Metagenomic Analysis of Freshwater Bacterial and Viral Biodiversity Using Shotgun Sequencing
Bibliographic record
Abstract
The metagenomic analysis is used to investigate complex microbial communities directly from the environment, without culturing or isolating organisms. It is used to identify taxonomic diversity and functional metagenomics. Shotgun metagenomic sequencing is an environmental sequencing approach that can examine thousands of organisms simultaneously and comprehensively for community function and biodiversity. It also detects the low abundance members of microbial communities. It is advantageous over 16S sequencing as it has the cross-domain coverage, greater taxonomy resolution, and functional profiling. Several studies have been carried out using the shotgun sequencing metagenomic analysis to explore the freshwater diversity especially bacterial and viral diversity in different regions. Freshwater metagenomic analysis shows the presence of unknown single-stranded DNA in arctic freshwater, an abundance of actinobacterial in Japan lakes, Virophage and Mimiviridae community in Canadian freshwater. Metagenomic analysis of Himalayan freshwater lake was conducted using non-chimeric sequence.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".