{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.004183291,0.0003746741,0.0005654836,0.0002162799,0.001988414,0.001240482,0.0005703293,0.0002513294,0.0003942747],"category_scores_gemma":[0.007953377,0.0002886549,0.00006152412,0.001423811,0.0002009299,0.5021722,0.0004262058,0.001860497,0.0002565798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002032466,"about_ca_system_score_gemma":0.005194462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006355461,"about_ca_topic_score_gemma":0.00000570668,"domain_scores_codex":[0.9912897,0.00252116,0.00406406,0.0003684142,0.0008421192,0.0009144989],"domain_scores_gemma":[0.9886849,0.005751933,0.003590419,0.0005220788,0.0001660812,0.001284621],"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":[0.004390383,0.0001400449,0.1709888,0.008921525,0.00003594792,0.000002089952,0.1134964,0.000210843,7.145522e-7,0.04418916,0.4297896,0.2278344],"study_design_scores_gemma":[0.000982131,0.0003880476,0.1140101,0.005079312,0.000004918465,0.000003566168,0.02804085,0.003780208,0.000002680121,0.000190215,0.8472502,0.0002677618],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01438364,0.002837392,0.003966655,0.9728355,0.0007241527,0.003439145,0.0007974087,0.0003046744,0.0007114592],"genre_scores_gemma":[0.1029585,0.007832067,0.006997205,0.8793355,0.000358493,0.0001970792,0.002029211,0.00002120183,0.0002707116],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.5009317,"threshold_uncertainty_score":0.9999565,"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."}}