{"id":"W4399181523","doi":"10.1007/s11227-024-06245-z","title":"Real-time RSS-based target localization for UWSNs using an IDE-BP neural network","year":2024,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"RSS; Artificial neural network; Computer science; Artificial intelligence; World Wide Web","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":[0.0002576424,0.0004485165,0.0003782877,0.0002328659,0.0002815325,0.000367881,0.000612915,0.0005312858,0.001256173],"category_scores_gemma":[0.0005614745,0.0002020691,0.000188658,0.0003281961,0.0002125175,0.0005403012,0.0004294815,0.0005672811,0.0004133859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003174809,"about_ca_system_score_gemma":0.0004856224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008076472,"about_ca_topic_score_gemma":0.007643675,"domain_scores_codex":[0.9998461,0.0000220675,0.000009032885,0.00004883197,0.00004859467,0.00002523545],"domain_scores_gemma":[0.999844,0.00003730795,0.00001223514,0.00001135114,0.0000849374,0.00001006154],"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":[0.0006936002,0.0002098445,0.003465503,0.000131327,0.00008496477,0.0001471986,0.0000995727,0.3843008,0.05235102,0.001921095,0.002883913,0.5537112],"study_design_scores_gemma":[0.000006416393,0.00002928563,0.000354314,0.000003075658,0.000008431954,0.00001354866,0.000006875859,0.9952366,0.003939768,0.0001562636,0.0002406285,0.000004829934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09381748,0.0004546258,0.8992339,0.0002340948,0.0002320224,0.00003756695,0.00008060986,0.00150347,0.004406122],"genre_scores_gemma":[0.9203976,0.0001973735,0.07421045,0.00008587052,0.00004442762,0.00004617076,0.0001037778,0.00003521653,0.004879152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008076472,"threshold_uncertainty_score":0.01605892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03039635186001619,"score_gpt":0.2648545588389868,"score_spread":0.2344582069789707,"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."}}