Bibliographic record
Abstract
目的比较Metis-200（深圳爱康）自动血型分析仪与Xantus双机械臂加样器联合Poseidon数字血型仪检测ABO及Rh D血型的效果。方法同时采用两种自动血型仪对本站无偿献血样本24 866份进行平行血型检测、脂血干扰试验、溶血干扰试验和对比分析。结果两种血型分析仪对ABO血型判读准确率均为100%。通过确认,Metis-200和Xantus双机械臂加样器联合Poseidon数字血型仪检出ABO亚型分别为7例、5例（P〉0.05）;检出不规则抗体分别为16例、9例（P〉0.05）。76份不同脂血程度血样在两种仪器上抗干扰试验一次判读正确率均为100%。溶血干扰试验在Hb≤27 g/L时,对UV型微板法结果判读无明显影响,当Hb〉27 g/L时对凝集端有影响,对非凝集端无影响;而当Hb≤20 g/L时,对梯形微板法试验结果无明显影响;在Hb〉20 g/L时对梯形微板法凝集端无影响,对非凝集端有影响。结论 Metis-200自动血型分析仪较Xantus双机械臂加样器联合Poseidon数字血型仪检测ABO及Rh D血型判读更加准确,速度更快,效率更高,极大地提高了血型批量检测的能力。
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".