Examples showing characteristics of the megatem airborne electromagnetic system
Bibliographic record
Abstract
The fixed-wing MEGATEM airborne transient electromagnetic (EM) system was introduced in 1998 (Smith et al., 2003) as a four-engine version of the GEOTEM system (Annan and Lockwood, 1991). The four engines were required so that the system could fly safely at high altitudes in the Andes Mountains (Smith et al., 2003). The larger aircraft required to carry four engines was also able to carry a larger transmitter loop, so the dipole moment of the system increased to more than one million Am2 ? hence the name MEGATEM. However, the aircraft was also able to draw power from more generators and carry heavier more powerful transmitter electronics, so a further increase was achieved in 2001 so that the dipole moment became more than two million Am2 (Smith et al., 2003). As a consequence, the system name was modified to MEGATEMII. The system also flies with a magnetometer for measuring the intensity of the earth?s field. In this paper, we review the results of our experience of using the MEGATEM system over the last 8 years. A comparison of systems with different power at the Reid-Mahaffy test site clearly demonstrates how the amplitude of the anomaly increases with increasing moment. A height attenuation test over the Iso ore body has been used to estimate the signal and noise levels of the system and to estimate the depth of penetration of the system when looking for this type of body. A test survey in the Athabasca basin of northern Saskatchewan has demonstrated that the MEGATEM system can see a large body at 700 m depth in a highly resistive environment. In a nearby location, a comparison of TEMPEST and MEGATEM shows the relative strengths of the two systems. Tests conducted at the Gallen site with the transmitter off show that how signals radiated from a nearby power line can corrupt the data. These data have been used to demonstrate an improved way of reducing this type of noise that makes it easier to identify true anomalies close to a power line. A comparison of a MEGATEM survey with an older survey in an area within the Chibougamau district has been used to document the improvements of the system compared with the results of an older survey. The greater depth of penetration of the MEGATEM system compared with a helicopter system is illustrated by a model study.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.007 |
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".