{"id":"W2790469541","doi":"10.5539/gjhs.v10n4p50","title":"Electronic Health Records Functionalities in Saudi Arabia: Obstacles and Major Challenges","year":2018,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Documentation; Business; Medical record; Medical emergency; Cluster sampling; Health records; Health care; Medicine; Environmental health; Computer science","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":[0.00367228,0.0002495133,0.0001680591,0.0007438943,0.001102912,0.002317327,0.0005273618,0.000630549,0.001556486],"category_scores_gemma":[0.00712968,0.0001730638,0.0002080322,0.001021488,0.0007593803,0.001266175,0.001368278,0.0005144447,0.000217786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002932401,"about_ca_system_score_gemma":0.006252265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02793001,"about_ca_topic_score_gemma":0.02407156,"domain_scores_codex":[0.9972234,0.0009079548,0.0003523998,0.0001691816,0.0008374425,0.0005096845],"domain_scores_gemma":[0.9894518,0.003748768,0.002203713,0.0002678361,0.003156394,0.001171478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003672666,0.0004776749,0.5663198,0.002524542,0.00009789186,0.002958706,0.03999164,0.0008755439,0.005380834,0.005115389,0.008880829,0.36701],"study_design_scores_gemma":[0.00005421807,0.0006356633,0.6350226,0.002363783,0.0001197444,0.003989871,0.2537101,0.003023284,0.003937828,0.001813613,0.09521548,0.000113858],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749039,0.003837856,0.0004094739,0.0157622,0.00005739455,0.00005798145,0.0001382873,0.00001933151,0.004813669],"genre_scores_gemma":[0.9929061,0.003475198,0.0009636712,0.001558728,0.00003338071,0.00001594455,0.00009850578,0.000004377702,0.0009440511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02793001,"threshold_uncertainty_score":0.0555349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07622394330070564,"score_gpt":0.4311598270792728,"score_spread":0.3549358837785672,"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."}}