Bibliographic record
Abstract
Although humans and microbes are inseparable, our knowledge and understanding of the majority of microbes that help keep us alive and well is in desperate need of further investigation. Of the organisms that influence humans before birth and inhabit various niches from birth to old age, we know little about their identity, origin, metabolic properties, attributes and mechanisms of interactions with the host and surrounding microbes. The use of probiotics ("live microorganisms which when administered in adequate amounts confer a health benefit on the host") has re-emerged as a means to restore and boost the beneficial microbes in our bodies. The timing of resurgent interest in this ancient field coincides with the need to augment or replace antibiotics whose side effects are unwelcome and whose efficacy is diminishing due to drug resistance. Evidence that probiotic strains can act as adjuncts to antibiotic therapy by reducing adverse effects, improving antibiotic function and enhancing mucosal immunity is mounting. It is to our discredit that basic research on microbial ecology has been stalled in Canada for the past 20 years. If supported, research into indigenous and probiotic microbes will form an important part of future research that sheds light on health, disease and a basic understanding of life itself. In some cases, probiotics will be the difference between a good quality of life and a bad one, or perhaps even life over death. Improvements in clinical studies, manufacturing and regulatory standards must coincide with this progress to ensure that physicians and consumers have reliable, proven products for safe and efficacious use.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".