{"id":"W4224278861","doi":"10.3390/su14084463","title":"A Social Network Analysis of International Creative Goods Flow","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gross domestic product; Per capita; Betweenness centrality; Economics; International trade; Population; Per capita income; Business; Centrality; Economic growth; Statistics; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001039793,0.00005611493,0.0001692818,0.00006331862,0.0009254452,0.00002412594,0.0002337975,0.00003602527,0.004910137],"category_scores_gemma":[0.0004025079,0.00005539432,0.0001562475,0.001547225,0.000232754,0.00006671329,0.0001956542,0.0001298404,3.028652e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001886023,"about_ca_system_score_gemma":0.0006255009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006243213,"about_ca_topic_score_gemma":0.001722736,"domain_scores_codex":[0.9986899,0.0003059137,0.0001902748,0.0001639223,0.0004333843,0.0002165491],"domain_scores_gemma":[0.9992725,0.00006715147,0.0001004736,0.00007736916,0.0004423282,0.00004014635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001689793,0.0002977646,0.5953302,0.00001104857,0.001500387,0.000008610701,0.1046802,0.01592295,8.976439e-7,0.0822833,0.1651329,0.03466275],"study_design_scores_gemma":[0.0001127605,0.00002494622,0.2472676,4.796096e-7,0.0001343874,5.636998e-8,0.08596631,0.0005033196,0.00000145284,0.01000032,0.6558875,0.0001008342],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8676785,0.0001157258,0.0003436351,0.06277011,0.0007452549,0.0008579651,0.0001306045,0.0001018424,0.06725638],"genre_scores_gemma":[0.9836162,0.00000315253,0.00008499254,0.0000610994,0.0001574686,0.00004427339,0.00004010096,0.000002180272,0.01599056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4907546,"threshold_uncertainty_score":0.9959995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449053768329456,"score_gpt":0.33506243607917,"score_spread":0.3105718983958755,"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."}}