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Record W7015389706

Status Review of Californiaâs Low Carbon Fuel Standard, 2011â2018 Q1\n September 2018 Issue\n

2018· article· en· W7015389706 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueeScholarship (California Digital Library) · 2018
Typearticle
Languageen
FieldEngineering
TopicSAS software applications and methods
Canadian institutionsnot available
Fundersnot available
KeywordsDiesel fuelGallon (US)GasolineRenewable energyRenewable fuelsGreenhouse gasBiogasNatural gasElectricity
DOInot available

Abstract

fetched live from OpenAlex

From 2011–2017, the share of alternative fuels in California’s transportation energy grew from 6.1 percent to 8.5 percent. Of alternative fuel energy, the portion coming from non-liquid fuels increased from 7.6 percent to 13.5 percent over the period.\n Through 2018 Q1, total emissions reduction requirements under the regulation were 28.9 million tons (MMT) CO2e. Actual reported emissions reductions were 38.3 MMT CO2e, representing overcompliance of 9.3 MMT CO2e, creating a system-wide credit “bank” that can be used to meet future targets.\n In 2017 and 2018 Q1, program deficits exceeded credits for the first time, by 0.1 MMT CO2e and 0.4 MMT CO2e, respectively, drawing down the credit “bank.”\n Increases in alternative fuel use and declines in carbon intensity (CI) rating came primarily from the diesel pool. Biomass-based diesel—biodiesel and renewable diesel—accounted for 0.4 percent of liquid diesel fuel by volume in 2011 and 15.6 percent in 2018 Q1. Natural gas in transportation grew 111 percent from 2011–2017 to 178.1 gasoline gallon equivalent (gge). Of this natural gas, biogas use was close to nil in 2011 but approximately two-thirds in 2017.\n Among gasoline substitutes, electricity use grew from less than 0.5 percent of alternative energy in 2011 to 4.5 percent in 2018 Q1. Use of ethanol, the largest renewable fuel by volume, remained close to a “blendwall” of 10 percent blended with gasoline.\n Prices of LCFS compliance credits (each representing 1 MMT CO2e) fluctuated. Average per- credit price increased from $20 to $80 in 2013, ranged between $20 and $30 in 2014 and 2015 under a frozen standard of 1%, rose above $100 in 2016 when the freeze was lifted, and exceeded $160 in summer 2018 as the California Air Resources Board (CARB) was in the process of adopting more stringent targets for 2030.\n LCFS amendments to be voted on at the September 26-27, 2018, CARB board meeting to take effect in 2019, include: a 2030 target of 20 percent CI reduction below 2010 levels; independent verification and monitoring of fuel pathway CI rating inputs; allowing alternative aviation fuel to generate program credits; a protocol for carbon capture and sequestration credits; credits for low- or zero-carbon intensity electricity use; requiring use of a portion of residential electricity credits to fund a statewide point-of-sale incentive program to electric vehicle (EV) buyers if such a program is approved by the California Public Utilities Commission; and introducing capacity credits for EV fast chargers and hydrogen fuel stations. The “capacity credit” provision would permit credit generation untied to current emissions reductions and favor particular fuels (those used in zero emission vehicles, which have no tailpipe emissions) for the first time.\n LCFS-like programs are in development in Canada (a Clean Fuel Standard to cover transportation, industry, and building sectors) and Brazil (the RenovaBio program focused on renewable liquid fuels and biogas). Neither plans to account for indirect land use change emissions in carbon intensity lifecycle analysis at program outset. Implementation of the Oregon and British Columbia LCFS programs is proceeding.\n \n Click here to see all the California LCFS status reviewsÂ

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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.

Opus teacher head0.013
GPT teacher head0.249
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it