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Record W2528840696 · doi:10.1071/aseg2016ab187

Applying advanced gravity and magnetic inversion methods to expand the Platreef PGE-Ni-Cu resource in the Bushveld Complex

2016· article· en· W2528840696 on OpenAlex
Nicholas Williams, Barry de Wet, Sello Melvyn Kekana, S. Suzanne Nielsen, David W. Broughton

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueASEG Extended Abstracts · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsIvanhoe Energy (Canada)BP (Canada)
FundersU.S. Geological Survey
KeywordsGeologyGradiometerInversion (geology)GeophysicsPlacer miningDrillingSeismologyMining engineeringGeochemistryMagnetic fieldMagnetometer

Abstract

fetched live from OpenAlex

There are many potential field inversion algorithms available, and all are sufficiently capable of generating a model that explains supplied geophysical observations. The challenge is extracting a model that provides real geological insight. Here we present applications of two different styles of advanced inversions to a deep exploration program at the Platreef PGE-Ni-Cu deposit in the Bushveld Igneous Complex of South Africa. The initial approach was to apply generalised focussing constraints to a 3D magnetic vector inversion, an approach chosen to manage the effect of expected strong remanent magnetisation. This resulted in successful prediction and drill definition of inferred resources within a deep, west-dipping extension to the shallow-dipping “Flatreef” deposit. Later, a detailed 3D model of geological constraints based on drilling and mapping was constructed and used to tightly constrain inversions of gravity data derived from a FALCON airborne gravity gradiometer survey. The resulting 3D density model accurately predicted a continuation of the Flatreef host rocks to shallower levels than previously anticipated. This facilitated further drilldefinition of additional inferred resources within a southern extension of the Flatreef deposit. Key to the success of the inversions at accurately targeting mineralisation at depths of 700-1300 m depth, was the inclusion and integration of all available information to ensure that predictions were consistent with prior observations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.288
Teacher spread0.261 · 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