{"id":"W1968587598","doi":"10.1371/journal.pcbi.1004143","title":"GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training","year":2015,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Biotechnology and Biological Sciences Research Council; Medical Research Council; Wellcome Trust; Sight Research UK; Government of Ontario; Strong; Ontario Institute for Cancer Research","keywords":"Globe; Stewardship (theology); Data science; Big data; Scale (ratio); Training (meteorology); Computer science; Knowledge management; Medicine; Political science; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006240375,0.001896245,0.001906701,0.004908831,0.001357481,0.01014224,0.002821708,0.004543927,0.3046636],"category_scores_gemma":[0.01420878,0.0005718542,0.000854534,0.007556083,0.002211633,0.006266644,0.004652786,0.005654868,0.288694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002965024,"about_ca_system_score_gemma":0.01420853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005908052,"about_ca_topic_score_gemma":0.002256388,"domain_scores_codex":[0.9949987,0.00115365,0.0003166469,0.0008702048,0.001762347,0.0008984371],"domain_scores_gemma":[0.9800986,0.002945869,0.002062852,0.003627572,0.003845894,0.007419134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004183945,0.0001138963,0.001119063,0.0006279743,0.00003351712,0.0002083545,0.000279381,0.0004941388,0.00251602,0.02375854,0.7044656,0.2659652],"study_design_scores_gemma":[0.00009391339,0.00002769163,0.002012547,0.0002344301,0.000003942642,0.0001049576,0.0001057023,0.0005027648,0.0003004896,0.004653637,0.9919441,0.000015826],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00787035,0.0267003,0.04192554,0.08145613,0.01623469,0.001660371,0.05736062,0.05350744,0.7132846],"genre_scores_gemma":[0.03402384,0.01049777,0.03942145,0.008994875,0.001488253,0.001724896,0.05769093,0.02212363,0.8240343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3046636,"threshold_uncertainty_score":0.9918129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0426191238216329,"score_gpt":0.3182810773130096,"score_spread":0.2756619534913767,"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."}}