Max Haase

By the way this is how the author describes mitosis "At cell division (including when sperm and eggs form), all normal cellular activity halts as the DNA is coiled up tight, inactivated." 🤦

1/8 What bothers me most about this Nature essay is its portrayal of evolutionary biology as a simplistic, gene-obsessed discipline finally being rescued by an appreciation of complexity. It's a compelling narrative, but a poor scientific argument.

7/8 There are excellent reasons to expand evolutionary theory. Developmental bias, niche construction and ecological inheritance raise important questions. But an expanded synthesis should tell us where existing models fail, what new mechanisms matter, and what distinct predictions follow.

1/8 What bothers me most about this Nature essay is its portrayal of evolutionary biology as a simplistic, gene-obsessed discipline finally being rescued by an appreciation of complexity. It's a compelling narrative, but a poor scientific argument.

5/8 The deeper issue is the suggestion that demonstrating biological complexity somehow challenges established evolutionary theory. Of course organisms shape their environments, developmental systems constrain variation, and inheritance can extend beyond DNA.

1/8 What bothers me most about this Nature essay is its portrayal of evolutionary biology as a simplistic, gene-obsessed discipline finally being rescued by an appreciation of complexity. It's a compelling narrative, but a poor scientific argument.

3/8 More troubling is how much scientific history this narrative erases. Quantitative genetics reconciled Mendelian inheritance with continuous traits over a century ago. Development, ecological interactions and environmental influences are hardly recent discoveries in evolutionary biology.

1/8 What bothers me most about this Nature essay is its portrayal of evolutionary biology as a simplistic, gene-obsessed discipline finally being rescued by an appreciation of complexity. It's a compelling narrative, but a poor scientific argument.

I wanted to dig into this institutional concentration a bit deeper, as I think its important to consider what the qed black box is actually learning. I think we should be very skeptical of a for-profit company claiming they have a neutral ranking to uncover exceptional preprints. 1/n

In sum, this analysis shows that qed selections are not institutionally exposure-neutral. Higher-output institutions had a higher per-paper hit rate. 12/n

I wanted to dig into this institutional concentration a bit deeper, as I think its important to consider what the qed black box is actually learning. I think we should be very skeptical of a for-profit company claiming they have a neutral ranking to uncover exceptional preprints. 1/n

Papers carry the fingerprints of the systems that produced them. Scale, polish, methods, dataset size, team size, topic, networks and resources. So a model trained to recognized "important" science may end up being entangled in those fingerprints. 10/n

I wanted to dig into this institutional concentration a bit deeper, as I think its important to consider what the qed black box is actually learning. I think we should be very skeptical of a for-profit company claiming they have a neutral ranking to uncover exceptional preprints. 1/n

Put another way: one-paper institutes: ~1:190 papers are qed 200+ paper institutes: ~1:50 papers are qed That a meaningful difference for something branded "The 1%" 8/n

I wanted to dig into this institutional concentration a bit deeper, as I think its important to consider what the qed black box is actually learning. I think we should be very skeptical of a for-profit company claiming they have a neutral ranking to uncover exceptional preprints. 1/n

So we can normalize the data to get a hit rate per paper and stratify the data by institutional size (number of bioRxiv papers posted). If the qed blackbox has no institutional bias we would expect the hit rate per paper to be ~1% across institutional size. 6/n

I wanted to dig into this institutional concentration a bit deeper, as I think its important to consider what the qed black box is actually learning. I think we should be very skeptical of a for-profit company claiming they have a neutral ranking to uncover exceptional preprints. 1/n

If we quantify this, using an HHI-style metric, we can score how institutionally concentrated the qed list is: qed papers: ~0.012 matched controls: ~0.0021, So qed papers are about 5.5x more concentrated than the controls. 4/n

I wanted to dig into this institutional concentration a bit deeper, as I think its important to consider what the qed black box is actually learning. I think we should be very skeptical of a for-profit company claiming they have a neutral ranking to uncover exceptional preprints. 1/n

The thing I wanted to know is the qed list spread out over the scientific landscape or is it really concentrated as Ran preliminary efforts suggest. I compared the qed list to matched bioRxiv controls (preprints posted from May 2025 and April 2026) 2/n