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Record W43495470

ESPOIR : A Program for Solving Structures by Monte Carlo from Powder Diffraction Data

2000· article· en· W43495470 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsPowder diffractionSimulated annealingCrystallographyMoleculeDiffractionMonte Carlo methodSource codeComputer scienceAlgorithmChemistryMaterials sciencePhysicsComputational scienceMathematicsProgramming languageQuantum mechanicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

Abstract A direct-space program (ESPOIR) for the crystal structure solution of small molecules, from powder diffraction data, is developed under the GNU Public License. The program allows solving the structures of the two samples distributed during the Structure Determination by Powder Diffractometry Round Robin (SDPDRR) : the tetracycline hydrochloride and a cobalt-amine. Three calculation modes are possible, either locating up to 4 different molecule fragments, or starting from a set of randomly distributed atoms, or mixed approaches. Introduction Powder diffraction is a theatre for the development of unconventional methods for stucture solution (different from classical Patterson and direct methods). However, less than 100 structures were solved from unconventional methods, and are reported in the SDPD (Structure Determination by Powder Diffractometry) Database [1]. Trying to locate a molecule in a crystalline cell while matching to either extracted "|Fobs| " or the full powder pattern or the Patterson function

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.279
Teacher spread0.267 · 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