{"id":"W7125942639","doi":"10.1109/smc58881.2025.11342542","title":"Lightweight and Dynamic Content-Augmented Object Detection for UAVs","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Object detection; Feature extraction; Software deployment; Feature (linguistics); Benchmark (surveying); Representation (politics); Pyramid (geometry); Edge detection","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":[0.0001213207,0.0003053099,0.0003047644,0.0002142294,0.0006649043,0.0002345977,0.0005141968,0.0001379503,0.0000134708],"category_scores_gemma":[0.00005367789,0.0002920647,0.0001170899,0.001033856,0.000137762,0.0004982768,0.0003646752,0.000187684,0.00001783278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001550528,"about_ca_system_score_gemma":0.00007278445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001595021,"about_ca_topic_score_gemma":0.0002346029,"domain_scores_codex":[0.9978141,0.00005527544,0.0005032984,0.0009806845,0.0001495177,0.0004971524],"domain_scores_gemma":[0.9983614,0.0004124246,0.0001665695,0.00070274,0.0002296287,0.0001272097],"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":[0.00009067487,0.0001353165,0.00007445747,0.00009974714,0.0001035389,0.000001361571,0.00009837859,0.0001632772,0.05158114,0.0860839,0.0005591456,0.8610091],"study_design_scores_gemma":[0.00137137,0.000250397,0.001677184,0.00009106709,0.00007505059,0.00001144828,0.00005341298,0.9118496,0.04489879,0.01845665,0.02090515,0.0003598901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006394487,0.001864177,0.9822589,0.004844137,0.0009959139,0.001921942,0.00001031361,0.0002428698,0.001467258],"genre_scores_gemma":[0.9456432,0.000863017,0.03526936,0.001185804,0.00005803259,0.0004922869,0.00000616872,0.00001874213,0.01646336],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9469895,"threshold_uncertainty_score":0.9999532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882696300876321,"score_gpt":0.2774377658271535,"score_spread":0.2586108028183903,"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."}}