MétaCan
Menu
Back to cohort
Record W1571451904 · doi:10.5772/10334

Solar Energy Absorbers

2010· book-chapter· en· W1571451904 on OpenAlexaff
Himanshu Dehra

Bibliographic record

VenueSciyo eBooks · 2010
Typebook-chapter
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversité du Québec à Montréal
Fundersnot available
KeywordsSolar energyMaterials scienceEngineering physicsPhysicsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The most of the solar energy is absorbed by moving planets, their satellites and their surrounding environment viz., planet surface, planet atmosphere, forests, farms, rivers, ponds, lakes & seas, living beings and civil structures (e.g. buildings, green houses, thermal power plants, collectors, panels, roads, bridges, ports, canals). The life and its activities are

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)0.000
metaresearch head score (Gemma)0.000
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: Other
Teacher disagreement score0.056
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0560.039

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 head0.005
GPT teacher head0.156
Teacher spread0.150 · 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

Citations14
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSciyo eBooksSame topicBuilding Energy and Comfort OptimizationFrench-language works237,207