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Record W4416366136 · doi:10.21203/rs.3.rs-7925497/v1

The inner-shell ionization and fragmentation of selenophene at 120 eV

2025· preprint· en· W4416366136 on OpenAlexafffund
Tiffany Walmsley, Felix Allum, James Harries, Yoshiaki Kumagai, Joseph McManus, Kiyonobu Nagaya, Mathew Britton, M. Brouard, P. H. Bucksbaum, Mizuho Fushitani, Ian Gabalski, T. Gejo, Paul Hockett, Andrew J. Howard, Hiroshi Iwayama, Edwin Kukk, C.C. Lam, Russell S. Minns, Akinobu Niozu, Sekito Nishimuro, Johannes Niskanen, Shigeki Owada, Weronika O. Razmus, Daniel Rolles, James Somper, Kiyoshi Ueda, James Unwin, S. Wada, Joanne L. Woodhouse, Ruaridh Forbes, Michael Burt, Emily M. Warne

Bibliographic record

VenueResearch Square · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsTrent UniversityNational Research Council Canada
FundersSLAC National Accelerator LaboratoryJapan Society for the Promotion of ScienceJesus College, University of OxfordJesus College, University of CambridgeBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaOffice of ScienceUniversity of OxfordUK Research and InnovationEngineering and Physical Sciences Research CouncilUniversity of SouthamptonLeverhulme TrustAlexander von Humboldt-StiftungU.S. Department of EnergyChemical Sciences, Geosciences, and Biosciences DivisionNational Science Foundation
KeywordsFragmentation (computing)IonizationHeteroatomChemical ionizationThiopheneSeleniumElectron ionizationIonization energy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.027
GPT teacher head0.370
Teacher spread0.343 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2025
Admission routes2
Has abstractno

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