MétaCan
Menu
Back to cohort

Role of clusters in nuclear astrophysics with Cluster Nucleosynthesis Diagram (CND)

2013· article· en· W1969261266 on OpenAlexaff
S. Kubono, Dam Nguyen Binh, S. Hayakawa, Hiroyuki Hashimoto, D. Kahl, H. Yamaguchi, Y. Wakabayashi, T. Teranishi, N. Iwasa, T. Komatsubara, S. Kato, A. Chen, S. Cherubini, Seonho Choi, I. S. Hahn, J. J. He, L. H. Khiem, C. S. Lee, Y. K. Kwon, Shinya Wanajo

Bibliographic record

VenueJournal of Physics Conference Series · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNucleosynthesisStellar nucleosynthesisPhysicsSupernovaAstrophysicsStellar evolutionCluster (spacecraft)Nuclear reactionNuclear fusionNuclear astrophysicsBig Bang nucleosynthesisAstronomyStarsNuclear physics

Abstract

fetched live from OpenAlex

FreeSASA is an open source library and command line tool to calculate the solvent accessible surface areas of protein molecules. The library is as fast and accurate as existing tools, with the advantage of being open source and available as both a library, a command line tool and it has Python bindings. Until there is a formal publication for this project use of FreeSASA can be cited using this DOI or that of later versions. Changes in this version: Output now doesn't repeat the parameters section if several calculations are made. Therefore the input section has been separated from parameters. To make this possible the function freesasa_log() has been deprecated and replaced by freesasa_write_parameters() and freesasa_write_result(). A bug where unrecognized long-options caused seg-faults has been fixed. Errors when from fprint() are now caught more consistently throughout the library. CLI documentation has been expanded with a more elaborate example.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.224
Teacher spread0.215 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Physics Conference SeriesSame topicNuclear physics research studiesFrench-language works237,207