{"id":"W2105451763","doi":"10.1109/tuffc.2010.1445","title":"The Allan Variance - challenges and opportunities","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Advanced Frequency and Time Standards","field":"Physics and Astronomy","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"Allan variance; Phase noise; Estimator; Noise (video); Spurious relationship; Aliasing; Noise floor; Electronic engineering; Bandwidth (computing); Computer science; Variance (accounting); Noise measurement; Telecommunications; Statistics; Engineering; Standard deviation; Mathematics; Noise reduction; Artificial intelligence","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":[0.0003247032,0.0002618528,0.000236777,0.00006795194,0.0008407775,0.0001123785,0.0001642548,0.00009808913,0.0001012688],"category_scores_gemma":[0.00000954433,0.0002013563,0.00008125061,0.00008881755,0.0003074449,0.0001859082,7.500791e-7,0.0007544111,0.00000363812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000156612,"about_ca_system_score_gemma":0.0001147504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004413763,"about_ca_topic_score_gemma":0.0001153318,"domain_scores_codex":[0.9987231,0.00005955636,0.0002572286,0.0003380348,0.0001932281,0.0004288321],"domain_scores_gemma":[0.9988099,0.0005070095,0.00009681832,0.000302818,0.0001140656,0.0001693462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004003874,0.00006488994,0.00002686927,0.000006585522,0.0001210949,0.000003175279,0.0001866286,0.00003105374,0.002600768,0.3992679,0.00002029593,0.5976307],"study_design_scores_gemma":[0.0090944,0.001892204,0.001029461,0.0001020789,0.0007071598,0.0001527357,0.001368052,0.01630191,0.009667563,0.8558424,0.1011821,0.002659985],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01515086,0.01197909,0.9056513,0.006697081,0.002062532,0.0009685378,0.0006064502,0.0001748293,0.0567093],"genre_scores_gemma":[0.9926568,0.00612,0.0003106353,0.000114891,0.0002483402,0.00008662393,0.000002822848,0.00002727038,0.0004326717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9775059,"threshold_uncertainty_score":0.8211071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532836225383043,"score_gpt":0.2308543489015896,"score_spread":0.2155259866477592,"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."}}