{"id":"W1964019662","doi":"10.1081/sta-100104350","title":"MULTI-FREQUENTIAL PERIODOGRAM ANALYSIS AND THE DETECTION OF PERIODIC COMPONENTS IN TIME SERIES","year":2001,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Estimator; Series (stratigraphy); Least-squares function approximation; Autoregressive model; Statistics; Trigonometric functions; Applied mathematics; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002471941,0.0002728176,0.0003341196,0.001998028,0.0002106958,0.0005896139,0.0003519024,0.0003666417,0.0008233881],"category_scores_gemma":[0.01309008,0.0001476297,0.0002983874,0.001097932,0.0005946202,0.0009835557,0.000513153,0.0003752375,0.0001554529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001981215,"about_ca_system_score_gemma":0.0002399654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005088106,"about_ca_topic_score_gemma":0.0005400288,"domain_scores_codex":[0.9992648,0.0003713136,0.00004539857,0.0001369891,0.0001467229,0.0000348146],"domain_scores_gemma":[0.9924271,0.005849847,0.0008225664,0.0003820399,0.0004319111,0.00008654698],"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":[0.0007067833,0.0001583566,0.05628825,0.0005426946,0.000309633,0.0009571491,0.0007968739,0.2051783,0.06372328,0.08019264,0.001405101,0.5897411],"study_design_scores_gemma":[0.000009834694,0.00007597,0.03605536,0.00003161325,0.00003296405,0.0003505294,0.00009361524,0.9263568,0.007489952,0.02847302,0.000999686,0.00003063801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2274414,0.0005314146,0.7702482,0.0001465023,0.00002865143,0.00003483726,0.0001224238,0.0001762914,0.001270342],"genre_scores_gemma":[0.8581453,0.0001514284,0.141224,0.00001538847,0.00003337087,0.00002703778,0.00008547441,0.00002772144,0.0002901751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002471941,"threshold_uncertainty_score":0.01307303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02996039654467612,"score_gpt":0.3732688548245003,"score_spread":0.3433084582798241,"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."}}