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Record W7001928085

2013 Maple Business Benchmark

2014· article· en· W7001928085 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks -A service of University of Vermont Libraries (University of Vermont) · 2014
Typearticle
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsMapleBenchmark (surveying)Yield (engineering)CurrencyInvestment (military)Financial market
DOInot available

Abstract

fetched live from OpenAlex

Strong market prices, technology improvements and increasing sugar bush sizes are key features of the Vermont maple industry. The continued growth of maple production and maple investments elevate the interest in the financial performance of harvesting maple sap and processing maple syrup. The 2013 Maple Business Benchmark is the result of the first year of focused collection of financial information for the sector. University of Vermont Extension worked with 10 maple producers to complete financial analysis of their maple enterprise. Participants each received a detailed financial summary of their business that included information on sales, expenses, investments and profitability. That same information has been combined to create the 2013 Maple Benchmark report. This report demonstrates key management and financial metrics including: yield statistics, land use, operating costs, investment requirements, total cost of production and net income. See later year publications for more recent Northeast Maple Benchmark reports.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.106
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.000
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.020

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 head0.008
GPT teacher head0.155
Teacher spread0.146 · 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 designObservational
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

Citations0
Published2014
Admission routes1
Has abstractyes

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