{"id":"W4386325744","doi":"10.18280/ts.400427","title":"Enhancement of Sonar Detection in Karst Caves Through Advanced Target Location and Image Fusion Algorithms","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Guizhou Institute of Technology","keywords":"Karst; Sonar; Cave; Geology; Artificial intelligence; Algorithm; Image fusion; Image (mathematics); Remote sensing; Computer science; Side-scan sonar; Computer vision; Pattern recognition (psychology); Geography; Archaeology; Paleontology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000261817,0.0001158109,0.000124095,0.0001463643,0.0001149362,0.00002286895,0.00007976785,0.00004054784,0.0001294364],"category_scores_gemma":[0.00005092041,0.0001172529,0.00002659212,0.0006813253,0.00008933341,0.0003079558,0.00003023964,0.00008942401,0.00003176317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006869575,"about_ca_system_score_gemma":0.00001914561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002256627,"about_ca_topic_score_gemma":0.00002056659,"domain_scores_codex":[0.9987413,0.0001006249,0.0003257467,0.0003489335,0.000293346,0.0001900211],"domain_scores_gemma":[0.9995955,0.00007927884,0.0001402861,0.0001065865,0.00004286605,0.00003543844],"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":[0.00005866676,0.00008714531,0.00005016418,0.00004208408,0.000001469685,0.000002885254,0.0007330565,0.0001495482,0.9604083,0.0002671671,0.00003706362,0.03816247],"study_design_scores_gemma":[0.0007891702,0.000204137,0.01282444,0.00003140006,0.000004036046,0.000004229196,0.0004051934,0.02630941,0.9576394,0.0007797424,0.0008922408,0.0001166349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9462132,0.00002797024,0.05218856,0.0004626136,0.0001692393,0.000469886,0.000009551052,0.0001037937,0.0003551928],"genre_scores_gemma":[0.9986442,0.0001540989,0.0007868924,0.0001413349,0.00003618001,0.00009775268,0.00001016643,0.00001239306,0.000117024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05243097,"threshold_uncertainty_score":0.4781436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02813420082788745,"score_gpt":0.2717269941697792,"score_spread":0.2435927933418917,"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."}}