{"id":"W4410863961","doi":"10.1007/978-3-031-84756-1_3","title":"An Introduction to ML Through PCG","year":2025,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on games and computational intelligence","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Sudbury; University of Alberta","funders":"","keywords":"Computer science; History","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001372165,0.0003691955,0.0003242882,0.0003826554,0.0001947623,0.0003644544,0.0009946601,0.00024465,0.0001439699],"category_scores_gemma":[0.0001597316,0.0003333735,0.0000946602,0.0001536381,0.0001350338,0.0002630442,0.0001892607,0.0003008069,0.000100408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008367861,"about_ca_system_score_gemma":0.00009863869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007202306,"about_ca_topic_score_gemma":0.000005314056,"domain_scores_codex":[0.9979736,0.00003406998,0.000374404,0.001015781,0.0003901749,0.0002120368],"domain_scores_gemma":[0.9982994,0.0005323216,0.0001706074,0.000731181,0.0001886465,0.00007779915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009908266,0.00001790414,6.554629e-7,0.00001276184,0.0000257812,0.000001401972,0.00009474293,0.006239511,0.000009113528,0.6324456,0.005803806,0.3553388],"study_design_scores_gemma":[0.0000200639,0.0002163281,0.00004888725,0.0001137372,0.00001998472,0.000008847393,0.00002784364,0.008631523,0.003756237,0.7643231,0.2224037,0.0004296867],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00001464016,0.0005246082,0.9443713,0.01958288,0.0003815257,0.0002966491,0.00001769488,0.0004644451,0.03434625],"genre_scores_gemma":[0.4032775,0.001714293,0.3799858,0.01182523,0.001604187,0.0003857067,0.0001313564,0.0001342972,0.2009417],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5643855,"threshold_uncertainty_score":0.9999118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02058684775986508,"score_gpt":0.2816071162018952,"score_spread":0.2610202684420301,"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."}}