{"id":"W4241638341","doi":"10.1142/s0218396x00000212","title":"MATCHED FIELD TOMOGRAPHIC INVERSION TO DETERMINE RANGE DEPENDENT GEOACOUSTIC PROPERTIES","year":2000,"lang":"en","type":"article","venue":"Journal of Computational Acoustics","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":"Broadband; Inversion (geology); Replica; Range (aeronautics); Geology; Tomography; Acoustics; Computer science; Seismology; Optics; Telecommunications; Physics; Materials science","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":[0.0001898392,0.000262472,0.0002056347,0.0005818332,0.0001363627,0.0003461066,0.0003078563,0.0003013966,0.001802118],"category_scores_gemma":[0.001153977,0.0001719792,0.0002150164,0.0005063873,0.0001886882,0.0006483526,0.0003492175,0.0002686395,0.0003906593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229644,"about_ca_system_score_gemma":0.0004380483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002960733,"about_ca_topic_score_gemma":0.003385371,"domain_scores_codex":[0.9999071,0.00001604874,0.000003656527,0.00001553223,0.00004618955,0.00001127416],"domain_scores_gemma":[0.9998322,0.00007162977,0.00001911628,0.00001995252,0.00004820452,0.00000897218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002539222,0.000106075,0.006001624,0.0001525743,0.00009586952,0.0001749595,0.0001076589,0.3523366,0.2001946,0.007197823,0.001958348,0.4314199],"study_design_scores_gemma":[0.00002088108,0.00003109934,0.001924133,0.000005736468,0.00001394383,0.00008645506,0.00002670838,0.9705113,0.0234354,0.001692333,0.002240095,0.00001197089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04503019,0.00008205086,0.9520393,0.00005456881,0.00001699424,0.00003830807,0.0001582061,0.0006181369,0.001962226],"genre_scores_gemma":[0.4935803,0.0001440788,0.5035899,0.00006972886,0.00002801004,0.00008966532,0.000489496,0.0001198663,0.001888968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002960733,"threshold_uncertainty_score":0.006028652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02754142347714053,"score_gpt":0.2408258963596727,"score_spread":0.2132844728825322,"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."}}