{"id":"W4206472704","doi":"10.33844/cjm.2021.60605","title":"How will the COVID-19 Pandemic Change Dermatology Services over the next Five Years?","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Medicine","topic":"Dermatological and COVID-19 studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Teledermatology; Coronavirus disease 2019 (COVID-19); Pandemic; Medicine; Triage; Competence (human resources); Dermatology; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Telemedicine; Medical emergency; Health care; Psychology; Political science; Pathology; Infectious disease (medical specialty)","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":[0.01246872,0.000319997,0.0005212511,0.001224576,0.003643841,0.007003696,0.002331052,0.005787315,0.02737452],"category_scores_gemma":[0.04913783,0.0003033188,0.0009274057,0.001859642,0.002997978,0.007110029,0.00227333,0.007510183,0.002929708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01794109,"about_ca_system_score_gemma":0.06001013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2784044,"about_ca_topic_score_gemma":0.4249167,"domain_scores_codex":[0.9930817,0.002086012,0.0003820874,0.0003916675,0.001863217,0.002195214],"domain_scores_gemma":[0.9559942,0.008393003,0.003841643,0.001129526,0.009552312,0.02108943],"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":[0.000472651,0.0005190918,0.05024182,0.002470101,0.0001919804,0.0009132539,0.003134019,0.0003939177,0.0004274503,0.04898725,0.6622613,0.2299871],"study_design_scores_gemma":[0.0002187536,0.000451673,0.07859874,0.009038049,0.0002288991,0.0009422862,0.02447854,0.0003663537,0.0003122177,0.0141084,0.8710774,0.0001787546],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008258305,0.02401666,0.0001971207,0.9489272,0.006015852,0.00005281836,0.0006856864,0.00003155493,0.01181474],"genre_scores_gemma":[0.212491,0.1035996,0.002511902,0.6601592,0.0125875,0.0001953057,0.001130794,0.00007615185,0.007248556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2784044,"threshold_uncertainty_score":0.5535678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0958386834888931,"score_gpt":0.310998782814995,"score_spread":0.2151600993261019,"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."}}