Research in Manitoba Provides Growth for the Potato Industry
Bibliographic record
Abstract
Historically, Manitoba’s potato industry has been the second largest in Canada, after Prince Edward Island’s. From 1980 to 2018, we calculated that the approximate direct monetary value of funding into potato research was $5.91 million for projects that were either partially funded by the Governments of Manitoba and/or Canada or took place at the Canada-Manitoba Crop Diversification Centre. The Manitoba potato industry grew dramatically between 1990 to 2017. The cash receipt amount for potatoes in Manitoba increased by 695% from 1990 to 2017. In terms of the monetary value, the increase in dollar value from cash receipts from 1990 to 2017 was $224.69 million. The domestic export for potatoes from Manitoba has increased by 8,805% from 1990 to 2017. In this export, there was $480 million increase from 1990 to 2018. The objective of this impact report is to investigate and evaluate how research funding focused on potato production has contributed to the $1.4 billion Manitoba potato industry complex. The 38-year history of potato research in Manitoba as described here demonstrates that research funded by Manitoba Agriculture and other sources have contributed to the overall growth of the industry and to the economic strength of the province.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".