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Record W6929203315 · doi:10.48322/gpwf-9m90

ISIS-2 Topside Sounder Average Ionogram over Sodankyla, Finland: SOD, Latitude 67, Longitude 27

2024· dataset· en· W6929203315 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2024
Typedataset
Languageen
FieldComputer Science
TopicExplainable Artificial Intelligence (XAI)
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsIonogramLongitudeIonosphereIonosondeLatitudeAmplitudeDepth sounding

Abstract

fetched live from OpenAlex

These Ionograms were digitized from the original ISIS-2 7-Track Analog Telemetry Tapes using the Facilities of the former Data Evaluation Laboratory at the NASA/GSFC. This Data Restoration Project is headed by Dr. R.F. Benson (NASA/GSFC). Ionograms were digitized at the Rate of 40,000 16-bit samples/s. This Sample Rate is higher than the Nyquist Frequency of 30 kHz. The Sample Frequency of 40 kHz provides a Measurement every 25 µs corresponding to an Apparent Range Interval equal to 3.75 km from c*t/2, where c is the Speed of Light. Ionograms with this Sample Rate are designated as 'Full' Ionograms because they have the full 3.75 km Apparent-Range Resolution. The Ionograms used for most Analyses, and those available from CDAWeb, were produced by averaging every four Samples of the Sounder-Receiver Video Amplitude Output to yield an average Value every 100 µs corresponding to an Apparent-Range Resolution of 15 km. These Ionogram Files are referred to as 'Average' Files with Standard Resolution. Each Ionogram consists of a Fixed-Frequency Portion and a Swept-Frequency Portion. The Time Resolution between Ionograms is typically 14 or 22 s depending on the Frequency Sweep Range.

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), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.080
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 communication0.0050.002
Open science0.0070.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.088

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 head0.050
GPT teacher head0.344
Teacher spread0.294 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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