AI Screening Tools in R for Systematic Reviewing
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Documentation for package ‘AIscreenR’ version 0.4.0
Help Pages
| approximate_price_gpt | Approximate price estimation for title and abstract screening using OpenAI's GPT API models |
| claude_model_prizes | Claude model prices (last updated May 13, 2026) Data set containing input and output prizes for all Claude's API models. |
| create_fine_tune_data | Function to generate dataset to be used for fine-tuning models |
| disagreements | Disagreement sample data |
| filges2015_dat | RIS file data from Functional Family Therapy (FFT) systematic review |
| gemini_model_prizes | Gemini model prices (last updated May 7, 2026) Data set containing input and output prizes for all Gemini's API models. |
| get_api_key | Get API key from R environment variable. |
| get_api_key_anthropic | Get Anthropic API key from R environment variable. |
| get_api_key_gemini | Get Gemini API key from R environment variable. |
| get_api_key_groq | Get GROQ API key from R environment variable. |
| get_api_key_mistral | Get Mistral API key from R environment variable. |
| groq_model_prizes | Groq model prices (last updated March 18, 2026) |
| is_chatgpt | Test if the object is a "chatgpt" object |
| is_chatgpt_tbl | Test if the object is a "chatgpt_tbl" object |
| is_gpt | Test if the object is a "gpt" object |
| is_gpt_agg_tbl | Test if the object is a "gpt_agg_tbl" object |
| is_gpt_tbl | Test if the object is a "gpt_tbl" object |
| mistral_model_prizes | Mistral model prices (last updated May 7, 2026) Data set containing input and output prizes for all Mistral's API models. |
| model_prizes | Model prize data (last updated March 18, 2026) |
| print.chatgpt | Print methods for "chatgpt" objects |
| print.gpt | Print methods for "gpt" objects |
| print.gpt_price | Print methods for "gpt_price" objects |
| print.groq | Print method for 'groq' objects |
| rate_limits_per_minute | Find updated rate limits for API models |
| read_ris_to_dataframe | Read an RIS file into a data frame |
| report | Generate a report for screening disagreements between human and AI decisions |
| sample_references | Random sample references |
| save_dataframe_to_ris | Write a data frame to a RIS file |
| save_fine_tune_data | Function to write/save fine tune dataset in required jsonl format |
| screen_analyzer | Analyze performance between the human and AI screening. |
| screen_errors | Generic function to re-screen failed title and abstract requests. |
| screen_errors.chatgpt | Re-screen failed requests. |
| screen_errors.gpt | Re-screen failed requests. |
| set_api_key | Creating a temporary R environment API key variable |
| tabscreen_claude | Title and abstract screening with Anthropic's API models |
| tabscreen_gemini | Title and abstract screening with Gemini API models using function calls |
| tabscreen_gpt | Title and abstract screening with GPT API models using function calls via the tools argument and the responses endpoint |
| tabscreen_gpt.original | Title and abstract screening with GPT API models using function calls via the original function call arguments |
| tabscreen_gpt.tools | Title and abstract screening with GPT API models using function calls via the tools argument |
| tabscreen_gpt.tools_responses | Title and abstract screening with GPT API models using function calls via the tools argument and the responses endpoint |
| tabscreen_groq | Title and abstract screening with GROQ API models using function calls via the tools argument |
| tabscreen_mistral | Title and abstract screening with mistral's API models |
| tabscreen_ollama | Title and abstract screening with OLLAMA API models using function calls via the tools argument |