{"id":"W4390505155","doi":"10.1016/j.physa.2023.129488","title":"Structure characteristics and formation mechanism of the RCEP manufacturing trade network: An ERGM analysis","year":2024,"lang":"en","type":"article","venue":"Physica A Statistical Mechanics and its Applications","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Office for Philosophy and Social Sciences; National Natural Science Foundation of China","keywords":"Centrality; Node (physics); Preferential attachment; Reciprocity (cultural anthropology); General partnership; International trade; Business; Computer science; Complex network; Engineering; Mathematics; Psychology; Statistics; Structural engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006238014,0.0001785838,0.0003602274,0.001592828,0.0006466614,0.001041738,0.0008331786,0.0008485614,0.006130159],"category_scores_gemma":[0.00374987,0.0002951658,0.0005344113,0.001009062,0.0008143,0.001671245,0.0006730112,0.0005027851,0.000384494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009767258,"about_ca_system_score_gemma":0.0005844763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004617218,"about_ca_topic_score_gemma":0.002722234,"domain_scores_codex":[0.9998602,0.00003807358,0.000005403052,0.00003601786,0.00002307976,0.00003728337],"domain_scores_gemma":[0.9979691,0.0009785997,0.0004823858,0.0001588432,0.0002185393,0.0001924626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002107424,0.0001550104,0.05044101,0.0001045526,0.00009109013,0.0008468591,0.0006541124,0.4220823,0.006071931,0.494894,0.004785279,0.01966312],"study_design_scores_gemma":[0.00001340547,0.00003367339,0.02005602,0.00001649976,0.00003054276,0.0001733839,0.0002711448,0.9005969,0.0006955912,0.07716002,0.0009296089,0.00002316657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9491844,0.0003054135,0.0402444,0.0007185995,0.00001694503,0.00003278748,0.0004718239,0.00007771005,0.008947913],"genre_scores_gemma":[0.9957635,0.0001276446,0.001695702,0.00002201417,0.00001524774,0.00001741735,0.0001598383,0.000009757619,0.00218876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006130159,"threshold_uncertainty_score":0.0205074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02475874318734329,"score_gpt":0.2212851425719456,"score_spread":0.1965263993846023,"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."}}