MétaCan
Menu
Back to cohort
Record W4399205964 · doi:10.1109/lsens.2024.3407928

Planar Ag/AgCl Reference Electrode for Electrochemical Agronomic Sensors

2024· article· en· W4399205964 on OpenAlexaff
Sreenivasulu Mamilla, Shah Zahid Yousuf, Madan Mohan Avulapati, Ahmed-Al Mallahi, N. V. L. Narasimha Murty

Bibliographic record

VenueIEEE Sensors Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrodePlanarMaterials scienceReference electrodeElectrochemistryOptoelectronicsChemistryComputer sciencePhysical chemistry

Abstract

fetched live from OpenAlex

Robust, stable, and portable planar reference electrodes that perform analogous to conventional Ag/AgCl reference electrodes are of paramount importance for any electrochemical soil sensors like soil pH and NPK sensors. This letter reports the fabrication and characterization of planar Ag/AgCl Reference Electrode (PARE) with Graphene Conductive Ink (GCI) as a protective layer. For its application in soil agronomy, the fabricated PARE is exclusively tested in soil solutions with different pH, 1 M KCl and pH buffer solutions. The fabricated PARE exhibited a drift of ±3 mV in pH buffers and is relatively insensitive to changes in pH. The drift in the open circuit potential of the PARE without GCI is found to be ±10.02 mV for a period of 72 hours in 1 M KCl, whereas the drift with GCI is significantly reduced to ± 0.98 mV resulting in a stable response. Furthermore, electrochemical impedance spectroscopic studies are performed to examine the protective layer's contribution to sustaining electrode stability over extended periods of time. Finally, the PARE is proven to be stable, exhibiting minimal drift for varying soil pH levels, indicating its potential as a stable reference electrode for agronomic applications.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Sensors LettersSame topicElectrochemical sensors and biosensorsFrench-language works237,207