{"id":"W2795524142","doi":"10.22363/2313-2299-2018-9-1-136-157","title":"The representation of canada in political discourse","year":2018,"lang":"en","type":"article","venue":"RUDN Journal of Language Studies Semiotics and Semantics","topic":"Discourse Analysis and Cultural Communication","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Politics; Representation (politics); Linguistics; Political communication; Subject (documents); Context (archaeology); Sociology; Discourse analysis; Cognitive linguistics; Political science; Social science; Cognition; Psychology; Computer science; Law; History","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":[0.0007363335,0.00004539141,0.0001756907,0.0000252409,0.0003022018,0.00002731391,0.0001555191,0.00001851363,0.000003516321],"category_scores_gemma":[0.0008181077,0.00002677196,0.00003739199,0.000160617,0.0004825931,0.00006647398,0.00004477102,0.00008584753,8.97022e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005595906,"about_ca_system_score_gemma":0.0001617246,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02627107,"about_ca_topic_score_gemma":0.6086282,"domain_scores_codex":[0.9990567,0.0001528089,0.0003049289,0.00004198265,0.0002853127,0.0001582819],"domain_scores_gemma":[0.9989749,0.0002926096,0.0002206003,0.0001027882,0.0003578289,0.00005129734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008629254,0.0001764479,0.05046886,0.00006181629,0.0008550455,0.00008401664,0.2708191,0.0000577447,0.0008695661,0.6503245,0.01035006,0.01584649],"study_design_scores_gemma":[0.0002133615,0.00008140829,0.005935358,0.0001316296,0.0001146698,0.000005685674,0.9873931,0.0001634552,0.0004908119,0.003453027,0.001935674,0.00008175516],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754741,0.00497917,0.00002151599,0.01489946,0.0001559756,0.00004011501,0.000001514469,0.000001098215,0.004427075],"genre_scores_gemma":[0.9960327,0.003339182,0.0001031034,0.0000607913,0.000183289,1.457931e-7,3.305087e-7,0.000002174685,0.000278312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7165741,"threshold_uncertainty_score":0.980213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03187746283907563,"score_gpt":0.4015258369972965,"score_spread":0.3696483741582209,"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."}}