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Record W3105701606 · doi:10.15406/paij.2020.04.00218

Geomagnetic inversion for delineation of ore deposits in chenar mine

2020· article· en· W3105701606 on OpenAlexaboutno aff
Ahmad Ala Amjadi, Mohsen Kushki

Bibliographic record

VenuePhysics & Astronomy International Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsnot available
FundersInternational Institute of Earthquake Engineering and Seismology
KeywordsGeologyEarth's magnetic fieldMining engineeringInversion (geology)GeochemistryMineralogyGeophysicsSeismology

Abstract

fetched live from OpenAlex

In this manuscript, we have performed an applied geomagnetic inversion study in the Chenar ferrous mine near Asadabad-Hamedan of Iran.The principal purpose of this study was to depict and visualize the ore massif of the Chenar ferrous mine in details and to find the suitable locations for geological drilling cores.In this study, 4300 Geomagnetic readings were acquired over a ten-day data acquisition period with a Canadian-built 2019 GEM-GSM19T magnetometer.The analyzes of the geomagnetic data in the Chenar ferrous mine successfully identified the susceptible zones in the area of study, and we have suggested the location of six drilling points in the mining area for further investigation and verifying of geophysical data.Our results depict four massifs which are extended as veins.According to the dimensions of the magnetic halos, our geophysical result estimates the ore deposit to be about two and a half million tons for three of the massifs in the Eastern part and 250 thousand tons for the fourth massif in the Western part of the study region.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.230
Teacher spread0.211 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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