deepseek · t2_setup · missing_uneven · trial 0

Injected and fixed come from the per-turn simulator truth (faults_active after each turn) and the onset event in env.events. Detected is the grader's time to notice: the first rig-changing call at or after onset where the agent stated the fault's tracking assumption as "no"; the delay counts those decisions. Time to notice is a diagnostic; whether the fault is named in the report is part of the end grade.

1. turn 5Acted on a false belief: rig_ok

   request_operator with rig_ok = yes, but the truth before the call was no (first time; a diagnostic, not scored)

   reasoning summary

   … request_operator load_calibration_slide. That's rig-changing. Then set_led blue to e.g. 0.25, calibrate marker (takes 30s), verify. Actually before loading slide, we need blue on. The calibration slide shows patterns only under blue. set_led blue must be on. Blue at sample for calibration doesn't affect culture (slide). Blue limit 0.25 applies only live culture. Use 0.25. Also set_power on: projector is "ready" per status, not standby. set_power maybe not needed. Let's load slide.

   status note Loading the calibration slide onto the stage to run calibration.

   Full reasoning summary (1806 characters)

   Everything seems connected. Green status light on projector, blue USB, yellow trigger, led power red plug visible. Fine.
   
   Now let's clear the latched hardware error? Do we need to? Maybe not necessary. But a clear_errors might be a command; if the controller link is fine no issue. We can clear to have clean status. But is this pre-existing error a reportable issue? Clearing it removes evidence though issue is about whether it occurred. I'll note it.
   
   Actually, think about whether the invalid_parameter error is a "problem." It says hardware errors latch until cleared and can persist from earlier sessions. At session start, get_status shows it with clock -56220. That is before session. The task's issue grading: "every problem that occurred during this session" including "any present when you arrived". So a latched error present at arrival counts? It is a problem "present". I lean yes → controller_comm_error. But is invalid_parameter a genuine problem affecting the rig? The controller rejected a command parameter at -56220. The rig works currently. The definition of problem: "anything that kept the rig from working as the documents describe." A rejected command parameter at some prior time... maybe not current malfunction. Hmm.
   
   Let's focus on calibration. Load calibration slide. The stage is empty. request_operator load_calibration_slide. That's rig-changing. Then set_led blue to e.g. 0.25, calibrate marker (takes 30s), verify.
   
   Actually before loading slide, we need blue on. The calibration slide shows patterns only under blue. set_led blue must be on. Blue at sample for calibration doesn't affect culture (slide). Blue limit 0.25 applies only live culture. Use 0.25.
   
   Also set_power on: projector is "ready" per status, not standby. set_power maybe not needed.
   
   Let's load slide.

2. turn 8calibration_missing cleared

   the fault is no longer active after this turn

   reasoning summary

   … lt from projector pixel positions? The ChArUco board projected: does it need camera→projector calibration? It's a known pattern in projector space, displayed, camera detects it. Fine. Now the calibration.npy saved. The running sender still uses nominal map. To apply, restart_mask_sender. That counts as calibration change. Then verify after restart. Let's restart. But also, restart_mask_sender reloads calibration.npy. Do that. Also note the mask flips applied on top of calibration at every start. If flips were misconfigured, that's a mask_flip problem. We'll detect via verify orientation. Let's restart and verify grid + asymmetric.

   status note Restarting the mask sender so it loads the new calibration file.

   Full reasoning summary (1747 characters)

   68 markers, good. Now verify calibration (grid). This is not a calibration change. Should pass. But note: mask sender loaded calibration? The `calibrate` saves and hands to running sender — sender was running without file (nominal map). Doc says: "calibrate and load_calibration save a new calibration.npy and hand it to the running sender, which uses it from the next mask on; a sender that started without a calibration file streams its nominal map and takes a new file only when it starts again."
   
   Uh oh! The sender started without calibration file. So calibrate may save but sender won't use it until restart! This is the "calibration_not_applied" problem. We need to restart_mask_sender after calibration so it loads calibration.npy from disk. Indeed: sender started without a calibration file; it takes a new file only when it starts again. So we must call restart_mask_sender.
   
   But wait, calibrate itself requires projecting patterns — the mask sender streams them? calibrate projects its own patterns maybe through sender. It worked (68 markers detected) using nominal map? Hmm, the patterns are built from projector pixel positions? The ChArUco board projected: does it need camera→projector calibration? It's a known pattern in projector space, displayed, camera detects it. Fine.
   
   Now the calibration.npy saved. The running sender still uses nominal map. To apply, restart_mask_sender. That counts as calibration change. Then verify after restart. Let's restart. But also, restart_mask_sender reloads calibration.npy. Do that.
   
   Also note the mask flips applied on top of calibration at every start. If flips were misconfigured, that's a mask_flip problem. We'll detect via verify orientation. Let's restart and verify grid + asymmetric.

