Bibliographic record
Abstract
Abstract. We describe a new FORTRAN 90 computer program to solve the system of equations for the NH4+–Na+–Ca2+–K+–Mg2+–SO42––NO3––Cl– system, based on the algorithms of ISORROPIA II, but containing algorithm improvements and corrections. These allow the code to deliver more accurate solution results in formal evaluations of accuracy of the roots of the systems of equations, while reducing processing time in practical applications by about 50 %. The improved solution performance results from several implementation improvements relative to the original ISORROPIA algorithms. These improvements include (i) the use of the ‘interpolate, truncate and project’ (ITP) root–finding approach rather than bisection, (ii) the allowance of search interval endpoints as valid roots at the onset of a search, (iii) the use of a more accurate method to solve polynomial subsystems of equations, (iv) the elimination of negative concentrations during iterative solutions, (v) corrections for mass conservation enforcement, and (vi) several code structure improvements. The new code may be run in either a “vectorization” mode wherein a global convergence criterion is used across multiple tests within the same chemical subspace, or a “by gridpoint” mode wherein individual test cases are solved with the same convergence criteria. The latter approach was found to be more efficient on the compiler tested here, but users of the code are recommended to test both options on their own systems. We also note that implementation of inorganic chemistry within chemical transport models should take care to retain residual or “free” mass of aerosol species remaining after partitioning, to ensure mass conservation – the new code has been constructed to explicitly conserve the input mass. The new code is provided as open–source FORTRAN 90 shareware.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.023 | 0.014 |
| Insufficient payload (model declined to judge) | 0.213 | 0.216 |
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".