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Record W4230872342 · doi:10.5858/2000-124-1416b-ir

In Reply

2000· article· en· W4230872342 on OpenAlexaff
Sam Thomson, Reinhard Lohmann, Linda Crawford, Ruby Dubash, Harold Richardson

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsIntegrity Testing Laboratory (Canada)London Health Sciences Centre
Fundersnot available
KeywordsBlood filmThin filmGametocyteParasitemiaValue (mathematics)MalariaComputer scienceMaterials scienceNanotechnologyMedicinePlasmodium falciparumPathology

Abstract

fetched live from OpenAlex

In Reply Dr Sheehan questions the value of preparing and interpreting thick films for malarial parasites largely on the basis of lack of technical expertise. We are fully aware ofthese difficulties. However, it was not the purpose of our review to examine the value of the thick film versus the thin film.We do not believe that our results infer that “the false-negative rate for thick films is 17 times higher than that for thin films.” Nor did we discuss the value, if any, of thick films in malaria speciation. As stated in our article, scanty parasites and Plasmodiumfalciparum gametocytes may be easier to detect in thick films and therefore might be of value in low infections and in P falciparum speciation.It would be of interest to test scientifically the accuracy of the thick film in low-level parasitemia compared to the thin film. Until such time, we believe that prompt examination of both thick and thin films is advisable.

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)0.003
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: none
Teacher disagreement score0.978
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0030.002
Research integrity0.0240.029
Insufficient payload (model declined to judge)0.0220.015

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 head0.009
GPT teacher head0.288
Teacher spread0.278 · 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
Published2000
Admission routes1
Has abstractyes

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