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Record W2029197367 · doi:10.1371/journal.pone.0052293

Full-Length Minor Ampullate Spidroin Gene Sequence

2012· article· en· W2029197367 on OpenAlexaff
Gefei Chen, Xiang‐Qin Liu, Yunlong Zhang, Senzhu Lin, Zijiang Yang, Jan Johansson, Anna Rising, Qing Meng

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsDalhousie University
FundersVetenskapsrådetKarolinska Institutet
KeywordsBiologySpider silkGeneSILKSpiderIntronGeneticsSequence analysisSequence alignmentPeptide sequenceZoology

Abstract

fetched live from OpenAlex

Spider silk includes seven protein based fibers and glue-like substances produced by glands in the spider's abdomen. Minor ampullate silk is used to make the auxiliary spiral of the orb-web and also for wrapping prey, has a high tensile strength and does not supercontract in water. So far, only partial cDNA sequences have been obtained for minor ampullate spidroins (MiSps). Here we describe the first MiSp full-length gene sequence from the spider species Araneus ventricosus, using a multidimensional PCR approach. Comparative analysis of the sequence reveals regulatory elements, as well as unique spidroin gene and protein architecture including the presence of an unusually large intron. The spliced full-length transcript of MiSp gene is 5440 bp in size and encodes 1766 amino acid residues organized into conserved nonrepetitive N- and C-terminal domains and a central predominantly repetitive region composed of four units that are iterated in a non regular manner. The repeats are more conserved within A. ventricosus MiSp than compared to repeats from homologous proteins, and are interrupted by two nonrepetitive spacer regions, which have 100% identity even at the nucleotide level.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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)0.0040.003

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 head0.076
GPT teacher head0.262
Teacher spread0.186 · 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 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

Citations100
Published2012
Admission routes1
Has abstractyes

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