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Record W2415812786

The Internet: an effective tool for nursing research with women.

2000· article· en· W2415812786 on OpenAlexaff
Barbara Thomas, Lynnette Leeseberg Stamler, Kathryn D. Lafreniere, Richard Dumala

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsThe InternetAnonymityPopulationMedical educationPsychologyInternet privacyMedicinePolitical scienceWorld Wide WebComputer scienceEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

This article outlines the methodology of using the Internet to survey an international population of women about their perceptions of breast health education and screening. Issues to consider in planning and implementing the research project by Internet are presented. A large population of women from North America and elsewhere was reached through the establishment of a website with linkages to other sites frequented by women. Women who visited the website were asked to complete a questionnaire. Anonymity was guaranteed and simple instructions were provided at the site. Benefits, limitations, and tips for success in using the Internet as a research tool are presented. These investigators found the Internet to be an appropriate medium for health-related research that also garnered national and international media interest. The address for this website is http:@www.uwindsor.ca/breast.study/quest.htm.

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)0.026
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0020.002
Scholarly communication0.0040.008
Open science0.0020.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.008

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 head0.134
GPT teacher head0.465
Teacher spread0.331 · 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 designObservational
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

Citations31
Published2000
Admission routes1
Has abstractyes

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