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Record W865058189

含硫化物镁铁质-超镁铁质侵入体中橄榄石Mg、Ni含量的制约:原理、模式及Voisey's Bay侵入体样品研究(英文)

2007· article· zh· W865058189 on OpenAlexaboutno aff
Anthony Anthony, J.Naldrett, Edward Edward, M.Ripley

Bibliographic record

Venue地学前缘 · 2007
Typearticle
Languagezh
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsBayOceanographyEnvironmental scienceGeology
DOInot available

Abstract

fetched live from OpenAlex

镁铁质-超镁铁质岩浆结晶分离早期形成镁铁矿物,镁铁矿物中的Ni和Mg是相容元素。随着结晶分离作用的进行,Ni、Mg在硅酸盐岩浆及后形成的硅酸盐物质中的丰度下降。橄榄石中Ni含量及硅酸盐物质MgO/FeO比值都与母岩浆的相关值相关,据此可推断母岩浆的信息,它们之间可由实验测得的系数相联系。当岩浆饱和硫化物时,在结晶分离过程中硫化物珠滴会与镁铁硅酸盐物质一道析出,同时,与硫化物非饱和岩浆相比,过多的Ni会随之析出。这也反映在Ni、Mg含量比无硫化物分离时有更迅速的降低上。Ni、Mg含量变化值可以在VoiseysBay侵入体的模式曲线上反映出,加拿大Labrador的这一侵入体赋存了一个世界级的Ni-Cu-Co硫化物矿床。过去的作法是将侵入体中橄榄石的Ni、Mg含量与Simkin和Smith得出的各种火成岩中橄榄石的Ni、Mg含量相比较以确定Ni亏损,进而假定橄榄石来自硫化物饱和、有经济价值的岩浆。现在的研究显示这种简单的对比会导致错误。将样品数据与模式曲线对比并反映出侵入体矿物结晶堆积特征是重要的方法。使用这一方法,样品数据能很好地被模式曲线拟合。以在VoiseysBay的研究为例,当硫化物液相与硅酸盐矿物被去除...

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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
Published2007
Admission routes1
Has abstractyes

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