{"id":"W3156450849","doi":"10.1007/978-3-030-73988-1_33","title":"The Effect of Agency on Cognitive Load in Dyads Learning Physics with a Serious Computer Game","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Affect (linguistics); Agency (philosophy); Cognitive load; Cognition; Context (archaeology); Dyad; Task (project management); Cognitive psychology; Dual (grammatical number); Psychology; Cognitive architecture; Cognitive science; Computer science; Social psychology; Engineering; Communication; Sociology; Neuroscience","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":[0.001810608,0.0002415885,0.0003167965,0.0004101454,0.0004847356,0.0005468333,0.0021244,0.00007351448,0.000001642579],"category_scores_gemma":[0.0001059803,0.0001773635,0.00005289639,0.000939519,0.001242951,0.00305851,0.001846145,0.00065867,0.00001599703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001421033,"about_ca_system_score_gemma":0.0004757544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001224823,"about_ca_topic_score_gemma":0.00002663321,"domain_scores_codex":[0.9980537,0.0001326989,0.000491786,0.0003429228,0.0006939922,0.0002848407],"domain_scores_gemma":[0.9966337,0.001203177,0.0004004511,0.001056161,0.0006398733,0.00006665193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001221347,0.00001268022,0.000242634,0.0000348756,0.000007663622,0.000002187021,0.00321564,0.0007983297,0.000002888406,0.08454767,0.000009609191,0.9111136],"study_design_scores_gemma":[0.00164743,0.001555394,0.008352974,0.003371288,0.00001667694,0.00005335254,0.0001094879,0.9636427,0.0001724117,0.002282405,0.01809019,0.0007057518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006708128,0.0006571338,0.822063,0.0007664982,0.0004151779,0.00133505,0.000008702241,0.0000968824,0.1679495],"genre_scores_gemma":[0.9768652,0.00358629,0.01754395,0.0008002123,0.0000648002,0.0000839557,0.00003345241,0.00001586149,0.001006317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.970157,"threshold_uncertainty_score":0.7232674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02056367534962383,"score_gpt":0.278933632900177,"score_spread":0.2583699575505532,"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."}}