Transient Holocene climate simulation data forced with different land-use reconstructions
Bibliographic record
Abstract
Summary Transient non-accelerated coupled climate model simulations covering the past 10,000 years testing different reconstructions of land-use. Format NetCDF format on the HadCM3 model grid (3.75 x 2.5 degrees longitude x latitude). Variables lu - land-use fraction prescribed in each gridcell at a 500 year timestep from 9750 to 250 years before CE 1950. temp_mm_1_5m - simulated surface air temperature for years 1 to 10,000 of the simulations which cover the period from 10,000 to 0 years before CE 1950. Climate Model HadCM3B-M2.1d (Valdes et al. 2017, doi: 10.5194/gmd-10-3715-2017) with modifications to atmospheric convection and vegetation moisture stress as described in Hopcroft & Valdes, (2021, doi: 10.1073/pnas.2108783118). Transient Holocene Forcing Forced with orbit, greenhouse gases, sea-level (coastline, topography, salinity), solar irradiance and land-use (as listed below). Land-use scenarios noLU - constant with no land-use anywhere. KK10 - Kaplan et al (2009, doi: 10.1016/j.quascirev.2009.09.028) and Kaplan et al. (2011, doi: 10.1177/0959683610386983). HYDE v3.2 - Goldewijk et al (2017, doi: 10.5194/essd-9-927-2017). HYDE v3.3 - this work. REVEALS - this work, only covers Europe, North America and China. Publication P.O. Hopcroft, B. Pirzamanbein, K.K. Goldewijk, J. Lindstrom, A. Dawson, J.O. Kaplan, F. Li & M.J. Gaillard. Surface temperature response to Holocene land use scenarios, in prep. Contact Peter Hopcroft (University of Birmingham): p.hopcroft@bham.ac.uk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".