MétaCan
Menu
Back to cohort
Record W6920252545 · doi:10.60692/5c0pn-nxf81

Synchrony in Leafing, Flowering, and Fruiting Phenology ofSenegalia senegalwithin Lake Baringo Woodland, Kenya: Implication for Conservation and Tree Improvement

2016· article· en· W6920252545 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhenologyWet seasonDry seasonShootRelative humidityFructificationBiological dispersal

Abstract

fetched live from OpenAlex

Leafing, flowering, and fruiting patterns of Senegalia senegal were studied over a period of 24 months from January 2014 to December 2015. The phenological events of the species are bimodal and follow the rainfall patterns. The leafing phase starts during the onset of rains and lasts for 18 weeks. New leaves continued to appear on the new shoots while old leaves persisted to the leaf fall period. Flowering event takes 12 weeks and is concentrated in the months of high relative humidity (April and October) with one-month peak flowering period. Fruiting phase starts at the peak of the rainy seasons (May and November) and peaks in June and December. This phase lasted for 14 weeks. The fruits mature towards the end of the rainy season (January/February and July/August). The fruits open for dispersal mainly in February/March and September during the peak dry season. High synchrony index (SI) was found in leafing (SI: 0.87), flowering (SI: 0.75), and fruiting (SI: 0.85) events among the populations. Temperature, precipitation, and soil moisture content were significantly correlated with the phenological events. Significant variations in floral morphology and fruits traits were also evident. Seed collections should be undertaken in the months of January/February and July/August.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.196

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 head0.024
GPT teacher head0.196
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 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueGreater South Information SystemSame topicAfrican Botany and Ecology StudiesFrench-language works237,207