{"id":"W4402109620","doi":"10.55016/ojs/jet.v42i2.52455","title":"The Chinese, Diversity, and the History of Science","year":2018,"lang":"en","type":"article","venue":"Journal of educational thought.","topic":"History of Science and Medicine","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversity (politics); History; Sociology; Anthropology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001317066,0.00003451758,0.00007500438,0.00007229187,0.001533855,0.00001606146,0.0003441377,0.000005399031,0.0003671067],"category_scores_gemma":[0.0003791574,0.00001431795,0.0000326994,0.00005507908,0.01278507,0.0002490185,0.00008833062,0.00006855139,0.000004869994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008820134,"about_ca_system_score_gemma":0.0005415147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003928803,"about_ca_topic_score_gemma":0.00006765722,"domain_scores_codex":[0.9993475,0.00001974045,0.0001512785,0.00004275288,0.0003690313,0.00006970036],"domain_scores_gemma":[0.998844,0.0002860242,0.0002189848,0.00007413424,0.0005322224,0.0000445825],"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":[0.00006352263,0.00003893272,0.001426639,0.0000040916,0.00001166353,1.81746e-7,0.1383755,1.671843e-7,0.0001172279,0.7154502,0.1435048,0.00100701],"study_design_scores_gemma":[0.0002695992,0.00008156728,0.009908002,0.00001880082,0.00001512031,0.00001834541,0.00428965,0.000006563386,0.000007050767,0.0136612,0.9716979,0.00002625126],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7643213,0.005394281,0.000003548191,0.02572859,0.01157199,0.00005811206,8.640761e-7,0.000001330896,0.19292],"genre_scores_gemma":[0.9449215,0.00009563301,0.00006219846,0.0004832179,0.002274716,3.386187e-7,4.877187e-8,0.000001286059,0.05216108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.828193,"threshold_uncertainty_score":0.999766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03388539703382789,"score_gpt":0.2730458355416933,"score_spread":0.2391604385078654,"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."}}