{"id":"W1540750675","doi":"10.18438/b8w317","title":"Development of Deal- and Journal-level Metrics and Methods Assists Librarians to Evaluate Big Deals","year":2014,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Library Science and Information","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University","funders":"","keywords":"Interlibrary loan; Computer science; Value (mathematics); Set (abstract data type); Metric (unit); Big data; Sign (mathematics); World Wide Web; Library science; Operations research; Business; Marketing; Mathematics; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.004081073,0.0001602912,0.00020508,0.0006772113,0.0003580382,0.001707672,0.000488092,0.00007675063,0.00001556693],"category_scores_gemma":[0.002341317,0.0001318777,0.00002344308,0.001232001,0.00005725914,0.3357377,0.0004153917,0.0001787427,0.00001343132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009156985,"about_ca_system_score_gemma":0.0004758731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001215824,"about_ca_topic_score_gemma":1.822131e-8,"domain_scores_codex":[0.997839,0.0004674587,0.0008089659,0.0001828171,0.0004791509,0.0002226025],"domain_scores_gemma":[0.9965217,0.00208795,0.0006673264,0.0002735905,0.0001229882,0.0003264966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005026445,0.00001390971,0.0004269264,0.0001025937,0.00001186501,4.51445e-7,0.002295431,0.0000991293,0.0001807236,0.09992739,0.0005872794,0.896304],"study_design_scores_gemma":[0.0006579611,0.0004355429,0.05463612,0.0003706637,0.00002770825,0.000135592,0.0006144538,0.1513557,0.01909732,0.001392819,0.7708488,0.0004272371],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009848217,0.0003281573,0.9616685,0.02520336,0.0001978747,0.0002308714,0.000002181886,0.0000662669,0.002454606],"genre_scores_gemma":[0.03392609,0.0006037434,0.9321917,0.03317893,0.00003630609,0.00001018696,0.000005030472,0.000004620977,0.00004344497],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8958768,"threshold_uncertainty_score":0.9993287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05731101813319728,"score_gpt":0.3253532643912125,"score_spread":0.2680422462580152,"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."}}