MétaCan
Menu
Back to cohort
Record W2793880089 · doi:10.1074/mcp.tir117.000302

Simple, scalable, and ultrasensitive tip-based identification of protease substrates

2018· article· en· W2793880089 on OpenAlexaff
Gerta Shema, Minh Tú Nguyễn, Fiorella A. Solari, Stefan Loroch, A. Saskia Venne, Laxmikanth Kollipara, Albert Sickmann, Steven H. L. Verhelst, René P. Zahedi

Bibliographic record

VenueMolecular & Cellular Proteomics · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsMcGill UniversityJewish General Hospital
FundersMinisterium für Kultur und Wissenschaft des Landes Nordrhein-WestfalenKU LeuvenBundesministerium für Bildung und Forschung
KeywordsChemistryChromatographyIon chromatographyAmine gas treatingOrganic chemistry

Abstract

fetched live from OpenAlex

Proteases are in the center of many diseases, and consequently, proteases and their substrates are important drug targets as represented by an estimated 5–10% of all drugs under development. Mass spectrometry has been an indispensable tool for the discovery of novel protease substrates, particularly through the proteome-scale enrichment of so-called N-terminal peptides representing endogenous protein N termini. Methods such as combined fractional diagonal chromatography (COFRADIC) 1The abbreviations used are: COFRADIC, combined fractional diagonal chromatography; ChaFRAtip, charge-based fractional diagonal chromatography in tip format; SCX, strong-cation-exchange chromatography; ChaFRADIC, charge-based fractional diagonal chromatography; TAILS, terminal amine isotopic labeling of substrates; TEAB, triethylammonium bicarbonate; BCA, bicinchoninic acid assay; TNC, theoretical net charge. 1The abbreviations used are: COFRADIC, combined fractional diagonal chromatography; ChaFRAtip, charge-based fractional diagonal chromatography in tip format; SCX, strong-cation-exchange chromatography; ChaFRADIC, charge-based fractional diagonal chromatography; TAILS, terminal amine isotopic labeling of substrates; TEAB, triethylammonium bicarbonate; BCA, bicinchoninic acid assay; TNC, theoretical net charge. and, later, terminal amine isotopic labeling of substrates (TAILS) have revealed numerous insights into protease substrates and consensus motifs. We present an alternative and simple protocol for N-terminal peptide enrichment, based on charge-based fractional diagonal chromatography (ChaFRADIC) and requiring only well-established protein chemistry and a pipette tip. Using iTRAQ-8-plex, we quantified on average 2,073 ± 52 unique N-terminal peptides from only 4.3 μg per sample/channel, allowing the identification of proteolytic targets and consensus motifs. This high sensitivity may even allow working with clinical samples such as needle biopsies in the future. We applied our method to study the dynamics of staurosporine-induced apoptosis. Our data demonstrate an orchestrated regulation of specific pathways after 1.5 h, 3 h, and 6 h of treatment, with many important players of homeostasis targeted already after 1.5 h. We additionally observed an early multilevel modulation of the splicing machinery both by proteolysis and phosphorylation. This may reflect the known role of alternative splicing variants for a variety of apoptotic genes, which seems to be a driving force of staurosporine-induced apoptosis. Proteases are in the center of many diseases, and consequently, proteases and their substrates are important drug targets as represented by an estimated 5–10% of all drugs under development. Mass spectrometry has been an indispensable tool for the discovery of novel protease substrates, particularly through the proteome-scale enrichment of so-called N-terminal peptides representing endogenous protein N termini. Methods such as combined fractional diagonal chromatography (COFRADIC) 1The abbreviations used are: COFRADIC, combined fractional diagonal chromatography; ChaFRAtip, charge-based fractional diagonal chromatography in tip format; SCX, strong-cation-exchange chromatography; ChaFRADIC, charge-based fractional diagonal chromatography; TAILS, terminal amine isotopic labeling of substrates; TEAB, triethylammonium bicarbonate; BCA, bicinchoninic acid assay; TNC, theoretical net charge. 