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Record W4280600608 · doi:10.1255/tosf.161

A comparison between conventional blast hole sampling and diamond core drilling for copper grade at the Antapaccay mine

2022· article· en· W4280600608 on OpenAlexaff
F. Toconas, L. Jordan, S. Kedda

Bibliographic record

VenueTOS forum · 2022
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsGlencore (Canada)
Fundersnot available
KeywordsDrillingDrillSampling (signal processing)DiamondCore (optical fiber)Computer scienceMining engineeringEngineeringMaterials scienceMechanical engineeringMetallurgy

Abstract

fetched live from OpenAlex

Even though the sampling technique result in potentially biased samples with poor precision of the metal grade and are classified as specimens and not samples, the manual sampling of rotary percussion blast hole chips is still widely performed in the industry for operational grade control purposes. The objectives of this investigation are to estimate the precision and“bias” of manual sampling by comparing the copper grade results of fifteen (15) diamond drill core samples versus fifteen (15) rotary percussion blast hole drilling chip samples. This also includes the determination of a practical manual sampling template with the highest precision to providean understanding of the distribution of the copper content within the cone of blast hole chips. The contouring plots of thecopper grades provides the selection of the best fit-for-purpose template with regards precision and operational resourcing requirements. The diamond drill core samples take into account the Increment Delimitation Error (IDE) andIncrement Extraction Error (IEE) and therefore can be considered as reference samples for the purpose of this review.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.496

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 studies0.0010.000
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 head0.062
GPT teacher head0.301
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2022
Admission routes1
Has abstractyes

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