0005249407,0.0004744047],"domain_scores_gemma":[0.9989319,0.0002115035,0.0000999828,0.0004834083,0.0001663413,0.000106819],"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":[0.0005114869,0.0002879013,0.071845,0.00006978118,0.00003139946,0.00001017525,0.003455966,0.0001147829,0.001599006,0.01879533,0.00803453,0.8952447],"study_design_scores_gemma":[0.003693073,0.0005096899,0.01985207,0.001402657,0.00006170689,0.000004852712,0.001354129,0.4824462,0.001506981,0.4640686,0.02460774,0.000492302],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3941949,0.00319007,0.570789,0.003670234,0.0005049545,0.002155081,0.00006712967,0.00008052298,0.02534808],"genre_scores_gemma":[0.985862,0.00002160212,0.01118506,0.0001655025,0.001913668,0.0002014838,0.00006590148,0.00003437089,0.000550397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8947523,"threshold_uncertainty_score":0.7728029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0400612784466083,"score_gpt":0.3417050441532384,"score_spread":0.3016437657066302,"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."}}