Hi Anastasia,
I am still experiencing the same problem, but honestly I cannot figure what could be the issue. For the April 2025 data, I included locality and country, which was missing in my past uploads, but nothing much improved. Perhaps I will share with you the May 2025 spreadsheet before I upload for your perusal.
I also operate in two sites (Lewa and Borana) of which I include in the spreadsheet. Does this mean that the software matches Borana for Borana and Lewa for Lewa, or it cuts across?. I would expect the latter to be ideal.
Thank you,
Timothy
Hi @Timothy
Yes, feel free to send me your spreadsheet before your upload so we can rule out any odd behavior there.
The bulk import page will automatically select the locations from your spreadsheet to run ID for. I checked this recent import from you that has encounters from Borana and Lewa and verified that both locations were selected in the menu:
This means that all encounters in the import are checked for matches across both sites.
Hi Anastasia,
Look through the ID below;
- LWC_GZ_MAY_2025_0001-3 AND LWC_GZ_MAY_2025_0001-1 are the same animal
- LWC_GZ_MAY_2025_0001-4 AND LWC_GZ_MAY_2025_0001-2 are the same animal
I got the above from uploads that I already know the animals.
I have sent you an email separately the data I uploaded.
Thank you
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Thanks for sending your bulk import data! I’ll review these and your above examples today and get back to you with my findings.
Hi @Timothy
Thanks for your patience!
I was looking at the original match results for these zebras and saw that the match page showed they were compared against 11,000 candidates across the following regions:
When re-running the match with just Lewa selected (checking against 260 candidates), the correct candidate appeared each time. When re-tested with the broader number of locations (against 11,000 candidates), no match was found within the top 50 results.
My recommendation is to start with just your location ID when searching for matches. If the correct individual is not shown, then you can start adding additional regions to see if a correct match appears. Sometimes the noise of too many candidates can obscure positive match results.
Edited to add that your spreadsheet and photos look good! It’s just that for this instance, casting too wide of a net for matching is making it harder to find the correct match.
I will try this Anastasia, maybe Lewa and Borana, as these are my core area.
Thank you
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Hi @Timothy
We found a bug in Zebra Wildbook that may have contributed to some the missing matches you’ve reported. Wildbook was ignoring annotations that were missing a viewpoint (this mostly impacted some old catalog data). If you’ve come across any questionable match results lately, re-running them now should show those older individuals as positive matches now.
