{"id":"W4411171866","doi":"10.1109/tg.2025.3578435","title":"Extending Heuristic Knowledge Transfer for General Game Playing","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Games","topic":"Educational Games and Gamification","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Heuristic; Computer science; Knowledge transfer; Transfer (computing); Artificial intelligence; Knowledge management; Parallel computing","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":[0.0001488304,0.0001711496,0.0001788739,0.0002894068,0.0001894011,0.00003824231,0.0001517073,0.0001228289,0.0005170181],"category_scores_gemma":[0.000006888784,0.000175279,0.0001822611,0.0002788492,0.00006136778,0.00006254473,3.604064e-7,0.0001848079,0.0001411038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008547236,"about_ca_system_score_gemma":0.00007384607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002724025,"about_ca_topic_score_gemma":0.00003318836,"domain_scores_codex":[0.9988933,0.00006414191,0.0002907652,0.0003892054,0.0000806787,0.0002818932],"domain_scores_gemma":[0.9991555,0.0003768186,0.00002567851,0.0002931792,0.00008737091,0.00006143337],"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":[0.0008256084,0.003304561,0.0002613225,0.0003402906,0.0007345907,0.000003805139,0.01723353,0.003046375,0.01536624,0.2194202,0.01531755,0.7241459],"study_design_scores_gemma":[0.01063731,0.00121271,0.08024936,0.0007036457,0.001574189,0.00006896952,0.009043803,0.01770481,0.04594991,0.01949765,0.8108081,0.002549601],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09718458,0.00064877,0.8877071,0.001087504,0.003800103,0.0004694285,0.000074605,0.0001223167,0.00890558],"genre_scores_gemma":[0.9422195,0.00003876914,0.001038463,0.0003448837,0.0001594176,0.0006720834,0.0000133107,0.00002633194,0.05548723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8866687,"threshold_uncertainty_score":0.7147669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03611801379245717,"score_gpt":0.3629785954587131,"score_spread":0.3268605816662559,"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."}}