Abiotic controls on nitrogen fixation and respiration in selected woody debris from the Pacific Northwest, U.S.A.
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
We estimated the effects of temperature, moisture, and oxygen concentration on nitrogen fixation and respiration in woody debris and used this information to model seasonal variation in these processes. We measured acetylene reduction and CO2 evolution of wood samples to determine the relative effect of these abiotic factors on nitrogen fixation and respiration. The interactions of these abiotic factors were examined in a model to test whether temperature alone can be used as a predictor of seasonal changes in nitrogen fixation and respiration rates in woody debris. Nitrogen fixation rates were optimum near 30ºC, whereas respiration rates were optimum over a broader range, from 30°C to 50°C. Nitrogen fixation and respiration rates were greatest above 175% and 100% wood moisture content, respectively, with little activity below 50%. Nitrogen fixation was optimum at 2% O2, with activity much reduced above and below this concentration. Respiration was optimal when O2 exceeded 1%. In our simulations, annual nitrogen fixation and respiration rates were 7.8 and 1.7 times greater, respectively, when only temperature limitation was included than when moisture and oxygen limitations were also included. Therefore, seasonal interactions of abiotic factors need to be considered when estimating annual nitrogen fixation and respiration rates.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it