MétaCan
Menu
Back to cohort

Graphical representation of production results versus estimates in placer mining

2015· article· en· W2108684221 on OpenAlexaff
R. H. T. Garnett

Bibliographic record

VenueApplied Earth Science Transactions of the Institutions of Mining and Metallurgy Section B · 2015
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsBAH Enterprises (Canada)
Fundersnot available
KeywordsPlacer miningVariable (mathematics)StatisticsLogarithmRepresentation (politics)EstimationComputer scienceMathematicsData miningGeologyEngineering

Abstract

fetched live from OpenAlex

Placer deposits are renowned for the difficulties inherent in the estimation of their mineral reserves. Mining and treatment often produce a recovered grade very different from that originally estimated. A measure traditionally used in the placer mining industry to report such technical performance is the ratio of recovered grade to estimated grade. The ratio, referred to as a factor, is determined and reported for a specified duration of continuous mining or for a mining block size. Over the life of mine numerous data pairs are generated for the estimated grade and the corresponding factor. The frequently inverse relationship between the two measures is expressed graphically on a scatter plot. Logarithmic scales are used for both the independent variable (estimated grade) and the dependent variable (factor). The factor may vary widely, and best-fit trend lines are derived by using either power or quadratic polynomial formulae. The relative estimated grade (each estimate divided by the average of all estimates of grade within the mined extent of a placer) may replace estimated grade as the independent variable. The graphical representation allows performance to be compared and contrasted for different mineral placers and mining methods employing diverse units of grade measurement.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.056
GPT teacher head0.282
Teacher spread0.227 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueApplied Earth Science Transactions of the Institutions of Mining and Metallurgy Section BSame topicMineral Processing and GrindingFrench-language works237,207