Environmental footprints of food consumption: Protocol for a systematic literature review
Bibliographic record
Abstract
Environmental footprints are indicators that can be used to estimate the impacts of diet on the environment. Since contemporary dietary practices are related to negative environmental impacts, this paper aims to describe a systematic review protocol to investigate the environmental footprints of food consumption by adults and elderly individuals worldwide. This protocol was developed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Search strategies and records of evidence searched in previously defined electronic databases will be defined. Original, population-based articles investigating the environmental footprints of food consumption by adults and the elderly will be included. Two independent reviewers will conduct the study selection and data extraction steps. Critical appraisal of the included studies will be based on the Newcastle-Ottawa Scale. For data synthesis, a narrative synthesis and, if possible, also a meta-analysis will be performed. The systematic review produced from this protocol will provide evidence for data synthesis of the environmental impact through environmental footprints of food consumption of the adult and elderly population from different territories and the footprint assessment tools used around the world. Therefore, it is a gap that needs to be filled because knowing these impacts will be important to inform the development of public policies that encourage healthy and sustainable food in the face of climate and epidemiological changes. PROSPERO registration number: CRD42021281488.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.108 | 0.147 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.097 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".