Comparison of Noble Gas Temperature with Recent Mean Annual Air and Soil Temperature in different regions of Hungary
Bibliographic record
Abstract
Abstract This paper describes the relation of noble gas temperature (NGT) and mean annual air (MAAT) and soil (MAST) temperature through studying water samples and meteorological data from six Hungarian regions. Alluvial plains, hilly and mountainous regions were studied to investigate the effects of geomorphological, hydrogeological and micro-climatic conditions. Water samples were collected from springs and wells fed from different aquifers. Comparing NGTs derived from these water samples with the MAAT and MAST values of the given region, we identified differences between the sampled areas. In case of the Geresd Hills, Mezőföld, Danube-Tisza Interfluves and Nyírség, the NGTs (13.0 ± 0.9 °C, 12.1 ± 1.1 °C, 12.1 ± 0.6 °C and 12.7 ± 1.6 °C, respectively) generally reflect MAST, however in karstic Bükk Mts. (6.8 ± 0.6 °C) and Mecsek Mts. (10.7 ± 1.9 °C) they are closer to MAAT. Consequently, it can be concluded that the direct relationship between noble gas temperature and mean annual air temperature is not always as well-defined as it is often assumed. It is shown that MAAT and MAST should be distinguished, especially when using NGT as a paleoclimate proxy.
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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 | 0.000 |
| 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 | 0.000 | 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 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".