This is a table of adjective/noun combinations and their frequencies from sentences in your study carrel. Use it to search & browse the list to learn more about your study carrel.
| adjective | noun | frequency |
|---|---|---|
| novel | coronavirus | 185 |
| differential | equations | 152 |
| fractional | order | 138 |
| optimal | control | 120 |
| infected | individuals | 111 |
| mathematical | model | 103 |
| infectious | diseases | 102 |
| - | time | 92 |
| new | cases | 81 |
| covid-19 | pandemic | 74 |
| covid-19 | epidemic | 74 |
| infected | population | 73 |
| total | number | 73 |
| infected | cases | 63 |
| - | order | 62 |
| infectious | disease | 59 |
| covid-19 | outbreak | 58 |
| covid-19 | cases | 57 |
| susceptible | individuals | 57 |
| mathematical | models | 56 |
| total | population | 53 |
| susceptible | population | 48 |
| real | data | 44 |
| different | countries | 35 |
| differential | equation | 33 |
| infectious | individuals | 33 |
| large | number | 28 |
| asymptomatic | individuals | 27 |
| other | countries | 26 |
| asymptomatic | cases | 23 |
| covid-19 | infection | 20 |
| different | values | 20 |
| covid-19 | transmission | 19 |
| infected | individual | 19 |
| stochastic | model | 18 |
| covid-19 | outbreaks | 17 |
| fractional | model | 17 |
| infectious | cases | 17 |
| susceptible | individual | 16 |
| new | infection | 16 |
| numerical | results | 16 |
| initial | value | 15 |
| covid-19 | model | 14 |
| mathematical | analysis | 13 |
| new | coronavirus | 13 |
| positive | cases | 13 |
| initial | values | 13 |
| initial | data | 12 |
| stochastic | epidemic | 12 |
| new | data | 11 |
| stochastic | models | 11 |
| new | infections | 11 |
| infectious | individual | 11 |
| many | countries | 11 |
| first | equation | 11 |
| - | values | 10 |
| first | case | 10 |
| new | covid-19 | 10 |
| total | cases | 9 |
| infectious | rate | 9 |
| same | time | 9 |
| initial | population | 8 |
| real | time | 8 |
| first | time | 8 |
| new | model | 7 |
| total | infections | 7 |
| other | parameters | 7 |
| other | individuals | 7 |
| optimal | controls | 7 |
| infected | case | 7 |
| more | data | 7 |
| first | day | 7 |
| different | parameters | 7 |
| covid-19 | infections | 7 |
| covid-19 | disease | 7 |
| new | outbreak | 6 |
| numerical | analysis | 6 |
| infected | country | 6 |
| different | population | 6 |
| - | value | 6 |
| infectious | population | 5 |
| susceptible | populations | 5 |
| other | epidemics | 5 |
| novel | covid-19 | 5 |
| such | models | 5 |
| fractional | orders | 5 |
| first | order | 5 |
| different | times | 5 |
| different | time | 5 |
| - | parameter | 5 |
| many | cases | 4 |
| susceptible | case | 4 |
| stochastic | systems | 4 |
| real | number | 4 |
| other | models | 4 |
| numerical | value | 4 |
| novel | virus | 4 |
| novel | model | 4 |
| initial | number | 4 |
| initial | time | 4 |
| infectious | dynamics | 4 |
| fractional | dynamics | 4 |
| different | models | 4 |
| different | disease | 4 |
| different | control | 4 |
| - | valued | 4 |
| - | populations | 4 |
| same | day | 3 |
| more | individuals | 3 |
| positive | result | 3 |
| positive | value | 3 |
| total | time | 3 |
| stochastic | analysis | 3 |
| stochastic | covid-19 | 3 |
| such | cases | 3 |
| large | populations | 3 |
| highest | number | 3 |
| - | virus | 3 |
| high | number | 3 |
| first | infection | 3 |
| first | country | 3 |
| different | epidemic | 3 |
| asymptomatic | transmission | 3 |
| - | infection | 3 |
| - | coronavirus | 3 |
| fractional | system | 3 |
| many | individuals | 2 |
| novel | epidemic | 2 |
| new | disease | 2 |
| more | time | 2 |
| more | cases | 2 |
| many | times | 2 |
| larger | number | 2 |
| largest | value | 2 |
| largest | number | 2 |
| large | population | 2 |
| initial | transmission | 2 |
| initial | populations | 2 |
| numerical | values | 2 |
| numerical | analyses | 2 |
| infectious | virus | 2 |
| other | model | 2 |
| positive | case | 2 |
| positive | numbers | 2 |
| real | epidemics | 2 |
| same | countries | 2 |
| same | dynamics | 2 |
| same | model | 2 |
| same | number | 2 |
| stochastic | coronavirus | 2 |
| stochastic | population | 2 |
| such | model | 2 |
| such | outbreaks | 2 |
| susceptibles | individuals | 2 |
| initial | infections | 2 |
| real | case | 2 |
| infectious | r | 2 |
| different | model | 2 |
| infectious | epidemics | 2 |
| - | analysis | 2 |
| - | day | 2 |
| - | model | 2 |
| - | population | 2 |
| asymptomatic | individual | 2 |
| asymptomatic | population | 2 |
| basic | analysis | 2 |
| basic | model | 2 |
