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Molecular Forensic Profiling of <i>Cryptosporidium</i> Species and Genotypes in Raw Water

2005· article· en· W1977199565 on OpenAlexaff
Norma J. Ruecker, Niravanh Bounsombath, P. M. Wallis, Corinne Ong, Judith L. Isaac‐Renton, Norman F. Neumann

Bibliographic record

VenueApplied and Environmental Microbiology · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsProvincial Laboratory of Public HealthBC Centre for Disease ControlUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsCryptosporidiumBiologyGenotypeDNA profilingRestriction fragment length polymorphismFecesComputational biologyDNAMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

The emerging concept of host specificity of Cryptosporidium spp. was exploited to characterize sources of fecal contamination in a watershed. A method of molecular forensic profiling of Cryptosporidium oocysts on microscope slides prepared from raw water samples processed by U.S. Environmental Protection Agency Method 1623 was developed. The method was based on a repetitive nested PCR-restriction fragment length polymorphism-DNA sequencing approach that permitted the resolution of multiple species/genotypes of Cryptosporidium in a single water sample.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.167
Teacher spread0.164 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations33
Published2005
Admission routes1
Has abstractyes

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