{"id":"W3165204199","doi":"10.48550/arxiv.2105.12633","title":"Edge Detection for Satellite Images without Deep Networks","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Deep learning; Computer science; Satellite; Satellite imagery; Artificial intelligence; Pixel; Training (meteorology); Computer vision; Remote sensing; Geography; Engineering","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":[0.0002315939,0.0005796741,0.0004424936,0.001533849,0.0002353574,0.0007913381,0.0007829987,0.0007202324,0.005125756],"category_scores_gemma":[0.001312925,0.0004070443,0.0005794526,0.001044685,0.0002885146,0.001041839,0.000705411,0.0007818472,0.002766731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004562622,"about_ca_system_score_gemma":0.0003510888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00475252,"about_ca_topic_score_gemma":0.009962172,"domain_scores_codex":[0.9998086,0.00001374858,0.000007722013,0.00006949513,0.000064457,0.00003598857],"domain_scores_gemma":[0.9997399,0.00005404581,0.00003354673,0.00007259436,0.00007958832,0.00002028166],"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":[0.0004603522,0.0001223189,0.003260219,0.0002758035,0.0001261752,0.0002395845,0.00006790953,0.1021802,0.04916666,0.01190879,0.02391207,0.8082799],"study_design_scores_gemma":[0.00001208493,0.00004237594,0.002719554,0.00003256394,0.00001850343,0.0001403456,0.00003021905,0.9570802,0.02120213,0.0109514,0.007757933,0.00001276775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06723338,0.0008382236,0.9147425,0.0004779109,0.0001542291,0.0001177795,0.002536863,0.006022458,0.007876663],"genre_scores_gemma":[0.4555103,0.001202208,0.5161138,0.0004366951,0.0001578042,0.0001422837,0.008291788,0.0007203058,0.01742477],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005125756,"threshold_uncertainty_score":0.01714736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02933026829014104,"score_gpt":0.1725158683932201,"score_spread":0.1431856001030791,"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."}}