Modelling the production and species richness of wild mushrooms in pine forests of the Central Pyrenees in northeastern Spain
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
Multiple-use forestry requires comprehensive planning to maximize the utilization and sustainability of many forest resources whose growth and productivity are interconnected. Forest fungi represent an economically important nonwood forest resource that provides food, medicine, and recreation worldwide. A vast majority of edible and marketed forest mushrooms belong to fungi that grow symbiotically with forest trees. To respond to the need for planning tools for multiple-use forestry, we developed empirical models for predicting the production of wild mushrooms in pine forests in the South-Central Pyrenees using forest stand and site characteristics as predictors. Mushroom production and species richness data from 45 plots were used. A mixed modelling technique was used to account for between-plot and between-year variation in the mushroom production data. The most significant stand structure variable for predicting mushroom yield was stand basal area. The stand basal area associated with maximum mushroom productivity (15–20 m 2 ·ha –1 ) coincides with the peak of annual basal area increment in these pine forests. Other important predictors were slope, elevation, aspect, and autumn rainfall. The models are aimed at supporting forest management decisions and forecasting mushroom yields in forest planning.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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