{"id":"W6999413970","doi":"","title":"The constraint satisfaction problem: complexity and approximability","year":2017,"lang":"en","type":"book","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Technische Universität Dresden; Grantová Agentura České Republiky","keywords":"Constraint satisfaction problem; Constraint satisfaction; Constraint (computer-aided design); Hybrid algorithm (constraint satisfaction); Computational complexity theory; Approximation algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001575946,0.0003603642,0.0005342004,0.0006362204,0.004428929,0.0002939576,0.002491246,0.000309647,0.0001089354],"category_scores_gemma":[0.0001330999,0.0003976574,0.000267657,0.0002855917,0.006588292,0.001091268,0.002613733,0.001466044,0.000009626162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000642349,"about_ca_system_score_gemma":0.001759883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008090558,"about_ca_topic_score_gemma":0.008273847,"domain_scores_codex":[0.9963974,0.0006686943,0.0002429724,0.0009837674,0.00100902,0.0006980975],"domain_scores_gemma":[0.9960258,0.0008214868,0.000559966,0.001452393,0.0007379547,0.0004023851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003681451,0.00008108321,0.003514418,0.0002871459,0.0002933287,0.0001235924,0.001766907,0.000033984,0.00003196269,0.6890631,0.01763302,0.2868033],"study_design_scores_gemma":[0.001644733,0.0003941461,0.03286372,0.0002312799,0.00006989912,0.00005218637,0.002252585,0.01415799,0.000003508826,0.1232441,0.8244562,0.0006297028],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0008529747,0.00007841601,0.3295605,0.003688872,0.0002252752,0.001742651,0.0004688524,0.0001947414,0.6631877],"genre_scores_gemma":[0.0603127,0.01881903,0.2261187,0.00006479961,0.0002037554,0.000002248988,0.0005556609,0.0001041517,0.6938189],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8068232,"threshold_uncertainty_score":0.9998475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04102692681197964,"score_gpt":0.25888046554094,"score_spread":0.2178535387289604,"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."}}