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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Nature Methods
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

403 results · 1 filter active ·
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20042025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
403 works in the cohort · of 4,299,418page 2 of 9

Labels cover 1 of 403 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 403 of 403 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

fundno affno abstractunlabeled
Comparison of Cas9 activators in multiple species
Alejandro Chavez, Marcelle Tuttle, Benjamin W. Pruitt, Ben Ewen‐Campen, Raj Chari, Dmitry Ter‐Ovanesyan +8 more
2016· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
553
citations
fundno affno abstractunlabeled
TCPA: a resource for cancer functional proteomics data
Jun Li, Yiling Lu, Rehan Akbani, Zhenlin Ju, Paul Roebuck, Wenbin Liu +8 more
2013· letter· en· Nature Methods· Chemistry
machine prediction:candidate · noneconsensus · none
538
citations
affno abstractunlabeled
High-throughput behavioral analysis in C. elegans
Nicholas A Swierczek, Andrew C. Giles, Catharine H. Rankin, Rex Kerr
2011· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
503
citations
affno abstractunlabeled
The curse(s) of dimensionality
Naomi Altman, Martin Krzywinski
2018· article· en· Nature Methods· Mathematics
machine prediction:candidate · noneconsensus · none
477
citations
affno abstractunlabeled
Using buoyant mass to measure the growth of single cells
Michel Godin, Francisco Feijó Delgado, Sungmin Son, William H. Grover, Andrea K. Bryan, Amit Tzur +5 more
2010· article· en· Nature Methods· Engineering
machine prediction:candidate · noneconsensus · none
405
citations
afffundno abstractunlabeled
Metrics reloaded: recommendations for image analysis validation
Lena Maier‐Hein, Annika Reinke, Patrick Godau, Minu D. Tizabi, Florian Buettner, Evangelia Christodoulou +66 more
2024· review· en· Nature Methods· Medicine
machine prediction:candidate · metaresearchconsensus · none
398
citations
affno abstractunlabeled
A monovalent streptavidin with a single femtomolar biotin binding site
Mark Howarth, Daniel J.‐F. Chinnapen, Kimberly Gerrow, Pieter C. Dorrestein, Melanie R Grandy, Neil L. Kelleher +2 more
2006· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
385
citations
affno abstractunlabeled
Classification and regression trees
Martin Krzywinski, Naomi Altman
2017· article· en· Nature Methods· Mathematics
machine prediction:candidate · noneconsensus · none
382
citations
afffundunlabeled
Critical assessment of protein intrinsic disorder prediction
Marco Necci, Damiano Piovesan, Md Tamjidul Hoque, Ian Walsh, Sumaiya Iqbal, Michele Vendruscolo +92 more
2021· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaresearchconsensus · none
363
citations
afffundno abstractunlabeled
Pathway and network analysis of cancer genomes
Rune Linding, Pau Creixell, Jüri Reimand, Gary D. Bader, Lincoln Stein, B. F. Francis Ouellette +13 more
2015· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
358
citations
fundno affno abstractunlabeled
Cas9 gRNA engineering for genome editing, activation and repression
Samira Kiani, Alejandro Chavez, Marcelle Tuttle, Richard Hall, Raj Chari, Dmitry Ter‐Ovanesyan +10 more
2015· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
356
citations
afffundno abstractunlabeled
Exploring single-cell data with deep multitasking neural networks
Matthew Amodio, David van Dijk, Krishnan Srinivasan, William S. Chen, Hussein Mohsen, Kevin R. Moon +10 more
2019· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
350
citations
affno abstractunlabeled
Machine learning: supervised methods
Danilo Bzdok, Martin Krzywinski, Naomi Altman
2018· article· en· Nature Methods· Mathematics
machine prediction:candidate · noneconsensus · none
337
citations
affno abstractunlabeled
The power of imaging to understand extracellular vesicle biology in vivo
Frederik J. Verweij, Leonora Balaj, Chantal M. Boulanger, David R. F. Carter, Ewoud B. Compeer, Gisela D’Angelo +23 more
2021· review· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
334
citations
affno abstractunlabeled
Transposon-mediated genome manipulation in vertebrates
Zoltán Ivics, Meng Amy Li, Lajos Mátés, Jef D. Boeke, András Nagy, Allan Bradley +1 more
2009· review· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
318
citations
afffundno abstractunlabeled
Alternative expression analysis by RNA sequencing
Malachi Griffith, Obi L. Griffith, Jill Mwenifumbo, Rodrigo Goya, A. Sorana Morrissy, Ryan D. Morin +20 more
2010· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
314
citations
afffundno abstractunlabeled
Megapixel digital PCR
Kevin A. Heyries, Carolina Tropini, Michael VanInsberghe, C. Doolin, Oleh I. Petriv, Anupam Singhal +3 more
2011· article· en· Nature Methods· Engineering
machine prediction:candidate · noneconsensus · none
309
citations
affno abstractunlabeled
The need for transparency and good practices in the qPCR literature
Stephen A. Bustin, Vladimı́r Beneš, Jeremy A. Garson, Jan Hellemans, Jim F. Huggett, Mikael Kubista +78 more
2013· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · metaresearchconsensus · metaresearch
291
citations
affno abstractunlabeled
Error bars
Martin Krzywinski, Naomi Altman
2013· article· en· Nature Methods· Decision Sciences
machine prediction:candidate · metaresearchconsensus · none
289
citations
affno abstractunlabeled
Prion strain discrimination using luminescent conjugated polymers
Christina J. Sigurdson, K. Peter R. Nilsson, Simone Hornemann, Giuseppe Manco, Magdalini Polymenidou, Petra Schwarz +4 more
2007· article· en· Nature Methods· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
277
citations

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