{"id":"W2036042055","doi":"10.1093/scan/nsu168","title":"Engaged listeners: shared neural processing of powerful political speeches","year":2015,"lang":"en","type":"article","venue":"Social Cognitive and Affective Neuroscience","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":146,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health","keywords":"Psychology; Politics; Communication; Cognitive psychology; Political science; Law","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":[0.0005082231,0.0002880586,0.0002322223,0.0003039855,0.0002241046,0.0008650376,0.0001524757,0.0004806281,0.002382086],"category_scores_gemma":[0.002989239,0.0002417575,0.0002021635,0.0001617443,0.0006375086,0.0008254164,0.001038943,0.000487031,0.0002317668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001160864,"about_ca_system_score_gemma":0.0001113834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002171857,"about_ca_topic_score_gemma":0.0004546684,"domain_scores_codex":[0.9997138,0.00005938945,0.0000101787,0.00009426148,0.0000718341,0.0000505165],"domain_scores_gemma":[0.999423,0.0002727268,0.0001185561,0.00005396389,0.00004230886,0.00008949221],"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":[0.001140621,0.0001011895,0.01726249,0.0001963267,0.0001475824,0.0004813733,0.00607312,0.0004508094,0.9219507,0.001272973,0.0002858436,0.05063699],"study_design_scores_gemma":[0.0001103043,0.001116152,0.9133808,0.0000657955,0.0002497155,0.001503622,0.003937751,0.00443466,0.06413543,0.009309675,0.001693564,0.00006249016],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925114,0.0001594903,0.003506203,0.00009277825,0.00001776453,0.00001278982,0.0000436581,0.00002590441,0.003630016],"genre_scores_gemma":[0.9982389,0.00007460237,0.00105213,0.00004208018,0.00002313901,0.00001572529,0.00003387938,0.00001427921,0.0005053005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002382086,"threshold_uncertainty_score":0.007968903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07407495775601558,"score_gpt":0.320296329765696,"score_spread":0.2462213720096804,"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."}}