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Record W4409799851 · doi:10.11159/iceptp25.142

Microbial Fuel Cells from Artichoke Waste: Preliminary Results

2025· article· en· W4409799851 on OpenAlexvenueno aff
Luis Cabanillas-Chirinos, Nélida Milly Otiniano, Terrones-Rodriguez Nicole

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsnot available
Fundersnot available
KeywordsMicrobial fuel cellWaste managementEnvironmental scienceChemistryEngineering

Abstract

fetched live from OpenAlex

Agricultural waste has increased rapidly in recent years due to increased food production, which has risen due to the increase in the world population.On the other hand, the high cost of energy consumption and scarcity of this sound in remote communities has caused the scientific community to look for new ways to sustain electricity.For this reason, the main objective of this research is to observe the potential of artichoke waste as fuel in single-chamber microbial fuel cells using carbon and zinc electrodes.An average maximum power density of 220.271 11.174 mW/cm 2 was achieved in an average current density of 5.841 0.285 A/cm 2 on the tenth day, with an average maximum voltage of 0.795 0.025 V and an average maximum electric current of 1.980 0.0.072mA.These electric flies were obtained on the tenth day, where the microbial fuel cells operated at a pH of 4.351 0.161 with an electrical conductivity of 127.844 8.512 mS/cm and an electrical resistance of 40.314 6.813 .The single-chamber microbial fuel cells with artichoke waste were connected in series, producing a 2.35 V voltage necessary to light an LED light.

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)0.000
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 score0.094
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.174
Teacher spread0.171 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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