MétaCan
Menu
Back to cohort
Record W2369111289

Reviews of Presidential Green Chemistry Challenge Awards of USA in 2010

2010· article· en· W2369111289 on OpenAlexaff
Pan Yi

Bibliographic record

VenueFain kemikaru · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChemistryManagementChemical companyChemical industryPresidential systemEngineeringPolitical sciencePolymer scienceOrganic chemistryLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

The innovation and benefits of five awards and winners of the US Presidential Green Chemistry Challenge(PGCC) Awards Program in 2010 are introduced:①The Dow Chemical Company and BASF Chemical Company were awarded greener synthetic pathways award because of their innovative,environmentally benign production of Propylene Oxide via Hydrogen Peroxide. ②Merck Co.,Inc. and Codexis,Inc. were awarded greener reaction conditions award because of their greener manufacturing of Sitagliptin enabled by an evolved Transaminase.③The Clarke Company was awarded designing greener chemicals award because of NatularTM Larvicide: adapting Spinosad for Next-Generation mosquito control.④LS9,Inc. was awarded small business award because of microbial production of renewable PetroleumTM Fuels and Chemicals.⑤Ph.D. J.C. Liao of University of California,Los Angeles was awarded academic award because of his Recycling Carbon Dioxide to Biosynthesize Higher Alcohols.

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)0.003
metaresearch head score (Gemma)0.008
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: Review · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0450.016

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 head0.215
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
GenreReview

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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueFain kemikaruSame topicChemistry and Chemical EngineeringFrench-language works237,207