Bibliographic record
Abstract
Abstract Genetic analysis of bacteriophage and bacteria, particularlyEscherichia coli, was a key to identifying DNA as the genetic material in the middle of the twentieth century, laying the foundations for the modern science of molecular biology in the process. Key experiments have become textbook classics, and most of those who performed them won Nobel Prizes for their work. The techniques that they developed, particularly conjugation and transduction, are still used in bacterial strain construction and for mapping of mutant genes. The advantages of large population size and rapid growth, combined with modern techniques of genome sequencing, the use of green fluorescent protein to measure gene expression and protein localisation, and one‐step strain construction will ensure thatEscherichia coliremains central to answering the big biological questions of the twenty‐first century. Key Concepts Escherichia coliand bacteriophage genetics enabled the identification of DNA as the genetic material in the mid‐twentieth century. Key experiments conducted by Luria and Delbrück; Hershey and Chase; Avery, MacLeod and McCarty are textbook classics. The first step towards understanding how gene expression is controlled came from Jacob and Monod's genetic studies of theEscherichia coli lacoperon. The genetic techniques of sexual conjugation and bacteriophage‐mediated transduction, pioneered by Joshua and Esther Lederberg, were the primary tools for chromosomal gene mapping and strain construction inEscherichia coliuntil recently. Well‐characterised genetics combined with large population numbers and rapid growth ensure thatEscherichia coliwill remain a favourite model organism for scientists tackling the big biological questions of the twenty‐first century.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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".