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Record W3032476399 · doi:10.1186/s12302-020-00340-7

Obituary for Tamara Grummt

2020· article· en· W3032476399 on OpenAlexaff
Thomas Braunbeck, Lothar Erdinger, Fritz H. Frimmel, Henner Hollert, Siegfried Knasmüller, David M. DeMarini, Michael J. Plewa, Susan D. Richardson, Rita Triebskorn, Gisela de Aragão Umbuzeiro, Paul A. White

Bibliographic record

VenueEnvironmental Sciences Europe · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsHealth Canada
Fundersnot available
KeywordsBathingObituaryEnvironmental ethicsEcologyGeographyBiologyArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Tamara Grummt passed away on January 26, 2020 in Oelsnitz/Vogtland, Germany. Tamara was one of the scientific pioneers in the field of environmental toxicology, namely genotoxicity and hygiene of drinking and bathing waters. Her passing is not only a great loss to environmental research and to the global environmental toxicology community—we have lost an outstanding personality with the heart in the right place, who has become, for many of us, a wonderful friend.

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)0.001
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.277
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.2770.160

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 head0.017
GPT teacher head0.196
Teacher spread0.180 · 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
Published2020
Admission routes1
Has abstractyes

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