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Add a local TODO list for technical details of changes
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hughjonesd committed Apr 17, 2024
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9 changes: 8 additions & 1 deletion README.md
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This is the repository for
[Unjournal](https://www.unjournal.org) evaluations, meta-analysis, and meta-science.

Our current reports are available at <https://unjournal.github.io>.
Outputs and reports from here are published at <https://unjournal.github.io>.


# How it works

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The site can be re-rendered by running `quarto render` from the command line,
or `quarto::quarto_render()` from within R, and pushing changes to the `main` branch.
The rendered HTML is then automatically deployed via github pages.

The shiny app can be deployed by running
`rsconnect::deployApp("shinyapp/DataExplorer")`, or from within RStudio by
opening `shinyapp/DataExplorer/app.R` and clicking the 'publish' button.


# TODO

TODO.md has a list of planned changes.
28 changes: 28 additions & 0 deletions TODO.md
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TODO

This is a place for planned or desirable technical changes.
Higher-level plans are discussed on
the [Unjournal coda.io project management website](https://coda.io/d/Project-Management-UJ_dOyXJoZ6imx/Projects_subw9#Projects_tuA9I/r30&view=full).

[ ] Render the quarto docs remotely via github actions.

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daaronr Apr 17, 2024

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@hughjonesd that could be very helpful, yeah


# Evaluating publication predictions

[ ] Find out how to check publication automatically (ish?)

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daaronr Apr 17, 2024

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@hughjonesd would be awesome

- get DOI; match it against databases; fall back to title and authors?
- map publications to "tiers"
[ ] Build functions to create predictions from pairs of indiv. predictions
- simple average
- weighted by interval width
- extremized average
- for CIs, a Bayesian CI combining both?
- see Hanea et al.
"Mathematically aggregating experts’ predictions of possible futures"
- see aggreCATS package for some examples, but don't use it, unmaintained

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daaronr Apr 17, 2024

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@hughjonesd yeah, that seems reasonable.

[ ] Test predictions against reality:
- both for our "aggregate predictions", and for preds from individual raters
- MSE or MAE for mean/medians
- coverage for confidence intervals
[ ] Make a .qmd document or Shiny app reporting results overall, or for
specific subcategories of evaluations.

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