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A mechanistic growth and development model of common ragweed

2001· article· en· W2173995365 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWeed Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRagweedMonocultureEnvironmental scienceGrowth modelBiomass (ecology)Range (aeronautics)GerminationAgronomyMathematicsAtmospheric sciencesBiologyPhysicsMaterials science

Abstract

fetched live from OpenAlex

A mechanistic model was constructed for common ragweed growth and development based on the generic plant model CROPSIM. Adaptations were made to CROPSIM's growth and development subroutines to enable common ragweed growth to be simulated. Data from field studies using a single-source common ragweed grown in monoculture and from the literature were used to parameterize the model. The influences of varying environmental conditions across years, densities, and emergence timing on leaf number, leaf area, leaf weight, height, and biomass accumulation were taken into account by the model. Deviations between simulated and measured values generally fell within a relatively narrow range. Deviations outside this range tended to be associated with common ragweed growth shortly after emergence, particularly during temperature and moisture extremes. Future versions of the CROPSIM model may need to include more detailed algorithms for upper soil surface layer temperature and moisture conditions and improved germination and emergence algorithms to reduce these deviations.

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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.176

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.048
GPT teacher head0.232
Teacher spread0.184 · 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