Time-Domain Electromagnetic Resistivity Mapping Of A Fjord-Head Delta
Bibliographic record
Abstract
An electromagnetic (EM) survey was conducted on the Zeballos River delta located approximately 300 kilometres north of Victoria, British Columbia, Canada to determine whether EM methods can help delineate the three-dimensional architecture of a fjord-head delta. The EM data were collected using a Geonics EM-47 system with a 40 m transmitter loop. The data were downloaded and subsequently edited and interpreted using the TEMIXGL layered earth inversion package from Interpex. The interpretation provided a regional picture of the three dimensional resistivity structure of the delta. Throughout most of the region surveyed, a relatively thick layer of resistive (> 400 ohm-m) sediment (gravel and sand - delta topsets and foresets) overlies more conductive (10 - 20 ohm-m) sediment (silt and clay - delta bottomsets) which in turn overlies resistive (> 2000 ohm-m) bedrock. Within the intertidal zone, the shallow sediments were saturated with sea water and hence very conductive. However, we were able to determine the depth to more resistive (fresh water) gravel and sand and, in some areas, resistive bedrock. The results of this study indicate that EM resistivity surveying can provide constraints on sediment type and thickness which, when used in conjunction with geological mapping, help improve our understanding of the three-dimensional architecture of these deltas.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".