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docs/src/api.md

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```@docs
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Base.convert
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ModelingToolkit.structural_simplify
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set_default_noise_scaling
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```
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## Chemistry-related functionalities

docs/src/inverse_problems/global_sensitivity_analysis.md

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!!! note
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We should make a couple of notes about the example above:
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- Here, we write our parameters on the forms $10^β$, $10^a$, and $10^γ$, which transforms them into log-space. This is advantageous in the context of inverse problems such as this one.
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- Here, we write our parameters on the forms $10^β$, $10^a$, and $10^γ$, which transforms them into log-space. As [previously described](@ref optimization_parameter_fitting_log_scale), this is advantageous in the context of inverse problems such as this one.
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- For GSA, where a function is evaluated a large number of times, it is ideal to write it as performant as possible. Hence, we initially create a base `ODEProblem`, and then apply the [`remake`](@ref simulation_structure_interfacing_problems_remake) function to it in each evaluation of `peak_cases` to generate a problem which is solved for that specific parameter set.
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- Again, as [previously described in other inverse problem tutorials](@ref optimization_parameter_fitting_basics), when exploring a function over large parameter spaces, we will likely simulate our model for unsuitable parameter sets. To reduce time spent on these, and to avoid excessive warning messages, we provide the `maxiters = 100000` and `verbose = false` arguments to `solve`.
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- As we have encountered in [a few other cases](@ref optimization_parameter_fitting_basics), the `gsa` function is not able to take parameter inputs of the map form usually used for Catalyst. Hence, as a first step in `peak_cases` we convert the parameter vector to this form. Next, we remember that the order of the parameters when we e.g. evaluate the GSA output, or set the parameter bounds, corresponds to the order used in `ps = [:β => p[1], :a => p[2], :γ => p[3]]`.

docs/src/model_simulation/simulation_introduction.md

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```
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If the `@default_noise_scaling` option is used, that term is only applied to reactions *without* `noise_scaling` metadata.
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While the `@default_noise_scaling` option is unavailable for [programmatically created models](@ref programmatic_CRN_construction), the [`remake_reactionsystem`](@ref simulation_structure_interfacing_problems_remake) function can be used to achieve a similar effect.
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While the `@default_noise_scaling` option is unavailable for [programmatically created models](@ref programmatic_CRN_construction), the `set_default_noise_scaling` function can be used to achieve a similar effect.
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## [Performing jump simulations using stochastic chemical kinetics](@id simulation_intro_jumps)
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