CMIP7 ScenarioMIP historical timeseries for harmonisation and simple climate model workflow
Bibliographic record
Abstract
History for CMIP7 ScenarioMIP emissions harmonisation The files here are compiled historical experiment timeseries. They were compiled for use as part of the CMIP7 ScenarioMIP exercise and are primarily used for supporting emissions harmonisation. Here, 'harmonisation' means alignment of modelled emissions from IAMs with the emissions used for the CMIP7 historical experiment. As a result, they are a key input for the process of 'gridding' emissions (i.e. taking raw emissions from IAMs and assigning them to a spatial grid, ready for use by Earth System Models (ESMs)) and for running the simple climate model based assessment of the scenarios to derive a first-order estimate of the warming associated with these scenarios (the ESMs will quantify the warming and other climate change associated with these scenarios as part of ScenarioMIP, and this quantification is underpinned by a deeper, more physically-based set of modelling assumptions.) There are three different files, provided in three different formats each. The three files are: gridding-history*: the history used for harmonisation at the 'gridding' level. The gridding requires emissions with regional and sectoral detail. It also has to support every IAMs' native regions. As a result, there are lots (of order 30 000) timeseries. country-history*: same as above, but at the country level rather than in native IAM regions. global-workflow-history*: the history used for harmonisation at the 'global' level. This only has global total emissions, except for CO2 which is split into fossil-based and land-based (i.e. originating from the land carbon pool) emissions. It includes a number of species that are not used in the gridding workflow but are relevant for climate projections e.g. all of the greenhouse gases covered by the Montreal Protocol. As a result, there are only 52 timeseries. The files were derived using the code in this repository: https://github.com/iiasa/emissions_harmonization_historical. The filenames are composed of identifiers related to the processing of each of the different input data sources. To identify the exact meaning of these identifiers, please see the processing code in https://github.com/iiasa/emissions_harmonization_historical.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.185 | 0.121 |
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".