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Record W4292952798 · doi:10.17760/d20429180

Environment-friendly and efficient hornet nest envelope-based photothermal absorber

2021· dissertation· en· W4292952798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsScience North
Fundersnot available
KeywordsSolar desalinationDesalinationEvaporationSeawaterEnvironmental sciencePhotothermal therapySolar stillDesiccationEnvironmental engineeringMaterials scienceNest (protein structural motif)HumidityEcologyNanotechnologyGeographyChemistryBiologyMeteorology

Abstract

fetched live from OpenAlex

Water shortage is a critical global issue that threatens human health, environmental sustainability, the preservation of Earth's climate. Desalination from seawater and sewage is a promising avenue for alleviating this stress. In this work, we use the hornet nest envelope material to fabricate a biomass-based photothermal absorber as part of a desalination isolation system. This system realizes an evaporation rate of 3.98 kg m-2 h-1 under one-sun illumination, with prolonged evaporation rates all above 4 kg m-2 h-1. This system demonstrates strong performance of 3.86 kg m-2 h-1 in 3.5 wt% saltwater, illustrating its effectiveness in evaporation seawater. Thus, with its excellent evaporation rate, great salt rejection ability, and easy fabrication approach, the hornet nest envelope constitutes a promising natural material for solar water treatment applications.--Author's abstract

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.012
GPT teacher head0.252
Teacher spread0.241 · 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

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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