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Record W4211197126 · doi:10.1007/978-3-030-45216-2_7

Urban Soils

2020· book-chapter· en· W4211197126 on OpenAlexaff
Richard V. Pouyat, Susan D. Day, Sally Brown, Kirsten Schwarz, Richard E. Shaw, Katalin Szlávecz, Tara L. E. Trammell, Ian D. Yesilonis

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeographyCensusPopulationPaceSocioeconomicsMegacityEnvironmental protectionDemographyEconomyEconomics

Abstract

fetched live from OpenAlex

The global population is expected to exceed 11 billion before the end of the twenty-first century (United Nations 2015). Populations within urban areas are also increasing, with the number of mega-sized (ten million people or more) cities expected to increase from 10 in 1990 to 41 in 2030 (United Nations 2015). In the United States, the human population is not growing as fast as the rest of the world, but the expansion of urban areas has proportionally kept pace, or exceeded, global estimates, with land devoted to urban uses growing by more than 34% between 1980 and 2000 alone (USDA NRCS 2001). Additionally, by 2010 almost 250 million people lived in urban areas, which roughly accounts for 81% of the total population of the United States (U.S. Census 2010).

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 categoriesInsufficient 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: Other · Consensus signal: Other
Teacher disagreement score0.196
Threshold uncertainty score0.964

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0630.036

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 head0.012
GPT teacher head0.184
Teacher spread0.173 · 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; both teacher heads agree on what is shown here.

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

Citations26
Published2020
Admission routes1
Has abstractyes

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