{"id":"W7084578043","doi":"10.6084/m9.figshare.30273052","title":"Global SARS-CoV-2 Genomic Sequences by City (2019 to 2025 Q1): Temporal Trends Across 734 Urban Locations World-Wide","year":2025,"lang":"en","type":"dataset","venue":"Figshare","topic":"Plant-Microbe Interactions and Immunity","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metadata; Pandemic; Quarter (Canadian coin); Sequence (biology); Genomic sequencing; Genomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006561223,0.0008390701,0.0007022989,0.002042561,0.000496337,0.001191757,0.001372354,0.001199155,0.02894947],"category_scores_gemma":[0.003495002,0.0003603589,0.0008723987,0.004337546,0.0002788284,0.0007367301,0.001319671,0.001103398,0.02263654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008297,"about_ca_system_score_gemma":0.00182698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03643385,"about_ca_topic_score_gemma":0.05814977,"domain_scores_codex":[0.9995407,0.00005623021,0.00006823037,0.0001503951,0.00009247457,0.00009194544],"domain_scores_gemma":[0.9989076,0.0003251442,0.0001602057,0.0001999785,0.0002646983,0.0001424474],"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":[0.0001966482,0.00003357996,0.008301746,0.001251379,0.00008635772,0.00007422695,0.0000875213,0.0008610276,0.000577019,0.0007469901,0.9812903,0.006493244],"study_design_scores_gemma":[0.0003248578,0.00004191036,0.04175477,0.0006591361,0.0000777157,0.0001706497,0.0003029845,0.001000721,0.0007992733,0.001041835,0.9537743,0.00005196228],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003854574,0.00002779119,0.00003438387,0.00004435741,0.00001008463,0.000004417741,0.9991496,0.00009457572,0.0002493638],"genre_scores_gemma":[0.001058775,0.000040016,0.0001807217,0.00002779005,0.000003208268,0.00002197357,0.9983906,0.00002147316,0.0002555791],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03643385,"threshold_uncertainty_score":0.09684563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04636390865880308,"score_gpt":0.309244139483635,"score_spread":0.262880230824832,"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."}}