{"id":"W3014244337","doi":"10.1088/1361-6382/ab8650","title":"New methods to assess and improve LIGO detector duty cycle","year":2020,"lang":"en","type":"article","venue":"Classical and Quantum Gravity","topic":"Pulsars and Gravitational Waves Research","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Indian Institute of Technology Gandhinagar; California Institute of Technology; Indo-US Science and Technology Forum; Massachusetts Institute of Technology; National Science Foundation","keywords":"LIGO; Detector; Physics; Interferometry; Gravitational wave; Noise (video); Gravitational-wave observatory; Duty cycle; Optics; Computer science; Artificial intelligence; Astronomy; Power (physics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003075218,0.0009938754,0.0008417576,0.003050518,0.0005619943,0.001344162,0.001315626,0.0008458996,0.001537499],"category_scores_gemma":[0.01398039,0.0004555006,0.0005457909,0.001123674,0.0004814819,0.001360068,0.0009349876,0.001317037,0.0008460851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052893,"about_ca_system_score_gemma":0.0009705371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005458514,"about_ca_topic_score_gemma":0.005881194,"domain_scores_codex":[0.9987079,0.0002698728,0.00009980031,0.0004594822,0.0003426696,0.0001202844],"domain_scores_gemma":[0.9942624,0.002324905,0.001229194,0.0007944814,0.001169914,0.0002190309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003578353,0.0004180043,0.1679921,0.0001233099,0.000268662,0.00008638976,0.0001936128,0.4557708,0.009105638,0.003330825,0.003745269,0.3586075],"study_design_scores_gemma":[0.000006496356,0.00002273093,0.007414316,0.00001094617,0.00001105293,0.0000173374,0.00001230849,0.9883913,0.002277659,0.001237026,0.0005852866,0.00001361096],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.277859,0.0006288899,0.7096881,0.000431646,0.000149591,0.0001640725,0.001128774,0.005103116,0.004846797],"genre_scores_gemma":[0.8972719,0.00008161232,0.09994218,0.0001008099,0.00006318781,0.0001028261,0.0008970788,0.0002241643,0.001316189],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005458514,"threshold_uncertainty_score":0.01626348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04211451032808117,"score_gpt":0.3898682652090921,"score_spread":0.347753754881011,"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."}}