{"id":"W4287691296","doi":"10.5281/zenodo.4046163","title":"UNRAVELING THE ECONOMIC DISPARITIES AND SIMILARITIES: THE CASE OF CANADA AND BANGLADESH","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Economic geography; Regional science; Political science","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":[0.0009991389,0.0002339961,0.0005560181,0.003008704,0.01083353,0.004625516,0.0009925535,0.001123601,0.003356653],"category_scores_gemma":[0.003360847,0.0001625734,0.0002776707,0.008656997,0.006417908,0.002459502,0.003972572,0.002202789,0.0001404086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04168687,"about_ca_system_score_gemma":0.03243219,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9792783,"about_ca_topic_score_gemma":0.9892881,"domain_scores_codex":[0.9988128,0.0001968251,0.00002456673,0.00007529653,0.0002270677,0.0006635084],"domain_scores_gemma":[0.9985272,0.0003790767,0.0002304999,0.00005760949,0.0004383385,0.0003673764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002334407,0.0001367288,0.2242886,0.000292508,0.00009598309,0.0129924,0.1542475,0.003752438,0.0008545955,0.5134481,0.009970169,0.07968743],"study_design_scores_gemma":[0.00005853936,0.00005131434,0.303453,0.0006508799,0.0001193522,0.001301538,0.5672435,0.002889241,0.0004919593,0.04105886,0.08253436,0.0001474073],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9109726,0.002647256,0.0002532908,0.007649355,0.00001982457,0.00003796922,0.0003316218,0.000005461463,0.07808265],"genre_scores_gemma":[0.9951764,0.001645444,0.0001774315,0.0002182576,0.000004408693,0.000008659704,0.0000962004,0.00000464042,0.002668453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04168687,"threshold_uncertainty_score":0.3024609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05560002714836463,"score_gpt":0.1910603925360098,"score_spread":0.1354603653876451,"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."}}