Chempath 1.0: an open-source pathway analysis program for photochemical models
Bibliographic record
Abstract
Abstract. We describe the development of Chempath, an open-source pathway analysis program for photochemical models. This algorithm can help understand the results of complex photochemical models by identifying the most important reaction chains (pathways) for the production and destruction of a species of interest in a reaction system. The algorithm can also quantify the contributions of the pathways to the production and destruction of a species. Chempath is an open-source Python re-implementation of the algorithm developed by Lehmann (2004). However, Chempath does not include the balance of concentration changes and reaction rates that Lehmann's algorithm uses to eliminate imbalances due to numerical errors. Instead, Chempath quantifies the contributions of these imbalances to the production and destruction of a species. We demonstrate how to apply Chempath to both a simple box model and a one-dimensional photochemical model, using a reaction system for Earth's present-day atmosphere. Chempath can identify well-known chemical mechanisms for O3 production and destruction in these models, suggesting that this algorithm can be applied to understand photochemical models of less-well-known atmospheres, like past and exoplanet atmospheres.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".