Bibliographic record
Abstract
A modified version of the two-parameter Weibull survival curve is used to investigate its applicability to analyze the influence of the Fenton's Reagent on the decomposition of 2,4-dinitrophenol solutions (DNP). Fenton's Reagent is one type of advanced oxidation processes (AOPs) in which strong oxidants, hydroxyl radicals, are generated. Fenton's Reagent was maintained at a ratio of 0.5 mM H2O2 to 0.1 mM Fe2+ at the start of all experiments. By varying the initial DNP concentration, we are not only able to correlate parameters (a) and (b) defined in the modified curve to the Fenton's oxidation process, but also interpret their physical significance on the process. The scale parameter (a) can be used to illustrate the rate of the decomposition of DNP in solutions. The imbalance between decomposition rate and initial DNP concentration can be easily observed with the aid of parameter (a). By defining a specific decomposition rate function, the shape parameter (b) indicates the strength of the oxidation power provided by the Fenton's Reagent. When (b) > 1, the existence of a maximum specific decomposition rate shows a sufficient supply of the hydroxyl radicals, whereas a first-order decomposition of DNP is obtained when (b) = 1. A lack of oxidation power becomes obvious if (b) < 1, showing a high dose of initial DNP in a solution. Knowing the physical interpretation of both parameters, they are further applied to design the Fenton's oxidation process.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".