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Record W2319923309 · doi:10.1295/koron.59.792

Direct Measurement of Specific Interactions between Nucleic Acid Base Pairing.

2002· article· en· W2319923309 on OpenAlexaff
Takahiro Harada, Takashi Miyahara, Naotoshi Nakashima, Kazue Kurihara

Bibliographic record

VenueKOBUNSHI RONBUNSHU · 2002
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsNucleic acidBase (topology)ChemistryPairingCombinatorial chemistryPhysicsBiochemistryMathematics

Abstract

fetched live from OpenAlex

チミン (T) およびアデニン (A) を末端に有する両親媒性分子を用いて, 雲母基板上に核酸塩基を表面に有する単分子膜を調製した. 水溶液中 (pH4~10) において, 調製した核酸塩基表面間に作用する力を, 表面力装置 (SFA) を用いて, 表面間距離の関数として測定した. (i) T-TおよびA-A表面間では, 核酸塩基の酸解離を反映して, それぞれ, pH7以上またはpH4以下において電気二重層斥力が観察された. また, A-Aの場合, pH8以上でも斥力となり, 水酸化物イオンの吸着による電気二重層斥力と考えている. それ以外のpH領域では, 90nmに及ぶ長距離引力が作用した. これは主に核酸塩基の疎水性による引力と考えられる. (ii) 相補的なT-A表面間においては, pH4~10の領域においてつねに長距離から引力が観察され, 特に純水中においては, 60nmの長距離から引力が観察された. 生理的pH条件下において, 相補的な核酸塩基間にpKaと疎水性の最適化が起こっていると考えられる. (iii) 接着力は, T-A表面間でもっとも強く, 特に中性のpH領域で接着力は極大となった. この事実は, 生理的pH条件下で, 相補的な核酸塩基対がもっとも効果的にその分子認識能を発現していることを示している.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.035
GPT teacher head0.206
Teacher spread0.171 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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