{"id":"W1991359457","doi":"10.1016/s0898-1221(02)00275-4","title":"Generalized hypergeometric functions associated with k-uniformly convex functions","year":2002,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Analytic and geometric function theory","field":"Mathematics","cited_by":85,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Mathematics; Hypergeometric function; Generalized hypergeometric function; Convex function; Convolution (computer science); Schwarzian derivative; Confluent hypergeometric function; Pure mathematics; Product (mathematics); Basic hypergeometric series; Barnes integral; Hadamard product; Hypergeometric identity; Hadamard transform; Special functions; Operator (biology); Hypergeometric function of a matrix argument; Regular polygon; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003778254,0.0004462072,0.0006375118,0.0008982812,0.0007114477,0.0001251561,0.0004197651,0.0001636465,0.001182394],"category_scores_gemma":[0.0002452951,0.0003381903,0.0001699197,0.004799592,0.000280621,0.0002022845,0.00007848586,0.0003455981,0.00076899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001857787,"about_ca_system_score_gemma":0.00006001456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005518953,"about_ca_topic_score_gemma":0.00001056844,"domain_scores_codex":[0.9975583,0.00005769278,0.0006707174,0.0005460447,0.0006347041,0.0005325354],"domain_scores_gemma":[0.9960528,0.001499835,0.0005425715,0.001084235,0.000520406,0.000300123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009886602,0.008905153,0.003032732,0.0005719272,0.004035425,0.0000288216,0.002258443,0.003496525,0.00005429141,0.7049643,0.2527328,0.01982072],"study_design_scores_gemma":[0.0180752,0.003071808,0.002254987,0.0009522634,0.007281659,0.001129992,0.007534712,0.4036386,0.0001607343,0.2836631,0.266035,0.006201954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01503262,0.0001532316,0.9629887,0.0003935699,0.0001111095,0.001137676,0.00005748942,0.0006809498,0.01944471],"genre_scores_gemma":[0.6081789,0.0001176529,0.2773734,0.000780506,0.0005154744,0.002679907,0.0003655936,0.0003532456,0.1096352],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6856152,"threshold_uncertainty_score":0.999907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03581901218543447,"score_gpt":0.2376375179625978,"score_spread":0.2018185057771634,"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."}}