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Record W2515499352 · doi:10.1080/08827509808962488

Historical Introduction to Refractory Metals

2001· article· en· W2515499352 on OpenAlexaff
Fathi Habashi

Bibliographic record

VenueMineral Processing and Extractive Metallurgy Review · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRefractory metalsRheniumMolybdenumLanthanide contractionTransition metalRefractory (planetary science)LanthanideTitaniumMaterials scienceMetallurgyInorganic chemistryChemistry

Abstract

fetched live from OpenAlex

Refractory metals vary in relative abundance in the Earth's crust from highly abundant like titanium (0.44%) to the least abundant rhenium (1.0 × 10-7%). A major part of these metals occurs as oxides and complex oxides (Ti, V, Cr, Nb, Ta, W), two as sulfides (Mo, Re), and the remaining two (Zr, Hf) as silicates. Due to the lanthanide contraction and being transition metals, some of them have the same atomic radii: Zr-Hf, Nb-Ta, and Mo-W and have very similar properties. Due to these various factors their discovery was extended over nearly a century and half from 1778 for molybdenum to 1924 for rhenium. A review of the historical events that led to their discovery is outlined.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0190.012

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 head0.030
GPT teacher head0.252
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2001
Admission routes1
Has abstractyes

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