{"id":"W4302309981","doi":"","title":"A study of the Bienstock-Zuckerberg algorithm, Applications in Mining and Resource Constrained Project Scheduling","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Algorithm; Correctness; Scheduling (production processes); Mathematical optimization; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001648172,0.0001816328,0.0002586296,0.0001996591,0.00005666645,0.00001517472,0.0003595378,0.0001597991,0.0000028639],"category_scores_gemma":[0.00001123827,0.0001640344,0.00005661549,0.0002213543,0.00008875851,0.00004362615,0.0004728923,0.0002417796,5.028709e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020152,"about_ca_system_score_gemma":0.00004562877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006055281,"about_ca_topic_score_gemma":0.00009346977,"domain_scores_codex":[0.9991932,0.00003706426,0.0002106755,0.0003622803,0.00002696559,0.0001698056],"domain_scores_gemma":[0.9992492,0.00007707771,0.0001142446,0.0005022169,0.00002274208,0.00003453555],"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":[0.00007387384,0.0006453936,0.2067264,0.0008848954,0.0007924715,0.0001072413,0.01582509,0.7433444,0.0003661994,0.01464082,0.0003185841,0.01627459],"study_design_scores_gemma":[0.002147248,0.0001495815,0.005378271,0.0009322627,0.0002320456,0.00001193199,0.01545056,0.9687765,0.0003874378,0.004451902,0.001013714,0.001068571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685305,0.00003247775,0.02868442,0.000006023469,0.00004560836,0.0008306789,0.00003019012,0.0001340106,0.00170605],"genre_scores_gemma":[0.9966429,0.00004406033,0.003170075,0.000003232926,0.00002312452,0.00001017957,0.000003032914,0.00002395314,0.00007944174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.225432,"threshold_uncertainty_score":0.668913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05377983743198913,"score_gpt":0.1912326308479163,"score_spread":0.1374527934159272,"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."}}