{"id":"W2355037099","doi":"","title":"An Analysis of the Current Situation of the She Nationality Language Use","year":2009,"lang":"en","type":"article","venue":"Wanxi Xueyuan xuebao","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nationality; Settlement (finance); Quarter (Canadian coin); Inheritance (genetic algorithm); Population; Endangered species; Geography; Political science; Sociology; Economic growth; Demography; Law; Business; Immigration; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008479676,0.00004976545,0.0001230855,0.0000682711,0.0001986631,0.00002359759,0.0003127586,0.00004253368,0.0001532467],"category_scores_gemma":[0.001782508,0.00003092012,0.0001336701,0.0007846323,0.000143102,0.00008383786,0.00001972296,0.00007960851,0.000001766809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008941391,"about_ca_system_score_gemma":0.0001853412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002839866,"about_ca_topic_score_gemma":0.005404014,"domain_scores_codex":[0.9987131,0.0003503398,0.0002155203,0.000116276,0.0005042914,0.000100493],"domain_scores_gemma":[0.9990363,0.0001033867,0.0002211073,0.0002972395,0.0003090237,0.00003295103],"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":[0.00001552411,0.0003763192,0.1072728,0.000006059234,0.0001289727,3.322741e-7,0.05088273,0.0009590699,0.002757393,0.8234778,0.0007753439,0.01334766],"study_design_scores_gemma":[0.000123173,0.00001254098,0.9833893,0.000006199705,0.0002339354,7.133224e-8,0.0008527998,0.001088202,0.0005530153,0.002981414,0.01070236,0.0000570219],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911093,0.00003690724,0.0004980506,0.002273341,0.0004997699,0.0001802735,0.00004850014,0.00001771138,0.005336121],"genre_scores_gemma":[0.9992159,0.000005631719,0.00009246328,0.0002950624,0.0001005847,0.000001582613,0.00001313897,0.00000183506,0.0002737911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8761165,"threshold_uncertainty_score":0.4293047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03239252712956393,"score_gpt":0.3654209620023562,"score_spread":0.3330284348727923,"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."}}