{"id":"W2314192417","doi":"10.1002/jtsa.12074","title":"A FAST FRACTIONAL DIFFERENCE ALGORITHM","year":2014,"lang":"en","type":"article","venue":"Journal of Time Series Analysis","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Mathematics; Algorithm; Applied mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009152573,0.0001096967,0.0003989717,0.0004161178,0.0001206086,0.0002414079,0.0006383901,0.00004304853,0.000204806],"category_scores_gemma":[0.0001301499,0.00008392041,0.0004119302,0.001012846,0.00004076832,0.0007271262,0.00008885081,0.000184636,0.00004148492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002941163,"about_ca_system_score_gemma":0.00004907681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001372713,"about_ca_topic_score_gemma":0.00000155584,"domain_scores_codex":[0.9985886,0.0002304535,0.0003927148,0.0001485229,0.0004762326,0.0001634741],"domain_scores_gemma":[0.9986639,0.0001790271,0.0004046777,0.0002800032,0.000362141,0.0001102752],"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":[0.00008023724,0.0001938588,0.001376437,0.00001081611,0.002846445,0.0001204382,0.0006131381,0.008561996,0.01098362,0.002352694,0.002613845,0.9702465],"study_design_scores_gemma":[0.0009032923,0.0007099354,0.02931778,0.00003494217,0.001395094,0.0005308861,0.00005615598,0.9271154,0.005206222,0.01522198,0.01901961,0.00048867],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001943887,0.00007751905,0.9959964,0.000932148,0.0001489531,0.00001190928,0.000001175968,0.00001596407,0.0008720547],"genre_scores_gemma":[0.03681411,0.00003955602,0.9553556,0.0004037055,0.0004355536,6.620216e-7,0.000001705585,0.000007935982,0.006941209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9697578,"threshold_uncertainty_score":0.3422175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007466335023744672,"score_gpt":0.2459587920183066,"score_spread":0.2384924569945619,"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."}}