{"id":"W3123718503","doi":"10.29038/eejpl.2017.4.1.kry","title":"Психолінгвістичні аспекти маніпулятивного перекладу у медійному просторі","year":2017,"lang":"uk","type":"article","venue":"East European Journal of Psycholinguistics","topic":"Innovative Educational Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Art","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":[0.002290877,0.0005014093,0.0003561066,0.002104945,0.001788071,0.004938346,0.000593945,0.001059773,0.02634037],"category_scores_gemma":[0.005996074,0.0005180424,0.0005957877,0.002592969,0.003448881,0.003000904,0.001808159,0.001942373,0.01282862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002603139,"about_ca_system_score_gemma":0.003309211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004198476,"about_ca_topic_score_gemma":0.004922331,"domain_scores_codex":[0.9971111,0.0008270168,0.0001719121,0.0003467641,0.001333495,0.0002097039],"domain_scores_gemma":[0.996155,0.001430781,0.0004797964,0.0006934371,0.001034775,0.0002062591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002782387,0.0001121104,0.004250509,0.0009734848,0.00005021547,0.001405198,0.01231742,0.001620012,0.01849022,0.6483108,0.02376877,0.288423],"study_design_scores_gemma":[0.00002511615,0.00009511907,0.007542902,0.0004572412,0.00005821252,0.001274265,0.004515149,0.00120553,0.01044932,0.1311601,0.8431336,0.00008328991],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0543081,0.01669754,0.1183622,0.01234951,0.00202887,0.0003745645,0.0008292224,0.0005946658,0.7944553],"genre_scores_gemma":[0.683871,0.01902093,0.1094503,0.001206114,0.0008226373,0.0006406987,0.000715975,0.0008050452,0.1834673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02634037,"threshold_uncertainty_score":0.0881173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09020785615980205,"score_gpt":0.351018097364106,"score_spread":0.260810241204304,"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."}}