How the microbiome challenges our concept of self
Bibliographic record
Abstract
Today, the three classical biological explanations of the individual self--the immune system, the brain, the genome--are being challenged by the new field of microbiome research.Evidence shows that our resident microbes orchestrate the adaptive immune system, influence the brain, and contribute more gene functions than our own genome.The realization that humans are not individual, discrete entities but rather the outcome of ever-changing interactions with microorganisms has consequences beyond the biological disciplines.In particular, it calls into question the assumption that distinctive human traits set us apart from all other animals--and therefore also the traditional disciplinary divisions between the arts and the sciences. Challenges to the classical biological explanations of the individual selfAre we humans really the individual, bounded selves we take ourselves to be? Until recently, little seemed more obvious to both the natural and the human sciences.The former found the material basis of the individual human self in the adaptive immune system, the brain, and the genome sequence, and the latter catalogued the many different ways in which humans-across time and space-have learned to make sense of what it means to be an individual self.The discrete self was a philosophical certainty in both the natural and the human sciences.Today, this philosophical certainty--and therefore our sense of self--faces major challenges [1][2][3][4].The source of this challenge is at first sight improbable: the study of microorganisms.It has been known from the inception of microbiology as a discipline in the 19th century (and arguably back to the invention of the microscope by van Leeuwenhoek in the 17th century) that animals, including humans, bear many microorganisms.Until recently, however, these microorganisms were generally treated as either pathogens or as insignificant: the absence of microbes was equated with health.This classical understanding of microbes has been called into question with the recent emergence of low-cost, high-throughput gene
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".