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Record W7045500049

The Basic Structure as Object: Institutions and Humanitarian Concern (draft)

2007· article· en· W7045500049 on OpenAlexaboutno aff

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101LiquationDiafiltrationHyporeflexiaProteogenomicsDysgeusiaFusible alloy
DOInot available

Abstract

fetched live from OpenAlex

[FIRST PARAGRAPHS] \nOne third of the human species is infested with worms. The World Health \nOrganization estimates that worms account for 40 percent of the global disease burden \nfrom tropical diseases excluding malaria. Worms cause a lot of misery. \n \n \nIn this article I will focus on one particular type of infestation, which is \nhookworm. Approximately 740 million people suffer from hookworm infection in areas \nof rural poverty: more than one human in ten, a total greater than 23 times the population \nof Canada or twice the population of the United States. The greatest numbers of cases \noccur in China, Southeast Asia and Sub-Saharan Africa—that is, mostly in the places in \nthe world where poverty is most severe.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.085
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0080.007
Open science0.0020.003
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0780.022

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 head0.048
GPT teacher head0.304
Teacher spread0.255 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2007
Admission routes1
Has abstractyes

Explore more

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