MétaCan
Menu
Back to cohort

Rare Earth Elements in Alberta Oil Sand Process Streams

2017· article· en· W6884330780 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsSTREAMSOil shaleRare earthRare-earth elementFraction (chemistry)Oil sandsLanthanideMass fraction

Abstract

fetched live from OpenAlex

The\nconcentrations of rare earth elements in Alberta, Canada oil\nsands and six oil sand waste streams were determined using inductively\ncoupled plasma mass spectrometry (ICP–MS). The results indicate\nthat the rare earth elements (REEs) are largely concentrated in the\ntailings solvent recovery unit (TSRU) sample compared to the oil sand\nitself. The concentration of lanthanide elements is ∼1100 mg/kg\n(1100 ppm or 0.11 wt %), which represents a >20× increase\nin\nthe concentration compared to the oil sand itself and a >7×\nincrease\ncompared to the North American Shale Composite (NASC). The process\nwater, which is used to extract the oil from oil sands, and the water\nfraction associated with the different waste streams had very low\nconcentrations of REEs that were near or below the detection limits\nof the instrument, with the highest total concentration of REEs in\nthe water fraction being less than 10 μg/L (ppb). Size and density\nseparations were completed, and the REEs and other potentially interesting\nand valuable metals, such as Ti and Zr, were concentrated in different\nfractions. These results give insights into the possibility of recovering\nREEs from waste streams generated from oil sand processing.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0600.001

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 head0.029
GPT teacher head0.289
Teacher spread0.259 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicExtraction and Separation ProcessesFrench-language works237,207