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Predispersal seed predation of redroot pigweed (Amaranthus retroflexus)

2003· article· en· W2040678500 on OpenAlexafffund
Nancy DeSousa, Jason T. Griffiths, Clarence J. Swanton

Bibliographic record

VenueWeed Science · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyInflorescenceWeedPredationSeed predationAgronomyCanopyPredatorPopulationShadingHorticultureBotanySeed dispersalEcologyBiological dispersal

Abstract

fetched live from OpenAlex

Field experiments were conducted in 1999 and 2000 to determine if (1) seed predation of redroot pigweed plants occurred in agricultural fields, (2) corn-cropping patterns could be manipulated to influence the quantity of weed seed predation, and (3) alterations in corn canopies affected the microenvironment, possibly influencing predator populations. Corn was planted in standard (75 cm) or narrow (37.5 cm) rows with corn population densities ranging from low to very high (2.5 to 10 plants m−2). The extent of seed predation occurring on terminal weed inflorescences in the treatments was evaluated. Predation levels of redroot pigweed were highly variable spatially and temporally. Coleophora lineapulvella Chambers (Lepidoptera: Coleophoridae) was the dominant predator of redroot pigweed seed. Seed predation was higher in 2000 than in 1999 (P < 0.05). On average, C. lineapulvella larvae attacked 11% of the inflorescences in 2000 and 3% of inflorescences in 1999. The proportion of damaged seeds per attacked inflorescence was as high as 93% in 2000 but only 42% in 1999. Row spacing and corn density did not affect levels of weed seed predation (P > 0.05). But canopies of closely spaced corn increased shading to redroot pigweed plants growing below the canopy, consequently decreasing total weed biomass and seed production.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.205
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations18
Published2003
Admission routes2
Has abstractyes

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