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Paleo-tethys late triassic orogenic gold mineralization recorded by the Yidi’nan gold deposit, West Qinling, China

2019· article· en· W2983353848 on OpenAlexaff
Hao‐Cheng Yu, Kun‐Feng Qiu, Sheng-Xun Sai, Duncan McIntire, Franco Pirajno, De-Wen Duo, Daniel P. Miggins, Jie Wang, Ru-Ya Jia, Mingqian Wu

Bibliographic record

VenueOre Geology Reviews · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Windsor
FundersOpen Research Fund Program of Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment MonitoringFundamental Research Funds for the Central UniversitiesHigher Education Discipline Innovation ProjectChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaMinistry of Science and Technology of the People's Republic of ChinaMinistry of Education of the People's Republic of ChinaChina Geological SurveyChina University of Geosciences, WuhanSociety of Economic Geologists Foundation
KeywordsGeologySericiteGeochemistryDioriteBrecciaZirconMineralization (soil science)DikeGeochronologyQuartzPaleontology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
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 score0.233
Threshold uncertainty score0.464

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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

Citations58
Published2019
Admission routes1
Has abstractno

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