{"id":"W4415012681","doi":"10.31292/wb.v5i2.241","title":"Analisis Kepuasan Pengguna Aplikasi Bhumi Kementerian Agraria dan Tata Ruang Dengan Pendekatan Model End-User Computing Satisfaction","year":2025,"lang":"en","type":"article","venue":"Widya Bhumi","topic":"Health, Technology, Consumer Behavior","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Geospatial analysis; Nonprobability sampling; User satisfaction; Christian ministry; Agency (philosophy); Usability","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003279024,0.0007298117,0.0006115962,0.0020793,0.0007773582,0.002856443,0.0007780512,0.0005101045,0.01448936],"category_scores_gemma":[0.009194332,0.0002895087,0.001447865,0.0032125,0.0007842052,0.002017455,0.001459427,0.001138282,0.00145785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590768,"about_ca_system_score_gemma":0.001528798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01088143,"about_ca_topic_score_gemma":0.006903698,"domain_scores_codex":[0.9968976,0.001367854,0.0001900259,0.0003206377,0.0009372646,0.0002866103],"domain_scores_gemma":[0.9872127,0.009164045,0.0008354456,0.0004203822,0.001908291,0.0004592009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005673643,0.0007480404,0.8934084,0.0004027378,0.000382777,0.0004910222,0.01218952,0.005416635,0.002248571,0.005475856,0.003119186,0.07554997],"study_design_scores_gemma":[0.00003569797,0.0009064593,0.8702139,0.0002227322,0.0003554817,0.0005121485,0.02998692,0.08306427,0.002535591,0.002788166,0.009274887,0.0001037733],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782181,0.0001667675,0.007643328,0.0003405091,0.00002421541,0.0001797145,0.0007408474,0.0001273973,0.01255892],"genre_scores_gemma":[0.9950045,0.00009491473,0.001602864,0.0000289154,0.000007233127,0.0001790992,0.0005303919,0.00002115862,0.002530935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01448936,"threshold_uncertainty_score":0.04847169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05870486579147731,"score_gpt":0.4229157252605675,"score_spread":0.3642108594690902,"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."}}