{"id":"W2763898130","doi":"10.1002/hbm.23837","title":"Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; École de Technologie Supérieure; Hôpital du Sacré-Cœur de Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Academic Center for Education, Culture and Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Epilepsy Society; Fonds de Recherche du Québec - Santé; American Epilepsy Society","keywords":"Magnetoencephalography; Epilepsy; Yield (engineering); Nuclear magnetic resonance; Current (fluid); Magnetic resonance imaging; Neuroscience; Physics; Psychology; Medicine; Electroencephalography; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001564661,0.0002523372,0.0005772978,0.0002499187,0.000862024,0.0001267527,0.0006600986,0.00004986421,0.00004160215],"category_scores_gemma":[0.009115574,0.0002330349,0.0001778943,0.000262647,0.0008072408,0.0002761982,0.0004823645,0.00050755,0.000008916124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005007548,"about_ca_system_score_gemma":0.00003934055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001394439,"about_ca_topic_score_gemma":0.0001295855,"domain_scores_codex":[0.9971344,0.0004621202,0.000684244,0.0008169197,0.0004363048,0.0004660173],"domain_scores_gemma":[0.9921941,0.006228938,0.0006504772,0.0007621062,0.00007040245,0.00009399342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007000798,0.0003825841,0.9214251,0.0001113745,0.00001814656,0.00001823873,0.0005938552,0.0002015799,0.05510067,0.002253076,0.005663223,0.01416213],"study_design_scores_gemma":[0.0009684331,0.0001900695,0.9728443,0.0005214589,0.00001674919,0.000008861121,0.0004440868,0.003621526,0.001120535,0.001600849,0.01831675,0.0003463821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8284615,0.0003968265,0.1587842,0.008343943,0.0006792414,0.0007777174,0.00006666109,0.0001690471,0.00232082],"genre_scores_gemma":[0.9981648,0.00001128889,0.0009639703,0.0005735558,0.0001356282,0.00004151645,0.000004704113,0.00002179131,0.00008269677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1697033,"threshold_uncertainty_score":0.999231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1490601146706177,"score_gpt":0.4011750349731601,"score_spread":0.2521149203025423,"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."}}