Use of World Wide Web-based Directories for Tracing Subjects in Epidemiologic Studies
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.056 | 0.115 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".