MétaCan
Menu
Back to cohort

New Conditions of Saturation of Aqueous Solutions for the Modeling of Regions of Solid Phases

2015· article· en· W2239571370 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2015
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSolubilityAqueous solutionSaturation (graph theory)ChemistryPrecipitationSolubility equilibriumThermogravimetryThermodynamicsInorganic chemistryPhysical chemistryMeteorologyMathematicsPhysics

Abstract

fetched live from OpenAlex

In modeling the regions of precipitation and formation of thin films, we used four conditions: 1. The rule of solubility product; 2. The rule of molecular solubility; 3. The rule of solubility by intermediate; 4. Condition of precipitate of priority. This technique was used to build mathematical models of equilibriums from the pH of solution, concentration of reactants, and temperature. Mathematical models were also developed on the basis of experimental data obtained by potentiometry, residual concentration, thermogravimetry, etc. This model considers fluctuations of the pH of solution and predicts the chemical composition of compounds. It has been demonstrated that in synthesizing target compounds, the possibility of processes of fluctuations must be taken into account. A systemic mathematical model has been designed to optimize the synthesis of thin films and target compounds.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.274

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 head0.056
GPT teacher head0.283
Teacher spread0.227 · 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