Murat Sakal
Entropy-TOPSIS-ML + Reviewer Objection
Produces a complete Methods + Results report from your entropy weighting + TOPSIS ranking + ML classifier (XGBoost, Random Forest, Logistic Regression, etc.) outputs. Correctly classifies AUC interpretation (Hosmer & Lemeshow criteria) and, if the train/test performance gap is large, states the overfitting risk explicitly. It also pre-identifies at least 4 objections journal reviewers frequently raise (e.g., "how was class imbalance handled," "no external validation set was used") and suggests a defense sentence for each. Suitable for: researchers working in health informatics, clinical risk prediction, or hybrid MCDM-ML methodology who want methodological robustness before journal submission.
TOPSIS Decision Analysis Writer
Produces a complete manuscript-ready Methods + Results text from your TOPSIS analysis outputs (normalized decision matrix, distances to positive/negative ideal solutions, closeness coefficients). Provides a ranking table and interprets which criteria the best and worst alternatives excelled or lagged in. Suitable for: researchers working on multi-criteria ranking problems such as supplier selection, product/service comparison, or clinical decision support.
AHP Criteria Weighting Writer
Converts the user's AHP (Analytic Hierarchy Process) pairwise comparison matrix outputs (criteria weights, consistency ratio) into an academic "Criteria Weighting" section ready to drop straight into a manuscript. If the consistency ratio (CR) exceeds 0.10, it states this openly rather than hiding it. Suitable for: researchers who use MCDM methods such as TOPSIS/VIKOR and determine criteria weights with AHP, and graduate students.
Entropy-TOPSIS-ML + Rebuttal
Generates a complete Methods + Results report from your entropy weighting, TOPSIS ranking, and ML classifier outputs (XGBoost, Random Forest, Logistic Regression, etc.). It correctly interprets AUC using Hosmer & Lemeshow criteria and clearly flags the risk of overfitting when the training and test performance gap is large. It also anticipates at least four objections commonly raised by journal reviewers (e.g., “How was class imbalance addressed?” and “Why was no external validation set used?”) and provides a defense statement for each. Suitable for researchers working in health informatics, clinical risk prediction, or hybrid MCDA-ML methodologies, and for those seeking methodological rigor before journal submission.
TOPSIS Decision Analysis Report Writer
Generates a complete, publication-ready Methods + Results section from your TOPSIS analysis outputs (normalized decision matrix, distances to positive/negative ideal solutions, and closeness coefficients). Presents a ranking table and interprets which criteria distinguish the best and worst alternatives. Suitable for researchers working on multicriteria ranking problems such as supplier selection, product/service comparisons, and clinical decision support.
AHP Criterion Weighting Writer
Transforms the user's AHP (Analytic Hierarchy Process) pairwise comparison matrix outputs (criterion weights and consistency ratio) into an academic “Criterion Weighting” section that can be added directly to a paper. If the consistency ratio (CR) exceeds 0.10, it states this clearly without hiding it. Who it's for: Researchers and graduate students who use MCDM methods such as TOPSIS/VIKOR and determine criterion weights with AHP.
PLS-SEM Report + Objection Engine
Produces a complete Measurement Model + Structural Model report from your PLS-SEM analysis outputs (outer loadings, CR/AVE, HTMT discriminant validity, path coefficients, R²/f²/Q², SRMR). Correctly applies the HTMT threshold and R² interpretation (Cohen/Chin criteria) and avoids causal language. It also pre-identifies at least 4 objections journal reviewers frequently raise (e.g., "why PLS over CB-SEM," "no CMB control reported") and suggests a defense sentence for each. Suitable for: business/social science researchers using PLS-SEM for structural equation modeling who want methodological robustness before journal submission.
Validity-Reliability Report Writer
Produces a complete manuscript-ready Methods + Results text from your EFA or CFA analysis outputs (KMO, Bartlett's test, factor loadings, fit indices, Cronbach alpha/CR/AVE). Correctly classifies fit index thresholds (CFI/TLI≥.90, RMSEA≤.08, etc.) and reports validity issues like AVE<0.50 without hiding them. Suitable for: academics and graduate students conducting scale development or adaptation studies.
Cronbach Alpha Reliability Writer
Converts the reliability statistics you enter (Cronbach alpha, item count, subscales) into an academic "Reliability Analysis" paragraph ready to drop straight into your manuscript. Provides an acceptability table by subscale and, if it detects a low alpha (<.60), states this openly rather than hiding it. Suitable for: graduate students and researchers using scales who want to write the method section quickly and correctly.
PLS-SEM Report & Rebuttal
Generates a complete Measurement Model + Structural Model report from your PLS-SEM analysis outputs (outer loadings, CR/AVE, HTMT discriminant validity, path coefficients, R²/f²/Q², and SRMR). It correctly applies the HTMT threshold and interprets R² using the Cohen/Chin criteria, while avoiding causal language. It also anticipates at least 4 common journal reviewer objections (e.g., “Why was PLS chosen instead of CB-SEM?” and “No CMB test was conducted”) and provides a defense statement for each. Suitable for: business and social science researchers conducting structural equation modeling with PLS-SEM and seeking methodological rigor before journal submission.
