{"id":"W3111986469","doi":"10.1155/2020/8861914","title":"A Correlative Analysis of Modern Logistics Industry to Developing Economy Using the VAR Model: A Case of Pakistan","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Belt and Road Initiative","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Context (archaeology); Developing country; Investment (military); Sustainable growth rate; Business; Relation (database); Economics; Industrial organization; Vector autoregression; Economy; Economic system; Economic growth; Computer science; Politics; Econometrics; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0008160301,0.0002547945,0.0002691415,0.001589241,0.0008231527,0.001613423,0.0004474242,0.0006896572,0.002740269],"category_scores_gemma":[0.001900226,0.0002126088,0.0007103129,0.00186596,0.0006049935,0.000913176,0.0009299665,0.001058512,0.0002235344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00146365,"about_ca_system_score_gemma":0.001414016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06991821,"about_ca_topic_score_gemma":0.04587146,"domain_scores_codex":[0.9996988,0.000101949,0.0000158537,0.00005579038,0.00004559388,0.00008203573],"domain_scores_gemma":[0.998511,0.0008865221,0.0002651814,0.00005542296,0.0002026675,0.00007911747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000260715,0.0005940144,0.5958759,0.000275121,0.0002716058,0.03031991,0.003920268,0.2169897,0.001506997,0.1018464,0.005352701,0.0427867],"study_design_scores_gemma":[0.00004899467,0.0003373305,0.2498223,0.0001235145,0.0002368828,0.001592406,0.01305566,0.7036143,0.001222541,0.01993267,0.009884667,0.0001287797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817421,0.0003398382,0.007808806,0.0009342562,0.00002514133,0.00004205613,0.0003841376,0.00003688487,0.008686701],"genre_scores_gemma":[0.9968767,0.000374965,0.001114799,0.00003270601,0.00001533361,0.00001086891,0.00016157,0.000003906191,0.001409084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06991821,"threshold_uncertainty_score":0.1390225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08939745899104758,"score_gpt":0.3087498216400507,"score_spread":0.2193523626490032,"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."}}