{"id":"W2597971040","doi":"10.18438/b8zp70","title":"Comparison of E-Book Acquisitions Strategies Across Disciplines Finds Differences in Cost and Usage","year":2017,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Usage data; Order (exchange); Mergers and acquisitions; Collection development; Business; Marketing; Computer science; Library science; World Wide Web; Finance","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004157055,0.0002293239,0.0003988833,0.006718488,0.0005845362,0.004612857,0.0007814204,0.0004043884,0.006966754],"category_scores_gemma":[0.03215621,0.0001889496,0.0005411575,0.01385347,0.0008685668,0.00570949,0.001564969,0.0004988068,0.001865381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001758737,"about_ca_system_score_gemma":0.001407846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007450968,"about_ca_topic_score_gemma":0.01266336,"domain_scores_codex":[0.9949804,0.0007772919,0.0006555944,0.0006586045,0.002579007,0.0003492128],"domain_scores_gemma":[0.9512794,0.02682426,0.009120817,0.001569847,0.0094782,0.001727458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002692533,0.0001552744,0.7029898,0.001165819,0.000244824,0.0002667666,0.009317102,0.0002315356,0.0009412232,0.003143745,0.006708934,0.2745658],"study_design_scores_gemma":[0.000005570525,0.00008361413,0.9690165,0.000347433,0.00005612998,0.0002519735,0.01150357,0.0001671241,0.00055612,0.0007420928,0.01724459,0.00002548424],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444929,0.01156173,0.001259078,0.001346509,0.00006405389,0.00005092251,0.001728617,0.00006229655,0.03943384],"genre_scores_gemma":[0.9850085,0.006271166,0.001203294,0.0004068334,0.000059753,0.0000332823,0.001659228,0.0000919336,0.005266048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9953871,"threshold_uncertainty_score":0.02330607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04083529652547378,"score_gpt":0.3291137686554482,"score_spread":0.2882784721299744,"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."}}