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Record W2316738208 · doi:10.2524/jtappij.65.539

Utilizing Wood Biomass as Energy such as Power Generation and Thermal Use-Current Situation of its Utilization and Problems to be Solved when Developing Biomass Utilization into Business-

2011· article· en· W2316738208 on OpenAlexaff
Junji Shinoda

Bibliographic record

VenueJAPAN TAPPI JOURNAL · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMetallurgy and Material Science
Canadian institutionsCanadian Journal of Communication (Canada)The Journal of Student Science and Technology
Fundersnot available
KeywordsBiomass (ecology)Current (fluid)Electricity generationNatural resource economicsThermal energyEnvironmental scienceEnergy (signal processing)Power (physics)Waste managementEnvironmental economicsBusinessEconomicsEngineeringAgronomyMathematicsElectrical engineeringBiology

Abstract

fetched live from OpenAlex

2002年の新エネルギー法政令改正に伴い,木質バイオマス発電施設建設への助成策が講じられ,企業や自治体,森林組合などによる施設整備が相次いだ。また,2003年にはRPS法が施行され,木質バイオマス発電施設の建設が加速された。さらに,セルロース系バイオエタノールなどの次世代バイオ燃料開発,バイオマス熱の利用拡大,バイオマス混焼による石炭火力発電などの木質バイオマスエネルギー利用に関する計画が幅広く進められている。不況などの影響で木質チップへの需要が緩和する事態が続いていたが,昨今,バイオマス混焼による石炭火力発電やバイオマス専焼の大型発電所などが計画されるようになり,再び需給がタイト化すると予想されている。森林資源のカスケード利用の観点からは,エネルギー利用は最終的な手段と位置づけられるが,昨今ではESCO,カーボンオフセット,CO2排出量取引などの新たな付加価値を付加したビジネスモデルも相次ぎ発表され,さらには木質バイオマス発電の固定価格買取制度の導入も見込まれている。こうした情勢変化は,最大の課題となっていた事業採算性にも期待をつなげる雰囲気を創り出しつつある。木質バイオマス利用による産業化はなかなか容易でないことも確かだが,一方ですぐにでもできることがあることも確かだ。CO2削減などを目的にいくつかの事業が動き出しているタイミングをとらえ,地域にバイオマス活用の道筋をつけていくことが必要だろう。2020年の木材自給率50%・低炭素社会実現を謳った『森林・林業再生プラン』の有効な促進策としても,強力に推進すべき時を迎えていると言えるだろう。

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0070.006
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.155
GPT teacher head0.295
Teacher spread0.141 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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Same venueJAPAN TAPPI JOURNALSame topicMetallurgy and Material ScienceFrench-language works237,207