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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".