{"id":"W3171150266","doi":"10.5267/j.jpm.2021.5.003","title":"Bibliometric evaluation of research on political risks in construction projects","year":2021,"lang":"en","type":"article","venue":"Journal of Project Management","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chinese Academy of Engineering; National Science Foundation","keywords":"Political risk; Politics; Context (archaeology); Risk management; Political science; Content analysis; Data science; Risk analysis (engineering); Business; Computer science; Sociology; Social science; Geography; Finance","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01707327,0.0008464137,0.001840407,0.2183805,0.00211022,0.009189611,0.001046613,0.001029919,0.006576425],"category_scores_gemma":[0.1069892,0.0003327673,0.001425358,0.2634288,0.001515917,0.006146875,0.003672909,0.0006339242,0.001149486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003497851,"about_ca_system_score_gemma":0.007072885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004308452,"about_ca_topic_score_gemma":0.005099233,"domain_scores_codex":[0.9620038,0.007756361,0.00724163,0.001776117,0.02018208,0.001040016],"domain_scores_gemma":[0.8543376,0.08977029,0.02123053,0.004797825,0.02792561,0.001938159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003967025,0.0002366685,0.2479756,0.0492037,0.001437933,0.001151477,0.01156822,0.002378731,0.00260193,0.03359518,0.03822828,0.6112255],"study_design_scores_gemma":[0.00006759357,0.0002774321,0.6101775,0.01661533,0.002804241,0.002340884,0.02799372,0.005285664,0.004356084,0.0195842,0.3102099,0.0002874814],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5004606,0.1805694,0.01359431,0.007801629,0.001451771,0.00132946,0.0582838,0.0008991227,0.2356099],"genre_scores_gemma":[0.8741034,0.08172527,0.01109229,0.0003528887,0.00116877,0.001157698,0.02429584,0.0001500471,0.005953839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7816195,"threshold_uncertainty_score":0.09029317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1848197151092685,"score_gpt":0.4536114605820278,"score_spread":0.2687917454727593,"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."}}