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Record W4254510323 · doi:10.1002/pro.2779

Issue information ‐ Copyright and Table of Contents

2016· paratext· en· W4254510323 on OpenAlexaff
Brian W. Matthews, Hans Neurath, Hideo Akutsu, Dorothy Beckett, M.G. Gruetter, R. L. Levy, Albert J. R. Heck, Yigong Shi, D.H. Juers, Serena Wiley, İvet Bahar, P. Balaram, Maurizio Brunori, Zengyi Chang, Roberto A. Chica, David W. Christianson, Robert A. Copeland, Andrew Doig, Arne Elofsson, A.E. Sauer-Eriksson, Mark Gerstein, Lila M. Gierasch, Rudi Glockshuber, Yuji Goto, Gerald L. Hazelbauer, Yoshiki Higuchi, Mei Hong, A. Joachimiak, Igor A. Kaltashov, Amy E. Keating, Alain Krol, Olivier Lichtarge, Andreas Matouschek, Stephen Matthews, Hiroyuki Noji, Michael F. Parker, Kevin W. Plaxco, Carol Beth Post, Ronald T. Raines, Daniel P. Raleigh, Christina Redfield, Robert G. Russell, Fred Salsbury, Robert T. Sauer, Brenda A. Schulman, Kevan M. Shokat, Jeffrey Skolnick, Brian D. Sykes, Dan S. Tawfik, Jill Trewhella, Vladimir N. Uversky, Xinquan Wang, James Wells, Ann West, Keith S. Wilson, Stephen G. Withers, Cynthia Wolberger, Todd O. Yeates, Hanna S. Yuan, Xuejun Zhang

Bibliographic record

VenueProtein Science · 2016
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaDiscovery CentreUniversity of Ottawa
Fundersnot available
KeywordsTable (database)CitationTable of contentsComputer scienceInformation retrievalWorld Wide WebLibrary scienceDatabase

Abstract

fetched live from OpenAlex

Protein Science, the flagship journal of The Protein Society, serves an international forum for publishing original reports on all scientific aspects of protein molecules. The Journal publishes papers by leading scientists from all over the world that report on advances in the understanding of proteins in the broadest sense. Protein Science aims to unify this field by cutting across established disciplinary lines and focusing on “protein-centered” science.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.072
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.088

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 head0.219
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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