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Record W2091075994 · doi:10.4141/s00-040

Soil-available phosphorus as evaluated by desorption techniques and chemical extractions

2001· article· en· W2091075994 on OpenAlexvenueaboutno aff
Noura Ziadi, R. R. Simard, T. Sen Tran, G. Allard

Bibliographic record

VenueCanadian Journal of Soil Science · 2001
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterChemistryDesorptionPhosphorusEnvironmental chemistryAnimal scienceAdsorptionSoil scienceEnvironmental science

Abstract

fetched live from OpenAlex

The P-supplying power of the fine-textured soils from Abitibi-Temiscaming (Quebec, Canada) has never been investigated. Anion exchange membranes (AEM), the electro-ultrafiltration (EUF) technique and chemical extractions were used to describe their P status. Phosphorus was desorbed from four soils that had received 52.4 kg P ha –1 yr –1 from 1994 to 1996 and from unfertilized soils. The cumulative amount of P desorbed in 75 min by EUF from unfertilized soils varied from 10 to 69 mg P kg –1 . Averaged over all sites and treatments, the amount of soil P extracted by different methods ranged from 1.0 to 18.9 mg P kg –1 . The cumulative grass P uptake was significantly related to P desorbed by all methods (0.39 < r < 0.84). A close relationship between grass P uptake and PAEMs indicated the adequacy of the AEMs to determine plant-available P in Abitibi-Temiscaming soils. A high degree of linearity (0.97 < R 2 < 0.99) of the EUF-P desorption curves at 200 V and 20°C with time was obtained. This indicates that soils have a high capacity to buffer removal of P from soil solution with reserve P. The EUF technique has shown that these soils hold very large inorganic P reserves and this may explain the lack of grass response to P fertilizers. Key words: Anion exchange membranes, grass-P uptake, P-desorption, Mehlich3-P, Olsen-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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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 designBench or experimental
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

Citations25
Published2001
Admission routes2
Has abstractyes

Explore more

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