Bibliographic record
Abstract
Abstract Chemical reactions show a separation of time scales in transient decay due to the stiffness of the ordinary differential equations (ODEs) that describe their evolution. This evolution can be represented as motion in the phase space spanned by the concentration variables of the chemical reaction. Transient decay corresponds to a collapse of the “compressible fluid” representing the continuum of possible dynamical states of the system. Collapse occurs sequentially through a hierarchy of nested, attracting, slow invariant manifolds (SIMs), i.e., sets that map into themselves under the action of the phase flow, eventually reaching the asymptotic attractor of the system. Using a symbolic manipulative language, explicit formulas for the SIMs can be found by iterating functional equations obtained from the system's ODEs. Iteration converges geometrically fast to a SIM at large concentrations and, if necessary, can be stabilized at small concentrations. Three different chemical models are examined in order to show how finding the SIM for a model depends on its underlying dynamics. For every model the iterative method provides a global SIM formula; however, formal series expansions for the SIM diverge in some models. Repelling SIMs can be also found by iterative methods because of the invariance of trajectory geometry under time reversal. © 2005 Wiley Periodicals, Inc. Int J Quantum Chem, 2006
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".