Tailoring software process capability/maturity models for telemedicine systems
Bibliographic record
Abstract
Developing high-quality asynchronous store-and-forward telemedicine systems (ASFTSs) remains a challenge. However, there is no accepted understanding as to what are the important quality characteristics for this type of software system and/or what defines a mature software process for producing high-quality ASTFSs. Through adopting a multi-step research methodology, we define a quality model for ASFTSs indicating relevant quality characteristics and their priority for this specific type of software system based upon ISO/IEC 25010. We, then, propose an extended software process capability/maturity model based on ISO/IEC 15504 and ISO/IEC 12207 to meet these particular quality requirements. The resulting model can be used to both guide the development and the evaluation of such systems. We expect that the availability of such a customized model will facilitate the development of high-quality ASFTSs, reducing related risks and improving the quality of telemedicine services.
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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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".