{"id":"W1941702124","doi":"10.1016/j.jsc.2015.11.005","title":"Faster sparse multivariate polynomial interpolation of straight-line programs","year":2015,"lang":"en","type":"article","venue":"Journal of Symbolic Computation","topic":"Polynomial and algebraic computation","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation of Sri Lanka; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Mathematics; Interpolation (computer graphics); Polynomial; Function (biology); Polynomial interpolation; Field (mathematics); Representation (politics); Multivariate statistics; Finite field; Applied mathematics; Degree (music); Line (geometry); Birkhoff interpolation; Algorithm; Mathematical optimization; Discrete mathematics; Algebra over a field; Linear interpolation; Pure mathematics; Mathematical analysis; Geometry; Computer science; Statistics; Artificial intelligence","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":[0.0006279638,0.0001492694,0.0003270324,0.0003312666,0.00003611338,0.0001094361,0.0004038182,0.00006502824,0.000004957592],"category_scores_gemma":[0.00007038454,0.0001269433,0.0001331447,0.0003996944,0.00004168789,0.0009026727,0.0001095251,0.0001683999,0.000009697589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007350859,"about_ca_system_score_gemma":0.000256037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004081614,"about_ca_topic_score_gemma":0.000005523237,"domain_scores_codex":[0.9981576,0.000127814,0.0008821534,0.0001683009,0.0004817819,0.000182408],"domain_scores_gemma":[0.9979759,0.00008117231,0.001008352,0.0001369744,0.0006153668,0.0001821711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002810272,0.0006593216,0.001282128,0.0000453674,0.0001420526,0.00002908621,0.01112443,0.03009872,0.009363861,0.00434792,0.001244119,0.941382],"study_design_scores_gemma":[0.00349677,0.001480543,0.01653438,0.0001986941,0.00004344104,0.0002328171,0.0002444052,0.9639815,0.00242348,0.01050153,0.0005791533,0.0002832576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3887144,0.00005328961,0.6095178,0.0004013455,0.0008901237,0.0001138395,9.140113e-7,0.00002662748,0.0002816803],"genre_scores_gemma":[0.9459107,0.000001766739,0.05357723,0.00004794126,0.000410226,0.000001216677,0.000005317754,0.000008713913,0.00003689023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9410987,"threshold_uncertainty_score":0.5176598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.046147414931284,"score_gpt":0.2875589054670081,"score_spread":0.2414114905357241,"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."}}