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Record W2305003496 · doi:10.14796/jwmm.r223-10

Continuous Surface Runoff, Groundwater and Water Quality Modeling of the C-100 Basin, Miami-Dade County, Florida

2005· article· en· W2305003496 on OpenAlexvenueno aff
Thomas Nye, Robert E. Dickinson, Michael K. Thompson, Michael Schmidt, Víctor Javier Mangas Martín, Gilberto Peralta

Bibliographic record

VenueJournal of Water Management Modeling · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSurface runoffMiamiHydrology (agriculture)GroundwaterEnvironmental scienceStructural basinWater qualitySurface waterGeologyEnvironmental engineeringGeomorphologySoil scienceGeotechnical engineeringEcology

Abstract

fetched live from OpenAlex

C-100 Basin is a 40.6 square mile (105 km 2 ) area in southern Miami-Dade County (Florida) with an approximate elevation range of 5 to 15 ft (1.5 to 4.6 m) NGVD.The basin is an urbanized area of the county, with a western boundary only a few miles from the Florida Everglades, and it drains eastward to Biscayne Bay through the C-100 canal and its tributary canals.There are three control structures in the basin which maintain groundwater levels, provide flood relief, and prevent saltwater intrusion from the bay.Development in South Miami-Dade County (including the C-100 Basin) has heightened concerns about the impact of stormwater runoff on the quality and quantity of water discharged into Biscayne National Park via the canals in these areas.The primary objective of this planning effort is to improve the quality, quantity and periodicity of freshwater discharges to, and prevent degradation of, Biscayne National Park.Parts II and III of the National Pollutant Discharge Elimination System (NPDES) permit requires implementation of a comprehensive Stormwater Management Master Plan for Miami-Dade County to provide pollutant load reduction and water quantity control by the construction/retrofitting of stormwater management systems.Unique modeling techniques were used in order to accurately calibrate the

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.588

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2005
Admission routes1
Has abstractyes

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