Drafts & paper ideas
A draft is an invitation to improve a question. A paper idea is not a novelty claim. Every item should survive an intellectual-lineage review before it enters the numbered sequence.
Working rule
If someone has already solved part of the problem, use their solution and move the research boundary.
Novelty is a conclusion of search, not a tone of voice.
The deep reviews have now reclassified machine discovery, knowledge routing, expert-attention bottlenecks and scarcity displacement as fields with substantial antecedents. The notebook therefore focuses increasingly on operational deltas and empirical questions.
Status labels describe both maturity and lineage. A mature antecedent narrows the question; it does not make the research direction worthless.
A formalism and benchmark proposal for allocating scarce expert review to candidate knowledge while measuring false negatives, expert-time yield, status bias and presentation sensitivity. Triage can route a claim but cannot confer authority.
A narrow, claim-sensitive handoff protocol built on contributorship, epistemic dependence, absorptive capacity, knowledge brokerage, innovation intermediaries, transactive memory and expert-evaluation research.
Builds on computational-discovery and collective-discovery scholarship to represent problem framing, generation, significance recognition, validation, integration and realization without confusing novelty, priority, contribution or authority.
A claim-sensitive authority layer built on, rather than competing with, mature contributorship systems such as CRediT and guarantorship models.
Asks how organizational and field-level absorptive/evaluative capacity behaves when machine cognition expands the supply of plausible candidate knowledge much faster than expert review and realization capacity.
Starts from established evidence that expert juries can become scarce evaluation bottlenecks and asks how expert, crowd and machine triage can be combined without credential capture, pay-to-be-heard markets or destructive false negatives.
Builds on computational-opacity and computer-assisted-proof literatures to examine the institutional consequences of reliable knowledge whose justification no individual human can fully survey.
Investigates whether existing knowledge-broker and innovation-intermediary models need new provenance, authority and routing machinery when candidate generation is machine-amplified. This replaces the looser “Epistemic Supply Chains” framing.
Publication boundary
Conceptual openness remains the default, but public release should distinguish an established idea from a local extension. Detailed technical mechanisms still pass a separate publish / protect / continue-developing review where IP could matter.