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Record W4392167452 · doi:10.5382/econgeo.5045

Alteration Mapping for Porphyry Cu Targeting in the Western Chagai Belt, Pakistan, Using ZY1-02D Spaceborne Hyperspectral Data

2024· article· en· W4392167452 on OpenAlexaff
Lei Liu, Chuntao Yin, Yasir Shaheen Khalil, Hong Jun, Jilu Feng, Huishan Zhang

Bibliographic record

VenueEconomic Geology · 2024
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologyEpidotePorphyry copper depositProspectingGeochemistryAluniteMineralization (soil science)Hyperspectral imagingSericiteMineral explorationRemote sensingMineralogyChloriteHydrothermal circulationFluid inclusionsSeismologyQuartzSoil science

Abstract

fetched live from OpenAlex

Abstract The Chagai porphyry Cu belt in Pakistan is an important metallogenic terrain extending approximately 400 km in an east-west direction. Most of the known porphyry Cu deposits, such as the world-class Reko Diq deposit and Saindak deposit, are located in the western Chagai belt. In this study, the ZY1-02D hyperspectral data acquired by a recently launched spaceborne imaging spectrometer with 166 bands within a 0.4- to 2.5-μm spectral region were used to map mineral information over 8,000 km2 for exploring potential targets of porphyry Cu mineralization in the western Chagai belt. False color composite, spectral angle mapper, and wavelength position mapping methods were used in this research leading to the identification of a series of alteration minerals (including muscovite [sericite], kaolinite, alunite, epidote, chlorite, and calcite) from ZY1-02D data. The alteration mineral maps derived from ZY1-02D data match well with the known deposits and field inspections. Twenty-three new targets were identified as potential porphyry Cu mineralization targets for further exploration in the study area. Three targets, north of Saindak, Koh-i-Sultan, and Durban Chah, and six alteration sites in the southwest of Durban Chah, were inspected in the field, and Cu-Au mineralization was confirmed in all these inspected areas. As the ZY1-02D hyperspectral data covers most of the land area of the earth, this study provides new insights for mineral exploration and lithologic mapping in remote regions.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.608

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 science0.0010.000
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 head0.056
GPT teacher head0.300
Teacher spread0.244 · 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 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

Citations22
Published2024
Admission routes1
Has abstractyes

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