{"meta":{"query_hash":"4aaa2b5e37be","filters":{"venue":"Jurnal Ekonomi dan Pembangunan"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/4aaa2b5e37be","api":"https://metacan.xera.ac/api/v1/cohort?venue=Jurnal+Ekonomi+dan+Pembangunan"},"results":[{"id":"W3042620028","doi":"10.22373/jep.v8i1.69","title":"ANALISIS TENAGA KERJA DAN PERTUMBUHAN EKONOMI DI INDONESIA DENGAN MENGGUNAKAN METODE VECTOR AUTOREGRESSIVE","year":2017,"lang":"id","type":"article","venue":"Jurnal Ekonomi dan Pembangunan","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Political science; Humanities; Art","score_opus":0.028785099972009686,"score_gpt":0.24458639626669834,"score_spread":0.21580129629468867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042620028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94010323,0.0023753191,0.022183213,0.0010147915,0.00010362516,0.0001268957,0.006965742,0.00028018715,0.026846917],"genre_scores_gemma":[0.972637,0.0013700041,0.007873443,0.00006408861,0.000032810793,0.00011694928,0.0034900808,0.000061718754,0.014353991],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990478,0.00023356412,0.00008453825,0.00019656014,0.00033576507,0.0001017285],"domain_scores_gemma":[0.99833566,0.0007269649,0.000245544,0.00011075307,0.00049963925,0.00008150679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011384652,0.0005245736,0.000535204,0.0011571192,0.00039059957,0.0021222825,0.00033798136,0.0002151559,0.004163689],"category_scores_gemma":[0.002397228,0.00023426868,0.0007224174,0.0024887447,0.00025961947,0.0006883407,0.0007275805,0.0007800745,0.0012361364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019490017,0.00014074541,0.779776,0.0004979158,0.0004370491,0.0004124046,0.006386963,0.0061140493,0.0026761298,0.0036551575,0.005221799,0.19448689],"study_design_scores_gemma":[0.0000071825793,0.0000868318,0.9525893,0.00020017868,0.00023844306,0.00021480155,0.008507761,0.014713894,0.002073045,0.0011036225,0.020226344,0.00003879475],"about_ca_topic_score_codex":0.029774904,"about_ca_topic_score_gemma":0.038123455,"teacher_disagreement_score":0.029774904,"about_ca_system_score_codex":0.0006728191,"about_ca_system_score_gemma":0.0011368592,"threshold_uncertainty_score":0.059203207},"labels":[],"label_agreement":null}]}