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Record W2326404550 · doi:10.1071/aseg2012ab310

3D Seismic Surveying in Kevitsa Open Pit Mine

2012· article· en· W2326404550 on OpenAlex

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 · 2012
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsFirst Quantum Minerals (Canada)
Fundersnot available
KeywordsGeologyOverburdenSeismologyMining engineeringFault (geology)Data processingGeologic mapGeomorphologyDatabaseComputer science

Abstract

fetched live from OpenAlex

Summary3D reflection seismic survey was conducted over an area of about 9 km2 at the Kevitsa Ni-Cu-PGE (platinum group elements) deposit, northern Finland. About 1000 active receivers and 3000 shots in nine overlapping swaths were used to acquire the data. The principal objective of the survey was to image major fault and fracture zones at depth. Understanding the geometry of these zones is important for designing a steep open-pit for mining. Geological structures are complex and a varying thickness of overburden combined with various weather conditions during the data acquisition pose the data processing very challenging. However, a careful processing design combined with our experience on this type of data helped to produce interesting results. Processing results suggest that the 3D seismic survey has been successful in imaging both gently dipping and steeply dipping reflections as shallow as about 150 m, many of which correlate with fault systems and lithological contacts observed at the surface. Several new target areas, bright spots, are identified in the seismic data that require further investigations for their mineralization potential.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.036
GPT teacher head0.304
Teacher spread0.269 · 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