Refines the authors code output from authors_clean()

authors_refine This function takes the author list output after the output has been synthesized for incorrect author matches. It contains a similarity score cutoff like read_authors. This however is to further constrain the list. New values ARE NOT created, instead it filters by the sim_score column in the output file.

Usage

authors_refine(review, prelim, sim_score = NULL, confidence = NULL)

Arguments

review

the review element from list output by authors_clean

prelim

the prelim element from list output by authors_clean

sim_score

similarity score cut off point. Number from 0-1.

confidence

confidence score cut off point. Number from 0 - 10.

Examples

## First gather the authors data.frame from authors_clean
data(BITR)
BITR_authors <- authors_clean(BITR)
#> 
#> Splitting author records
#> 
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#> 
#> Splitting addresses.
#> 
#> standardizing country names...
#> 
#> extracting the names of institutions...
#> 
#> extracting cities...
#> 
#> extracting states/provinces...
#> 
#> extracting country...
#> 
#> processing postal codes...
#> 
#> review, correction, and clean-up...
#> 
#> Please be patient - this might take a bit.
#> 
#> (still working on it...)
#> 
#> (getting closer...)
#> 
#> (not much longer...)
#> 
#> (almost done...)
#> 
#> (so close...the end is in sight!)
#> 
#> (this is it - the last step!)
#> 
#> Matching authors
#> 
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#> 
#> Pruning groupings...
BITR_review_df <- BITR_authors$review 
BITR_prelim_df <- BITR_authors$prelim

## If accepting the preliminary disambiguation 
## from authors_clean() without review:
refine_df <- authors_refine(BITR_review_df, BITR_prelim_df,
    sim_score = 0.90, confidence = 5)

## Note that 'sim_score' and 'confidence' are optional arguments and are
## only required if changing the default values. 
refine_df <- authors_refine(BITR_review_df, BITR_prelim_df)


## If changes were made to groupID or authorID in the "_review.csv" file: 
## then incorporate those changes in a text editor, save the corrections as
## a new file name, load in to R and run `authors_refine()` with the 
## new corrections as the review arguement.