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Record W4400100926 · doi:10.5539/ijc.v16n2p42

Counting and Demonstrating Electron Transfer in Buswell’s Equation

2024· article· en· W4400100926 on OpenAlexvenueno aff
Pong Kau Yuen, Cheng Man Diana Lau

Bibliographic record

VenueInternational Journal of Chemistry · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryElectron transferPhotochemistry

Abstract

fetched live from OpenAlex

Anaerobic digestion is a microorganism-mediated redox system which is chemically represented by Buswell’s equation. In the equation, quantity of methane and carbon dioxide can be counted by the elemental composition of organic matter, however there is a lack of connection between electron transfer and formations of methane and carbon dioxide. Although the mechanism of direct interspecies and mediated interspecies electron transfer in anaerobic digestion has been widely researched, the method of counting electron transfer in Buswell’s equation has not yet been explored. This article develops a method to count electron transfer of organic molecules in Buswell’s equation. Mathematical equations are established through integration of relationships among mean oxidation number of organic carbons, quantity of methane, and number of transferred electrons. With any known organic structural formula, three tasks can be achieved: (1) determine the Buswell-Ratio, (2) count Buswell-Electron, and (3) demonstrate electron transfer among organic carbons by drawing the Buswell-Electron diagram.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.272
Teacher spread0.264 · 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 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
Published2024
Admission routes1
Has abstractyes

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