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Allelopathy: Past Achievements and Future Approaches, Proceedings of a Symposium of the Weed Science Society of America, February 9, 2000, Toronto, Canada

2001· article· en· W2266630416 on OpenAlexaboutno aff
Inderjit Inderjit, Chester L. Foy

Bibliographic record

VenueWeed Technology · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAllelopathy and phytotoxic interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAllelopathyAbiotic componentWeedBiologyBioassayEcologyHerbivoreAgronomyGermination

Abstract

fetched live from OpenAlex

The number of papers published on allelopathy was low until the 1970s but has accelerated rapidly in recent years. Alleged allelopathic activity has been suggested for numerous weed and crop species; however, many studies employed preliminary bioassays (leachates or extracts in the absence of soil). The importance of substratum and of abiotic and biotic stresses (nutrients, shade, herbides, plant diseases, herbivores), plant density, habitat, and climate has been realized in recent years. Laboratory bioassay, the first step to investigate probable involvement of allelopathy, should be designed to correspond to field conditions. Studies need to focus on the effects of (1) climatic, environmental, and habitat factors on allelopathic potential; (2) abiotic and biotic soil components on fate and biological activity of allelochemicals; and (3) allelochemicals on soil nutrient dynamics, microbial ecology, and other abiotic and biotic components. Recently, attempts to find crop cultivars with a competitive allelopathic edge have been made. Interaction of professionals from different disciplines is needed to understand the complexity of the ecosystem. The following are important topics for discussion: allelopathy and the transition to sustainable agriculture; physiological and biochemical studies; using transgenes to produce allelopathic crops; microbial allelochemicals and pathogens as weed biological agents; bioassays for allelopathy (problems and solutions); pollen allelopathy; and an ecological perspective of allelopathy.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.008
GPT teacher head0.180
Teacher spread0.172 · 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 designBench or experimental
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
Published2001
Admission routes1
Has abstractyes

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