{"id":"W2128891491","doi":"10.1109/oceans.2008.5151989","title":"Improved torpedo range estimation using modified fast orthogonal search techniques","year":2008,"lang":"en","type":"article","venue":"","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Royal Military College of Canada; Sonaca (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chirp; Range (aeronautics); Path (computing); SIGNAL (programming language); Algorithm; Mathematics; Matched filter; Acoustics; Filter (signal processing); Computer science; Physics; Engineering; Computer vision; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003387681,0.0001231574,0.0001320439,0.0001746819,0.0003016467,0.00007375137,0.0002135165,0.00008524388,0.00247408],"category_scores_gemma":[0.00002543808,0.00009813483,0.00004233237,0.0002474589,0.0001472838,0.0003168108,0.0000260513,0.0001966859,0.0001116226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001234328,"about_ca_system_score_gemma":0.0001623696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004272953,"about_ca_topic_score_gemma":0.0004759208,"domain_scores_codex":[0.9985696,0.0000750516,0.0001911161,0.0002561641,0.0004881253,0.0004199111],"domain_scores_gemma":[0.9994364,0.00008794908,0.00002537576,0.0001824582,0.0001108155,0.0001569634],"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":[0.0004265213,0.0001704359,0.2815657,0.0001598699,0.00009132995,0.000254078,0.001380253,0.3864871,0.05442815,0.00008669333,0.0010297,0.2739202],"study_design_scores_gemma":[0.0001535399,0.00008531295,0.009825032,0.000005099977,0.000003930092,0.00006875538,0.00003674013,0.979553,0.009984023,0.0001206177,0.00002724829,0.0001366772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4732136,0.00002350498,0.5141197,0.00005772186,0.00004743987,0.0002839793,0.0000323601,0.0001401035,0.01208157],"genre_scores_gemma":[0.9139369,0.00002294009,0.08502072,0.00005590875,0.00008304254,0.00000136252,0.00005753159,0.000005481528,0.0008161549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5930659,"threshold_uncertainty_score":0.9984378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06960818736324062,"score_gpt":0.2924385901696043,"score_spread":0.2228304028063637,"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."}}