MétaCan
Menu
Back to cohort

Remediation of Sea Water Intrusion: A Case Study

2001· article· en· W2147326685 on OpenAlex

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

VenueGroundwater Monitoring & Remediation · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsGroundwater rechargeAquiferHydrogeologyGeologyEnvironmental remediationIntrusionHydrology (agriculture)Saltwater intrusionGroundwaterEnvironmental scienceGeotechnical engineeringGeochemistryContamination

Abstract

fetched live from OpenAlex

Abstract Sea water intrusion and remediation in the Upper Floridan Aquifer in South Carolina is simulated using the finite‐element model SUTRA developed by the U.S. Geological Survey. A sensitivity analysis of the effect of the hydrogeologic parameters on the sea water recharge and seepage velocities is performed. An increase in confining unit and/or in aquifer conductivity results in an increase of the sea water recharge. An increase in aquifer porosity results in a decrease of the sea water recharge. Among the three remedial techniques simulated—reduced aquifer withdrawals, an injection well, and a combined injection and capture well—the reduced aquifer withdrawals and injection well are the best methods for preventing sea water intrusion.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.625

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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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