{"id":"W4416014030","doi":"10.1609/aiide.v21i1.36852","title":"Embedded Mechanics Generation","year":2025,"lang":"","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Metric (unit); Game design; Game mechanics; Measure (data warehouse); Reinforcement learning; Video game","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":[0.0007258619,0.001035372,0.0004281478,0.000742504,0.00041775,0.001305514,0.001477366,0.0008909714,0.01751337],"category_scores_gemma":[0.003452195,0.0005069417,0.0007010511,0.0003301275,0.0006817923,0.001269015,0.001896692,0.0008223452,0.003949856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006006245,"about_ca_system_score_gemma":0.000799824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009365113,"about_ca_topic_score_gemma":0.001556147,"domain_scores_codex":[0.9991807,0.00009924208,0.00003704249,0.0001559384,0.0004589084,0.00006804987],"domain_scores_gemma":[0.9989611,0.0003610743,0.00006753908,0.0002938642,0.0002673526,0.0000491481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000263724,0.0003252615,0.00423722,0.000859004,0.00008721487,0.00069765,0.0005940137,0.2933198,0.06290168,0.1192591,0.02026533,0.49719],"study_design_scores_gemma":[0.00007969936,0.0002800582,0.0009540798,0.0001260907,0.00003463387,0.0004748465,0.000166942,0.8214074,0.03386982,0.04979663,0.09276268,0.00004713662],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02186767,0.0002491454,0.9369294,0.0001736193,0.0002085276,0.0005332796,0.0005648959,0.005506521,0.03396694],"genre_scores_gemma":[0.3697276,0.0004062276,0.5970388,0.0001989435,0.00004336,0.0008146598,0.001827209,0.001968207,0.02797505],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01751337,"threshold_uncertainty_score":0.05858803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05823496438359969,"score_gpt":0.3079348827911407,"score_spread":0.249699918407541,"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."}}