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Record W2552898700 · doi:10.3897/rio.2.e11065

A Data Management Plan for Effects of particle size on physical and chemical properties of mine wastes

2016· article· en· W2552898700 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

VenueResearch Ideas and Outcomes · 2016
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPlan (archaeology)Data management planData managementComputer scienceData scienceBusinessEngineering managementDatabaseEngineering

Abstract

fetched live from OpenAlex

<p>It is a data management plan created based the a NSF funded research project: Effects of particle size on physical and chemical properties of mine wastes (https://www.nsf.gov/awardsearch/showAward?AWD_ID=0847811) The plan addresses how to management the data collected by the project according to the requirements of NSF funded grants.</p> <p>It is not a real data management implementation plan. It is originally created as an assignment on an online course “<i>What You Need to Know about Writing Data Management Plans.</i>” offered by Association of College & Research Libraries in 2014. The data management plan was created using the NSF funded project as a virtual research scenario.</p>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.122

Codex and Gemma teacher scores by category

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

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 head0.082
GPT teacher head0.339
Teacher spread0.258 · 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