{"id":"W3135518602","doi":"","title":"Journalists, Judges, and State Officials: How Russian Courts Adjudicate Defamation Lawsuits Against the Media","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Cybersecurity and Cyber Warfare Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Lawsuit; Law; Plaintiff; Political science; Politics; Reputation; State (computer science); Economic Justice; Adjudication","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004436963,0.0001348819,0.0003817856,0.002430321,0.003098119,0.006173074,0.0006862584,0.001442516,0.005340705],"category_scores_gemma":[0.0278306,0.0003796907,0.0002043652,0.003148518,0.00155624,0.002796696,0.00231983,0.001434696,0.002107201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001962396,"about_ca_system_score_gemma":0.0016691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03056178,"about_ca_topic_score_gemma":0.06391211,"domain_scores_codex":[0.9949292,0.002793958,0.000308293,0.0006957276,0.0006454723,0.000627405],"domain_scores_gemma":[0.9757013,0.0156331,0.005050159,0.0009133117,0.001544184,0.001157946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003345248,0.0003317557,0.6671803,0.000406362,0.000127056,0.001236098,0.2066267,0.0006336425,0.001938374,0.01432601,0.03900111,0.06785807],"study_design_scores_gemma":[0.00004299632,0.00009173466,0.7188866,0.0003719891,0.00007427879,0.0004206716,0.1990089,0.001431705,0.000696864,0.004471087,0.07443605,0.00006717676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569319,0.001207247,0.0004399175,0.004242192,0.00006737892,0.00006047611,0.001887878,0.00002219104,0.03514079],"genre_scores_gemma":[0.989986,0.001131997,0.0005382344,0.0008176756,0.00009838604,0.00005339595,0.002157117,0.0000314318,0.005185737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03056178,"threshold_uncertainty_score":0.06076777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194219089413434,"score_gpt":0.2821387148142335,"score_spread":0.2627168058728901,"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."}}