Chromium speciation using large scale plasmas in a lab and towards field deployable speciation by employing a battery-operated microplasma-on-a-chip and optical emission spectrometry
Bibliographic record
Abstract
Chemical speciation is defined as the determination of the concentration of an analyte (e.g., Chromium or Cr) in the oxidation state in which it exists in the environment (e.g., sea water). Determinations of the concentration of different Cr-species is important due to toxicity differences of the different oxidation states of Cr. For example, Cr(III) is regarded as generally non-toxic and is considered as an essential micro-nutrient. But Cr(VI) is considered as carcinogenic. In this paper, speciation methods for Cr in sea water samples using large scale plasmas, such as an ICP (Inductively Coupled Plasma) and steps taken toward using a microplasma are described.
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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 | 0.001 | 0.001 |
| 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 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".