{"id":"W3125241912","doi":"","title":"Extractive Industries and Investor–State Arbitration: Enforcing Home Standards Abroad","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Mining and Resource Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Language change; Arbitration; State (computer science); Business; Developing country; Poverty; Control (management); Economic growth; Law; Economics; 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":[0.003142035,0.0001848947,0.0002343498,0.0004787646,0.004033796,0.007541986,0.0008522994,0.003376515,0.006457368],"category_scores_gemma":[0.005339633,0.000154308,0.0003249008,0.0006748276,0.01097559,0.0042982,0.004303056,0.003503047,0.0002879284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004220351,"about_ca_system_score_gemma":0.005253504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01834925,"about_ca_topic_score_gemma":0.03076887,"domain_scores_codex":[0.9981142,0.0007450323,0.00006654569,0.0002131809,0.0002954042,0.0005656375],"domain_scores_gemma":[0.9980028,0.0009275331,0.0004451643,0.0002032959,0.0002221585,0.0001990583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001180566,0.00002268252,0.001631583,0.00001605128,0.000006757308,0.0001831917,0.003425362,0.0004109673,0.000137526,0.984632,0.00139277,0.008129331],"study_design_scores_gemma":[0.0000592283,0.0001039674,0.009261542,0.000565194,0.00007295522,0.0004476172,0.02299248,0.005082589,0.002597352,0.767016,0.1917325,0.000068587],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.184333,0.002038763,0.01637546,0.02074904,0.0001601315,0.00006714155,0.00002124761,0.00003846606,0.7762167],"genre_scores_gemma":[0.9775581,0.0005114813,0.0009569098,0.00108016,0.0000343647,0.00001394761,0.000006133369,0.000008741918,0.01983017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01834925,"threshold_uncertainty_score":0.0364849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004518838755227027,"score_gpt":0.2119010061616363,"score_spread":0.2073821674064093,"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."}}