{"id":"W1105888516","doi":"10.1016/j.jmr.2015.08.001","title":"Modeling T1 and T2 relaxation in bovine white matter","year":2015,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"","keywords":"Inversion (geology); Amplitude; Bandwidth (computing); Biological system; Nuclear magnetic resonance; Chemistry; Exponential function; Computational physics; Physics; Computer science; Optics; Mathematics; Mathematical analysis; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002159091,0.00005449919,0.0001455664,0.00007395374,0.00001116599,0.000006939903,0.00004043804,0.00003662629,0.00002774335],"category_scores_gemma":[0.00005125388,0.00004378285,0.0000205627,0.0001009078,0.00002034717,0.00008404097,0.00001554736,0.0001620092,0.000004798114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003946222,"about_ca_system_score_gemma":0.00003970182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006435821,"about_ca_topic_score_gemma":0.000003310939,"domain_scores_codex":[0.9993948,0.00001128002,0.0002899154,0.00007420615,0.0001452489,0.00008456576],"domain_scores_gemma":[0.9995801,0.00001037082,0.00009693063,0.0001008085,0.0001295111,0.00008226767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002510081,0.0007493746,0.4453849,0.0001863778,0.000009035385,0.0003827593,0.002628357,0.01495905,0.0056475,0.002171433,0.04451296,0.4808581],"study_design_scores_gemma":[0.008740556,0.00373705,0.4922087,0.001641109,0.0001098182,0.002911435,0.0006890765,0.2693147,0.0005072755,0.02548007,0.1941991,0.0004610953],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9154949,0.01632377,0.05585364,0.008892801,0.00004056343,0.0002264279,0.000001356371,0.0000126116,0.003153922],"genre_scores_gemma":[0.8984976,0.001206857,0.09806232,0.0005005965,0.0001127063,0.00000741783,7.687703e-7,0.00001217326,0.00159956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.480397,"threshold_uncertainty_score":0.1785413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02436341429047723,"score_gpt":0.2973319078792152,"score_spread":0.272968493588738,"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."}}