{"id":"W2060094373","doi":"10.1016/j.tate.2014.11.004","title":"Content knowledge and pedagogical content knowledge in Taiwanese and German mathematics teachers","year":2014,"lang":"en","type":"article","venue":"Teaching and Teacher Education","topic":"Mathematics Education and Teaching Techniques","field":"Social Sciences","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Max-Planck-Gesellschaft; Deutsche Forschungsgemeinschaft; Strategic Innovation Fund","keywords":"German; Mathematics education; Subject matter; Teacher education; Selection (genetic algorithm); Pedagogy; Psychology; Subject (documents); Computer science; Curriculum; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004707544,0.0002090002,0.0002966514,0.0002072685,0.0005903117,0.0001915147,0.000149142,0.0001659667,0.00003423245],"category_scores_gemma":[0.001148058,0.0001877388,0.00003447201,0.00008832209,0.0002815672,0.0002033974,0.00007308246,0.0006342672,0.000008424909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001373967,"about_ca_system_score_gemma":0.0001731079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002596412,"about_ca_topic_score_gemma":0.000860896,"domain_scores_codex":[0.9978676,0.0009712029,0.0003659692,0.0003493637,0.0001585702,0.0002872454],"domain_scores_gemma":[0.9988974,0.0004293847,0.0001444268,0.0002188324,0.00006370289,0.0002463086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003286255,0.00110642,0.01343104,0.0001076933,0.000009032727,1.387221e-7,0.5009591,2.083506e-8,0.0001642377,0.328121,0.001194041,0.1549039],"study_design_scores_gemma":[0.001874527,0.0003056614,0.1306274,0.00125499,0.0001922091,0.00006536674,0.3582682,0.002096411,0.00007369196,0.1428697,0.3607008,0.001671041],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9425268,0.001335985,0.00176936,0.002188797,0.0001844089,0.0004184433,6.80337e-7,0.0001919214,0.05138359],"genre_scores_gemma":[0.9825889,0.000127785,0.006307579,0.000138607,0.0002456474,0.00007802133,0.000007082104,0.00002291374,0.01048346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3595067,"threshold_uncertainty_score":0.7655766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1855020227082781,"score_gpt":0.4435969228448379,"score_spread":0.2580949001365598,"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."}}