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Record W4248422378 · doi:10.1002/bip.22612

Happy new year

2015· editorial· en· W4248422378 on OpenAlexaboutno aff
Joel P. Schneider

Bibliographic record

VenueBiopolymers · 2015
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsHonorLibrary sciencePublishingMarie curieArt historyClassicsPolitical scienceArtLawComputer science

Abstract

fetched live from OpenAlex

Dear Colleagues: A short note wishing all of you a happy and prosperous new year. I hope last year served all of you well. This coming year promises to be an exciting year for both the Journal and the American Peptide Society. In addition to a host of original research papers, the Journal will be publishing several outstanding special issues. The first, a collection of papers dedicated to Bill DeGrado on the occasion of his 60th birthday and his contributions to peptide and protein science. Special symposiums were held in his honor at the ACS meeting and at UCSF last fall. The second issue stems from the Peptides and Proteins Molecules of Life symposium held in Paris. The workshop was organized by Anna Maria Papini (University of Cergy- Pontoise), Solange Lavielle (Université Pierre et Marie Curie), and William Lubell (Université de Montreal, Québec). This year the Society will be holding its 24th symposium in sunny Orlando Florida co-chaired by Ved Srivastava, GlaxoSmithKline and Andei Yudin, University of Toronto. The program is shaping up nicely with key-note lectures from Richard Lerner, Scripps and Robert Grubbs, Caltech. With additional contributions from both academia and industry, the six-day meeting should prove to be excellent. Other meetings being held this year that will certainly be of interest include the 11th Australian Peptide Conference in Kingscliff, NSW as well as the Pacifichem 2015 in Hawaii. Best regards, Joel Schneider

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.023
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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 teacher head, not a consensus.

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
Published2015
Admission routes1
Has abstractyes

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