MétaCan
Menu
Back to cohort
Record W4383820227 · doi:10.3390/min13070923

Role of Elemental Sulphur in Stage B Self-Heating of Sulphide Minerals, and the Potential Role of Polysulphides

2023· article· en· W4383820227 on OpenAlexafffund
H. Kim, Frank Rosenblum, Ozan Kökkılıç, Kristian E. Waters

Bibliographic record

VenueMinerals · 2023
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSulfurPyrrhotiteChemistryMineralStage (stratigraphy)MineralogyGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Sulphide minerals undergo numerous stages of mineral processing to extract the desired metal. When they are exposed to certain environmental conditions, some sulphide minerals can spontaneously heat up, a process called self-heating (SH), which, if left unchecked, can be a major hazard. Self-heating occurs in three distinct temperature stages, termed Stage A (temperature below 100 °C), Stage B (temperature range of 100 °C–350 °C), and Stage C (above 350 °C). Historically, it was understood that elemental sulphur generated in Stage A fuels Stage B reactions; however, the full extent of this behaviour is still unknown. The aim of this study is to understand the role of elemental sulphur in Stage B reactions. The results have demonstrated that elemental sulphur is incapable of fueling Stage B self-heating on its own, and it needs to interact with sulphide minerals in ambient temperatures in the presence of moisture and air. This interaction seems to be unique to pyrrhotite, as it failed to demonstrate stage B self-heating with other sulphide minerals. Previous works in surface chemistry suggest that this interaction leads to the formation of polysulphides.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueMineralsSame topicMetal Extraction and BioleachingFrench-language works237,207