Development and application of a fatty acid based microbial community structure similarity index
Bibliographic record
Abstract
Abstract This article presents an index of similarity that has application in monitoring relative changes of complex microbial communities for the purpose of understanding the impact of community instability in biological wastewater treatment systems. Gas chromatographic data quantifying microbial fatty acid esters extracted from biosolids samples can be used to infer the occurrence of changes in mixed culture community structure. One approach to rapidly assess the relative dissimilarity between samples is to calculate a similarity index scaled between 0 and 1. The many arbitrary scales that are associated with the available calculation methods for similarity indices limits the extent of application. Therefore, a specialized index of similarity was derived from consideration of the measurement errors associated with the chromatographic data. The resultant calculation method provides a clear mechanism for calibrating the sensitivity of the similarity index, such that inherent measurement variability is accommodated and standardization of scaling is achieved. The similarity index sensitivity was calibrated with respect to an effective gas chromatographic peak coefficient of variation, and this calibration was particularly important for facilitating comparisons made between different systems or experiments. The proposed index of similarity was tested with data acquired from a recently completed study of contaminant removal from pulp mill wastewater. The results suggest that this index can be used as a screening tool to rapidly process microbial fatty acid (MFA) compositional data, with the objective of making preliminary identification of underlying trends in (MFA) community structure, over time or between experimental conditions. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".