{"id":"W4416683839","doi":"10.18280/mmep.121024","title":"A Hybrid Multiscale and CNN-Based Fusion Framework for Enhanced SAR–MS Image Integration","year":2025,"lang":"","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Image fusion; Image (mathematics); Fusion; Image processing; Pattern recognition (psychology); Image segmentation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004352729,0.0006370177,0.0007479576,0.000326239,0.0002113231,0.0002564956,0.0001787022,0.0003403375,0.00002761534],"category_scores_gemma":[0.0004353267,0.000641807,0.0001404333,0.0002446528,0.0001083305,0.0002584548,0.0001072609,0.0006759202,0.000005447806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001039558,"about_ca_system_score_gemma":0.00002429758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006697112,"about_ca_topic_score_gemma":2.973934e-7,"domain_scores_codex":[0.9975907,0.00002075958,0.0008702287,0.0006660687,0.0002065981,0.0006456284],"domain_scores_gemma":[0.9981898,0.0009426066,0.00009571281,0.0004346215,0.0001377616,0.0001994696],"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":[0.00004188383,0.0001192656,5.776614e-7,0.008321681,0.00005715109,0.000002100343,0.0006057172,0.8640647,0.07538559,0.0274146,0.00004268487,0.02394406],"study_design_scores_gemma":[0.0004641952,0.00008659146,8.426588e-7,0.005400293,0.00008126786,0.000003079812,0.00002282349,0.7402696,0.1089571,0.1440609,0.0002038429,0.000449438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01191348,0.001711227,0.9832472,0.0002051096,0.0002387856,0.001514038,0.00003089777,0.0008829943,0.0002562567],"genre_scores_gemma":[0.3868617,0.0004618224,0.6121686,0.00002366076,0.00004627672,0.000226521,0.0000123298,0.00008820108,0.0001108955],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3749482,"threshold_uncertainty_score":0.9996033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01251838851984866,"score_gpt":0.2474042484563719,"score_spread":0.2348858599365233,"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."}}