{"id":"W1981909329","doi":"10.1108/01604950610658847","title":"A decade of ARL collection development: a look at the data","year":2006,"lang":"en","type":"article","venue":"Collection Building","topic":"Publishing and Scholarly Communication","field":"Arts and Humanities","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Collection development; Originality; Library science; Snapshot (computer storage); Value (mathematics); Sociology; Statistics; Computer science; Social science; Database; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007185721,0.00009039198,0.0001074796,0.0001754532,0.002020171,0.0005051846,0.0005136624,0.00004474058,0.0003012548],"category_scores_gemma":[0.0001599802,0.00007230556,0.0000317353,0.0002706627,0.0001039439,0.0007981596,0.0002700097,0.0001735196,0.00001483127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143048,"about_ca_system_score_gemma":0.0001291156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00142206,"about_ca_topic_score_gemma":0.01127819,"domain_scores_codex":[0.9990436,0.0001094674,0.000300417,0.0001944771,0.0002094988,0.000142545],"domain_scores_gemma":[0.998919,0.0001532872,0.0001860971,0.0005486227,0.0001729153,0.00002011577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001647392,0.0003187211,0.007085725,0.00006371495,0.0001518596,0.000001166149,0.02775843,0.0003774149,0.007484431,0.07427976,0.8744328,0.007881215],"study_design_scores_gemma":[0.000346803,0.00002367895,0.003199181,0.00004413379,0.0000265978,0.000008542345,0.0008812968,0.001618382,0.003446688,0.001164687,0.9890969,0.0001431333],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8473401,0.00125764,0.001806739,0.001460838,0.0009983983,0.0003964628,0.0000222941,0.0002013443,0.1465162],"genre_scores_gemma":[0.9497711,0.00002159632,0.0007539859,0.00005241053,0.0002417253,0.00002948444,0.00009224778,0.00001364996,0.0490238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.114664,"threshold_uncertainty_score":0.9992791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06360799006774218,"score_gpt":0.2631715032413804,"score_spread":0.1995635131736383,"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."}}