Bibliographic record
Abstract
Here is the new template for the Canadian Acoustics articles from the Canadian Acoustical Association.The electronic versions of this template are available in L A T E X and Microsoft R Word formats on the journal website, in the "Authors Guidelines" section.The present template is written in Lorem Ipsum and shows the "final" format for publication.For L A T E X, the template can be compiled with three options : "francais" or "english" for the desired language, "article" or "proceeding" depending on the manuscript type and "preprint" or "final" depending on stage of publication.During the submission of an article to the journal, the "article" and "preprint" options must be used.Later, once the article has been accepted, the "article" and "final" options must be used.For conference proceedings, the "proceeding" and "final" options must be used.Note that for Word, the proposed template corresponds to an article in its final formatting, ready for publication.During the submission of an article to the journal, this template must be edited so that the entire text is double spaced and each line numbered.For conference proceedings, the same template must be used, but modified so that the "Abstract" section is omitted.Please note, that whatever word processor is used, all the files submitted to Canadian Acoustics journal must be in PDF format.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.022 |
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 source (direct Gemma or distilled Codex), 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".