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Record W6950615409 · doi:10.5683/sp2/6hnrjm

Bazalgette Lancaster FM-159 -- Nanton -- Laser Scanning -- Metadata -- 2021

2021· dataset· en· W6950615409 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2021
Typedataset
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMetadataSet (abstract data type)Laser scanningInteroperabilityData setLaser

Abstract

fetched live from OpenAlex

This data set contains the metadata of the sixty-five (65) registered scans of the Bazalgette Lancaster FM-159 at the Bomber Command Museum of Canada. Two scanners were employed to collect the data, a Z+F 5010X and a BKL 360. The Z+F 5010X collected twenty-eight (28) of the scans around the exterior of the Bazalgette Lancaster FM-159. The BKL 360 collected thirty-seven (37) scans of the interior of the Bazalgette Lancaster FM-159. The data was collected by the Capture 2 Preserve team on March 18, 2021. Scans from the Z+F 5010X were registered and processed in Z+F Laser Control V. 9.2.1. Scans from the BKL 360 were registered and processed in Cyclone Register 360 (BKL Edition) V 2021.0.0

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.263
Teacher spread0.252 · 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.

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

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

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