Test volume data for 51 most commonly ordered laboratory tests in Calgary, Alberta, Canada
Bibliographic record
Abstract
Data presented in this article include the top 51 ordered laboratory tests in Calgary and surrounding area, Alberta, from January to December 2017. This data set was collected from Calgary Laboratory Service's Laboratory Information System, and included top 51 tests ordered from community (n = 11, 224, 330), inpatient (n = 2,340,594) and emergency (n = 1,670,062) settings. Test order mnemonic that were not true laboratory tests (eg: "extra PST tube", "extra tube", etc.) were excluded in the analysis. The top test ordered in all 3 test encounters was the complete blood count test (community encounter, n = 921, 873; inpatient setting, n = 357, 375; and emergency setting, n = 276, 954). This data article was submitted as a companion paper to the related research article, "Estimated costs of 51 commonly ordered laboratory tests in Canada" [1].
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.017 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".