{"id":"W4402648493","doi":"10.2196/57204","title":"Allied Health Professionals’ Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queensland Health","keywords":"Preprint; Cross-sectional study; Health professionals; Psychology; Perception; Medicine; Family medicine; Health care; Computer science; Political science; Pathology; World Wide Web","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":[0.003487441,0.0001437532,0.0003389444,0.0009230011,0.0007713189,0.0009157045,0.0002979721,0.0004947499,0.002410577],"category_scores_gemma":[0.008702569,0.0003537966,0.0002846653,0.001189517,0.0005813069,0.0008128362,0.001128329,0.0008392443,0.0003827895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007965458,"about_ca_system_score_gemma":0.001272926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033946,"about_ca_topic_score_gemma":0.0120909,"domain_scores_codex":[0.9981372,0.000586828,0.0002441478,0.0001478317,0.0005258286,0.0003581755],"domain_scores_gemma":[0.9924302,0.00199503,0.002992183,0.0001660521,0.001030036,0.00138658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003357415,0.0001851773,0.9871437,0.0001027407,0.00001936023,0.0001345816,0.008763786,0.00002785856,0.0002363702,0.00002789044,0.0005174016,0.00280769],"study_design_scores_gemma":[0.000007868163,0.0003094003,0.9744845,0.00005737238,0.000008980483,0.0002182251,0.02393851,0.000130961,0.00004881004,0.00002189467,0.0007669801,0.00000652946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990073,0.00007508436,0.00003562885,0.0002246489,0.000003806185,0.00003469143,0.0001403318,0.000001385803,0.0004770751],"genre_scores_gemma":[0.9992037,0.0001895508,0.00009939364,0.0002333708,0.000007066475,0.00004996196,0.00009447638,9.386013e-7,0.0001215005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01033946,"threshold_uncertainty_score":0.0205586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5915661983242902,"score_gpt":0.6782458294640461,"score_spread":0.08667963113975585,"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."}}