{"id":"W4254515680","doi":"10.21236/ada618033","title":"Bayesian Inversion of Seabed Scattering Data","year":2014,"lang":"en","type":"report","venue":"","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":"Seabed; Inversion (geology); Geology; Bayesian probability; Oceanography; Geodesy; Remote sensing; Computer science; Artificial intelligence; Seismology","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":[0.001346173,0.0005065162,0.0005386298,0.0009106238,0.0002025091,0.0009118618,0.0008427532,0.0005332172,0.001394018],"category_scores_gemma":[0.007093771,0.0007005468,0.0003777443,0.0007627059,0.0004810402,0.001601921,0.0007705351,0.001005587,0.0007393429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005583288,"about_ca_system_score_gemma":0.001192384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007137039,"about_ca_topic_score_gemma":0.01417718,"domain_scores_codex":[0.9993491,0.000219618,0.00003543078,0.0001141064,0.0002236281,0.00005825354],"domain_scores_gemma":[0.9983589,0.0008035264,0.0001579531,0.0001893396,0.000436388,0.00005382886],"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":[0.0001440891,0.0000650853,0.004645694,0.0001180842,0.00007815139,0.00005545538,0.0000727629,0.8594737,0.009061464,0.01735978,0.002011989,0.1069137],"study_design_scores_gemma":[0.000008217017,0.000007500332,0.0007502643,0.00001035121,0.00000406455,0.00001073263,0.00001081639,0.9922659,0.0009104369,0.005596446,0.0004178766,0.00000733497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02560091,0.0001191751,0.9721858,0.0001166,0.00001544565,0.00001787836,0.0002410041,0.0003256279,0.001377572],"genre_scores_gemma":[0.6901826,0.0006174286,0.3031507,0.0001300985,0.00005765898,0.00009368585,0.002090145,0.0001938663,0.003483708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007137039,"threshold_uncertainty_score":0.01419097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1068853626847056,"score_gpt":0.3148261254820048,"score_spread":0.2079407627972992,"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."}}