Proline content and varying barometric pressure: an analysis of six genes, across three marine a<i>ltererythrobacter s</i>trains
Bibliographic record
Abstract
Environmental stresses select for suitably adapted genes. These stresses will promote the propagation of certain mutations, and the loss of others, throughout the evolution of a species. For organisms living two thousand meters below the ocean’s surface, one of these stresses is certainly high barometric pressure. Due to the imino ring structure of proline it was hypothesized that bacteria sampled from greater depths would show a larger proportion of content in their proteins. This hypothesis was examined by analyzing the proline content of 6 proteins common to 3 species from the altereythrobacter speciesl All the selected strains are Gram negative, moderately halophilic marine bacteria with optimum temperatures around 30⁰C. A. marensis strain KCTC22370 (taxonomy ID: 543877) was sampled, and genomically annotated, by Soo and Lee from the surface of the sea near Jeju island in the Republic of North Korea (2010). A. epoxidivorans strain JCS350 (taxonomy ID: 361183) was sampled from cold-seep sediment in the Kagoshima Bay, off the coast of Japan, at an approximate depth of 120m. The strain was isolated and genomically annotated by Kwon et.al. (2007). A. atlanticus strain 26DY36 (taxonomy ID: 1267766) was sampled from a North Atlantic mid ocean range at a depth of 2577m. The strain was isolated and annotated by Wu et. al. (2015). The data showed no significant differences in the proline content of the 3 species examined, however a more expansive study would be required to fully reject the hypothesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".