{"id":"W3099746525","doi":"","title":"QUASI-CONCAVE DENSITY ESTIMATION","year":2013,"lang":"en","type":"article","venue":"","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematics; Estimator; Hellinger distance; Principle of maximum entropy; Concave function; Density estimation; Maximum entropy probability distribution; Reciprocal; Square root; Applied mathematics; Limiting; Regular polygon; Entropy (arrow of time); Maximum likelihood; M-estimator; Mathematical optimization; Statistics; Geometry; Physics","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":[0.006143031,0.001274334,0.001531931,0.001424291,0.0006027518,0.002335023,0.002461276,0.002143231,0.004739245],"category_scores_gemma":[0.02526525,0.001165429,0.001197209,0.001357079,0.002509862,0.003579448,0.002508875,0.002684698,0.001636323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001647636,"about_ca_system_score_gemma":0.001249714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002752888,"about_ca_topic_score_gemma":0.002072231,"domain_scores_codex":[0.9967028,0.002024126,0.00009629632,0.0004509999,0.0005887321,0.0001370993],"domain_scores_gemma":[0.990132,0.006779603,0.0006073906,0.0009975887,0.001229388,0.0002539898],"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":[0.0001360021,0.00004838031,0.001869525,0.0003419522,0.00009904338,0.0002463087,0.0001607119,0.3574046,0.002869204,0.5910532,0.007701948,0.03806913],"study_design_scores_gemma":[0.00000855804,0.00001429838,0.0002768249,0.00002995645,0.000009135957,0.00007248559,0.00001205469,0.9095001,0.0005821197,0.087795,0.001684869,0.00001461846],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002292101,0.0002432971,0.9954146,0.0003102791,0.00003760448,0.0000277848,0.0001280293,0.00009998585,0.001446293],"genre_scores_gemma":[0.3776873,0.002289315,0.5987586,0.0009167472,0.0005686445,0.0005088595,0.001552342,0.0004065276,0.01731167],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006143031,"threshold_uncertainty_score":0.03248787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09274296344671107,"score_gpt":0.3805608804326517,"score_spread":0.2878179169859407,"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."}}