Pigment assemblages in subtropical bloom-forming cyanobacteria strains
Bibliographic record
Abstract
Abstract Pigments are powerful indicators for chemotaxonomy and remote sensing studies, which are the approaches used for cyanobacterial bloom monitoring. Cyanobacterial pigments include high concentrations of phycobilins and diverse carotenoids. Filamentous nitrogen-fixing species (Nostocales) are frequent in cyanobacterial blooms of warm climate lakes, and more information about pigments can be useful for improving management. We analyzed the carotenoid ratios to chlorophyll a of nine subtropical cyanobacterial strains (orders: Synechococcales, Chroococcales, Oscillatoriales and Nostocales), for some of which we also characterized the in vivo absorption spectra (aph). The main carotenoids were β,β-carotene, echinenone, hydroxy-echinenone-like, zeaxanthin and myxoxanthophyll (including aphanizophyll and unknown myxoxanthophyll-like myxol-glycoside carotenoids); however, proportions diverged greatly between orders, a trend also observed for the aph. Zeaxanthin ratios were highest in the picocyanobacterium. Nostocales species were rich in myxoxanthophyll and echinenone, with low zeaxanthin signals. We identified four pigment assemblages differentiating the strains according to their phylogenetic orders, information that needs to be considered for tracking cyanobacterial groups, particularly Nostocales.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".