Isoecological curves on characterising the ecotypes central Mecsaek MTS of Hungary
Bibliographic record
Abstract
Ecological indicator values, widely used botany, are empricial scales worked out for the most important factors. Values of enviromental factors determine the position of the vegetation units in a multidimensional abstarct space. Their latest version in Hungary is the catergory system of Borhidi (1995), which is adjusted ti the European systems (e. g. Ellenberg et al. 1992). Indicator values or categories, respectively, can be found, according to European practice, in a relational computerised database (Horváth et al. 1995) which is accpeted as a standard for the botanists. An example of isoline analysis, completed using ecological indicator values of vegetation samples, is presented on a modell area in Mecsek Mts of South Hungary. It has varied vegetation with diverse kind of human interference near Pécs. From the existing indicator values applied here temperatur (TB), water demand (WB) of plants and soil reaction (RB). Each single isocurve was constructed from the similar indicator values on a computerised way (Surfer 6.1). All the curves were made by the use of avarages, single values and certain groups of ecological indicator values. Only the figures amde by the avarages are presented here, because there is no additional unformation in the case of the use of single curves. Curves of temperature and water indicators (isoTB, isoWB) show climatic conditions changed by human impact. Curves of soil reaction (isoR) show in a given moment the actual vegetation, in time dimension that parts of enviroment wich are more sensitive to acidification. Analysing isoecological curves, human impact is easily recognisable (e.g. in surroundings of clear-cuttings, etc.). On the basis of our results added to monitoring system enviromental impacts of future industrial and forestry establishments can be modelled. Isolines, using above-mentioned indicator values help to reveal and quantify enviromental change, which is model-valued posibility for preparing enviromental impact studies and making quick decisions.
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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 | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".