{"id":"W2558488042","doi":"10.15353/joci.v12i3.3288","title":"Some Key Challenges for Data Literacy","year":2016,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Research Data Management Practices","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Praxis; Key (lock); Literacy; Information literacy; Computer science; Data science; Sociology; Political science; World Wide Web; Pedagogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.01249078,0.00008341602,0.000146115,0.0001429109,0.0003229259,0.0007826104,0.01483311,0.0000228556,0.000002175487],"category_scores_gemma":[0.0022624,0.00003924751,0.00003597975,0.0001106697,0.00008136913,0.07718974,0.00419629,0.0004118791,0.00001742246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002871817,"about_ca_system_score_gemma":0.00008097787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007367471,"about_ca_topic_score_gemma":0.000004208502,"domain_scores_codex":[0.9980663,0.0006514378,0.0005727491,0.00001382798,0.0004877345,0.000207956],"domain_scores_gemma":[0.990681,0.004813445,0.0007917893,0.00331514,0.0003252147,0.00007343786],"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":[0.00009367252,0.0001980502,0.00001404389,0.0002715549,0.0002236432,9.022787e-7,0.06234735,0.00001603321,0.00005895676,0.2199698,0.02053406,0.6962719],"study_design_scores_gemma":[0.001398794,0.0007444586,0.0005441232,0.0002622409,0.00005567182,0.0001438386,0.012989,0.007547578,0.000202004,0.05592894,0.9199948,0.0001885211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01435491,0.0008866091,0.9416386,0.0412681,0.0002340389,0.0002047627,0.00002868323,0.00002354128,0.001360714],"genre_scores_gemma":[0.6589259,0.1365646,0.1987067,0.004319294,0.0006824227,0.000008641356,0.00002723857,0.00003080276,0.0007344396],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8994607,"threshold_uncertainty_score":0.9904971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2923414867879107,"score_gpt":0.4189963810447337,"score_spread":0.126654894256823,"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."}}