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Record W2121674362 · doi:10.2307/1224759

Flavonoids of the Sunflower Family (Asteraceae)

2001· article· en· W2121674362 on OpenAlexfundno aff
B. L. Turner, Bruce A. Bohm, Tod F. Stuessy

Bibliographic record

VenueTaxon · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAustrian Science FundNational Geographic SocietyNational Science Foundation
KeywordsAsteraceaeBiologyHeliantheaeBotanyFlavonoidFlavanoneChemotaxonomyTaxonomy (biology)Biochemistry

Abstract

fetched live from OpenAlex

Certainly many of the readers of this book will remember the early developments of chemosystematics in the late 1950s.We ourselves remember the excitement of these new data bearing on plant interrelationships.The hopes were high, the techniques were rapidly evolving, the quantities of data were large, and young workers were eagerly enthusiastic.Some even went so far as to predict that chemical data would soon replace morphological information as the basis for plant classification.These overly zealous predictions did not materialize, of course, as the history of plant systematics has amply shown during the past two centuries.If there is any distinct characteristic of systematics it is synthesis, as Lincoln Constance (1964) called it, the "unending synthesis."New tools generate new data and provide insights on additional dimensions of plant relationships.This will never change-we will continue to discover new tools and new data in the years ahead, and they will continue to be incorporated into the predictive general reference system of classification.The earlier efforts in chemosystematics focused on secondary plant products: alkaloids, betacyanins, carbohydrates, cyanogenic glycosides, glucosinolates, lipids, terpenoids, and especialiy flavonoids.The latter were particularly well suited for chemosystematic investigation for several reasons: ease of isolation and characterization, small amounts of plant material needed for analysis, stability of compounds especially through routine preparation of herbarium specimens, and low cost to obtain useful information.As a result of these considerable advantages, literally thousands of studies on use of flavonoids in plant systematics have been published.Although now with the present zest for macromolecular data from DNA restriction sites and sequences, there are fewer workers and laboratories dedicated to flavonoid chemosystematic studies; twenty years ago they were the new currency of exciting data in plant systematics.Because of many workers historically interested in the sunflower family, Asteraceae (or Compositae), in part due to its large size (approximately 23,000 species; Bremer, 1994), and because hundreds of flavonoid compounds were discovered in this family, many chemosystematic investigations have been completed on various taxa.

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: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.030
GPT teacher head0.214
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

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

Citations116
Published2001
Admission routes1
Has abstractyes

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