{"id":"W4387818860","doi":"10.21065/22226184.9.1","title":"DEMAND AND SUPPLY ANALYSIS OF TEACHER EDUCATION INSTITUTIONS IN PREPARATION OF TEACHERS FOR THE WORKPLACE","year":2019,"lang":"en","type":"article","venue":"","topic":"Educational Innovations and Challenges","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply and demand; Teacher preparation; Business; Mathematics education; Pedagogy; Teacher education; Sociology; Psychology; Economics; Microeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009176006,0.0001814712,0.0003324274,0.003156777,0.001088017,0.002566472,0.0008987383,0.0005363932,0.02184845],"category_scores_gemma":[0.004735773,0.0003162146,0.0004658958,0.005079133,0.0002904396,0.0008409507,0.0007939516,0.0005634148,0.003836046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008745045,"about_ca_system_score_gemma":0.007702336,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5171034,"about_ca_topic_score_gemma":0.6252594,"domain_scores_codex":[0.998925,0.0001500531,0.00006817742,0.0001141883,0.0004294215,0.0003130439],"domain_scores_gemma":[0.9917729,0.002503729,0.0007465301,0.000184508,0.003058559,0.001733799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008416427,0.0002794718,0.9317865,0.0002171878,0.00004187532,0.0004964406,0.003458882,0.003937414,0.002118205,0.003266563,0.01662305,0.03693277],"study_design_scores_gemma":[0.00001452333,0.0001145041,0.9473653,0.00009532686,0.00002728799,0.0001157985,0.02285298,0.01248414,0.0008624936,0.0004574612,0.01557536,0.00003480591],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654218,0.0002656529,0.0009651036,0.0006747911,0.00001615962,0.0000749312,0.01858596,0.00007140111,0.01392429],"genre_scores_gemma":[0.9788899,0.000194545,0.0006680734,0.00004657797,0.00001233453,0.00003893821,0.007485701,0.00004072137,0.01262317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5171034,"threshold_uncertainty_score":0.971481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02930192969100447,"score_gpt":0.3428437026362356,"score_spread":0.3135417729452311,"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."}}