MétaCan
Menu
Back to cohort

The Regularities of Electrolytic Dissociation of Weak Dibasic and Tribasic Organic Wine Acids

2013· article· en· W2034237747 on OpenAlexvenueno aff
Elene Kvaratskhelia, Ramaz Kvaratskhelia, Rusudan Kurtanidze

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDibasic acidChemistryDissociation (chemistry)ElectrolyteWineTartaric acidInorganic chemistryMalic acidDimerCitric acidTartrateOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The weak dibasic and tribasic organic acids in wine: tartaric, malic, citric and succinic acids are the important components having direct influence on various properties of wine. The regularities of electrolytic dissociation of these acids determine all their useful properties. With the aid of suggested by authors original method for analysis the complex equilibria of the processes of dissociation of weak multibasic organic acids the main dissociation parameters of tartaric, malic, citric and succinic acids in their dilute solutions: the values of usual and “partial” degrees of dissociation of all steps, the concentrations of all anions, hydrogen ions and undissociated acid molecules are determined. The concentration intervals of predominance of various charged and uncharged substances in dilute solutions of all above mentioned acids are also determined. The simple empirical equations for fast approximate calculation of the dissociation degrees and pH values are also suggested.

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 score0.158
Threshold uncertainty score0.102

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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Solution Chemistry and ModelingSame topicFermentation and Sensory AnalysisFrench-language works237,207