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Record W2056640846 · doi:10.2113/gscanmin.43.4.1183

A METHODOLOGY TO DETERMINE THE ACID-NEUTRALIZATION CAPACITY OF ROCK SAMPLES

2005· article· en· W2056640846 on OpenAlexvenueno aff
Paul Weber, Joan E. Thomas, William Skinner, Roger St. C. Smart

Bibliographic record

VenueThe Canadian Mineralogist · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsNeutralizationGeologyGeochemistryMineralogyMining engineeringVirology

Abstract

fetched live from OpenAlex

Chemical calculations based on the molar quantity of neutralizing cations (Na, K, Mg, Ca, Mn) released to solution associated with the acidic dissolution of minerals provide a method to chemically quantify the acid-neutralization capacity (ANC) of carbonates, silicates, simple assemblages of mixed minerals, and waste-rock samples obtained from international mining operations. The acidity neutralized by each cation is equivalent to its valence within the mineral structure. Fe and Al are hydrolyzed during the ANC back-titration and thus are effectively non-acid- neutralizing cations. Sulfur derived from pyrite oxidation is equivalent to the release of two moles of H+, although non-acid-forming S (e.g., gypsum) should be addressed. Calculations based on these principles for the samples tested correlate well with the ANC determined by titration-type tests.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.084
GPT teacher head0.281
Teacher spread0.197 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations49
Published2005
Admission routes1
Has abstractyes

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