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Another great example of this working is the genomic variant calling models from Deepmind "DeepVariant". They use the "alignment pile-up" images which are also used by humans to debug genomic alignments, with some additional channels to further feature engineer the CNN.

What was true last year may be false today. For instance, ...

Good example of a medical QA dataset shifting but not a good example of a medical "fact" since it is an opinion. Another way to think about shifting medical targets over time would be things like environmental or behavioral risk factors changing.

Anyways, thank you for putting this dataset together, certainly we need more third-party benchmarks with careful annotations done. I think it would be wise if you segregate tasks between factual observations of data, population-scale opinions (guidelines/recommendations), and individual-scale opinions (prognosis/diagnosis). Ideally there would be some formal taxonomy for this eventually like OMOP CDM, maybe there is already in some dusty corner of pubmed.

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Resume: https://drive.google.com/file/d/0B9ld6yEz58mYenRYbW9nMFJLS1k...

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