{"id":"W7123337241","doi":"10.1109/icspis67605.2025.11318387","title":"SceneMixer: Exploring Convolutional Mixing Networks for Remote Sensing Scene Classification","year":2025,"lang":"","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Convolutional neural network; Land cover; Pointwise; Identification (biology); Feature extraction; Computation; Remote sensing application; Channel (broadcasting)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001161543,0.000765219,0.0007095778,0.0006985048,0.0008419732,0.0005073206,0.0003645054,0.0006004045,0.00003385693],"category_scores_gemma":[0.0007817138,0.0009660216,0.0003903563,0.001340949,0.0002443722,0.0007470903,0.0001270962,0.0007425069,0.00005895493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001654889,"about_ca_system_score_gemma":0.0003194545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008640712,"about_ca_topic_score_gemma":0.00003188772,"domain_scores_codex":[0.9953458,0.0001652245,0.001572992,0.001243184,0.0004295229,0.001243226],"domain_scores_gemma":[0.9964133,0.0009458629,0.0003205953,0.001197074,0.0008832166,0.0002399387],"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":[0.0001395979,0.00004313677,0.00009120948,0.0007124293,0.0003338273,0.000004978088,0.0001950196,0.1232738,0.1012502,0.007049398,0.005104461,0.761802],"study_design_scores_gemma":[0.001180517,0.00002831923,0.003211427,0.001476744,0.0002553346,0.00001663417,0.0003967732,0.9644429,0.01445306,0.001171968,0.01257757,0.0007887499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006143577,0.001662425,0.9707481,0.002212956,0.006840541,0.001457632,0.00001291489,0.0008887501,0.01003308],"genre_scores_gemma":[0.7153568,0.0009922544,0.2794701,0.0002231297,0.001113216,0.000007815275,0.0001543312,0.0001686648,0.002513728],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8411691,"threshold_uncertainty_score":0.999279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07059593135919698,"score_gpt":0.277557471114831,"score_spread":0.2069615397556341,"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."}}