Bibliographic record
Abstract
This paper looks to provide insight on the Canadian stereotype of using and producing maple syrup, investigating if the Canadian production of the sweetener could support each Canadian having maple syrup at breakfast every day for a year. First, it is estimated how much maple syrup would be consumed for a specific age group and sex using suggested daily Calorie (kcal) values and Canadian demographic population estimates. A sample calculation is outlined for males aged 20-24, finding that solely for this age group it would require 6.24x10 4 L of maple syrup for one day’s consumption. This method is then repeated for each age group and sex (see Appendix), then summed and multiplied by 365, getting a final value of 5.11x10 8 L of maple syrup in total for the whole year. Therefore, it was determined that since the annual production of maple syrup in 2017 was only 5.69x10 7 L, it would not be sustainable for every Canadian to have maple syrup at breakfast for an entire year.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".