{"id":"W596664051","doi":"","title":"VISAT™: The Avenue to Highway Data Bank","year":2008,"lang":"en","type":"article","venue":"Seventh International Conference on Managing Pavement AssetsTransportation Research BoardAlberta Infrastructure and Transportation, CanadaFederal Highway Administration","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Mobile mapping; Computer science; Photogrammetry; Inertial measurement unit; Digital mapping; Geographic information system; Inertial navigation system; Real-time computing; Remote sensing; Geography; Telecommunications; Computer vision; Inertial frame of reference","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001635512,0.0005776676,0.0009528793,0.004659792,0.001073931,0.002444245,0.001918129,0.0006488375,0.06531427],"category_scores_gemma":[0.00596528,0.0005938024,0.0003135794,0.008075207,0.0002702206,0.002045307,0.001160891,0.001057171,0.07558729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002885657,"about_ca_system_score_gemma":0.009501563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1190426,"about_ca_topic_score_gemma":0.09790641,"domain_scores_codex":[0.9984055,0.0001006843,0.0002024239,0.000227173,0.0008772889,0.0001869256],"domain_scores_gemma":[0.9907634,0.0003799507,0.0005058316,0.001387988,0.00617705,0.0007858463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002282419,0.00005021365,0.006791617,0.0001532491,0.00002100946,0.00003899433,0.00008028381,0.0005599032,0.0004485381,0.002652362,0.9451063,0.04386931],"study_design_scores_gemma":[0.00005950824,0.00001398117,0.008965938,0.00006676325,0.00001398663,0.00003540063,0.00006972369,0.001323943,0.001052853,0.0005914961,0.987776,0.0000303852],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.002817067,0.0001475409,0.003444762,0.0003038676,0.0001183147,0.0003392928,0.9545702,0.006568993,0.03168995],"genre_scores_gemma":[0.006913906,0.000200325,0.00765388,0.0001103372,0.00004360078,0.0004227906,0.9699085,0.000522165,0.01422445],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1190426,"threshold_uncertainty_score":0.2366995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05720980956154797,"score_gpt":0.3242365314423246,"score_spread":0.2670267218807766,"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."}}