{"id":"W626997782","doi":"10.1016/j.giq.2015.05.003","title":"Civic open data at a crossroads: Dominant models and current challenges","year":2015,"lang":"en","type":"article","venue":"Government Information Quarterly","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":286,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Open government; Open data; Government (linguistics); Public relations; Citizen journalism; Business; Computer science; Internet privacy; Political science; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001810436,0.00014532,0.000168825,0.00002410028,0.0003756362,0.0008762084,0.00123383,0.00007205493,0.0000956642],"category_scores_gemma":[0.00004696619,0.0001306724,0.0000207426,0.00009698683,0.0001244946,0.01104572,0.0006905632,0.0000830549,0.0001667653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005012137,"about_ca_system_score_gemma":0.0001574902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001592491,"about_ca_topic_score_gemma":0.00540562,"domain_scores_codex":[0.9974969,0.00009813847,0.0003614626,0.0002149755,0.001513144,0.000315402],"domain_scores_gemma":[0.9987835,0.00006610402,0.0003072941,0.0005004979,0.00007516872,0.0002674577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001765354,0.000135062,0.001157658,0.00009402049,0.00004476105,9.554543e-7,0.3354506,0.00001193966,0.000002605286,0.1597478,0.03533751,0.4678406],"study_design_scores_gemma":[0.001134878,0.0001578544,0.0007846884,0.00003668292,0.0000163922,0.000001378067,0.1341697,0.003904168,0.000004695142,0.003595716,0.8559613,0.0002325385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2371511,0.004931172,0.001663113,0.02452417,0.002159649,0.002529531,0.0009156287,0.0001932202,0.7259324],"genre_scores_gemma":[0.9965361,0.001388636,0.0002327024,0.0005161681,0.0001881043,0.00006417412,0.0001523024,0.000008651931,0.0009131188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8206238,"threshold_uncertainty_score":0.8449298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1730569066855999,"score_gpt":0.3559588033477553,"score_spread":0.1829018966621553,"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."}}