1The abbreviations used are: COFRADIC, combined fractional diagonal chromatography; ChaFRAtip, charge-based fractional diagonal chromatography in tip format; SCX, strong-cation-exchange chromatography; ChaFRADIC, charge-based fractional diagonal chromatography; TAILS, terminal amine isotopic labeling of substrates; TEAB, triethylammonium bicarbonate; BCA, bicinchoninic acid assay; TNC, theoretical net charge. and, later, terminal amine isotopic labeling of substrates (TAILS) have revealed numerous insights into protease substrates and consensus motifs. We present an alternative and simple protocol for N-terminal peptide enrichment, based on charge-based fractional diagonal chromatography (ChaFRADIC) and requiring only well-established protein chemistry and a pipette tip. Using iTRAQ-8-plex, we quantified on average 2,073 ± 52 unique N-terminal peptides from only 4.3 μg per sample/channel, allowing the identification of proteolytic targets and consensus motifs. This high sensitivity may even allow working with clinical samples such as needle biopsies in the future. We applied our method to study the dynamics of staurosporine-induced apoptosis. Our data demonstrate an orchestrated regulation of specific pathways after 1.5 h, 3 h, and 6 h of treatment, with many important players of homeostasis targeted already after 1.5 h. We additionally observed an early multilevel modulation of the splicing machinery both by proteolysis and phosphorylation. This may reflect the known role of alternative splicing variants for a variety of apoptotic genes, which seems to be a driving force of staurosporine-induced apoptosis. Proteolysis plays a crucial role in maintaining cellular homeostasis by modulating protein function and activity and its dysregulation underlies many diseases such as cancer and Alzheimer (1.Vögtle F.N. Wortelkamp S. Zahedi R.P. Becker D. Leidhold C. Gevaert K. Kellermann J. Voos W. Sickmann A. Pfanner N. Meisinger C. Global analysis of the mitochondrial N-proteome identifies a processing peptidase critical for protein stability.Cell. 2009; 139: 428-439Abstract Full Text Full Text PDF PubMed Scopus (353) Google Scholar, 2.Quirós P.M. Langer T. López-Otín C. New roles for mitochondrial proteases in health, ageing and disease.Nature Rev. Cell Biol. 2015; 16: 345-359Crossref PubMed Scopus (347) Google Scholar, 3.López-Otín C. Hunter T. The regulatory crosstalk between kinases and proteases in cancer.Nature Rev. Cancer. 2010; 10: 278-292Crossref PubMed Scopus (195) Google Scholar). Through proteolytic cleavage, novel protein N termini are generated. The identification of these so-called neo N termini is an important step toward understanding which proteins are substrates of a specific protease and revealing regulatory proteolytic networks in health and disease. Moreover, it also allows identifying protease cleavage motifs, which is important for developing protease inhibitors or chemical proteomics tools. As protein N termini and, more importantly, neo N termini are significantly underrepresented in the proteome, specific methods have been developed for the enrichment of N-terminal peptides followed by mass spectrometry (N-terminomics) to enable the system-wide identification of protease substrates and cleavage patterns (4.Agard N.J. Wells J.A. Methods for the proteomic identification of protease substrates.Curr. Opin. Chem. Biol. 2009; 13: 503-509Crossref PubMed Scopus (63) Google Scholar). Several methods, namely combined fractional diagonal chromatography (COFRADIC) (5.Gevaert K. Goethals M. Martens L. Van Damme J. Staes A. Thomas G.R. Vandekerckhove J. Exploring proteomes and analyzing protein processing by mass spectrometric identification of sorted N-terminal peptides.Nature Biotech. 2003; 21: 566-569Crossref PubMed Scopus (504) Google Scholar), subtiligase N-terminal labeling and enrichment (6.Mahrus S. Trinidad J.C. Barkan D.T. Sali A. Burlingame A.L. Wells J.A. Global sequencing of proteolytic cleavage sites in apoptosis by specific labeling of protein N termini.Cell. 2008; 134: 866-876Abstract Full Text Full Text PDF PubMed Scopus (369) Google Scholar) and, later, terminal amine isotopic labeling of substrates (TAILS) (7.Kleifeld O. Doucet A. auf dem Keller U. Prudova A. Schilling O. Kainthan R.K. Starr A.E. Foster L.J. Kizhakkedathu J.N. Overall C.M. Isotopic labeling of terminal amines in complex samples identifies protein N-termini and protease cleavage products.Nature Biotech. 