{"id":"W4244231150","doi":"10.23952/jano.1.2019.2.04","title":"Computing minimal elements of finite families of sets w.r.t. preorder relations in set optimization","year":2019,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii","keywords":"Preorder; Set (abstract data type); Mathematics; Computer science; Combinatorics; Discrete mathematics; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002279615,0.0001130864,0.0003156892,0.0002737532,0.00002073449,0.00001327468,0.00007333442,0.00008841213,0.00007546145],"category_scores_gemma":[0.00004523567,0.0001098644,0.00004253696,0.0004086037,0.00002523798,0.0001503447,0.00001922248,0.0001453317,0.00000107617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000273838,"about_ca_system_score_gemma":0.00002607833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001643791,"about_ca_topic_score_gemma":1.013267e-7,"domain_scores_codex":[0.9987751,0.00002185389,0.0007920257,0.0000934406,0.000203106,0.0001144664],"domain_scores_gemma":[0.9992271,0.0001309937,0.0003740392,0.00007519151,0.0001456645,0.00004702857],"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":[0.00005671621,0.00004334452,0.002937085,0.0000513124,0.00003096705,3.424374e-7,0.0006197531,0.9946607,0.0001378154,0.00007470365,0.00001085144,0.00137643],"study_design_scores_gemma":[0.001013559,0.00008493014,0.001066614,0.00007243561,0.00002319102,0.000002541124,0.0003749361,0.9968747,0.0003453919,0.00003109036,0.00001275383,0.00009789167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1283063,0.00009887217,0.8699192,0.00002329598,0.0001353272,0.0001513942,0.000006459273,0.00001804006,0.001341054],"genre_scores_gemma":[0.6131549,0.000119707,0.3866645,0.00001009165,0.00001470214,7.442739e-7,0.0000172569,0.00001321059,0.000004907346],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4848486,"threshold_uncertainty_score":0.4480141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006736461028911781,"score_gpt":0.2216589757036264,"score_spread":0.2149225146747147,"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."}}