Magnetic Airborne Survey – Geophysical Flight
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
Abstract. Geophysics is a Geoscience that involves the study of the Earth via physical measurements. In this context, there are many types of physical measurements that can be studied. Airborne geophysics involved one of these types of measurements. It uses airborne data to characterize larger areas with mineral exploration potential. Measurements are typically taken at a preliminary point of the exploration process, after the soil of the area has been classified. The first geophysical method to utilize airborne research was the magnetic method. Discovered by Faraday, Sect. XIX, the method was initially used by the USSR (current day Russia) in 1936 (Hood, 1969) and better adapted by America in 1940 (Hood, 1969). Both countries had a vested military interest in the technology, particularly for submarine applications. After some adaptations, another early flight was made in the US in 1944 using the Beech Staggerwing NC18575 (Morrison, 2004). The first geophysical airborne survey in Brazil occurred 60 years ago (1953) in the city of Sao Joao Del Rey, Minas Gerais (Hildebrand, 2004). It was conducted by the Prospec Company, which later became Geomag. The survey utilized both magnetic and radiometric methods. The fixed wing aircraft used in the survey was the PBY-5 (Catalina). It was equipped with a Fluxgate magnetometer, which measured the total magnetic field, in the tail of the aircraft (Hildebrand, 2004). The system was totally analogic and constructed using electromechanical units and an infinite series of valves. All the data processing was done manually because, at that time, analogic data was recorded, tabulated, corrected, interpolated and plotted on a cartographic base. The data were then presented in the form of a profile overlay on contour maps. All tracing was also manually completed.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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