Variations in microbial community on different materials in Sanya Marine Environment Experimental Station, China
Bibliographic record
Abstract
Marine biofouling occurs through the colonization of undesired microorganisms on the surfaces of structures. In this study, four immersion cycles (2, 5, 15, and 25 days) of total immersion in seawater were carried out at the Sanya Marine Environmental Test Station using three materials: industrial pure titanium (Ti), hot-dip zinc (Zn), and glass slide (GS). Three phyla, four classes, and nine bacterial genera were identified. The dominant genera were Pseudomonas, Alteromonas, and Pseudoalteromonas. The number of bacteria increased with soaking time. Sixty-one species of diatoms belonging to 30 genera, 24 families, and 16 orders were detected, among which the dominant genera were Amphora, Nitzschia, and Navicula. Four genera of ciliates belonged to two classes, three orders, and four families, among which the dominant species were Euplotes sp. and Uronema marinum. Tubular polychaetes was the dominant metazoans. Species diversity increased over time. The highest biofilm diversity was observed on the GS surface. The diversity of biofilms on the Ti surface was higher than that on the Zn surface. This study provides basic data for marine material research, marine corrosion, and national defence construction.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".