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Record W2361885401

Recent progress in the study of the deep-penetrating geochemical migration mechanisms and methods.

2007· article· en· W2361885401 on OpenAlexaboutno aff
Shi Jun-fa

Bibliographic record

VenueDizhi tongbao · 2007
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsLeaching (pedology)GeologyLeachateEarth scienceMining engineeringGeochemistrySoil scienceSoil waterEngineeringWaste management
DOInot available

Abstract

fetched live from OpenAlex

This paper systematically introduces the recent progress in the study of deep-penetrating geochemical migration methods and mechanisms in the international exploration community, with the focus on introducing the new models and theories of vertical migration of elements, including the reduced chimney model, electrically charged storm cell model and pump pressure effect mechanism. It summaries the main results of the deep-penetrating geochemical research, both domestically and internationally, mainly including the achievements obtained by the international collaborative research project funded by the Canadian Mining Industry Research Organization (CAMIRO), the research projects funded by the Research Centre for Landscape Environments and Mineral Exploration (CRCLEME) in Australia and research by other countries. On the basis of the outcomes of these research projects, the authors discuss the key factors affecting the selective leaching techniques. They think that the strategic choice of selective leaching techniques and the selective leaching of single target minerals are rather complex and affected by the process of soil formation and its physical-chemical factors such as pH and Eh to some extent, and additionally, they are also related to the controls on the concentration of the leachates, sampling depths and leaching conditions and process.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.022
GPT teacher head0.306
Teacher spread0.284 · 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 designOther design
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
Published2007
Admission routes1
Has abstractyes

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