Bibliographic record
Abstract
The equations for pair distribution functions are used to derive the multimoment hydrodynamics equations for gas mixture. The gas mixture pair distribution functions are specified. The equations for pair functions are derived directly from the general statistical mechanics concepts. The basic property of the pair functions is established. In conformity with basic property, these functions remain unchanged in time along the trajectory of the center of inertia of a pair. The basic property of the pair distribution functions reveals the existence of an infinite number of principle hydrodynamic values. Multimoment hydrodynamics equations are constructed using 3L+4 principle hydrodynamic values, where is the number of gas mixture components. Just these principle values specify measurable moments. The measurable moments are represented by linear combination of principle and non-principle hydrodynamic values. The general structure of constructed multimoment conservation laws is identical to the structure of appropriate multimoment conservation laws in a gas of identical particles. Each of the multimoment conservation laws is divided into two separate equations. The first group of conservation equations corresponds to convective phenomena. The second group of conservation equations corresponds to dissipative phenomena. Derived multimoment hydrodynamics equations are designed for interpreting the behavior of unstable systems. As is shown previously, classic hydrodynamics equations are incapable of reproducing flows after they lose stability. That is, the solutions to the classic hydrodynamics equations do not find the direction of instability development correctly. The possibility of improvement of classic hydrodynamics equations for a gas mixture is sought on the way toward an increase in the number of principle hydrodynamic values.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".