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Record W2252884297

Molybdenum as a tracer to anthropogenic activity

2014· article· en· W2252884297 on OpenAlexaboutno aff
Alexander Tennant, Stephen M. Lane, Bernadette C. Proemse, Michael E. Wieser

Bibliographic record

VenueeCite Digital Repository (University of Tasmania) · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
Fundersnot available
KeywordsTRACEREnvironmental scienceEnvironmental chemistryMolybdenumTrace metalChemistryMetal
DOInot available

Abstract

fetched live from OpenAlex

The trace metal molybdenum (Mo) is not very abundant in the environment,but has numerous applications in anthropogenic activities. For instance,Mo sulphide (MoS<sub>2</sub>) is a component of diesel fuel. Mo is used as a catalyst in manyengines and is believed to be the most efficient catalyst for the hydro-cracking of bitumen,and has even been found in the emissions of coal-fired power plants. Hence,anthropogenic activities may release Mo in larger amounts to the environment thatmay affect terrestrial and aquatic ecosystems (e.g. via its coupling with the N cycle).We have therefore investigated the potential of Mo concentration and isotopicabundances as a tracer of androgenic emissions. Using a method of elemental doublespiking, we measured Mo concentrations and isotopic composition of aerosolsthroughout the city of Calgary, Alberta, Canada. Airborne Mo was collected at severallocations, ranging from an isolated weather station to a busy bus garage wherebuses were left to idle for extended periods of time. Mo concentrations ranged from0.07 ng/m<sup>3</sup> in the laboratory 19.0 ng/m<sup>3</sup> in the bus garage. The isotopic compositionswere variable from throughout the sampling sites. These results suggest thatMo has the potential to be used as a tracer of anthropogenic activity.

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 score0.244
Threshold uncertainty score0.651

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 communication0.0000.001
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 head0.006
GPT teacher head0.171
Teacher spread0.165 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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