{"id":"W2943842518","doi":"10.1007/978-3-030-24766-9_29","title":"Efficient Second-Order Shape-Constrained Function Fitting","year":2019,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Convexity; Mathematics; Monotonic function; Lipschitz continuity; Combinatorics; Function (biology); Norm (philosophy); Concave function; Linear programming; Simple (philosophy); Generalization; Regular polygon; Range (aeronautics); Convex function; Algorithm; Discrete mathematics; Mathematical optimization; Pure mathematics; Mathematical analysis","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":[0.0008193908,0.001389097,0.001696334,0.00117201,0.0007209551,0.002297922,0.002171549,0.002284434,0.009031411],"category_scores_gemma":[0.003628302,0.0009648156,0.001530705,0.00193615,0.0005930054,0.001550061,0.00241021,0.002112479,0.006353448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008603865,"about_ca_system_score_gemma":0.001844319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003583919,"about_ca_topic_score_gemma":0.00567855,"domain_scores_codex":[0.9991097,0.0001272479,0.00003185061,0.0001070987,0.000516163,0.0001079236],"domain_scores_gemma":[0.9988207,0.0004040336,0.000070114,0.0003767685,0.0002441275,0.00008423065],"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":[0.0005199378,0.0002087072,0.001342273,0.0002937887,0.0001372789,0.0002941263,0.0002297135,0.3291623,0.06609355,0.04437991,0.01296934,0.5443691],"study_design_scores_gemma":[0.000009955266,0.00001816138,0.0002099257,0.000007535872,0.000007976497,0.00009822292,0.00001904469,0.9813343,0.008229506,0.006531804,0.003516903,0.00001664723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006852073,0.0001418878,0.9886814,0.0000869395,0.00003741072,0.00002272781,0.0001053818,0.001428028,0.002644062],"genre_scores_gemma":[0.1971135,0.0003267908,0.7825162,0.0001941123,0.0000691862,0.0001329094,0.001057481,0.002036714,0.01655309],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009031411,"threshold_uncertainty_score":0.03021312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499386270493992,"score_gpt":0.2605993946539593,"score_spread":0.2456055319490193,"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."}}