Haloarchaeal communities in the crystallizers of two adriatic solar salterns
Bibliographic record
Abstract
Solar salterns operate only for short dry periods of the year in the north shore of the Adriatic Sea because of its relatively humid and cold Mediterranean climate. In a previous paper, we showed that the NaCl precipitation ponds (crystallizers) of Northern Adriatic Secovlje salterns have different haloarchaeal populations from those typically found in dry and hot climates such as Southern Spain. To check whether there is a common pattern of haloarchaeal diversity in these less extreme conditions, diversity in crystallizers of other Adriatic solar salterns in Ston, Croatia was ascertained by molecular and culture methods. In addition, the cultivation approach was used to further describe haloarchaeal diversity in both salterns. Over the period of two solar salt collection seasons, isolates related to species of the genera Haloferax, Haloarcula, and Haloterrigena were recovered from both salterns. Within the same sampling effort, relatives of the genus Halorubrum and a Natrinema-like isolate were cultivated from Slovenian Secovlje salterns while Halobacterium related isolates were obtained from the Croatian Ston salterns. Concurrent with our previous findings, a library of Croatian saltern crystallizer PCR-amplified 16S rRNA genes was dominated by sequences related to the genus Halorubrum. The microbial community structure was similar in both salterns but diversity indices showed greater values in Slovenian salterns when compared with Croatian salterns.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".