{"id":"W2152903677","doi":"","title":"An Exploration of University Library Marketing","year":2014,"lang":"en","type":"article","venue":"Cross-cultural communication","topic":"Web and Library Services","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Marketing; Marketing management; Marketing strategy; Digital marketing; Marketing research; Business; Order (exchange); Quality (philosophy); Marketing science; Product (mathematics); Service (business); Marketing mix; Relationship marketing; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001539182,0.0003603859,0.0003124391,0.003800031,0.003664308,0.01181817,0.0006222314,0.001455765,0.02506336],"category_scores_gemma":[0.003230967,0.0002598431,0.000452021,0.006110577,0.003854622,0.007655188,0.002189391,0.001215499,0.001810002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006558602,"about_ca_system_score_gemma":0.003486123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003046816,"about_ca_topic_score_gemma":0.004567761,"domain_scores_codex":[0.9976082,0.001703196,0.00004006056,0.00009285897,0.0003445915,0.0002110414],"domain_scores_gemma":[0.9978059,0.001576255,0.0001377395,0.00007262798,0.0001723442,0.0002351047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007191188,0.0001556488,0.002369384,0.0004297321,0.00001412409,0.0004824623,0.01853749,0.0008765415,0.0004047778,0.877089,0.01277555,0.08679334],"study_design_scores_gemma":[0.00001654736,0.00008186403,0.007727291,0.0006668109,0.00001531598,0.0007658952,0.03833276,0.003488915,0.0006860715,0.1391607,0.8090143,0.00004350963],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06474283,0.01973595,0.007339265,0.01243175,0.0003008692,0.00007641463,0.0001092971,0.0001121019,0.8951516],"genre_scores_gemma":[0.8597951,0.01880488,0.007747004,0.002041405,0.001047003,0.0001278164,0.00008912385,0.0001363178,0.1102114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02506336,"threshold_uncertainty_score":0.08384532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505898209938506,"score_gpt":0.2687506591062521,"score_spread":0.2436916770068671,"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."}}