{"id":"W3171052867","doi":"","title":"A generalized SMT-based framework for Diusion MRI microstructural model estimation","year":2017,"lang":"en","type":"article","venue":"Medical Image Computing and Computer-Assisted Intervention","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Estimation; Estimation theory; Artificial intelligence; Algorithm; Materials science; Mathematical optimization; Applied mathematics; Mathematics; Engineering","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":[0.001442329,0.001160356,0.00119978,0.001255868,0.0004529853,0.00116002,0.002137543,0.001866868,0.00366678],"category_scores_gemma":[0.004097063,0.0008889523,0.001635436,0.001564486,0.0005283265,0.001194493,0.00181611,0.002053552,0.002042016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005007156,"about_ca_system_score_gemma":0.001566637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009066301,"about_ca_topic_score_gemma":0.01125623,"domain_scores_codex":[0.9994524,0.0001846676,0.0000391988,0.0001099177,0.0001693546,0.00004451509],"domain_scores_gemma":[0.9989638,0.0004293587,0.0001051847,0.0001250262,0.0003084496,0.00006819372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001758325,0.00009064433,0.0006551386,0.000221811,0.0001863871,0.0002103712,0.00006500127,0.6435903,0.01434504,0.02039815,0.005152949,0.3149083],"study_design_scores_gemma":[0.000003042966,0.00001063287,0.00005899487,0.00000490764,0.000008314363,0.00004085827,0.000002993567,0.9952591,0.0004595248,0.003370881,0.0007738251,0.000006792771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007876548,0.0001088274,0.9985548,0.00004546151,0.00001375397,0.00001431495,0.00005377682,0.0002238612,0.0001975108],"genre_scores_gemma":[0.0848059,0.0007418087,0.9087953,0.0002122921,0.0001473312,0.0002310553,0.001055181,0.0005225671,0.00348855],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009066301,"threshold_uncertainty_score":0.01802707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06444238563923192,"score_gpt":0.4156114653257816,"score_spread":0.3511690796865496,"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."}}