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Record W6950589725 · doi:10.5281/zenodo.8259450

Fig. 6 in Genome-wide identification and characterization of genes involved in melatonin biosynthesis in Morus notabilis (wild mulberry)

2021· other· en· W6950589725 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicAquatic and Environmental Studies
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsRecombinant DNAlac operonEscherichia coliChaperone (clinical)EnzymeGeneMolecular massMelatonin

Abstract

fetched live from OpenAlex

Fig. 6. Purification and enzymatic analyses of recombinant His-tagged MnCOMT1. A: Purification of recombinant His-tagged MnCOMT1 (lane1: Protein Marker; lane2: pCold TF (+IPTG); lane3: recombinant protein (-IPTG); lane4: recombinant protein (+IPTG); lane5: purified protein). B: Mass spectrum of compounds detected using UPLC-MS/MS. a: melatonin standard; b: Chromatogram of N-acetylserotonin catalyzed by MnCOMT1. C: Determination of Km and Vmax of MnCOMT1 for Nacetylserotonin. MnCOMT1 (1.0 μg) was co-incubated with different concentrations of N-acetylserotonin for 20 min at 37 ◦C. D: Mass spectrum of compounds detected using UPLC-MS/MS. a: 5-methoxytryptamine standard; b: Chromatogram of serotonin catalyzed by MnCOMT1. E: Determination of Km and Vmax of MnCOMT1 for serotonin. MnCOMT1 (1.0 μg) was co-incubated with different concentrations of serotonin for 20 min at 37 ◦C. " IPTG" stand without addition of 1 mM IPTG to the E. coli BL21 (DE3) culture, "+IPTG" stand addition of 1 mM IPTG to the E. coli BL21 (DE3) culture. "TF" is Trigger Factor, a prokaryotic ribosomerelated molecular chaperone that facilitates the translation and folding of peptides. "*" indicates Trigger factor.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.196
Teacher spread0.173 · 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 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
Published2021
Admission routes1
Has abstractyes

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