2010; 28: 281-288Crossref PubMed Scopus (405) Google Scholar) pioneered the field of N-terminomics. COFRADIC and TAILS utilize the specific labeling of protein N termini (and Lys residues) as an initial step of the enrichment procedure. Upon proteolytic cleavage as part of the common bottom-up proteomics strategy, this labeling allows quantifying N-terminal peptides but also distinguishing them from internal peptides with free N termini generated during in vitro digestion. Both methods have been used in numerous studies providing novel insights into proteases and their substrates (1.Vögtle F.N. Wortelkamp S. Zahedi R.P. Becker D. Leidhold C. Gevaert K. Kellermann J. Voos W. Sickmann A. Pfanner N. Meisinger C. Global analysis of the mitochondrial N-proteome identifies a processing peptidase critical for protein stability.Cell. 2009; 139: 428-439Abstract Full Text Full Text PDF PubMed Scopus (353) Google Scholar, 8.Prudova A. Serrano K. Eckhard U. Fortelny N. Devine D.V. Overall C.M. TAILS N-terminomics of human platelets reveals pervasive metalloproteinase-dependent proteolytic processing in storage.Blood. 2014; 124: e49-e60Crossref PubMed Scopus (44) Google Scholar, 9.Prudova A. Gocheva V. Auf dem Keller U. Eckhard U. Olson O.C. Akkari L. Butler G.S. Fortelny N. Lange P.F. Mark J.C. Joyce J.A. Overall C.M. TAILS N-terminomics and proteomics show protein degradation dominates over proteolytic processing by cathepsins in pancreatic tumors.Cell Rep. 2016; 16: 1762-1773Abstract Full Text Full Text PDF PubMed Scopus (55) Google Scholar, 10.Gawron D. Ndah E. Gevaert K. Van Damme P. Positional proteomics reveals differences in N-terminal proteoform stability.Mol. Syst. Biol. 2016; 12: 858Crossref PubMed Scopus (51) Google Scholar). Nevertheless, likely due to challenges in technical and (particularly in the past) data analysis aspects, the number of labs worldwide applying N-terminomics methods to screen for protease substrates is still limited. We recently introduced an alternative HPLC-based strategy for N-terminal peptide enrichment, charge-based fractional diagonal chromatography (ChaFRADIC) (11.Venne A.S. Vögtle F.N. Meisinger C. Sickmann A. Zahedi R.P. Novel highly sensitive, specific, and straightforward strategy for comprehensive N-terminal proteomics reveals unknown substrates of the mitochondrial peptidase Icp55.J. Proteome Res. 2013; 12: 3823-3830Crossref PubMed Scopus (78) Google Scholar). The method depends on the separation of peptides into distinct charge-state fractions at pH 2.7, where a peptide's net charge in solution is mainly defined by the number of positively (Arg, Lys, His residues and free N termini) and negatively (e.g. phosphorylation) charged groups (Fig. 1 A) (12.Ballif B.A. Villen J. Beausoleil S.A. Schwartz D. Gygi S.P. Phosphoproteomic analysis of the developing mouse brain.Mol. Cell Proteomics. 2004; 3: 1093-1101Abstract Full Text Full Text PDF PubMed Scopus (319) Google Scholar). Though providing a high sensitivity for N-terminomics studies, the protocol requires a dedicated, highly reproducible HPLC system with automatic fractionation, which is associated with great costs and maintenance expenses. We therefore advanced the method into charge-based fractional diagonal chromatography in a pipette tip (ChaFRAtip). ChaFRAtip only requires well-established protein chemistry and minimal equipment: A pipette tip with a cellulose frit, strong cation exchange chromatography (SCX) beads and common buffers. We demonstrate that the tip-based approach is efficient and reproducible and that, in conjunction with iTRAQ-8-plex labeling, it allows quantifying more than 2,000 N-terminal peptides across eight samples using only as little as 4.3 μg of protein per condition/channel. The experiments to evaluate the performance and scalability of charge-based separation of peptides in a tip (Fig. 1) in technical using of the Methods for are represented as of the (Fig. scalability or as (Fig. and all charge-state per for the peptides and for the the between HPLC-based and ChaFRAtip, of with in to apoptosis or with as labeling and the samples in of which used for HPLC-based and for N-terminal peptides based on their and unique N termini that in at of per approach used for the (Fig. a consensus and a only unique N termini that at in at of the the study of the dynamics of staurosporine-induced with for 1.5 h, 3 h, and 6 h or as in per only N termini that quantified in at per the and a based on a per 1.5 h A and 3 h A and 6 h A and