MétaCan
Menu
Back to cohort
Record W4210512984 · doi:10.1126/science.abk2177

Southeast Asian Dipterocarp origin and diversification driven by Africa-India floristic interchange

2022· article· en· W4210512984 on OpenAlexaff
Mahi Bansal, Robert J. Morley, Shivaprakash K. Nagaraju, Suryendu Dutta, Ashish Kumar Mishra, Sumit Kumar, Deepti Niyolia, Sachin Medigeshi Harish, Omer Babiker Abdelrahim, Shaa eldin Hasan, B.R. Ramesh, Selvadurai Dayanandan, Harsanti P. Morley, Peter S. Ashton, Vandana Prasad

Bibliographic record

VenueScience · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsConcordia UniversityMontreal Biodome
Fundersnot available
KeywordsDipterocarpaceaeBiological dispersalGeographySoutheast asiaTropical AsiaEast AsiaDiversification (marketing strategy)BiogeographyEcologyBiologyChinaAncient historyArchaeologyPopulationHistory

Abstract

fetched live from OpenAlex

The evolution and diversification of ancient megathermal angiosperm lineages with Africa-India origins in Asian tropical forests is poorly understood because of the lack of reliable fossils. Our palaeobiogeographical analysis of pollen fossils from Africa and India combined with molecular data and fossil amber records suggest a tropical-African origin of Dipterocarpaceae during the mid-Cretaceous and its dispersal to India during the Late Maastrichtian and Paleocene, leading to range expansion of aseasonal dipterocarps on the Indian Plate. The India-Asia collision further facilitated the dispersal of dipterocarps from India to similar climatic zones in Southeast Asia, which supports their out-of-India migration. The dispersal pathway suggested for Dipterocarpaceae may provide a framework for an alternative biogeographic hypothesis for several megathermal angiosperm families that are presently widely distributed in Southeast Asia.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.029
GPT teacher head0.195
Teacher spread0.166 · 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

Citations90
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueScienceSame topicPlant Diversity and EvolutionFrench-language works237,207