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Record W4403463711 · doi:10.25080/frkj7844

Pooch: A friend to fetch your data files

2024· dataset· en· W4403463711 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typedataset
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFetchComputer scienceGeologyOceanography

Abstract

fetched live from OpenAlex

Pooch is a Python library that can download and locally cache files from the web without hassle. Novices can use it to simply download files in one line of code and focus on the data. Package maintainers can use it to provide sample datasets to their users, in examples and tutorials, as libraries like SciPy, scikit-image, napari and MetPy do. During this talk, we'll show you how you can use the different features that Pooch offers and also how you can extend its capabilities by writing your own downloaders or post-processors.More information in: https://github.com/santisoler/scipy2024-pooch

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.

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 categoriesInsufficient 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 score0.110
Threshold uncertainty score0.979

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0040.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.022

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 head0.069
GPT teacher head0.348
Teacher spread0.279 · 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