{"id":"W3209907849","doi":"10.1093/biosci/biab107","title":"Data Science in Undergraduate Life Science Education: A Need for Instructor Skills Training","year":2021,"lang":"en","type":"article","venue":"BioScience","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Curriculum; Coding (social sciences); Science education; Mathematics education; Medical education; Higher education; Computer science; Psychology; Pedagogy; Medicine; Sociology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001698195,0.0001205185,0.0001246263,0.0002337843,0.0003718377,0.0002427786,0.001991247,0.00006661737,0.000007207647],"category_scores_gemma":[0.006961963,0.000108537,0.00002942544,0.001780044,0.002872211,0.00006939087,0.001058321,0.00008620093,0.000006382365],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005667975,"about_ca_system_score_gemma":0.0163584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001293941,"about_ca_topic_score_gemma":0.00008781949,"domain_scores_codex":[0.9974948,0.00002048186,0.0002986011,0.0007764623,0.0007431192,0.0006665632],"domain_scores_gemma":[0.9980817,0.0000308449,0.00007570998,0.0009141184,0.0004800885,0.0004174876],"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":[0.00001155508,0.0001577117,0.001383566,0.00004068925,0.000002417528,0.000001114673,0.0002625332,0.000004684445,0.9530765,0.001070807,0.00092617,0.04306221],"study_design_scores_gemma":[0.002124547,0.0006791007,0.06243159,0.0002045885,0.00001605732,0.00009426164,0.009859885,0.01270352,0.75046,0.001694553,0.15861,0.001121845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880134,0.0003366533,0.002911689,0.003222034,0.001524039,0.0004034611,0.0001241376,0.00001362367,0.003450927],"genre_scores_gemma":[0.979417,0.0002504545,0.01858669,0.0009906617,0.0001754966,0.00001333917,0.00007213995,0.000006586887,0.000487575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2026165,"threshold_uncertainty_score":0.9998414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05315910352846157,"score_gpt":0.3562254380915492,"score_spread":0.3030663345630876,"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."}}