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Record W2589127841 · doi:10.18260/1-2--6578

Framework For A Computer Based Corrosion Course

2020· article· en· W2589127841 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDiverse Research and Applications
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsComputer scienceSession (web analytics)Course (navigation)Subject-matter expertHypertextPopulationMultimediaCorrosionSituational ethicsWorld Wide WebExpert systemEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 3213 Session 3213 Framework for a Computer Based Corrosion Course M.A.A. Tullmin and P.R. Roberge Department of Chemistry and Chemical Engineering Royal Military College of Canada, Kingston, Ontario, Canada, K7K 7B4 Abstract A framework for a computer based corrosion course has been developed, with a view to distance learning applications. Potential advantages of the computer based learning approach over a conventional course offering include access to a larger target population and optimization of the shrinking expert instructor pool. However, experience has shown that, despite advances in software applications, an enormous investment in professional time in planning and developing the course material is required. This computer based corrosion course is unique, in that emphasis has been placed on quantitative material, rather than on more descriptive subject matter often found in existing corrosion education products. The course was also designed to be fundamentally interactive in nature, with the use of situational case studies and assignments, in direct contrast to some approaches of re-creating books in hypertext format. Course modules have been created initially in paper based format, to place the scientific/technical course content on a sound footing. Selected case studies and assignments have subsequently been designed in electronic format to develop skills in applying the knowledge and understanding gained from the paper based course notes. Following detailed planning, additional work is underway to present further selected material in electronic format. 1. Introduction Corrosion Science and Engineering (CSE) is an important element of chemical engineering education, at both the university student and practicing professional levels. For the purposes of this paper these two populations will simply be referred to as “the students”. While not all chemical engineering university students receive formal education in this field, most chemical engineers can be expected to have to deal with corrosion damage in technical and/or managerial capacities. At the Royal Military College of Canada (RMC), CSE is an integral part of the Chemical and Materials Engineering program in the Department of Chemistry and Chemical Engineering.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.935
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

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

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 head0.060
GPT teacher head0.328
Teacher spread0.268 · 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

Quick stats

Citations2
Published2020
Admission routes2
Has abstractyes

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