45 Matching Annotations
  1. Aug 2023
    1. Sarah Grace

      Not Alvsce

    2. Rachel Laura

      Accept if space?

    3. Eung Joo Lee

      Already an expert!

    4. Bryan Roxas

      Admit. Did incubator with group.

    5. Renee Grambihler

      Seems like good opportunity to network with Biosphere 2 & build DS capacity there. However, already pretty advanced practicioner.

    6. Rachel Leih

      Admit. Good answers, stands to benefit a lot

    7. Parker Geffre

      Admit.

    8. Mary Ahern

      Admit

    9. Madeleine deBlois

      Admit. Good fit. Terrace's co-worker.

    10. Madeleine Wallace

      Admit. ALVSCE, good answers

    11. Likith Kumar Dundigalla

      Cut. Already highly skilled, answers dont' match course description

    12. Katherine King

      Not ALVSCE, but admit if space

    13. Jordan Gunning

      Admit.

    14. Giovanni Melandri

      Admit? Curious if he'll really have time

    15. Eldridge Wisely

      Not in ALVSCE, but admit if space

    16. Edwin Alvarado-Mena

      Not in ALVSCE, but admit if space

    17. Ryan

      Cut. Not at UAZ

    18. Bryan Blue

      Admit. ALVSCE, good answers, stands to benefit

    19. Ajay Perumbeti

      Cut? Already highly skilled, not in ALVSCE

    20. Zoe Scott

      Admit. Will benefit, good answers, in CALES

    21. YIJYUN LIN

      I kept the duplicate application because her answers are quite different LOL

    22. YIJYUN LIN

      Accept. I've worked with YiJyun and she would benefit from this course

    23. 1: Not able to perform task

      This should be a 2. See answers below

    24. SQL for phenotyping

      How?

    25. Simone Williams

      Accept. I've been working with Simone and she would benefit from this course

    26. Rohit Hemaraja

      Cut? Vague answers

    27. Rachel Gildersleeve

      Cut. No R

      This is Terrace's co-worker. We should follow up personally with resources to get started in R so they can take this course next year.

    28. Michael Hernandez

      Cut. Answers don't match workshop description

    29. Meccah Jarrah

      Cut. No R experience

    30. Mariam Hovhannisyan

      Cut? Already has a lot of skills and not in ALVSCE

    31. Kylie Boyd

      Cut. No R

    32. Joshua Oyekanmi

      Cut? Answers are terse, low R skill

    33. Damian Barraza

      Cut. His answer to "how" doesn't match the course description.

  2. Aug 2022
    1. However, it is also common to only include a subset of principal component scores when building regression models

      This is probably rarely a good idea. If ecologically relevant variables are not the ones that contribute to co-variation, they will be lost. In fact, principal component regression is rarely a good idea, especially since there are many supervised multivariate analysis techniques to deal with multicollinearity in regression like problems (e.g. RDA, CCA, PLSR). For more detailed discussion of why PCA regression is probably almost always the wrong choice for ecological data, see Scott & Crone 2021

      Scott, Eric R., and Elizabeth E. Crone. “Using the Right Tool for the Job: The Difference between Unsupervised and Supervised Analyses of Multivariate Ecological Data.” Oecologia 196 (February 12, 2021): 13–25. https://doi.org/10.1007/s00442-020-04848-w.

  3. Jul 2022
    1. xecutable code

      change this to something else

  4. Apr 2022
    1. https://ourcodingclub.github.io/, https://www.openscapes.org/

      convert to citations

    2. (Box 1)[#box-1-definitions])

      Markdown issue

    3. General background about GitHub

      We should comment out any headers that we don't actually want showing up in the rendered doc

    4. The source code and data for this manuscript are available at https://github.com/SORTEE-Github-Hackathon/manuscript.

      Add Zenodo DOI.

    5. German Centre for Integrative Biodiversity Research (iDiv).

      change to citation

    6. [[22]][7].

      Typo here in formatting citation

    7. Ecologists who write code often use the R programming language, and the rOpenSci community has a well-established software peer review process that involves both rOpenSci’s staff software engineers and the broader R user community. Their software review GitHub repository provides instructions for submitting an R package for review as well as guidelines for code reviewers. rOpenSci’s efforts have resulted in many well-used R packages for ecology research including rfishbase [21] and taxize [22].

      rOpenSci review is mentioned earlier in the Peer-Review section. I suggest moving this up and merging

    8. GitHub can bGitHub

      Typo

  5. Mar 2022
    1. The standard GitHub licensing options are best suited for software. If your code is intended only for your specific analysis, consider a Creative Commons License. The Choose a License website can offer further guidance. If you wish to allow anyone to re-use your code, consider a CC0 1.0 public domain dedication. If you wish to receive attribution for any reuse of your code, consider a CC BY 4.0 license, which requires attribution upon reuse. If you have build an app, tool, package, or other product that you would like others to use and would like attribution for any reuse of your code, consider the GNU General Public License v3. This license also prohibits the re-user from making their re-used version private. If you do not wish to receive attribution and are open to private use, consider the MIT license.

      I think probably less detail is needed here. Distill down to most important points

    2. Box 2

      This should just be Table 1 I think