{"id":"W1422126550","doi":"10.2139/ssrn.2566128","title":"Factors Affecting Language Change","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Linguistics, Language Diversity, and Identity","field":"Arts and Humanities","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Burman University","funders":"","keywords":"Language change; Linguistics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001531651,0.0001433414,0.0002754689,0.001654912,0.002567478,0.002856294,0.0005413417,0.0007960644,0.01499877],"category_scores_gemma":[0.01303902,0.0001461655,0.0002878738,0.001782339,0.001716902,0.001426492,0.00157095,0.001389178,0.001274979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001496813,"about_ca_system_score_gemma":0.00203371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201277,"about_ca_topic_score_gemma":0.02238795,"domain_scores_codex":[0.9977175,0.0006197778,0.0001522744,0.0003502771,0.0003801365,0.0007800683],"domain_scores_gemma":[0.9918807,0.002987184,0.001573317,0.0003585836,0.001467062,0.001733133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007712604,0.0005845956,0.9075792,0.00006826882,0.00005782126,0.002252983,0.03667271,0.0001539191,0.003846167,0.005540367,0.001501734,0.04097098],"study_design_scores_gemma":[0.00001880129,0.0001478343,0.9350988,0.00004030959,0.0000315726,0.001296697,0.04778447,0.0001730027,0.001114878,0.001656999,0.0126149,0.00002172083],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880327,0.0003385269,0.0001364925,0.001339969,0.00003738008,0.00002512787,0.0001224498,0.000006664073,0.009960776],"genre_scores_gemma":[0.9977556,0.0001042698,0.00005713083,0.0001130125,0.00002930616,0.000007798823,0.00004777021,0.000005458056,0.001879768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201277,"threshold_uncertainty_score":0.05017585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02975737411611883,"score_gpt":0.2433377630152844,"score_spread":0.2135803888991655,"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."}}