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Record W6922083020 · doi:10.1139/cjss-2014-035

Phosphorus forms and response to changes in pH in acid-sensitive soils on the Precambrian Shield

2015· article· en· W6922083020 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterSorptionPhosphorusPrecambrianFractionationSoil pHSoil horizonSurface water

Abstract

fetched live from OpenAlex

Baker, S. R., Watmough, S. A. and Eimers, M. C. 2015. Phosphorus forms and response to changes in pH in acid-sensitive soils on the Precambrian Shield. Can. J. Soil Sci. 95: 95-108. Soil acidification may explain declines in total phosphorus (TP) levels that have been observed in surface waters in central Ontario, Canada, but much of the research on phosphorus (P) mobility in pH manipulated soils has been performed at high P concentrations (i.e., >500 µM). This study investigated P fractionation in acidic (pH≤4.6) soils in south-central Ontario and relationships between soil pH and P sorption at relatively low P concentrations to test whether long-term declines in soil pH could have increased soil P sorption. Soils from three forested catchments that vary naturally in soil pH and outlet stream [TP] (0.1-0.4 µM in 2008) had very similar soil P concentrations and distributions (Hedley fractionation). Only hydrochloric-acid extractable P (i.e., apatite) differed amongst catchments and was greatest at the catchment with the highest stream [TP]. The fraction of P present as labile/soluble P did not decline with pH as expected and experiments indicated that P sorption at P concentrations between 4.52 and 452.1 µM was insensitive to manipulated solution pH. Soils were, however, able to sorb >90% of P added in sorption experiments at [P]≤452.1 µM. These results suggest that acidification-induced P sorption in upland soils has not contributed to observed decreases in surface water TP concentrations.

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)0.001
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 score0.108
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.193
GPT teacher head0.235
Teacher spread0.043 · 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
Published2015
Admission routes1
Has abstractyes

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