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Record W2127351406 · doi:10.1088/2041-8205/752/2/l26

ANALYSIS OF THE EARLY-TIME OPTICAL SPECTRA OF SN 2011fe IN M101

2012· article· en· W2127351406 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersIstituto Nazionale di AstrofisicaU.S. Department of EnergyScience and Technology Facilities CouncilOffice of ScienceNational Science Foundation
KeywordsSupernovaAbsorption (acoustics)Spectral lineAbsorption spectroscopyOptical spectraProgenitor

Abstract

fetched live from OpenAlex

The nearby Type Ia supernova (SNIa) SN2011fe in M101 (cz = 241kms -1) provides a unique opportunity to study the early evolution of a "normal" SNIa, its compositional structure, and its elusive progenitor system. We present 18 high signal-to-noise spectra of SN2011fe during its first month beginning 1.2days post-explosion and with an average cadence of 1.8days. This gives a clear picture of how various line-forming species are distributed within the outer layers of the ejecta, including that of unburned material (C+O). We follow the evolution of C II absorption features until they diminish near maximum light, showing overlapping regions of burned and unburned material between ejection velocities of 10,000 and 16,000kms-1. This supports the notion that incomplete burning, in addition to progenitor scenarios, is a relevant source of spectroscopic diversity among SNeIa. The observed evolution of the highly Doppler-shifted O I λ7774 absorption features detected within 5days post-explosion indicates the presence of O I with expansion velocities from 11,500 to 21,000kms-1. The fact that some O I is present above C II suggests that SN2011fe may have had an appreciable amount of unburned oxygen within the outer layers of the ejecta. © 2012. The American Astronomical Society. All rights reserved..

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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 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

Citations88
Published2012
Admission routes1
Has abstractyes

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