Distribution of corrosive microbial communities in rust layers of steel immersed in seawater
Bibliographic record
Abstract
In this paper, high-throughput sequencing technology was adopted to visualize the microbial communities on the surfaces of two types of carbon steel immersed in Sea Area Ⅰ. The results showed that different microbial communities were formed on different carbon steel surfaces, in which the genus with the highest abundance on the surface of Q235 was Escherichia– Shigella, while anaerobic Desulfovibrio on the surface of 921a was the most abundant, and the dominant genus varied with the depth of the rust layer. In addition, the distribution of sulfate-reducing bacteria (SRB) on the surface of Q235 submerged in Sea Area Ⅱ was compared with the sulfate-reducing bacteria's distribution in Sea Area Ⅰ, using the environmental factors correlation analysis. The results showed that the concentrations of Ca 2+ , Na + , K + , Mg 2+ , and Al 3+ were positively correlated with the distribution of SRB, while the concentrations of Cu 2+ , Zn 2+ , SO 4 2− , Cl − , NO 3 − , and organic carbon were negatively correlated with it. Furthermore, there was a highly significant correlation between each geochemical factor and Desulfotomaculum ( p < 0.01).
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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 | 0.000 |
| 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".