{"id":"W2465482794","doi":"10.18438/b89d0p","title":"Educating Assessors: Preparing Librarians with Micro and Macro Skills","year":2016,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Accreditation; Medical education; Information literacy; Professional development; Needs assessment; Psychology; Collection development; Skills management; Library science; Computer science; Sociology; Medicine; 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":[0.02592163,0.0003483933,0.0004384088,0.002738511,0.00289832,0.008186922,0.001129883,0.001741178,0.01789841],"category_scores_gemma":[0.06065238,0.0007229807,0.000474979,0.001616052,0.001213916,0.006977999,0.006000292,0.002142922,0.008189912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002150312,"about_ca_system_score_gemma":0.01332814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003413556,"about_ca_topic_score_gemma":0.01015724,"domain_scores_codex":[0.9889108,0.004668357,0.0007915273,0.0005982767,0.003949671,0.001081398],"domain_scores_gemma":[0.9393883,0.02097093,0.007395279,0.002880605,0.01492482,0.01443995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002686329,0.00184964,0.2334865,0.001475044,0.00004809205,0.0006725027,0.02787467,0.0001667145,0.002294031,0.002084871,0.07389043,0.6558889],"study_design_scores_gemma":[0.0002662246,0.002229951,0.4964602,0.003593042,0.0001493045,0.001492941,0.0798561,0.001120342,0.00659093,0.005704658,0.4023527,0.0001835389],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7853709,0.006333319,0.01313856,0.06205506,0.001020719,0.001616527,0.0004804599,0.001460416,0.128524],"genre_scores_gemma":[0.9273263,0.003669625,0.02447879,0.01104684,0.0005339687,0.0008715042,0.0004768077,0.000129286,0.03146689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02592163,"threshold_uncertainty_score":0.1370883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008473204708147998,"score_gpt":0.2744208291570531,"score_spread":0.2659476244489051,"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."}}