{"id":"W2754756029","doi":"","title":"Approximation Algorithms using Allegories and Coq","year":2017,"lang":"en","type":"dissertation","venue":"Brock University Digital Repository (Brock University)","topic":"Advanced Algebra and Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Brock University","keywords":"Computer science; Algorithm; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003716043,0.0009586174,0.0008876887,0.001694498,0.001471999,0.003744303,0.002909316,0.00148797,0.006806339],"category_scores_gemma":[0.01326808,0.0006595181,0.001321038,0.002102792,0.003060844,0.006999883,0.004043766,0.003474077,0.001513121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003669984,"about_ca_system_score_gemma":0.002582035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004837727,"about_ca_topic_score_gemma":0.004304774,"domain_scores_codex":[0.9958418,0.001062542,0.0002774943,0.0007394036,0.001598026,0.0004807149],"domain_scores_gemma":[0.9941174,0.003278019,0.0002864099,0.001557328,0.0006414113,0.0001194405],"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":[0.00016711,0.0001396233,0.0009269387,0.0001797004,0.0000429509,0.00006968137,0.0004012573,0.05172441,0.002812628,0.8465852,0.002932332,0.09401835],"study_design_scores_gemma":[0.0001248759,0.00008452917,0.000323497,0.00007881292,0.00004827608,0.0001816265,0.0001884109,0.4092505,0.01463385,0.5395436,0.03548269,0.00005930792],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.009519144,0.0001560714,0.9827002,0.0003411093,0.00005859917,0.0000642764,0.0000752757,0.002136263,0.004948895],"genre_scores_gemma":[0.179963,0.0003273377,0.8139829,0.0002003756,0.00005490324,0.0001994337,0.0003577633,0.0006507413,0.004263537],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.006806339,"threshold_uncertainty_score":0.02662766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427789015590454,"score_gpt":0.2100497208649349,"score_spread":0.1957718307090304,"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."}}