{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001011415,0.0002536009,0.0002019037,0.007835215,0.0006421146,0.001284704,0.0002648649,0.0003478182,0.00360963],"category_scores_gemma":[0.004133083,0.0001153359,0.0004487025,0.005721644,0.0003889991,0.002478012,0.0006619094,0.0003020021,0.0002833037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060607,"about_ca_system_score_gemma":0.0006119868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009915116,"about_ca_topic_score_gemma":0.007696193,"domain_scores_codex":[0.9994928,0.0002593409,0.00002682753,0.0000837734,0.00008293216,0.00005438268],"domain_scores_gemma":[0.9976816,0.001411668,0.0004189764,0.00009111566,0.0002617534,0.0001348252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005202534,0.0004127171,0.6484741,0.000429473,0.0005254233,0.0007092988,0.01126187,0.04233661,0.004664258,0.09876523,0.006021865,0.1858789],"study_design_scores_gemma":[0.00003328229,0.0002070116,0.5425659,0.0001415347,0.0002024552,0.0004667683,0.01552673,0.3807925,0.001257216,0.03917982,0.01954145,0.00008519868],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457513,0.0004017183,0.03359506,0.0006384633,0.00002810514,0.000168738,0.002657333,0.0001334092,0.01662587],"genre_scores_gemma":[0.9902635,0.000153173,0.007682709,0.00001328566,0.00001422151,0.00007381687,0.0008008628,0.00000791967,0.0009906496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009915116,"threshold_uncertainty_score":0.01971477,"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."}}