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PMC:7033348 / 20899-21963 JSONTXT

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LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T76 41-42 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T77 589-590 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T78 805-811 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tested
T79 816-817 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T80 888-889 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T16 128-134 http://purl.obolibrary.org/obo/GO_0040007 denotes growth

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T136 0-239 Sentence denotes The 2019-nCoV outbreak in China presents a significant challenge for modelers, as there are limited data available on the early growth trajectory, and epidemiological characteristics of the novel coronavirus have not been fully elucidated.
T137 240-539 Sentence denotes Our timely short-term forecasts based on phenomenological models can be useful for real-time preparedness, such as anticipating the required number of hospital beds and other medical resources, as they provide an estimate of the number of cases hospitals will need to prepare for in the coming days.
T138 540-692 Sentence denotes In future work, we plan to report the results of a retrospective analysis of forecasting performance across models based on various performance metrics.
T139 693-812 Sentence denotes Of note, the case definition changed on February 12, 2020 to count clinical cases that have not been laboratory tested.
T140 813-940 Sentence denotes As a result in this change in reporting, the province of Hubei experienced a jump in the nuber of cases on February 13th, 2020.
T141 941-1064 Sentence denotes This change in reporting will need to be taken into account in order to assess the accuracy of the forecasts reported here.