{"id":"W4390837495","doi":"10.1101/2024.01.12.24301247","title":"Estimating epidemiological delay distributions for infectious diseases","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Wellcome Trust","keywords":"Censoring (clinical trials); Computer science; Econometrics; A priori and a posteriori; Statistics; Risk analysis (engineering); Operations research; Mathematics; Medicine","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":[0.007250998,0.0007859505,0.0006845861,0.002906703,0.0003620319,0.001526302,0.001199587,0.0009447838,0.002096518],"category_scores_gemma":[0.04943272,0.000445783,0.0007980886,0.001633121,0.0008227391,0.00243263,0.001492254,0.001747068,0.0003691526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387249,"about_ca_system_score_gemma":0.001486736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009889044,"about_ca_topic_score_gemma":0.005752586,"domain_scores_codex":[0.9980072,0.001067146,0.0001082566,0.0004385017,0.0002637747,0.0001151261],"domain_scores_gemma":[0.9679781,0.0259943,0.002661373,0.001496685,0.001542484,0.0003271638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002174216,0.00008692632,0.08374786,0.0004332925,0.000241302,0.0001613966,0.0005336824,0.7636776,0.001126631,0.05125393,0.002119253,0.09640071],"study_design_scores_gemma":[0.000025116,0.00005437358,0.009767457,0.0001400209,0.0000313587,0.00009488285,0.0002196393,0.9232074,0.0008337385,0.0635345,0.002049726,0.00004166407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1547149,0.001450165,0.839548,0.0007812024,0.00008714096,0.0001486702,0.001104281,0.0003936648,0.001771979],"genre_scores_gemma":[0.874318,0.0008890562,0.1220706,0.0001015933,0.00008723223,0.0001214757,0.001208391,0.00006446668,0.001139197],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009889044,"threshold_uncertainty_score":0.03834736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2308668082529526,"score_gpt":0.4557792427537978,"score_spread":0.2249124345008453,"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."}}