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Record W3043120482 · doi:10.1016/j.dib.2020.106022

Datasets of solid and liquid discharges of an urban Mediterranean river and its karst springs (Las River, SE France)

2020· article· en· W3043120482 on OpenAlex
Christiane Dufresne, Bruno Arfib, Loïc Ducros, C. Duffa, Frank Giner, Vincent Rey, Thierry Lamarque

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueData in Brief · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsUniversité du Québec à Rimouski
FundersMétropole Toulon-Provence-MéditerranéeAgence de l'Eau Rhône Méditerranée CorseInstitut de Radioprotection et de SÛreté NucléaireCentre National de la Recherche ScientifiqueResearch Management Centre, International Islamic University MalaysiaAix-Marseille UniversitéAgence de l'Eau Adour-Garonne
KeywordsTributaryHydrology (agriculture)KarstEnvironmental scienceSurface runoffMediterranean climateTurbidityDrainage basinDischargeStormwaterMain riverBayGeologyOceanographyGeographyEcology

Abstract

fetched live from OpenAlex

This data paper presents: (1) the liquid and solid discharge characteristics of the Las River, an urban Mediterranean stream flowing to the Bay of Toulon (south of France), and (2) the water height of the main karst springs supplying the Las River. We assessed the river's discharge with hydrological observations and we explored floods characteristics influencing its solid discharge [1]. The location of the monitoring station near the river's mouth was selected accordingly to accessibility and technical constraints, as far downstream as possible. The vast majority of tributaries (such as possible underground springs, stormwater outlets, urban runoff) were taken into account. A multi-parameter probe (temperature, pressure, turbidity and electric conductivity) and a sediment trap were deployed continuously for 17 months, from October 2012 to March 2014. At the river's sources, probes (temperature, water height) were deployed to characterized karst springs. Times series were averaged at a daily time step, and water height converted in discharge when the rating curve was available. Sediment samples were analyzed for grain-size distribution. Datasets may help to estimate karsts' contributions to the Mediterranean Sea and to assess their influence on rivers discharge and solid yield. Stakeholders may also use the maximum water height to evaluate the flooding risk. Our data also contribute to linking the catchment freshwater to the coastal sea, a connection yet to be fully explored.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.258
Teacher spread0.222 · 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