{"id":"W4393240691","doi":"10.28995/2073-0101-2024-1-179-192","title":"Counteraction to the spread of anti-government publications on the railroads of Russia in the last quarter of the XIX - early XX century. On the materials of the gendarme railway police","year":2024,"lang":"en","type":"article","venue":"Herald of an Archivist","topic":"Library Science and Information","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Christian ministry; Quarter (Canadian coin); Empire; Law; Exhibition; Law enforcement; Principle of legality; Spanish Civil War; China; Political science; History; Public administration; Archaeology","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":[0.001912659,0.000182511,0.0001676678,0.002403306,0.00273773,0.003981568,0.000362915,0.0009237159,0.002485286],"category_scores_gemma":[0.00591367,0.0002167357,0.0001150825,0.002156426,0.003752298,0.001538378,0.001931455,0.001215678,0.0005101536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001851682,"about_ca_system_score_gemma":0.001560377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003597508,"about_ca_topic_score_gemma":0.007162426,"domain_scores_codex":[0.9987304,0.000472889,0.00007399515,0.0001753005,0.0003712895,0.0001760014],"domain_scores_gemma":[0.9958392,0.001623187,0.001619724,0.0003622594,0.0003806324,0.0001750484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001797861,0.00005527496,0.07219759,0.001228996,0.00007276178,0.005171794,0.4901203,0.0003334017,0.0069489,0.2211842,0.02022327,0.1822837],"study_design_scores_gemma":[0.00001011215,0.0001288276,0.1581969,0.001143316,0.00003299435,0.002986842,0.07685505,0.000143788,0.003318042,0.003164317,0.7539874,0.00003234982],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8609058,0.03174201,0.0006048704,0.01311347,0.0009131951,0.00002191336,0.0002341878,0.00005977,0.09240483],"genre_scores_gemma":[0.9804608,0.005969908,0.0002050995,0.0004271074,0.0002883427,0.000006434271,0.00006925652,0.00002019934,0.01255291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003981568,"threshold_uncertainty_score":0.01343495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01268052110676197,"score_gpt":0.2350896849412527,"score_spread":0.2224091638344908,"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."}}