{"id":"W1986459416","doi":"10.1121/1.4708090","title":"Assessment of geoacoustic inversion methods","year":2012,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Inversion (geology); Ground truth; Benchmarking; Geology; Waves and shallow water; Consistency (knowledge bases); Acoustics; Transmission loss; Computer science; Seismology; Oceanography; Machine learning; Telecommunications; 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":[0.01993702,0.001273072,0.0007205197,0.002595753,0.0006345296,0.002057812,0.001666549,0.001701585,0.003026764],"category_scores_gemma":[0.06357632,0.0004099756,0.0007262193,0.001227231,0.0008003406,0.002672979,0.002391131,0.001046287,0.0008217511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009669071,"about_ca_system_score_gemma":0.00212022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003078627,"about_ca_topic_score_gemma":0.002492671,"domain_scores_codex":[0.9869332,0.005203397,0.0007302435,0.0006583818,0.006201986,0.000272743],"domain_scores_gemma":[0.9482309,0.0294465,0.002420795,0.003711608,0.01580034,0.0003899055],"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":[0.0009282063,0.000300956,0.02291727,0.001044078,0.000416085,0.0001660591,0.0004971546,0.231211,0.01461337,0.01551292,0.003434973,0.7089577],"study_design_scores_gemma":[0.0001966016,0.0008546452,0.01829811,0.0004513433,0.0001601507,0.0005534859,0.0004486371,0.9213566,0.03451102,0.009124013,0.01389388,0.0001515801],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1325403,0.003356744,0.8407941,0.001793482,0.0002635971,0.0004743236,0.0009159067,0.001876899,0.01798464],"genre_scores_gemma":[0.5257266,0.001583981,0.4666714,0.0003396024,0.0001460531,0.000374846,0.001180773,0.0005761179,0.003400529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01993702,"threshold_uncertainty_score":0.1054383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0351025154763506,"score_gpt":0.3403430649442903,"score_spread":0.3052405494679398,"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."}}