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Record W2128840370 · doi:10.22230/jem.2007v8n3a372

Development and potential of the cultivated and wild-harvested mushroom industries in the Republic of Korea and British Columbia

2007· article· en· W2128840370 on OpenAlexafffundabout
Shannon M. Berch, Kang-Hyeon Ka, Hyun Park, Richard S. Winder

Bibliographic record

VenueJournal of Ecosystems and Management · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceGovernment of British Columbia
FundersCanadian Forest ServiceNatural Resources CanadaU.S. Forest Service
KeywordsMushroomForest industryGeographyAgroforestryForestryBiologyBotany

Abstract

fetched live from OpenAlex

Inspired by collaborative work among researchers from the two jurisdictions, we explore the commercial mushroom industry in the Republic of Korea and British Columbia, Canada, searching for similarities and differences that may guide future development. First, we provide a history of forest mushroom use in both areas and summarize the development of the cultivated mushroom industry. Second, we describe the forest-harvested commercial mushrooms. We focus on pine mushroom (Tricholoma magnivelare) and provide an overview of the management in Korea of the closely related matsutake (Tricholoma matsutake) that could be translated to pine mushroom management in British Columbia. Generally, the cultivated mushroom industry in Korea is much larger and more diverse, reflecting local traditions of mushroom use. There is potential for expansion of the industries in both jurisdictions, especially in British Columbia, through the exploration and exploitation of novel native forest mushrooms and through the cultivation of additional exotic species with demonstrated market value.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.188
Teacher spread0.177 · 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

Citations17
Published2007
Admission routes3
Has abstractyes

Explore more

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