{"id":"W3034718375","doi":"10.1017/s1047951120001213","title":"Reply to letter “Leveraging e-learning for medical education in low- and middle-income countries”","year":2020,"lang":"en","type":"letter","venue":"Cardiology in the Young","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta Hospital; Alberta Hospital Edmonton","funders":"","keywords":"Medicine; Low and middle income countries; E learning; Low income; Medical education; Internet privacy; Economic growth; Developing country; Demographic economics; World Wide Web; The Internet; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003422846,0.0005876085,0.0007330599,0.0006445383,0.003699271,0.002948843,0.001370969,0.05049464,0.01254015],"category_scores_gemma":[0.02002558,0.0006067797,0.0008531648,0.0006032141,0.001930412,0.003641687,0.001702457,0.02405671,0.009987398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003347314,"about_ca_system_score_gemma":0.007104076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01245358,"about_ca_topic_score_gemma":0.01751288,"domain_scores_codex":[0.997601,0.0005766561,0.0003149307,0.0002635346,0.0007581502,0.0004857781],"domain_scores_gemma":[0.9927893,0.003302511,0.000464792,0.0001407723,0.001635683,0.001666917],"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":[0.00001971841,0.00001039784,0.0003236683,0.00001880991,0.000003065967,0.0004151374,0.00009154637,0.00001512538,0.00007762337,0.0006962687,0.996224,0.002104618],"study_design_scores_gemma":[0.00004617397,0.00004509239,0.001841086,0.0002588178,0.00001372373,0.00119267,0.000753207,0.0002169512,0.0002540878,0.003323925,0.9919935,0.00006078641],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0002619711,0.0003167038,0.00004088491,0.98966,0.007258883,0.000008199135,0.00008300211,0.00003357268,0.002336777],"genre_scores_gemma":[0.001381294,0.0002101665,0.00008402433,0.987548,0.0050122,0.00001936216,0.00002761793,0.00001622591,0.005701103],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.05049464,"threshold_uncertainty_score":0.041951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01579523713890007,"score_gpt":0.2585641416276133,"score_spread":0.2427689044887132,"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."}}