| covid-19 | dynamics | 2 |
| covid-19 | time | 2 |
| covid-19 | virus | 2 |
| different | cases | 2 |
| asymptomatic | infection | 2 |
| different | parameter | 2 |
| high | population | 2 |
| infectious | case | 2 |
| different | rates | 2 |
| infected | covid-19 | 2 |
| higher | values | 2 |
| higher | order | 2 |
| higher | value | 2 |
| high | order | 2 |
| fractional | epidemic | 2 |
| first | days | 2 |
| first | covid-19 | 2 |
| first | control | 2 |
| different | transmission | 2 |
| novel | infection | 1 |
| optimal | population | 1 |
| novel | pandemic | 1 |
| novel | results | 1 |
| numerical | model | 1 |
| optimal | model | 1 |
| optimal | number | 1 |
| optimal | parameters | 1 |
| other | time | 1 |
| optimal | time | 1 |
| optimal | value | 1 |
| optimal | values | 1 |
| other | data | 1 |
| other | diseases | 1 |
| other | dynamics | 1 |
| other | values | 1 |
| other | viruses | 1 |
| new | transmission | 1 |
| new | virus | 1 |
| mathematical | modelling | 1 |
| new | system | 1 |
| new | results | 1 |
| many | disease | 1 |
| many | dynamics | 1 |
| many | infection | 1 |
| many | models | 1 |
| many | parameters | 1 |
| positive | covid-19 | 1 |
| mathematical | results | 1 |
| more | disease | 1 |
| more | parameter | 1 |
| new | analysis | 1 |
| new | case | 1 |
| new | control | 1 |
| new | epidemic | 1 |
| new | individuals | 1 |
| new | outbreaks | 1 |
| new | pandemic | 1 |
| new | parameters | 1 |
| others | countries | 1 |
| same | result | 1 |
| positive | individual | 1 |
| stochastic | equations | 1 |
| stochastic | transmission | 1 |
| such | analysis | 1 |
| such | case | 1 |
| such | country | 1 |
| such | dynamic | 1 |
| such | equations | 1 |
| such | individuals | 1 |
| such | outbreak | 1 |
| such | pandemic | 1 |
| such | system | 1 |
| such | times | 1 |
| susceptible | cases | 1 |
| susceptible | epidemics | 1 |
| total | epidemic | 1 |
| total | infection | 1 |
| total | numbers | 1 |
| total | outbreak | 1 |
| stochastic | system | 1 |
| stochastic | equation | 1 |
| positive | population | 1 |
| stochastic | epidemics | 1 |
| positive | values | 1 |
| real | cases | 1 |
| real | numbers | 1 |
| real | order | 1 |
| real | outbreak | 1 |
| real | outbreaks | 1 |
| real | parameters | 1 |
| same | disease | 1 |
| same | infection | 1 |
| same | parameter | 1 |
| same | rate | 1 |
| largest | population | 1 |
| same | results | 1 |
| same | t | 1 |
| same | transmission | 1 |
| social | disease | 1 |
| social | population | 1 |
| many | data | 1 |
| initial | infection | 1 |
| largest | pandemic | 1 |
| basic | virus | 1 |
| covid-19 | coronavirus | 1 |
| covid-19 | covid-19 | 1 |
| covid-19 | data | 1 |
| covid-19 | epidemics | 1 |
| covid-19 | pandemics | 1 |
| covid-19 | viruses | 1 |
| different | country | 1 |
| different | days | 1 |
| different | infection | 1 |
| different | numbers | 1 |
| different | order | 1 |
| different | orders | 1 |
| different | pandemic | 1 |
| different | populations | 1 |
| different | rate | 1 |
| different | results | 1 |
| differential | model | 1 |
| covid-19 | case | 1 |
| basic | parameters | 1 |
| largest | outbreak | 1 |
| basic | number | 1 |
| - | case | 1 |
| - | cases | 1 |
| - | control | 1 |
| - | controlled | 1 |
| - | countries | 1 |
| - | covid-19 | 1 |
| - | data | 1 |
| - | disease | 1 |
| - | dynamics | 1 |
| - | epidemic | 1 |
| - | equation | 1 |
| - | infections | 1 |
| - | number | 1 |
| - | pandemic | 1 |
| asymptomatic | parameter | 1 |
| asymptomatic | populations | 1 |
| asymptomatic | virus | 1 |
| differential | models | 1 |
| differential | system | 1 |
| first | cases | 1 |
| first | epidemic | 1 |
| infectious | data | 1 |
| infectious | outbreak | 1 |
| initial | cases | 1 |
| initial | coronavirus | 1 |
| initial | days | 1 |
| initial | numbers | 1 |
| initial | parameter | 1 |
| initial | parameters | 1 |
| initial | times | 1 |
| large | disease | 1 |
| large | numbers | 1 |
| large | outbreak | 1 |
| large | r | 1 |
| large | value | 1 |
| larger | covid-19 | 1 |
| largest | disease | 1 |
| largest | epidemic | 1 |
| infected | populations | 1 |
| infected | numbers | 1 |
| infected | epidemic | 1 |
| high | numbers | 1 |
| first | model | 1 |
| first | pandemic | 1 |
| fractional | case | 1 |
| fractional | equations | 1 |
| fractional | values | 1 |
| high | disease | 1 |
| high | epidemic | 1 |
| high | r | 1 |
| infected | countries | 1 |
| high | rate | 1 |
| high | rates | 1 |
| high | value | 1 |
| high | values | 1 |
| higher | number | 1 |
| higher | numbers | 1 |
| highest | case | 1 |
| total | populations | 1 |