The Gut Microbiome - Implications for Human Disease
Bibliographic record
Abstract
In the last decades, the importance of gut microbiome has been linked to medical research on different diseases. Developments of other medical disciplines (human clinical pharmacology, clinical nutrition and dietetics, everyday medical treatments of antibiotics, changes in nutritional inhabits in different countries) also called attention to study the changes in the gut microbiome. This book contains five excellent review chapters in the field of gut microbiome, written by researchers from the USA, Canada, China, and India. These chapters present a critical review about some clinically important changes in the gut microbiome in the development of some human diseases and therapeutic possibilities (liver disease, cardiovascular diseases, brain diseases, gastrointestinal diseases). The book brings to attention the essential role of gut microbiome in keeping our life healthy. This book is addressed to experts of microbiology, podiatrists, gastroenterologists, internists, nutritional experts, cardiologists, basic and clinical researchers, as well as experts in the field of food industry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".