{"id":"W2885550214","doi":"10.3968/10284","title":"Understanding of Sexism in English Vocabulary in Chinese Context","year":2018,"lang":"en","type":"article","venue":"Studies in literature and language","topic":"Gender Studies in Language","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Phenomenon; Vocabulary; Meaning (existential); Context (archaeology); Linguistics; Psychology; Cultural phenomenon; China; Sociology; History; Epistemology; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008395188,0.0001432245,0.0003508881,0.0002498119,0.0001197883,0.00002563838,0.0001458772,0.0001121206,0.00002054426],"category_scores_gemma":[0.0009990486,0.0001181088,0.00002996423,0.000901755,0.0008290011,0.0001667739,0.0001572235,0.000249618,6.921122e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001613822,"about_ca_system_score_gemma":0.00002414756,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000688364,"about_ca_topic_score_gemma":0.0529667,"domain_scores_codex":[0.9987694,0.0001993335,0.0002701216,0.0002527879,0.0001837008,0.0003246489],"domain_scores_gemma":[0.9994302,0.0002594418,0.00005957175,0.0001515248,0.00006787007,0.00003137349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002444519,0.00003134743,0.0765936,0.00006933755,0.00002301976,0.0001342891,0.9130368,3.231446e-7,0.00002626232,0.009021404,0.0004138634,0.0006253223],"study_design_scores_gemma":[0.0009926925,0.00007280586,0.02074666,0.0005838058,0.000005602401,0.000001683686,0.9710418,0.000004061865,0.00002340396,0.004621083,0.00170541,0.0002009649],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8783495,0.06027591,0.00000592984,0.000227858,0.0007668454,0.0002375613,0.00001136881,0.00002506969,0.06009997],"genre_scores_gemma":[0.997716,0.001209031,0.0001125369,0.0002306057,0.0003961855,0.00001299029,0.000002663294,0.00000838198,0.0003115749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1193665,"threshold_uncertainty_score":0.9643142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05931417420655405,"score_gpt":0.3705701342017775,"score_spread":0.3112559599952235,"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."}}