Validation of cell‐based fluorescence assays: Practice guidelines from the ICSH and ICCS – part III – analytical issues
Bibliographic record
Abstract
Clinical diagnostic assays, may be classified as quantitative, quasi-quantitative or qualitative. The assay's description should state what the assay needs to accomplish (intended use or purpose) and what it is not intended to achieve. The type(s) of samples (whole blood, peripheral blood mononuclear cells (PBMC), bone marrow, bone marrow mononuclear cells (BMMC), tissue, fine needle aspirate, fluid, etc.), instrument platform for use and anticoagulant restrictions should be fully validated for stability requirements and specified. When applicable, assay sensitivity and specificity should be fully validated and reported; these performance criteria will dictate the number and complexity of specimen samples required for validation. Assay processing and staining conditions (lyse/wash/fix/perm, stain pre or post, time and temperature, sample stability, etc.) should be described in detail and fully validated.
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 | 0.019 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.009 |
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".