Difference between revisions of "WormBase-Caltech Weekly Calls"
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[[WormBase-Caltech_Weekly_Calls_2019|2019 Meetings]] | [[WormBase-Caltech_Weekly_Calls_2019|2019 Meetings]] | ||
+ | [[WormBase-Caltech_Weekly_Calls_2020|2020 Meetings]] | ||
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− | = | + | = 2021 Meetings = |
− | + | [[WormBase-Caltech_Weekly_Calls_January_2021|January]] | |
− | + | [[WormBase-Caltech_Weekly_Calls_February_2021|February]] | |
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− | == | + | == March 4, 2021 == |
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− | === | + | === Webinar Monday === |
− | * | + | * Juancarlos can send a reminder email; he just needs the text for the body of the email message |
− | * | + | * Can we send the webinar reminder to WB staff? Cannot use staff@wormbase.org to register |
+ | * Raymond will try to remember to forward to staff | ||
− | === | + | === Neural Network (NN) evaluation === |
− | * | + | * Kimberly (and other curators) looking through NN results |
− | * | + | * Had previously prevented LOW scoring SVMs(?) from being sent to authors |
− | * | + | * We need an agreed upon protocol for evaluation |
− | + | * To avoid bias, we should randomly sample papers; usually will find negatives; how do we represent high, medium and low-scoring papers in the set without making curators review >> 100 papers? | |
− | + | * Michael will come up with protocol and send around list of papers for each data type (in Google Doc) | |
− | + | * Perhaps evaluation should happen on non-curated, newer papers | |
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Latest revision as of 18:42, 4 March 2021
Contents
Previous Years
2021 Meetings
March 4, 2021
Webinar Monday
- Juancarlos can send a reminder email; he just needs the text for the body of the email message
- Can we send the webinar reminder to WB staff? Cannot use staff@wormbase.org to register
- Raymond will try to remember to forward to staff
Neural Network (NN) evaluation
- Kimberly (and other curators) looking through NN results
- Had previously prevented LOW scoring SVMs(?) from being sent to authors
- We need an agreed upon protocol for evaluation
- To avoid bias, we should randomly sample papers; usually will find negatives; how do we represent high, medium and low-scoring papers in the set without making curators review >> 100 papers?
- Michael will come up with protocol and send around list of papers for each data type (in Google Doc)
- Perhaps evaluation should happen on non-curated, newer papers