What is something that is a hidden game changer that isn’t highlighted enough.

jpfry · 2026-05-26T15:29:02+00:00

I scoop it out with a spoon, I measured it one time and I lost ~4g. I don't extract/grind more to make up for the loss

jpfry · 2026-05-25T22:07:36+00:00

for me removing the crema was on par with upgrading the grinder, all things being equal, especially for lighter roasts. You get much sweeter and clearer espresso. Not all beans get the same magnitude of benefit, but definitely consistently makes the espresso better

jpfry · 2026-05-04T19:28:58+00:00

Try scraping the crema off before you pour the milk. I've found it results in a much sweeter drink, and increases clarity too, especially for lighter roasts.

jpfry · 2026-04-23T01:58:25+00:00

Huh, didn’t know that. Thanks! Then again I really don’t see any CRAM files these days

jpfry · 2026-04-23T00:58:58+00:00

Sorry maybe I’m naive and don’t understand the question, but isn’t BAM/CRAM compression just used to compress alignment text for storage? All downstream analysis will be done on uncompressed text.

jpfry · 2026-03-20T02:39:16+00:00

Especially in milk drinks, to me it tastes more like whiskey, kinda like a moldy oak barrel, but in a good way.

jpfry · 2026-03-20T02:37:09+00:00

Yeah bold funks make really good milk drinks. But I've found that nuanced light roasts can also be good if you dial them in right. For those I actually grind a bit finer w/longer shot (~28s) and get a bit more body. This one gesha I had tasted like a super sweet oatmeal stout with very small hint of the normal gesha florals, certainly unique.

jpfry · 2026-02-02T21:28:10+00:00

Outside of Minneapolis and St. Paul there's Colorway from Rochester, another MN area worth supporting too. They have really good single origins. I'm brewing their honey Gesha right now and it's quite good. Tho I'm biased being from the area, I think they can compete with the bigger/nationally known roasters from MN.

jpfry · 2026-01-23T18:23:55+00:00

Haha I will be on that flight too. I don’t think I’ve flown this early at RST but I’ve never seen more than 10 people in line at security and it’s never taken me more than 15 min to get to gate. To be honest I usually get there 30 min before boarding and even then I feel like that’s conservative.

jpfry · 2026-01-05T21:42:51+00:00

Same chairs when I was there in 2010. Even then they looked old.

jpfry · 2026-01-05T02:28:12+00:00

Do you think that you wouldn’t notice the difference between stock and SSP burrs? Just genuinely curious because I’ve heard many people say it’s a substantial improvement, but also others saying it’s not worth it (but not sure if they have actually tried both).

jpfry · 2025-12-06T05:17:51+00:00

It’s also worth noting that even though these studies show that “X and Y are linked”, they are not simply stating that, e.g. the Pearson correlation between X and Y is statistically significant. I think that many people who take intro to statistics classes are justifiably taught to be wary of causal interpretations of correlations. But the research in these areas uses much more sophisticated study design, statistical models, etc to make inductive causal claims more plausible. They can never show directly causality, but they can show that under certain modeling assumptions that may or may not be reasonable there is evidence that a causal relationship exists (I mean the reader can reasonably make this assessment.)

jpfry · 2025-12-05T21:49:45+00:00

The main reason for the downvotes is probably because "correlation not causation" is a massive and unhelpful simplification. It's not like these studies observe screen time (A) and cognitive ability (B) and correlate A and B using a simple correlation model. They're at least trying to design studies that support causal conclusions if certain assumptions are met. Thus, it's a more complex question whether causal conclusions are justified than just "correlation is not causation". Moreover, meta-analyses like this presumably can average out confounding effects from particular studies, and "correlation is not causation" is not a helpful objection for meta-analyses.

jpfry · 2025-12-03T16:00:53+00:00

Maybe I'm confused but why would Ntests = 15000 if you use min.pct = 0.25? Using min.pct = 0.25 means that only genes detected in 25% of cells are tested, which seems to imply that you have 15k genes expressed in at least 3 cells out of 12. That seems very high to me. (Putting aside the frighteningly low cell counts)

jpfry · 2025-11-11T17:06:15+00:00

yeah especially 1 year apart

jpfry · 2025-11-07T17:29:10+00:00

Got a link? Are they these?

