{"id":"W7135770295","doi":"","title":"Constructing Achievement in the International Criminal Tribunal for the Former Yugoslavia (ICTY):A Corpus-Based Critical Discourse Analysis’","year":2016,"lang":"da","type":"article","venue":"Research at the University of Copenhagen (University of Copenhagen)","topic":"Gender, Security, and Conflict","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for International Governance Innovation","funders":"","keywords":"Tribunal; Critical discourse analysis; Government (linguistics); Criticism; Criminal justice","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["sts","insufficient_payload"],"category_scores_codex":[0.007483522,0.0002902445,0.000581219,0.0003862527,0.003873852,0.0001354734,0.004559377,0.0002146557,0.1276725],"category_scores_gemma":[0.0006504968,0.0002014944,0.0007620762,0.001635256,0.005857966,0.0006023732,0.0009226389,0.0005448906,0.002898765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008144947,"about_ca_system_score_gemma":0.001263592,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.006972957,"about_ca_topic_score_gemma":0.03422697,"domain_scores_codex":[0.9935829,0.002092749,0.0003720204,0.0006472133,0.002288002,0.001017113],"domain_scores_gemma":[0.9907163,0.00671089,0.0003805039,0.0008096398,0.001132755,0.0002498636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008262163,0.001781343,0.001328803,0.0003260972,0.004095603,0.000290674,0.1462848,0.0001580074,0.001925098,0.05121967,0.7485264,0.03580137],"study_design_scores_gemma":[0.003211806,0.000469403,0.01845288,0.0001385264,0.001683666,0.000003607244,0.4730666,0.001596839,0.0003916836,0.0001015152,0.5005499,0.0003335876],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.705502,0.006301483,0.04698483,0.1192278,0.0008131503,0.005082563,0.002162353,0.00004384887,0.113882],"genre_scores_gemma":[0.9067628,0.0003861146,0.0001955079,0.0001037827,0.00009268385,0.000001117933,0.00004323064,0.00001240096,0.09240229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3267818,"threshold_uncertainty_score":0.9996397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103991188376558,"score_gpt":0.3723494884712968,"score_spread":0.2683583000947388,"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."}}