{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005526043,0.00022062,0.0002816051,0.0001198926,0.0005880641,0.0004059169,0.000400508,0.0001636561,0.0002135179],"category_scores_gemma":[0.001546413,0.0002145068,0.0001711714,0.0009442943,0.0001313347,0.0008886429,0.0001336306,0.0002814245,0.00006488027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283122,"about_ca_system_score_gemma":0.0004966875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000530862,"about_ca_topic_score_gemma":0.0005279992,"domain_scores_codex":[0.9976736,0.0001569274,0.000397867,0.0004370177,0.0008145989,0.0005199751],"domain_scores_gemma":[0.9987853,0.0001905328,0.0002113836,0.0001517168,0.0002064414,0.0004546048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005128099,0.0001951345,0.5292473,0.00007359033,0.0001977266,0.00006832313,0.03616252,0.001346394,0.0006320512,0.001226139,0.4063434,0.02399459],"study_design_scores_gemma":[0.002840457,0.0008046827,0.4789841,0.0004321092,0.0004164443,0.00001963046,0.07090201,0.1955442,0.001049781,0.0008703452,0.2447369,0.003399414],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8765746,0.0001234633,0.0007842932,0.01219283,0.001591212,0.0003056925,0.00002783786,0.0003025833,0.1080974],"genre_scores_gemma":[0.9960776,0.00004608722,0.0002281235,0.001381514,0.001171465,0.00001798988,0.0000204119,0.0000287942,0.001028002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1941978,"threshold_uncertainty_score":0.8747333,"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."}}