Effect of soil properties and vegetation characteristics in determining the frequency of Burgundy truffle fruiting bodies in Southern Poland
Bibliographic record
Abstract
The Burgundy truffle (Tuber aestivum Vittad.) has a wide-ranging distribution across Europe, yet its ecology is far from being well understood. For instance, although the literature on the ecophysiology of this species is dominated by the symbiosis with deciduous hosts, the real range of hosts in nature seems to be much wider than the current distribution of T. aestivum. The aim of this study was to determine the relative importance of abiotic (soil) and biotic (vegetation) properties in determining the performance of T. aestivum in this pioneering stage of research on truffles in Poland. Soil parameters influenced the formation of T. aestivum fruiting bodies more strongly than plant composition. The number of fruiting bodies increased with increasing concentration of soil calcium and phosphorus. The number of plant species was the only significant predictor among the investigated vegetation characteristics. The influence of this predictor was positive, as an increasing number of fruiting bodies was found when the number of plant species was higher. The presence of truffle fruiting bodies was significantly correlated with the presence of five plant species, viz.: Brachypodium sylvaticum, Cephalanthera damasonium, Cornus sanguinea, Sanicula europaea and Viola mirabilis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".