{"id":"W2952043232","doi":"10.48550/arxiv.1403.7135","title":"On subgradient projectors","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subgradient method; Mathematics; Computer science; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004965948,0.001651816,0.00130385,0.001703385,0.001067564,0.002099384,0.001203957,0.001509593,0.007419233],"category_scores_gemma":[0.01661559,0.0008091994,0.001191389,0.002359875,0.004186806,0.006461723,0.004643282,0.005926022,0.001896705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175204,"about_ca_system_score_gemma":0.001341283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001243357,"about_ca_topic_score_gemma":0.0008644406,"domain_scores_codex":[0.9973596,0.001567764,0.00009447313,0.0003102524,0.0005271796,0.0001407025],"domain_scores_gemma":[0.995218,0.003120409,0.0002619383,0.0004432144,0.0007129753,0.0002433959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003814517,0.00002431369,0.0002231134,0.000126483,0.00001658578,0.00007557492,0.0001518684,0.0168795,0.001171806,0.949951,0.003245126,0.02809641],"study_design_scores_gemma":[0.00002021427,0.00006679168,0.0002110393,0.00007301418,0.00001418523,0.0001455071,0.00005480611,0.1445518,0.001263624,0.8423781,0.01120182,0.00001912855],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007885088,0.001584249,0.9730706,0.0008188215,0.0001305264,0.00005735134,0.0001194027,0.0001157524,0.01621822],"genre_scores_gemma":[0.3325648,0.01118044,0.6172868,0.001657015,0.00123206,0.0006985575,0.0007753785,0.001220957,0.0333839],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007419233,"threshold_uncertainty_score":0.02626276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05283505477446836,"score_gpt":0.1749155112617012,"score_spread":0.1220804564872329,"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."}}