{"id":"W4389002521","doi":"10.17083/ijsg.v10i4.645","title":"How ChatGPT can inspire and improve serious board game design","year":2023,"lang":"en","type":"article","venue":"International Journal of Serious Games","topic":"Educational Games and Gamification","field":"Psychology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Ambrose University","funders":"","keywords":"Brainstorming; Computer science; Process (computing); Game design; Curriculum; Game Developer; Game based learning; Game mechanics; Game design document; Serious game; Multimedia; Human–computer interaction; Psychology; Artificial intelligence; Pedagogy","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":[0.005462768,0.001242444,0.0003645016,0.001628738,0.0007648825,0.004502638,0.002067554,0.001268596,0.006905767],"category_scores_gemma":[0.02820037,0.0006285201,0.0007518836,0.0006682064,0.001661797,0.006210465,0.003947242,0.001866881,0.001797606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009438692,"about_ca_system_score_gemma":0.001163348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151921,"about_ca_topic_score_gemma":0.002609593,"domain_scores_codex":[0.996393,0.002307283,0.0001754209,0.0003420142,0.0006042924,0.0001778771],"domain_scores_gemma":[0.9886326,0.007474227,0.0004584203,0.001553536,0.001057812,0.000823307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007665209,0.001276809,0.01131772,0.002349657,0.00012889,0.001804565,0.03451175,0.02900911,0.03086398,0.1198268,0.02924522,0.7388991],"study_design_scores_gemma":[0.0005106808,0.002668255,0.009543804,0.00185805,0.0003103403,0.004693191,0.01150965,0.2004369,0.02808628,0.1879679,0.5520432,0.0003715676],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07997528,0.0005204057,0.8711786,0.003119061,0.000360102,0.000948631,0.0002368474,0.007540177,0.03612084],"genre_scores_gemma":[0.2802237,0.0004712589,0.7050683,0.0005022326,0.0000758621,0.0006801243,0.0004329171,0.0008637029,0.01168189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006905767,"threshold_uncertainty_score":0.02889019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259372333873611,"score_gpt":0.3124398941347903,"score_spread":0.2898461707960542,"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."}}