{"id":"W3069416164","doi":"10.1111/tgis.12680","title":"OpenStreetMap quality assessment using unsupervised machine learning methods","year":2020,"lang":"en","type":"article","venue":"Transactions in GIS","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Volunteered geographic information; Geospatial analysis; Reliability (semiconductor); Computer science; Quality (philosophy); Data science; Feature (linguistics); Quality assurance; Data quality; Data mining; Geography; Engineering; Cartography; Metric (unit)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006244079,0.0006841939,0.0005630138,0.007843634,0.0007401595,0.002651532,0.001407661,0.0006983003,0.001498868],"category_scores_gemma":[0.02275742,0.0002419891,0.000921118,0.005595539,0.0008799973,0.001841321,0.001566499,0.0008218893,0.0008090875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118855,"about_ca_system_score_gemma":0.0013906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009288009,"about_ca_topic_score_gemma":0.01141599,"domain_scores_codex":[0.9948946,0.001731502,0.0004626647,0.0009298728,0.001670778,0.0003106095],"domain_scores_gemma":[0.9758782,0.0101131,0.003193481,0.002526753,0.007941,0.0003473929],"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":[0.0003372168,0.0005174829,0.3239965,0.0004331627,0.0005986093,0.0003175003,0.001847303,0.1534183,0.005703458,0.005296092,0.01366281,0.4938717],"study_design_scores_gemma":[0.00001210433,0.00005433306,0.06118825,0.00007105525,0.00004590687,0.00009693853,0.0008870817,0.9240233,0.003946705,0.005861692,0.003771976,0.00004063304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5249059,0.0003130447,0.4598054,0.0006803064,0.0001203901,0.0004337264,0.004208648,0.004193443,0.005339188],"genre_scores_gemma":[0.8332676,0.00008872218,0.1592409,0.00005447145,0.00004483324,0.0002205013,0.005490819,0.0002094187,0.001382683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009288009,"threshold_uncertainty_score":0.03302222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2001277540490803,"score_gpt":0.4650789032279641,"score_spread":0.2649511491788838,"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."}}