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Record W7082004057 · doi:10.11159/icert25.140

Implementation of an Algal-Voltaic Energy Center in the Fishing Port of Pachacutec City

2025· article· en· W7082004057 on OpenAlexvenueno aff

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)FishingCenter (category theory)Energy (signal processing)Energy consumption

Abstract

fetched live from OpenAlex

This article explores the feasibility of a hypothetical project using algae-based solar panels to generate energy in Ventanilla, considering the associated technical, social, and environmental factors.The proposed design integrates modular "bioreactor" systems within traditional photovoltaic structures, optimizing the use of urban space and leveraging local resources such as treated wastewater and carbon dioxide emitted by nearby industrial sources.These algavoltaic panels not only produce electricity from sunlight; they also allow the cultivation of microalgal biomass, which can be transformed into biofuels, bioplastics, or fertilizers.This has a positive impact on the circular economy.Throughout the development of this theoretical project, multiple aspects are analyzed, from the selection of microalgae species adapted to Lima's desert climate to the implementation of automated monitoring systems to optimize photosynthetic productivity.The potential impact in terms of CO₂ emission reduction and energy supply to communities is also assessed.The study also addresses the importance of involving the local community in the design and management of the project; this ensures its social acceptance and long-term sustainability.In this regard, the implementation of educational programs on renewable energy is crucial.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on New TechnologiesSame topicMarine and coastal ecosystemsFrench-language works237,207