{"id":"W4383652676","doi":"10.1093/jnlids/idad017","title":"A tale of policy carve-outs and general exceptions: <i>Eco Oro v Colombia</i> as a case study","year":2023,"lang":"en","type":"article","venue":"Journal of International Dispute Settlement","topic":"International Arbitration and Investment Law","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Expropriation; Tribunal; Scope (computer science); Duty; Political science; State (computer science); Free trade agreement; Law and economics; Law; Investment (military); Business; Free trade; Economics; International trade; Politics","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":[],"consensus_categories":[],"category_scores_codex":[0.0005057335,0.000142617,0.0002004475,0.0007176015,0.00009991281,0.0001879089,0.0002379113,0.00003012258,0.000567951],"category_scores_gemma":[0.0001253348,0.0001244504,0.000123637,0.00034552,0.00005448459,0.0008821805,0.0001850303,0.0001141308,0.0001062779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001073871,"about_ca_system_score_gemma":0.00008255206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017485,"about_ca_topic_score_gemma":0.0002425538,"domain_scores_codex":[0.9982764,0.00002070005,0.0007116126,0.0001528397,0.000685284,0.0001532007],"domain_scores_gemma":[0.9985371,0.00004499557,0.0006351953,0.00009574499,0.0006566296,0.00003036945],"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":[0.0004189573,0.002841262,0.105966,0.0001629793,0.001796271,0.004082767,0.002377105,0.001336785,0.005203463,0.7313061,0.1390816,0.005426707],"study_design_scores_gemma":[0.017466,0.001611976,0.242514,0.0005184505,0.0006235988,0.004615741,0.02397159,0.02082253,0.001576984,0.03055464,0.6543539,0.001370609],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738821,0.00002461332,0.00008401606,0.004841182,0.0008797541,0.0002611869,0.00004692012,0.00002208159,0.01995812],"genre_scores_gemma":[0.9913265,0.00003802001,0.0001452356,0.00514411,0.001527363,0.00001534224,0.00005708406,0.00001598699,0.001730419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7007515,"threshold_uncertainty_score":0.6218665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01674625229084615,"score_gpt":0.2920021136260593,"score_spread":0.2752558613352131,"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."}}