{"id":"W7125214462","doi":"10.1109/sensors59705.2025.11330353","title":"Leveraging TS2Vec to Enhance Radar-Based Object Detection Under Adverse Weather Conditions","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Object detection; Object (grammar); Adverse weather; Noise (video); Change 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":[0.0002314911,0.0005331275,0.0004104175,0.0007164403,0.0003472432,0.00008271512,0.0003338624,0.0001963094,0.0008394739],"category_scores_gemma":[0.0001180389,0.0006490919,0.0002087219,0.001233935,0.00009616508,0.000396714,0.000118971,0.0005659745,0.0002532302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001139251,"about_ca_system_score_gemma":0.000168012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001692824,"about_ca_topic_score_gemma":0.0001545323,"domain_scores_codex":[0.9976705,0.00008388253,0.0005662311,0.0007173124,0.0002606686,0.0007014179],"domain_scores_gemma":[0.9985219,0.0002283011,0.00006965389,0.0008629609,0.0001539302,0.0001633034],"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":[0.00009987832,0.0002050206,0.0001714075,0.0003945459,0.0003326365,0.0000281639,0.0005685757,0.2772677,0.6420731,0.003020675,0.005464416,0.07037389],"study_design_scores_gemma":[0.0004539826,0.00006580983,0.0006520473,0.0006265753,0.0001118215,0.000004415538,0.0004294388,0.04304833,0.9282895,0.008478163,0.01703615,0.0008038208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01254448,0.0002368734,0.9559053,0.00117756,0.001040276,0.0008909603,0.00001928667,0.002494666,0.02569065],"genre_scores_gemma":[0.9020262,0.00002894764,0.08957566,0.001986775,0.00007638669,0.0001720632,0.00000965841,0.0001021999,0.006022149],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8894817,"threshold_uncertainty_score":0.9995961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00842024934820899,"score_gpt":0.2903385901575168,"score_spread":0.2819183408093078,"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."}}