{"id":"W2148815219","doi":"10.1002/ejp.716","title":"A novel electroencephalography‐based tool for objective assessment of network dynamics activated by nociceptive stimuli","year":2015,"lang":"en","type":"article","venue":"European Journal of Pain","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Chief Scientist Office; Office of the Chief Scientist","keywords":"Electroencephalography; Psychology; Neuroimaging; Brain activity and meditation; Audiology; Perception; Multivariate statistics; Nociception; Set (abstract data type); Multivariate analysis; Reliability (semiconductor); Neuroscience; Medicine; Computer science; Machine learning; Internal medicine","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":[0.0005511853,0.0005771827,0.0002906337,0.001234042,0.0001060321,0.0004665382,0.0002927113,0.000232078,0.003016665],"category_scores_gemma":[0.002169344,0.0001224626,0.0002445896,0.0007282558,0.0001640772,0.0004656579,0.0003519001,0.0003173545,0.0005198739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001776955,"about_ca_system_score_gemma":0.0002575058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000654439,"about_ca_topic_score_gemma":0.001337196,"domain_scores_codex":[0.999718,0.00007449634,0.00001904811,0.00006256015,0.0001129212,0.00001287243],"domain_scores_gemma":[0.9994475,0.0002140346,0.000107878,0.00005532162,0.0001407966,0.00003442533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007316745,0.0002513071,0.03252327,0.0004400676,0.000216739,0.0002276814,0.0001501339,0.01769795,0.2672989,0.002306401,0.003636166,0.6745197],"study_design_scores_gemma":[0.0001903423,0.001161142,0.2412551,0.000102492,0.000234908,0.002441966,0.0001543392,0.6771472,0.06338871,0.004350696,0.009440216,0.0001329337],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.160376,0.0003661244,0.833514,0.0001397711,0.00007392908,0.000277032,0.001398363,0.001405786,0.002448864],"genre_scores_gemma":[0.5808296,0.0003603683,0.4154393,0.00005571944,0.00008897974,0.000630088,0.001026772,0.0001250533,0.001444063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003016665,"threshold_uncertainty_score":0.01009172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.043010405207676,"score_gpt":0.2935867312412928,"score_spread":0.2505763260336167,"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."}}