Question and related work
Separate a candidate gap from the contribution that sources actually establish.
Academia · The scientific workspace within General MMT
Move the question, data and evidence forward together.
Start with an idea, data, unfinished analysis, a manuscript or reviewer feedback. Academia brings what you know, what is missing and what the next scientific step requires into the same work.
Where does your work begin?
Start from where your research stands.
Illustrative example · no work is started
I have an idea
- What you bring
- Your question, field, goal and accessible resources.
- Work to develop
- Related work, candidate gaps, data acquisition and method options are examined.
- Your decision
- Which question and evidence needs to focus on.
- Output to keep
- Reasoned question candidates, supporting sources and a research starting point.
Keep the evidence connected as it becomes a result or manuscript.
Not every study needs the same depth at every step. Your field, experience, data access and time shape which question comes first. Critical scientific decisions remain yours.
Claim and source
Examine the source, passage and limitation behind a claim.
Data and method
Assess adequacy and prerequisites; plan acquisition when data is missing.
Calculation and interpretation
Review the input data, method, run record and output together.
Critique and further work
Test weak assumptions, contrary evidence and alternative explanations.
Revision and continuity
Keep text, decisions and outcome notes in the same research context.
Synthetic research scenario · not real user or success data
SELECTED STAGE
Actual gap
RESEARCH QUESTION
Under which conditions does remote work change knowledge loss inside teams?
Candidates only; full-text verification is in progress.
No novelty claim opens before comparison is complete.
YOU CHOOSE THE METHODMethod decision waits for the researcher
When data is missing, turn the gap into a research plan.
Identify the variables, sources or measurements needed. Compare a bounded analysis of existing data, public-source research or new data acquisition against time, cost, access and ethical conditions. A planned survey, experiment or field study is not collected data.
Explore current file and computation support
The workspace uses text, CSV, JSON, text-containing PDF, DOCX and XLSX. The current computation screen offers Python descriptive summaries and linear regression, with separate data adequacy and method approval checks. R or another method can run only when its tool path is available and verified. Uploading code does not automatically execute it.
Limits: 6 MiB per file, up to 16 selected files and 20 MiB per step, and 20 MiB account file storage. Scanned PDFs have no OCR; DOCX reading covers main text and tables. Select an Excel sheet; formula-bearing sheets are not recalculated.
Turn critique into a question that can strengthen the work.
Which assumption is weak, which contrary evidence matters, and is another explanation possible? Examine claims through these questions. Connect reviewer feedback to the relevant text and evidence; distinguish clarification, further work and revision. Accessible current journal requirements can inform preparation; publication acceptance is not promised.
Keep the context as the research changes.
Record different people's input, pending replies and decisions in your work. Return to the earlier source, data used and reason for a change. This way of working also helps General MMT; it does not mean sharing user data or automatically training a model.
Start wherever your research is today.
You do not need to begin with a method name. Describe your question and what you have.
Return to my description