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Record W4319157507 · doi:10.2138/gselements.18.5.291

On the Path to Decarbonisation

2022· article· en· W4319157507 on OpenAlexaff
Andrew Stewart

Bibliographic record

VenueElements · 2022
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsLafargeHolcim (Canada)
Fundersnot available
KeywordsCementFocus (optics)Architectural engineeringKey (lock)SkyEmbodied cognitionPath (computing)Civil engineeringEnvironmental scienceEngineeringComputer scienceMaterials scienceGeographyMeteorologyComposite materialArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Cement and concrete are the fundamental building materials of the modern built environment. Our cities grow to the sky and into the ground, all based on concrete and its key ingredient, cement. Concretes are changing, but the role of concrete in our world is not. At present, most concrete has significant embodied CO2, but there is growing focus on changing that.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0080.013
Open science0.0010.008
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0260.007

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2022
Admission routes1
Has abstractyes

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