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The HST peer review process for Cycle 26 has moved to a double-anonymous review process, in which authors’ identities are concealed from both review panel members and TAC members. See the FAQ on Anonymizing Proposal Reviews for more general information on this change.

As in previous cycles, proposers will still enter the names and affiliations of all investigators into the APT system. APT will not include these names in the documents that the reviewers will see.

However, it is also necessary for proposers to take additional steps to anonymize their PDF attachment before it is uploaded to APT. Below are some guidelines to follow to do this:

  • Do not include author names or affiliations anywhere in the manuscript, including the page headers and footers.
  • When citing references within the proposal, use third person neutral wording when possible. For example, replace phrases like “as we have shown in our previous work (Doe et al. 2010)” with “as Doe et al. (2010) showed...”

  • If self-referencing is essential, cite papers published by the author also in the third person. [–delete as [author(s) et al. 2010] in the text. In the reference list, delete the citation, and use the placeholder [author(s) et al. 2010]. --]

  • Do not refer to previous campaigns using HST or other observatories in an identifying fashion. For instance, rather than write "we observed another cluster, similar to the one we are proposing for here, in 2014 under HST program #XXXXX," instead write "HST has observed this target in the past..."

  • Do not include acknowledgements, or the source of any grant funding.
  • Check that no author information is included in the metadata that is automatically created by many word processing programs. In many common programs, like Word or Acrobat Reader, this information can be displayed (and edited) in the “File” tab, under “properties.” 
  • Remove any identifying information that might be present in figures and tables. Including watermarks.

  • Create bullet that tells authors they need to put more effort in describing past work, and how this proposal will improve/build upon past work. What sort of statistical completeness?
  • Start early in reworking your manuscript

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