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Record W4398323854 · doi:10.7910/dvn/bdcjnp

Replication Data for: MODIS and PROBA-V NDVI Products Differ when Compared with Observations from Phenological Towers at Four Tropical Dry Forests in the Americas

2019· dataset· en· W4398323854 on OpenAlexaff
J. Antonio Guzmán Q., Arturo Sánchez‐Azofeifa, Espírito-Santo Mário M.

Bibliographic record

VenueHarvard Dataverse · 2019
Typedataset
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhenologyReplication (statistics)Tropical and subtropical dry broadleaf forestsNormalized Difference Vegetation IndexEnvironmental scienceGeographyClimatologyPhysical geographyRemote sensingForestryEcologyClimate changeBiologyGeology

Abstract

fetched live from OpenAlex

Preprocessed data of daily NDVI observations from phenological towers at four tropical dry forests in the Americas. Acronyms represent: Chamela Biological Station (CBS), Santa Rosa National Park Environmental Monitoring Super Site (SRNP-EMSS), Lagoa do Cajueiro State Park (LC-SP), and Parque Estadual da Mata Seca–Environmental Monitoring Super Site (PEMS-EMSS). Observations at the PEMS-EMSS come from four towers located in sites with different successional stages (Pastures, Early, Intermediate, and Late).

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.050
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0500.072

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 head0.079
GPT teacher head0.260
Teacher spread0.181 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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