{"id":"W3212517299","doi":"10.25681/iaras.2018.978-5-94375-278-0.210-215","title":"КАРТОГРАФИЧЕСКИЙ МЕТОД В ИЗУЧЕНИИ ПОМЕЩИЧЬИХ ВЛАДЕНИЙ ПСКОВСКОЙ ГУБЕРНИИ В ПОСЛЕДНЕЙ ЧЕТВЕРТИ XVIII В.","year":2018,"lang":"en","type":"article","venue":"Археология и история Пскова и Псковской земли","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Landlord; Quarter (Canadian coin); Geography; Distribution (mathematics); State (computer science); Archaeology; Cartography; History; Law; Political science; 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":[0.001067967,0.0002796404,0.0002777742,0.001921415,0.001599777,0.004442412,0.0004132846,0.0005654934,0.0215189],"category_scores_gemma":[0.00293024,0.0004430229,0.0003141878,0.001959601,0.002174123,0.001749437,0.001342966,0.001374334,0.006013099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001400468,"about_ca_system_score_gemma":0.002706899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005673977,"about_ca_topic_score_gemma":0.01238843,"domain_scores_codex":[0.9989951,0.0001802033,0.00005368783,0.0001989131,0.0004721697,0.00009986872],"domain_scores_gemma":[0.9990541,0.0002921375,0.0001072434,0.0002295228,0.0002458787,0.00007108446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000119725,0.00007530821,0.004108341,0.0005753887,0.00003641841,0.001009381,0.008533181,0.0008328334,0.01121318,0.616316,0.0207575,0.3364228],"study_design_scores_gemma":[0.00001554843,0.00006959843,0.01009721,0.0003117233,0.00005032022,0.0009716066,0.003068523,0.0004865046,0.007017673,0.07724883,0.9005935,0.00006889815],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.100015,0.02659644,0.07191092,0.007296236,0.002823574,0.0002639853,0.002929689,0.0004550304,0.7877092],"genre_scores_gemma":[0.7084361,0.02111326,0.08056307,0.000467225,0.0007229023,0.0004414427,0.001179356,0.000330959,0.1867457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0215189,"threshold_uncertainty_score":0.07198787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03341680842005893,"score_gpt":0.3502673746626074,"score_spread":0.3168505662425484,"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."}}