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Record W2205366479 · doi:10.5822/978-1-61091-460-4_2

Physical Climate Forces

2012· book-chapter· en· W2205366479 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIsland Press/Center for Resource Economics eBooks · 2012
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEcosystemCoral reefClimate changeEnvironmental scienceWatershedWetlandFisheryEstuaryGeographyOceanographyEnvironmental protectionEcology

Abstract

fetched live from OpenAlex

More than 50 percent of Americans live in coastal watershed counties, a percentage that continues to increase (see section 1.3). In addition, the coast is home to the majority of major urban centers as well as major infrastructure such as seaports, airports, transportation routes, oil import and refining facilities, power plants, and military facilities. All of these human uses, which represent trillions of dollars in economic investment as well as valuable coastal ecosystems, are vulnerable in varying degrees to rising global temperature and hazards such as sea-level rise, storms, and extreme floods. Intense human activity over the past century has degraded many coastal environments and stressed natural ecosystems. Nationwide, nearshore areas and estuaries are polluted with excess nitrogen and other chemicals, toxic coastal algal blooms are increasing, fish stocks are depleted, wetland loss has been dramatic, and coral reefs are bleached and dying. Climate change exacerbates these stresses on ecosystems.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.222
Teacher spread0.198 · 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