{"id":"W1480463520","doi":"","title":"Clinical coding internationally: A comparison of the coding workforce in Australia, America, Canada and England","year":2004,"lang":"en","type":"article","venue":"QUT ePrints (Queensland University of Technology)","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; Workforce development; Health care; Medicine; Public relations; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.0004239166,0.00006511611,0.0002699635,0.0001290601,0.0001948047,9.888028e-7,0.0002382089,0.0002074815,0.0000416221],"category_scores_gemma":[0.0003446572,0.00005579749,0.00002539565,0.0002267913,0.0002389593,0.00004036886,0.0001768286,0.000709898,0.000004344948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001812144,"about_ca_system_score_gemma":0.0004002926,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1924588,"about_ca_topic_score_gemma":0.3298697,"domain_scores_codex":[0.9990106,0.00008005146,0.0004437075,0.0001220863,0.0001593559,0.0001841969],"domain_scores_gemma":[0.9990906,0.000208059,0.0003959467,0.0001631046,0.00008399547,0.00005835236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000441076,0.00002423424,0.9840369,0.0001008498,0.00001021052,0.000002387403,0.001222495,0.00004763277,0.0000135471,0.006859642,0.0002509652,0.007387007],"study_design_scores_gemma":[0.002346033,0.00005340416,0.9669963,0.0009251704,0.00001457149,0.000001256073,0.005133773,0.0007257797,0.0000473496,0.001127284,0.02254267,0.0000864767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931648,0.00001269105,0.001107612,0.00431782,0.0001740434,0.0002054616,0.00001058149,0.00001938079,0.0009875804],"genre_scores_gemma":[0.9987414,0.00008869469,0.0007864991,0.0001029201,0.00001305383,4.721698e-7,0.000002916121,0.00000232552,0.0002617337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1374109,"threshold_uncertainty_score":0.8129187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129712969770953,"score_gpt":0.4065160487036707,"score_spread":0.2768030789327177,"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."}}