Life aquatic: the amazing self-purifying properties of the Ganges River.
Bibliographic record
Abstract
The Ganges is India’s holiest and most revered river. Often referred to as “Mother Ganges”, this river originates from the Gangotri glacier in the Himalayas, and provides a lifeline for the millions of people living along its banks, before emptying into the Bay of Bengal. Today, the river is among the world’s most polluted, filled with untreated sewage, industrial waste and pesticides. Amazingly, in spite of the pressures posed by modern India, the Ganges River supports a surprising amount of biodiversity thanks to its remarkable self–purifying and regeneration properties. Studies from as far back as 1896 have shown the unique antimicrobial properties of the Ganges against Vibrio cholera–the causative agent of cholera–which died within 3 hours in Ganges water, but persisted for 48 hours in distilled water. French scientist Félix d’Herelle later attributed this mystic characteristic to the action of bacteriophages–bacteria killing viruses. Besides just being fascinating science, bacteriophages may hold important implications in modern medicine. We live in an era where antibiotic resistance could become a global crisis, owing to the liberal and widespread use of antibiotics. Studies have shown that bacteriophages can be modified to target specific bacteria and provide long-lasting treatment for a vast array of infections. Scientists are now hopeful that the Ganges might provide clues for the design and synthesis of a new class of antimicrobial drugs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".