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Record W1969508988 · doi:10.4236/ijg.2013.41009

A Review of Some Experimental Spray Methods for Marine Cloud Brightening

2013· review· en· W1969508988 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Geosciences · 2013
Typereview
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsnot available
FundersFund for Innovative Climate and Energy ResearchPurdue UniversityUniversity of CalgaryNational Science Foundation
KeywordsCloud computingCapillary actionSubstrate (aquarium)CondensationMaterials sciencePolymerNanotechnologySeawaterComputer scienceGeologyComposite materialMeteorologyPhysicsOceanography

Abstract

fetched live from OpenAlex

Marine Cloud Brightening (MCB), should it ever need to be deployed, envisions the formation of 1017salt Cloud Condensation Nuclei (CCN) per second coming from each of several thousand vessels deployed worldwide. The creation of this many nuclei on such a vast scale, from micron- or submicron-sized seawater droplets, preferably mono-disperse, poses a considerable engineering challenge. Various existing or experimental spray methods were investigated for feasibility, resulting in the identification of a few with promising results. Electro-spraying from Taylor cone-jets, using either silicon micromachined long capillaries or short capillary polymer substrates attached to a porous substrate, appears to have the best potential for implementation of all the methods that have been investigated so far.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.385
Teacher spread0.358 · 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