Differential Diagnosis of Microcytic Anemia, Thalassemia or Iron Deficiency Anemia: A Diagnostic Test Accuracy Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diagnostic test accuracy (DTA) We evaluated the most common indices to compare their sensitivity and specificity to introduce the most sensitive and specific index. We systematically searched five international indexing databases up to Dec 2018. For each index, we measured the diagnostic odds ratio (DOR), as well as summary ROC (SROC) curve which was used to compare the performance of each index. Deeks tests of all discriminant indices indicated that there is no potential publication bias. The area under curves (AUCs) of all discriminant indices indicate overall good differential performance. The M/H ratio index was more sensitive and specific compared to other studied indices. In this meta-analysis, the M/H ratio index was more potential to discriminate iron deficiency anemia (IDA) from thalassemia trait. However, we cannot use this index alone to achieve the final diagnosis. The capability of this index to discriminate IDA from thalassemia trait must be used alongside with the common laboratory procedure to ensure the final differentiation.
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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 | 0.001 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 it