{"id":"W2127161079","doi":"10.1109/freq.1994.398259","title":"Frequency control of hydrogen masers using high accuracy calibrations","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Frequency and Time Standards","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Hydrogen maser; Frequency standard; Maser; Calibration; Series (stratigraphy); Noise (video); Computer science; Standard uncertainty; Control (management); Algorithm; Measurement uncertainty; Statistics; Mathematics; Physics; Engineering; Artificial intelligence; Electrical engineering; Optics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003351389,0.0001023466,0.0001563956,0.00003366782,0.00009659406,0.00001090073,0.00009027322,0.00002435309,0.01743076],"category_scores_gemma":[0.000008012009,0.00009157747,0.00008015472,0.000126019,0.00005979163,0.0003087227,0.000009254333,0.00007090528,0.00002956767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001509534,"about_ca_system_score_gemma":0.00002465219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003636087,"about_ca_topic_score_gemma":0.000002327474,"domain_scores_codex":[0.9993493,0.00002179433,0.0002216831,0.0001321614,0.0001075652,0.0001675216],"domain_scores_gemma":[0.9995533,0.00005667589,0.00009769354,0.0001834505,0.0000538582,0.00005498586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000882253,0.0002103712,0.03143524,0.00001367092,0.0002590768,0.000004432548,0.0002591334,0.00653141,0.03418415,0.9092159,0.0007198905,0.01715789],"study_design_scores_gemma":[0.008338704,0.0002734938,0.0008044644,0.0001145549,0.0004769418,0.000006978175,0.0006715569,0.1686487,0.2241285,0.5861,0.008732196,0.001703899],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2078134,0.0001595607,0.5882448,0.0002596656,0.0001660885,0.0003257145,0.0006797379,0.00005514831,0.2022959],"genre_scores_gemma":[0.9936923,0.000001307477,0.005470132,0.0000382137,0.000242772,0.000006473551,0.00001138066,0.00001102401,0.0005264354],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7858788,"threshold_uncertainty_score":0.9834675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169812102287428,"score_gpt":0.2516985979173726,"score_spread":0.2347173876886298,"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."}}