Trend 1980 - 2010. Energy Information Administration. International Energy Statistics: Energy Intensity | Country: Canada | Indicator: Energy Intensity - Total Primary Energy Consumption per Dollar of GDP (Btu per Year 2005 U.S. Dollar, 1980-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 004-014-041.
Bibliographic record
Abstract
Energy Information Administration (2015). International Energy Statistics: Energy Intensity | Country: Canada | Indicator: Energy Intensity - Total Primary Energy Consumption per Dollar of GDP (Btu per Year 2005 U.S. Dollar, 1980-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 004-014-041. Dataset: Reports statistics on energy intensity by country, as available. Energy intensity refers to a ratio of energy consumption to another metric, typically national gross domestic product (GDP) in the case of a country's energy intensity. Sector-specific intensities may refer to energy consumption per household, per unit of commercial floorspace, per dollar value industrial shipment, or another metric indicative of a sector. Improvements in energy intensity include energy efficiency and conservation as well as structural factors not related to technology or behavior. Energy intensity using market exchange rates is calculated by dividing the data on total primary energy consumption in quadrillion Btus for each country and year by the GDP using either market exchange rates or purchasing power parities (PPPs). The dataset provides data for 220 countries, as available, on energy-related metrics, including total and crude oil production, oil consumption, natural gas production and consumption, coal production and consumption, electricity generation and consumption, primary energy, energy intensity, CO2 emissions and imports and exports for all fuels. Data are sourced from Energy Information Administration research, as well as from national and international agencies, listed at http://www.eia.gov/cfapps/ipdbproject/docs/sources.cfm. Category: Energy Resources and Industries, International Relations and Trade Source: Energy Information Administration The Energy Information Administration (EIA), created by Congress in 1977, is an independent statistical and analytical agency within the United States Department of Energy. Its mission is to provide policy-independent data, forecasts, and analyses to promote sound policy making, efficient markets, and public understanding regarding energy and its interaction with the economy and the environment. http://www.eia.doe.gov/ Subject: Energy Demand, Energy Consumption
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.027 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.059 |
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".