Wetland plant functional trait responses to experimental warming and flooding, Yukon-Kuskokwim Delta (Western Alaska, USA) (2022-2023)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This dataset was created to understand plant trait responses to warming and flooding in the Yukon-Kuskokwim (Y-K) Delta (western Alaska, USA). We conducted a two-year field experiment in which we passively increased temperatures, simulated periodic tidal flooding at two intensity levels (low and high) during the 2022 and 2023 summer growing season. Our treatments reflect changes expected in the Y-K Delta in the next 10-20 years. We conducted the experiment in a wet sedge-shrub meadow and only sampled the dominant species in this community. At the end of the 2023 season, we measured economics traits (specific leaf area, leaf dry matter content, specific stem density) and size-related traits (height, leaf area, leaf thickness) in four focal species: the dominant sedge Carex rariflora, the dominant deciduous dwarf-shrub Salix fuscescens, the most abundant grass, Calamagrostis canadensis, and the most abundant forb, Potentilla palustris. We also measured additional traits related to seasonal growth, reproduction, and reproductive phenology to capture species temporal responses to warming and flooding in the two most dominant species. These included vegetative height over time, number of reproductive structures, reproductive structure length, reproductive shoot height (Carex only), and reproductive phenological stages (Salix only).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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 it