MétaCan
Menu
Back to cohort
Record W7116950231 · doi:10.7343/as-2025-905

Comparative analysis of water temperatures variability from hourly to annual time scales in two large karst springs in the dinaric karst

2025· article· it· W7116950231 on OpenAlexaff
Ognjen Bonacci, Ana Žaknić‐Ćatović, Tanja Roje Bonacci

Bibliographic record

VenueAcque Sotterranee-Italian Journal of Groundwater · 2025
Typearticle
Languageit
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsThe Scarborough Hospital
Fundersnot available
KeywordsKarstHydrology (agriculture)Air temperatureSpring (device)HydrogeologyTable (database)Surface water

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.260
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAcque Sotterranee-Italian Journal of GroundwaterSame topicKarst Systems and HydrogeologyFrench-language works237,207