{"id":"W2011334778","doi":"10.1002/hbm.20991","title":"Mapping reliability in multicenter MRI: Voxel‐based morphometry and cortical thickness","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Mental Health; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Reproducibility; Statistical power; Multicenter study; Voxel; Reliability (semiconductor); Nuclear medicine; Computer science; Artificial intelligence; Pattern recognition (psychology); Statistics; Medicine; Mathematics; Pathology; Power (physics); Randomized controlled trial","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001390064,0.0002465263,0.0003153325,0.000391795,0.0006244318,0.000109057,0.0002493229,0.0001401098,0.000142639],"category_scores_gemma":[0.02239024,0.0002506054,0.00007306017,0.0005746618,0.0005635874,0.0002579746,0.0002683134,0.001010327,0.00003523335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007491032,"about_ca_system_score_gemma":0.00003895323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005786313,"about_ca_topic_score_gemma":0.000173055,"domain_scores_codex":[0.9974687,0.0003320682,0.0004046681,0.0009349145,0.0003738549,0.0004858218],"domain_scores_gemma":[0.9901798,0.009064225,0.0001040172,0.0004724913,0.00006294534,0.0001165024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002388712,0.0001455802,0.13094,0.0001045489,0.000004078313,0.00003159414,0.0008346944,0.00004382529,0.8648248,0.002049218,0.0008245869,0.0001731919],"study_design_scores_gemma":[0.00136319,0.00004223563,0.9750479,0.0001042729,0.000003675861,0.00001839974,0.0003788038,0.009540405,0.004068158,0.002128663,0.006910437,0.0003938912],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834234,0.00001221547,0.002416342,0.01201253,0.0004947705,0.0004175978,0.000007323359,0.0001520094,0.001063773],"genre_scores_gemma":[0.9905495,0.00000139596,0.001170291,0.007881051,0.0001389017,0.00005341336,0.000002225726,0.00002649668,0.0001766992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8607566,"threshold_uncertainty_score":0.9999946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0413836798739593,"score_gpt":0.2834814504208738,"score_spread":0.2420977705469145,"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."}}