Comparative analysis of water temperatures variability from hourly to annual time scales in two large karst springs in the dinaric karst
Bibliographic record
Abstract
This study presents a comparative analysis of water temperatures from the Jadro and Ombla springs, two of the largest karst springs in the Dinaric Karst region of Croatia, situated 162.7 km apart. Both analyzed springs fall into the category of highly karstified systems. The analysis encompasses data recorded hourly from January 1, 2013, to December 31, 2021. During this period, comprehensive datasets of hourly water temperatures were available for both springs. The study examined four temporal scales: annual, monthly, daily, and hourly. Results revealed both similarities and distinctions in water temperature behavior within the coastal Dinaric Karst region. At Jadro and Ombla, the average annual water temperatures were 12.895ºC and 12.875ºC, respectively. The air temperature significantly influences the variations in water temperatures at both springs. At Jadro, the upward temperature trend was statistically insignificant, while at Ombla, the downward trend was similarly insignificant. The temperature range at Jadro (2.0°C) was significantly smaller than that at Ombla (3.4°C). From December to April, Jadro exhibited higher average monthly water temperatures than Ombla, while from June to September, temperatures at Jadro were lower than those at Ombla. The water temperatures at both springs were nearly identical during May, October, and November. The differences in water temperature ranges between the two springs are primarily shaped by the location, size, and natural characteristics of their catchments, including surface terrain, geological structure, hydrogeological properties, and the relative position of the water table to the ground surface.
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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 | 0.002 |
| 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) | 0.001 | 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".