{"id":"W2112425134","doi":"10.1109/oceans.2008.5151909","title":"Reconstruction and fusion of perceptual features for automatic classification of sonar echoes","year":2008,"lang":"en","type":"article","venue":"","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Research and Development Canada; Pennsylvania State University","keywords":"Sonar; Computer science; Bandwidth (computing); Artificial intelligence; Marine mammals and sonar; Clutter; Sonar signal processing; Speech recognition; Underwater; Pattern recognition (psychology); Computer vision; Radar; Signal processing; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007009706,0.0004351541,0.0004606841,0.0008827149,0.0002088721,0.0005352328,0.0003476234,0.0004176694,0.0006098095],"category_scores_gemma":[0.002771157,0.0002406796,0.0003465632,0.000584799,0.0003172271,0.0007300763,0.0006869916,0.0004885338,0.0003133233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001758797,"about_ca_system_score_gemma":0.000292668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008948709,"about_ca_topic_score_gemma":0.001208766,"domain_scores_codex":[0.999542,0.00009217515,0.0000292938,0.00009343002,0.0001814404,0.00006159913],"domain_scores_gemma":[0.9990301,0.0004201909,0.0001066345,0.0001485367,0.0002513099,0.00004326924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001163495,0.0002370239,0.004588705,0.000120764,0.00006928129,0.0001516607,0.00024597,0.0190972,0.530489,0.000488944,0.0002985459,0.4430495],"study_design_scores_gemma":[0.00008454794,0.0008911322,0.06188032,0.00002378393,0.0001701857,0.0005437349,0.0002653961,0.6515707,0.2819552,0.001194606,0.001304901,0.0001155941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.618133,0.0001844695,0.3800716,0.00005165383,0.00002698047,0.00005948983,0.0001344345,0.0006936523,0.0006447686],"genre_scores_gemma":[0.8840674,0.00007463637,0.1151519,0.00001254763,0.00001159936,0.00003817473,0.0002062552,0.00003989678,0.000397629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008948709,"threshold_uncertainty_score":0.003707111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04547713100042073,"score_gpt":0.2598942630847377,"score_spread":0.214417132084317,"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."}}