MétaCan
Menu
Back to cohort
Record W4408320353 · doi:10.1002/ppj2.70020

Use of arduino‐based potentiometric sensors to measure changes in leaf apoplastic pH in common bean ( <i>Phaseolus vulgaris</i> L.)

2025· article· en· W4408320353 on OpenAlexaff
Robert McGee, Jennifer Lin, Ravinder Dahiya, Valerio Hoyos‐Villegas

Bibliographic record

VenueThe Plant Phenome Journal · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhaseolusPotentiometric titrationMeasure (data warehouse)ArduinoApoplastHorticultureChemistryBotanyBiologyComputer scienceData miningElectrode

Abstract

fetched live from OpenAlex

Abstract Following an abiotic or biotic stress, the pH of the extracellular space or the apoplast of a plant can change dramatically, such as wounding that causes an increase in pH or alkalinization. In this proof‐of‐concept‐study, a newly developed carbon‐based bendable potentiometric sensor was tested for the first time in vivo on common bean ( Phaseolus vulgaris L.). The sensor was able to detect the same magnitude and direction of pH change after wounding as the conventional infiltration‐centrifugation method in five out of eight tested common bean cultivars. This highly scalable, non‐destructive, and cheap carbon‐based sensor could be used in the future within plant breeding to screen large populations of plants for responses to plant stresses.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.240
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 teacher head, 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueThe Plant Phenome JournalSame topicAnalytical Chemistry and SensorsFrench-language works237,207