MétaCan
Menu
Back to cohort

The EDIBLES survey

2019· article· en· W6884504937 on OpenAlexfundno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
FundersCentre National de la Recherche ScientifiqueNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekCentre National d’Etudes Spatiales
KeywordsIonizationStarsInterstellar mediumSpectral lineCosmic rayCOSMIC cancer database

Abstract

fetched live from OpenAlex

We report cosmic ray ionization rates toward ten reddened stars studied within the framework of the EDIBLES (ESO Diffuse Interstellar Bands Large Exploration Survey) program, using the VLT-UVES. For each sightline, between two and ten individual rotational lines of OH+ have been detected in its (0,0) and (1,0) A3Π − X3Σ− electronic band system. This allows constraining of OH+ column densities toward different objects. Results are also presented for 28 additional sightlines for which only one or rather weak signals are found. An analysis of these data makes it possible to derive the primary cosmic ray ionization rate ζp in the targeted diffuse interstellar clouds. For the ten selected targets, we obtain a range of values for ζp equal to (3.9–16.4) × 10−16 s−1. These values are higher than the numbers derived in previous detections of interstellar OH+ in the far-infrared/submillimeter-wave regions and in other near-ultraviolet studies. This difference is a result of using new OH+ oscillator strength values and a more complete picture of all relevant OH+ formation and destruction routes (including the effect of proton recombinations on PAHs), and the relatively high N(OH+) seen toward those ten targets.

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)0.001
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.004

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 head0.011
GPT teacher head0.233
Teacher spread0.221 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSpringer Link (Chiba Institute of Technology)Same topicAstrophysics and Star Formation StudiesFrench-language works237,207