{"id":"W3193778551","doi":"","title":"Повседневная жизнь населения Сибирской губернии в контексте реформ Петра I в первой четверти XVIII века","year":2021,"lang":"ru","type":"article","venue":"Nauchnyi Dialog","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Modernization theory; Everyday life; Quarter (Canadian coin); Population; Clothing; Peasant; State (computer science); Ethnology; Geography; Legislature; History; Political science; Sociology; Economic growth; Demography; Law; 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":[0.001142737,0.000283392,0.0001879545,0.001450068,0.001853809,0.003354037,0.0002749612,0.0005209342,0.01231667],"category_scores_gemma":[0.002065276,0.0002642353,0.0001876991,0.001730187,0.002262079,0.0009126202,0.0009561285,0.001333543,0.004446638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259103,"about_ca_system_score_gemma":0.002614278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004946472,"about_ca_topic_score_gemma":0.008229529,"domain_scores_codex":[0.9991313,0.0002290504,0.0000571711,0.0001187413,0.000377131,0.00008676],"domain_scores_gemma":[0.9992024,0.0002416395,0.0001269515,0.0001265273,0.0002425167,0.00005991826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006978968,0.00004601603,0.005845419,0.0003444472,0.00002488278,0.001215958,0.02272694,0.00124283,0.008990807,0.4850326,0.01267928,0.461781],"study_design_scores_gemma":[0.000008459456,0.00007011628,0.01616846,0.0002545601,0.00003221286,0.001356408,0.004530922,0.0004620954,0.003486039,0.05769433,0.915881,0.00005541193],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1366875,0.04221502,0.06615604,0.007534068,0.002598785,0.0001998237,0.0005138589,0.0003015119,0.7437934],"genre_scores_gemma":[0.7618722,0.02918752,0.04615335,0.0003516464,0.0007751538,0.0002414311,0.0002598758,0.0001442683,0.1610146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01231667,"threshold_uncertainty_score":0.04120338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03110286574341826,"score_gpt":0.2961221231103293,"score_spread":0.2650192573669111,"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."}}