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Record W2094014059 · doi:10.4141/cjps07099

Breeding meadow bromegrass for forage characteristics under a line-source irrigation design

2008· article· en· W2094014059 on OpenAlex
Kevin B. Jensen, Blair L. Waldron, Joseph G. Robins, Thomas A. Monaco, Michael D. Peel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Plant Science · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsForageNeutral Detergent FiberHeritabilityPastureDry matterIrrigationBiologyAgronomyGrowing seasonAnimal science

Abstract

fetched live from OpenAlex

Production from less productive lands limited by irrigation can be increased if genetically improved pasture grasses are developed with increased dry matter production (DMY) and nutritional quality. In 2000, 18 half-sib families of meadow bromegrass were seeded in a modified strip-plot design with four replications and water levels (WL) applied as nonrandom strips ranging from 10.1 mm wk -1 at WL-5 to 36.8 mm wk -1 at WL-1. The objective was to estimate genetic variability and parameters as affected by irrigation level and harvest date for DMY, crude protein (CP), in vitro true digestibility (IVTD), neutral detergent fiber (NDF), and digestible neutral detergent fiber (dNDF). Low h 2 estimates for DMY suggest that gains in total DMY from selection within these half-sib families (HSF) are not likely. Crude protein concentrations were more influenced by harvest date than WL. Heritability estimates were relatively high regardless of WL or harvest date for IVTD. The effect of WL on h 2 estimates for NDF were less defined, suggesting that gains might be achieved faster if selection was done on forage harvested later in the growing season at less than optimum irrigation. Heritability estimates for dNDF were either small or associated with large standard errors. Key words: Heritability, irrigation rates, forage yield and quality, crude protein, neutral detergent fiber, in vitro true digestibility

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.221
Teacher spread0.172 · 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