{"id":"W4241015390","doi":"10.22215/etd/2013-10013","title":"Validation of the Bookend Method in Dynamic Contrast Enhanced MRI","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Reproducibility; Contrast (vision); Imaging phantom; Dynamic contrast; Dynamic contrast-enhanced MRI; Biomedical engineering; Nuclear medicine; Computer science; Artificial intelligence; Mathematics; Medicine; Magnetic resonance imaging; Radiology; Statistics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.007396125,0.0007363948,0.0005603616,0.001462567,0.0006695304,0.001486207,0.001873128,0.00131804,0.0027405],"category_scores_gemma":[0.02086699,0.0005419868,0.0002884914,0.0007829812,0.001169734,0.000900614,0.0009612811,0.0009796591,0.002772596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004753507,"about_ca_system_score_gemma":0.000884603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001728215,"about_ca_topic_score_gemma":0.002227135,"domain_scores_codex":[0.9959721,0.001542152,0.0001775471,0.0008203247,0.001361317,0.000126577],"domain_scores_gemma":[0.9847932,0.008538215,0.0005761449,0.001870858,0.004030931,0.0001907024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00167504,0.0003911369,0.005016307,0.0008047321,0.00009837134,0.0003397565,0.0005726385,0.006167951,0.7387981,0.002861492,0.001728802,0.2415457],"study_design_scores_gemma":[0.00009282253,0.00169692,0.007599168,0.0001024173,0.000113886,0.001408213,0.0002054009,0.03092855,0.9412833,0.0009687406,0.01546568,0.0001348079],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2039308,0.005218653,0.770523,0.0006827423,0.000675017,0.001358283,0.0009835198,0.002236279,0.0143917],"genre_scores_gemma":[0.2514832,0.003537739,0.7270834,0.0002856218,0.0001150846,0.0008498641,0.0007099381,0.0008161991,0.01511894],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007396125,"threshold_uncertainty_score":0.03911495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088613688997101,"score_gpt":0.3445111579486851,"score_spread":0.3336250210587141,"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."}}