{"id":"W2898631783","doi":"10.28924/2291-8639-16-2018-822","title":"New Modified Method of the Chebyshev Collocation Method for Solving Fractional Diffusion Equation","year":2018,"lang":"en","type":"article","venue":"International Journal of Analysis and Applications","topic":"Fractional Differential Equations Solutions","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Islamic Azad University","keywords":"Mathematics; Fractional calculus; Collocation (remote sensing); Collocation method; Chebyshev filter; Chebyshev polynomials; Orthogonal collocation; Applied mathematics; Reliability (semiconductor); Space (punctuation); Derivative (finance); Scheme (mathematics); Mathematical analysis; Differential equation; Computer science; Ordinary differential equation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003846775,0.0004977726,0.000621296,0.0004837875,0.0004146093,0.0005425693,0.0007942296,0.001141184,0.001969469],"category_scores_gemma":[0.0008332676,0.0001784191,0.000597053,0.0005612593,0.0005121817,0.0007008303,0.0005041896,0.0009887024,0.00050555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003848407,"about_ca_system_score_gemma":0.0007390566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00302549,"about_ca_topic_score_gemma":0.002253222,"domain_scores_codex":[0.9996616,0.00009718598,0.00001597828,0.00004908093,0.0001535085,0.00002274292],"domain_scores_gemma":[0.9997126,0.00009206603,0.00002087333,0.00003084879,0.000129712,0.00001392715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002845753,0.0001169436,0.001504536,0.0007826595,0.0001776564,0.000690228,0.0004644526,0.3531643,0.1177319,0.1239894,0.008269066,0.3928243],"study_design_scores_gemma":[0.00002297621,0.00006207802,0.0003769248,0.00002646932,0.00002054952,0.0002282202,0.00002523308,0.9648453,0.007921968,0.007579327,0.01885627,0.00003458211],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005502028,0.0006170312,0.990994,0.00009353265,0.0002283516,0.00003062926,0.00002876337,0.00009897499,0.002406729],"genre_scores_gemma":[0.2745751,0.002100265,0.7088066,0.0002417597,0.0003216685,0.0002536898,0.0001658074,0.0001515182,0.01338364],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00302549,"threshold_uncertainty_score":0.006588519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06338575499498691,"score_gpt":0.4107134323479008,"score_spread":0.3473276773529139,"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."}}