{"id":"W3196738263","doi":"10.20944/preprints202109.0098.v1","title":"Neural Correlation of Faradarmani Consciousness Field Mind Mediation: A Comparative Functional Connectivity and Graph Analysis","year":2021,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Brain Mapping Laboratory","keywords":"Consciousness; Psychology; Electroencephalography; Graph theory; Cognitive psychology; Neuroscience; Functional connectivity; Graph; Power graph analysis; Mediation; Correlation; Path analysis (statistics); Frontal lobe; Artificial intelligence; Computer science; Mathematics; Machine learning; Theoretical computer science; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002237005,0.0001535258,0.0001431423,0.001169174,0.0002037758,0.0003419371,0.0001712617,0.0002038751,0.001967744],"category_scores_gemma":[0.001439984,0.00008443017,0.0002231881,0.0005900228,0.0003016533,0.000460373,0.0002428954,0.0001462921,0.0001065023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001583737,"about_ca_system_score_gemma":0.0001384476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001636961,"about_ca_topic_score_gemma":0.001769376,"domain_scores_codex":[0.9998829,0.00002506647,0.000006541523,0.0000414199,0.00002409593,0.00001991809],"domain_scores_gemma":[0.9997036,0.0001234815,0.00007579305,0.00002247447,0.00004651385,0.00002818035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00123611,0.0002543477,0.6396733,0.0004033866,0.0008064575,0.003148959,0.003628032,0.01041613,0.122772,0.01443369,0.002108163,0.2011194],"study_design_scores_gemma":[0.00001314394,0.0001373617,0.9784366,0.00001219316,0.00008405765,0.001264255,0.0006336358,0.01197829,0.00236631,0.004296878,0.0007541371,0.00002308913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920748,0.0002252825,0.005756909,0.00007834309,0.000006444508,0.0000181113,0.0001507002,0.00001866988,0.001670877],"genre_scores_gemma":[0.9983749,0.00008867077,0.001167778,0.00000554491,0.000007349218,0.000009284843,0.0001293028,0.00000308694,0.000214022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001967744,"threshold_uncertainty_score":0.006582797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1328457880393737,"score_gpt":0.3462985518584207,"score_spread":0.2134527638190471,"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."}}