{"id":"W2156545100","doi":"10.1093/bib/bbt043","title":"Best practices in bioinformatics training for life scientists","year":2013,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Novo Nordisk Fonden; Sveriges Lantbruksuniversitet; Wellcome Trust; King Abdullah University of Science and Technology; European Commission; Uppsala Universitet; Ontario Institute for Cancer Research; European Bioinformatics Institute","keywords":"Excellence; Training (meteorology); Context (archaeology); Computer science; Interactivity; Resource (disambiguation); Quality (philosophy); Globe; Data science; Knowledge management; Multimedia; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05854908,0.0007654703,0.0006896316,0.003881304,0.005121836,0.01194541,0.004925721,0.005708562,0.01288433],"category_scores_gemma":[0.1159061,0.0007718083,0.0008952841,0.004503664,0.004751561,0.006208475,0.009693734,0.006977113,0.0132236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004792713,"about_ca_system_score_gemma":0.02327804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003371855,"about_ca_topic_score_gemma":0.006930235,"domain_scores_codex":[0.9255436,0.04870899,0.004844913,0.003099001,0.01403887,0.00376461],"domain_scores_gemma":[0.8725386,0.05217765,0.006462912,0.01254595,0.0259747,0.0303002],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001107454,0.001165639,0.006324946,0.002849955,0.00005606291,0.0007528576,0.02577301,0.001497669,0.001933936,0.03155121,0.2847418,0.6432422],"study_design_scores_gemma":[0.00007895548,0.0003315725,0.009374114,0.007956087,0.00004482782,0.001450223,0.02615882,0.001603387,0.001939576,0.07318486,0.8777717,0.0001058516],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02421165,0.03191555,0.1373451,0.6061034,0.01295462,0.001690448,0.0005002008,0.002444278,0.1828348],"genre_scores_gemma":[0.1695221,0.043488,0.6090643,0.1064498,0.003979607,0.00440546,0.001222885,0.001200644,0.06066725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.941451,"threshold_uncertainty_score":0.3096408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06911075359891737,"score_gpt":0.3381606877965708,"score_spread":0.2690499341976534,"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."}}