Replication Data for: Aqueous-phase Direct Photolysis of Phenolic Compounds - the Formation of Dimers and Their Contributions to Atmospheric Brown Carbon
Bibliographic record
Abstract
This dataset contains the experimental, analytical, and visualization-ready data associated with the study “Aqueous-phase Direct Photolysis of Phenolic Compounds - the Formation of Dimers and Their Contributions to Atmospheric Brown Carbon”. The dataset includes the complete numerical data used to generate all figures in both the main manuscript and the Supplementary Information. Methods Overview: Photolysis experiments were conducted in aqueous solution under controlled UVA/UVB irradiation. Mass spectrometric analyses were performed using Thermo Orbitrap and Waters QTOF instruments, and LC–MS data were processed using Thermo FreeStyle. UV–Vis absorption measurements were obtained using a diode-array spectrophotometer. Full experimental and analytical details are provided in the associated manuscript. Purpose: This dataset is provided to support transparency, reproducibility, and reuse of the results presented in the manuscript. The files enable independent regeneration of all figures, quantitative analyses, and data visualizations associated with the study.
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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.191 | 0.128 |
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".