{"id":"W4292551538","doi":"10.5539/ijel.v12n6p13","title":"The Colexification of Xià in Modern Chinese","year":2022,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Categorization, perception, and language","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Semantics (computer science); Syntax; Lexical semantics; China; Value (mathematics); Lexical item; Mathematics; Philosophy; Computer science; Political science; Law; Statistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0006604026,0.0000653274,0.0001116891,0.0001791375,0.00007182561,0.0000245387,0.0004672042,0.0000292685,0.0005106772],"category_scores_gemma":[0.01060372,0.00005301418,0.00007343094,0.0001573113,0.00004717762,0.00002480726,0.0000467442,0.0002486275,0.000001844197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001179662,"about_ca_system_score_gemma":0.00007975127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005813806,"about_ca_topic_score_gemma":0.00006006444,"domain_scores_codex":[0.9987147,0.000113564,0.0005548928,0.00007941335,0.0004487188,0.00008869927],"domain_scores_gemma":[0.9939215,0.0002468248,0.0004518013,0.0001313047,0.005221042,0.0000275695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002614314,0.002635744,0.3295342,0.00002478503,0.0008071476,0.0002103876,0.1623185,0.03682962,0.0006318495,0.3988268,0.04315998,0.0224067],"study_design_scores_gemma":[0.003551958,0.0003566338,0.288949,0.00002777625,0.00005777463,0.00003434622,0.02135627,0.002237997,0.00006025501,0.02535444,0.657726,0.0002874528],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.859751,0.001111026,0.00197055,0.0001260328,0.06213937,0.0001689199,0.0000995637,0.00001983573,0.07461365],"genre_scores_gemma":[0.9949048,0.00005176197,0.00008690601,0.00006237195,0.004322882,0.000005892195,0.00002590277,0.00001117058,0.0005282733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6145661,"threshold_uncertainty_score":0.9977304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226554530328783,"score_gpt":0.3242427338830169,"score_spread":0.3119771885797291,"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."}}