MIRRI-ERIC and MICROBES-4-CLIMATE: advancing culturomics and synthetic communities for climate action
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This presentation was delivered by Ana Portugal Melo, Executive Director of MIRRI-ERIC, at the 2025 Food System Microbiomes Conference, in Wageningen, The Netherlands. Abstract MIRRI-ERIC, the Microbial Resource Research Infrastructure, is a pan-European ERIC that coordinates microbial Biological Resource Centres and services. It provides access to curated microorganisms, data, and expertise, supporting research, innovation, and European priorities for sustainable food systems and climate action. MICROBES-4-CLIMATE (M4C), coordinated by MIRRI-ERIC, is a Horizon Europe project that brings together leading Research Infrastructures to study soil and plant microbiomes under climate stress. It develops interoperable services, experimental approaches, and data workflows to understand microbial responses to drought, heat, and other factors, strengthening resilience in agroecosystems and related environments. Within M4C, one goal is the establishment and validation of synthetic microbial communities (SMCs). It standardises sampling, isolation, and preservation, identifies new microbial isolates, and designs SMCs with key ecosystem functions that protect plants under stress. These resources and workflows are preserved in partner collections, ensuring long-term availability for research and innovation. In parallel, culturomics provides a complementary approach to broaden the range of microbial strains available for such efforts. By diversifying cultivation conditions and applying high-throughput MALDI-TOF MS dereplication and genome-based identification, it uncovers microbial diversity often missed by conventional approaches. Such strains can enhance soil and plant health, support climate-resilient farming, and accelerate microbiome-based innovation for climate change mitigation. Together, these activities demonstrate how MIRRI-ERIC and its partners advance microbiome research to foster sustainable systems under climate change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it