{"id":"W3129201251","doi":"10.1371/journal.pcbi.1008661","title":"An integrated, modular approach to data science education in microbiology","year":2021,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of Victoria; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Curriculum; Modular design; Relevance (law); Computer science; Raw data; Science education; Engineering ethics; Experiential learning; Data science; Mathematics education; Pedagogy; Psychology; Political science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004683943,0.0001251514,0.000152797,0.0001979765,0.00008070378,0.00004005108,0.0008577121,0.000160105,0.00001848739],"category_scores_gemma":[0.0005750696,0.0001138704,0.0000214373,0.0004208349,0.0004077422,0.00001456791,0.0005462683,0.0001298747,0.00003268556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003877042,"about_ca_system_score_gemma":0.002868401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002551046,"about_ca_topic_score_gemma":0.00004420064,"domain_scores_codex":[0.9984323,0.0001328647,0.0002919372,0.0006583672,0.0001330766,0.0003514559],"domain_scores_gemma":[0.9986667,0.000026459,0.00004533905,0.0005836093,0.0004841952,0.0001936815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004055079,0.0008638618,0.002925702,0.00002551438,0.00002515007,0.000001276764,0.00007348416,0.001413754,0.9693694,0.00126321,0.001087699,0.02291039],"study_design_scores_gemma":[0.002969748,0.002665819,0.04146222,0.0001071474,0.00004596635,0.0004529336,0.002850804,0.4252118,0.2970172,0.00765416,0.2176107,0.00195156],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9393264,0.0003435908,0.05674997,0.0006333734,0.0002730042,0.0003065179,0.000270547,0.00001435724,0.00208225],"genre_scores_gemma":[0.8908501,0.00005448535,0.09468138,0.001295466,0.0001569252,0.00001468539,0.01284385,0.000009207776,0.00009388317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6723523,"threshold_uncertainty_score":0.5088421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03626736953171995,"score_gpt":0.3315171632237694,"score_spread":0.2952497936920495,"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."}}