Nutrient status and its assessment by pulse amplitude modulated (PAM) fluorometry of phytoplankton at sites in Lakes Erie and Ontario
Bibliographic record
Abstract
Variable fluorescence of chlorophyll a (Fv/Fm), as measured by pulse amplitude modulated (PAM) fluorometry, has been proposed as a metric of nutrient deficiency in phytoplankton. However, not all studies use the same make or model of instrument, which may contribute to inconsistent findings. Three different PAM instruments (DivingPAM, WaterPAM, and PhytoPAM) were compared, testing the relationship between Fv/Fmand nutrient deficiency indicators (nitrogen (N) debt, phosphorus (P) debt, and alkaline phosphatase activity (APA)) in natural phytoplankton communities in Lakes Erie (all basins) and Ontario (two sites) in July and September 2011. Varying degrees of N and P deficiency were indicated in both lakes and months, with P deficiency most prevalent, though deficiency appeared to ease prior to the onset of a major cyanobacterial bloom. WaterPAM and PhytoPAM Fv/Fmwere positively well-correlated, whereas DivingPAM was negatively but poorly correlated with the others. DivingPAM Fv/Fmwas negatively correlated with P debt and APA, consistent with expected Fv/Fmresponses to nutrient deficiency. Measurements with the other PAMs designed specifically to measure phytoplankton produced systematically higher values of Fv/Fm, which were uncorrelated to measures of nutrient deficiency. Different models of PAM cannot be assumed to produce equivalent measures of Fv/Fm, and care must be taken in interpreting results.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".