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Record W7128304307 · doi:10.5281/zenodo.18529039

Binding Energy, Critical Radii, & Information Maintenance Tax

2025· article· W7128304307 on OpenAlexaboutno aff
Kurtis Kemple

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldPhysics and Astronomy
TopicStatistical Mechanics and Entropy
Canadian institutionsnot available
Fundersnot available
KeywordsSupernovaWhite dwarfBankruptcyChandrasekhar limitGravitationPhase spaceGravitational binding energyDegeneracy (biology)

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.008

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.

Opus teacher head0.015
GPT teacher head0.250
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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