{"id":"W4229456586","doi":"10.1121/10.0010685","title":"Layered and gradient model parameterizations in geoacoustic inversion","year":2022,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Inversion (geology); Speed of sound; Homogeneous; Geology; Modal; Bayesian probability; Bayesian information criterion; Polynomial; Acoustic dispersion; Computer science; Acoustics; Mathematics; Mathematical analysis; Acoustic wave; Statistical physics; Physics; Materials science; Artificial intelligence","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":[0.002433209,0.0007907331,0.0006290876,0.0007866597,0.0003143441,0.001880235,0.001621285,0.001096061,0.0009242861],"category_scores_gemma":[0.01313101,0.0007318248,0.0007798657,0.0008540266,0.001130485,0.003619052,0.001942896,0.001878497,0.0003658342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008827935,"about_ca_system_score_gemma":0.00112115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007649148,"about_ca_topic_score_gemma":0.006382803,"domain_scores_codex":[0.9990556,0.0003608681,0.00005967942,0.0001523728,0.0002765677,0.00009493867],"domain_scores_gemma":[0.9978992,0.001208575,0.0002484494,0.0002861875,0.0002820353,0.00007544694],"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":[0.00006301312,0.00002360296,0.001623609,0.00006223642,0.00004995885,0.00004743678,0.00007114235,0.934653,0.004287348,0.03180623,0.0002721605,0.02704017],"study_design_scores_gemma":[0.000007391841,0.00001581823,0.0003933788,0.00001183862,0.000008204932,0.0000243613,0.00001971353,0.9803575,0.0009095463,0.01782049,0.000409619,0.00002219066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01605155,0.0001380507,0.9824337,0.0001315012,0.00002119634,0.00001901246,0.0000746161,0.0002071154,0.0009233709],"genre_scores_gemma":[0.6994798,0.0005462523,0.297357,0.0002461065,0.00006179306,0.0001498065,0.0004700935,0.0002807921,0.001408357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007649148,"threshold_uncertainty_score":0.01520926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02436297361263764,"score_gpt":0.2416360852144659,"score_spread":0.2172731116018282,"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."}}