{"id":"W4283215073","doi":"10.2196/33833","title":"Using Implementation Science to Understand Teledermatology Implementation Early in the COVID-19 Pandemic: Cross-sectional Study","year":2022,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Fogarty International Center; National Institutes of Health","keywords":"Teledermatology; Pandemic; Coronavirus disease 2019 (COVID-19); Medicine; Telemedicine; MEDLINE; Medical education; Nursing; Medical emergency; Health care; Pathology; Political 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":[0.05579475,0.0004037999,0.0006131579,0.003454797,0.001240193,0.003095212,0.001171043,0.00191531,0.002331087],"category_scores_gemma":[0.09889728,0.0009284844,0.001683095,0.002815158,0.001766653,0.006380619,0.002822548,0.003388873,0.0002541758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003232627,"about_ca_system_score_gemma":0.005745352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005256547,"about_ca_topic_score_gemma":0.005016764,"domain_scores_codex":[0.9721884,0.01884352,0.002802518,0.001169378,0.002863718,0.002132443],"domain_scores_gemma":[0.8900019,0.06467739,0.0313,0.003673397,0.007452835,0.002894515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005282085,0.0009969245,0.9761289,0.0001698275,0.00009897915,0.00004834239,0.01482639,0.0001083691,0.00006201155,0.0003318113,0.0001821552,0.006993597],"study_design_scores_gemma":[0.0000258104,0.001019211,0.9656889,0.0003214174,0.0000671339,0.0001263275,0.03031272,0.001131759,0.0001275974,0.0002986278,0.0008568523,0.00002372298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956528,0.0002805154,0.001501544,0.0007598086,0.00001151767,0.0005118903,0.0001512439,0.000006245689,0.001124432],"genre_scores_gemma":[0.9972563,0.0001835952,0.001343115,0.0002987422,0.00001099868,0.0006159567,0.0001395375,0.000004784821,0.0001468714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05579475,"threshold_uncertainty_score":0.2950743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1527144507498607,"score_gpt":0.4836864901610005,"score_spread":0.3309720394111397,"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."}}