Validity & Reliability Writer
Generates a complete, publication-ready Methods + Results section from your EFA or CFA analysis outputs (KMO, Bartlett’s test, factor loadings, fit indices, Cronbach’s alpha/CR/AVE). Correctly classifies fit-index thresholds (CFI/TLI≥.90, RMSEA≤.08, etc.) and reports validity concerns such as AVE<0.50 without hiding them. Suitable for academics and graduate students conducting scale development or adaptation studies.
Cronbach Alpha Writer
Transforms the reliability statistics entered by the user (Cronbach's alpha, item count, and subscales) into an academic “Reliability Analysis” paragraph ready to add directly to a paper. Provides an acceptability table for each subscale and clearly reports low alpha values (<.60) without hiding them. Suitable for: graduate students and researchers using scales who want to write the methods section of a thesis or paper quickly and accurately.
CONSORT 2010 Report Writer
From your randomized controlled trial (RCT) data — randomization method, blinding status, power analysis, CONSORT flow numbers (screened/randomized/allocated/analyzed), ITT/PP analysis approach — it produces a complete Abstract + Methods + Results draft compliant with all 25 items of CONSORT 2010. It never confuses ITT/PP; it checks the consistency of flow diagram numbers (randomized ≥ allocated ≥ followed-up ≥ analyzed). It also pre-identifies at least 4 objections journal reviewers frequently raise (e.g., "why wasn't an ITT analysis reported," "was blinding success tested," "was there outcome switching") and suggests a defense sentence for each. Designed for clinical researchers in medicine/nursing/pharmacy conducting RCTs who want methodological robustness before journal submission. What it does not do: it does not perform statistical analysis or generate data — it only converts results you already have into a CONSORT-standard report.
STROBE Methods Writer
Based on your cross-sectional, cohort, or case-control study design; when you enter your participant selection method, variables, sample size rationale, and statistical methods, it produces a complete Methods and Results draft with implicit reference to all 22 items of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. It also provides a mapping table at the end showing which paragraph corresponds to which STROBE item — ready to answer a journal's "please complete the STROBE checklist" request. Avoids causal language (uses "is associated with" rather than "causes" for observational studies) and explicitly discusses sources of bias/confounding. Suitable for academics working in epidemiology, public health, and clinical research.
Missing Data Reporting Assistant
When you enter your sample size, missing data proportion/pattern (MCAR/MAR/MNAR), missing data method (listwise deletion, multiple imputation, etc.), and outlier detection method (Z-score, IQR, Mahalanobis), it produces an academic paragraph that can be inserted directly into the "Data Pre-processing" section of your manuscript. If there is a methodological contradiction between your method choice and the missing data pattern (e.g., using listwise deletion under an MNAR pattern), it states this explicitly. Suitable for: graduate students and researchers doing survey/clinical data analysis who want to write the data pre-processing section quickly and correctly.
Scale Development Data Audit
This skill systematically audits raw survey data collected as part of a scale development study for missing data, outliers, careless responding (straightlining, longstring, random responding), item-level distribution problems, and the prerequisites for reliability and factorability. It does not produce final EFA/CFA results; instead, it provides an evidence-based “go/no-go” decision on whether the data are ready for subsequent analyses, along with a recommendation for a stratified sample split (EFA/CFA split). All calculations are performed by running real code (Python: pandas, scipy, factor_analyzer, pingouin); no assumed numbers are generated.
Meta-Analysis Full Report Writer
Produces a complete Methods + Results + Limitations text compliant with PRISMA 2020 and the Cochrane Handbook from your meta-analysis statistics (pooled effect size, I², Q, tau², publication bias indicators). Never misinterprets the I² value (including the "percentage of variance" framing); avoids overstated causal language (uses cautious phrasing like "findings are consistent with..." instead of "evidence demonstrates that"). At the end, it also offers at least 3 questions a reviewer might ask along with defense sentences. Suitable for: researchers writing a meta-analysis paper who want to strengthen the methods section before journal submission. What it does not do: it does not perform statistical calculations from raw data (you must already have your R/RevMan/CMA output) — it only converts and interprets your results into academic text.
Bibliometric Findings Writer
Converts the raw numbers you obtain from VOSviewer or Biblioshiny (Bibliometrix/R) outputs (keyword frequencies, citation network clusters, yearly publication trend, country/institution/journal distribution) into publication-ready, interpreted academic text. Uses an academic tone that narrates where the literature is heading rather than repeating raw numbers; avoids speculative causal claims. Suitable for: researchers writing a thesis/paper who need a bibliometric analysis section but struggle to translate raw data into academic language. Usage: paste your cluster/keyword list from VOSviewer or your Biblioshiny summary table directly; the skill thematically names and interprets the keyword clusters, and evaluates the citation network and country collaboration pattern.
