A Study of rhythm in London: is syllable-timing a feature of multicultural London English?
Bibliographic record
Abstract
Although thousands of in vitro selection and evolution experiments have been performed to seek different types of targets, most of them have only inspected the terminal evolutionary pool for patterns. In addition, to rapidly obtain the most favorable target, many experiments have been carried out under increasing selection pressure. However, increasing selection pressure seldom occurs in natural evolution. We studied the dynamic features of DNA in vitro evolution in the presence of the Mnt repressor under sequential constant selection pressure. When evolving under a constant pressure from an initial random pool of DNA, our system showed a clear, sharp, and reproducible crossover from a random population to an advantageous population (higher binding affinities of DNA sequences to the Mnt repressor). This crossover occurs after a long latent period during which there are no obvious changes in the population phenotype. We demonstrated that the existence of the crossover is caused by a significant sequence-nonspecific binding in the repressor-DNA system. After the crossover, the population settled in a stationary distribution of genotypes, which responded immediately to a subsequent sudden increase in selection pressure. We also experimentally tested the linear correlation between the evolution speed and sequence diversity (Fisher's theorem) in our system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".