unique N-terminal peptides that at with and a as for the are in the of to more than in The by 1 in or to followed by for 6 h at The of and with and by with for at Cell with 1 and by The and to for protein μg to of protein from and to with of and of labeling triethylammonium in of in to have a of of to to a and at for h. with for at followed by of for at samples and to with of 6 which to with TEAB, pH and to a of and in to and at for h. using as C. Wortelkamp S. Sickmann A. Zahedi R.P. and of and reveals the of on Proteomics. PubMed Scopus Google Scholar). by 1 μg by for a analysis in to from based on protein and to labeling The of the in and into to μg of technical μg using HPLC-based and the μg using HPLC using a HPLC system and a 1 A in with a system of A pH pH and pH of the peptides at a of with an to charge and fractions using the The as A for followed by a from to in at for and the from to for at for and to in at to in 1 and for A to in 1 and the at A for fractions to charge and as in fractions under and to with pH to a pH of N termini of internal peptides with in from Staes A. Van Damme P. Goethals M. E. Vandekerckhove J. Gevaert K. protein N-terminal peptides by combined fractional diagonal PubMed Scopus Google Scholar) to a of and samples at for 1 h, followed by of under the h of the using for at followed by for at with acid and using peptides with of acid and with of peptides in of A. and in a under the as N-terminal peptides their charge-state internal peptides to based on the in theoretical net charge by the N-terminal fractions and in for of in and as in the Methods and in the fractions and to with pH free N termini of internal peptides as followed by peptides in of A. tip-based as in in the Methods and in for by using an to a HPLC system using a N. P. by and identification of peptides using and on an 2010; PubMed Scopus Google Scholar), as in the per in the that used for and in the that used for identification data an human using and the Proteome the and a strategy and with a of cleavage enable the of both of N-terminal with N-terminal and with endogenous we a data with at peptide N termini and at Lys as N-terminal and at Lys as both of as and of as As high to a discovery and 1 Mass to for and for representing the acid and protein and their using from the analysis in to for differences in across used to the of to of of and to based on a analysis for and based on unique N-terminal peptides on the unique the between the HPLC and the tip (Fig. HPLC and tip-based enrichment, only N-terminal peptides quantified at with of the methods (Fig. only unique N-terminal peptides representing only a that at in at of the used to a consensus the to and A. the of the of specific peptide inhibitors of Res. PubMed Scopus Google Scholar) (Fig. protein used to a high protein using P. A. O. D. N. T. A for of Res. 2003; 13: PubMed Scopus Google Scholar) to more than per in The by 1 in or and 1.5 h, 3 h, and 6 h in to for of apoptosis and of under a for in and as for apoptosis The of which and with with in for at The and the and by at for Cell in and with for labeling at for by and of the by by of the using a the a The after at in and at for the and 6 per with for 6 h used as and labeling as eight samples and by acid and the per the into in to the of the method for N-terminal peptides with ChaFRAtip by as in the technical fractions by per of HPLC and on a data peptides even quantified based on Lys quantifying the unique and and the as and the used to a and used to the on the unique the and with the using the and only N termini that quantified in at per the and a based on a per 1.5 h A and 3 h A and 6 h A and unique N-terminal peptides that at with and a as for the N-terminal peptides to a using S. T. P. A. T. M. J. The for comprehensive analysis of 2016; 13: PubMed Scopus Google Scholar) and a protein using (Fig. and using the and for proteomic using PubMed Scopus Google Scholar, A. N. M. method for 2009; PubMed Scopus Google Scholar) protocol with to μg acid analysis of protein to with pH L. Zahedi R.P. or in vitro 2013; 13: PubMed Scopus Google Scholar), and on a The at at for the at by with of pH followed by with of TEAB, pH of sequencing in TEAB, pH and at for h. The generated peptides by followed by with of TEAB, pH and of with and as C. Wortelkamp S. Sickmann A. Zahedi R.P. and of and reveals the of on Proteomics. PubMed Scopus Google Scholar). samples and in TEAB, pH The peptide using a labeling with J.N. K. S. N. S. S. S. S. P. S. M. A. protein in using Proteomics. 