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Record W4389153506 · doi:10.1101/2023.11.28.569100

Onsager's relations and Ecology

2023· preprint· en· W4389153506 on OpenAlexaff
Jae S. Choi, Roger I. C. Hansell

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsBedford Institute of Oceanography
Fundersnot available
KeywordsAmbiguityReciprocalEntropy (arrow of time)Onsager reciprocal relationsStatistical physicsRepresentation (politics)Context (archaeology)EcologyTheoretical physicsEpistemologyComputer sciencePhysicsClassical mechanicsGeographyThermodynamicsBiology

Abstract

fetched live from OpenAlex

There are two complementary approaches to thermodynamics: an empirical, phenomenological representation of macroscopic states and a model-based, statistical-mechanical representation of microscopic states. If only a few energy transformation steps are involved, macroscopic quantities such as energy and entropy can be estimated without ambiguity, and often the associated microscopic states are well characterised. Both approaches have been used to develop and guide many key early ecological ideas. However, most ecosystems are characterized by uncountably many transformations that operate on a wide range of space and time scales. This renders the bounds of such systems ambiguous making both the macroscopic and microscopic approaches a challenge. As such, the implementation of both approaches remain areas ripe for further investigation. In particular, the Onsager reciprocal relations permit simplification of expectations that are yet to be fully understood in an ecological context. Here we begin to take a few first steps in trying to understand the far-reaching ramifications of these thermodynamic relations.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.230
Teacher spread0.218 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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