{"id":"W4401024324","doi":"10.24963/ijcai.2024/293","title":"Constrained Sequential Inference in Machine Learning Using Constraint Programming","year":2024,"lang":"en","type":"article","venue":"","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Giro (Canada)","funders":"Engineering and Physical Sciences Research Council; National Natural Science Foundation of China; Leverhulme Trust","keywords":"Facility location problem; Computer science; Capacity planning; Operations research; Engineering; Operating system","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":[0.007491174,0.00178675,0.002067553,0.001301896,0.001158811,0.002530538,0.003294935,0.002086261,0.005225727],"category_scores_gemma":[0.02885552,0.001844247,0.001882061,0.002645233,0.003203415,0.003327662,0.003194605,0.005405026,0.0007594357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003239906,"about_ca_system_score_gemma":0.004271275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01623769,"about_ca_topic_score_gemma":0.02370955,"domain_scores_codex":[0.9947373,0.003082007,0.0002189151,0.0008947419,0.0008255005,0.0002416113],"domain_scores_gemma":[0.9607173,0.0360785,0.0008263162,0.001047524,0.001026202,0.0003041516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006397719,0.00006587523,0.0005318095,0.0001913996,0.0001222539,0.00011922,0.0000940305,0.8524629,0.0002565433,0.105846,0.001955835,0.03829011],"study_design_scores_gemma":[0.00001200993,0.000009056343,0.00003090396,0.00001107365,0.000004894064,0.000007738894,0.000005807258,0.9206057,0.0001276711,0.07859273,0.0005867609,0.000005721184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00259411,0.0003379783,0.9948397,0.0004691869,0.00002998541,0.00006171058,0.0001341119,0.0003412332,0.001191851],"genre_scores_gemma":[0.2189012,0.0008573526,0.7726492,0.0006540727,0.0002893776,0.0008039426,0.001016063,0.000553387,0.004275456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01623769,"threshold_uncertainty_score":0.0396176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0526286398821645,"score_gpt":0.2902463706270517,"score_spread":0.2376177307448872,"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."}}