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Record W2353928176

The Characteristics of the current situation of mineral resources

2012· article· en· W2353928176 on OpenAlexaboutno aff
XU Gui-fen

Bibliographic record

VenueChina Mining Magazine · 2012
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNatural resource economicsMineral resource classificationQuarter (Canadian coin)Investment (military)Iron oreBusinessChinaAgricultural economicsEconomicsGeochemistryGeologyGeography
DOInot available

Abstract

fetched live from OpenAlex

As the world economic growth is slowing,the demand of major mineral commodities has been shrinking since the fourth quarter of 2011.At the same time,financing is more and more difficult,and the mining cost is rising,and the prices of iron ore,copper,aluminum,lead,zinc,nickel and other metal have declined,and mining stocks have fallen.As a result,the global mining has entered again into the down phase.However,the demestic situation of mineral resources runs smooth.The demand of mineral resources is tight in China and loose in the world,which will be relieving in short-term and tightening in long-term.First,the mining fixed asset investment growth has increased by quarter.Second,the supply capability of mineral products has been increasing constantly.Third,the imports of important minerals kept going up.Fourth,the prices of important mineral commodities have kept fluctuating at high level.At last,the markets of exploration and mining rights are active.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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
Published2012
Admission routes1
Has abstractyes

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