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Record W1980940512 · doi:10.1103/physreva.63.022509

Shannon entropies and logarithmic mean excitation energies from cusp- and asymptotic-constrained model densities

2001· article· en· W1980940512 on OpenAlexfundno aff
Robin P. Sagar, Juan Carlos Ramírez Rodríguez, Rodolfo O. Esquivel, Minhhuy Hô, Vedene H. Smith

Bibliographic record

VenuePhysical Review A · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsPhysicsJoint quantum entropyEntropy (arrow of time)Statistical physicsConfiguration entropyLogarithmMaximum entropy probability distributionPosition and momentum spaceMaximum entropy thermodynamicsMathematical physicsQuantum mechanicsMathematical analysisPrinciple of maximum entropyStatisticsMathematicsQuantum

Abstract

fetched live from OpenAlex

A model correctly describing the asymptotic behavior of the charge density is used to derive an expression for the Shannon entropy in terms of the ionization potential of the system. A strong similarity is observed between this model entropy and the entropy obtained from correlated wave functions providing evidence that it is the asymptotic regions that are responsible for the behavior of the entropy. We also show via a model entropy that the behavior of the momentum space Shannon entropy is due to a correct description of the cusp behavior at the nucleus. The changes in the position and momentum space entropies as a function of a parameter are shown to be linearly related for these models. The expression for the entropy, derived from a density model that obeys the asymptotic behavior, is shown to be almost identical in nature to the general expression for entropy emanating in the stopping power formalism.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.278
Teacher spread0.266 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations29
Published2001
Admission routes1
Has abstractyes

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Same venuePhysical Review ASame topicSpectroscopy and Quantum Chemical StudiesFrench-language works237,207