Bibliographic record
Abstract
Abstract While trivalent chromium (Cr(III)) is an essential nutrient, hexavalent chromium (Cr(VI)) is a human carcinogen and genotoxic. In evaluation of the toxicological risks and environmental impacts, the separate analysis of Cr(III) and Cr(VI) in water samples provides more information than the analysis of total Cr. The relatively high instability of the Cr species in natural water samples further complicates the analysis, requiring preservation or other advanced procedures. This article is intended to present the broad range of available separation methods for Cr analysis, discussing the possible interferences, detection limits, and preserving options. The intense color complex formed between dichromate ions and 1,5‐diphenylcarbazide (DPC) is used for Cr(VI) measurement in spectrophotometric, flow injection analysis (FIA), ion chromatography (IC), liquid chromatography (LC), capillary electrophoresis (CE), and electrochemical methods. Atomic spectrometry, molecular spectrometry, and other methods are also discussed. An absolute analysis with accurate measurement of Cr(VI) at the time of sample collection can be achieved with speciated isotope dilution mass spectrometry (SIDMS) by using LC separation coupled to the inductively coupled plasma mass spectrometry (ICP‐MS) or IC separation coupled to electrospray ionization tandem mass spectrometry (ESI‐MS/MS).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".