2004; 3: Full Text Full Text PDF PubMed Scopus Google Scholar), by to differences in due to or based on the of with to the The into μg for analysis and μg for enrichment, and both in a enrichment using K. K. M. V. A novel method for the enrichment, and of and applied to a of mouse Proteomics. Full Text Full Text PDF PubMed Scopus Google Scholar, C. S. Zahedi and enrichment from using D. Proteomics. New Scopus Google Scholar) beads followed by chromatography L. Sickmann A. Zahedi R.P. with of and using Biol. 2016; PubMed Scopus Google Scholar). chromatography fractions and at the peptides in of and using peptides and in pH μg of by chromatography at pH on a using an system with pH and in pH the with A at a of and using the for in in in for in of the with for fractions at 1 from to in a and all fractions and at chromatography fractions in of and by using an system to a as in the The in and from to at a of using the at as mass P. A. Lange O. S. M. per mass on an mass mass into a Proteomics. Full Text Full Text PDF PubMed Scopus Google Scholar). The with a and by with a of into a of pH fractions in of and of by as with data using the with Proteome and the as used the number of we protein identification by using mass spectrometry PubMed Scopus Google Scholar), A.L. approach to mass data of peptides with acid in a protein Mass PubMed Scopus Google Scholar), and V. P. T. J. T. S. K. a identification for high mass Proteome Res. 2014; 13: PubMed Scopus Google using the of Mass to and for and as with a of of and iTRAQ-8-plex on N and Lys as of and for the data of as data with the peptide with discovery the we additionally used the T. T. P. C. A. C. K. and using Proteome Res. 10: PubMed Scopus Google Scholar) for the proteome, of working with as by the Proteome into for a generated in to have eight data in an The of protein and for a over all proteins a generated by the across all from to the for used to the for a by the for protein across all This from the of protein to for by the average or 1.5 h by the average of the proteins quantified by at unique peptides A strategy for the data of unique of for unique representing the peptide and per and as unique with The of the and quantified and used to using (Fig. The mass spectrometry proteomics data have been to the the J.A. A. N. J.A. J. T. of the and its Res. 2016; PubMed Scopus Google Scholar) with the of the tip namely of the and beads to peptide as as for the and of the and and the protocol to (Fig. and (Fig. The fractions on average in distinct charge and The is (Fig. be applied to complex and and to the HPLC-based N-terminal (11.Venne A.S. Vögtle F.N. Meisinger C. Sickmann A. Zahedi R.P. Novel highly sensitive, specific, and straightforward strategy for comprehensive N-terminal proteomics reveals unknown substrates of the mitochondrial peptidase Icp55.J. Proteome Res. 2013; 12: 3823-3830Crossref PubMed Scopus (78) Google Scholar) enrichment to the ChaFRAtip (Fig. This with a of and as and reproducible HPLC is and samples be in We ChaFRAtip to the HPLC-based but at a of the costs and we in and with or to apoptosis. The samples μg of protein based on with iTRAQ-8-plex on the protein with and into of μg peptide used for HPLC-based and ChaFRAtip, followed by of per (Fig. we a of technical for both methods (Fig. and quantified ± and ± unique N-terminal peptides at discovery highly reproducible across technical and as as both methods neo N-terminal peptides to the activity (Fig. and the substrates are in protein and (Fig. ChaFRAtip highly N-terminomics with performance as the more HPLC-based We to the of the ChaFRAtip method by the dynamics of staurosporine-induced apoptosis in on initial of staurosporine-induced we h 1.5 h, h, and h of treatment, in labeling of μg on acid of peptide per μg in and we the in to 4.3 μg of protein per and the for a method to we the ChaFRAtip enrichment with samples in a of technical we quantified 2,073 ± 52 unique N-terminal peptides representing only unique protein with a strong across and technical and This to the of unique N-terminal peptides per μg of protein allow N-terminomics from such as clinical A of N termini regulation after applying unique N-terminal peptides quantified in at technical of both and