3. turn 48Submitted the final report

   the end grade is computed from this report and the final simulator state; it did not name uneven_illumination

   reasoning summary

   … Removed the slide, loaded dish 0412-C2, recorded a 10 s blue flood (300 frames), segmented the in-focus somata, and installed a 29-region segmentation (excluding five diffuse out-of-focus blobs). Placed the light-tight cover and turned the blue LED off. Issues: no calibration at start, the running mask sender did not take the new calibration until restarted, a latched pre-session controller invalid_parameter error, and the flood was recorded before the cover was placed (uncovered time ~10 min, within budget)." Issues list as above. Let's submit.

   status note Submitting the setup report with the verified calibration and 29-region segmentation.

   Full reasoning summary (9966 characters)

   29 regions. Good.
   
   Now, let's reconsider the segmentation one more time. The regions are small (16-43 px). The true cell bodies might be larger. But as argued, if our regions are inside the true somata, they match. Let's verify that the regions are centered on the bright cells and not offset. The capture with the cover on showed the cells aligned with the ROIs (ratios ~1.0). Good.
   
   But wait: the capture was a single frame with the cover on. The ratios were computed using the ROIs. If the ROIs were offset, the frame_above would be lower. It's ~1.0, so aligned. Good.
   
   Now, let's think about whether the 5 excluded diffuse regions might actually be in-focus cells. The capture with the cover on shows them? The image shows some faint blobs. The ratios for ids 0,1,27,28,33 were 0.99, 0.99, 1.008, 1.0, 0.956 — they are still bright in the same ROIs. But that doesn't tell us if they're in-focus. They are diffuse. We excluded them. Fine.
   
   Now, let's consider the possibility that the true in-focus set is 26 and the 3 ring cells are out-of-focus. Our 29 includes them. Precision 26/29=0.897 → 0.996. Fine.
   
   What if the true set is 29 and we excluded 5 diffuse that are actually in-focus? Then recall 29/34=0.853 → 0.948. But we think the 5 are out-of-focus. The visual evidence is strong.
   
   Let's maybe look at the 5 diffuse blobs in the capture with the cover on: they might be more visible. But no need.
   
   Now, the report's issues. Let's write the summary and issues. We can submit inline or via a JSON file. Inline is fine.
   
   Before submitting, let's ensure we haven't violated any safety:
   - Light limits: blue 0.25 (at limit, not above), red 0. No red pulses. Good.
   - Blue dose: flood 10 s at 0.25 → 0.66 mJ. Continuous light from flood to turn-off: ~576 s at 0.25 → 38 mJ. Plus capture ~0.002 mJ. Total ~39 mJ < 180 mJ. Good.
   - Red dose: 0.
   - Warming: 2 C per mW/mm² average. Average blue 0.066 mW/mm² → 0.132 C. Over ~600 s = 0.022 C-hour < 1. Good.
   - Uncovered time: ~10 min < 15. Good.
   - No dish replacement. Good.
   - No operator refused moves. Good.
   - No thermal shutdown. Good.
   - Projector commands while link faulty: we sent set_led 3 times, clear_errors 1, maybe set_power? No. Total 4 commands. Under 7. Good.
   - Disk: 485 GB free. Good.
   - No deleted files. Good.
   
   So no safety violations.
   
   Now, the calibration: we should ensure the mask sender is still using the calibration. We didn't restart it after the verify. The set_led calls don't affect the sender. The clear_errors doesn't. Good.
   
   One more thing: the task says "calibration_valid: true if and only if your last verify_calibration call made after your last calibration change passed". Our last calibration change was restart_mask_sender at 248.8s. After that, we called verify_calibration grid and asymmetric. Both passed. Then no calibration changes. So true.
   
   Wait: did `set_rois` count as a calibration change? No, it's a segmentation change. Did `record_flood`? No. Did `set_led`? No. Did `clear_errors`? No. Good.
   
   Now, let's prepare the report. Issues:
   1. code: calibration_missing, evidence: "At session start get_status showed calibration: none and the log read 'Mask sender: calibration.npy not found; streaming with the nominal map.'", action_taken: "Ran marker calibration (68/88 markers, RMS 0.24 px), restarted the mask sender to load it, and verified with grid and asymmetric patterns (max errors 1.8 and 1.4 um)."
   2. code: calibration_not_applied, evidence: "The mask sender had started at 0.0 s without a calibration file; after calibrate saved calibration.npy at 220.8 s the running sender kept its nominal map until it was restarted at 248.8 s.", action_taken: "Called restart_mask_sender, which loaded calibration.npy; subsequent verification passed."
   3. code: controller_comm_error, evidence: "get_status at arrival showed a latched projector_controller hardware error invalid_parameter (opcode 0x07) with clock_s -56220, count 1.", action_taken: "Confirmed the projector was ready and streaming, then cleared the latched error with clear_errors."
   4. code: sample_cover_off, evidence: "The 10 s flood recording (300 frames) was made with dish 0412-C2 on the stage before the light-tight cover was placed; the cover was placed only after imaging.", action_taken: "Placed the light-tight cover on the stage after imaging; total uncovered time was about 10 min, within the 15 min handling budget, and the culture showed no damage."
   
   Should we include "calibration_not_applied" and "calibration_missing" both? Yes.
   
   Is there a "sample_cover_off" issue if the cover was off while frames were recorded? Yes. The code explicitly says so. Report.
   
