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Record W4387461534 · doi:10.47765/0869-5997-2023-10014

Composition, formation conditions, distribution patterns and zoning of gold mineralization in the Stadukhinsky ore-placer region (Western Chukotka)

2023· article· en· W4387461534 on OpenAlexaboutno aff
Yu. N. Nikolaev, Irina Balykova, Sergei Kuzin, И. А. Бакшеев, Andrey V. Apletalin, V. Yu. Prokofiev, E. A. Vlasov, I.A. Kalko, Valery Kosyatov

Bibliographic record

VenueOres and metals · 2023
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsProspectingGeologyGeochemistryMineralization (soil science)Placer miningIgneous rockPlacer depositMetallogenyZoningIntrusionMineralogyPyriteSphalerite

Abstract

fetched live from OpenAlex

Gold deposits associated with granitoid intrusions have long been known. Recently, a class of deposits was identified among them, called intrusion-related granite systems, IRGS (gold-rare metal formation). The standards of the geological prospecting model for them are the deposits of the Tintin metallogenic belt (Alaska, Canada). In Russia, this type has been studied less; IRGS includes the Shkolnoye and Butarnoye (Magadan region) and Kekura (Chukotka) deposits. Based on field and laboratory studies, generalization of prospecting geological and geochemical data, the characteristics and localization features of gold mineralization associated with granitoids of a large igneous uplift in the South Anyui structural-formational zone (Western Chukotka) were determined. The mineral composition of ores, the sequence of their formation were studied, homogenization temperatures and salt concentrations in gas-liquid inclusions were determined. The geochemical and mineralogical zoning of the ore-magmatic system has been identified, and criteria have been developed for assessing erosion and predicting gold mineralization to depth.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.176

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 science0.0000.000
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 head0.022
GPT teacher head0.251
Teacher spread0.230 · 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 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

Citations3
Published2023
Admission routes1
Has abstractyes

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