{"id":"W2070314309","doi":"10.1108/01604951111146983","title":"Collection development in library and information science at ARL libraries","year":2011,"lang":"en","type":"article","venue":"Collection Building","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Collection development; Library science; Subject (documents); Work (physics); Collections management; Stock management; Accreditation; Originality; Institution; Computer science; Value (mathematics); Sociology; World Wide Web; Political science; Engineering; History; Social science","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001988777,0.0001524174,0.0001300467,0.001744695,0.0009921826,0.0009706125,0.0003960361,0.00006575223,0.00006424159],"category_scores_gemma":[0.0000732938,0.0001541815,0.00002094064,0.005539868,0.0001200706,0.04521975,0.0006731157,0.00009882644,0.00001839734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001589109,"about_ca_system_score_gemma":0.0006014036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006933124,"about_ca_topic_score_gemma":0.000003803354,"domain_scores_codex":[0.998657,0.00002970931,0.0003641701,0.0003338655,0.0003049211,0.0003103024],"domain_scores_gemma":[0.9994901,0.00005788028,0.0001201352,0.0001595099,0.00003601053,0.0001363361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005443518,0.0002710623,0.3923658,0.0001347917,0.00005255191,0.00002174212,0.05552862,0.00009911373,0.002284836,0.4655851,0.009940254,0.07317173],"study_design_scores_gemma":[0.001376583,0.0001836681,0.3981785,0.0001043481,0.000003519576,0.0001037547,0.0003354662,0.0146166,0.3430989,0.006211453,0.2349848,0.0008023616],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7396057,0.0001356738,0.02352171,0.0003034495,0.00074236,0.0004235949,3.957578e-7,0.0006367178,0.2346304],"genre_scores_gemma":[0.9183181,0.00008825669,0.07633674,0.0003237634,0.00002113986,0.00007044293,0.00000246938,0.000009770895,0.004829345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4593737,"threshold_uncertainty_score":0.9681343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720330485476741,"score_gpt":0.1889491291500775,"score_spread":0.1717458242953101,"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."}}