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Record W4249798167 · doi:10.1201/9780203747902

Mechanical Conveyors

2018· book· en· W4249798167 on OpenAlexaboutno aff
Muhammad E. Fayed, Thomas S. Skocir

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This book is a comprehensive, practical guide and reference to today's mechanical conveyor systems. It covers all types of mechanical conveyors, providing in-depth information on their design, function and applications. More than 180 photographs and schematics illustrate details of design and system layout. An introductory chapter provides an understanding of the characteristics of various types of bulk solids, including their conveyability and the types of conveying systems most effective for each. Following chapters examine each of five major categories of conveying systems, with practical details on their design, operation and applications. The final chapter presents basic information on motors and drives for conveying systems, as well as related equipment such as speed reduction systems and conveyor brakes. The emphasis throughout the text is on practical engineering and operating information, with a minimum of theory. The presentation is systematic and organized for easy reference. A very detailed index enables the quick location of needed information. This guide and reference will be useful to all engineers and other personnel involved in the continuous movement of bulk solids. It serves as both a basic introduction and a desk-top reference. The AuthorsDr. Fayed is a Professor and Director of the Powder Science & Technology Group at Ryerson Polytechnic University in Toronto. He is also a licensed Consulting Engineer, a Fellow of the American Institute of Chemical Engineers and the Canadian Society of Chemical Engineering. Previously he held positions in process design and development with ICI, Davy McKee, M. W. Kellogg, and Peabody. He has lectured at numerous seminars and workshops at meetings of the American Institute of Chemical Engineers, and other organizations. He has published many papers on particulate technology and is the co-editor of Powder Science & Technology Handbook. Thomas Skocir in an engineer presently with ECO-TEC

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)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.245
Threshold uncertainty score0.819

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0050.005
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2450.139

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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