Bibliographic record
Abstract
Binding energies across all scales — nuclear, electromagnetic, gravitational — represent ongoing thermodynamic maintenance costs against entropy, following from Landauer's principle (E = k_B T ln 2 per bit). Each fundamental force imposes a characteristic "bankruptcy radius" where maintenance equals total energy: QCD confinement at ~1 fm, electromagnetic at the classical electron radius, and gravitational at the Schwarzschild radius. A complexity multiplier M(η,d) = φ^{2^{d-2}} × (1-η)^{-ρ*}, where ρ* = 4πφ²/10 ≈ 3.29 is the coupling constant from constraint geometry, quantifies organizational overhead. White dwarf trajectories toward the Chandrasekhar limit provide empirical test: geometric compression increases by factor 2.2 while organizational complexity explodes by factor 2200, indicating information bankruptcy drives instability. Independent analysis of the Montreal White Dwarf Database (5,519 objects) and Gaia DR3 (7,496 objects) identifies R/R_S ≈ 10³ as a discrete phase transition boundary, with anomaly-zone objects appearing systematically older than matched references (+103 Myr at 3.59σ; +58 Myr at 34.6σ). Type Ia supernova energy equals the Landauer cost of reorganizing phase space information from electron to neutron degeneracy — counting bits (ΔN ≈ 4.5 × 10⁵⁸) at shock temperature (T ~ 10⁹ K) gives E = 4.3 × 10⁴⁴ J, matching observed supernova energies.
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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".