Bibliographic record
Abstract
These twelve lessons, and an introductory lesson, are tutorials in basic topics of introductory chemistry. They are suitable for school use, individual study, or distance learning. They are particularly valuable as review material for students in more advanced courses who may have been away from the subject for some time. They contain a great variety of problems and exercises driven by random-number generators, so that the same problem never repeats exactly.The lessons are, for the most part, Socratic dialogues in which the student is required to answer questions and perform simulated experiments in order to discover chemical principles. They are organized in an intuitive chapter and page structure. One may move readily around each lesson. There are many on-screen facilities such as help, data tables, and a calculator."Chemical Calculations: Combustion Analysis" is one of the 12 modules in Introductory Chemistry Lessons. This screen shows an animation of the combustion of a hydrocarbon. Note the on-screen data table displayed at the bottom of the screen and the on-screen calculator in the lower right corner.Many lessons contain simulations and animations corresponding to those in the previously published Simulations and Interactive Resources (1). The lessons on the periodic table, oxidation numbers, nomenclature, and reactions will be reinforced by playing the Periodic Table Games (2). These latter two programs are meant to be coordinated with the lessons. They are now available for free download by Journal subscribers.All of the lessons end with comprehensive review quizzes. It is good strategy for a student to look first at the quiz, to ascertain whether the material of the lesson will be of value, or whether only certain topics are needed. Ten of the quizzes produce scores out of 100. Scores may be recorded in a dataset, and presented in histogram form. There is a "hall of fame" display, which shows the top fifteen scores. The instructor may view the lesson scores or reset the scoreboards. Scores are kept starting on the date of resetting.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.007 | 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".