{"id":"W4297995915","doi":"10.1126/science.adf0775","title":"Signs of state meddling seen in Russian academy election","year":2022,"lang":"en","type":"article","venue":"Science","topic":"Russia and Soviet political economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"State (computer science); Political science; Law; Computer science","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006140899,0.0001232706,0.0001817538,0.0007378739,0.003271617,0.00179045,0.0002163045,0.001064296,0.006355131],"category_scores_gemma":[0.003112488,0.0001433066,0.0001358334,0.0006321251,0.0007444361,0.0005245933,0.001219883,0.003006462,0.001128289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007839148,"about_ca_system_score_gemma":0.0006939761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006762468,"about_ca_topic_score_gemma":0.02112279,"domain_scores_codex":[0.999449,0.0001337594,0.0000227188,0.00005193604,0.0001387706,0.0002037996],"domain_scores_gemma":[0.9985372,0.0004012864,0.0003342736,0.00007353368,0.0002352523,0.0004185659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001620542,0.0003864839,0.3612033,0.0003815538,0.0001274355,0.01243334,0.1482323,0.0008788404,0.01002465,0.02864306,0.3479462,0.08812229],"study_design_scores_gemma":[0.00004319921,0.0002423495,0.6181326,0.0001871902,0.00004713495,0.001953221,0.1480927,0.0008966228,0.003037605,0.002167518,0.2251067,0.00009314653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.906514,0.000307266,0.0003263623,0.01017087,0.001050337,0.00002917912,0.000823594,0.0001197071,0.08065869],"genre_scores_gemma":[0.989159,0.0001328646,0.0001012027,0.000787411,0.0001232867,0.000011748,0.0002949204,0.0000193263,0.009370166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9967284,"threshold_uncertainty_score":0.02126002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375608046077829,"score_gpt":0.3415003672312526,"score_spread":0.3177442867704743,"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."}}