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Record W7144771964

Dynamic Spectra data of VLF/ELF measurements at Athabasca, Canada

2014· dataset· en· W7144771964 on OpenAlexaboutno aff
Kazuo Shiokawa, Mitsunori Ozaki, ISEE IUGONET Metadata Management Group

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2014
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSpectral lineAntenna (radio)MagnetometerSampling (signal processing)Sensitivity (control systems)Magnetic fieldField (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Dynamic spectra data (binary) of ISEE VLF/ELF antenna observation at Athabasca, Canada cooperated by the Athabasca University. 9min50s spectrum is available in every 10 min. The sampling frequency is 100 kHz, and the sensitivity has a peak at 8 kHz. ch:1(VLF-NS): E-W antenna measuring NS magnetic field variation, and ch:2(VLF-EW): N-S antenna measuring EW magnetic field variation. The original 1 datafile = 9min50s = 472,000,032Bytes.

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)0.001
metaresearch head score (Gemma)0.005
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.112
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.020
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0400.037

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 head0.045
GPT teacher head0.288
Teacher spread0.243 · 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
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

Citations0
Published2014
Admission routes1
Has abstractyes

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