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AN INTERVENTION STRATEGY TO ASSIST ACADEMICALLY UNDER-PERFORMING MECHANICAL ENGINEERING UNDERGRADUATE STUDENTS IN A SOUTH AFRICAN UNIVERSITY

2013· article· en· W28751027 on OpenAlex
F. Martínez

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEDULEARN13 Proceedings · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsIntervention (counseling)Mathematics educationEngineering educationEngineeringEngineering ethicsPedagogyMedical educationEngineering managementPsychologyMedicine

Abstract

fetched live from OpenAlex

The size and settling velocity of oil-mineral aggregates (OMAs) derived from diluted bitumen are primary constituents in predictive models for evaluating the potential fate of oil spilled in the aquatic environment. A series of low sediment concentration (15mg·L<sup>-1</sup>), colder water (<10°C) wave tank experiments designed to measure variability in these parameters in naturally-formed OMAs in response the presence or absence of chemical dispersant are discussed. Corresponding lab experiments revealed settling velocities of artificially formed OMAs on the order of 0.1-0.4mm·s<sup>-1</sup>. High-resolution imagery of settling particles were analyzed for particle size, density and settling velocity. In situ formation of OMAs in the wave tank was unsuccessful. Possible effects of chemical dispersant on natural sediment flocculation, the size of suspended oil droplets and clearance rates of suspended particles are discussed.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.291
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