Qualitative & Quantitative Gas Stoichiometry and Determination of an Unknown Alkali Carbonate
Bibliographic record
Abstract
This experiment looks at two types of chemical reactions that produce hydrogen and carbon dioxide gases. It explores both qualitative observations (no measurements or numbers involved) about the reactions, as well as quantitative measurements of the volume of gas produced to explore concepts of stoichiometry and the ideal gas law. These concepts will be used to relate the stoichiometry of gas produced to the molar mass of an unknown to identify which alkali metal salt it is. The experiment emphasizes green chemistry principles that are used in chemistry labs on a daily basis to reduce environmental impact. This laboratory material is adapted with permission from the laboratory manual developed by Prof. Jessica D’eon and Prof. Kristine Quinlan at the University of Toronto for a first-year general chemistry experiment. It is further discussed in the publication: J. Chem. Educ., 2019, 96 (12), 2836–2844. DOI:https://doi.org/10.1021/acs.jchemed.9b00287
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".