{"id":"W1579166901","doi":"10.1080/10875301.2013.870391","title":"Using Libguides to Enhance Library Services","year":2014,"lang":"en","type":"article","venue":"Internet Reference Services Quarterly","topic":"Web and Library Services","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University","funders":"","keywords":"World Wide Web; Computer science; Library science; Business","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002040952,0.0004687386,0.0004286125,0.0002989949,0.0001156626,0.00170763,0.004966907,0.0001753487,0.0002708802],"category_scores_gemma":[0.000001548759,0.0004178248,0.0001010839,0.000664331,0.00003004897,0.006425719,0.000601872,0.000256298,0.001395012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002211465,"about_ca_system_score_gemma":0.00005467635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00176806,"about_ca_topic_score_gemma":0.0005914196,"domain_scores_codex":[0.9968846,0.0002123704,0.0006179677,0.001109884,0.0004675854,0.0007075208],"domain_scores_gemma":[0.9977307,0.0001140408,0.0002708957,0.001368245,0.00009028363,0.0004258775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002953714,0.0006993698,0.03938296,0.003750308,0.0003161951,0.0001237874,0.1130885,0.0005044775,0.02631976,0.24125,0.001696696,0.5725725],"study_design_scores_gemma":[0.0007603058,0.003719167,0.0245618,0.002650477,0.00005537099,0.00009864938,0.003740908,0.5437719,0.06105521,0.02686032,0.3294993,0.003226609],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9295986,0.0001818503,0.04769829,0.001139913,0.000697493,0.0002653642,0.00001066013,0.001042854,0.01936494],"genre_scores_gemma":[0.9513718,0.000006667944,0.03846185,0.008449094,0.0003183726,0.00002207181,0.00002674751,0.00004452166,0.001298854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5693459,"threshold_uncertainty_score":0.9998274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443933245851014,"score_gpt":0.2607036505674876,"score_spread":0.2462643181089775,"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."}}