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Record W2322898262 · doi:10.1103/physrevc.68.015206

Search for<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:mrow><mml:mi>K</mml:mi></mml:mrow><mml:mrow><mml:mi>−</mml:mi></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:mrow><mml:mover><mml:mrow><mml:mi>p</mml:mi></mml:mrow><mml:mrow><mml:mo>→</mml:mo></mml:mrow></mml:mover></mml:mrow></mml:mrow><mml:mrow><mml:msup><mml:mrow><mml:mi>π</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:msup><mml:mrow><mml:mi>π</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msup></mml:mrow><mml:mrow><mml:msup><mml:mrow><mml:mi>π</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msup></mml:mrow><mml:mi>Λ</mml:mi></mml:math>from threshold to<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>p</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:msup><mml:mrow><mml:mi>K</mml:mi></mml:mrow><mml:mrow><mml:mi>−</mml:mi></mml:mrow></mml:msup></mml:mrow></mml:mrow></mml:msub></mml:mrow><mml:mo>=</mml:mo><mml:mn>750</mml:mn><mml:mn/><mml:mi/><mml:mi mathvariant="normal">MeV</mml:mi><mml:mo>/</mml:mo><mml:mi>c</mml:mi></mml:math>

2003· article· lv· W2322898262 on OpenAlexaff
M. Borgh, S. Prakhov, B. M. K. Nefkens, C. Allgower, V. Bekrenev, W. J. Briscoe, M. Clajus, J. R. Comfort, K. Craig, D. Grosnick, D. Isenhower, N. S. Knecht, D. D. Koetke, A. Koulbardis, N. Kozlenko, S. P. Kruglov, G. J. Lolos, I. Lopatin, D. M. Manley, R. Manweiler, A. Marušić, S. McDonald, J. Olmsted, Z. Papandreou, D. C. Peaslee, N. Phaisangittisakul, J. W. Price, A. F. Ramirez, M. E. Sadler, A. Shafi, H. Spinka, T. D. S. Stanislaus, A. Starostin, H. M. Staudenmaier, I. Supek, W. B. Tippens

Bibliographic record

VenuePhysical Review C · 2003
Typearticle
Languagelv
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of Regina
FundersSLAC National Accelerator LaboratoryUppsala UniversitetSwedish Foundation for International Cooperation in Research and Higher Education
KeywordsComputer scienceAlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

The results of a search for ${K}^{\ensuremath{-}}\stackrel{\ensuremath{\rightarrow}}{p}{\ensuremath{\pi}}^{0}{\ensuremath{\pi}}^{0}{\ensuremath{\pi}}^{0}\ensuremath{\Lambda}$ (where the $3{\ensuremath{\pi}}^{0}$'s are not from $\ensuremath{\eta}$-meson decay) are presented. The data were obtained with the Crystal Ball spectrometer at eight beam momenta from 514 to $750\mathrm{MeV}/c.$ For the six beam momenta below ${p}_{{K}^{\ensuremath{-}}}=714\mathrm{MeV}/c,$ no signal was found; the 90% C.L. upper limit obtained for the ${K}^{\ensuremath{-}}\stackrel{\ensuremath{\rightarrow}}{p}3{\ensuremath{\pi}}^{0}\ensuremath{\Lambda}$ total cross section ${\ensuremath{\sigma}}_{t}$ varies between 2 and $7\ensuremath{\mu}\mathrm{b}.$ This small upper limit is indicative that spontaneous ${\ensuremath{\pi}}^{0}$ emission is insignificant, since the ${K}^{\ensuremath{-}}\stackrel{\ensuremath{\rightarrow}}{p}{\ensuremath{\pi}}^{0}{\ensuremath{\pi}}^{0}{\ensuremath{\pi}}^{0}\ensuremath{\Lambda}$ threshold is at ${p}_{{K}^{\ensuremath{-}}}=397\mathrm{MeV}/c.$ A signal was observed only at ${p}_{{K}^{\ensuremath{-}}}=750\mathrm{MeV}/c,$ with ${\ensuremath{\sigma}}_{t}=25\ifmmode\pm\else\textpm\fi{}7\ensuremath{\mu}\mathrm{b}.$ These results can be explained only if triple ${\ensuremath{\pi}}^{0}$ production goes predominantly by hyperon resonance deexcitation, ${K}^{\ensuremath{-}}\stackrel{\ensuremath{\rightarrow}}{p}{\ensuremath{\Sigma}}^{*}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}{\ensuremath{\Lambda}}^{*}.$ There are several candidates for the ${\ensuremath{\Sigma}}^{*}$ but only one for the ${\ensuremath{\Lambda}}^{*},$ namely, the $\ensuremath{\Lambda}(1520){\frac{3}{2}}^{\ensuremath{-}},$ as the threshold for ${K}^{\ensuremath{-}}\stackrel{\ensuremath{\rightarrow}}{p}{\ensuremath{\pi}}^{0}\ensuremath{\Lambda}(1520)$ is at ${p}_{{K}^{\ensuremath{-}}}=704\mathrm{MeV}/c.$

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)0.016
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.020
Meta-epidemiology (narrow)0.0080.019
Meta-epidemiology (broad)0.0030.019
Bibliometrics0.0070.013
Science and technology studies0.0130.018
Scholarly communication0.0140.013
Open science0.0220.019
Research integrity0.0210.017
Insufficient payload (model declined to judge)0.9820.018

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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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 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

Citations7
Published2003
Admission routes1
Has abstractyes

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Same venuePhysical Review CSame topicMedical Imaging Techniques and ApplicationsFrench-language works237,207