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Record W4385779049 · doi:10.2172/1813301

Frequency Comb-Based Remote Methane Observation Network (Final Scientific/Technical Report)

2021· report· en· W4385779049 on OpenAlexfundno aff
S. Coburn, Caroline B. Alden, Robert Wright, Kevin C. Cossel, Esther Baumann, Subhomoy Ghosh, Gar-Wing Truong, A. Karion, Colm Sweeney, Kuldeep Prasad, Ian Coddington, Nathan R. Newbury, Greg Rieker

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersAdvanced Research Projects AgencyAdvanced Research Projects Agency - EnergyUniversity of Colorado BoulderNational Oceanic and Atmospheric AdministrationDefense Advanced Research Projects AgencyNational Institute of Standards and TechnologyOffice of Fossil EnergyCarbon Management CanadaU.S. Department of Energy
KeywordsMethaneEnvironmental scienceMethane emissionsRemote sensingComputer scienceGeographyChemistry

Abstract

fetched live from OpenAlex

Accomplishments and ObjectivesThrough the ARPA-E MONITOR program, the CU Boulder/NIST/NOAA team sought to develop a regional methane monitoring system based on dual-frequency comb spectrometry.As part of working towards that goal, a number of Tasks and Milestones were pursued, as summarized in Attachment 3, the Technical Milestones and Deliverable.The table below contains a summary of the actual performance against all milestones outlined in the award.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.011

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 head0.072
GPT teacher head0.296
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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