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Record W1996210969 · doi:10.1021/jp1029745

How Ambiguous Is the Local Kinetic Energy?<sup>†</sup>

2010· article· en· W1996210969 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2010
Typearticle
Languageen
FieldMaterials Science
TopicMachine Learning in Materials Science
Canadian institutionsMcMaster University
Fundersnot available
KeywordsKinetic energyExpansiveCauchy stress tensorTensor (intrinsic definition)Virial theoremStatistical physicsAmbiguityStress (linguistics)Energy (signal processing)PhysicsClassical mechanicsMathematicsThermodynamicsQuantum mechanicsPure mathematicsComputer science

Abstract

fetched live from OpenAlex

The local kinetic energy and the closely related local electronic stress tensor are commonly used to elucidate chemical bonding patterns, especially for covalent bonds. We use three different approaches-transformation properties of the stress tensor, quasiprobability distributions, and the virial theorem from density-functional theory-to clarify the inherent ambiguity in these quantities, discussing the implications for analyses based on the local kinetic energy and stress tensor. An expansive-but not universal-family of local kinetic energy forms that includes the most common choices and is suitable for both chemical-bonding and atoms-in-molecule analysis is derived. A family of local electronic stress tensors is also derived. Several local kinetic energy functions that are mathematically justified, but unlikely to be conceptually useful, are derived. The implications of these forms for atoms-in-molecule analysis are discussed.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.226
Teacher spread0.221 · 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