{"id":"W7020642815","doi":"","title":"Making the most of data: Data skills training in English universities","year":2015,"lang":"en","type":"other","venue":"Digital Education Resource Archive (University College London)","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Keele University; University of Bristol; University of the West of England; University of Reading; University of Warwick; University of Bath; University of Oxford; University of Essex; University College London; University of Southampton; Manchester Metropolitan University; University of Leicester; University of Exeter; London School of Economics and Political Science; University of Leeds; University of Roehampton; Leeds Trinity University; University of Hull; Kingston University; King's College London; University of Portsmouth; Nottingham Trent University; Trent University; University of Greenwich; Queen Mary University of London","keywords":"Government (linguistics); Work (physics); Set (abstract data type); Order (exchange); Economic shortage; Training (meteorology); Analytics","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":[],"consensus_categories":[],"category_scores_codex":[0.01760622,0.0002734204,0.0005106226,0.001086199,0.006880336,0.007760023,0.00199281,0.001973192,0.02138842],"category_scores_gemma":[0.03867543,0.0005577009,0.0003429864,0.001568433,0.002620985,0.00900072,0.0109554,0.002910393,0.003261327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008484031,"about_ca_system_score_gemma":0.04333154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02017114,"about_ca_topic_score_gemma":0.04265069,"domain_scores_codex":[0.9886456,0.005604784,0.0004837461,0.0005019817,0.001331409,0.003432495],"domain_scores_gemma":[0.9427988,0.01749539,0.002294324,0.001372932,0.005510456,0.03052807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000621153,0.002287525,0.0597632,0.00534931,0.00003016803,0.004357466,0.2799709,0.0004003785,0.003282965,0.03010009,0.1505311,0.4633057],"study_design_scores_gemma":[0.0001330841,0.001027402,0.1338615,0.007628486,0.00003456196,0.0009578486,0.3795566,0.0007728418,0.002148145,0.01657947,0.4571474,0.0001526991],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6512157,0.01289864,0.003921937,0.2254469,0.001809206,0.0006903439,0.0009741366,0.0003274101,0.1027157],"genre_scores_gemma":[0.9322959,0.004502805,0.004678868,0.02681447,0.0003131805,0.0003710533,0.0004062752,0.0001236953,0.03049385],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02138842,"threshold_uncertainty_score":0.09311169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03507462132776759,"score_gpt":0.2371179718268764,"score_spread":0.2020433504991088,"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."}}