Advanced imaging techniques for assessment of structure, composition and function in biofilm systems
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
Scientific imaging represents an important and accepted research tool for the analysis and understanding of complex natural systems. Apart from traditional microscopic techniques such as light and electron microscopy, new advanced techniques have been established including laser scanning microscopy (LSM), magnetic resonance imaging (MRI) and scanning transmission X-ray microscopy (STXM). These new techniques allow in situ analysis of the structure, composition, processes and dynamics of microbial communities. The three techniques open up quantitative analytical imaging possibilities that were, until a few years ago, impossible. The microscopic techniques represent powerful tools for examination of mixed environmental microbial communities usually encountered in the form of aggregates and films. As a consequence, LSM, MRI and STXM are being used in order to study complex microbial biofilm systems. This mini review provides a short outline of the more recent applications with the intention to stimulate new research and imaging approaches in microbiology.
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 | 0.001 | 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