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Record W3124723440 · doi:10.1093/wber/lhaa018

Caloric Intake and Energy Expenditures in India

2020· article· en· W3124723440 on OpenAlex
Shari Eli, Nicholas Li

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

VenueThe World Bank Economic Review · 2020
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCaloric theoryFalling (accident)Energy expenditureAnthropometryEconomicsCaloric intakePopulationDemographyCalorieDemographic economicsBody weightMedicineEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

Abstract Total energy expenditures for the Indian population between 1983 and 2012 are estimated to shed light on the debate concerning falling measured caloric intake during the period (A. Deaton and J. Drèze. 2009. “Food and Nutrition in India: Facts and Interpretations.” Economic and Political Weekly 44(7): 42–65). Anthropometric, time-use, and detailed employment surveys are used to estimate the separate components of total energy expenditure related to metabolism and physical activity levels. Despite a significant drop in adult physical activity levels, total energy expenditures are flat overall between 1983 and 2012. Rising metabolic requirements due to increases in weight dampened the effect of falling activity levels on total energy expenditure. In addition, the 10 percent decline in the population share of children in the period raised average total energy expenditures considerably as children have much lower metabolic requirements and activity levels than adults.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

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

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 head0.023
GPT teacher head0.269
Teacher spread0.247 · 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