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Record W2157892273 · doi:10.1093/ndt/gfq213

Slouching towards Bethlehem: the beast of biocompatibility

2010· letter· en· W2157892273 on OpenAlexaff
Joanne M. Bargman

Bibliographic record

VenueNephrology Dialysis Transplantation · 2010
Typeletter
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineBiocompatibilityMedical physicsEngineering

Abstract

fetched live from OpenAlex

Gambrosol resulted in better preservation of RRF. Furthermore, they proposed that the renoprotective effect may be ultimately responsible for the claim of reduced mortality with the use of these solutions in other reports [2]. Thisstudy adds tothegrowingliteraturethat comfortsand buttressesthe believers in‘biocompatible’solutions,but only further confuses the non-believers and biocompatibilityagnostics. In the last decade, studies have [3–6] or have not [7–11] demonstrated better preservation of RRF, have [4]ormostlyhavenotshowntobeassociatedwithlowerrates of PD peritonitis, and have [9,10] or have not [5,6,11] been associated with a reduction in blood levels of CRP. There are many factors that may contribute to the variability in the results, including the composition of the ‘biocom

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)0.009
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.012
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0120.015
Insufficient payload (model declined to judge)0.0060.003

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 head0.261
Teacher spread0.246 · 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
GenreCommentary

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

Citations16
Published2010
Admission routes1
Has abstractyes

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