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Record W2329645362 · doi:10.2138/am-2014-651

ORE DEPOSIT GEOLOGY

2014· article· en· W2329645362 on OpenAlexaff
Alexander Gysi

Bibliographic record

VenueAmerican Mineralogist · 2014
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeologyGeochemistryEconomic geologyMining engineeringMineralogyMetamorphic petrologySeismologyTectonics

Abstract

fetched live from OpenAlex

John Ridley (2013) Cambridge University Press, New York, p. 409. $85 ISBN 978-1-107-02222-5 (Hardback). www.cambridge.org/oredeposit The book Ore Deposit Geology has a beautiful cover of banded iron formations and the hardback format is very practical and robust for reading during travels, which makes this book not a dusty addition to your shelf collection. The book is subdivided into six chapters, with glossary, index, and references. Figures, cross sections, ore and mine photographs, and geological maps are available in color online with additional resources for teachers, which is an excellent source for lecture material. The target audience is advanced undergraduate to graduate students, and the major goal of the book is to link the building blocks of geosciences to ore deposit geology. The book is also intended as reference for professionals who wish to refresh their knowledge or learn about other types of deposits. The author, John Ridley, sought balance between detail and global perspective and between scientific research and applied field ore geology. The book demonstrates progress in ore geology that has been made by collaboration among the academic research and professional communities. Instances of this collaboration are among the topics covered “text boxes,” which provide additional explanation and call attention to topics that are worthy of more detail than can be covered in the chapters. Examples of the “text box” themes are research techniques, novel research findings, and discussions of the genesis of ore deposit types. For the students and teachers, there are exercises and further reading suggestions at the end of each chapter, to permit linking different chapter themes, build discussions, and make quantitative calculations. Common expressions in economic geology that may not be part of the normal geological lexicon such as cut-off grade and prospects are marked in bold and summarized in a handy glossary at the end of the book permitting the reader unfamiliar …

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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