{"id":"W3092388514","doi":"10.35870/emt.v4i2.129","title":"Analisis Kredit UMKM di Provinsi Aceh: Analisis Empiris Vector Error Correction Model (VECM)","year":2020,"lang":"en","type":"article","venue":"Jurnal EMT KITA","topic":"SMEs Development and Digital Marketing","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Error correction model; Cointegration; Econometrics; Gross domestic product; Loan; Term (time); Economics; Quarter (Canadian coin); Variables; Variable (mathematics); Non-performing loan; Statistics; Mathematics; Macroeconomics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002136976,0.0005535877,0.0008654151,0.002073006,0.000375858,0.001861082,0.0004676121,0.0003125851,0.008241389],"category_scores_gemma":[0.0051746,0.0001992293,0.001110153,0.003031805,0.0002941035,0.0005317978,0.0007086226,0.0009221134,0.001122629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000851231,"about_ca_system_score_gemma":0.001618731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06674052,"about_ca_topic_score_gemma":0.03383151,"domain_scores_codex":[0.9983332,0.0006758574,0.0001009897,0.0002801715,0.0004436889,0.0001661371],"domain_scores_gemma":[0.9962214,0.002526734,0.0003385536,0.0002939091,0.0005284625,0.00009085675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00026565,0.0003898198,0.7983545,0.000625499,0.001817348,0.001406541,0.001702312,0.04188492,0.001794353,0.009981452,0.0131815,0.1285961],"study_design_scores_gemma":[0.00003843122,0.0003568559,0.818158,0.0002265029,0.0004580409,0.0005538149,0.004939463,0.1302376,0.002030424,0.00310987,0.03981811,0.00007277638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9330328,0.001629048,0.0347221,0.0007965474,0.0001559784,0.0002150813,0.01261317,0.0005921852,0.01624305],"genre_scores_gemma":[0.9801932,0.0004770316,0.005662703,0.00004404181,0.00003902819,0.0001117336,0.005837497,0.00004159258,0.007593087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06674052,"threshold_uncertainty_score":0.1327041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06243699910724195,"score_gpt":0.3150272579972242,"score_spread":0.2525902588899823,"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."}}