Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neutron stars are astrophysical laboratories of many extremes of physics. Their rich phenomenology provides insights into the state and composition of matter at densities which cannot be reached in terrestrial experiments. Since the core of a mature neutron star is expected to be dominated by superfluid and superconducting components, observations also probe the dynamics of large-scale quantum condensates. The testing and understanding of the relevant theory tend to focus on the interface between the astrophysics phenomenology and nuclear physics. The connections with low-temperature experiments tend to be ignored. However, there has been dramatic progress in understanding laboratory condensates (from the different phases of superfluid helium to the entire range of superconductors and cold atom condensates). In this review, we provide an overview of these developments, compare and contrast the mathematical descriptions of laboratory condensates and neutron stars and summarize the current experimental state-of-the-art. This discussion suggests novel ways that we may make progress in understanding neutron star physics using low-temperature laboratory experiments.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it