Getting to Neutral: Options for Negative Carbon Emissions in California
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This report is an assessment of negative emissions pathways - ones that physically remove CO2 from the atmosphere - that can help California achieve carbon neutrality by 2045, or sooner. It integrates original research findings with current published research on three main pillars of negative emissions: natural and working lands, carbon capture from biomass conversion to fuels, and direct air capture. The focus and scope of this report is unique: it only addresses practices and technologies for removing carbon dioxide from the air. It also encompasses the entire breadth of strategies, from land management to the latest technological options, and it evaluates the cost of every step of the solution, from waste biomass collection to carbon dioxide transport and geologic storage. The methods are intended to be transparent; details of the calculations and underlying data are included in the report body and appendices. This study intentionally avoids any discussion of policies and does not include current incentives; it provides a range of options, tradeoffs and costs that can be used to inform future policies. The key finding of this report is that carbon neutrality is achievable.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it