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Record W2745270820 · doi:10.2533/chimia.2017.511

13. Freiburger Symposium 2017: Green Chemistry – from Concept to Industrial Reality

2017· article· en· W2745270820 on OpenAlexfundno aff
Kerstin Bodmann, Roger Martí

Bibliographic record

VenueCHIMIA International Journal for Chemistry · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsnot available
FundersInstitute of Population and Public HealthDefense Advanced Research Projects AgencyInstitute for Basic ScienceKing Saud UniversityNational Research Foundation
KeywordsEnvironmental chemistryEnvironmental scienceChemistryAstrobiologyBiochemical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

of Industrial and Applied Chemistry -took place at the College of Engineering and Architecture in Fribourg (CH) on May 11 th and 12 th 2017.On the topic 'Green Chemistry -from Concept to Industrial Reality' a total of 14 lectures with industrial examples for sustainability in the chemical industry were presented during the two days of the symposium.Within the diverse program the keynote lecture of Dottikon Exclusive Synthesis CEO

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)0.001
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: Editorial · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0620.026

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 head0.280
Teacher spread0.252 · 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
GenreEditorial

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
Published2017
Admission routes1
Has abstractyes

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