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Record W3047902437 · doi:10.1149/1945-7111/abad6c

Review—Potentiometric Determination of Phosphate Using Cobalt: A Review

2020· review· en· W3047902437 on OpenAlexafffund
Reem Zeitoun, Asim Biswas

Bibliographic record

VenueJournal of The Electrochemical Society · 2020
Typereview
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Economic Development, Job Creation and Trade
KeywordsCobaltPotentiometric titrationPhosphateElectroanalytical methodZirconium phosphateInorganic chemistryElectrochemistryChemistryElectrodeMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Inorganic phosphorus (orthophosphate) determination is crucial within environmental applications. Conventional accredited measurement methods of orthophosphate provide accurate measurements for a limited number of samples due to cost, time, and labor involved with laboratory analysis and are insufficient to characterize phosphate variability within environmental applications. Precise electrochemical sensing has the potential to provide accurate phosphate measurements and has the advantage of being inexpensive to produce and portable. Cobalt is a robust metal that has shown a unique selectivity towards phosphate in potentiometric sensors. In this manuscript, we reviewed the cobalt phosphate ion-selective electrodes with cobalt matrices in the form of pure metal, microelectrode, thin-film, and heterogeneous metal membrane in building integrated probes for determining phosphate concentrations in aqueous solutions. We reviewed different proposals of the cobalt-phosphate chemical reactions on the electrode surface, the factors affecting the stability of the phosphate measurement, and the success stories in the form of the limit of detection, linear range, and sensitivity. With strong progress in recent decades, we restricted ourselves at the time between 1995 and 2018. We discussed future opportunities of cobalt sensors towards more reliable phosphate sensing using novel approaches like cobalt alloys, three in one cobalt phosphate sensors, and external interference elimination methods.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.032
GPT teacher head0.315
Teacher spread0.282 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations42
Published2020
Admission routes2
Has abstractyes

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