{"id":"W1987249453","doi":"10.1007/s10669-011-9309-x","title":"Evolution of hybrid functional imaging in bioelectromagnetics research","year":2011,"lang":"en","type":"article","venue":"The Environmentalist","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Bioelectromagnetics; Electroencephalography; Computer science; Field (mathematics); Functional magnetic resonance imaging; Physics of magnetic resonance imaging; Artificial intelligence; Neuroscience; Electromagnetic field; Magnetic resonance imaging; Physics; Biology; Mathematics; Medicine; Relaxometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0001942749,0.0000408269,0.00005491128,0.00005171172,0.0000510032,0.00000102737,0.0000588372,0.000009020119,0.0002459904],"category_scores_gemma":[0.000006899426,0.0000310947,0.00002083034,0.00009527931,0.0002990119,0.00002269459,0.00004343264,0.0001222461,0.00001865236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001610831,"about_ca_system_score_gemma":0.00001078477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002446806,"about_ca_topic_score_gemma":0.000004464218,"domain_scores_codex":[0.9995033,0.00002292515,0.000109836,0.00009657157,0.0001492896,0.0001181179],"domain_scores_gemma":[0.9997146,0.00001920092,0.00002554277,0.0002124922,0.000006664344,0.00002151544],"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":[0.0002228548,0.0007569952,0.0748568,0.00001738616,0.000006029192,0.00001736446,0.0003574841,0.00004815468,0.8810817,0.02688935,0.002777309,0.01296855],"study_design_scores_gemma":[0.0008287862,0.0004840623,0.5830101,0.00005430559,0.00003255947,0.0001761463,0.001190066,0.002120721,0.3557301,0.05274468,0.003486563,0.0001419268],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495425,0.0004518196,0.03637808,0.0006969162,0.00001614229,0.0004684377,0.00001039222,0.00002582207,0.01240988],"genre_scores_gemma":[0.9948856,0.00007448036,0.00460573,0.00003623046,0.00002296336,0.00002713264,0.00001141698,0.000007866406,0.0003285639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5253516,"threshold_uncertainty_score":0.2693422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06615438229515462,"score_gpt":0.3172140367990782,"score_spread":0.2510596545039236,"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."}}