Food Science Expert Needed to Scientifically Rebuild a Peer-Reviewed Manuscript

Project overview I am seeking an experienced food-proteomics researcher or analytical mass-spectrometry scientist to critically evaluate and substantially reconstruct a manuscript on structure-informed peptide-marker development for food authentication. Payment for this project: The total budget is $1,000 USD, to be paid in milestones based on progress: $500 USD​ upon the delivery of the rebuilt manuscript submission package, and the remaining $500 USD​ upon acceptance. The manuscript covers food-authentication proteomics, peptide-marker selection, DIA/SWATH-MS, predicted spectra, protein-structure prediction, processed-food matrices, and analytical method validation. The manuscript has undergone external peer review and was rejected in its present form. Reviewers considered the topic timely but identified major scientific weaknesses: The proposed validation framework was mainly conceptual and insufficiently distinguished from existing analytical-validation guidelines. The literature-search, study-selection and evidence-classification methods were not sufficiently transparent or reproducible. The framework was not systematically applied to published food-authentication studies. The manuscript lacked benchmark analysis, worked case studies and objective decision criteria. Processing effects, post-translational modifications, matrix effects and cross-platform/interlaboratory transferability require deeper treatment. The logical organization, academic rigor and expression accuracy require substantial improvement. This is not a language-polishing assignment. I need independent scientific judgment, source verification and evidence-based reconstruction. Proposed scope of work Part 1 — Independent scientific audit Review the manuscript, supplementary materials, decision letter and reviewer comments. Assess whether the central contribution is genuinely novel relative to existing food-authentication proteomics reviews and analytical-validation frameworks. Identify unsupported claims, methodological gaps, irrelevant or inaccurate references and AI-generated artifacts. Recommend one of the following routes: A structured/scoping review with a reproducible evidence map and operational validation rubric; or A benchmark study comparing sequence-only and structure-informed peptide nomination using suitable public proteomics datasets. Recommend a realistic article type and target-journal shortlist. Deliver a concise reconstruction plan before substantive rewriting begins. Part 2 — Evidence and methods reconstruction Depending on the agreed route: Develop a transparent search strategy, eligibility criteria, screening procedure and study-classification method. Construct an assay-level evidence table covering species, food matrix, processing conditions, peptide markers, MS platform, detection limits, decision thresholds, external validation and interlaboratory evidence. Define the inputs, minimum evidence, failure criteria, uncertainty requirements and permissible claims for each validation stage. Develop representative worked cases for meat adulteration, seafood species authentication and dairy-species identification. Address heating, fermentation, glycation, oxidation, denaturation, digestion and other processing-related changes affecting peptide detectability. If feasible, design or conduct a public-data benchmark comparing structure-informed ranking with an appropriate sequence-only baseline. Part 3 — Manuscript reconstruction Substantively rewrite the manuscript with tracked changes. Revise the title, abstract, argument structure, figures, tables and conclusions. Reposition AlphaFold or other structure-prediction tools as bounded candidate-prioritization inputs rather than substitutes for experimental validation. Verify every retained reference and DOI. Prepare a clean manuscript and an internal point-by-point matrix showing how the reviewer concerns were addressed. Tailor the final version to the verified requirements of the selected journal. Required qualifications PhD, postdoctoral or equivalent research experience in food proteomics, analytical chemistry, mass spectrometry or a closely related field. Demonstrated publications involving peptide markers, LC-MS/MS, DIA/SWATH-MS, food authentication, processed-food matrices or analytical-method validation. Strong understanding of peptide uniqueness, proteotypicity, matrix effects, processing stability, detection performance and method transferability. Experience conducting critical, systematic or scoping reviews. Ability to distinguish structural-model confidence from experimental peptide detectability. Excellent academic English and proficiency with Microsoft Word Track Changes. Willingness to challenge or remove unsupported claims rather than merely improve their wording. Academic-integrity requirements No fabricated, unverifiable or decorative citations. No citation padding or guaranteed-publication claims. No invented experimental results or representation of predictions as observed validation. Any AI tools used by the contractor must be declared, and all outputs must be independently verified. This is a paid scientific-consulting and editing engagement. Payment does not automatically confer authorship. If the final contribution independently satisfies accepted authorship criteria, authorship and CRediT roles will be discussed separately and transparently. Confidentiality is required; the manuscript will be shared with shortlisted candidates only. When applying, please answer Please provide two or three of your most relevant publications or DOIs and explain your specific contribution to each. How would you determine whether the proposed evidence ladder adds anything genuinely new beyond established analytical-method validation principles? How would you evaluate AlphaFold confidence, peptide detectability and processing/PTM effects without conflating them?