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"save_fine_tune_data",
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"screen_errors",
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"screen_errors.gpt",
"set_api_key",
"tabscreen_claude",
"tabscreen_gemini",
"tabscreen_gpt",
"tabscreen_gpt.original",
"tabscreen_gpt.tools",
"tabscreen_groq",
"tabscreen_mistral",
"tabscreen_ollama"
],
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"object": "claude_model_prizes",
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],
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"price_in_per_token",
"price_out_per_token"
],
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"table": true,
"tojson": true
},
{
"name": "disagreements",
"title": "Disagreement sample data",
"object": "disagreements",
"class": [
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"tbl_df",
"tbl",
"data.frame"
],
"fields": [
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"human_code",
"studyid",
"title",
"abstract",
"promptid",
"prompt",
"model",
"question",
"top_p",
"incl_p",
"final_decision_gpt",
"final_decision_gpt_num",
"longest_answer",
"reps",
"n_mis_answers",
"submodel"
],
"rows": 7,
"table": true,
"tojson": true
},
{
"name": "filges2015_dat",
"title": "RIS file data from Functional Family Therapy (FFT) systematic review",
"object": "filges2015_dat",
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],
"fields": [
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],
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"table": true,
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},
{
"name": "gemini_model_prizes",
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"object": "gemini_model_prizes",
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],
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"price_out_per_token"
],
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"table": true,
"tojson": true
},
{
"name": "groq_model_prizes",
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},
{
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"object": "mistral_model_prizes",
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],
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"table": true,
"tojson": true
},
{
"name": "model_prizes",
"title": "Model prize data (last updated March 18, 2026)",
"object": "model_prizes",
"class": [
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],
"fields": [
"model",
"price_in_per_token",
"price_out_per_token"
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"rows": 76,
"table": true,
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}
],
"_help": [
{
"page": "approximate_price_gpt",
"title": "Approximate price estimation for title and abstract screening using OpenAI's GPT API models",
"topics": [
"approximate_price_gpt"
]
},
{
"page": "claude_model_prizes",
"title": "Claude model prices (last updated May 13, 2026) Data set containing input and output prizes for all Claude's API models.",
"topics": [
"claude_model_prizes"
]
},
{
"page": "create_fine_tune_data",
"title": "Function to generate dataset to be used for fine-tuning models",
"topics": [
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]
},
{
"page": "disagreements",
"title": "Disagreement sample data",
"topics": [
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},
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"title": "RIS file data from Functional Family Therapy (FFT) systematic review",
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{
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"title": "Gemini model prices (last updated May 7, 2026) Data set containing input and output prizes for all Gemini's API models.",
"topics": [
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]
},
{
"page": "get_api_key",
"title": "Get API key from R environment variable.",
"topics": [
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]
},
{
"page": "get_api_key_anthropic",
"title": "Get Anthropic API key from R environment variable.",
"topics": [
"get_api_key_anthropic"
]
},
{
"page": "get_api_key_gemini",
"title": "Get Gemini API key from R environment variable.",
"topics": [
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]
},
{
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"title": "Get GROQ API key from R environment variable.",
"topics": [
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]
},
{
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"title": "Get Mistral API key from R environment variable.",
"topics": [
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},
{
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"title": "Groq model prices (last updated March 18, 2026)",
"topics": [
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},
{
"page": "is_chatgpt",
"title": "Test if the object is a ''chatgpt'' object",
"topics": [
"is_chatgpt"
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},
{
"page": "is_chatgpt_tbl",
"title": "Test if the object is a ''chatgpt_tbl'' object",
"topics": [
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]
},
{
"page": "is_gpt",
"title": "Test if the object is a ''gpt'' object",
"topics": [
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]
},
{
"page": "is_gpt_agg_tbl",
"title": "Test if the object is a ''gpt_agg_tbl'' object",
"topics": [
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]
},
{
"page": "is_gpt_tbl",
"title": "Test if the object is a ''gpt_tbl'' object",
"topics": [
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]
},
{
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"topics": [
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]
},
{
"page": "model_prizes",
"title": "Model prize data (last updated March 18, 2026)",
"topics": [
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},
{
"page": "print.chatgpt",
"title": "Print methods for ''chatgpt'' objects",
"topics": [
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]
},
{
"page": "print.gpt",
"title": "Print methods for ''gpt'' objects",
"topics": [
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]
},
{
"page": "print.gpt_price",
"title": "Print methods for ''gpt_price'' objects",
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},
{
"page": "print.groq",
"title": "Print method for 'groq' objects",
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},
{
"page": "rate_limits_per_minute",
"title": "Find updated rate limits for API models",
"topics": [
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]
},
{
"page": "read_ris_to_dataframe",
"title": "Read an RIS file into a data frame",
"topics": [
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]
},
{
"page": "report",
"title": "Generate a report for screening disagreements between human and AI decisions",
"topics": [
"report"
]
},
{
"page": "sample_references",
"title": "Random sample references",
"topics": [
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]
},
{
"page": "save_dataframe_to_ris",
"title": "Write a data frame to a RIS file",
"topics": [
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]
},
{
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"title": "Function to write/save fine tune dataset in required jsonl format",
"topics": [
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]
},
{
"page": "screen_analyzer",
"title": "Analyze performance between the human and AI screening.",
"topics": [
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]
},
{
"page": "screen_errors",
"title": "Generic function to re-screen failed title and abstract requests.",
"topics": [
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]
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{
"page": "screen_errors.chatgpt",
"title": "Re-screen failed requests.",
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},
{
"page": "screen_errors.gpt",
"title": "Re-screen failed requests.",
"topics": [
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]
},
{
"page": "set_api_key",
"title": "Creating a temporary R environment API key variable",
"topics": [
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]
},
{
"page": "tabscreen_claude",
"title": "Title and abstract screening with Anthropic's API models",
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{
"page": "tabscreen_gemini",
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{
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{
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{
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}
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