{"id":"W3197871828","doi":"10.29173/slw8260","title":"Technology use in Government School Libraries in Medellin, Colombia","year":2021,"lang":"en","type":"article","venue":"School Libraries Worldwide","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"School library; Government (linguistics); Social media; Technology integration; Public relations; Political science; Sociology; Educational technology; Pedagogy; Library science; Computer science; World Wide Web","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003357137,0.0003090674,0.0004151909,0.0004836131,0.0001359495,0.001555432,0.001474272,0.0002572675,0.00062569],"category_scores_gemma":[0.002847831,0.0003486602,0.00006861398,0.003819573,0.000188867,0.004943717,0.001174824,0.001067073,0.0003492674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003755883,"about_ca_system_score_gemma":0.001409963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008088442,"about_ca_topic_score_gemma":0.0005060169,"domain_scores_codex":[0.996693,0.0003301594,0.0007198481,0.0009585068,0.0005884216,0.0007101194],"domain_scores_gemma":[0.9974593,0.0005748353,0.0002058567,0.001431509,0.00007066478,0.0002578558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000330719,0.0002751086,0.7570216,0.00003213741,0.00002026216,0.0002476019,0.0004372971,0.001136453,0.0004085257,0.2143914,0.01807461,0.007921923],"study_design_scores_gemma":[0.00167356,0.0001284536,0.5723103,0.0004570897,0.0000121953,0.00005739228,0.001492909,0.005359765,0.02238346,0.1395327,0.2555122,0.001079904],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8339878,0.007680641,0.03411914,0.09062301,0.004468313,0.001822396,0.00002536066,0.002058556,0.02521479],"genre_scores_gemma":[0.7479457,0.000232697,0.2261776,0.003848892,0.0002168817,0.00046477,0.00003483415,0.00007832749,0.02100037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2374377,"threshold_uncertainty_score":0.9998965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01176871160674253,"score_gpt":0.2240375577764404,"score_spread":0.2122688461696979,"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."}}