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Record W3103435799

Near-infrared High-resolution Imaging Polarimetry of FU Ori-type Objects: Toward a Unified Scheme for Low-mass Protostellar Evolution

2018· article· en· W3103435799 on OpenAlexaff
M. Takami, Guangwei Fu, Hauyu Baobab Liu, Jennifer L. Karr, Jun Hashimoto, Á. Kóspál, Eduard I. Vorobyov, Peter Scicluna, Ruobing Dong, Motohide Tamura, Tae‐Soo Pyo, Misato Fukagawa, Toru Tsuribe, Michael M. Dunham, Thomas Henning, Jerome de Leon

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsAstrophysicsYoung stellar objectAstronomyAccretion (finance)StarsPolarimetryInfraredStar formationScatteringOptics
DOInot available

Abstract

fetched live from OpenAlex

We present near-IR imaging polarimetry of five classical FU Ori-type objects (FU Ori, V1057 Cyg, V1515 Cyg, V1735 Cyg, Z CMa) with an ̃0.″1 resolution observed using HiCIAO+AO188 at the Subaru Telescope. We observed scattered light associated with circumstellar dust around four of them (i.e., all but V1515 Cyg). Their polarized intensity distribution shows a variety of morphologies with arms, tails or streams, spikes, and fragmented distributions, many of which were reported in our previous paper. The morphologies of these reflection nebulae significantly differ from many other normal young stellar objects (Class I-II objects). These structures are attributed to gravitationally unstable disks, trails of clump ejections, dust blown by a wind or a jet, and a stellar companion. We can consistently explain our results with the scenario that their accretion outbursts (FUor outbursts) are triggered by gravitationally fragmenting disks, and with the hypothesis that many low-mass young stellar objects experience such outbursts. Based on data collected at the Subaru Telescope, which is operated by the National Astronomical Observatory of Japan.

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 score0.495
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.003
Open science0.0020.001
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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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

Citations39
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences)Same topicAstrophysics and Star Formation StudiesFrench-language works237,207