MétaCan
Menu
← Back to cohort
Record W6930527908 · doi:10.5281/zenodo.10211675

Uproot

2023· other· en· W6930527908 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typeother
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsExecutorSerializationByteJSONSource codeObject (grammar)HeaderCover (algebra)Scheme (mathematics)

Abstract

fetched live from OpenAlex

New features feat: improve uri scheme parsing with list of available schemes from fsspec by @lobis in https://github.com/scikit-hep/uproot5/pull/1009 feat: use only loop executor for fsspec source by @lobis in https://github.com/scikit-hep/uproot5/pull/999 feat: modify how multipart bytes header is built (no space) on http source by @lobis in https://github.com/scikit-hep/uproot5/pull/1018 feat: basic fsspec writing by @lobis in https://github.com/scikit-hep/uproot5/pull/1016 feat: correct fsspec source serialization by @lobis in https://github.com/scikit-hep/uproot5/pull/1033 Bug-fixes and performance fix: url and object splitting for local files by @lobis in https://github.com/scikit-hep/uproot5/pull/1007 fix: s3 source options and repr by @lobis in https://github.com/scikit-hep/uproot5/pull/1024 fix: processing of pathlib.Path argument for writing by @lobis in https://github.com/scikit-hep/uproot5/pull/1031 fix: multithreaded file source breaks interpretation by @lobis in https://github.com/scikit-hep/uproot5/pull/1036 Other test: local http server for tests by @lobis in https://github.com/scikit-hep/uproot5/pull/1010 test: testing sshfs with local ssh server by @lobis in https://github.com/scikit-hep/uproot5/pull/1013 test: use paramiko for ssh instead of sshfs by @lobis in https://github.com/scikit-hep/uproot5/pull/1014 test: cover more fsspec backends by @lobis in https://github.com/scikit-hep/uproot5/pull/1015 test: review skipped tests (networking timeouts) by @lobis in https://github.com/scikit-hep/uproot5/pull/1027 test: s3fs pytest unraisable exception by @lobis in https://github.com/scikit-hep/uproot5/pull/1012 test: improve path object split tests by @lobis in https://github.com/scikit-hep/uproot5/pull/1039 chore: update pre-commit hooks by @pre-commit-ci in https://github.com/scikit-hep/uproot5/pull/1005 chore: replace some old code (python 2) by @lobis in https://github.com/scikit-hep/uproot5/pull/1020 Full Changelog: https://github.com/scikit-hep/uproot5/compare/v5.1.2...v5.2.0rc2

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)0.002
metaresearch head score (Gemma)0.008
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: Software · Consensus signal: Software
Teacher disagreement score0.593
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0080.013
Open science0.0040.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.5930.651

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 head0.018
GPT teacher head0.210
Teacher spread0.192 · 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
GenreSoftware

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicPlant Water Relations and Carbon Dynamics→French-language works237,207→