OpenArx

The full arc from finding a question in the literature to a new result and publishing it. The only cycle whose output is something that didn't exist before; every other cycle works with knowledge that already exists.

1. Find the tension, pose the question — spot a contradiction, an unresolved debate, an unexplained pattern, and turn it into your own question.
2. Find footings, check it's unsaid — locate the prior work you stand on; confirm no one has already answered it.
3. Map the landscape — see the approaches, active zones, silos, and gaps around the question.
4. Generate candidate hypotheses — bridge disconnected areas, transfer a method, combine results, or drop an assumption.
5. Select one to develop — weigh the candidates (where IdeaRank applies) and choose, with a plan.
6. Get evidence, validate — run the code, the benchmark, the proof; or prepare the experiment where the lab is external.
7. Integrate and publish — fold the result into the map; publish, including negative results, or iterate.

Take an already-published claim and re-check it carefully, producing working artifacts. This cycle strengthens existing knowledge: it turns “a claim published somewhere” into “a verified result with explicit boundaries and tooling others can use.” Underrepresented in academia, high infrastructural value.

1. Select a work, justify the re-check — why this one: foundational, long un-checked, reproducibility doubts, missing artifacts, or contested.
2. Extract verifiable claims — turn the narrative into operationalizable statements that can actually be tested.
3. Inventory available materials — what's on hand (code, data, method detail) vs. what must be reconstructed.
4. Reproduce — run the experiment or benchmark, or check the proof step by step.
5. Refine the boundaries — rewrite the claim precisely: where it holds, where it breaks, under what assumptions.
6. Prepare reusable artifacts — clean code, documented data, a method note, the sharpened claim.
7. Surface side findings — note unexpected observations that can feed discovery or agenda cycles.
8. Publish the re-check — a distinct genre: what held, what didn't, exact boundaries, working code and data.

Integrate many works on a topic into a coherent description of the field. This cycle maps the state of an area at a moment in time. A good review becomes a standing footing: later researchers enter with a structural map instead of from scratch.

1. Define scope and focus — what the review covers, and what it deliberately leaves out.
2. Build the corpus — gather a sufficiently complete sample, recording why each work is included.
3. Extract key content — compress each work to its claim, method, results, and boundaries.
4. Structure by approaches and themes — cluster the corpus; note the gaps between clusters.
5. Analyze evolution over time — how the field moved; what triggered conceptual shifts.
6. Synthesize a coherent narrative — the most creative step: turn structure and facts into a readable through-line.
7. Publish the review — a standalone artifact that can anchor later work in the area.

Work on the methods of science itself — how questions get posed, evidence gets gathered, methods get applied and where they break. Two linked movements: studying existing methods, and building new ones when existing ones fall short.

1. Identify the question or limitation — “how is X done now,” “existing methods for Y break under Z,” or “we have no tool for W.”
2. Review existing methods — gather the methods that apply, with their known characteristics.
3. Analyze applicability and limits — where each works, where it breaks, what hidden assumptions it carries.
4. Generalize or design a new method — the creative fork: a methodological generalization, or a new method's architecture.
5. Validate — test the generalization on new cases, or build and benchmark a prototype.
6. Prepare for reuse — a method note with boundaries, or working code with docs and an API.
7. Publish and release — a methods paper, the implementation, or both.

A live scientific debate has several working positions that aren't reconciled. This cycle doesn't pick a side; it structures the debate itself — who stands on what, where the real disagreement is, and what would settle it. A standalone artifact, often more useful than the original papers, which don't cite each other.

1. Identify an active controversy — separate a real dispute from terminology clashes or technical noise.
2. Collect works from all sides — symmetrically, including replies, critiques, and defenses.
3. Extract each side's positions — the specific claims set against the others, tabulated.
4. Match arguments to evidence — what each side actually stands on; where they read the same data differently.
5. Isolate the core disagreements — factual, interpretive, theoretical, or methodological — each needs a different resolution.
6. Formulate resolution conditions — the experiment, observation, or proof that would settle each point.
7. Publish the controversy map — sides, arguments, fault lines, and what would resolve them.

Not “how to do science” but “what science should investigate next.” A meta-level over the other cycles: choosing direction. Rarely published formally, but high-leverage — a well-formed agenda steers dozens of later studies.

1. Map the field's current state — what's known, the schools, the nodes of agreement and dispute.
2. Identify open questions and gaps — empty zones, unresolved questions, unclosed limitations.
3. Assess significance — separate trivial openness from questions that would move a wide circle of later work.
4. Assess readiness — important-and-attackable-now vs. important-but-needing-an-infrastructure-breakthrough-first.
5. Analyze shifts in relevance — what recently became urgent (new technique, new data, external events) and what quietly left.
6. Assemble the research program — connected clusters of questions, with rationale and ordering.
7. Publish the agenda — open questions, a program, justification, infrastructure requirements.