{"id":"W1589867293","doi":"","title":"Sharing information literacy resources as open educational resources: lessons from DELILA","year":2012,"lang":"en","type":"article","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information literacy; Open educational resources; Commons; Institution; Best practice; Literacy; Public relations; World Wide Web; Sociology; Library science; Political science; Computer science; Pedagogy; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.009289663,0.0008965646,0.0007342646,0.002723571,0.009525985,0.01785893,0.003313275,0.004119639,0.01892115],"category_scores_gemma":[0.02805025,0.0008730216,0.0008856015,0.003113509,0.01035999,0.04727346,0.0193997,0.004331979,0.004213016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006151304,"about_ca_system_score_gemma":0.005419495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01915506,"about_ca_topic_score_gemma":0.01941586,"domain_scores_codex":[0.9936219,0.004032298,0.0001769262,0.0004955358,0.000965275,0.0007080453],"domain_scores_gemma":[0.9792589,0.01416638,0.0004600302,0.002304544,0.001866816,0.001943286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001452541,0.0003807689,0.00556558,0.000917423,0.00004620038,0.001409248,0.09790971,0.001055302,0.0005097747,0.5145686,0.09012076,0.2873713],"study_design_scores_gemma":[0.00005448767,0.0001130686,0.001800618,0.00135876,0.00002751566,0.0009523335,0.06264645,0.002347548,0.0008663144,0.2975379,0.63222,0.00007491747],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06534919,0.01504778,0.07167596,0.2394652,0.001312794,0.0004218373,0.0004234444,0.001275927,0.6050279],"genre_scores_gemma":[0.7435917,0.02137823,0.07886659,0.01607415,0.0008695107,0.0008722769,0.000661941,0.001683908,0.1360017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9966867,"threshold_uncertainty_score":0.06329763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05896773527633339,"score_gpt":0.3967178764063991,"score_spread":0.3377501411300657,"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."}}