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Analysis of Phosphorus Species in Water

2019· other· en· W2998258731 on OpenAlexaff
Vlastimil Packa, Vadim Bostan, Vasile I. Furdui

Bibliographic record

VenueEncyclopedia of Water · 2019
Typeother
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsToronto Metropolitan UniversityMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsPhosphorusPhosphateChemistryInductively coupled plasmaEnvironmental chemistryInductively coupled plasma mass spectrometryCapillary electrophoresisMass spectrometryAquatic ecosystemChromatographyPlasma

Abstract

fetched live from OpenAlex

Abstract A limiting nutrient for aquatic ecosystems, the natural and anthropogenic sourced phosphorus is present in surface waters. Monitoring of phosphorus in water samples and reduction procedures were developed to minimize the occurrence of harmful algal blooms. Phosphate is the most common phosphorus species in water, being present in anionic form (inorganic phosphate) or attached to a carbon‐based molecule (organic phosphate). Although various methods have been developed for phosphate and total phosphorus analysis, the spectrophotometric and ion chromatographic methods remain the most frequently used. Other methods discussed are based on capillary electrophoresis, inductively coupled plasma coupled to atomic emission spectrometry, electrochemical, and nuclear magnetic resonance techniques. The simultaneous analysis of various phosphorus species was possible by coupling chromatographic separations with mass spectrometry, using either electrospray or inductively coupled plasma ionization.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.193
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2019
Admission routes1
Has abstractyes

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