{"id":"W2557720241","doi":"10.15353/joci.v12i3.3276","title":"Data Literacy defined pro populo: To read this article, please provide a little information","year":2016,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Literacy; Context (archaeology); Information literacy; Data science; Computer science; Sociology; Public relations; Political science; World Wide Web; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007129336,0.0008404328,0.0007278968,0.003708338,0.003420961,0.01002451,0.001373985,0.005653201,0.009452121],"category_scores_gemma":[0.04662628,0.0003101465,0.0004493598,0.004313129,0.01087475,0.01374694,0.006161282,0.01050337,0.004533478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001873627,"about_ca_system_score_gemma":0.003971651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00225811,"about_ca_topic_score_gemma":0.00190542,"domain_scores_codex":[0.99066,0.005546779,0.0006160202,0.0008195817,0.00194355,0.0004141003],"domain_scores_gemma":[0.9699768,0.0195002,0.001741202,0.00151599,0.005873967,0.001391813],"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":[0.0000402048,0.00003641372,0.001298839,0.0006905204,0.000012864,0.0001927362,0.00961241,0.0001165194,0.0002438302,0.3189283,0.5575384,0.111289],"study_design_scores_gemma":[0.000004586404,0.00001671973,0.0005331938,0.001193344,0.00000449682,0.0003173772,0.00231174,0.0001200154,0.0002097931,0.04065172,0.9546139,0.00002312793],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002905377,0.04468984,0.0203926,0.8013778,0.03721394,0.00009683196,0.0006050703,0.0002003233,0.09251825],"genre_scores_gemma":[0.1742146,0.1126088,0.04022255,0.492136,0.07294156,0.0009063983,0.001500494,0.001192736,0.1042768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01002451,"threshold_uncertainty_score":0.03770399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2366070300383545,"score_gpt":0.428376994059941,"score_spread":0.1917699640215865,"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."}}