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Finding the Public Domain

2016· book· en· W2436160470 on OpenAlexaffabout
Melissa Levine, Justin Bonfiglio

Bibliographic record

Venuenot available
Typebook
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsOntario Council of University LibrariesUniversity of Toronto
FundersCollege of Pharmacy, University of MichiganUniversity of MichiganUniversity of MinnesotaInstitute of Museum and Library Services
KeywordsPublic domainDomain (mathematical analysis)Computer scienceWorld Wide WebHistory

Abstract

fetched live from OpenAlex

In CRMS-US (2008-11), CRMS reviewed over 170,000 volumes in the HathiTrust Digital Library that were published in the United States between 1923 and 1963 ("CRMS-US").That first project team

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)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.998
Threshold uncertainty score0.347

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0040.005
Scholarly communication0.0210.044
Open science0.0020.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1040.053

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 head0.133
GPT teacher head0.353
Teacher spread0.220 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

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Citations4
Published2016
Admission routes2
Has abstractyes

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