D4.5. Final - Report on agronomic performance of the obtained BBFs and TMFs in laboratory setting
Bibliographic record
Abstract
This study was carried out and published as a part of the European demonstration project FERTIMANURE funded by the H2020 programme (project number 862849). The FERTIMANURE project focuses on the implementation of nutrient recovery and reuse technologies at 5 pilot installations with aim to produce bio-based fertilisers (BBFs) from animal manure and tailor-made fertilisers (TMFs) as blends of BBFs and (synthetic) mineral fertilisers for crop specific applications. One of the tasks within the FERTIMANURE project is to assess BBFs and TMFs produced in the context of FERTIMANURE for their ability to substitute current mineral fertilisers that are produced based on finite fossil-based resources and on high energy consumption. The mentioned assessments take part on laboratory scale and in a full field scale. Deliverable D4.5 ‘Final - Report on agronomic performance of the obtained BBFs and TMFs in laboratory setting’ gives insight into final results of the BBF and TMF testing in laboratory settings, whereas the full field scale results are reported in D4.6 ‘Final - Report on agronomic and environmental performance in field trial experiences’. The D4.5 more specifically reports on nitrogen (N) and carbon (C) dynamics of tested BBFs via incubation tests, phosphorus (P) plant availability of BBFs by plant growth assay, the effect of biologically activated BBFs, and lastly effect of the produced biostimulant. We would like to acknowledge the researchers and staff of RITTMO Agroenvironnement (France), Fraunhofer-Institut für Umwelt, Sicherheits und Energietechnik (Germany), Ghent University (Belgium), BETA – University of Vic (Spain) and University of Milano (Italy) for their work and contribution.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.019 |
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".