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Record W2560872482 · doi:10.14796/jwmm.c412

Simulating the Upper St. Johns River for Extreme Events

2016· article· en· W2560872482 on OpenAlexvenueno aff
Christopher Brown, Amanda E. Tancreto

Bibliographic record

VenueJournal of Water Management Modeling · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsWatershedHydrology (agriculture)OceanographyEnvironmental scienceArchaeologyGeographyGeology

Abstract

fetched live from OpenAlex

The St. Johns River is one of the most important river systems in Florida. The watershed begins in East Central Florida and discharges to the Atlantic Ocean east of Jacksonville, Florida. The watershed is susceptible to large rainfall events including tropical storms and hurricanes and is topographically flat such that flooding is a real concern. The Upper St. Johns River Basin (USJRB) encompasses an area of approximately 4 530 km 2 . USJRB mainly comprises marsh and agricultural land types including man-made storage areas used for flood control and environmental management, and includes numerous water control structures. The Middle St. Johns River Basin (MSJRB) is downstream of the USJRB and covers an area of approximately 3 100 km 2 . The land use in this region is dominated by more urbanized areas including parts of Orlando. Recently, researchers at the University of North Florida developed a preliminary HEC-HMS rainfall-runoff model of the USJRB and a portion of the MSJRB. The model domain covers roughly 5 200 km 2 and includes numerous subbasins. The model was calibrated and verified against observed data recorded between 2007 and 2011 and including a large tropical storm event.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.601
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.029
GPT teacher head0.249
Teacher spread0.219 · 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.

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

Citations2
Published2016
Admission routes1
Has abstractyes

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