{"id":"W1748476117","doi":"10.3998/ticker.16481003.0001.102","title":"Our Year of Assessment at Columbia University’s Business and Economics Library","year":2019,"lang":"en","type":"article","venue":"Ticker The Academic Business Librarianship Review","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watson; Space (punctuation); Service (business); Work (physics); Quality (philosophy); Service quality; Marketing; Perception; Sociology; Public relations; Psychology; Library science; Business; Management; Medical education; Engineering; Computer science; Political science; Economics; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007120326,0.0006715683,0.0006682678,0.007981106,0.008766565,0.007719045,0.00172335,0.001357063,0.0207637],"category_scores_gemma":[0.01259863,0.0004887235,0.0004037228,0.003833055,0.001621616,0.002438028,0.004473952,0.002902246,0.007982461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01282805,"about_ca_system_score_gemma":0.02152152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1095335,"about_ca_topic_score_gemma":0.3189093,"domain_scores_codex":[0.9935662,0.0007453039,0.0002873208,0.000351922,0.004014552,0.001034559],"domain_scores_gemma":[0.952952,0.0005400205,0.000947919,0.0008951348,0.03032339,0.01434144],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001833723,0.002073823,0.08370609,0.0002570068,0.00002098847,0.0004765619,0.01178819,0.000403788,0.003391096,0.003892216,0.5981786,0.2956282],"study_design_scores_gemma":[0.00001062125,0.000288635,0.2674042,0.0002414498,0.00001061161,0.0001700138,0.01462932,0.000335077,0.002108188,0.001045211,0.7136857,0.00007097387],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4655032,0.007264634,0.01036714,0.09428087,0.02327863,0.002997058,0.01130753,0.001260779,0.3837402],"genre_scores_gemma":[0.4085235,0.003998712,0.004966478,0.008366216,0.002662945,0.001099729,0.005401068,0.0003968913,0.5645845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9928797,"threshold_uncertainty_score":0.2177919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641632190764311,"score_gpt":0.2242759176402217,"score_spread":0.1978595957325786,"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."}}