{"id":"W2489790941","doi":"","title":"El acceso universal a la información: del modelo librario al digital","year":2016,"lang":"es","type":"article","venue":"Boletín del Instituto de Investigaciones Bibliográficas","topic":"Data Privacy and Cybersecurity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01251399,0.001192805,0.001768177,0.008220855,0.003219876,0.02429733,0.004051287,0.00704375,0.04390782],"category_scores_gemma":[0.07953974,0.001423696,0.002289498,0.007215111,0.01213791,0.05068593,0.009846401,0.003979162,0.00576153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005968516,"about_ca_system_score_gemma":0.004232301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009141242,"about_ca_topic_score_gemma":0.003741139,"domain_scores_codex":[0.9873314,0.006947336,0.0005698233,0.002234843,0.002106241,0.0008104052],"domain_scores_gemma":[0.9336824,0.04231104,0.003090071,0.01179037,0.006317261,0.002808836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002147731,0.0001516213,0.002129576,0.0002545655,0.00004547607,0.0001615074,0.002972122,0.004847231,0.0002965723,0.9565693,0.003646288,0.02871092],"study_design_scores_gemma":[0.0001478207,0.0002005253,0.001234356,0.0005308824,0.0002744385,0.0006862421,0.003093988,0.06062366,0.0009015215,0.8919389,0.04026413,0.0001035313],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1422556,0.00774391,0.4225744,0.05044737,0.0006513387,0.0003687181,0.001958355,0.002606733,0.3713937],"genre_scores_gemma":[0.9111299,0.003185043,0.04069158,0.001692671,0.0004614453,0.0003287523,0.0005446299,0.0004223736,0.04154371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04390782,"threshold_uncertainty_score":0.1468863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03299804796716933,"score_gpt":0.3065123786509969,"score_spread":0.2735143306838276,"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."}}