{"id":"W4280614681","doi":"10.31223/x52s80","title":"Broadband Ocean Bottom Seismometer Noise Properties","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Seismic Waves and Analysis","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Lamont-Doherty Earth Observatory, Columbia University; Ocean Life Institute, Woods Hole Oceanographic Institution; Woods Hole Oceanographic Institution; National Science Foundation","keywords":"Seismometer; Microseism; Noise (video); Seismology; Broadband; Geology; Ambient noise level; Seismic noise; Acoustics; Remote sensing; Computer science; Telecommunications; Physics; Oceanography","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":[0.0002704676,0.0002843319,0.0003860192,0.0001957119,0.0002252478,0.0002326591,0.0005476888,0.0001335809,0.0532974],"category_scores_gemma":[0.00001741492,0.0001998287,0.000290893,0.0001961611,0.00006926239,0.00009124212,0.0001986799,0.0006638231,0.0002747519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008204127,"about_ca_system_score_gemma":0.0001092871,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01886258,"about_ca_topic_score_gemma":0.0001968286,"domain_scores_codex":[0.9981958,0.0001054115,0.0003186165,0.0005883875,0.000446177,0.0003456531],"domain_scores_gemma":[0.9991689,0.0000388812,0.0001199418,0.0004981736,0.00002998005,0.0001440812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001137833,0.00009967745,0.7595674,0.0003950883,0.0008787939,0.0001539568,0.000929939,0.1271292,0.00001688956,0.00005366475,0.07411437,0.0365472],"study_design_scores_gemma":[0.0005473723,0.0002527663,0.2176271,0.0001109722,0.0005287395,0.00002813355,0.002319991,0.3020918,0.00009423833,0.0052044,0.4690281,0.002166284],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9485614,0.002718455,0.0001084766,0.001839604,0.0010658,0.0002702096,0.000486307,0.0001558464,0.04479392],"genre_scores_gemma":[0.9559263,0.0003856162,0.0006774249,0.002126626,0.0002628997,0.00000154643,0.000939773,0.000009000977,0.0396708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5419403,"threshold_uncertainty_score":0.9876709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02596892612546986,"score_gpt":0.210540413272013,"score_spread":0.1845714871465432,"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."}}