Models for ultraviolet radiation—dependent photoinhibition of Lake Erie phytoplankton
Bibliographic record
Abstract
We calibrated a model for ultraviolet radiation (UVR) and photosynthetically active radiation‐dependent photoinhibition, with explicit damage and recovery processes (the R model), against observations of photosynthesis by Lake Erie phytoplankton exposed to natural sunlight in the summer of 1998. The model explained 74%–96% of the variation in photosynthetic rates and indicated active recovery processes at 4 of the 5 experimental stations. UVR‐dependent photoinhibition kinetics were not as well explained by two simpler models that assumed either a lack of recovery processes or an instantaneous equilibrium between damage and recovery. The 1998‐calibrated R model also provided consistently significant predictions of photoinhibition in 10 experiments done the previous year, albeit with a reduced goodness‐of‐fit, whereas simpler models did not. Biological weighting functions (BWFs) derived for UVR effects in 1998 were similar in shape throughout the UVR part of the spectrum, with an especially steep decrease from 300 to 320 nm, compared with BWFs published for other phytoplankton communities and/or species. The R model predicted photoinhibitory losses of primary production, integrated through the photic zone, that were intermediate between the two simpler models and showed that Lake Erie phytoplankton varied in both their spectral sensitivity (as expressed by the BWF) and recovery rates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".