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Record W4205855063 · doi:10.1016/j.nds.2019.100524

Nuclear Data Sheets for A=218

2019· article· en· W4205855063 on OpenAlexaff
Balraj Singh, M. S. Basunia, M.J. Martin, E. A. McCutchan, Indu Bala, R. Caballero-Folch, R. Canavan, R. Chakrabarti, A. Chekhovska, M. Grinder, S. Kaim, D. Kanjilal, D. V. Kasperovych, Mst Jannatul Kobra, H. Koura, S. Nandi, A. Olăcel, A. P. Singh, B.P.E. Tee

Bibliographic record

VenueNuclear Data Sheets · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsTRIUMFMcMaster University
FundersLawrence Berkeley National LaboratoryOak Ridge National LaboratoryOffice of ScienceInternational Atomic Energy AgencyNuclear PhysicsAbdus Salam International Centre for Theoretical PhysicsU.S. Department of Energy
KeywordsNuclideExcited stateNuclear structureNuclear dataPhysicsNuclear physicsDipoleAtomic physicsGround stateNeutron

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)0.002
metaresearch head score (Gemma)0.015
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 score0.525
Threshold uncertainty score0.678

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5250.439

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 head0.073
GPT teacher head0.338
Teacher spread0.265 · 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

Citations17
Published2019
Admission routes1
Has abstractno

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