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Record W3200909774 · doi:10.1201/b11502-18

The ViewRay™ System

2011· book-chapter· en· W3200909774 on OpenAlexaboutno aff
Daniel A. Low, RICHARD B. STARK, James F. Dempsey

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicRobotics and Automated Systems
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Clinical cobalt therapy units and MV linear accelerators were introduced nearly simultaneously in the early 1950s. e rst two clinical cobalt therapy units were installed in October 1951 in Saskatoon and London, Ontario (Litt 2000). e rst MV linear accelerator installed solely for clinical use was at Hammersmith Hospital, London in June 1952 (Bernier et al. 2004). In August 1953, the rst patient was treated with this machine. e deeply penetrating ionizing photon beams quickly became the mainstay of radiation therapy, allowing the widespread noninvasive treatment of deep-seated tumors. An additional advantage of these photon beams was based on the fact that photons deliver most of their dose through the interactions of highly energetic scattered electrons. e dose delivery properties of the photon/ scattered electron system leave the patient’s skin surface with a considerably lower dose than inside the body. is allowed aggressive doses to be used internally while sparing the skin from severe radiation damage. Consequently, this feature was called skin sparing and played an important role in the clinical utility of linear-accelerator and cobalt-beam therapies.

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.225
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.2250.212

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 head0.015
GPT teacher head0.163
Teacher spread0.147 · 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
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

Citations1
Published2011
Admission routes1
Has abstractyes

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