{"id":"W2790891482","doi":"10.1007/s12532-018-0147-4","title":"QPLIB: a library of quadratic programming instances","year":2018,"lang":"en","type":"article","venue":"Mathematical Programming Computation","topic":"Process Optimization and Integration","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Engineering and Physical Sciences Research Council; Bundesministerium für Bildung und Forschung","keywords":"Undecidable problem; Computer science; Quadratic programming; Variety (cybernetics); Integer programming; Selection (genetic algorithm); Quadratic equation; Combinatorial optimization; Class (philosophy); Set (abstract data type); Theoretical computer science; Mathematical optimization; Mathematics; Algorithm; Programming language; Artificial intelligence; Decidability","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":[0.0001147142,0.0001394144,0.0001972086,0.0001160962,0.00006307806,0.0001142125,0.0001136649,0.00006950918,0.00007349779],"category_scores_gemma":[0.00007054651,0.0001250551,0.00004816023,0.0004509237,0.0001226254,0.0004723699,0.00001996921,0.00008690259,0.00005569835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000182608,"about_ca_system_score_gemma":0.00002067791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.293564e-7,"about_ca_topic_score_gemma":0.000001215698,"domain_scores_codex":[0.9990153,0.00002178055,0.0004352945,0.0001382372,0.0002008922,0.0001884548],"domain_scores_gemma":[0.9995847,0.00006961613,0.00008381874,0.0001042952,0.00009742647,0.00006014012],"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":[0.00002778656,0.0004005662,0.000181772,0.001919363,0.00008567575,0.000002234254,0.004496833,0.0123768,0.0005723858,0.04742175,0.00102596,0.9314889],"study_design_scores_gemma":[0.00023743,0.0002180728,0.00003278229,0.0002335903,0.00002107265,0.000005401174,0.0002946402,0.973829,0.005335133,0.01682598,0.002767938,0.0001989455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03189544,0.00008938384,0.9592262,0.00005439579,0.0001182054,0.0003731524,0.000001181925,0.0009203388,0.007321731],"genre_scores_gemma":[0.7240819,0.000004467635,0.275712,0.00001503702,0.00006096634,0.00003722402,0.00002149753,0.00002922617,0.00003772806],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9614522,"threshold_uncertainty_score":0.50996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133077586837698,"score_gpt":0.2487562590210415,"score_spread":0.2354485003372717,"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."}}