Instruments and observing systems

Drafted human-editable specification · v0.4.4 · 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.
• Definition and evidence (modes meeting, drafted October 2026): Defined as distinct work by Baird (2004); experimentation and invention have “a life of its own” in Hacking (1983) (pp. 150, 163); instruments move between technical and epistemic status (Rheinberger 2011). A new instrument, archive, or computer was a precondition in 15 of 18 coded geoscience advances; a cost shock to one sensing tool widened the knowledge teams combined (Teodoridis 2018). On graph v0.4: N (new capability).
• 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

Baird, Davis. 2004. Thing Knowledge: A Philosophy of Scientific Instruments. University of California Press. https://doi.org/10.1525/9780520928206.

Becker, Keir, James A. Austin, Neville Exon, et al. 2019. “Fifty Years of Scientific Ocean Drilling.” Oceanography 32 (1): 17–21. https://doi.org/10.5670/oceanog.2019.110.

Chang, Hasok. 2004. “Measurement, Justification, and Scientific Progress.” In Inventing Temperature. Oxford University Press. https://doi.org/10.1093/0195171276.003.0005.

Hacking, Ian. 1983. Representing and Intervening: Introductory Topics in the Philosophy of Natural Science. Cambridge University Press. https://doi.org/10.1017/cbo9780511814563.

Lindsey, Nathaniel J., T. Craig Dawe, and Jonathan B. Ajo-Franklin. 2019. “Illuminating seafloor faults and ocean dynamics with dark fiber distributed acoustic sensing.” Science 366 (6469): 1103–7. https://doi.org/10.1126/science.aay5881.

Lindsey, Nathaniel J., Horst Rademacher, and Jonathan B. Ajo-Franklin. 2020. “On the Broadband Instrument Response of Fiber-Optic DAS Arrays.” Journal of Geophysical Research: Solid Earth 125 (2): e2019JB018145. https://doi.org/10.1029/2019JB018145.

Rheinberger, Hans-Jörg. 2011. “Consistency from the perspective of an experimental systems approach to the sciences and their epistemic objects.” Manuscrito 34 (1): 307–21. https://doi.org/10.1590/s0100-60452011000100014.

Tal, Eran. 2013. “Old and New Problems in Philosophy of Measurement.” Philosophy Compass 8 (12): 1159–73. https://doi.org/10.1111/phc3.12089.

Teodoridis, Florenta. 2018. “Understanding Team Knowledge Production: The Interrelated Roles of Technology and Expertise.” Management Science 64 (8): 3625–48. https://doi.org/10.1287/mnsc.2017.2789.