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Record W3098986351 · doi:10.3390/rs12233954

Mapping the Melatonin Suppression, Star Light and Induced Photosynthesis Indices with the LANcube

2020· article· en· W3098986351 on OpenAlexafffund
Martin Aubé, Charles Marseille, Amar Farkouh, Adam Dufour, Alexandre Simoneau, J. Zamorano, Johanne Roby, Carlos Tapia

Bibliographic record

VenueRemote Sensing · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicImpact of Light on Environment and Health
Canadian institutionsUniversité de SherbrookeCégep de SherbrookeBishop's University
FundersFonds de Recherche du Québec - SantéFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsStarlightPanchromatic filmMelatoninPhotosynthesisEnvironmental scienceArtificial lightRemote sensingPhysicsAstrophysicsAstronomyBiologyGeologyOpticsImage resolutionBotanyStars

Abstract

fetched live from OpenAlex

Increased exposure to artificial light at night can affect human health including disruption of melatonin production and circadian rhythms which can extend to increased risks of hormonal cancers and other serious diseases. In addition, multiple negative impacts on fauna and flora are well documented, and it is a matter of fact that artificial light at night is a nuisance for ground-based astronomy. These impacts are frequently linked to the colour of the light or more specifically to its spectral content. Artificial light at night is often mapped by using spaceborne sensors, but most of them are panchromatic and thus insensitive to the colour. In this paper, we suggest a method that allows high-resolution mapping of the artificial light at night by using ground-based measurements with the LANcube system. The newly developed device separates the light detected in four bands (Red, Green, Blue and Clear) and provides this information for six faces of a cube. We found relationships between the LANcube’s colour ratios and (1) the Melatonin Suppression Index, (2) the StarLight Index and (3) the Induced Photosynthesis Index. We show how such relationships combined with data acquisition from a LANcube positioned on the top of a car can be used to produce spectral indices maps of a whole city in a few hours.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.408

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.217
Teacher spread0.191 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations18
Published2020
Admission routes2
Has abstractyes

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