Comparative phylogenetic analysis of microbial communities in pristine and hydrocarbon-contaminated Alpine soils
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
A molecular characterization of pristine and petroleum hydrocarbon-contaminated Alpine soils sampled in Tyrol (Austria) was performed. To identify predominant bacteria, PCR-amplified 16S rRNA gene fragments from five pristine and nine contaminated soils were analysed using denaturing gradient gel electrophoresis (DGGE). Sequencing and phylogenetic analyses demonstrated that the majority of the DGGE bands represented bacteria in the Actinobacteria and Proteobacteria phyla: 18 and 73%, respectively, in pristine soils, compared with 20 and 76%, respectively, in contaminated soils. A different distribution pattern of bacterial classes in the Proteobacteria was observed between pristine and contaminated soils. The relative proportion of microorganisms belonging to the Alphaproteobacteria was larger in pristine (46%) than in contaminated (24%) soils, while Betaproteobacteria and Gammaproteobacteria were detected only in the hydrocarbon-contaminated soils. This result compared favourably with earlier work in which hydrocarbon-degradation genotypes, largely pseudomonads and Acinetobacter, belonging to the Gammaproteobacteria, were enriched following oil hydrocarbon contamination. In contrast, members of the Actinobacteria phylum, represented by Rhodococcus and Mycobacterium, were found in pristine soils where contamination events had not occurred. The results demonstrate a significant shift in the microbial community structure in Alpine soils following contamination. Furthermore, more potentially novel phylotypes were found in the pristine soils than in the contaminated soils.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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