{"id":"W2052548655","doi":"10.1051/matecconf/20152001004","title":"Spectrum construction for non stationary vibration: Application to a moving flexible robot","year":2015,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Hydro-Québec","keywords":"Vibration; Autoregressive model; Modal; Computation; Computer science; Autoregressive–moving-average model; Block (permutation group theory); Robot; Representation (politics); Sliding window protocol; Trajectory; Modal analysis; Series (stratigraphy); Algorithm; Mathematics; Artificial intelligence; Acoustics; Window (computing); Physics","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":[0.00009632208,0.0001006939,0.0001861262,0.000139865,0.00005361682,0.00004204153,0.0001407373,0.00006581177,0.0004249766],"category_scores_gemma":[0.00005745807,0.00009847016,0.00003811699,0.000307934,0.00005054947,0.0001206703,0.0000231328,0.00004426583,0.00001755281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004440698,"about_ca_system_score_gemma":0.0004204949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001038921,"about_ca_topic_score_gemma":0.0000302567,"domain_scores_codex":[0.9992384,0.00000484253,0.0002437727,0.0001962926,0.0001821662,0.0001345556],"domain_scores_gemma":[0.9993927,0.00005652229,0.0001542244,0.0001514192,0.0001689585,0.00007613517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005007781,0.0002412671,0.04273615,0.0005842603,0.000228726,9.198936e-7,0.0006542361,0.002857954,0.8402295,0.09577666,0.003198613,0.01299094],"study_design_scores_gemma":[0.0004412,0.00009724495,0.0007376382,0.00002217337,0.00006084548,0.000003580279,0.002090221,0.007297065,0.9744691,0.01105663,0.003559614,0.0001647201],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4072556,0.0001318718,0.5050097,0.001608233,0.0001462214,0.0003532972,0.00008303643,0.0001920003,0.08521999],"genre_scores_gemma":[0.9885773,0.000007902943,0.01048491,0.00003872066,0.0001028525,0.00008952169,0.00007276519,0.000007931344,0.0006180794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5813217,"threshold_uncertainty_score":0.4653196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02966475830888653,"score_gpt":0.2951345855797259,"score_spread":0.2654698272708394,"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."}}