What happened
in a pdf files with parsed sentences such as:
ANOVAs confirmed that the images differed significantly in terms of valence (F(2, 63) = 590, p < .001, ƞ²p = .95) and arousal (F(2, 63) = 276, p < .001, ƞ²p = .90).
See: https://osf.io/preprints/psyarxiv/zvymd_v1
the p-values are parsed as = while the symbol in the pdf is <
What did you expect
Ideally, the module can detect these weird formattings of < and parse them correctly. if not, it should perhaps not fire on these sentences and replace the < with = (which is not the correct symbol).
Steps to reproduce
json_file <- convert(file_path = "C:\Users\dlakens\Downloads\main_manuscript.pdf",
save_path = "C:\Users\dlakens\Downloads",
crossref_lookup = TRUE)
paper <- read(json_file)
statnonsig_res <- module_run(paper, "stat_p_nonsig")
statnonsig_res$table
What happened
in a pdf files with parsed sentences such as:
ANOVAs confirmed that the images differed significantly in terms of valence (F(2, 63) = 590, p < .001, ƞ²p = .95) and arousal (F(2, 63) = 276, p < .001, ƞ²p = .90).
See: https://osf.io/preprints/psyarxiv/zvymd_v1
the p-values are parsed as = while the symbol in the pdf is <
What did you expect
Ideally, the module can detect these weird formattings of < and parse them correctly. if not, it should perhaps not fire on these sentences and replace the < with = (which is not the correct symbol).
Steps to reproduce
json_file <- convert(file_path = "C:\Users\dlakens\Downloads\main_manuscript.pdf",
save_path = "C:\Users\dlakens\Downloads",
crossref_lookup = TRUE)
paper <- read(json_file)
statnonsig_res <- module_run(paper, "stat_p_nonsig")
statnonsig_res$table