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Record W1993006073 · doi:10.1080/02763860903484897

Have Computers, Will Travel: Providing On-site Library Instruction in Rural Health Facilities Using a Portable Computer Lab

2010· article· en· W1993006073 on OpenAlexaffabout
Christine Neilson

Bibliographic record

VenueMedical Reference Services Quarterly · 2010
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsSaskatchewan HealthUniversity of Saskatchewan
Fundersnot available
KeywordsOutreachGeneral partnershipAsideHealth careComputer scienceWorld Wide WebMedical educationMultimediaBusinessMedicinePolitical science

Abstract

fetched live from OpenAlex

The Saskatchewan Health Information Resources Partnership (SHIRP) provides library instruction to Saskatchewan's health care practitioners and students on placement in health care facilities as part of its mission to provide province-wide access to evidence-based health library resources. A portable computer lab was assembled in 2007 to provide hands-on training in rural health facilities that do not have computer labs of their own. Aside from some minor inconveniences, the introduction and operation of the portable lab has gone smoothly. The lab has been well received by SHIRP patrons and continues to be an essential part of SHIRP outreach.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.004

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 head0.021
GPT teacher head0.297
Teacher spread0.276 · 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
GenreEmpirical

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

Citations3
Published2010
Admission routes2
Has abstractyes

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