{"id":"W4294243752","doi":"10.23889/ijpds.v7i3.1826","title":"Impact of the COVID-19 pandemic on skin cancer diagnosis: A population-based study.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Pandemic; Skin cancer; Biopsy; Poisson regression; Cancer registry; Population; Cancer; Cohort; Cohort study; Melanoma; Dermatology; Coronavirus disease 2019 (COVID-19); Demography; Internal medicine; Disease; Environmental health; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00192493,0.0001111278,0.000174661,0.0004758213,0.0008196334,0.00008066684,0.001304587,0.00002223178,0.0004674557],"category_scores_gemma":[0.003623833,0.0000758699,0.0001350953,0.0006097431,0.000053918,0.0004315205,0.0002812374,0.0002939948,8.081466e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003034901,"about_ca_system_score_gemma":0.003178378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01513122,"about_ca_topic_score_gemma":0.001616064,"domain_scores_codex":[0.9969966,0.0001108623,0.0004928561,0.0003278991,0.00185484,0.0002169331],"domain_scores_gemma":[0.997917,0.0003758122,0.0005211075,0.0005266005,0.0003899396,0.0002695536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004101593,0.0003142615,0.9646654,0.000009810256,0.00004143426,0.000004174599,0.0001859206,0.02797841,0.00004634248,0.00008665671,0.00170246,0.004555029],"study_design_scores_gemma":[0.001659994,0.0005095802,0.9857349,0.00004198134,0.00003852555,0.0000605328,0.00008721212,0.008709062,0.0000050162,0.0002485221,0.002828273,0.00007644465],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865808,0.00003655199,0.0003280356,0.00914301,0.001590972,0.0007422599,0.00155517,0.00001740558,0.000005818108],"genre_scores_gemma":[0.9954008,0.00001312742,0.00008521478,0.003818578,0.0002744794,0.0001098535,0.0002496381,0.00001074307,0.00003760128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02106952,"threshold_uncertainty_score":0.9914271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2482335446101796,"score_gpt":0.550354455012218,"score_spread":0.3021209104020384,"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."}}