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Record W3093802133 · doi:10.1039/d0cc05196a

Studying the cellular distribution of highly phototoxic platinated metalloporphyrins using isotope labelling

2020· article· en· W3093802133 on OpenAlexaff
Riccardo Rubbiani, Wenyu Wu, Anu Naik, Michele Larocca, Lukas Schneider, Roxane Padrutt, V. V. Suresh Babu, Christiane König, Doris Hinger, Caroline Maake, Stefano Ferrari, Gilles Gasser, Bernhard Spingler

Bibliographic record

VenueChemical Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsInstitute of Cancer Research
FundersH2020 European Research CouncilUniversität ZürichNovartis Stiftung für Medizinisch-Biologische ForschungSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAgence Nationale de la Recherche
KeywordsPhototoxicityLabellingChemistryIsotopeEnvironmental chemistryPhotochemistryRadiochemistryBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Novel tetraplatinated metalloporphyrin-based photosensitizers (PSs) are reported, which show excellent phototoxic indexes (PIs) up to 5800 against HeLa cells, which is, to the best of our knowledge, the highest value reported for any porphyrin so far. Furthermore, 67Zn isotope labelling allowed the determination of the ratio of zinc to platinum inside the cells using ICP-MS.

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 score0.039
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.111
GPT teacher head0.341
Teacher spread0.230 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

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