MétaCan
Menu
Back to cohort
Record W2123243210 · doi:10.1190/1.1444873

Development of 3-D seismic exploration technology for deep nickel-copper deposits—A case history from the Sudbury basin, Canada

2000· article· en· W2123243210 on OpenAlexaffabout
B. Milkereit, E. K. Berrer, Alan R. King, Anthony H. Watts, B. R. Roberts, Erick Adam, David W. Eaton, Jianjun Wu, Matthew H. Salisbury

Bibliographic record

VenueGeophysics · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsPricewaterhouseCoopers (Canada)Geological Survey of CanadaVale (Canada)
Fundersnot available
KeywordsGeologyPetrophysicsSeismologyStructural basinMineral explorationGeochemistryIgneous rockSeismic explorationMining engineeringGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Following extensive petrophysical studies and presite surveys, the Trill area of the Sudbury basin was selected for conducting the first 3-D seismic survey for mineral exploration in North America. The 3-D seismic experiment confirms that in a geological setting such as the Sudbury Igneous Complex, massive sulfide bodies cause a characteristic seismic scattering response. This provides an excellent basis for the direct detection of massive sulfides by seismic methods. The feasibility study suggests that high-resolution seismic methods offer a large detection radius in the order of hundreds to thousands of meters, together with accurate depth estimates.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.089

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 studies0.0020.001
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 head0.014
GPT teacher head0.186
Teacher spread0.172 · 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 designNot applicable
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

Citations97
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueGeophysicsSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207