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Record W6955584668 · doi:10.5880/intermagnet.1991.2018

Intermagnet Reference Data Set (IRDS) 2018 – Definitive Magnetic Observatory Data

2021· dataset· en· W6955584668 on OpenAlexaff

Bibliographic record

VenueGFZ Data Services · 2021
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsData setSet (abstract data type)Data qualitySection (typography)Data fileObservatoryReference dataDigital data

Abstract

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Definitive digital values of the Earth's mangetic field recorded during 1991..2018 at INTERMAGNET observatories around the world. Data includes minute, hourly and daily vector values, along with observatory baseline values for quality control. K indices and annual means are also included. All data is included on the single downloadable archive files. This is the 28th annual publication in the series. Beginning with the publication of the definitive data for 2015, INTERMAGNET stopped publishing individual years of data and started publishing the entire, cumulative definitive data set since INTERMAGNET’s first recorded definitive data in 1991. This data set is known as the "INTERMAGNET Reference Data Set" (IRDS). The IRDS comprises all INTERMAGNET one-minute definitive data since 1991 and is annually updated with a new year and occasional corrections to previous releases. Some national data institutions may have related DOIs that describe subsets of the data. These DOIs are shown under "Related DOIs to be quoted". File names for IRDS data are formatted in the form mag_def.zip. The mag section of the filename describes the year in which the data was recorded. The def section of the filename describes the most recent annual INTERMAGNET publication in which the data was updated. Files where mag = def have had no corrections since their original publication. For example, "mag2015_def2016" indicates that this file is different from the first release "mag2015_def2015". For more information on the data formats used in this publication and the technical standards used to create the data, please refer to the INTERMAGNET Technical Manual (https://doi.org/10.48440/INTERMAGNET.2020.001).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.131
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0250.010
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.003

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 head0.150
GPT teacher head0.293
Teacher spread0.143 · 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 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

Citations7
Published2021
Admission routes1
Has abstractyes

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