{"id":"W2361609301","doi":"","title":"Superconducting Gravimeter Data Analysis and Signal Detection","year":2008,"lang":"en","type":"article","venue":"Hydrographic Surveying and Charting","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fast Fourier transform; SIGNAL (programming language); Gravimeter; Noise (video); Spectral density; Computer science; Spectral analysis; Algorithm; Electrical engineering; Geography; Electronic engineering; Physics; Telecommunications; Engineering; Artificial intelligence; Optics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001283351,0.0001256257,0.0001945439,0.0002234417,0.00064463,0.0000791952,0.0001125442,0.00004242602,0.00005223841],"category_scores_gemma":[0.0000492781,0.0001133512,0.00004926488,0.0007781198,0.0001010153,0.0003143929,0.0000320613,0.0001384762,0.000004482107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":7.530783e-7,"about_ca_system_score_gemma":0.000006799886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007098093,"about_ca_topic_score_gemma":0.004476686,"domain_scores_codex":[0.9987408,0.0001476025,0.000200246,0.0004216427,0.0002208738,0.0002688655],"domain_scores_gemma":[0.9994215,0.0001265766,0.00007470262,0.0002311639,0.00003078321,0.0001152568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003849973,0.000005640455,0.944167,0.000006638556,0.0001110655,0.000004655284,0.0001934407,0.00002496045,0.001154326,3.423437e-7,0.000001110934,0.054327],"study_design_scores_gemma":[0.0001306175,0.00003489213,0.9758446,0.000007671483,0.000120263,0.00002336373,0.0001609802,0.02304699,0.0003480185,0.0000963827,0.0000324841,0.0001537093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987385,0.0006544503,0.0003319331,0.00001724868,0.00006581109,0.00005374349,0.00002871328,0.00003657522,0.00007308007],"genre_scores_gemma":[0.9993991,0.00008408774,0.0002530759,0.00003212617,0.00006435307,4.971365e-7,0.0001534209,0.000003367029,0.000009982749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05417329,"threshold_uncertainty_score":0.9995137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09338867046074303,"score_gpt":0.2374384336745702,"score_spread":0.1440497632138272,"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."}}