MétaCan
Menu
Back to cohort
Record W7098727784

International Conference on Engineering Education August 6 -- 10, 2001 Oslo, Norway

2001· article· en· W7098727784 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumGeneral partnershipMultidisciplinary approachEngineering educationTeamworkState (computer science)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Under the NSF-CRCD program, an innovative team-based and industry-oriented curriculum development is underway at The Ohio State University (OSU). This curriculum builds around the multifaceted partnership at the NSF Center for Industrial Sensors and Measurement (CISM) that provides a framework for interaction among scientists, engineers, students and business leaders. Under this program, a three-course sequence in sensor materials including instructional laboratories with industrial experience for senior undergraduate and starting graduate students has been developed. This paper describes the offering of a 3-credit hour honors course during the Spring Quarter of 2001. Students were exposed to: (i) lectures given by a multidisciplinary team of experts covering basic scientific and technological principles, (ii) computer simulation and modeling of sensor arrays, and (iii) teamwork experience in a laboratory experiment leading to the fabrication of a sensor probe starting from raw materials to probe design, packaging and testing.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.495
Threshold uncertainty score0.707

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5050.205

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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2001
Admission routes1
Has abstractyes

Explore more

Same topicBioactive natural compoundsFrench-language works237,207