Bibliographic record
Abstract
On April 7 2025, Zeeya Merali wrote an article for the Foundational Questions Institute (https://qspace.fqxi.org/news/165296/gerard-t-hooft-and-13508-lhc-physicists-are-among-this-years-us$3million-breakthrough-prize-winners) which announced a special Breakthrough Prize in fundamental physics was awarded to Nobel laureate Gerard 't Hooft, one of the principal architects of the Standard Model of particle physics. Alongside this, 13,508 physicists at CERN were honored for their collaborative efforts at the Large Hadron Collider, where they’ve rigorously tested the Standard Model. The holographic principle, which states that information within a 3-D region of space can be encoded on its 2-D boundary, also originated with 't Hooft – although today it is not one of his favorite insights. People run away doing mysterious things with it, but they don't really build theories that I can understand," says 't Hooft. He also says - “when someone of the older generation tells you something cannot be done, don't believe them. You have to think harder than those old guys did, and that's always how breakthroughs get done.” I’d like to do my best to “think harder” and write a few brief comments on points mentioned in the article. They’re taken from my article in the science journal “IPI Letters” called “A Different Perspective on Cosmological and Quantum Phenomena That Involves the Temporal Multiverse and the Static Universe” (with some extra thoughts included). (1)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.024 |
| Insufficient payload (model declined to judge) | 0.025 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".