{"id":"W4318384911","doi":"10.1101/2023.01.25.23285005","title":"Call detail record aggregation methodology impacts infectious disease models informed by human mobility","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"European and Developing Countries Clinical Trials Partnership; Government of the United Kingdom; Department of Health and Social Care; Economic and Social Research Council; Medical Research Council; National Institute for Health and Care Research","keywords":"Metapopulation; Computer science; Infectious disease (medical specialty); Transmissibility (structural dynamics); Transmission (telecommunications); Econometrics; Population; Spatial epidemiology; Data science; Geography; Disease; Telecommunications; Biological dispersal; Epidemiology; Demography; Medicine; Mathematics","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":[0.009882561,0.0005273138,0.0006065909,0.001098496,0.0004259136,0.001641159,0.001023921,0.0009008102,0.001695292],"category_scores_gemma":[0.04082054,0.0003246011,0.0008918114,0.001477432,0.0007073804,0.001463415,0.001112724,0.0008422859,0.0002688732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649463,"about_ca_system_score_gemma":0.0008763933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03985522,"about_ca_topic_score_gemma":0.0206665,"domain_scores_codex":[0.9959397,0.003073246,0.0001455763,0.0003722475,0.0003151755,0.0001540347],"domain_scores_gemma":[0.9671409,0.02455146,0.003240814,0.003349928,0.00135049,0.0003663071],"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":[0.0004134071,0.0001088467,0.1921927,0.0001161199,0.0003234431,0.0001545086,0.0005335194,0.7728219,0.0008878518,0.008075984,0.0022286,0.02214316],"study_design_scores_gemma":[0.0000551505,0.0001345754,0.03809374,0.00004258921,0.00005745726,0.0000512267,0.0003160987,0.9532045,0.0006396616,0.005890299,0.001471565,0.00004322954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9423395,0.0003052658,0.04988682,0.001281782,0.00009273156,0.0001169965,0.002192091,0.0004736968,0.003311191],"genre_scores_gemma":[0.9824635,0.00008721359,0.01537445,0.00008769114,0.00002837209,0.00005227167,0.001319317,0.00003179178,0.0005554809],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03985522,"threshold_uncertainty_score":0.07924646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4998735102184654,"score_gpt":0.4822613454168166,"score_spread":0.01761216480164879,"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."}}