<scp>AI</scp> models for correlation of physical properties in system of <scp>1DMA2P‐CO<sub>2</sub>‐H<sub>2</sub>O</scp>
Bibliographic record
Abstract
Abstract In this work, the density, viscosity, and specific heat capacity of pure 1‐dimethylamino‐2‐propanol (1DMA2P) as well as aqueous unloaded and CO2‐loaded 1DMA2P solution (with a CO2 loading of 0.04–0.70 mol CO2/mol amine) were measured over the 1DMA2P concentration range of 0.5–3.0 mol/L and temperature range of 293–323 K. The observed experimental results of these thermophysical properties of the 1DMA2P‐H2O‐CO2 system were correlated using empirical models as well as artificial neural network (ANN) models (namely, back‐propagation neural network [BPNN] and radial basis function neural network [RBFNN] models). It was found that the developed BPNN and RBFNN models could predict the experimental results of 1DMA2P‐H2O‐CO2 better than correlations using empirical models. The results could be treated as one of the accurate and potential methods to predict the physical properties for aqueous amine CO2 absorption systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".