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Record W4386747788 · doi:10.61153/taym1799

Global Irish – Diversity of the diaspora

2023· article· en· W4386747788 on OpenAlexaboutno aff
N Reynolds, R. Mark Allen, P. Muhling, Charlie Gianfriddo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIrishGeologyStructural basinContext (archaeology)Mineralization (soil science)GeochemistryProspectivity mappingPaleontology

Abstract

fetched live from OpenAlex

The spectrum of zinc-lead deposits formed in basinal mineral systems encompasses VMS (volcanogenic massive sulphide), SHMS (shale-hosted massive sulphide), Irish-type and MVT (Mississippi valley Type) deposits. The platform carbonate-hosted part of that spectrum, the Irish-type and MVT deposits, has created the greatest challenges to pigeonholing approaches and the Irish Midland deposits have been variably considered as unique, “SedEx” variants, or MVT variants. In fact, the Irish-type spectrum of deposits can be considered as a global diaspora of diverse deposits that, nonetheless, show a number of distinct and economically significant characteristics in style and setting. For this reason, they warrant consideration as a discrete deposit type, though not in a neat pigeonhole, that is best considered in a mineralizing system context. The distinguishing features of Irish-type mineral systems can be considered in terms of source, trigger, pathway, trap, and preservation. The key features that distinguish Irish-type from ‘typical’ MVT and SHMS deposits are related to basin type and setting, timing of the mineralization event, mineralization style and chemistry, and deposit geometry. Empirically, these characteristic basin to deposit scale features overlap both MVT and SHMS but, together, are unique to Irish-type systems. This gives rise to criteria that can be applied to determine prospectivity of basins for Irish-type deposits and to target deposits within these basins. It is important to distinguish Irish-type from MVT systems because their economic characteristics are different. However, it is also important to recognise that there is great variability within the broad basinal carbonate-hosted zinc-lead deposit family and that each basin, and indeed each trend and deposit, are to some extent unique. It is therefore extremely important to avoid model-driven exploration and to develop a targeting understanding that acknowledges the model framework but is based on actual observations and data. To understand this diversity and targeting context, it is pertinent to consider the wide range of carbonate-hosted deposits that do not fit into the published MVT pigeonhole, including the Irish Midlands deposits; the Alpine deposits; deposits in the Basque-Cantabria Basin; deposits on the Gondwana margin including a number of deposits in North African,, southeast Turkey, Iran, and Duddar in Pakistan; the Early Cretaceous deposits on the Atlantic margin in Gabon; the Ordovician of the Sibumasu terrane (Tibet to Southeast Asia); Polaris in the Franklinian Basin; Nanisivik in the Borden Basin; and the Devonian Lennard Shelf deposits of Western Australia. All of these deposits occur in rift-sag basins with carbonate platforms, in some cases with multiple rift-sag cycles or with successor basins and, where constrained, the mineralization event is syn-basinal and typically related to early extension or inversion events. The deposits are stratabound and mostly tabular and continuous, often show strong direct control by extensional structures, are typically dominated by replacement, and commonly have significantly higher grades than ‘typical’ MVT deposits such as those in the mid-continent US, Silesia (Poland) and Pine Point (Canada).

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)0.000
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: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.001

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 head0.019
GPT teacher head0.193
Teacher spread0.174 · 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
Published2023
Admission routes1
Has abstractyes

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