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Record W4383175845 · doi:10.5281/zenodo.8107872

Data Remediation as Collaborative Process

2023· paratext· en· W4383175845 on OpenAlexaffabout
Kim Martin, Susan Brown

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typeparatext
Languageen
FieldDecision Sciences
TopicData Quality and Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsProcess (computing)Computer scienceEnvironmental remediationProcess managementProcess engineeringEngineeringOperating systemContamination

Abstract

fetched live from OpenAlex

This paper utilizes the concept of remediation (of research conceptualization, of data, and by interfaces) to describe the processes developed by Linked Infrastructure for Networked Cultural Scholarship (LINCS), a Canadian infrastructure project for mobilizing Canadian scholarship through the creation, dissemination, and use of linked open data (LOD).

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)0.008
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.581
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0030.000
Scholarly communication0.0050.001
Open science0.0090.009
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0990.680

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 head0.282
GPT teacher head0.434
Teacher spread0.152 · 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
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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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