{"id":"W566021556","doi":"10.1007/978-1-4613-0147-9_11","title":"Some Statistical Aspects of Magnetoencephalography","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in statistics","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Magnetoencephalography; Inverse problem; Computer science; Statistical physics; Nonlinear system; Simplicity; Noise (video); Algorithm; Dipole; Mathematics; Artificial intelligence; Physics; Mathematical analysis; Psychology; Electroencephalography; Image (mathematics)","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":[0.0001292876,0.0004979581,0.000737321,0.0004352446,0.00009247715,0.0000271823,0.0002984959,0.0003336285,0.0007320339],"category_scores_gemma":[0.01251461,0.0004941839,0.00009669302,0.0001686642,0.0008852766,0.00006472442,0.0001440702,0.0008368776,0.00006852639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001122952,"about_ca_system_score_gemma":0.0001407355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003138931,"about_ca_topic_score_gemma":0.0002746468,"domain_scores_codex":[0.9973776,0.00007663336,0.0005606926,0.0008390002,0.0007287137,0.0004173689],"domain_scores_gemma":[0.9776924,0.02137947,0.0003033865,0.0004264818,0.0001128702,0.00008534588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006897961,0.000057925,0.0001103916,0.0001479341,0.00002768098,0.0005615336,0.00007077578,0.0003335609,0.0006119926,0.9819695,0.002629127,0.01341065],"study_design_scores_gemma":[0.0002664538,0.0003711756,0.000353591,0.0001117713,0.0000573304,0.00004456179,9.944137e-7,0.0001969799,0.001210995,0.9676633,0.02927169,0.0004511349],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00009010242,0.002589268,0.5433222,0.001344548,0.002434061,0.001157686,0.01332368,0.0001953073,0.4355431],"genre_scores_gemma":[0.7428802,0.01174306,0.1756453,0.02395451,0.004714196,0.000180405,0.001052998,0.00114663,0.0386827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.74279,"threshold_uncertainty_score":0.999751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03151330268191886,"score_gpt":0.2728391427682101,"score_spread":0.2413258400862912,"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."}}