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Record W30059019 · doi:10.3791/57778

USING PROGRAM VISUALIZATION TOOLS TO FACILITATE TEACHING AND LEARNING COMPUTER PROGRAMMING: A LITERATURE REVIEW

2012· review· en· W30059019 on OpenAlexfundno aff
K. Kaseb, F. Zandkarimi, M. Sayedi, E. Khoshkhoo, F. Badakhshan

Bibliographic record

VenueEDULEARN12 Proceedings · 2012
Typereview
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsComputer scienceVisualizationHuman–computer interactionSoftware engineeringMultimediaArtificial intelligence

Abstract

fetched live from OpenAlex

Air volume changes created by a conscious subject breathing spontaneously within a body box are at the basis of plethysmography, a technique used to non-invasively assess some features of the respiratory function in humans as well as in laboratory animals. The present article focuses on the application of the double-chamber plethysmography (DCP) in small animals. It provides background information on the methodology as well as a detailed step-by-step procedure to successfully assess respiratory function in conscious, spontaneously breathing animals in a non-invasive manner. The DCP can be used to monitor the respiratory function of multiple animals in parallel, as well as to identify changes induced by aerosolized substances over a chosen time period and in a repeated manner. Experiments on control and allergic mice are used herein to demonstrate the utility of the technique, explain the associated outcome parameters, as well as to discuss the related advantages and shortcomings. Overall, the DCP provides valid and theoretically sound readouts that can be trusted to evaluate the respiratory function of conscious small animals both at baseline and after challenges with aerosolized substances.

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 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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0010.003
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 head0.146
GPT teacher head0.435
Teacher spread0.288 · 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 teacher head, not a consensus.

Study designOther design
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

Citations0
Published2012
Admission routes1
Has abstractyes

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