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Record W4394161691 · doi:10.6084/m9.figshare.21382502

Additional file 5 of The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

2022· dataset· en· W4394161691 on OpenAlexaff
Hiba Mohammed Taha, Reza Aalizadeh, ‪Nikiforos Alygizakis, Jean‐Philippe Antignac, Hans Peter H. Arp, Richard Bade, Nancy Baker, Lidia Belova, Lubertus Bijlsma, Evan Bolton, Werner Brack, Alberto Celma, Wen‐Ling Chen, Tiejun Cheng, Parviel Chirsir, Ľuboš Čirka, Lisa A. D’Agostino, Yannick Djoumbou-Feunang, Valeria Dulio, Stellan Fischer, Pablo Gago-Ferrero, Aikaterini Galani, Birgit Geueke, Natalia Głowacka, Juliane Glüge, Ksenia J. Groh, Sylvia Grosse, Peter Haglund, Pertti J. Hakkinen, Sarah E. Hale, Félix Hernández, Elisabeth M.‐L. Janssen, Tim Jonkers, Karin Kiefer, Michal Kirchner, Jan Koschorreck, Martin Krauß, Jessy Krier, M.H. Lamoree, Marion Letzel, Thomas Letzel, Qingliang Li, James J. Little, Yanna Liu, David M. Lunderberg, Jonathan W. Martin, Andrew D. McEachran, John A. McLean, Christiane Meier, Jeroen Meijer, Frank Menger, Carla Merino, Jane Muncke, Matthias Muschket, Michael Neumann, Vanessa Neveu, Kelsey Ng, Herbert Oberacher, Jake O’Brien, Peter Oswald, Martina Oswaldova, Jaqueline A. Picache, Cristina Postigo, Noelia Ramírez, Thorsten Reemtsma, Justin B. Renaud, Paweł Rostkowski, Heinz Rüdel, Reza M. Salek, Saer Samanipour, Martin Scheringer, Ivo Schliebner, W. Schulz, Tobias Schulze, Manfred Sengl, Benjamin A. Shoemaker, Kerry Sims, Heinz Singer, Randolph R. Singh, Mark W. Sumarah, Paul Thiessen, Kevin V. Thomas, Sònia Torres, Xenia Trier, Annemarie P. van Wezel, Roel Vermeulen, Jelle Vlaanderen, Peter C. von der Ohe, Zhanyun Wang, Antony Williams, Egon Willighagen, David S. Wishart, Jian Zhang, Νikolaos S. Τhomaidis, Juliane Hollender, Jaroslav Slobodnı́k, Emma Schymanski

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsUniversity of AlbertaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSuspectComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Additional file 5: Authorship contributions and acknowledgements mapped to NORMAN-SLE lists (XLSX format).

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)0.002
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.558
Threshold uncertainty score0.630

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.5580.131

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 head0.253
Teacher spread0.236 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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