MELISSA: 10 years of Research, Results, Status and Perspectives
Bibliographic record
Abstract
Initiated in March 1989, the MELISSA (Micro-Ecological Life Support Alternative) has been conceived as a micro-organisms and higher plants based ecosystem intended as a tool to gain understanding of the behaviour of artificial ecosystems, and for the development of the technology for a future biological life support system for long term manned space missions, e.g. a lunar base or a mission to Mars. The collaboration was established through a Memorandum of Understanding and is managed by ESA/ESTEC. It involves several independent organisations: IBP Orsay (F), University of Ghent (B), University of Clermont Ferrand (F), VITO Mol (B), ADERSA (F), University “Autonoma” of Barcelona (E), University of Guelph (CND). It is co-funded by ESA, the MELISSA partners, the Spanish (CIRIT and CICYT) and Canadian (CRESTech) authorities. The driving element of MELISSA is the recovering of edible biomass from waste (faeces, urea), carbon dioxide and minerals. Based on the principle of an “aquatic” ecosystem, MELISSA comprises 5 compartments from the anoxygenic fermenter up to the photosynthetic one (algae and higher plants). The choice of this compartmentalised structure is required by the very high level of space safety requirements and justified by the possibility to use an engineering approach and to built deterministic control strategy. During the past 10 years a very progressive approach has been developed to understand and control the MELISSA loop. This approach starts from the selection of the microbial strains and higher plant crops, their characterisation and mathematical modelling, up to the demonstration on Earth, at pilot scale. In this paper, we recall the main concepts of MELISSA, as well as the main objectives. A survey of the main results is presented and the main orientations are justified. At the end the new topics of research as well as preliminary development schedule will be exposed.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".