{"id":"W7118630031","doi":"10.7256/2585-7797.2025.4.76337","title":"Employees of the magistrates of Priikamye in the focus of network analysis (based on materials from urban institutions of the first quarter of the 19th century)","year":2025,"lang":"en","type":"article","venue":"Историческая информатика","topic":"Biographical and Historical Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Magistrate; Centrality; Debt; Subject (documents); Social network analysis; Novelty","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":[0.0005093859,0.0001527759,0.0001364279,0.001524257,0.001797637,0.0008392579,0.0002799325,0.000181072,0.007913522],"category_scores_gemma":[0.001147629,0.0002023562,0.00009977521,0.00235558,0.0005099485,0.0005690826,0.001125474,0.0002750343,0.001217186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001686895,"about_ca_system_score_gemma":0.0009533677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0124026,"about_ca_topic_score_gemma":0.03755761,"domain_scores_codex":[0.9997502,0.00005511653,0.0000106525,0.0000538472,0.00003353223,0.00009678401],"domain_scores_gemma":[0.9993705,0.0002370153,0.0001652001,0.00003290681,0.00005929934,0.0001349873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003070183,0.00009826866,0.5796205,0.0005395985,0.00003072343,0.002143538,0.2931733,0.0005871375,0.005180936,0.01017697,0.006488182,0.1016538],"study_design_scores_gemma":[0.000005238338,0.00006461211,0.7767629,0.00008879881,0.00001516806,0.0005413912,0.1378657,0.0002573817,0.001653428,0.0003362587,0.08239366,0.00001550957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911383,0.0003906491,0.0003028111,0.0001406013,0.000009150663,0.00003285496,0.0004366926,0.00001005237,0.007539028],"genre_scores_gemma":[0.9804524,0.0006834663,0.0006724609,0.0000478355,0.00001247414,0.00006315731,0.0006379632,0.00001017385,0.01742001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0124026,"threshold_uncertainty_score":0.0264734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310972211496945,"score_gpt":0.1990528109477376,"score_spread":0.1859430888327681,"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."}}