MétaCan
Menu
Back to cohort
Record W2910472043

EMPHASIS – European Multi-environment Plant pHenotyping And Simulation InfraStructure

2015· preprint· en· W2910472043 on OpenAlexaff
Ulrich Schurr, François Tardieu, Dirk Inzé, Xavier Dreyer, Jörg Durner, Thomas Altmann, John H. Doonan, Malcolm J. Bennett

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2015
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsToronto Centre for Phenogenomics
Fundersnot available
KeywordsEmphasis (telecommunications)Computer scienceSystems engineeringRisk analysis (engineering)EngineeringTelecommunicationsBusiness
DOInot available

Abstract

fetched live from OpenAlex

The EMPHASIS proposal aim to establish a European Infrastructure within the ESFRI framework, based on national phenotyping infrastructure (Belgium, France, Germany and UK). The partnership will be extended to other European member states.EMPHASIS will develop and provide access to infrastructures addressing multi-scale phenotyping for analysing genotype performance under diverse environmental conditions and quantify the diversity of traits contributing to performance in diverse environmental scenario (i.e. plant architecture, major physiological functions and output, yield components and quality).EMPHASIS will address the technological and organizational limits. EMPHASIS will:• develop an integrated pan-European network of instrumented phenotyping platforms using current and future agro-climatic scenarios.• link data acquisition to a European-level data management system and to state-of-the art crop models to simulate plants and crops in current and future climates.• develop, evaluate and disseminate novel technologies, thereby providing new opportunities for research involved in phenotyping and precision agriculture• make these infrastructures and concepts accessible to European plant science community in academia and industryEMPHASIS infrastructures will include• platforms in (semi-)controlled conditions for high resolution and throughput phenotyping• Intensive field experimental sites• a coordinated network of field experiments with phenotyping infrastructure• Modelling platforms for testing existing or virtual combinations of alleles.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.207
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueHAL (Le Centre pour la Communication Scientifique Directe)Same topicGreenhouse Technology and Climate ControlFrench-language works237,207