{"id":"W2473128379","doi":"10.17645/up.v1i2.644","title":"The V in VGI: Citizens or Civic Data Sources","year":2016,"lang":"en","type":"article","venue":"Urban Planning","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Volunteered geographic information; Citizenship; Government (linguistics); Public relations; Context (archaeology); Open government; Political science; Civic engagement; Typology; Business; Open data; Sociology; Politics; Geography; Computer science; Data science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00140011,0.00006368079,0.00009284393,0.00007591144,0.0008474968,0.0001025509,0.0005456428,0.00003989444,0.00004045107],"category_scores_gemma":[0.0006396387,0.00003094149,0.0000160821,0.000270458,0.0002244927,0.0003094792,0.0001555382,0.00005625866,0.00008615496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000285828,"about_ca_system_score_gemma":0.00005686837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004589351,"about_ca_topic_score_gemma":0.002582934,"domain_scores_codex":[0.9989803,0.00008032475,0.0002181137,0.0001220553,0.0002892468,0.0003098873],"domain_scores_gemma":[0.9987599,0.0007791941,0.00009956839,0.0002839517,0.0000401567,0.00003717398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001729151,0.00000461298,0.8221687,0.000006774047,0.00002640841,0.000008766924,0.114553,0.000002295138,0.000008371922,0.007286389,0.05283425,0.003083167],"study_design_scores_gemma":[0.0002231845,0.000009276837,0.07431871,0.0001424171,0.000003516913,0.00000133415,0.05198517,0.0000147941,0.000002385892,0.0002981543,0.8728986,0.0001024154],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6862386,0.002886333,0.0004604936,0.01718839,0.001662212,0.000774982,0.00007959943,0.0003778048,0.2903315],"genre_scores_gemma":[0.9912656,0.00006379608,0.00002753937,0.0001180942,0.0002019256,0.00001183419,0.00000257254,0.000004082078,0.008304546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8200644,"threshold_uncertainty_score":0.6518345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09671777055258711,"score_gpt":0.3410997372413905,"score_spread":0.2443819666888034,"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."}}