{"id":"W11552681","doi":"10.1007/978-3-540-72108-6_3","title":"A Fuzzy Relational Method For Image-Based Road Extraction For Traffic Emergency Services","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in geoinformation and cartography","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Segmentation; Computer vision; RGB color model; Relation (database); Satellite imagery; Remote sensing; Geography; Pattern recognition (psychology); Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006850913,0.0005201547,0.0007866477,0.001626858,0.0005976058,0.00125648,0.001252331,0.0005862947,0.00566631],"category_scores_gemma":[0.001497564,0.0003734642,0.0009548053,0.001782214,0.0003724345,0.001145626,0.0006935128,0.00061348,0.002294905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004107424,"about_ca_system_score_gemma":0.0006415748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004947728,"about_ca_topic_score_gemma":0.005436619,"domain_scores_codex":[0.9992414,0.000103659,0.00006413246,0.0002055988,0.0003472894,0.00003808531],"domain_scores_gemma":[0.9995048,0.0001614786,0.00002946822,0.00007942948,0.0002047956,0.00002004098],"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":[0.0001579197,0.0001129695,0.001017089,0.0003064364,0.0001169745,0.0002202183,0.0002598798,0.02833486,0.06634484,0.0207099,0.006266939,0.8761519],"study_design_scores_gemma":[0.00003220308,0.000120756,0.002550391,0.00005324506,0.0002061629,0.0006883835,0.0002111373,0.9041464,0.04813121,0.01488939,0.0288857,0.00008503004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003282093,0.0002839901,0.9947047,0.0000324047,0.00002979728,0.00003750559,0.0001521195,0.0005846262,0.000892825],"genre_scores_gemma":[0.05891679,0.0003517888,0.9373511,0.00003685725,0.00004886753,0.00006317056,0.0004543888,0.000100594,0.002676518],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00566631,"threshold_uncertainty_score":0.01895571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166502835626855,"score_gpt":0.2658740337049161,"score_spread":0.2542090053486476,"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."}}