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Record W3005799560 · doi:10.1515/npprj-2019-0083

On the development of the refiner mechanical pulping process – a review

2020· review· en· W3005799560 on OpenAlexfundno aff
Christer Sandberg, Jan Hill, Michael A. Jackson

Bibliographic record

VenueNordic Pulp & Paper Research Journal · 2020
Typereview
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsnot available
FundersMittuniversitetetUniversity of British ColumbiaStiftelsen för Kunskaps- och Kompetensutveckling
KeywordsProcess (computing)Focus (optics)Process developmentComputer scienceManufacturing engineeringEngineeringProcess engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract This paper is a review of the development of the mechanical pulping process with focus on refiner-based processes. The intention is to provide an overview of the trends and the major advances in the development of the mechanical pulping (MP) process. The focus is on the development of the entire MP process, rather than the refiner as such. However, when discussing the MP process development, it is inevitable to consider the development of the refiner unit operation briefly. Processes for printing papers based on softwood is mainly discussed, but board processes are discussed briefly as well.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.125
GPT teacher head0.399
Teacher spread0.274 · 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
GenreReview

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

Citations28
Published2020
Admission routes1
Has abstractyes

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