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Record W2009896774 · doi:10.1139/f00-131

Cause of pH decline in stream water during spring melt runoff in northern Sweden

2000· article· en· W2009896774 on OpenAlexvenueno aff
Hjalmar Laudon, Olle Westling, Kevin Bishop

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
FundersNaturvårdsverket
KeywordsSnowmeltSpring (device)Surface runoffSTREAMSEnvironmental scienceAcid neutralizing capacityDeposition (geology)Environmental chemistryHydrology (agriculture)Acid depositionAcid rainDilutionChemistryEcologyGeologySoil waterSedimentBiologySoil science

Abstract

fetched live from OpenAlex

This study has sought to distinguish the anthropogenic and natural factors that drive episodic pH decline in northern Sweden. Approximately 600 stream water chemistry samples from 12 streams during the spring melt runoff of 1997 and 1998 were collected. Although the acid deposition levels of the region are relatively low (2-4 kg SO 4 2- -S·ha -1 ·year -1 ), the pH decline in all of the almost two dozen spring melt events ranged from nearly 1 to 3 pH units. By using the sum of base cation concentration as a dilution index and an organic acid pH model, the sources contributing to the pH decrease were quantified. For a majority of the spring melt events, organic acids contributed over 75% of the acidity at peak runoff (minimum pH). In only three of the monitored events was the anthropogenic SO 4 2- contribution as high as that from natural sources. NO 3 - did not contribute to the pH decline during spring melt in this study. An interannual variation was observed that was probably due to a larger anthropogenic deposition load during the winter of 1997-1998 and a more rapid snowmelt during the spring of 1998.

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 score0.442
Threshold uncertainty score0.942

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 science0.0000.000
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 head0.011
GPT teacher head0.197
Teacher spread0.187 · 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

Citations77
Published2000
Admission routes1
Has abstractyes

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