{"id":"W2037976666","doi":"10.1115/imece2003-42428","title":"Quintic Spline Interpolation With Minimal Feed Fluctuation","year":2003,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spline (mechanical); Spline interpolation; Parameterized complexity; Mathematics; Smoothing spline; Jerk; Arc length; Quintic function; Interpolation (computer graphics); Control theory (sociology); Algorithm; Applied mathematics; Mathematical analysis; Arc (geometry); Computer science; Bilinear interpolation; Acceleration; Geometry; Engineering; Structural engineering; Physics; Artificial intelligence; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00005284118,0.0001264139,0.0001279597,0.00009520449,0.00003526869,0.00002233676,0.00005780005,0.00003578432,0.0001116473],"category_scores_gemma":[0.00001467045,0.0001082748,0.00003199719,0.00009298998,0.00001582208,0.0001664755,0.000008776775,0.0001072906,0.00002831013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008573552,"about_ca_system_score_gemma":0.000003248671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005423925,"about_ca_topic_score_gemma":0.000009652125,"domain_scores_codex":[0.9994282,0.0000116033,0.000152686,0.0001359115,0.0001100309,0.0001615556],"domain_scores_gemma":[0.9997525,0.00002219595,0.00002815383,0.0001444473,0.00001293209,0.0000397471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001320636,0.0001147131,0.002870555,0.0004037404,0.0004734554,0.00005107851,0.001332716,0.5014655,0.3784535,0.002018732,0.000704332,0.1119796],"study_design_scores_gemma":[0.0002202806,0.00005541511,0.004119586,0.0000360928,0.00003530926,0.0000108573,0.00006244558,0.04942888,0.941109,0.001372086,0.00325961,0.0002904643],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5551338,0.00002572467,0.4414256,0.00001256486,0.0000286095,0.00007499698,4.181524e-7,0.0004485424,0.0028497],"genre_scores_gemma":[0.9616678,0.000005388679,0.03815334,0.00001899899,0.00002731059,0.00001281607,0.000006850546,0.00002735292,0.00008009921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5626555,"threshold_uncertainty_score":0.4415319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005858038061409717,"score_gpt":0.2086460669752586,"score_spread":0.2027880289138489,"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."}}