{"id":"W3163477952","doi":"10.1007/978-3-030-74608-7_15","title":"Designing the BrainTagger Researcher Platform to Automate Development of Customized Cognitive Games","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Educational Games and Gamification","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Popularity; Computer science; Process (computing); Scale (ratio); Video game development; Engineering management; Game design; Knowledge management; Human–computer interaction; Engineering; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006140976,0.0007972707,0.000306767,0.0004896311,0.0002995101,0.001044222,0.001644553,0.0008111247,0.01850576],"category_scores_gemma":[0.002083722,0.0006124253,0.0004449984,0.0002121975,0.0003296548,0.001311918,0.001656926,0.0009724679,0.007190673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003227164,"about_ca_system_score_gemma":0.0007155096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001434937,"about_ca_topic_score_gemma":0.003175916,"domain_scores_codex":[0.9996106,0.00007304447,0.00001724337,0.0001041683,0.0001366902,0.00005822102],"domain_scores_gemma":[0.9995116,0.000229523,0.00002443342,0.0000798808,0.00009305672,0.00006151213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001162489,0.0008948391,0.003735497,0.0005553825,0.0001442284,0.001348178,0.002857533,0.008745097,0.249179,0.02374377,0.08158737,0.6260467],"study_design_scores_gemma":[0.000614453,0.001300707,0.004432511,0.0001838732,0.0001836538,0.001887174,0.0008367522,0.2195019,0.3271865,0.01703867,0.4265571,0.0002767945],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04814488,0.000170079,0.8367687,0.0003140054,0.0002277073,0.001058821,0.0005511765,0.07591706,0.03684754],"genre_scores_gemma":[0.1468073,0.0002411882,0.7548068,0.0004582102,0.00003314769,0.001331542,0.001436646,0.01026477,0.08462048],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01850576,"threshold_uncertainty_score":0.06190789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05801196826255003,"score_gpt":0.3321168645341384,"score_spread":0.2741048962715884,"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."}}