MétaCan
Menu
Back to cohort
Record W2520131396 · doi:10.3390/min6030096

Pb-Isotopic Study of Galena by LA-Q-ICP-MS: Testing a New Methodology with Applications to Base-Metal Sulphide Deposits

2016· article· en· W2520131396 on OpenAlexafffundabout
Christopher McFarlane, Azam Soltani Dehnavi, David R. Lentz

Bibliographic record

VenueMinerals · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of New Brunswick
FundersNatural Resources CanadaU.S. Department of Energy
KeywordsGalenaIsotopeInductively coupled plasma mass spectrometryGeologyLaser ablationAnalytical Chemistry (journal)Mass spectrometryMineralogyChemistrySphaleritePyriteEnvironmental chemistryLaserPhysics

Abstract

fetched live from OpenAlex

In situ laser ablation quadrupole inductively coupled plasma mass spectrometry was used to measure Pb isotopes in galena. Data acquisition was optimized by adjusting spot size, energy density, and ablation time to obtain near steady-state low relative standard deviation (%RSD) signals. Standard-sample bracketing using in-house Broken Hill galena as external reference standard was used and offline data reduction was carried out using VizualAge for Iolite3. Using this methodology, galena grain in polished thin sections from selected massive sulphide deposits of the Bathurst Mining Camp, Canada, were tested and compared to previously published data. Absolute values and errors on the weighted mean of ~20 individual analyses from each sample compared favourably with whole-rock Pb-Pb isotope data. This approach provides a mean to obtain rapid, accurate, and moderately (0.1% 2σ) precise Pb isotope measurements in galena and is particularly well suited for exploratory or reconnaissance studies. Further refinement of this approach may be useful in exploration for volcanogenic massive sulphides deposits and might be a useful vectoring tool when complemented with other conventional exploration techniques.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.263
Teacher spread0.200 · 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.

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

Citations16
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueMineralsSame topicGeological and Geochemical AnalysisFrench-language works237,207