Trend 1961 - 2011. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization Statistics: Commodity Balance - Livestock, Fish | Country: Canada | Item: Cream | Element: Domestic supply quantity - tonnes, 1961-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 067-001-029.
Bibliographic record
Abstract
Food and Agriculture Organization of the United Nations (2017). Food and Agriculture Organization Statistics: Commodity Balance - Livestock, Fish | Country: Canada | Item: Cream | Element: Domestic supply quantity - tonnes, 1961-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 067-001-029. Dataset: Commodity balances show balances of food and agricultural commodities in a standardized form. The scope of standardization is to present these data in a less detailed form for a selected number of commodities without causing any significant loss of the basic variables monitoring the agricultural sector. The selected commodities include the equivalents of their derived products falling in the same commodity group, but exclude the equivalents of by-products and derived commodities, which through processing, change their nature and become part of different commodity groups. The commodity list in this domain has been generally confined to primary commodities - except for sugar, oils and fats and beverages. Whenever possible trade in processed commodities is expressed in the originating primary commodity equivalent. Rice is expressed in milled equivalent. The time-series and cross-sectional data provided here are from the FAOSTAT database of the Food and Agriculture Organization of the United Nations. Statistics include measures related to the food supply; forestry; agricultural production, prices, and investment; and trade and use of resources, such as fertilizers, land, and pesticides. As available, data are provided for approximately 245 countries and 35 regional areas from 1961 through the present. The data are typically supplied by governments to FAO Statistics through national publications and FAO questionnaires. Official data have sometimes been supplemented with data from unofficial sources and from other national or international agencies or organizations. In particular, for the European Union member countries, with the exception of Spain, data obtained from EUROSTAT have been used. Category: Agriculture and Food, International Relations and Trade Source: Food and Agriculture Organization of the United Nations Established in 1945 as a specialized agency of the United Nations, the Food and Agricultural Organization’s mandate is to raise levels of nutrition, improve agricultural productivity, better the lives of rural populations, and contribute to the growth of the world economy. Staff experts in seven FAO departments serve as a knowledge network to collect, analyze, and disseminate data, sharing policy expertise with member countries and implementing projects and programs throughout the world aimed at achieving rural development and hunger alleviation goals. The Statistics Division of the Food and Agricultural Organization collates and disseminates food and agricultural statistics globally. http://www.fao.org/ Subject: Agricultural Imports, Food Supply, Agricultural Exports, Agricultural Production, Agricultural Commodities, Fish Products, Livestock, Agricultural Products, Agricultural Trade, Food Products
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.022 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.070 | 0.081 |
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".