{"id":"W4372200658","doi":"10.26740/independent.v1i3.43421","title":"PENGARUH PERTUMBUHAN EKONOMI DAN IPM TERHADAP TINGKAT KEMISKINAN DI KABUPATEN PASURUAN","year":2021,"lang":"id","type":"article","venue":"Independent Journal of Economics","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Forestry; Mathematics; Geography","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":[0.002215127,0.0005445833,0.0006514473,0.002390957,0.001543485,0.004519194,0.0006514653,0.000704365,0.01973931],"category_scores_gemma":[0.005431655,0.0003533724,0.0006467667,0.0050079,0.000776801,0.002657113,0.002436329,0.001404524,0.004086668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002154258,"about_ca_system_score_gemma":0.004646715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02153716,"about_ca_topic_score_gemma":0.03301049,"domain_scores_codex":[0.9981483,0.0003933502,0.0001758518,0.0003241478,0.0006897005,0.0002686212],"domain_scores_gemma":[0.9964826,0.001229206,0.000595242,0.0002666425,0.001132019,0.0002942198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005612956,0.0002681089,0.3050195,0.003914574,0.0003317188,0.00170131,0.0203073,0.003196733,0.006221689,0.02933131,0.05288738,0.5762591],"study_design_scores_gemma":[0.00003268258,0.0002583879,0.4976072,0.001729143,0.000237819,0.0007777458,0.0294799,0.002952072,0.005271378,0.009528555,0.4519845,0.0001406307],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6198488,0.01589364,0.03104163,0.01341018,0.001070183,0.0008775484,0.02484835,0.0007415792,0.292268],"genre_scores_gemma":[0.8624664,0.01007423,0.01760715,0.0008915372,0.0003310607,0.0006963338,0.006882404,0.0002095141,0.1008413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02153716,"threshold_uncertainty_score":0.06603456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03655155174840894,"score_gpt":0.2144940636754905,"score_spread":0.1779425119270815,"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."}}