A new science readiness level standard for space science investigations
Bibliographic record
Abstract
This article presents a new Science Readiness Level (SRL) Standard that has been developed at the Canadian Space Agency (CSA) for universal application to all space science investigations. Other authors have recognised that the traditional mission management process that relies on Technology Readiness Levels as the main tool to track mission maturity is missing important elements when it comes to science missions, and this is discussed. The motivation for developing a useable new science readiness assessment tool for missions of scale from CubeSats to flagships, in configurations as diverse as satellite constellations and ground-based instrument networks, with operations that can be robotic or crew-enabled, and with investigations that can range from traditional remote sensing to rover wet chemistry laboratories, is described. Universality of the derived SRL standard is achieved by assessing the quality and maturity of three independent elements of success that don’t depend on the type of science, the project management structure, or the scale of the project: (1) the baseline investigation (2) the science success strategy, and (3) the science plan. Using language from NASA’s Standard Principal Investigation-led Mission Announcement of Opportunity Template and in deliberate alignment with the European Space Agency (ESA) Earth Observation SRL scale, the final level of Science Readiness assesses Science Impact, underlining that the scale does not assess readiness simply to operate in the space environment, but readiness to deliver advances in knowledge associated with specific science objectives. Two examples are provided to illustrate the application of the Standard to investigations from different science disciplines and of widely different scope: a notional “FireSat” Cubesat mission, and a notional future “Mars life detection investigation at a methane seep”. It is expected that the CSA SRL Standard will evolve using lessons learned from users, and to align with evolving science practice and policy. The discussion addresses the international nature of science missions and science instrument contributions, suggesting value in convergence towards an international SRL standard.
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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 | 0.022 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".