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Record W3155971705 · doi:10.82308/45796

A simplified Gravity-Recoverable-Gold test /

2005· article· en· W3155971705 on OpenAlexaboutno aff
Jason Clarke

Bibliographic record

VenueeScholarship@McGill (McGill) · 2005
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)GeologyGold standard (test)Environmental scienceComputer scienceMathematicsStatisticsPaleontology

Abstract

fetched live from OpenAlex

Gravity-Recoverable-Gold (GRG) is defined as gold present in a particle in sufficient quantities as to be selectively recoverable from gangue via gravity methods. The McGill standard GRG test is an ore characterization test using three stages of sequential liberation and recovery with a Knelson KC-MD3 centrifuge to determine the size distribution of GRG. This thesis describes the development and testing of two simplified versions of the GRG test, using two and one stages of recovery respectively. Both tests use a feed mass of 20 kg, as opposed to the 40 to 100 kg normally used for the standard test. Eighteen differing ore samples were processed with the simplified GRG tests. For non-abrasive ores the one-stage simplified test returns a similar GRG content and size distribution, making the two-stage test superfluous. For abrasive ores, the one-stage test returns a GRG content that can be as much as 33% relative lower than that of the standard test, with a much finer size distribution. The two-stage test exhibited similar poor performance, though to a slightly lesser degree due to and additional stage of recovery attempted prior to grinding the abrasive material. The GRG lost typically reports to size fractions coarser than 25 µm, strongly suggesting smearing onto gangue particles. Because of the lower feed mass used, both simple tests are susceptible to the nugget effect; feed representativity also becomes challenging for ore samples of a head grade of 1 g/t or less.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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.

Study designBench or experimental
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
Published2005
Admission routes1
Has abstractyes

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Same venueeScholarship@McGill (McGill)Same topicSpaceflight effects on biologyFrench-language works237,207