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Record W32808003 · doi:10.1039/d0np00028k

Climate Change: Federal Expenditures for Science and Technology

2005· article· en· W32808003 on OpenAlexfundno aff
Michael Simpson, John R. Justus

Bibliographic record

VenueNatural Product Reports · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Environmental Impact
Canadian institutionsnot available
FundersDivision of ChemistryNational Institute of General Medical SciencesU.S. Geological SurveyNational Oceanic and Atmospheric AdministrationNational Institute of Standards and TechnologyNatural Sciences and Engineering Research Council of CanadaSmithsonian InstitutionU.S. Department of AgricultureNational Aeronautics and Space AdministrationU.S. Department of StateU.S. Department of TransportationNational Science FoundationNational Institutes of HealthU.S. Department of Health and Human ServicesUnited States Agency for International DevelopmentU.S. Department of Housing and Urban DevelopmentU.S. Department of CommerceU.S. Department of EnergyU.S. Department of Defense
KeywordsClimate changePolitical scienceNatural resource economicsEnvironmental scienceEconomicsGeology

Abstract

fetched live from OpenAlex

Covering: 2000 to 2020 The hallucinogenic diterpene salvinorin A potently and selectively agonizes the human kappa-opioid receptor (KOR). Its unique attributes-lack of a basic nitrogen, rapid brain penetrance, short half-life-combined with the potential of KOR as an emerging target for analgesics have stimulated extensive medicinal chemistry based on semi-synthesis from extracts of Salvia divinorum. Total synthesis efforts have delivered multiple, orthogonal routes to salvinorin A, its congeners and related analogs with the goal of optimizing its activity towards multiple functional endpoints. Here we review total syntheses of the salvinorin chemotype and discuss outstanding problems that synthesis can address in the future.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.023
GPT teacher head0.288
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2005
Admission routes1
Has abstractyes

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