{"id":"W2944669769","doi":"10.1108/ils-05-2018-0042","title":"Generating gameworlds with computers: the case for procedural creativity","year":2019,"lang":"en","type":"article","venue":"Information and Learning Sciences","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Creativity; Status quo; Originality; Computer science; Creativity technique; Abstraction; Generative grammar; Action (physics); Computational creativity; Value (mathematics); Knowledge management; Cognitive science; Management science; Epistemology; Psychology; Artificial intelligence; Social psychology; Engineering","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001536252,0.00008052424,0.00007636353,0.00007473592,0.001255377,0.00124318,0.0002608856,0.00002291693,0.000002261262],"category_scores_gemma":[0.0001760427,0.00004596239,0.0000194255,0.0002793597,0.0001086954,0.00183343,0.00006307457,0.000248638,0.000008582487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009054748,"about_ca_system_score_gemma":0.00005922936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006926578,"about_ca_topic_score_gemma":0.000009376266,"domain_scores_codex":[0.9992738,0.00009963604,0.0001363558,0.0001425015,0.0001564192,0.0001912779],"domain_scores_gemma":[0.9992285,0.0004280292,0.0001495258,0.0001002703,0.00005720128,0.00003651633],"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":[0.00000584054,0.000007081802,0.00775176,0.00004854403,0.000007596336,0.000002601374,0.02681202,0.07959069,0.000008346492,0.02079792,0.0001094129,0.8648582],"study_design_scores_gemma":[0.0002293432,0.0003548266,0.0007828867,0.00004298345,0.000002576025,0.0004747994,0.00370963,0.9213976,0.000009672825,0.0000265669,0.07284808,0.0001210044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4760925,0.00002415604,0.5212153,0.001817734,0.0001112438,0.000202061,1.601731e-7,0.0001454073,0.0003913625],"genre_scores_gemma":[0.8700193,7.213079e-7,0.1293007,0.0005195699,0.00002386641,0.000012839,0.000001045308,0.000001655445,0.0001204229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8647372,"threshold_uncertainty_score":0.9997936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01516597437849218,"score_gpt":0.2645911375938205,"score_spread":0.2494251632153283,"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."}}