{"id":"W2168024986","doi":"10.1177/1046878114542316","title":"From Simulation to Imitation","year":2014,"lang":"en","type":"article","venue":"Simulation & Gaming","topic":"Educational Games and Gamification","field":"Psychology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Ontario Tech University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Conflation; Affordance; Imitation; Embodied cognition; Competence (human resources); Cognitive science; Computer science; Video game; Human–computer interaction; Psychology; Epistemology; Artificial intelligence; Social psychology; Multimedia","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002882702,0.0001249669,0.0001197338,0.0001565076,0.0001202362,0.00005375989,0.000105742,0.00009728297,0.0008868846],"category_scores_gemma":[0.0003678533,0.0001383712,0.00004876211,0.0002665315,0.00001493812,0.0001701591,0.00001605403,0.00007978757,0.001520712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006728456,"about_ca_system_score_gemma":0.00001305501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001380423,"about_ca_topic_score_gemma":0.00001141849,"domain_scores_codex":[0.9987617,0.000132977,0.0003283835,0.0003696258,0.0002199652,0.000187396],"domain_scores_gemma":[0.9982486,0.0009888207,0.0001413444,0.0003418865,0.0001843419,0.00009505684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003640892,0.00005743993,0.003566049,0.000002991684,0.00001656255,1.31761e-7,0.008987638,0.8488677,0.0008635919,0.008143007,0.000258254,0.1292003],"study_design_scores_gemma":[0.0004250753,0.0000579654,0.3964019,0.00002219954,0.00002456387,1.870861e-7,0.001118577,0.51662,0.0000805118,0.006252536,0.07876443,0.0002320435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5710893,0.0000273988,0.4199386,0.0008251252,0.0009130626,0.0002477565,0.000007556095,0.0001094725,0.00684183],"genre_scores_gemma":[0.9927938,2.875711e-7,0.003571755,0.0007815345,0.0009949405,0.0000371695,0.0002179294,0.00002631782,0.001576291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4217045,"threshold_uncertainty_score":0.9992567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0473031043885004,"score_gpt":0.3893693137088884,"score_spread":0.342066209320388,"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."}}