{"id":"W3171892779","doi":"10.1101/2021.06.01.446616","title":"Building Back More Equitable STEM Education: Teach Science by Engaging Students in Doing Science","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Columbia College","funders":"","keywords":"Curriculum; Equity (law); Apprenticeship; Engineering ethics; Psychology; Public relations; Mathematics education; Sociology; Pedagogy; Medical education; Political science; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004157963,0.0004551606,0.0004092796,0.0005569182,0.000529059,0.001192656,0.002661153,0.0003937044,0.00001776912],"category_scores_gemma":[0.0006556723,0.0004844488,0.00009655314,0.001482032,0.001340909,0.00006339194,0.004523906,0.00085782,0.00001789021],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005205302,"about_ca_system_score_gemma":0.007338622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007890475,"about_ca_topic_score_gemma":0.000003106901,"domain_scores_codex":[0.9945821,0.0001026375,0.0006875931,0.001486876,0.001752582,0.001388221],"domain_scores_gemma":[0.9964375,0.00002581476,0.0002840955,0.001473644,0.001160542,0.0006184361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008208782,0.0002269066,0.01210724,0.000333013,0.00002078693,0.000005387574,0.00003820447,0.00004962329,0.9867882,0.00002650627,0.0002990256,0.00009693422],"study_design_scores_gemma":[0.0004220635,0.0000691231,0.01668464,0.0006838465,0.00001913196,8.802572e-8,0.0002058418,0.0005487553,0.9737699,6.369208e-7,0.006888207,0.0007077502],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929695,0.002487889,0.002445252,0.0001592094,0.001199291,0.0005842655,0.00004134838,0.0000328892,0.00008042072],"genre_scores_gemma":[0.9783165,0.0006188532,0.02028161,0.000289188,0.00030979,0.00008517247,0.000001769908,0.00005251065,0.0000446153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01783636,"threshold_uncertainty_score":0.9998442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01507951274962416,"score_gpt":0.2980461749015754,"score_spread":0.2829666621519513,"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."}}