# AIscreenR 0.4.0

## New features
* Adding `tabscreen_mistral()` and `get_api_key_mistral()` functions to screen titles and abstracts using Mistral's API models.
* Adding `tabscreen_gemini()` and `get_api_key_gemini()` function to screen titles and abstracts using Gemini's API models.
* Adding `tabscreen_claude()` and `get_api_key_anthropic()` function to screen titles and abstracts using Anthropics's API models.

## Major improvements
* Migrating from chat/completions endpoint to responses for all OpenAI functions. This includes:
    * `tabscreen_gpt()`
    * `screen_errors.gpt()`
    * `rate_limits_per_minute()`

## Minor improvements
* Updated the prize function with up-to-date prizes for the GPT-5 models. 
* Adding the n_screened and n_missing variables to the key results in `screen_analyzer()`.


# AIscreenR 0.3.2

## Minor improvements
* Updating the default inclusion threshold and documentation hereof when conducting replicate screenings to be aligned with the finding from Vembye et al. (2025).
* Updating the handling of coding missing abstracts in the vignette now when using `read_ris_to_dataframe()`.
* Better error messages for unknown GPT models when using newer or fine-tuned models.


## Bug fixes
* Fixed bug in `report()` when rendering large amounts of text.
* Fixed bug in `tabscreen_gpt()` when using multiple reps and gpt-5 models.
* Fixed bug in `screen_analyzer()` when working with multiple prompts, models, and reps.
* Correcting path in generating-disagreement-reports article.
* Set max_tries in `rate_limits_per_minute()` to avoid message from httr2.

## Further documentation
* Add installation guide to ollama article.
* Include an example of fine-tuning a model and using it to fine-tuning article.

# AIscreenR 0.3.1

* Updating documentation of `tabscreen_gpt()`


# AIscreenR 0.3.0

## New features
* Adding `tabscreen_groq()` function to screen titles and abstracts using Groq AI.
* Adding `tabscreen_ollama()` function to screen titles and abstracts using local ollama models.
* Adding functions to read and write RIS files: `read_ris_to_dataframe()` and `save_dataframe_to_ris()`.
* Adding function to generate disagreement reports: `generate_disagreement_report()`.
* Making new refinements to the tabscreen_* functions. Making it possible to steer the model's (over)inclusion behavior via the `overinclusive = TRUE` argument in tabscreen_* functions. 

## Further documentation
* Adding articles for fine-tuning OpenAI models, generating disagreement reports, generating fine-tuning data and reading/writing RIS files.
* Adding article for comparing performance of reasoning models (including gpt-5 models) with gpt-4o-mini.

## Minor improvements
* Updated prize data, including all up-to-date models


# AIscreenR 0.2.0

* Adding Thomas Olsen as co-author.

## New features
* Adding `create_fine_tune_data()` and `write_fine_tune_data()` to generate data for fine tuning OpenAI's models.

## Minor improvements
* Minor change in the setup of the vignette.
* Updated prize data, including all up-to-date models.


# AIscreenR 0.1.1

* A typo in the vignette has been corrected.
* The vignette now draws on functions from synthesisr instead of revtools to handle RIS files.
* `tabscreen_gpt()` now treats the study ID variable as a factor to keep original order of the dataset with titles and abstracts.

# AIscreenR 0.1.0

* This is the first release of AIscreenR.
