Takes a plain-text article (a TXT file, or the text itself) and returns all ten indicators of transparency the package detects: conflicts of interest, funding, protocol registration, novelty, replication, data sharing, code sharing, generative-AI-use disclosure, open-access licensing and reporting-guideline use. The file is read once and every detector runs on the same text, with the same logic as the standalone plain-text functions ([rt_coi()], [rt_fund()], [rt_register()], [rt_novelty()], [rt_replication()], [rt_data_code()], [rt_ai()], [rt_oa()], [rt_reporting()]).
Value
A one-row tibble: the file name (`article`) and PMID (`pmid`, the digits after "PMID" in the file name, `NA` if absent), then each indicator with the text that triggered it. The indicator columns carry the same names as in [rt_all_pmc()] (`is_coi_pred`, `is_fund_pred`, `is_register_pred`, `is_novelty_pred`, `is_replication_pred`, `is_open_data`, `is_open_code`, `is_ai_pred`, `is_open_access`, `is_reporting_pred`), so the result can be passed to [rt_summary()]. The pattern-function flags of the novelty and replication detectors are also returned; if one is `NA` it was not run. Unlike [rt_all_pmc()], `is_ai_pred` has no publication-year gate (see [rt_ai()]). `is_funded_pred` and `funding_text` are deprecated copies of the funding columns, kept for one release.
See also
[rt_all_pdf()] for a PDF, [rt_all_txt_dir()] for many files, and [rt_all_pmc()] for PMC XML.
Examples
# \donttest{
# Write a short example article to a temporary text file.
filepath <- file.path(tempdir(), "PMID00000000-PMC0000000.txt")
writeLines(c(
"To our knowledge, this is the first study of its kind.",
"Conflicts of interest: none declared.",
"This work was supported by the National Institutes of Health (R01-000000).",
"The protocol was registered at ClinicalTrials.gov (NCT00000000).",
"All data and code are available at https://github.com/example/repo.",
"We independently replicated the original analysis."
), filepath)
# Identify and extract indicators of transparency.
results_table <- rt_all(filepath)
# The same, from text already in memory.
results_table <- rt_all(text = readLines(filepath))
# }