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Record W7084388375 · doi:10.5281/zenodo.17241309

PUDL Raw EIA Form 930 -- Hourly and Daily Balancing Authority Operations Report

2025· dataset· en· W7084388375 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationRaw dataSoftwareRaw materialData sourceData exchangeData collection

Abstract

fetched live from OpenAlex

The EIA Form 930 provides hourly demand and generation statistics by balancing area (or sub-balancing area in the case of some larger areas). These statistics include a breakdown by energy source (coal, gas, hydro, wind, solar, etc.) as well as interchange between the balancing areas, including international exchanges with Canada and Mexico. Archived from https://www.eia.gov/electricity/gridmonitor/ This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into Frictionless Data Packages. For additional information about this data and PUDL, see the following resources: The PUDL Repository on GitHub PUDL Documentation Other Catalyst Cooperative data archives

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 categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.252
Teacher spread0.226 · 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.

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
Published2025
Admission routes1
Has abstractyes

Explore more

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