{"id":"W6927462723","doi":"10.3389/fped.2020.00544.s003","title":"Data_Sheet_3_Unsupervised Machine Learning Algorithms Examine Healthcare Providers' Perceptions and Longitudinal Performance in a Digital Neonatal Resuscitation Simulator.docx","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Enterobacteriaceae and Cronobacter Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Neonatal resuscitation; Resuscitation; Mindset; Health care; Perception; Dreyfus model of skill acquisition; Health professionals; Baseline (sea)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003593437,0.0008688482,0.0009231889,0.001843192,0.0006212987,0.001234169,0.001749967,0.001364244,0.6020316],"category_scores_gemma":[0.0329447,0.0005519231,0.001245462,0.001926347,0.0003332057,0.001279442,0.001146578,0.001156541,0.1101965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021793,"about_ca_system_score_gemma":0.002788988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007572136,"about_ca_topic_score_gemma":0.01238359,"domain_scores_codex":[0.9980924,0.0004577553,0.0004446119,0.0001998019,0.0006415886,0.0001638894],"domain_scores_gemma":[0.9693773,0.01928415,0.001823041,0.001921269,0.006952381,0.0006419347],"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":[0.001263668,0.0004382713,0.009925674,0.003299255,0.00008172987,0.00006023332,0.00008801914,0.0006778559,0.0002841458,0.0008675777,0.9165874,0.06642602],"study_design_scores_gemma":[0.003721726,0.001141268,0.1106641,0.004064418,0.0001186341,0.0002152164,0.0006066665,0.002435045,0.003067192,0.002696195,0.8711268,0.000142644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00304625,0.0001064313,0.001221513,0.0006804921,0.0001418984,0.003789305,0.9724983,0.001561012,0.01695467],"genre_scores_gemma":[0.04111552,0.0007389478,0.02505583,0.003788603,0.0003182077,0.05711302,0.7884171,0.002104299,0.08134855],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6020316,"threshold_uncertainty_score":0.5676537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03356254390350797,"score_gpt":0.2908509915312338,"score_spread":0.2572884476277258,"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."}}