{"id":"W2142427031","doi":"","title":"ROBUST AND EFFICIENT ROAD TRACKING IN AERIAL IMAGES","year":2005,"lang":"en","type":"article","venue":"Griffith Research Online (Griffith University, Queensland, Australia)","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Particle filter; Computer vision; Robustness (evolution); Computer science; Artificial intelligence; Tracking (education); Tracking system; Road map; Kalman filter; Geography; Cartography","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":[0.0007388588,0.0003366134,0.0003771374,0.0009935809,0.0002842101,0.0001414066,0.0003833979,0.0003413556,0.0001152509],"category_scores_gemma":[0.00008566324,0.0003505322,0.00008193251,0.0009977673,0.000242076,0.0004557799,0.000162557,0.001345246,0.00006783271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004399788,"about_ca_system_score_gemma":0.00008437814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029208,"about_ca_topic_score_gemma":0.002768507,"domain_scores_codex":[0.9972098,0.0002068415,0.0003383468,0.0005478188,0.0006618886,0.001035253],"domain_scores_gemma":[0.9990012,0.0001211539,0.00005763438,0.0003165555,0.0001875345,0.0003159342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000593458,0.001074248,0.02204004,0.0004174979,0.0001843528,0.0009310778,0.001352016,0.8969371,0.01572863,0.0006035719,0.02445574,0.03568232],"study_design_scores_gemma":[0.007948599,0.0003867311,0.7162292,0.0007516554,0.00009228534,0.0002185131,0.002723684,0.2156555,0.005094834,0.00005249618,0.04915455,0.001691946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996644,0.0001952904,0.0002229843,0.0009009347,0.0002680109,0.0003941962,0.0001319177,0.0004288172,0.0008139171],"genre_scores_gemma":[0.9948292,0.000537969,0.002114489,0.00001146604,0.0005396805,0.000002150745,0.00008381577,0.00005044754,0.001830792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6941891,"threshold_uncertainty_score":0.9998947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0920875156140365,"score_gpt":0.3318959761177768,"score_spread":0.2398084605037403,"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."}}