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Record W3042211954 · doi:10.1051/epjconf/202023708016

Optical Properties of Canadian Biomass Burning Particles Over Europe Observed with Calipso and Ground-Based Lidar Systems

2020· article· en· W3042211954 on OpenAlexaboutno aff
Christina–Anna Papanikolaou, Elina Giannakaki, Alexandros Papayannis, M. Tombrou, Maria Mylonaki, Ουρανία Σουπιωνά

Bibliographic record

VenueEPJ Web of Conferences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
Fundersnot available
KeywordsLidarBackscatter (email)Angstrom exponentBiomass (ecology)Biomass burningEnvironmental scienceAtmospheric sciencesAerosolDepolarization ratioAngstromRemote sensingMeteorologyPhysicsGeologyChemistryOceanography

Abstract

fetched live from OpenAlex

A long-lasting biomass burning event affected Europe from 27 August to 3 September 2018. The biomass burning aerosol layers were observed with ground- and space-based lidars in heights ranged between 2-7 km (a.s.l.). The mean backscatter coefficient for the ground-based stations ranged between 0.29 and 1.51 Mm-1sr-1, while the CALIPSO retrieved values ranged between 0.43 and 1.83 Mm-1sr-1. Moreover, the mean Ångström exponent (AEb) values, relevant to backscatter, ranged from 0.83 to 1.04 for the aforementioned lidar stations. At the same time, the mean AEb values obtained from CALIPSO ranged between 0.17 and 1.89. The mean particle depolarization ratio ranged between 0.037 and 0.080.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.046
GPT teacher head0.196
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 designObservational
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

Citations2
Published2020
Admission routes1
Has abstractyes

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