{"id":"W45574125","doi":"","title":"Semi-automatic Road Extraction from Very High Resolution Remote Sensing Imagery by RoadModeler","year":2009,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Remote sensing; Extraction (chemistry); Aerial imagery; High resolution; Artificial intelligence; Geography; Computer science; Computer vision; Cartography; Chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004485533,0.0005514136,0.0004947223,0.001116528,0.0002540197,0.0007046977,0.0007515462,0.0005637796,0.002817231],"category_scores_gemma":[0.0007596684,0.0004729547,0.0006008848,0.000529372,0.00017724,0.001324958,0.0006575928,0.0004187422,0.001744985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003146644,"about_ca_system_score_gemma":0.0005118828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002386153,"about_ca_topic_score_gemma":0.006343119,"domain_scores_codex":[0.9996718,0.0000440661,0.00001420502,0.000103162,0.0001337365,0.00003308195],"domain_scores_gemma":[0.9996883,0.0000735245,0.00003605641,0.00008621804,0.0001015101,0.00001438075],"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":[0.0002879357,0.0001836748,0.002619437,0.0002727791,0.0001183229,0.0002337142,0.0002711828,0.04872238,0.4631291,0.002072793,0.006781003,0.4753078],"study_design_scores_gemma":[0.00003988352,0.0001288797,0.007850592,0.0000205723,0.00004286061,0.0003187651,0.00009132781,0.8327604,0.1487117,0.0007630321,0.009190079,0.00008191649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.118675,0.0001820014,0.8601364,0.00007964821,0.00003361904,0.0002545359,0.000679036,0.01761266,0.002347145],"genre_scores_gemma":[0.1975935,0.000141799,0.797425,0.00003876929,0.000008104008,0.0001463669,0.001840681,0.00060327,0.002202639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002817231,"threshold_uncertainty_score":0.009424627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005586475464252226,"score_gpt":0.1892461809450472,"score_spread":0.183659705480795,"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."}}