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Record W2006813694 · doi:10.1016/j.jash.2014.02.001

Reporting bias: Achilles' heel of home blood pressure monitoring

2014· editorial· en· W2006813694 on OpenAlexaff
Martin G. Myers, George S. Stergiou

Bibliographic record

VenueJournal of the American Society of Hypertension · 2014
Typeeditorial
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBlood pressureEveningInternal medicineMorningConfidence intervalCardiologyLogistic regressionOdds ratioDiastoleSphygmomanometerWhite coat hypertensionAmbulatory blood pressure

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.149
metaresearch head score (Gemma)0.463
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.851
Threshold uncertainty score0.789

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1490.463
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0160.009
Bibliometrics0.0090.007
Science and technology studies0.0060.012
Scholarly communication0.0170.012
Open science0.0140.004
Research integrity0.0670.042
Insufficient payload (model declined to judge)0.0100.006

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 head0.050
GPT teacher head0.295
Teacher spread0.245 · 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
DomainReporting
GenreEditorial

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

Citations42
Published2014
Admission routes1
Has abstractno

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