An automated and high‐throughput method for adenosine triphosphate quantification
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
Abstract Exposure to microbial contamination through drinking water is a major global health concern. Effective management of microbial drinking water quality requires rapid detection equipment. Currently, microbial quality is monitored using time‐consuming laboratory methods, which delay any response. This study demonstrates the development of an automated and high‐throughput method for the measurement of viable biomass in water through the quantification of cellular adenosine triphosphate (ATP). The developed method was able to efficiently and accurately quantify cellular ATP in multiple water samples simultaneously. In addition, it proved to be 5× faster and as accurate as the Standard Test Method for Adenosine Triphosphate (ATP) Content of Microorganisms in Water (ASTM D4012). The developed method has the potential to represent a significant advancement for microbial monitoring and could benefit utilities interested in measuring viable biomass in water to monitor the health of biofilters and the effectiveness of disinfection strategies.
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) | 0.000 | 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 it