MétaCan
Menu
Back to cohort
Record W4411402925 · doi:10.5539/ijc.v17n2p36

Chemical Formula-based Method for Balancing Organic Combustion and Quantifying Redox Parameters

2025· article· en· W4411402925 on OpenAlexvenueno aff
Pong Kau Yuen, Cheng Man Diana Lau

Bibliographic record

VenueInternational Journal of Chemistry · 2025
Typearticle
Languageen
FieldMaterials Science
TopicThermal and Kinetic Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCombustionChemistryRedoxChemical equationOrganic matterStoichiometryOrganic compoundThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

Organic combustion is a classic redox reaction. In the study of stoichiometric organic combustion, structural formula has been given little attention when compared to empirical formula. This article uses the arithmetic method to develop a chemical formula-based molecular organic combustion equation, in which the mean oxidation number of organic carbons is selected to be a redox and structural metric for differentiating empirical formula and structural formula, connecting redox parameters, and balancing organic combustion equations. When any empirical formula of organic matter is given, the organic combustion equation can be balanced and deduced. Furthermore, when known atomic coefficients of an empirical formula are input into the general deduced organic combustion equation, the balanced organic combustion can be easily determined. Comparatively, when any structural formula is given, it must undergo the fragmentation method to have the designated products identified and then the arithmetic method can be applied to balance the organic combustion equation. More importantly, this study establishes that for any given chemical formula of organic matter, the parameters of organic matter, the redox parameters of organic combustion, and the balanced organic combustion equation can be determined.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.251

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)0.0000.000

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 head0.014
GPT teacher head0.310
Teacher spread0.296 · 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.

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of ChemistrySame topicThermal and Kinetic AnalysisFrench-language works237,207