{"id":"W4387835509","doi":"10.1145/3586183.3606772","title":"WorldSmith: Iterative and Expressive Prompting for World Building with a Generative AI","year":2023,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada)","funders":"","keywords":"Computer science; Generative grammar; Leverage (statistics); Formative assessment; Scratch; Human–computer interaction; Process (computing); Artificial intelligence; Programming language; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001651463,0.0001205023,0.0001228179,0.000171225,0.0003165303,0.0002492964,0.0002606518,0.00001943888,0.000003862149],"category_scores_gemma":[0.00002284575,0.00009029235,0.00002095667,0.0008967326,0.00005698936,0.0004485121,0.0002060108,0.00008663006,0.000007232154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003019289,"about_ca_system_score_gemma":0.00004333185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009899734,"about_ca_topic_score_gemma":0.00007760584,"domain_scores_codex":[0.9990093,0.0000310893,0.0001402629,0.0004367488,0.0001367277,0.0002459026],"domain_scores_gemma":[0.9992145,0.0002509312,0.00007697689,0.0002637737,0.0001204196,0.00007336653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001860582,0.00005148312,0.0003978268,0.00003892916,0.0001024449,0.000008872394,0.006717384,0.003411767,0.01385963,0.9495315,0.011491,0.01437055],"study_design_scores_gemma":[0.0008528334,0.0001255127,0.0009022338,0.0001180367,0.00001499752,0.000008938779,0.0003847594,0.9188806,0.0551754,0.0157274,0.007428178,0.0003810366],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00557223,0.00001735821,0.9856442,0.006660838,0.00002444937,0.0007525252,0.000008313493,0.0003338497,0.0009862051],"genre_scores_gemma":[0.3854768,0.000003956098,0.6061243,0.001335075,0.00009728549,0.001531327,0.00001010464,0.00002070861,0.005400436],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9338041,"threshold_uncertainty_score":0.3682015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02752014472764055,"score_gpt":0.3065254036185444,"score_spread":0.2790052588909038,"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."}}