A kinetic model for hydroconversion processing of vacuum residue
Why this work is in the frame
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Bibliographic record
Abstract
Hydroconversion is a complex process involving many chemical reactions. Mathematical models of hydroconversion processes often have more kinetic parameters than can be estimated from data. In this work the identifiability and estimability of parameters in a model describing the hydroconversion processing of vacuum residue are analyzed. The model under consideration contains five states, two outputs, and seven parameters. This lumped model was developed by grouping molecules based on their solubility characteristics. The model parameters were found to be identifiable. However, using previously published experimental data, the model parameters were found to be inestimable. It is shown that the model can be reparameterized using a linear transformation in the parameter space. This transformation allows the model outputs to be predicted based on only three pseudo-parameters. Confidence intervals for the three pseudo-parameters and the mean responses were calculated.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it