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Record W2498237303 · doi:10.1017/cbo9781139022217.021

Elementary statistical mechanics

2012· other· en· W2498237303 on OpenAlexaff
David H. Boal

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsStatistical mechanicsIdeal gasStatistical physicsThermal fluctuationsEntropy (arrow of time)ObservableThermal physicsBoltzmann constantPhysicsBoltzmann's entropy formulaPartition function (quantum field theory)Classical mechanicsFormalism (music)ThermodynamicsBoltzmann equationQuantum mechanicsNon-equilibrium thermodynamics

Abstract

fetched live from OpenAlex

Soft materials, such as the filaments and membranes of the cell, may be subject to strong thermal fluctuations and sample a diverse configuration space. Each of these accessible configurations, of varying shape and energy, contribute to the ensemble average of an observable such as the mean length of a polymer chain. Statistical mechanics provides a formalism for describing the thermal fluctuations of a system; in this appendix, we review several of its cornerstones – entropy, the Boltzmann factor and the partition function – following a compact approach laid out in Reif (1965). As applications, the thermal fluctuations of a Hooke’s law spring and the entropy of an ideal gas are calculated.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.532
Threshold uncertainty score1.000

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)0.1870.001

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 head0.007
GPT teacher head0.255
Teacher spread0.248 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations23
Published2012
Admission routes1
Has abstractyes

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