{"id":"W4210978734","doi":"10.31315/be.v18i1.5621","title":"OPTIMALISASI KECEPATAN PELAYANAN TERHADAP KEPUASAN DAN LOYALITAS DENGAN KEPERCAYAAN WAJIB PAJAK SEBAGAI VARIABEL INTERVENING (STUDI PADA KANTOR UPPD SAMSAT KABUPATEN KARANGANYAR)","year":2021,"lang":"en","type":"article","venue":"Buletin Ekonomi Manajemen Ekonomi Pembangunan Akuntansi","topic":"Consumer Behavior and Marketing Influence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Adidas (Canada)","funders":"","keywords":"Taxpayer; Accidental sampling; Loyalty; Population; Business; Business administration; Advertising; Psychology; Political science; Marketing; Sociology; Law; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","scholarly_communication"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.002076524,0.001582032,0.001627101,0.0006668059,0.001254998,0.001902652,0.00184701,0.0004918156,0.000848214],"category_scores_gemma":[0.0005708673,0.001744722,0.0008731458,0.001098961,0.0004248506,0.001686868,0.00202834,0.001084464,0.0003071674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007745081,"about_ca_system_score_gemma":0.0003049033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003114271,"about_ca_topic_score_gemma":0.002345879,"domain_scores_codex":[0.9919626,0.000316245,0.00213535,0.002544726,0.0008057192,0.002235327],"domain_scores_gemma":[0.9954003,0.0003623347,0.00108812,0.002190985,0.0006749143,0.0002833169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006981812,0.001332319,0.9156979,0.001172953,0.001060711,0.001727929,0.0009977893,0.0002774505,0.01110664,0.01153048,0.01479263,0.03960501],"study_design_scores_gemma":[0.004661196,0.0001068479,0.5599057,0.0007412669,0.001510308,0.0001320702,0.005500023,0.001299838,0.001499639,0.0001581821,0.4210819,0.003403012],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670896,0.0009815006,0.0002458238,0.002579093,0.00273842,0.001169726,0.00005847823,0.0008821879,0.02425517],"genre_scores_gemma":[0.989474,0.000085279,0.001731641,0.0027401,0.002198806,0.000280584,0.0008344876,0.0003870202,0.002268089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4062893,"threshold_uncertainty_score":0.9996928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01913461588238922,"score_gpt":0.2289417121259232,"score_spread":0.209807096243534,"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."}}