Application of iChip to Grow “Uncultivable” Microorganisms and its Impact on Antibiotic Discovery
Bibliographic record
Abstract
PURPOSE: Antibiotics have revolutionized modern medicine, allowing significant progress in healthcare and improvement in life expectancy. Development of antibiotic resistance by pathogenic bacteria is a natural phenomenon; however, the rate of antibiotic resistance emergence is increasing at an alarming rate, due to indiscriminate use of antibiotics in healthcare, agriculture and even everyday products. Traditionally, antibiotic discovery has been conducted by screening extracts of microorganisms for antimicrobial activity. However, this conventional source has been over-used to such an extent that it poses the risk of "running out" of new antibiotics. Aiming to increase access to a greater diversity of microorganisms, a new cultivation method with an in situ approach called iChip has been designed. The iChip has already isolated many novel organisms, as well as Teixobactin, a novel antibiotic with significant potency against gram-positive bacteria.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".