PRISMA 2020 Flow Diagram Writer
Generates a PRISMA 2020-compliant flow diagram text and protocol paragraph for researchers conducting systematic reviews. When you enter your database screening counts (identification → screening → eligibility → included), it checks the consistency of the numbers and produces text defensible against the reviewer question "why does your flow diagram lose so many records?" It also converts your inclusion/exclusion criteria into a PICO/PECO-format table. Suitable for: graduate students, academics, and journal editors' pre-checks for systematic review/meta-analysis papers. If it detects a numeric inconsistency (e.g., included > eligibility) it states this explicitly rather than silently correcting it.
CONSORT 2010 Report Writer
Generates a complete Abstract + Methods + Results draft from your randomized controlled trial (RCT) data—randomization method, blinding status, power analysis, CONSORT flow counts (screened/randomized/allocated/analyzed), and ITT/PP analysis approach—in accordance with CONSORT 2010's 25-item checklist. It never confuses ITT and PP, and checks the consistency of flow diagram counts (randomized ≥ allocated ≥ followed-up ≥ analyzed). It also proactively identifies at least 4 objections that journal reviewers frequently raise (such as "Why was the ITT analysis not reported?", "Was the success of blinding tested?", and "Was there any outcome switching?") and suggests a defense statement for each. Designed for clinical researchers and academics conducting RCTs in medicine, nursing, or pharmacy who want methodological rigor before journal submission.
Scale Data Precheck
Triggered when raw scale development data (Excel/CSV) collected by a professional survey firm needs to be reviewed for psychometric data quality before proceeding to EFA/CFA or final reliability analyses. It comprehensively evaluates missing data, outliers, careless responding, response bias, item quality, and sample adequacy, then produces a Go/No-Go decision. It does not modify the data; it only provides a diagnostic audit report.
STROBE Checklist Method Writer
Based on your cross-sectional, cohort, or case-control study design, this Skill generates a complete Methods and Results draft when you provide your participant selection methods, variables, sample size rationale, and statistical methods, with implicit reference to the 22 items on the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. At the end, it also provides a mapping table showing which paragraph addresses each STROBE item—giving you a ready response to the “fill out the STROBE checklist” request during journal submission. It avoids causal language (because this is an observational study, it uses “is associated with” rather than “causes”) and explicitly discusses sources of bias and confounding. Suitable for academics working in epidemiology, public health, and clinical research.
Missing Data & Outlier Assistant
Enter your sample size, missing-data rate/pattern (MCAR/MAR/MNAR), missing-data method (listwise deletion, multiple imputation, etc.), and outlier detection method (Z-score, IQR, Mahalanobis) to generate an academic paragraph that can be added directly to the "Data Preprocessing" section of your paper. If there is a methodological inconsistency between your selected method and the missing-data pattern (for example, using listwise deletion for an MNAR pattern), it will be clearly identified. Suitable for graduate students and researchers conducting survey or clinical data analysis who want to write their data preprocessing section quickly and accurately.
Meta-Analysis Report
Produces a complete Methods + Results + Limitations text from your meta-analysis statistics (pooled effect size, I², Q, τ², and publication bias indicators), aligned with PRISMA 2020 and the Cochrane Handbook. It never misinterprets I², including the percentage of variance explained, and avoids overstated causal language by using cautious phrasing such as “the findings are consistent with...” instead of “the evidence shows that...”. It also provides at least 3 potential questions a reviewer may ask, along with defense statements. Suitable for researchers writing a meta-analysis paper or strengthening the Methods section before journal submission. What it does not do: calculate statistics from raw data (you must already have calculated your results using R/RevMan/CMA); it only converts and interprets your results as academic text.
Bibliometric Findings Writer
Transforms the raw numbers from VOSviewer or Biblioshiny (Bibliometrix/R)—including keyword frequencies, citation network clusters, annual publication trends, and country/institution/journal distributions—into interpreted text ready for academic publication. Rather than repeating the numbers, it uses an academic tone to explain how the literature is evolving and avoids speculative causal claims. Suitable for researchers writing theses or articles who need to prepare a bibliometric analysis section but struggle to translate raw data into academic language. Usage: Paste the cluster/keyword list from VOSviewer or the Biblioshiny summary table directly; the skill names and interprets keyword clusters thematically, and evaluates citation networks and country collaboration patterns.
PRISMA 2020 Flowchart Writer
Generates PRISMA 2020 checklist-compliant flowchart text and a protocol paragraph for researchers conducting systematic reviews. When you enter your database screening counts (identification → screening → eligibility → included), it checks the numbers for consistency and produces defensible wording to address a reviewer’s question: “Why does your flowchart show so many losses?” It also converts your inclusion and exclusion criteria into a table in PICO/PECO format. This skill is suitable for graduate students writing systematic reviews or meta-analyses, as well as for preliminary checks by journal editors. If it detects a numerical inconsistency (e.g., included > eligibility), it states this clearly rather than silently correcting it.