Bibliographic record
Abstract
New Zealand produces premium quality wines and its wine industry is growing rapidly. The winegrowing regions have growing degree-days that range from 900 in cool Central Otago and Canterbury, to more than 1600 in the warmest region in the country, Auckland. Average growing season temperatures for the same regions range from approximately 14.3°C to 17.6°C. Most trophy-winning red wines are grown in areas with a climate cooler than where similar wines are grown to high standard internationally. New Zealand vineyards are planted mainly on flat alluvium and aggradation gravels with slopes of less than 3°. Rapid growth is pushing new plantings onto adjacent hillsides that are underlain by greywacke, schist, and (less commonly) limestone. The expansion of the industry onto these different substrates will affect grape and wine characteristics and may lead to new styles of New Zealand ultra-premium wines. SOMMAIRE La Nouvelle-Zelande produit des vins de hautes qualites et son industrie vini-cole croit rapidement. Les degresjours de croissance des regions vinicoles vont de 900 dans les regions fraiches d’Otago et de Canterbury, et depasse 1 600 dans la region d’Auckland, la plus chaude du pays. Les temperatures de croissance moyenne pour ces memes regions vont de 14,3 °C a 17,6 °C. La plupart des vins rouges primes proviennent de regions au climat plus frais que leurs equivalents ailleurs dans le monde. Les vignes de Nouvelle-Zelande sont cultivees dans des sols alluvionnaires plats et des graviers d’aggradation au pendage de moins de 3°. La croissance rapide de l’industrie vinicole entraine la plantation de vignes sur les sols des collines environnantes qui recouvrent des formations de grauwackes, de schistes argileux, et plus rarement de calcaires. L’expansion de l’industrie vinicole sur ces nouveaux substrats aura des repercussions sur les caracteristiques du raisin et du vin, ce qui pourrait donner de nouveaux styles de tres grands vins de Nouvelle-Zelande.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".