{"id":"W2168637209","doi":"10.1186/1471-2261-13-24","title":"Multi-parametric MRI as an indirect evaluation tool of the mechanical properties of in-vitrocardiac tissues","year":2013,"lang":"en","type":"article","venue":"BMC Cardiovascular Disorders","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal","funders":"Réseau en Bio-Imagerie du Quebec","keywords":"Parametric statistics; Principal component analysis; Magnetic resonance imaging; Medicine; Angiology; Biomedical engineering; Linear regression; Fractional anisotropy; Diffusion MRI; Nuclear magnetic resonance; Nuclear medicine; Mathematics; Cardiology; Radiology; Statistics; Physics","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":[0.001342813,0.0005347026,0.0002770934,0.000666433,0.0001804336,0.0006211518,0.0003464593,0.0004887249,0.001179617],"category_scores_gemma":[0.001558762,0.0002306421,0.000331736,0.000482653,0.0005594965,0.0005755021,0.0003876577,0.0006921768,0.000349938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001457318,"about_ca_system_score_gemma":0.0002096327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001824882,"about_ca_topic_score_gemma":0.0004501266,"domain_scores_codex":[0.9993556,0.0002342228,0.00002846642,0.000115783,0.0002246739,0.0000412603],"domain_scores_gemma":[0.998876,0.0005233446,0.0002502245,0.0001110626,0.0001872506,0.00005209372],"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":[0.0001306713,0.00006463831,0.005029426,0.0002069322,0.00004105833,0.000113008,0.00008987323,0.00192546,0.9612364,0.0003043955,0.000143744,0.03071448],"study_design_scores_gemma":[0.00001365705,0.001401068,0.1062123,0.00006530443,0.0002161137,0.00261392,0.0002076245,0.04839767,0.8343824,0.001027637,0.005362787,0.00009959065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6160576,0.006406275,0.3720204,0.0003059746,0.0001028155,0.0001190811,0.000445486,0.0005315579,0.004010824],"genre_scores_gemma":[0.8993955,0.001358947,0.09779271,0.00006432595,0.00004699585,0.000144348,0.0001936972,0.00006556413,0.0009378853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001342813,"threshold_uncertainty_score":0.007101595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338726358668022,"score_gpt":0.2188352808547725,"score_spread":0.1954480172680923,"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."}}