Data Visualization for the Characterization of Naphthenic Acids within Petroleum Samples
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fourier transform ion cyclotron resonance mass spectrometry has made a significant contribution to the characterization of naphthenic acids in petroleum samples. The characterization of naphthenic acids is of particular interest due to their believed involvement in corrosion and deposit formation, as well as their toxicity toward aquatic organisms. Analysis of a complex mixture, such as a petroleum sample, can present challenges in terms of data analysis and visualization. A variety of graphical methods for representing the data are evaluated, and the use of a heat map, a method primarily used within molecular biology, is highlighted. An Athabasca oil sands sample was characterized and compounds of the empirical formula C n H 2 n + z O x, where x = 2−5, were observed. The range of oxygen content is of particular relevance in light of other research, which has shown that the total acid number of a petroleum sample is not a reliable method for evaluating the acid content, as not all of the acids are monoprotic.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it