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Record W2901390111 · doi:10.1594/pangaea.836902

(Table 1) Water chemistry of groundwater and snow samples from three sites in Ontario, Canada

2010· dataset· en· W2901390111 on OpenAlexaboutno aff
William Shotyk, Michael Krachler, Werner Aeschbach, Stephen Hillier, Jiancheng Zheng

Bibliographic record

VenueFigshare · 2010
Typedataset
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsnot available
Fundersnot available
KeywordsTable (database)SnowGroundwaterWater tableHydrology (agriculture)Water chemistryEnvironmental sciencePhysical geographyChemistryEnvironmental chemistryGeographyGeologyMeteorologyDatabaseComputer science

Abstract

fetched live from OpenAlex

Snow samples collected from hand-dug pits at two sites in Simcoe County, Ontario, Canada were analysed for major and trace elements using the clean lab methods established for polar ice. Potentially toxic, chalcophile elements are highly enriched in snow, relative to their natural abundance in crustal rocks, with enrichment factor (EF) values (calculated using Sc) in the range 107 to 1081 for Ag, As, Bi, Cd, Cu, Mo, Pb, Sb, Te, and Zn. Relative to M/Sc ratios in snow, water samples collected at two artesian flows in this area are significantly depleted in Ag, Al, Be, Bi, Cd, Cr, Cu, Ni, Pb, Sb, Tl, V, and Zn at both sites, and in Co, Th and Tl at one of the sites. The removal from the waters of these elements is presumably due to such processes as physical retention (filtration) of metal-bearing atmospheric aerosols by organic and mineral soil components as well as adsorption and surface complexation of ionic species onto organic, metal oxyhydroxide and clay mineral surfaces. In the case of Pb, the removal processes are so effective that apparently ''natural'' ratios of Pb to Sc are found in the groundwaters. Tritium measurements show that the groundwater at one of the sites is modern (ie not more than 30 years old) meaning that the inputs of Pb and other trace elements to the groundwaters may originally have been much higher than they are today; the M/Sc ratios measured in the groundwaters today, therefore, represent a conservative estimate of the extent of metal removal along the flow path. Lithogenic elements significantly enriched in the groundwaters at both sites include Ba, Ca, Li, Mg, Mn, Na, Rb, S, Si, Sr, and Ti. The abundance of these elements can largely be explained in terms of weathering of the dominant silicate (plagioclase, potassium feldspar, amphibole and biotite) and carbonate minerals (calcite, dolomite and ankerite) in the soils and sediments of the watershed. Arsenic, Mo, Te, and especially U are also highly enriched in the groundwaters, due to chemical weathering: these could easily be explained if there are small amounts of sulfides (As, Mo, Te) and apatite (U) in the soils of the source area. Elements neither significantly enriched nor depleted at both sites include Fe, Ga, Ge, and P.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.579
Threshold uncertainty score0.710

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.5790.000

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 head0.020
GPT teacher head0.192
Teacher spread0.172 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2010
Admission routes1
Has abstractyes

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