{"id":"W2148555353","doi":"10.1109/ccece.1999.808020","title":"Interpolation using elliptic sine function: a digital signal processing approach","year":2003,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Interpolation (computer graphics); Sine; Bilinear interpolation; Digital filter; Jacobian matrix and determinant; Realization (probability); Trigonometric interpolation; Computer science; Signal processing; Algorithm; Mathematics; Linear interpolation; Elliptic filter; SIGNAL (programming language); Digital signal processing; Filter (signal processing); Multivariate interpolation; Bicubic interpolation; Low-pass filter; Applied mathematics; Artificial intelligence; Prototype filter; Computer vision; Computer hardware; Geometry","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":[0.0005133692,0.0003901575,0.0004279512,0.0007359294,0.0003636012,0.0007776727,0.000528094,0.0007326485,0.002876966],"category_scores_gemma":[0.0009247877,0.0001990857,0.0004435725,0.0008688528,0.0006512611,0.0009920322,0.0005373337,0.0006971336,0.0009410792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003397407,"about_ca_system_score_gemma":0.000417849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003432519,"about_ca_topic_score_gemma":0.0002954015,"domain_scores_codex":[0.9997033,0.00005553371,0.00001751954,0.00004675712,0.0001559989,0.00002081019],"domain_scores_gemma":[0.9997807,0.00008119619,0.00001893347,0.00003840089,0.00006827091,0.00001244541],"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":[0.0003107583,0.00009100336,0.0008609085,0.0004659196,0.00005391812,0.0004423939,0.0004337522,0.0901448,0.08437787,0.347151,0.004010997,0.4716567],"study_design_scores_gemma":[0.00005426411,0.0003966647,0.000583462,0.00009945881,0.00005706017,0.001171796,0.0001063439,0.7234536,0.06911295,0.110102,0.09478842,0.00007388051],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00403613,0.0005030293,0.9897012,0.0001416092,0.0001084406,0.00002192746,0.00001421695,0.0002068517,0.005266606],"genre_scores_gemma":[0.3090671,0.004002423,0.6673266,0.0003214933,0.0004567857,0.00009992186,0.0001073452,0.0001490357,0.01846926],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002876966,"threshold_uncertainty_score":0.009624422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04920391103580082,"score_gpt":0.2604686468335296,"score_spread":0.2112647357977288,"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."}}