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Record W2073117121 · doi:10.13031/2013.13909

Pelleting of Fractionated Alfalfa Products

2003· article· en· W2073117121 on OpenAlexfundno aff
Phani Adapa, Greg Schoenau, Lope G. Tabil, S. Sokhansanj and B. Crerar

Bibliographic record

Venue2003, Las Vegas, NV July 27-30, 2003 · 2003
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPelletPelletsWater contentMoistureMaterials sciencePulp and paper industryComposite material

Abstract

fetched live from OpenAlex

A pilot scale pellet mill was used to produce pellets using ground alfalfa leaf and stemfractions. The moisture content of the dehydrated alfalfa chops was 9.6% (wet basis). The leaf andstem fractions were segregated into two lots and ground in a hammer mill using two screen sizes of3.2 mm (1/8 in.) and 1.98 mm (5/64 in.). The leaf and stem fractions from each sample lot of samegrind sizes were combined to get five different samples with leaf content ranging from 0% to 100%with an increment of 25%. The moisture content and temperature of the samples were raised to 10-11% (w.b.) and 76oC, respectively, in a double chamber steam conditioner prior to pelletingoperation. Material temperature was further raised to 95oC in the pellet mill due to the frictionbetween its roller-die assembly. During this whole process the average particle size of sample lots,temperature and moisture content of samples after various pelleting stages were recorded.Durability of dehydrated alfalfa fluctuated between high and medium range (except for 100% stems,which was low). Dehydrated alfalfa with 0% leaves produced pellets with better color.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations32
Published2003
Admission routes1
Has abstractyes

Explore more

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