{"id":"W1969428076","doi":"10.1002/nbm.685","title":"Relaxation times and microstructures","year":2001,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Medical Research Council; Medical Research Council Canada; Fondation pour la Recherche Médicale","keywords":"Relaxation (psychology); Biological system; Sampling (signal processing); Focus (optics); Microstructure; Nuclear magnetic resonance; Principal component analysis; Sample (material); Component (thermodynamics); Computer science; Statistical physics; Chemistry; Computational physics; Materials science; Physics; Artificial intelligence; Optics; Thermodynamics; Chromatography; Biology; Neuroscience; Computer vision","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":[0.00007731026,0.0002019695,0.0005802988,0.0001748978,0.00004835156,0.00001764591,0.000109238,0.00009168455,0.0005370412],"category_scores_gemma":[0.000002790704,0.0001487422,0.00006299272,0.0004250147,0.00009124758,0.00002863028,0.00003239981,0.0002326548,0.00003727626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002560018,"about_ca_system_score_gemma":0.00004508721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001376313,"about_ca_topic_score_gemma":0.000003249817,"domain_scores_codex":[0.9991705,0.00002383857,0.0003163642,0.0002550944,0.00007473589,0.0001594137],"domain_scores_gemma":[0.9995145,0.00005353072,0.000175078,0.0001958424,0.00001093853,0.00005012372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[7.75985e-7,0.00002129528,0.0001723505,0.0004735673,0.00002581271,0.000001157391,0.00002566321,3.347318e-8,0.00001279377,0.004789335,0.002275852,0.9922014],"study_design_scores_gemma":[0.0001626983,0.0000166659,0.00006923122,0.001745144,0.0001111766,0.000006397122,0.00001842513,0.000001624899,0.00000547165,0.003247775,0.9944828,0.0001326462],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003543413,0.9922715,0.0001716257,0.0001060516,0.00006395212,0.0003580729,0.00005507343,0.00001577534,0.006922444],"genre_scores_gemma":[0.0001852809,0.99707,0.000320846,0.00002019408,0.0006159117,0.00007979913,0.0004999666,0.00002059102,0.001187393],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9922069,"threshold_uncertainty_score":0.6065531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613688730642915,"score_gpt":0.38465434477688,"score_spread":0.3685174574704509,"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."}}