{"id":"W2562437438","doi":"10.6017/ital.v35i4.9601","title":"Editorial Board Thoughts: Metadata Training in Canadian Library Technician Programs","year":2016,"lang":"en","type":"paratext","venue":"Information Technology and Libraries","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Technician; Metadata; Library science; Computer science; Training (meteorology); World Wide Web; Political science; Geography","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01903814,0.002642316,0.002830467,0.008557638,0.01054462,0.02187923,0.005430089,0.01794434,0.073723],"category_scores_gemma":[0.08202802,0.001375878,0.002336684,0.008518247,0.004373842,0.007462554,0.002665797,0.01436618,0.02201231],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03447287,"about_ca_system_score_gemma":0.09978662,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.380963,"about_ca_topic_score_gemma":0.5536819,"domain_scores_codex":[0.9764124,0.001557048,0.00253369,0.001271986,0.01600471,0.002220012],"domain_scores_gemma":[0.7983985,0.01489256,0.005186649,0.002822439,0.1561803,0.02251955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003658433,0.000003226131,0.00001670367,0.00002566123,6.674941e-7,0.000007182667,0.000006454713,0.000006245875,0.000002764763,0.0001058367,0.9988552,0.0009663188],"study_design_scores_gemma":[0.00003736434,0.00001262598,0.0007516055,0.0006266134,0.0000197168,0.00003043316,0.0002670827,0.00007861277,0.00004084063,0.0003941173,0.9977129,0.00002822537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00009048905,0.0024128,0.0000922408,0.1742949,0.8116767,0.0001029454,0.0007830552,0.0001214698,0.01042542],"genre_scores_gemma":[0.0040664,0.01108614,0.0006120691,0.1186497,0.6416005,0.000333456,0.001134338,0.0004505176,0.2220669],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.9781207,"threshold_uncertainty_score":0.7574911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167431100892696,"score_gpt":0.2099156729512909,"score_spread":0.1982413619423639,"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."}}