{"id":"W1972650637","doi":"10.1121/1.3097770","title":"The impact of ocean sound speed variability on the uncertainty of geoacoustic parameter estimates","year":2009,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Speed of sound; Geology; Inversion (geology); Empirical orthogonal functions; Water column; Waves and shallow water; Acoustics; Underwater acoustics; Bayesian probability; Oceanography; Underwater; Statistics; Mathematics; Seismology; Climatology; 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":[0.01121232,0.0005838544,0.0006524564,0.001234614,0.0005337183,0.001379563,0.0006786182,0.000740367,0.0003205472],"category_scores_gemma":[0.07961449,0.0007809113,0.0005717828,0.0009380276,0.00111236,0.001909753,0.001407239,0.001145595,0.0001103434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007173971,"about_ca_system_score_gemma":0.000843704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00502553,"about_ca_topic_score_gemma":0.005254321,"domain_scores_codex":[0.9938205,0.002011036,0.0005520715,0.001353835,0.001860342,0.000402216],"domain_scores_gemma":[0.8934694,0.09077499,0.006239878,0.005398435,0.003838683,0.0002786033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001338726,0.0001010603,0.1919703,0.0002535907,0.0008667613,0.0006897986,0.0008223253,0.6972104,0.03178715,0.003048134,0.0005043958,0.07140727],"study_design_scores_gemma":[0.00007128152,0.0002647449,0.2689472,0.00009522436,0.0002879842,0.0006415118,0.0002999466,0.6853713,0.03681392,0.005805098,0.001125891,0.0002758694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8606306,0.0004227874,0.1368006,0.0002393471,0.00004219437,0.00002667456,0.0003798982,0.000239178,0.001218696],"genre_scores_gemma":[0.9941477,0.00008147896,0.005344451,0.00002580131,0.0000176668,0.000009370478,0.0002272243,0.00008624233,0.00006011631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01121232,"threshold_uncertainty_score":0.05929714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02327611391627612,"score_gpt":0.2885340614587458,"score_spread":0.2652579475424697,"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."}}