Data for publication "Asymmetry in the climate-carbon cycle response to positive and negative CO2 emissions"
Bibliographic record
Abstract
This dataset contains output from UVic ESCM simulations driven by instantaneous ('pulse') CO2 emissions and removals. File names starting with 'tsi_avg' contain annually and globally averaged variables (netcdf format). File names starting with 'tavg' contain annually averaged spatially resolved variables (netcdf format). 1) tsi files: The suffix 'Yxco2' indicates the atmospheric CO2 concentration from which the emission/removal is applied 'equil' or 'trans" indicate whether the emission/removal is applied from an equilibrium or a transient climate state (e.g. '2xco2equil' inidicates that the emission/removal is applied from a state in equilibrium with twice the pre-industrial CO2 concentration) 'spinup' indicates a spinup simulation for the given atmospheric CO2 concentration 'x00', 'negx000', indicate the size of the pulse CO2 emission and removal, respectively 'ctl' indicates a control simulation with zero CO2 emissions 'zeroemit' indicates a zero CO2 emission simulation initialized from a transient climate state '10pyr' indicates simulations with CO2 emission/removal rates of +/- 10 GtC/yr (as opposed to instantaneous emissions/removals) 'bgc' indicates bigeochemically coupled simulations 2) tavg files The first number indicates the time interval. Except for the 'spinup' files, all tavg files include ten time slices (1975-2065 for simulations initialized from 2xCO2; 2045-2135 for simulations initialized from 2xCO2). These correspond to 100-190 years after the emission/removal is applied. Files with the suffix 'landC' contain a subset of land carbon cycle variables. See article reference for further details.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.184 | 0.124 |
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".