{"id":"W4387951345","doi":"10.1109/ccece58730.2023.10288845","title":"Analysis of Experimental Data Fusion Schemes for Underwater Communication over a Hydrophone Array","year":2023,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Carleton University","funders":"","keywords":"Underwater acoustic communication; Underwater; Hydrophone; Computer science; Projector; Distortion (music); Channel (broadcasting); SIGNAL (programming language); Acoustics; Noise (video); Frame (networking); Energy (signal processing); Sea trial; Telecommunications; Remote sensing; Geology; Engineering; Artificial intelligence; Physics; Marine engineering; Bandwidth (computing)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001939708,0.0003892593,0.000339932,0.0005112949,0.0004842874,0.0003761424,0.0005260494,0.0004817409,0.001111543],"category_scores_gemma":[0.00604627,0.000150382,0.000290906,0.0005680924,0.0006512425,0.0006317761,0.000385868,0.0003883703,0.0001617858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000654535,"about_ca_system_score_gemma":0.0004222001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001193654,"about_ca_topic_score_gemma":0.001201207,"domain_scores_codex":[0.9989105,0.000249331,0.00008422682,0.0001245103,0.0005268058,0.0001046558],"domain_scores_gemma":[0.9965026,0.002002811,0.0003173121,0.0002958712,0.0008308857,0.00005059313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002641824,0.0007722135,0.006165428,0.000925332,0.0002327456,0.0002335683,0.0005207011,0.2303716,0.6186502,0.007020477,0.0007696109,0.1316963],"study_design_scores_gemma":[0.00009073617,0.002422231,0.01241215,0.00003545213,0.00007860623,0.0001988621,0.0002271862,0.6099553,0.3716218,0.001541721,0.001355579,0.00006043167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8694938,0.0003448032,0.1273705,0.0001256553,0.00004820989,0.0001829528,0.0002731276,0.0001854264,0.001975527],"genre_scores_gemma":[0.9729916,0.0001298523,0.02614779,0.00001601925,0.000006248724,0.00009374137,0.0001903946,0.00001356554,0.0004106661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001939708,"threshold_uncertainty_score":0.01025832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05945250887878525,"score_gpt":0.3031367265878572,"score_spread":0.243684217709072,"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."}}