MétaCan
Menu
Back to cohort
Record W272690673 · doi:10.2172/1040698

Final Report to DOE

2012· report· en· W272690673 on OpenAlexaff
Ismail Gültepe

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsAerosolEnvironmental scienceMeteorologyMinor (academic)Computer scienceOperations researchClimatologyGeographyEngineeringPolitical scienceGeology

Abstract

fetched live from OpenAlex

This final report summarizes the accomplished goals and provide a list of the publications and presentations made during the project. The goals of the project were accomplished through the various publications submitted to Journals and presentations done at the DOE and international meetings and conferences. The 8 journal articles related to the goals of this project were accepted or submitted. The 23 presentations related to goals of the project were presented at the meetings. There were some minor changes regarding to project goals because of issues encountered during the analysis of the data. For example, a total water probe sensor mounted on the Convair-580 that can be used for defining mixed phase conditions and parameterization, had some problems to estimate magnitude of total water mass, and this resulted in issues providing an accurate parameterization for cloud fraction. Variability related aerosol number concentrations and their composition for direct and indirect effects were studied and published. Results were given to explain aerosol and ice microphysical effects on climate change studies. It is suggested that developed parameterizations should consider the variability in aerosol and ice parameters over the Arctic regions.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.113
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1130.060

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 head0.085
GPT teacher head0.293
Teacher spread0.207 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicIcing and De-icing TechnologiesFrench-language works237,207