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Record W6910906455 · doi:10.5063/f1cf9njs

Census of flowering annuals in the open and associated with Larrea tridentata, Mojave Desert, April 2019

2022· dataset· en· W6910906455 on OpenAlexaff

Bibliographic record

VenueUC Santa Barbara · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsYork University
Fundersnot available
KeywordsLarreaShrubCensusSpecies richnessAridAnnual plant

Abstract

fetched live from OpenAlex

Larrea tridentata is a well known facilitator of annuals in arid ecosystems. We surveyed the annual flowering community associated with 100 Larrea tridentata and paired open areas in the Mojave Desert three times over the course of the flowering season of 2019. Only annual species that were flowering in the area were identified. Plant density, species richness and flowering density was recorded for each shrub. A total of 15 annual species across 6 families and 14 genera were recorded.This dataset has three files:1. flowering_censuses_2019 contains the annual community data (e.g. density, richness, and floral density)2. ShrubInfo contains the characteristics of each shrub (e.g. size and location)3. code2.R contains code related to the presentation and analysis of the data.

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)0.001
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 score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.012

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 head0.027
GPT teacher head0.300
Teacher spread0.273 · 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
Published2022
Admission routes1
Has abstractyes

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