{"id":"W3149291993","doi":"10.29173/iasl7946","title":"Using Technology to Prepare World Class School Librarians to Deliver Learning and Literacy","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic shortage; Class (philosophy); Literacy; World class; School library; Medical education; Information literacy; Mathematics education; Psychology; Pedagogy; Political science; Library science; Computer science; Engineering; Medicine","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":[0.002783736,0.0001659962,0.0002348947,0.001501728,0.001648617,0.002508599,0.0005465525,0.0005448633,0.01468424],"category_scores_gemma":[0.01287347,0.0002218644,0.000433666,0.001249527,0.0003526238,0.003195027,0.001422968,0.0007511471,0.006901926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008005465,"about_ca_system_score_gemma":0.004199116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003596939,"about_ca_topic_score_gemma":0.01477458,"domain_scores_codex":[0.9987643,0.0006328314,0.00008174219,0.0001023838,0.0002047662,0.0002140062],"domain_scores_gemma":[0.9917304,0.00348981,0.001025131,0.000691833,0.001212282,0.001850642],"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":[0.0002113184,0.003750871,0.2485082,0.0003961619,0.00004145669,0.000226894,0.007690257,0.0001778534,0.003221761,0.001405629,0.02468422,0.7096854],"study_design_scores_gemma":[0.0002539167,0.006410189,0.7334595,0.00085638,0.0001972191,0.001048698,0.04283201,0.001038559,0.01769237,0.002526165,0.1935457,0.0001394124],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9269114,0.001363912,0.007285328,0.005332017,0.0001452253,0.000540263,0.000371323,0.0009819457,0.05706861],"genre_scores_gemma":[0.9432049,0.001848509,0.02458145,0.00184349,0.00008971705,0.0003766867,0.0006939902,0.0001314746,0.02722976],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01468424,"threshold_uncertainty_score":0.04912364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02466150753690166,"score_gpt":0.340069148591872,"score_spread":0.3154076410549703,"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."}}