{"id":"W7133027813","doi":"","title":"Interpretable and Constrained Machine Learning via Combinatorial Optimization","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Domain (mathematical analysis); Variety (cybernetics); Transformative learning; Instance-based learning; Computational learning theory; Domain knowledge; Deep learning","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":[0.003208721,0.001732616,0.001066286,0.001289105,0.0006642232,0.003207509,0.00148874,0.001555066,0.005457952],"category_scores_gemma":[0.01484318,0.0009738379,0.002000469,0.001258924,0.003657185,0.002901899,0.003014927,0.004455123,0.0009358762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00202481,"about_ca_system_score_gemma":0.001830462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001657103,"about_ca_topic_score_gemma":0.002899274,"domain_scores_codex":[0.9976701,0.001159241,0.0001181382,0.000309514,0.0006179654,0.0001249884],"domain_scores_gemma":[0.9947453,0.004031814,0.0002688159,0.0005287696,0.0003245051,0.0001008381],"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":[0.00003279985,0.00005806978,0.0003105364,0.0002220323,0.00004203427,0.00009614063,0.0001488138,0.4574088,0.0008232011,0.5031559,0.002801442,0.03490023],"study_design_scores_gemma":[0.00001648808,0.0000158538,0.00004624865,0.00004446401,0.000007553645,0.00001847449,0.00002653265,0.5249985,0.0003902111,0.4715022,0.002923011,0.00001039302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00516925,0.0002739856,0.9864356,0.0006109781,0.00004536994,0.00006282004,0.0001156895,0.0002734209,0.007012896],"genre_scores_gemma":[0.1517821,0.0008065496,0.8396983,0.0003678544,0.0001123059,0.0005739307,0.0006261803,0.0006002196,0.005432569],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005457952,"threshold_uncertainty_score":0.01825863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533767424158137,"score_gpt":0.3045177227674565,"score_spread":0.2891800485258751,"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."}}