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Record W2324611266 · doi:10.1139/v11-154

The expected time to attain chemical equilibrium from a thermodynamic probabilistic analysis

2012· article· en· W2324611266 on OpenAlexvenueno aff
Christopher Pastore, Moishe Garfinkle

Bibliographic record

VenueCanadian Journal of Chemistry · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryChemical reactionProbabilistic logicChain reactionStatistical physicsChemical equilibriumStoichiometryThermodynamicsReaction mechanismChain (unit)Computational chemistryPhysical chemistryPhysicsMathematicsCatalysisQuantum mechanicsStatisticsOrganic chemistry

Abstract

fetched live from OpenAlex

Employing a stochastic model, both Planck and Fokker proposed almost a century ago that stoichiometric chemical reactions proceed by a chain mechanism involving discrete reaction steps. To determine whether such a chain mechanism was in fact a valid mechanism for chemical reactions was the subject of a recent study (Garfinkle, M. 2002. J. Phys. Chem. 106A: 490). Using a thermodynamic–probabilistic algorithm the stochastic reaction paths were found to be in excellent agreement with the observed reaction paths plotted from experimental data. This study was then extended to test the conclusions of Ehrenfest and Prigogine that a chain mechanism dictates that the number of discrete reaction steps required for a chemical reaction to attain equilibrium must be finite. The stochastic and empirical reaction paths were compared using experimental data for first-, second-, and third-order reactions as well as fractional order reactions. The empirical verification was excellent.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.212
Teacher spread0.207 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

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