{"id":"W4388731308","doi":"10.29242/hslstats.2022","title":"ARL Academic Health Sciences Library Statistics 2022","year":2023,"lang":"en","type":"report","venue":"","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Health statistics; Medical library; Academic library; Biomedical sciences; Political science; Data science; Statistics; Computer science; Sociology; Medicine; Demography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003641335,0.00163853,0.001239064,0.01023842,0.00133481,0.0054865,0.001628316,0.001239928,0.07401029],"category_scores_gemma":[0.02439497,0.000953133,0.001024792,0.02725159,0.0003930418,0.002014785,0.001272815,0.002651029,0.1522692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007966245,"about_ca_system_score_gemma":0.02863897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3812195,"about_ca_topic_score_gemma":0.3086101,"domain_scores_codex":[0.9928942,0.0005922244,0.000706735,0.0003403517,0.004882065,0.0005843241],"domain_scores_gemma":[0.9696606,0.004505714,0.00217941,0.001382777,0.02069338,0.001578133],"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":[0.00001236189,0.000007176791,0.0002629259,0.00004337217,0.000002963734,0.000003082069,0.000005232966,0.00003687708,0.000008120117,0.0002743007,0.995594,0.003749558],"study_design_scores_gemma":[0.00002746671,0.00001196608,0.009367956,0.0002075847,0.000008392449,0.00002000375,0.00004210327,0.0002055005,0.00009758394,0.0003108783,0.9896767,0.00002391438],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003044107,0.0006463294,0.000339779,0.002014156,0.0008897486,0.0001614875,0.9470085,0.001269476,0.0473661],"genre_scores_gemma":[0.002235555,0.001989569,0.002247987,0.00163969,0.0007575701,0.0005262234,0.9056503,0.0007242074,0.08422899],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9897616,"threshold_uncertainty_score":0.7580012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6689998139954805,"score_gpt":0.6748843263687156,"score_spread":0.005884512373235173,"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."}}