{"id":"W2999999793","doi":"10.1109/joe.2019.2960879","title":"An Experimental Benchmark for Geoacoustic Inversion Methods","year":2020,"lang":"en","type":"article","venue":"IEEE Journal of Oceanic Engineering","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Defence Research and Development Canada","funders":"Office of Naval Research","keywords":"Inversion (geology); Benchmark (surveying); Sonar; Geology; Computer science; Attenuation; Underwater; Seabed; Waves and shallow water; Acoustics; Geophysics; Seismology; Artificial intelligence; Geodesy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045936,0.0009603309,0.0003418224,0.001156225,0.000689582,0.001048176,0.001410017,0.001313037,0.003541122],"category_scores_gemma":[0.01631715,0.0003217756,0.0004947664,0.001079983,0.0009919249,0.001627303,0.001868979,0.001117795,0.001108146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005318601,"about_ca_system_score_gemma":0.0006445884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001703244,"about_ca_topic_score_gemma":0.00193904,"domain_scores_codex":[0.9965968,0.00102094,0.0003872477,0.0004413142,0.001369049,0.0001845957],"domain_scores_gemma":[0.989893,0.004354363,0.0005497771,0.001669964,0.00335776,0.0001750067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002886924,0.003687534,0.02622486,0.001744013,0.0003549393,0.0003871927,0.0008269652,0.2591228,0.3273979,0.01157995,0.007440054,0.3583469],"study_design_scores_gemma":[0.0003936352,0.005375961,0.01940258,0.000206077,0.000147917,0.0006763301,0.0009172603,0.4974286,0.4485363,0.006442958,0.02022964,0.000242744],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5505106,0.001206388,0.4288937,0.0006293611,0.0006170881,0.0007457088,0.002826708,0.00233914,0.01223147],"genre_scores_gemma":[0.8139744,0.0004138956,0.1777942,0.0001912419,0.0001287461,0.0006489139,0.004162685,0.0003925072,0.002293366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0045936,"threshold_uncertainty_score":0.02429354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04011369039094436,"score_gpt":0.3123288788384476,"score_spread":0.2722151884475032,"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."}}