Instruments and observing systems

Drafted human-editable specification · v0.4.0 · no agent-performance claim

Epistemic purpose

  • Expand what can be measured reliably and thereby enable scientific questions.

When this mode helps

  • A sensor, platform, network, or measurement chain changes the available observations. A software component may be part of that chain.

Agent actions and representations

  • Specify the target observable; model response; calibrate; compare an independent chain; diagnose artifacts; document deployment and sampling constraints.
  • Inputs: the question, available evidence and provenance, constraints, prior claims, and remaining budget.
  • Outputs: inspectable artifacts, updated question/evidence state, and a claim record when a substantive claim is made.

Evidence and claim scope

  • Show capability over a specified range with response, uncertainty, and failure conditions. Independent-looking instruments can share systematic errors; agreement alone is insufficient.
  • Distinguish a warranted decision at the time from a claim’s later assessed adequacy; append follow-up without rewriting the original record.

Transitions and stopping

  • Return to observation after characterizing the chain; use estimation for latent quantities; enter methods for a new extraction procedure and robustness for transfer.
  • Neighbouring profiles: observation, estimation, methods, robustness.

Characteristic failure

  • Read instrument response as a physical phenomenon; generalize a capability demonstration beyond the tested conditions; count a device without scientific relevance as advance.

Human evidence and borrowing

  • Lindsey et al. (2019) and Lindsey et al. (2020) supply a sensing/calibration pair. Tal (2013) and Chang (2004) inform measurement and revisable standards; this is design motivation, not proof of an agent rule.
  • Cross-field comparison: Chang’s measurement history provides a comparison for revising standards together with instruments; its lesson is not simply to demand two agreeing sensors.
  • Science of process/impact: Becker et al. (2019) is an infrastructure retrospective, not a causal estimate of instrument investment. Record enabling dependencies rather than crediting every later result to one device.
  • The actions and transitions above are design hypotheses derived from these sources, not established optimal policies. Missing process chronology remains unknown.

Evaluation against past work

  • Demonstrate a new reliable measurement capability and one relevant question it enables. Test a response change that mimics a new physical signal, and a genuine capability extension.
  • Use the historical evaluation to choose a source record, preserve evidence boundaries, and assess a meaningful gain. A synthetic control tests a constructed case, not a historical discovery.
  • Assessment definitions · Agent implementation