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Record W4407330404 · doi:10.1021/acs.jchemed.4c01039

An Interactive Exploration of the Societal Impacts of Inorganic Chemistry─A Base Metal View on Sustainable Catalysis

2025· article· en· W4407330404 on OpenAlexafffundabout
Marissa L. Clapson, Emma C. Davy, Connor S. Durfy, Shauna Schechtel, Sabrina S. Scott

Bibliographic record

VenueJournal of Chemical Education · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsWestern UniversityQueen's UniversityUniversity of British ColumbiaUniversity of Prince Edward Island
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBase metalChemistryCatalysisBase (topology)Green chemistryMetalEnvironmental chemistryNanotechnologyEngineering physicsEngineeringMaterials scienceOrganic chemistryMetallurgyReaction mechanism

Abstract

fetched live from OpenAlex

Sustainable development and green chemistry applications are at the forefront of research and chemistry education as chemists begin to respond to the transgression of planetary boundaries, such as the climate crisis. As such, innovative methods to explore learning and research at chemistry conferences (the professional’s classroom) are required to assist researchers in building their professional network, innovating in their field, and expanding their knowledge in sustainable design. Herin, we describe the development and application of a series of real-world, active learning activities focused on sustainability as it relates to inorganic chemistry, specifically base metal catalysis. Together the activities were hosted during the Societal Impacts of Inorganic Chemistry symposium at the 2023 Canadian Chemistry Conference and Exhibition, representing the first example of a hands-on symposium in the inorganic division at this conference. Due to the broad range and application of the symposium activities described, researchers and educators alike can take inspiration from this interactive approach to engage their communities in the discussion of sustainability and inorganic 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.269

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 head0.004
GPT teacher head0.252
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations4
Published2025
Admission routes3
Has abstractyes

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