{"id":"W4402073119","doi":"10.1111/jon.13234","title":"Reliability of quantitative magnetic susceptibility imaging metrics for cerebral cortex and major subcortical structures","year":2024,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"NextGenerationEU; Ministero dell'Università e della Ricerca","keywords":"Medicine; Reliability (semiconductor); Neuroscience; Magnetic resonance imaging; Radiology","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":[0.009257686,0.0009234255,0.0005280325,0.001406977,0.0003076929,0.0007972023,0.000674322,0.0006024963,0.0006826301],"category_scores_gemma":[0.03394046,0.0003281942,0.00046452,0.0005809884,0.0008030756,0.0006384854,0.0006183396,0.0003615718,0.0002530174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002569199,"about_ca_system_score_gemma":0.0003156427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001140548,"about_ca_topic_score_gemma":0.001496564,"domain_scores_codex":[0.9951747,0.002151543,0.0005506256,0.00104158,0.0009491571,0.0001324658],"domain_scores_gemma":[0.9768237,0.01197495,0.003610107,0.002930582,0.004409782,0.0002508806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00456854,0.0002697648,0.55556,0.001311063,0.003155462,0.0003131846,0.002093391,0.02579405,0.2205258,0.001849257,0.002796153,0.1817634],"study_design_scores_gemma":[0.0001007111,0.001417834,0.8817503,0.0001484289,0.0005187229,0.001622214,0.0003785356,0.05692377,0.0518253,0.00275441,0.002405179,0.0001546386],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9089973,0.001890956,0.08572145,0.0001135563,0.00007847576,0.0001268098,0.0008047948,0.0006747093,0.001592058],"genre_scores_gemma":[0.989024,0.00008036077,0.01033108,0.00001977925,0.00002066297,0.00005761964,0.0002702628,0.00007661236,0.0001196333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009257686,"threshold_uncertainty_score":0.04895991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02785717138214888,"score_gpt":0.363087767566429,"score_spread":0.3352305961842801,"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."}}