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Record W2327465548 · doi:10.2524/jtappij.69.68

The Highest Nip Load Shoepress in Japan-Energy Saving by Introduction of High Nip Load Shoe Press to the Container Board Machine

2015· article· en· W2327465548 on OpenAlexaff
Akio Kato

Bibliographic record

VenueJAPAN TAPPI JOURNAL · 2015
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsNIPContainer (type theory)Automotive engineeringEngineeringMaterials scienceMechanical engineeringComposite material

Abstract

fetched live from OpenAlex

近年,環境に対する企業活動の重要性が求められており,また化石エネルギーが高騰し続ける中,エネルギー使用量削減への取組みが企業にとっての最重要課題である。省エネに取り組む中,製紙工場で使用するエネルギーの大半を占めるドライヤーの蒸気使用量を削減することを目的に,八潮工場の中芯原紙マシンである1号抄紙機では,プレス出口で最大限のドライネスを得るため海外で数多くの実績があるハイニップシュープレスを導入し,大幅な蒸気使用量の削減が図れた。今回の改造を行う際,現在のプレスデザインの主流であるタンデムシュープレスまたはトライニッププレスも検討したが,『プレス出口水分46%以下』を実現するために,中芯専抄マシンとしては設置例が少ないNo.4プレスとしてハイニップシュープレスを設置した。本稿では,改造工事の概要および改造後の省エネ効果について報告する。

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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