Pigments and photoacclimation processes
Bibliographic record
Abstract
Introduction This chapter reviews the nature of pigment variations in phytoplankton in response to changes in light regime (irradiance, spectral composition and day length). These changes belonging to processes called acclimation and/or adaptation maximize the evolutionary fitness of a species, within the constraints set by the environmental conditions (Raven and Geider, 2003). In general, adaptation indicates long-term evolutionary outcome based on the genes present in a given species (genetic adaptation) while acclimation denotes adjustments in response to variation in key environmental variables (physiological acclimation). Photo-acclimation corresponds to a mosaic of processes involving many cellular components and occurring over a broad range of time scales, from seconds to days. These processes, covering many physiological, biochemical, biophysical and biological changes, allow the optimization of cell activities, such as photosynthesis, respiration, growth and division, when faced with changing irradiance (e.g. Herzig and Dubinsky, 1993; Anning et al ., 2000; Raven and Geider, 2003). This is an important issue in phytoplankton ecology because of the fluctuating light environment experienced by pelagic algae, related to daylight variations together with the exponential decrease of light and the vertical – active or passive – movements of algae along the water column.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".