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Record W3021216121 · doi:10.18167/dvn1/w29ggt

Cover plant growth response to different sowing dates in Reunion

2020· dataset· en· W3021216121 on OpenAlexaff
Mathias Christina, André Chabanne, Adrien Négrier, Pascal Marnotte, Emmanuel Hoarau, Ginot Gauvin, Jean-Maurice Gueno, Jean-ClaudeCIRAD Ribotte

Bibliographic record

VenueCentre de coopération internationale en recherche agronomique pour le développement · 2020
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsSowingBiomass (ecology)PhenologyPlant coverRaw dataBiologyCover (algebra)GeographyTraitAgronomyEnvironmental scienceForestryEcologyStatisticsMathematicsEngineeringComputer scienceCanopy

Abstract

fetched live from OpenAlex

In the current study, we aimed to assess the cover plant growth response to sowing date of 16 different plant species in the north of Reunion island. The files in the dataset included: - "Trial and species description" : description of the trials and cover plant species - "DATARAW" files: raw measurements of plant coverage, height, number of leaves, phenology and biomass performed in the different trials. - "DATA_calculated": provides trait variables calculated from the raw measurements per species and trials

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)0.001
metaresearch head score (Gemma)0.001
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.082
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.104
GPT teacher head0.283
Teacher spread0.179 · 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
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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