Quantification of a single population in a mixed microbial community using a laser integrated microarray scanner
Bibliographic record
Abstract
A laser integrated microarray scanner was used to quantify and compare the biomass of Burkholderia cepacia G4 alone, mixed with Afipia sp., and mixed with a trichloroethylene and phenol degrading community. Samples containing B. cepacia G4 were placed in 3-mm diameter wells on gelatin coated glass slides then fixed and immunofluorescently labeled using an IgG conjugate with an attached AlexaTM 546 fluorophore. Linearity and sensitivity of the scanner for biomass quantification were established, and a lower detection limit of 25 mg L1 (103104 cells mL1) was calculated. Growth of B. cepacia G4 alone and in the presence of the TCE degrading community was measured using the scanner. Results suggest that the microarray scanner can be used to quantify the biomass of a single population in a dense mixed microbial community. Key words: biomass, Burkholderia cepacia G4, fluorescent antibody, microarray scanner, mixed community.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".