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
Maintaining a clean water supply is of utmost importance for human civilization. Human activities are putting an increasing strain on Earth's freshwater reserves and on the quality of available water on Earth. To ensure cleanliness and potability of water, sensors are required to monitor various water quality parameters in surface, ground, drinking, process, and waste water. One set of parameters with high importance is the presence of cations. Some cations can play a beneficial role in human biology, and others have detrimental effects. In this review, various lab-based and field-based methods of cation detection are discussed, and the uses of these methods for the monitoring of water are investigated for their selectivity and sensitivity. The cations chosen were barium, cadmium, chromium, copper, hardness (calcium, magnesium), lead, mercury, nickel, silver, uranium, and zinc. The methods investigated range from optical (absorbance/fluorescence) to electrical (potentiometry, voltammetry, chemiresistivity), mechanical (quartz crystal microbalance), and spectrometric (mass spectrometry). Emphasis is placed on recent developments in mobile sensing technologies, including for integration into microfluidics.
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) | 0.001 | 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 | 0.001 |
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