{"id":"W3013298784","doi":"10.18438/eblip29640","title":"Digital Health and Professional Identity in Australian Health Libraries: Evidence from the 2018 Australian Health Information Workforce Census","year":2020,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; Census; Workforce planning; Population; Public relations; Population health; Digital health; Health care; Medical education; Medicine; Political science; Environmental health","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":[],"consensus_categories":[],"category_scores_codex":[0.009652108,0.0001232187,0.0003365331,0.004296451,0.00117454,0.00204828,0.0009243424,0.0004851512,0.004202812],"category_scores_gemma":[0.061083,0.0004028547,0.0003637841,0.007098368,0.001006039,0.002993832,0.005029934,0.0006267037,0.0007789269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002246597,"about_ca_system_score_gemma":0.004105583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09574989,"about_ca_topic_score_gemma":0.09582148,"domain_scores_codex":[0.9916546,0.003899477,0.001110828,0.0005288379,0.002192669,0.0006134926],"domain_scores_gemma":[0.9460346,0.01810364,0.01658767,0.002374283,0.01421831,0.002681451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001253904,0.0001060023,0.9039245,0.001321714,0.00007430636,0.0001591256,0.03720841,0.00007676746,0.0001038207,0.0007159094,0.005357153,0.05082693],"study_design_scores_gemma":[0.000003427598,0.00004330827,0.9776169,0.0004070203,0.00001623024,0.00006771094,0.01645668,0.000128386,0.00004284889,0.00012938,0.005079651,0.000008468619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805561,0.003237066,0.0003560185,0.003727582,0.0000663895,0.00008254967,0.001943987,0.000009504449,0.01002084],"genre_scores_gemma":[0.9946844,0.002229276,0.0002543952,0.000622665,0.00005074839,0.0001101645,0.0007753493,0.000007086442,0.001266063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09574989,"threshold_uncertainty_score":0.1903851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09065250015719212,"score_gpt":0.4247662592518066,"score_spread":0.3341137590946144,"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."}}