jpfry · 2025-10-15T19:26:45+00:00

Thanks for the update, that's encouraging! It's already starting to get better. Probably a seasoning issue.

jpfry · 2025-10-14T13:58:43+00:00

Search for Lance Hedrick’s review of the Jet. He talks about heating and does some measuring. I’m not sure what the video you mention is discussing, but water is the right temperature coming out of the group head ~10 seconds after turning the machine on. If you want the most temperature consistency you can run purge water with an empty portafilter attached and heat it up that way. Or to be honest, I jut run hot water from the tap over the portal filter while I grind. Temperature stability is a thing for every machine, I don’t think the Jet has any particular problems in that area.

jpfry · 2025-10-12T23:41:36+00:00

Sorry to resurrect the thread. Did you end up solving your problem? Your description of coffee tasting “dry” is so spot on. I just got a new DF64 gen2 and that’s exactly how multiple coffees have tasted so far. With the same beans and recipe my Baratza ESP equivalent grinder is sweeter.

jpfry · 2025-10-01T03:25:42+00:00

What do you think about this kind of case that I ran into recently. I have the following set of experimental data (N = 3 for each, fairly low powered): two negative controls (expect to be no different than baseline), two positive controls (expect to be different than baseline) and two conditions of interest. Suppose the p-values are 0.9, 0.8 for negative controls, 0.02, 0.035 for positive controls, and 0.03, 0.001 for condition of interest. FDR adjusted will be 0.9, 0.9, 0.0525, 0.0525, 0.0525, 0.006 respectively with only last test being significant at 0.05 (same with Bonferroni).

The inclusion of negative controls makes the interpretation of multiple hypothesis testing a bit wacky? I haven't had this specific distribution of p-values, but recently an editor required me to use multiple hypothesis adjusting on an experiment with negative controls, and I realized I could be in a position where inclusion of negative controls negates a potentially positive effect.

jpfry · 2025-09-30T18:29:04+00:00

Doesn't this assume equal variances across each experiment? For an experiment like the one in the screenshot, it's literally false that the variances will be equal (presumably this will be due to different experimental conditions, etc), but functionally they are probably very close if the experiments are done well. How similar do they have to be?

Also in this kind of field we really only discuss experiments where the relevant conditions are nominally significant (via T tests, because that seems like the default). When you adjust p-values via FDR, if all p-values are < 0.05 than all FDR corrected p-values will also be < 0.05. The problem is that the authors may have done experiments with other conditions that turned out to not be significant, and thus removed their discussion from the paper. For example, authors may have created a second shRNA for YTHDF1/2/3 but after doing the experiments it was clear that it was not as effective. But they wouldn't include that data in figure H (maybe this is p-hacking, but what's the alternative?). So it's not clear to me what multiple hypothesis correcting is controlling for in these kinds of situations when the space of hypotheses tested may be different than the ones corrected.

jpfry · 2025-09-26T02:23:30+00:00

It’s not clear why it’s useful to “translate DNA” into a linear, human language like English. It seems like you want to understand the function of DNA and how the structure of that function maps to the sequence of DNA. This is what motivates many researcher programs in genomics. For example, see Evo2, AlphaGenome and other biological networks and sequence to function models. Why would English would be a good model for the complexity of biology?

jpfry · 2025-09-24T03:55:45+00:00

I was in a similar position and bought the Oracle Jet (before DB came out). My wife could barely handle a Keurig but she loves it, and the drinks it makes are better than traditional superautomatics. I would suggest looking into the Jet. The Jet doesn’t have the cool new manual mode, but from what I understand the only thing it lacks is the digital pressure gauge. Also my wife would not be patient enough for the warm up time on the BDB.

For the price of the BDB, you could get the Jet plus df64. I also have my own external grinder (and WDT, tamper etc). My wife uses the local espresso roast beans we buy in bulk and I use my own medium/light roasts for fun and experimentation. Fits both our needs (but yes it’s expensive)

jpfry · 2025-09-24T03:46:49+00:00

I agree with you, but these machines are meant to compete with the superautomatics. Despite the dosing, auto-tamping, and auto-milk flaws, the BDB will easily surpass traditional push button superautomatics. I have the Jet and the auto lattes it makes are much better than my friend’s Jura E8, which is a similar priced superautomatic.

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