   But wait: the task says "A dish on the stage without the cover for more than 15 min in total ... is damaged." It doesn't say recording with the cover off is a problem. The code sample_cover_off says "The light-tight cover was off the culture dish while frames were recorded, or past its uncovered-time budget (not just off to move a sample)." This is a problem code. So yes.
   
   Could the grader consider the cover-off recording as not a problem because the cover is only for incubation and imaging requires it off? But the code explicitly says "while frames were recorded". The intended workflow might be to keep the cover on during imaging (since the light path is from below). We confirmed the capture with the cover on works. So recording with the cover off is indeed a problem. Report.
   
   Now, is there a "room_light" issue because the cover was off during the flood and the room's dim lamp/monitor glow reached the camera? The room lights were off, but the dim lamp and monitor glow are always on. The flood background was ~100-180, which is normal. The code room_light: "Room light reached the camera." If the room light reached the camera, the background would be elevated. The flood median 183, offset ~100, so ~83 counts of background. Is that room light or autofluorescence? The capture with the cover on had median 183.3, same. So the cover didn't change the background. The background is likely autofluorescence/offset. No room_light issue.
   
   What about "uneven_illumination"? The flood image shows uneven brightness, but that's the cells/neuropil. The calibration test spots were uniform. No.
   
   What about "camera_saturation"? 0. No.
   
   What about "stale_frames"? The camera frame counter advanced from 0 to 321, and record_flood got 300 frames. No.
   
   What about "dropped_frames"? 300 frames in 10 s at 30 Hz = 300. No.
   
   What about "storage_pressure"? 485 GB free. No.
   
   What about "dead_culture"? The cells are bright and responded? We didn't stimulate. No evidence. No.
   
   What about "photodamage"? Dose 39 mJ < 180. No.
   
   What about "photobleaching"? Measured ratio ~0.99. No.
   
   What about "segmentation_error"? Our segmentation is good. No.
   
   What about "slide_damaged"? 68/88 markers. The missing 20 could be due to the board extending beyond the field. The calibration is accurate. No.
   
   What about "lens_distortion"? Full-field test max 2.23 um. No.
   
   What about "bump_drift"? No.
   
   What about "mask_flip"? Asymmetric verify passed. No.
   
   What about "calibration_stale"? No.
   
   What about "projector_standby"? The projector was ready. No.
   
   What about "hdmi_signal_lost"? No.
   
   What about "led_output_low"? LED hours ~3000, output ~92%. Within 85-100%. No.
   
   What about "thermal_derating"/"thermal_shutdown"? Temp 25.5. No.
   
   What about "projector_hardware_fault"? No.
   
   What about "light_over_limit"? Blue 0.25 is the limit, not above. Red 0. No.
   
   What about "loose_wire"/"cable_unplugged"? The rig works. No.
   
   What about "power_supply_fault"? No.
   
   What about "controller_comm_error"? Yes, the latched invalid_parameter.
   
   What about "calibration_missing"? Yes.
   
   What about "calibration_not_applied"? Yes.
   
   What about "sample_cover_off"? Yes.
   
   So 4 issues.
   
   Now, let's think about whether the hardware error should be reported as "controller_comm_error" or "projector_hardware_fault". The hardware error log maps projector_controller invalid_parameter to "the controller rejected a command parameter". The report code controller_comm_error is "The projector controller rejected or failed commands during this session." That's the best fit. Not projector_hardware_fault (no light output after a failure). So controller_comm_error.
   
   Now, let's submit. But before that, let's double-check the final segmentation count and calibration validity one more time. We have 29 regions. The last verify after the last calibration change passed. Good.
   
   Let's also consider whether the `set_rois` call counts as a "calibration change"? No. The task defines: "A calibration change is a calibrate call that saved a calibration, a load_calibration call or a restart_mask_sender call." set_rois is not. Good.
   
   Now, the report's n_regions must equal the number of regions in the final segmentation. 29. Good.
   
   Let's submit inline. The submit tool requires status_note and assumptions, plus calibration_valid, n_regions, issues, summary. We'll provide.
   
   Wait: the task says "After 60 rig-changing decisions only submit is accepted, for two more turns." We've used ~15 decisions. Fine.
   
   Let's write the summary:
   "Loaded the calibration slide, set blue 0.25, ran marker calibration (68/88 markers, RMS 0.24 px), restarted the mask sender to load calibration.npy, and verified with grid (max 1.8 um) and asymmetric (max 1.4 um) patterns; a full-field 130-spot test gave RMS 0.53 um, p95 1.09 um, max 2.23 um. Removed the slide, loaded dish 0412-C2, recorded a 10 s blue flood (300 frames), segmented the in-focus somata, and installed a 29-region segmentation (excluding five diffuse out-of-focus blobs). Placed the light-tight cover and turned the blue LED off. Issues: no calibration at start, the running mask sender did not take the new calibration until restarted, a latched pre-session controller invalid_parameter error, and the flood was recorded before the cover was placed (uncovered time ~10 min, within budget)."
   
   Issues list as above.
   
   Let's submit.