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Record W3169851720 · doi:10.2172/1784684

RCT Continuing Training (Q2 2021) [Slides]

2021· report· en· W3169851720 on OpenAlexaboutno aff
Matthew Cheatham

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSection (typography)Event (particle physics)Quarter (Canadian coin)Computer scienceALARMPoint (geometry)EngineeringGeographyOperating systemMathematicsPhysics

Abstract

fetched live from OpenAlex

This quarter’s training assignment is split into two sections. Section one will review the fundamental elements of removing items from controlled areas. This section discusses each decision point and the required actions to determine if an item is suitable for release. Section two briefly reviews Area Radiation Monitors, commonly referred to as ‘ARMs’, and discusses the required actions to take in the event of an ARM alarm.” Report includes slides and transcript.

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)0.009
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.674
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.6740.444

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 head0.101
GPT teacher head0.396
Teacher spread0.296 · 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.

Study designNot applicable
Domainnot available
GenreOther

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 routes1
Has abstractyes

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