Analysis of Bacteria Contaminating Ultrapure Water in Industrial Systems
Bibliographic record
Abstract
Bacterial populations inhabiting ultrapure water (UPW) systems were investigated. The analyzed UPW systems included pilot scale, bench scale, and full size UPW plants employed in the semiconductor and other industries. Bacteria present in the polishing loop of the UPW systems were enumerated by both plate counts and epifluorescence microscopy. Assessment of bacterial presence in UPW by epifluorescence microscopy (cyanotolyl tetrazolium chloride [CTC] and DAPI [4',6'-diamidino-2-phenylindole] staining) showed significantly higher numbers (10 to 100 times more bacterial cells were detected) than that determined by plate counts. A considerable proportion of the bacteria present in UPW (50 to 90%) were cells that did not give a positive signal with CTC stain. Bacteria isolated from the UPW systems were mostly gram negative, and several groups seem to be indigenous for all of the UPW production systems studied. These included Ralstonia pickettii, Bradyrhizobium sp., Pseudomonas saccharophilia, and Stenotrophomonas strains. These bacteria constituted a significant part of the total number of isolated strains (>or=20%). Two sets of primers specific to R. pickettii and Bradyrhizobium sp. were designed and successfully used for the detection of the corresponding bacteria in the concentrated UPW samples. Unexpectedly, nifH gene sequences were found in Bradyrhizobium sp. and some P. saccharophilia strains isolated from UPW. The widespread use of nitrogen gas in UPW plants may be associated with the presence of nitrogen-fixing genes in these bacteria.
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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 | 0.000 | 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) | 0.002 | 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".