Message in a bottle: the wine terroir concept in Canada, from an earth sciences perspective
Bibliographic record
Abstract
Geology is an important, but less-recognized, scientific factor in the agriculture of long-lived, deep-rooted plant crops such as vineyards, orchards and forests. This report focusses on the concept of vineyard agriculture as one example of how geological factors may affect a resulting crop. While acknowledging the pre-eminence of climatic factors, Earth Science forms part of the multi-factor, holistic concept of mp;lt;"terroirmp;gt;", which can help to maximize the potential of wine quality in a cool-climate country like Canada. Key publications, such as Wallace (1972), Wilson (1998), the series launched by Haynes (1999), and Macqueen and Meinert (2006) have emphasized the role of geology in the terroir concept and set the scene for further study. Thinking conceptually, from the ground upward, the main components of the Terroir concept can be divided into: 1) Geological (bedrock geology, surficial geology, soil, groundwater, topography and bodies of water); 2) Climatological (latitude, macro-climate, rainfall, sunshine, temperature and micro-climate); 3) Biological (vineyard age, grape varietal, microorganisms, nutrients and yeast); and, 4) Agricultural (viticultural techniques, management practices) (although this last is not dealt with in this report). While not an exhaustive study, this report is meant to bring together and organize a preliminary summary of relevant information and sources, in order to suggest areas of study where geoscience may be able to contribute to improved understanding. Although this report focusses on wine terroir, the principles are equally applicable to other, similar long-lived, deep-rooted plant systems such as fruit orchards (particularly cider production, which is closely-related to wine-making), olive orchards and forests. Each of the terroir factors (including the geological ones) needs to be studied, and new understanding improved and applied within each wine region and sub-region of Canada, to maximize the potential for quality wine from our northern, cool-climate, constantly-evolving wine industry.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".