{"id":"W2603266381","doi":"","title":"Канадская модель государственной юридической службы и ее адаптация в России","year":2014,"lang":"ru","type":"article","venue":"Ленинградский юридический журнал","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":[0.001122013,0.0002553149,0.0001655954,0.001693321,0.002922876,0.00495129,0.0004620454,0.0009411428,0.009886491],"category_scores_gemma":[0.003477123,0.0003564002,0.0002231439,0.001876655,0.005715131,0.002027231,0.001507766,0.001765064,0.002629502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004750265,"about_ca_system_score_gemma":0.007776356,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03168071,"about_ca_topic_score_gemma":0.04712795,"domain_scores_codex":[0.9985354,0.0002945499,0.00005017705,0.0001609704,0.0007717874,0.0001870722],"domain_scores_gemma":[0.9988722,0.0003392,0.000129522,0.0001703139,0.0003747798,0.0001140052],"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":[0.00001111708,0.000009607706,0.0006780274,0.00002870843,0.000003205412,0.0001814948,0.002450543,0.0002250193,0.0006920719,0.9734862,0.001383326,0.02085061],"study_design_scores_gemma":[0.00002017067,0.00005455941,0.005793663,0.0001547927,0.00002951341,0.0008151384,0.005008048,0.00118302,0.002220133,0.4863204,0.4983517,0.0000488748],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07152579,0.003412285,0.0661713,0.005388209,0.0002688903,0.0001879776,0.0003853843,0.0002240351,0.8524362],"genre_scores_gemma":[0.8949131,0.002250233,0.02715513,0.0002432988,0.0000991479,0.0001810315,0.0001250608,0.00007514716,0.0749578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9683193,"threshold_uncertainty_score":0.06299257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008924429550942354,"score_gpt":0.2572197477360932,"score_spread":0.2482953181851508,"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."}}