{"id":"W4392920142","doi":"10.3390/languages9030100","title":"(Heritage) Russian Case Marking: Variation and Paths of Change","year":2024,"lang":"en","type":"article","venue":"Languages","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Variation (astronomy); Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001192398,0.0001429612,0.0001503447,0.00126227,0.0004429534,0.001032852,0.0002934847,0.0001811673,0.002650052],"category_scores_gemma":[0.004852027,0.0001677397,0.0001706959,0.001009514,0.001022284,0.0007385697,0.001118297,0.0003019362,0.0003646518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005042042,"about_ca_system_score_gemma":0.0002496623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008023486,"about_ca_topic_score_gemma":0.01222316,"domain_scores_codex":[0.9989858,0.0003490502,0.00006668872,0.0003262012,0.0001526204,0.000119531],"domain_scores_gemma":[0.9973632,0.001228958,0.000618823,0.0003603681,0.0003247261,0.0001040297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003965652,0.00004606937,0.8405542,0.00009017192,0.0001217124,0.0007872544,0.059491,0.0005193031,0.02051295,0.005953647,0.0005926398,0.0709344],"study_design_scores_gemma":[0.00000259348,0.00003957006,0.9872578,0.00001150644,0.0000140763,0.0004950603,0.007390806,0.0004426392,0.001001234,0.0007968494,0.002535578,0.00001232862],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974139,0.0001029538,0.000344824,0.0000301623,0.000002233414,0.000004397225,0.0001222097,0.000007821003,0.001971512],"genre_scores_gemma":[0.9992854,0.00003995683,0.0002374107,0.000002794283,0.000001050682,0.000003310612,0.0001046761,0.000007776294,0.0003176237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008023486,"threshold_uncertainty_score":0.0159536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04535307468857143,"score_gpt":0.3456779261071359,"score_spread":0.3003248514185645,"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."}}