{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004300618,0.0004800613,0.0004993513,0.002514502,0.0004981141,0.0006715332,0.0004818061,0.0003378559,0.005824414],"category_scores_gemma":[0.002071278,0.000202534,0.0001869119,0.003733391,0.0002470032,0.0005425295,0.000562397,0.0003937522,0.002988223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000299652,"about_ca_system_score_gemma":0.0006134093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002080878,"about_ca_topic_score_gemma":0.002929051,"domain_scores_codex":[0.9993271,0.00006593083,0.00005328863,0.0001172332,0.000390452,0.00004603841],"domain_scores_gemma":[0.9990947,0.00009519653,0.00008365902,0.0001672162,0.0005260512,0.00003314164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005477504,0.0001389395,0.03245657,0.0006900949,0.00007072356,0.0007750234,0.0008397594,0.008203008,0.3849305,0.01387688,0.02066314,0.5368075],"study_design_scores_gemma":[0.00005812559,0.0005925673,0.104006,0.00007956207,0.0001005793,0.001206248,0.0008142409,0.1462688,0.5399019,0.007610365,0.1991733,0.0001883801],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2087475,0.0005933582,0.7331781,0.0002789453,0.0003649227,0.0009602823,0.01402257,0.01394983,0.02790445],"genre_scores_gemma":[0.5369934,0.0004982789,0.4352449,0.0001473054,0.0001716032,0.0008313773,0.01020453,0.0009068394,0.01500168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005824414,"threshold_uncertainty_score":0.01948464,"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."}}