{"id":"W2186254090","doi":"10.24046/neuroed.20120101.5","title":"Bridging the gap between cognitive neuroscience and education: Psychophysiological and behavioral data collection in authentic contexts","year":2012,"lang":"en","type":"article","venue":"Neuroeducation","topic":"Neuroscience, Education and Cognitive Function","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Université du Québec à Montréal","funders":"","keywords":"Bridging (networking); Cognition; Cognitive neuroscience; Psychology; Data collection; Cognitive science; Neuroscience; Computer science; Sociology; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003544646,0.0001663054,0.0001280942,0.0001882382,0.000553158,0.0001867412,0.000272647,0.00004323479,0.00001808197],"category_scores_gemma":[0.001241528,0.0001364147,0.00001660046,0.000868947,0.0004703154,0.001095735,0.0001499876,0.0002833976,0.00001645198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003291681,"about_ca_system_score_gemma":0.0001789462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004370199,"about_ca_topic_score_gemma":0.000005772667,"domain_scores_codex":[0.9979888,0.0004408855,0.0002477944,0.0007268607,0.0002578409,0.0003377828],"domain_scores_gemma":[0.9989145,0.0003971796,0.0001486674,0.0003177949,0.00005909101,0.0001627989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001071204,0.002178471,0.4261089,0.00003609316,0.00000157143,0.000001517753,0.004736132,6.477795e-7,0.2750055,0.001829177,0.002488506,0.2875063],"study_design_scores_gemma":[0.0002485844,0.0001220188,0.9927702,0.00002666821,0.00002553531,0.00008223819,0.0006235198,0.0003702377,0.004188729,0.00035802,0.001023609,0.0001606269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940228,0.00008844658,0.0001715376,0.002213504,0.002400069,0.0005923228,0.00001319302,0.00004234199,0.000455801],"genre_scores_gemma":[0.9959083,0.0001133942,0.00001450865,0.003064312,0.000332399,0.00009622138,0.00001914757,0.00001319614,0.0004385511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5666613,"threshold_uncertainty_score":0.556283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1523158408992799,"score_gpt":0.3925581866147107,"score_spread":0.2402423457154308,"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."}}