Quantification of Metals and Semimetals in Carbon‐Rich Rocks: A New Sequential Protocol Including Extraction from Humic Substances
Bibliographic record
Abstract
We have developed a new sequential extraction technique that does not require complex procedures and is efficient in determining metal and semimetal contents of carbon‐rich rocks. Six geological reference materials ( SBC ‐1, SCHS ‐1, SC o‐1, SDO ‐1, SGR ‐1b and SL g‐1) and an in‐house black shale ( SH ‐1) were selected to test the method, which consists of four main digestion steps involving: (a) dilute HC l acid; (b) Na OH ; (c) aqua regia; and (d) hydrofluoric acid. Compared with traditional aqua regia + hydrofluoric acid attack, this new protocol recovers more of the moderately volatile elements during early extraction of humic substances. In addition when compared with reference values, those for most elements are in agreement within uncertainty. Furthermore, this new protocol reveals important information on the partitioning of elements; for instance, steps one and two indicate which elements are associated with carbonates and organic phases from fulvic and humic acid extractions, whereas step three provides results for which elements are associated with sulfide minerals and step four indicates which elements remained in the silicate and oxide phases.
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 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".