Bibliographic record
Abstract
Water is fundamental to most aspects of human civilization and terrestrial life in general. The problem of deteriorating water quality is very real, but often hard to quantify for lack of data. Hence the development of water quality sensors has become an urgently important area of research. Here we summarize an emerging class of water quality sensors based on field effect or chemiresistive geometries, which work completely in the solid state and can operate without reference electrodes. Such devices are candidates for continuous online monitoring applications of surface, ground, drinking, process, and wastewater streams. Single layer and few layer graphenes are suitable materials for the sensing channels in these devices due to their chemical and mechanical robustness and favorable electronic properties. While single layer graphene devices are more sensitive, few layer graphene sensors are easier to manufacture at a lower cost and offer a wider dynamic range. Detection of pH, disinfectants, mercury, lead, chromium, arsenic, potassium, calcium, some anions, as well as organic and biological species has all been demonstrated at the proof of concept stage, with much more work in progress. One can anticipate the commercial availability of such devices in the near future.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".