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Record W3088640101 · doi:10.1021/acs.jchemed.0c00887

The Science of Human Health—A Context-Based Chemistry Course for Non-Science Majors Incorporating Systems Thinking

2020· article· en· W3088640101 on OpenAlexaff
David R. Armstrong, Judith C. Poë

Bibliographic record

VenueJournal of Chemical Education · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)Chemistry educationChemistryCritical thinkingSystems thinkingEngineering ethicsScience educationMathematics educationPsychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract The Science of Human Health is an undergraduate chemistry course for non-science majors. This course presents chemistry content following a systems thinking approach and was created with the goal of providing students with the necessary chemistry foundation to make informed decisions which will affect their own well-being and their global citizenship. Chemistry is taught and learned on a need-to-know basis in order to address the three themes: nutrition for the prevention of disease, diagnostics for the detection of disease, and medicine for the treatment of disease. The course relies heavily on active learning assignments and group work, promoting the development of critical thinking and communication skills. Presenting chemistry with a systems thinking orientation through the context of human health and well-being is particularly effective at engaging non-science students who might otherwise struggle to relate to chemistry.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0350.012

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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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
GenreMethods

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

Citations13
Published2020
Admission routes1
Has abstractyes

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