Airborne electromagnetic and magnetic survey of Delaware Bay and surrounding regions of New Jersey and Delaware, 2022 (ver 2.0, April 2025)
Bibliographic record
Abstract
Airborne electromagnetic (AEM) and magnetic survey data were collected during July and August 2022 over a distance of 3,588.5 line kilometers covering Delaware Bay and surrounding regions in New Jersey and Delaware. Data were collected as part of the USGS Delaware River Basin Next Generation Water Observing Systems (NGWOS) project to improve understanding of groundwater salinity distributions near Delaware Bay. The survey was primarily funded by the USGS, with partial support through collaboration with the University of Delaware to extend data collection to parts of Rehoboth Bay and Indian River Bay. Data were acquired by SkyTEM Canada Inc. with the SkyTEM 304M time-domain helicopter-borne electromagnetic system together with a Geometrics G822A cesium vapor magnetometer. The survey was acquired at a nominal flight height of 30 - 40 m above terrain along parallel flight lines primarily oriented southwest-northeast and with nominal line spacing of 500 m over land and nearshore, and 3000 m over open-water parts of Delaware Bay. Several irregular flightlines were acquired along, and perpendicular to, nearby rivers to capture salinity patterns along these hydrologic flowpaths. Version 2.0 includes additional processed AEM data and inverted resistivity models.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".