MétaCan
Menu
← Back to cohort
Record W4410632680 · doi:10.22215/etd/2024-16402

Application of FactSage to Model the Compositional Variability of the of the Tamarack Intrusive Complex Ni-Cu-PGE Mineralization at the Main Zone

2024· dissertation· en· W4410632680 on OpenAlexfundno aff
Abdul Karim El Ghawi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMineralization (soil science)GeochemistryGeologySoil science

Abstract

fetched live from OpenAlex

The Tamarack Intrusive complex (TIC) is one of the satellite intrusions of the Duluth Complex, and is located about 75 kilometers west of Duluth, Minnesota. The Ni-Cu-PGE sulfide mineralization at the Main Zone of the TIC exhibits diverse ore types, including disseminated sulfides, semi-massive sulfides, and massive sulfide veins, distinguished by their compositions. This study aims to understand the processes responsible for these variations by employing for the first time the thermodynamic model FactSage 8.3 as a tool to understand the evolutionary path of the sulfide melt. Initial segregation of sulfide liquid was modeled in various ways. FactSage was used to show that the assimilation of 27wt% local semipelite by the presumed parental picritic magma could provoke sulfide saturation. The study also demonstrates that sulfide mineralization at the Main Zone could have been driven by the assimilation of H2S gas generated by devolatilization of the host Virginia Formation during

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicGeochemistry and Geologic Mapping→French-language works237,207→