PR-420-183903-R01 Pipeline Right-of-Way River Crossing Monitoring With Satellites
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.
Bibliographic record
Abstract
The goal of the work described herein is to provide PRCI and the pipeline industry further understanding of the current capabilities and limitations of combined SAR and high resolution optical satellite imagery for the monitoring of pipeline ROWs which span river crossings. Four Areas of Interests (AOIs) with pipeline ROWs that span river crossings were selected for analysis: South Saskatchewan River, Saskatchewan, Canada operated by SaskEnergy Incorporated; Thompson Creek, Louisiana, USA operated by Colonial Pipeline Company; Gila River, Arizona, USA operated by Kinder Morgan Incorporated; and Humber Estuary, UK, operated by National Grid. For each AOI, monitoring requirements were defined by the operators. Amplitude Change Detection (ACD) and Interferometric Synthetic Aperture Radar (InSAR) were performed for all AOIs; results correlated to the defined monitoring requirements are discussed. A high level summary of the role of combined SAR and optical satellite operational monitoring of pipeline river crossings is listed below: - InSAR "Phase" used for (a) Subsidence (b) Slope Movement - SAR "Amplitude" used to both detect and classify (a) large scale Land Cover/Land Use Change (e.g. bridge construction), (b) flooding, (c) river channel changes, (d) river bed exposure, and (e) vessel traffic. - SAR "Amplitude" used to detect changes resulting from (a) small scale Land Cover/ Land Use (e.g. construction of individual buildings), and possibly (b) bank erosion and (c) pipeline exposure. Optical Satellite imagery is required for classification of these changes.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it