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Record W6894300255 · doi:10.5683/sp3/w22q8x

Replication data for: Final report for Neudorff Fiesta efficacy trial – Project # G21-04

2024· dataset· en· W6894300255 on OpenAlexaff

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of GuelphAgricultural Research Institute of Ontario
Fundersnot available
KeywordsDandelionWeed controlLawnWeedReplication (statistics)

Abstract

fetched live from OpenAlex

Low risk herbicides are now commonly used on lawn height turfgrass to manage weeds. This study compared various rates of Fiesta liquid, granular, and soluble granular formulations to determine their effectiveness of controlling broadleaf weed populations on lawn-height turfgrass. To analyze control of weed populations, point-quadrat weed counts, NDVI and visual ratings were used throughout the experiment. There were significant differences in percent control of dandelion at 18DAT1 and 7DAT2 - all treatments provided good control at 7DAT2; this effect was not evident at 14DAT2 and 21DAT2. There were significant differences in percent control of black medic at 14DAT1, 7,14, and 21DAT2; all treatments provided significant control of black medic at 21DAT2.

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)0.014
metaresearch head score (Gemma)0.069
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 score0.231
Threshold uncertainty score0.773

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.069
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.2310.112

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 head0.191
GPT teacher head0.428
Teacher spread0.237 · 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
Published2024
Admission routes1
Has abstractyes

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