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Record W4238760127 · doi:10.4095/220219

Downhole seismic imaging of the Victor kimberlite, James Bay Lowlands, Ontario: a feasibility study

2005· report· en· W4238760127 on OpenAlexaffabout
Gilles Bellefleur, L Matthews, B. R. Roberts, B McMonnies, Matthew H. Salisbury, D. B. Snyder, G Perron, J McGaughey

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsKimberliteBayGeologySeismologyArchaeologyOceanographyGeochemistryGeographyMantle (geology)

Abstract

fetched live from OpenAlex

Downhole seismic data were acquired at the Victor kimberlite, in the James Bay Lowlands of Ontario, in order to attempt to produce an image of the pipe at 10 to 300mdepths and, in doing so, to evaluate the applicability of this method in delineating diamond resources. The survey was designed to allow two different imaging strategies, one using shot points located over the kimberlite pipe and the other using shots over the host sedimentary rocks. It was hoped that shot points over the kimberlite would directly image the kimberlite-sedimentary rock contact, whereas shots over the nearby (<250 m) sedimentary rocks would indirectly determine the kimberlite margin by mapping truncations of reflections from the sedimentary layers. Results demonstrate that the indirect mapping approach has potential to define the geometry of the kimberlite at depth.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.256
Teacher spread0.232 · 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

Citations3
Published2005
Admission routes2
Has abstractyes

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