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Record W2966852171 · doi:10.1145/3332186.3332196

IceCube's Long Term Archive Software

2019· article· en· W2966852171 on OpenAlexfundno aff
Patrick Meade, Benedikt Riedel, David Schultz

Bibliographic record

VenueProceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceDeutsches Elektronen-SynchrotronNatural Sciences and Engineering Research Council of CanadaOffice of Polar ProgramsCollege of Engineering, Michigan State UniversityInstitute for Global Prominent Research, Chiba UniversityRWTH Aachen UniversityChiba UniversityKnut och Alice Wallenbergs StiftelseVillum FondenNational Research Foundation of KoreaFonds Wetenschappelijk OnderzoekMarsden FundBundesministerium für Bildung und ForschungHelmholtz Alliance for Astroparticle PhysicsDanmarks GrundforskningsfondSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science FoundationBelgian Federal Science Policy OfficeDeutsche ForschungsgemeinschaftMichigan State UniversityNational Research FoundationWestern Canada Research GridFonds De La Recherche Scientifique - FNRSPolarforskningssekretariatetCompute CanadaMarquette UniversityUniversity of Wisconsin-MadisonU.S. Department of EnergyVetenskapsrådet
KeywordsTerm (time)SoftwareRaw dataComputer scienceEvent (particle physics)Data centerNeutrinoData archiveAstronomyDatabasePhysicsOperating systemParticle physicsAstrophysics

Abstract

fetched live from OpenAlex

IceCube is a cubic kilometer neutrino detector located at the South Pole. It generates 1 TiB of raw data per day, which must be archived for possible retrieval years or decades later. Other low-level data products are also archived for easy retrieval in the event of a catastrophic data center failure. The Long Term Archive software is IceCube's answer to archiving this data across several computing sites.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.124
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0060.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1240.106

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 head0.013
GPT teacher head0.327
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreSoftware

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
Published2019
Admission routes1
Has abstractyes

Explore more

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