{"id":"W2005924051","doi":"10.1007/s10601-005-0552-y","title":"An Efficient Bounds Consistency Algorithm for the Global Cardinality Constraint","year":2005,"lang":"en","type":"article","venue":"Constraints","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Local consistency; Cardinality (data modeling); Constraint programming; Consistency (knowledge bases); Constraint (computer-aided design); Benchmark (surveying); Computer science; Mathematical optimization; Constraint logic programming; Constraint satisfaction; Algorithm; Mathematics; Stochastic programming; Artificial intelligence; Probabilistic logic; Data mining","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":[0.003097228,0.001538277,0.002206949,0.002442113,0.001448332,0.004037075,0.004023822,0.002119887,0.0103164],"category_scores_gemma":[0.01530627,0.001279268,0.001647459,0.004039602,0.001195185,0.006062706,0.004556483,0.00467304,0.002250353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001638005,"about_ca_system_score_gemma":0.003404181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004866068,"about_ca_topic_score_gemma":0.005549349,"domain_scores_codex":[0.9959837,0.000942833,0.0002395382,0.0008532901,0.00161402,0.0003666359],"domain_scores_gemma":[0.9925565,0.003826666,0.0003806697,0.001779817,0.00127472,0.0001817273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005105662,0.0002884278,0.00085097,0.0003474012,0.0001526964,0.000149247,0.000279656,0.2005251,0.008608475,0.1233691,0.02447748,0.6404409],"study_design_scores_gemma":[0.0001522919,0.00005854148,0.0002651512,0.0000535785,0.00006012508,0.0001160349,0.00007825428,0.8925508,0.0078585,0.08881631,0.00995415,0.00003632144],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003021688,0.0001959743,0.9927511,0.0001728335,0.00006068773,0.00009533944,0.0001748801,0.001027093,0.002500277],"genre_scores_gemma":[0.06718592,0.0002206573,0.9277301,0.0001544574,0.00008964194,0.0002486471,0.000838777,0.0006533,0.002878557],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0103164,"threshold_uncertainty_score":0.0345118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721744243950913,"score_gpt":0.2827290062673527,"score_spread":0.2655115638278436,"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."}}