{"id":"W3211298881","doi":"","title":"The Brain Imaging Data Structure: a format for organizing and describing neuroimaging data","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroimaging; Computer science; Neuroinformatics; Artificial intelligence; Natural language processing; Cognitive science; Neuroscience; Data science; Psychology","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","open_science"],"consensus_categories":[],"category_scores_codex":[0.007061808,0.0001668483,0.0001395728,0.00007304523,0.001176471,0.0009936643,0.005391984,0.00003483282,0.000005378995],"category_scores_gemma":[0.008438719,0.0001163632,0.00002228687,0.0003120753,0.0001583503,0.001502904,0.00546925,0.0002124811,0.000003708239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004156811,"about_ca_system_score_gemma":0.0001463866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002896329,"about_ca_topic_score_gemma":0.0007852049,"domain_scores_codex":[0.9960628,0.002068758,0.0003333491,0.0008425589,0.0002672891,0.000425237],"domain_scores_gemma":[0.9871904,0.006148344,0.0002576091,0.00563517,0.0006346885,0.0001337719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003795978,0.00001772103,0.009679228,0.00004535226,0.000012303,0.000002018966,0.002585709,0.000001517269,0.005909193,0.0929543,0.003330013,0.8854588],"study_design_scores_gemma":[0.0007100767,4.32694e-7,0.004314626,0.000651652,0.00001263297,0.000100142,0.0001136886,0.8967791,0.003583901,0.005838774,0.08755413,0.0003408796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007451428,0.0009006883,0.8464649,0.144112,0.0001641408,0.0002741514,0.00007973269,0.0002170935,0.0003358356],"genre_scores_gemma":[0.7912619,0.0001516248,0.2073358,0.0006472353,0.00003296086,0.000008331519,0.0001436257,0.00003515804,0.0003833693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8967776,"threshold_uncertainty_score":0.9999893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04156215653252059,"score_gpt":0.2718281090498872,"score_spread":0.2302659525173666,"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."}}