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Record W2098537850 · doi:10.1093/aje/152.9.889

Use of World Wide Web-based Directories for Tracing Subjects in Epidemiologic Studies

2000· article· en· W2098537850 on OpenAlexaffabout
Malcolm M. Koo

Bibliographic record

VenueAmerican Journal of Epidemiology · 2000
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDirectoryThe InternetWorld Wide WebMedicineTracingComputer science

Abstract

fetched live from OpenAlex

The recent availability of World Wide Web-based directories has opened up a new approach for tracing subjects in epidemiologic studies. The completeness of two World Wide Web-based directories (Canada411 and InfoSpace Canada) for subject tracing was evaluated by using a randomized crossover design for 346 adults randomly selected from respondents in an ongoing cohort study. About half (56.4%) of the subjects were successfully located by using either Canada411 or InfoSpace. Of the 43.6% of the subjects who could not be located using either directory, the majority (73.5%) were female. Overall, there was no clear advantage of one directory over the other. Although Canada411 could find significantly more subjects than InfoSpace, the number of potential matches returned by Canada411 was also higher, which meant that a longer list of potential matches had to be examined before a true match could be found. One strategy to minimize the number of potential matches per true match is to first search by InfoSpace with the last name and first name, then by Canada411 with the last name and first name, and finally by InfoSpace with the last name and first initial. Internet-based searches represent a potentially useful approach to tracing subjects in epidemiologic studies.

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)0.006
metaresearch head score (Gemma)0.056
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.114
GPT teacher head0.391
Teacher spread0.277 · 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 teacher head, not a consensus.

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

Citations8
Published2000
Admission routes2
Has abstractyes

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