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Record W2010450621 · doi:10.1190/1.1487244

AeroTEM characteristics and field results

2001· article· en· W2010450621 on OpenAlexaff
W. P. Boyko, Norman R. Paterson, Karl Kwan

Bibliographic record

VenueThe Leading Edge · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsAgriculture Environmental Renewal Canada (Canada)
Fundersnot available
KeywordsElectrical conductorElectromagnetic coilTransmitterConductorBandwidth (computing)Transient (computer programming)Electrical engineeringAcousticsPhysicsEngineeringComputer scienceMaterials scienceTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

After half a century of rapid AEM (airborne EM) development and application, the 1980s were a “decade of uncertainty” (Fountain 1998) in which improvements focused mainly on increased bandwidth, multiple coil systems, and other advantages attendant on improved electronics and signal processing. An exception was the University of California Berkeley UNICOIL cryogenic helicopter system which adopted a single coil as both transmitter and receiver. Morrison et al. (1998) showed that this array maximized the ratio of target-to-host response in conductive environments. UNICOIL development was suspended in the early 1990s, but the same principle was used by AeroQuest in the AeroTEM transient (time domain) AEM system, which places the receiving coil centrally within the transmitting loop, thus achieving the same coupling with ground conductors simultaneously in both coils.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.006

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.

Opus teacher head0.028
GPT teacher head0.255
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2001
Admission routes1
Has abstractyes

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