{"id":"W2014833813","doi":"10.1016/j.neuroimage.2015.04.028","title":"OMEGA: The Open MEG Archive","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":147,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Douglas Mental Health University Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Magnetoencephalography; Neuroimaging; Raw data; Open science; Computer science; Modalities; Scarcity; Data science; Psychology; Neuroscience; Electroencephalography; Sociology","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"],"consensus_categories":[],"category_scores_codex":[0.0003162001,0.0001137476,0.0001171684,0.00003461414,0.0002815313,0.0001943212,0.0008504865,0.00001378987,0.00001957914],"category_scores_gemma":[0.01430506,0.00007574051,0.00004023523,0.0002407348,0.0002355213,0.0003067178,0.000993478,0.0002086866,0.0004634853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002212264,"about_ca_system_score_gemma":0.00006369858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004207529,"about_ca_topic_score_gemma":0.00003309131,"domain_scores_codex":[0.9986278,0.0002970993,0.0001041844,0.0004371651,0.0003166343,0.0002170707],"domain_scores_gemma":[0.9956496,0.003742398,0.0000487098,0.0004431441,0.00003662577,0.00007950433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001857564,0.0001613916,0.001066675,0.000006476761,0.00000960543,0.0002018379,0.001171586,0.0001002676,0.1570958,0.03011592,0.8073063,0.002578269],"study_design_scores_gemma":[0.0008705911,0.000273383,0.01297219,0.000005530721,0.00001072997,0.0001260875,0.0001781692,0.000525948,0.04199015,0.02068252,0.9221452,0.0002194414],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2039607,0.00006317931,0.000560515,0.0930146,0.002247094,0.001186544,0.00007924881,0.0002783371,0.6986097],"genre_scores_gemma":[0.9685218,0.000007370839,0.0001224572,0.02746729,0.0001650994,0.00005465918,7.594925e-7,0.00002166242,0.003638859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7645611,"threshold_uncertainty_score":0.9939979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1488028642203066,"score_gpt":0.322989377948306,"score_spread":0.1741865137279994,"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."}}