{"id":"W2294439425","doi":"10.1007/978-3-319-22479-4_22","title":"Comparing Local e-Government Websites in Canada and the UK","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Local government; Conceptualization; E-Government; Government (linguistics); Computer science; World Wide Web; Public relations; Political science; Public administration; Artificial intelligence; Information and Communications Technology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001960808,0.0002340597,0.0003633965,0.00007109853,0.0002798927,0.0002881863,0.001167316,0.0001193237,0.00009973152],"category_scores_gemma":[0.00009510672,0.0001701698,0.0000316927,0.0002487919,0.001868969,0.00018273,0.0005697354,0.0004542326,0.00000490166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002346208,"about_ca_system_score_gemma":0.002388984,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8556296,"about_ca_topic_score_gemma":0.9963637,"domain_scores_codex":[0.996572,0.00007252349,0.0002827969,0.0005097719,0.002101129,0.0004618148],"domain_scores_gemma":[0.9985235,0.000793222,0.0001646592,0.0002966272,0.00007044084,0.0001515059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001917112,0.0000445373,0.2645401,0.0001075829,0.00006265229,0.000162504,0.03404207,0.03623638,0.000005239909,0.2732292,0.001221701,0.3901564],"study_design_scores_gemma":[0.006655756,0.0002098576,0.02777158,0.00188164,0.00008893796,0.00003273002,0.001095617,0.3711735,0.0001309063,0.3999833,0.1872469,0.003729298],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05767021,0.01117814,0.1986571,0.03020068,0.008317464,0.002926737,0.0000489015,0.0001323633,0.6908684],"genre_scores_gemma":[0.9967524,0.00008595046,0.0007435041,0.001454402,0.0003126458,0.000004610371,0.000001335957,0.000009692971,0.0006354438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9390822,"threshold_uncertainty_score":0.6939324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02174406250172177,"score_gpt":0.238185482797523,"score_spread":0.2164414202958012,"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."}}