{"id":"W2586861931","doi":"10.1027/2151-2604/a000266","title":"Measuring Implicit Cognitive and Emotional Engagement to Better Understand Learners’ Performance in Problem Solving","year":2016,"lang":"en","type":"article","venue":"Zeitschrift für Psychologie","topic":"Neuroscience, Education and Cognitive Function","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Université du Québec à Montréal","funders":"","keywords":"Cognition; Field (mathematics); Cognitive psychology; Psychology; Data collection; Measure (data warehouse); Computer science; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.000538489,0.0001819055,0.0001339573,0.0002841413,0.0002730672,0.00008616712,0.000180626,0.00005705499,0.000149927],"category_scores_gemma":[0.0007673927,0.0001372583,0.00002970568,0.000456973,0.0001733839,0.0004344283,0.0001051593,0.0002221394,0.0002284869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002750647,"about_ca_system_score_gemma":0.00005272252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002719899,"about_ca_topic_score_gemma":0.000005214929,"domain_scores_codex":[0.9979352,0.0002021821,0.0002428463,0.0008286851,0.0003274342,0.0004636664],"domain_scores_gemma":[0.9991949,0.000372494,0.0000743544,0.0001640593,0.00005864012,0.0001355156],"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":[0.0002177546,0.0003075763,0.1079461,0.00003210566,0.000005499614,0.00001600054,0.001826121,0.00001053355,0.7516692,0.003233771,0.0005996876,0.1341356],"study_design_scores_gemma":[0.002292872,0.000635199,0.869427,0.0005039272,0.000009753599,0.00005201604,0.001621972,0.00003562619,0.1174059,0.0005291185,0.006943233,0.0005433958],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611945,0.00001069018,0.005025351,0.004284513,0.0005293237,0.0004896915,0.000009260041,0.00008667061,0.02837002],"genre_scores_gemma":[0.9936479,0.0001002134,0.0001943725,0.005318873,0.00007616963,0.000055984,6.915863e-7,0.00001766233,0.000588097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7614809,"threshold_uncertainty_score":0.5597231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1318086216272879,"score_gpt":0.3380497250480944,"score_spread":0.2062411034208065,"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."}}