{"id":"W856071238","doi":"","title":"Nogood processing in csps","year":2008,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Constraint satisfaction problem; Computer science; Speedup; Solver; Domain (mathematical analysis); Satisfiability; Boolean satisfiability problem; Constraint (computer-aided design); Theoretical computer science; Constraint satisfaction; Mathematical optimization; Artificial intelligence; Parallel computing; Mathematics; Programming language","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":[0.00005723142,0.0001353029,0.0001434881,0.000216792,0.00007255599,0.00008464308,0.0002429246,0.0001432549,0.00006617203],"category_scores_gemma":[0.00002612747,0.0001475918,0.0000354503,0.0003888059,0.00001048334,0.0002288707,0.00001694318,0.0002122859,0.00004660269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005932895,"about_ca_system_score_gemma":0.0002518384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006048949,"about_ca_topic_score_gemma":0.0007475344,"domain_scores_codex":[0.9991733,0.0000237329,0.0001638999,0.0002892737,0.0001957411,0.0001540292],"domain_scores_gemma":[0.9995587,0.0000116861,0.0001261244,0.0001976186,0.00006519107,0.00004061576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002844376,0.0001215313,0.001646606,0.0002621927,0.00001116955,0.0001093581,0.06399311,0.001704815,0.001147245,0.003982153,0.002674867,0.9243185],"study_design_scores_gemma":[0.005556239,0.0003213801,0.4163655,0.003067255,0.00007490111,0.0004347049,0.02024356,0.4843377,0.01735728,0.003022774,0.04324576,0.005972914],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1214239,0.002306015,0.3825303,0.002094507,0.003519511,0.001127173,0.000002616218,0.001263386,0.4857326],"genre_scores_gemma":[0.8569592,0.0003683978,0.0637181,0.0003206085,0.0001508195,0.00005903151,0.0002079253,0.00005242442,0.0781635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9183456,"threshold_uncertainty_score":0.6018619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694446723756259,"score_gpt":0.3103620588814904,"score_spread":0.2934175916439278,"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."}}