I'm not sure if this is it, but assuming the correctness of the test is independent of the sample quality, a sample could be split and tested multiple times to obtain a result with a much better FPR.
I think this might be a bit premature. For the bulk of these tools (pandas/numpy/tensorflow/torch), most of their users have probably been using them for 3-5 years max.
A universal API standard is a nice idea, but I don't know that the ecosystem has been around long enough to justify this effort.
Given the asynchronous nature of consortiums though, maybe this exactly the right time to start talking about this.
Without some form of compression, I don't think it is.
In particular, consider your example (5 horcruxes with 3 needed to reconstruct). View the original file as the interval (0, N) and view it as a set covering problem. If each horcrux covers an interval of size N/3, then if any pair overlaps, there is no third horcrux that can complete the covering. This is a contradiction because 5 horcruxes of size N/3 must overlap somewhere.
Surely you mean the number of publications, or some other superficial metric (e.g. being the third "supervising" author on a paper with a dozen authors).
If I read a paper and have a great appreciation for the ideas, and have a sense that an author contributed significantly to the aspects I appreciate (either from explicit descriptions of the authors' contributions in the publication, or by speaking to them), why would that not be impressive to me?
> * Public access to research results, methods, and data, with some exceptions (such as PII)
You mentioned PII, so I'm assuming some familiarity with the health field. I'm curious about your thoughts on the position that one should not be required to immediately publicize their data, because there needs to be an expectation that a researcher can translate the capital (both time and money) they expend to acquire quality data into academic and institutional capital (in the form of research output, i.e. papers). The fear being, there might be insufficient motivation to conduct large data collection-oriented studies due to another researcher beating the data collector to the punch in terms of publishing certain findings.
That's an interesting idea that could stop very specific types of fraud, certainly in the life sciences. But it's not feasible for all kinds of research, and in fact could hinder lots of research.
> All papers would be required to be made public.
This is more universally feasible. Publicizing the data and analysis tools (scripts, software) falls into the same category, and would go a long way to help without the need for such strong separation.
I'm not saying the policy is worthwhile or even justifiable, but the comment I replied to later used the word "treason" (sorry, I didn't quote it) which implies that these actions aren't endorsed, and certainly not encouraged, by the US government.
Not to be over-speculative, but I think OP is probably referring to the rebound effects of corticosteroids which have been documented recently as related to skin conditions [1].
So cool. In my opinion, so many of the open problems in biology can be approached from the direction of specificity - from specificity in measurement to specificity in targeting interventions. For example, tools like this for elucidating cognition; alternatively, cancer (identifying and targeting problematic cells).
Gain-of-function literally only means the protein has, in some sense, gotten better at its "job" (or has taken on an additional "job"). In this case, the "job" of the protein is to infect organisms more effectively.
Some background: viruses primarily contain the genetic material and a protein coat. The Spike (S) protein is one of the proteins in the coat, and plays a role in whether an infection will take root.
From the paper:
> we identified a peculiar furin-like cleavage site in the Spike protein of the 2019-nCoV, lacking in the other SARS-like CoVs
Furin is a protease that is present in healthy humans. Some proteins aren't "active" until they're cut (cleaved) at specific sites along their sequence, so furin's "job" is to cleave these proteins - activating them. Notably, furin is highly expressed in the lungs.
2019-nCoV apparently has a "furin-like site" in its Spike protein - a sequence that furin can bind to and cleave. Notably, furin is the protease that cleaves one of the proteins in the protein coat of HIV, which then allows for viral replication [1]. The authors therefore hypothesize that this mutation which creates the furin-like cleavage site accounts for some of the pathogenicity of 2019-nCoV. They further hypothesize that furin inhibitors may be effective agents in combating the virus (which have shown some promise in combating other viruses, tumours, etc.).
Disclaimer: not a virologist, just a computational biologist with a bit of interest in structural biology. Also, the authors emphasize that further experimentation needs to be done to validate this claim.
Source? Everything I've read suggests that crime rates are pretty much the same across race and ethnicity when controlling for economic status. The primary variable is contact with the justice system, i.e. getting caught.
Okay, as a layman, can you clarify a scenario where (even huge-scale) money laundering would pose a similar threat to the stability of the Icelandic banking system as the misbehaviour of banks on an international level leading up to 2008?