Chaotic characterization of macromixing effect in a gas–liquid stirring system using modified 0–1 test
Bibliographic record
Abstract
Abstract A new approach to extract the chaotic characteristics of the two‐phase stirring and mixing state is proposed for bottom‐blown oxygen‐enriched bath smelting process of copper. By quantifying the local mixing characteristics in the stirred reactor of bottom‐blowing copper smelting, an improved 0–1 chaotic test method was introduced to measure the chaotic characteristics of a time series of mixing index. It was found that the different channels of the RGB image of turbulence flow field are not the same for the contour feature extraction of the bubble; the single‐channel horizontal profile of the single‐ and double‐distributor flow field images shows single and double peaks, respectively, verifying the accuracy of the hybrid characterization. After calculating the mean and standard deviation time series of grey intensity of the region of interest, the median of the asymptotic growth rate K corr ( c ) of the mixing index time series was used as the criteria of chaos detection in the molten pool dynamic balance state. The variability of chaos in different mixing processes has been more accurately characterized.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".