{"id":"W4389108208","doi":"10.5539/ibr.v16n12p20","title":"A Multicriteria Evaluation of Local E-Government in Terms of Citizen Satisfaction","year":2023,"lang":"en","type":"article","venue":"International Business Research","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia","keywords":"Benchmarking; Portuguese; Local government; Identification (biology); Sustainable development; Set (abstract data type); Government (linguistics); Sample (material); Computer science; Business; Knowledge management; Environmental economics; Process management; Public relations; Political science; Marketing; Public administration; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01155422,0.0003496915,0.0008312949,0.002669349,0.0007764039,0.001673151,0.0004751284,0.0006883449,0.003379287],"category_scores_gemma":[0.02197687,0.0002056153,0.001484313,0.003767019,0.001118436,0.001255791,0.001894704,0.0006257315,0.0005550301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001803819,"about_ca_system_score_gemma":0.000873895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00172602,"about_ca_topic_score_gemma":0.001782663,"domain_scores_codex":[0.984439,0.01113955,0.000911029,0.0008313846,0.002070237,0.0006088893],"domain_scores_gemma":[0.9787236,0.01301601,0.002415888,0.00142881,0.003560154,0.000855578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003769958,0.003523449,0.8386111,0.0008293876,0.000842153,0.0002612354,0.01227114,0.006414563,0.004366814,0.003588505,0.002196608,0.123325],"study_design_scores_gemma":[0.0001175886,0.006856836,0.9558977,0.0001320489,0.000226206,0.0001778713,0.01621181,0.01562151,0.00217619,0.0008019784,0.001706224,0.0000741024],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935851,0.00003891383,0.001697363,0.0000585035,0.000008513309,0.0001751788,0.0002117181,0.00001945728,0.004205254],"genre_scores_gemma":[0.9985513,0.00002379549,0.0007976263,0.0000135015,0.00000484775,0.0001428893,0.0001522109,0.00000398719,0.0003099026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01155422,"threshold_uncertainty_score":0.06110525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1558282628116778,"score_gpt":0.4736364314831941,"score_spread":0.3178081686715163,"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."}}