Characteristics, Desired Functionalities, and Datasets of State Web-based Data Query Systems
Bibliographic record
Abstract
In Brief Based on a review of state public health department Web sites, this article describes Web-based Data Query Systems (WDQSs) currently used in 27 US states. In addition, functionalities of selected well-established state WDQSs are defined as major functionalities (11), subfunctionalities (21), and specific functionalities (141), on the basis of a consensus process with participants from states and national organizations in the United States and Canada. Also, on the basis of the consensus process, specific functionalities are categorized as core, enhanced, and expert. Key terms relevant to WDQSs are defined. The information contained in this article should prove useful to public health agencies developing, revising, or evaluating the WDQS. This article describes Web-based Data Query Systems (WDQSs) currently used in 27 US states and provides an overview of functionalities and datasets in 33 WDQSs available through state WDQSs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".