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Record W2121466153 · doi:10.5539/mas.v8n4p97

Protein and Fiber Profiles of Cottonseed from Upland Cotton with Different Fertilizations

2014· article· en· W2121466153 on OpenAlex

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

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicResearch in Cotton Cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsCottonseedNeutral Detergent FiberAgronomyFertilizerDry matterLitterBiologyChemistryBiotechnology

Abstract

fetched live from OpenAlex

Whole cottonseed and its derived products can be used as human food, animal feed, and industrial raw material. Chemical composition of cottonseed is one of the critical parameters for evaluating its quality and potential end use. Especially, protein and dietary fibers are two desirable nutritional properties of cottonseed for animal feed. In this study, we determined their contents in cottonseed harvested from different fertilization managements with or without wheat cover crop in two consecutive years. Seed content of crude protein increased in the order of no fertilizer ? poultry litter ? chemical fertilizer. Both neutral and acid detergent fiber profiles were affected by fertilization and planting year/cover crop in an order reversing that of crude protein. Few statistically significant (P>0.05) impacts were observed on the content of acid detergent lignin. Observations derived from this work will provide information on nutritional value and digestibility of cottonseed as affected by cropping management practices.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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