Time Series Analysis of the Clinical Laboratory Test Result on Chemotherapy for Gastric Cancer
Bibliographic record
Abstract
PURPOSE: Time series analysis may be helpful to estimate hematological data on gastric cancer patients who receive S 1, but untreated raw clinical data are not suitable for this approach. Hematological monitoring data interpolated by spline were analyzed by an attractor plot, which is a form of time series analysis. METHODS: Hematological data of three gastric cancer patients were interpolated by cubic spline. The leave-one-out cross validation method was carried out and an attractor plot was adopted to evaluate red blood count (RBC) data. RESULTS: Well-predicted data, such as RBC, changed slightly; however, data with great deviation, such as the white blood count (WBC), were poorly predicted. The reaction of marrow function to chemotherapy was observable by spline interpolation of RBC data. Furthermore, an attractor plot clarified the tendency of the interpolated hematological monitoring data. CONCLUSIONS: It is suggested that spline interpolation is effective as a pretreatment to analyze clinical data from a time series.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".