Bone marrow aspirate and biopsy: a pathologist's perspective. II. interpretation of the bone marrow aspirate and biopsy
Bibliographic record
Abstract
Bone marrow examination has become increasingly important for the diagnosis and treatment of hematologic and other illnesses. Morphologic evaluation of the bone marrow aspirate and biopsy has recently been supplemented by increasingly sophisticated ancillary assays, including immunocytochemistry, cytogenetic analysis, flow cytometry, and molecular assays. With our rapidly expanding knowledge of the clinical and biologic diversity of leukemia and other hematologic neoplasms, and an increasing variety of therapeutic options, the bone marrow examination has became more critical for therapeutic monitoring and planning optimal therapy. Sensitive molecular techniques, in vitro drug sensitivity testing, and a number of other special assays are available to provide valuable data to assist these endeavors. Fortunately, improvements in bone marrow aspirate and needle technology has made the procurement of adequate specimens more reliable and efficient, while the use of conscious sedation has improved patient comfort. The procurement of bone marrow specimens was reviewed in the first part of this series. This paper specifically addresses the diagnostic interpretation of bone marrow specimens and the use of ancillary techniques.
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".