at a regulation with the with a in both We the all technical and of from our data in and average of and 1.5 h of treatment, protease substrates followed by and substrates after 3 h and 6 h, and substrates the activity and an orchestrated regulation of specific pathways (Fig. The 1.5 h substrates of the splicing and machinery but also of protein and proteins to the after 3 h of and and the targeted by substrates after 6 h an of the We our N-terminomics study with proteomics and quantifying proteins with at unique peptides as as only in protein as an to a in protein with 2,000 at a after 1.5 h (Fig. from proteins a more than after 1.5 h. proteins a of This early multilevel modulation of the splicing machinery by proteolysis and may reflect the known role of alternative splicing variants for a variety of apoptotic C. splicing and homeostasis to 2016; PubMed Scopus Google Scholar, Damme P. Martens L. Van Damme J. K. Staes A. Vandekerckhove J. Gevaert K. and in protein processing during PubMed Scopus Google Scholar), which seems to be a driving force of staurosporine-induced apoptosis. Our novel ChaFRAtip approach allows the identification of proteolytic targets and consensus on a The protocol is and requires only minimal that is in proteomics the protocol be to the and may the of novel and of on their and As tip-based ChaFRAtip has for using for the of high N-terminomics. As the protocol be to of and also with chemical labeling such as or mass labeling Moreover, it be for straightforward and protease using peptide M. T. and S. in a pipette tip using peptide Scholar). The sensitivity is high for N-terminomics and may allow samples with such as biopsies but also analysis as quantifying the N-terminal the proteins with at unique and the with only 4.3 and μg of protein per and based on acid these N-terminomics after labeling μg of protein per of which into μg in to 4.3 μg of protein per condition/channel. We quantified the average of 2,073 N-terminal peptides by fractions for by h of to quantified unique N-terminal peptides per and that this be by for using L. L. for in 2014; PubMed Scopus Google Scholar). Nevertheless, and the even with as little as μg of of quantified N-terminal peptides and technical may be due to during and the Nevertheless, combined with and the sensitivity may even allow N-terminomics of needle We also our data for that may from the enrichment as this is for M. Sickmann A. Zahedi R.P. is still a 2015; PubMed Google Scholar). We therefore the unique N-terminal peptides in this study to N-terminal peptides in the peptide in as in the We only differences in peptide and net charge-state that, be to the of labeling of to identification Proteome Res. 2010; PubMed Scopus Google Scholar) than our ChaFRAtip enrichment The combined analysis of proteome, and is particularly as the complex between M. A. of crosstalk from data Proteome Res. 2014; 13: PubMed Scopus Google Scholar, A.S. L. Zahedi R.P. The of of 2014; PubMed Scopus Google Scholar, R.P. to Rev. Proteomics. 2016; 13: PubMed Scopus Google Scholar) but also between C. A. Sickmann A. Zahedi R.P. A approach for Cell Proteomics. 2016; Full Text Full Text PDF PubMed Scopus Google Scholar) has been that proteases are by N. G.S. E. S. J.C. of protease by PubMed Scopus Google Scholar), kinases be by proteolytic cleavage A. of dynamics by proteolysis of Biol. Chem. 2010; Full Text Full Text PDF PubMed Scopus Google Scholar). degradation of protease substrates M. E. J. of in human by the Biol. Chem. 2004; Full Text Full Text PDF PubMed Scopus Google Scholar). allowing the multilevel study of samples be an important step toward as it may allow identifying novel L. Sickmann A. Zahedi R.P. with of and using Biol. 2016; PubMed Scopus Google Scholar), drug and for The mass spectrometry proteomics data have been to the the with the We for critical of the with

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 categoriesMeta-epidemiology (narrow)
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 score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.242
Teacher spread0.234 · 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.

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

Citations40
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMolecular & Cellular ProteomicsSame topicAdvanced Proteomics Techniques and ApplicationsFrench-language works237,207