Inductive interaction between closely spaced steeply dipping tabular conductors located in a resistive host
Bibliographic record
Abstract
Abstract Physical scale-model studies of the responses provided by horizontal coplanar and vertical coincident coil moving-source electromagnetic systems when operated over closely spaced, steeply dipping, tabular conductors located in a resistive host are presented. For separations of the conductors that permit separate anomalies to be identified, the detected effect of inductive interaction between the conductors depends on the configuration of the exploration device. As conductors are moved closer together, the horizontal coplanar coil system produces responses for each conductor that become progressively weaker than the individual responses when each conductor is isolated. By comparison, vertical coincident coils detect an initial increase of the anomalies from the individual conductors as the conductor separation is reduced until just before the separate anomalies merge. As the anomalies merge, the vertical coincident coil responses decline in magnitude. After the anomalies merge and present the appearance of the response of a single conductor, both coil systems record an expected strong increase of response which exceeds the response when the conductors are in contact. These mutual inductive interactions cause significant variations in the depth estimates provided by horizontal coplanar coils. Depth estimates provided by vertical coincident coils are always smaller than the true target depths. The vertical coincident coil configuration displays an ability to identify separate conductors at significantly smaller conductor separations than can the horizontal coplanar coils.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".