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Record W2587517335 · doi:10.1021/acs.est.6b04947

The Essential Role for Laboratory Studies in Atmospheric Chemistry

2017· article· en· W2587517335 on OpenAlexaff
James B. Burkholder, Jonathan P. D. Abbatt, Ian Barnes, J. M. Roberts, Megan L. Melamed, Markus Ammann, Allan K. Bertram, Christopher D. Cappa, Annmarie G. Carlton, Lucy J. Carpenter, John N. Crowley, Yael Dubowski, C. George, Dwayne E. Heard, Hartmut Herrmann, Frank N. Keutsch, Jesse H. Kroll, V. Faye McNeill, N. L. Ng, Sergey A. Nizkorodov, John J. Orlando, Carl J. Percival, Bénédicte Picquet‐Varrault, Yinon Rudich, Paul W. Seakins, Jason D. Surratt, Hiroshi Tanimoto, Joel A. Thornton, Geoffrey S. Tyndall, Andreas Wahner, Charles J. Weschler, Kevin Wilson, Paul J. Ziemann

Bibliographic record

VenueEnvironmental Science & Technology · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersNational Oceanic and Atmospheric Administration
KeywordsAtmospheric chemistryAtmosphere (unit)Air pollutionAir quality indexHuman healthEnvironmental scienceClimate changeEnvironmental resource managementEnvironmental planningOzoneMeteorologyEcologyGeographyEnvironmental healthBiology

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 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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score1.000

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 studies0.0020.005
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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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

Citations157
Published2017
Admission routes1
Has abstractyes

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