MétaCan
Menu
← Back to cohort
Record W2810971002 · doi:10.1139/cjfr-2018-0164

Histology of resin vesicles and oleoresin terpene composition of conifer seeds

2018· article· en· W2810971002 on OpenAlexafffundvenue
Kristina Kshatriya, Justin G. A. Whitehill, Lina Madilao, Hannah Henderson, Allison R. Kermode, David Kolotelo, Jörg Bohlmann

Bibliographic record

VenueCanadian Journal of Forest Research · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMinistry of ForestsSimon Fraser UniversityCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGenome British ColumbiaGenome Canada
KeywordsTsugaBotanyThujaBiologyTerpeneAbies balsameaBalsam

Abstract

fetched live from OpenAlex

The seed coats of several conifers contain terpene-filled resin vesicles, which may be involved in the protection of the dormant embryo and the seed storage tissue against herbivores or pathogens. We analyzed the terpenoid composition of seeds from four Abies species (Abies amabilis Douglas ex J. Forbes, Abies balsamea (L.) Mill., Abies grandis (Douglas ex D. Don) Lindl., and Abies lasiocarpa (Hook.) Nutt.), two Thuja species (Thuja plicata Donn ex D. Don and Thuja occidentalis L.), and three Tsuga species (Tsuga canadensis (L.) Carrière, Tsuga mertensiana (Bong.) Carrière, and Tsuga heterophylla (Raf.) Sarg.) and examined histological features of resin vesicles in seeds from one species from each genus. Resin vesicle morphology was generally similar among the species analyzed. The composition of the seed terpenes varied largely between species. The described seed terpene profiles of the nine species will serve as a foundation for future studies into the function of seed terpenes and resin vesicles in the seed coat.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.086
GPT teacher head0.283
Teacher spread0.198 · 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 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

Citations8
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Forest Research→Same topicPlant and animal studies→French-language works237,207→