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Record W2210130261 · doi:10.1073/pnas.1514034112

Sea spray aerosol as a unique source of ice nucleating particles

2015· article· en· W2210130261 on OpenAlexaff
Paul J. DeMott, Thomas C. J. Hill, Christina S. McCluskey, Kimberly A. Prather, Douglas B. Collins, Ryan C. Sullivan, Matthew J. Ruppel, Ryan H. Mason, Victoria E. Irish, Taehyoung Lee, Chung Yeon Hwang, Tae Siek Rhee, Jefferson R. Snider, G. R. McMeeking, Suresh Dhaniyala, Ernie R. Lewis, Jeremy J. B. Wentzell, Jonathan P. D. Abbatt, Christopher Lee, Camille M. Sultana, Andrew P. Ault, Jessica L. Axson, Myrelis Diaz Martinez, I. Venero, G. Santos-Figueroa, M. Dale Stokes, Grant B. Deane, O. L. Mayol‐Bracero, Vicki H. Grassian, Timothy H. Bertram, Allan K. Bertram, Bruce F. Moffett, Gary D. Franc

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of TorontoEnvironment and Climate Change CanadaUniversity of British Columbia
FundersKorea Polar Research InstituteU.S. Department of EnergyNational Science Foundation
KeywordsAerosolSea sprayIce nucleusEnvironmental scienceOceanographyAtmospheric sciencesMeteorologyGeologyNucleationGeographyChemistry

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 studies0.0000.000
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 head0.044
GPT teacher head0.269
Teacher spread0.225 · 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 designObservational
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

Citations670
Published2015
Admission routes1
Has abstractyes

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