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Record W3038805302 · doi:10.5539/ijc.v12n2p1

An Irreversible Heat Engine Working at the Reversible Efficiency

2020· article· en· W3038805302 on OpenAlexvenueno aff
José Iñiguez

Bibliographic record

VenueInternational Journal of Chemistry · 2020
Typearticle
Languageen
FieldChemistry
TopicChemical Thermodynamics and Molecular Structure
Canadian institutionsnot available
Fundersnot available
KeywordsHeat engineWork (physics)ChemistryThermodynamic cycleSimple (philosophy)ThermodynamicsProcess engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

The thermodynamic analysis of the coupling of one cycle in the operation of a reversible heat engine with a work-degrading step in which the whole of the engine’s work output is frictionally degraded into heat at the temperature of its cold reservoir, allows identification of the fact that the engine’s reversibility is dependent on the continued availability of its work output. As long as this work remains available the engine will be reversible, this on reason of the fact that the initial condition can be restored via the simple expedient of using the said work to propel the inverse cycle. The moment this work becomes, for whatever reason, unavailable, restoration of the engine’s initial condition becomes impossible, and what was a reversible engine becomes irreversible. The inability of current thermodynamic terminology to deal with this situation is brought to light and a simple suggestion aimed at correcting this deficiency is advanced.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.234
Teacher spread0.225 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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