{"id":"W2809724245","doi":"10.1016/j.dib.2018.06.031","title":"Interaction analysis data of simulation gaming events using the serious game Aqua Republica","year":2018,"lang":"en","type":"article","venue":"Data in Brief","topic":"Educational Games and Gamification","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Visualization; Computer science; Context (archaeology); Representation (politics); Human–computer interaction; Data visualization; Data mining; Geography; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001107546,0.000606065,0.0006395967,0.003924598,0.0008304596,0.001052415,0.0004528255,0.0004899134,0.005391613],"category_scores_gemma":[0.01014634,0.0001950947,0.0004943822,0.002967262,0.0005093077,0.0005264517,0.00159541,0.0008686181,0.001448626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004911185,"about_ca_system_score_gemma":0.0005085582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004125794,"about_ca_topic_score_gemma":0.008960517,"domain_scores_codex":[0.9975997,0.000768261,0.0002402996,0.0003714733,0.0008244266,0.000195947],"domain_scores_gemma":[0.9891347,0.006298949,0.0008917943,0.0007463139,0.002265353,0.0006629023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007138334,0.005136741,0.4701523,0.002867134,0.0006203929,0.002010574,0.07170869,0.01098435,0.04188822,0.004675299,0.02317832,0.3596396],"study_design_scores_gemma":[0.0001048842,0.001774215,0.9337618,0.0002388431,0.0001460517,0.0006412819,0.01408522,0.01148338,0.01146728,0.002504696,0.02358978,0.0002024806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9752378,0.00006806438,0.006161376,0.0000627566,0.000027134,0.0007217224,0.009506058,0.0002184409,0.007996697],"genre_scores_gemma":[0.9571311,0.0001333601,0.01816123,0.00005774988,0.00002779447,0.003205567,0.01630349,0.0001655715,0.004814038],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.005391613,"threshold_uncertainty_score":0.01803678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1758762655302848,"score_gpt":0.4631272102310953,"score_spread":0.2872509447008105,"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."}}