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Record W2074821313 · doi:10.1088/0067-0049/187/2/409

SPECTRAFACTORY.NET: A DATABASE OF MOLECULAR MODEL SPECTRA

2010· article· en· W2074821313 on OpenAlexaff
J. Cami, Roeland Van Malderen, A. J. Markwick

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2010
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsWestern University
FundersScience and Technology Facilities Council
KeywordsIsotopologueSpectral linePhysicsDatabaseLine (geometry)Range (aeronautics)AstrophysicsComputer scienceAstronomyMaterials science

Abstract

fetched live from OpenAlex

We present a homogeneous database of synthetic molecular absorption and emission spectra from the optical to mm wavelengths for a large range of temperatures and column densities relevant for various astrophysical purposes, but in particular for the analysis, identification, and first-order analysis of molecular bands in spectroscopic observations. All spectra are calculated in the LTE limit from several molecular line lists, and are presented at various spectral resolving powers corresponding to several specific instrument simulations. The database is available online at http://www.spectrafactory.net , where users can freely browse, search, display, and download the spectra. We describe how additional model spectra can be requested for (automatic) calculation and inclusion. The database already contains over half a million model spectra for 39 molecules (96 different isotopologues) over the wavelength range 350 nm–3 mm (≈3–30000 cm −1 ).

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.095
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0030.005
Open science0.0060.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0950.074

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 head0.008
GPT teacher head0.253
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations22
Published2010
Admission routes1
Has abstractyes

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