{"submission_id":"fc2b487b-e205-4195-8c4c-2169079161a3","submission_revision_id":"0ce8c049-c7af-45ea-b60d-02d5472ed126","revision_version":4,"submission_status":"under_review","submitted_at":"2026-08-15T17:38:38.745037Z","submitter_name":"Gaojing Zhang","submitter_email":"poshoier@gmail.com","task":{"status":"submitted","version":4,"extra_fields":{"difficulty_self_test":{"model":"gemini-3.6-flash","harness":"Gemini Interactions API: code execution + video review + text synthesis","estimated_score":">60%"}},"submitted_at":"2026-08-15T17:38:38.745037+00:00","industry_domain":"Robotics / Laboratory Automation / Robot Learning Data Operations","task_short_name":"lab_robot_demo_audit_instance_1","operating_system":"Linux","task_description":"Objective: Audit two partially inconsistent laboratory-robot teleoperation\ncollections and ten blinded multimodal demonstrations. Determine whether each\ndemonstration is a centrifuge-tube pick or place stage, identify the right\ngripper state-change step, verify record integrity, reconcile collection\nmanifests, and create normalized machine-readable deliverables.\n\nStarting State: The input package contains redacted collection manifests,\nper-episode metadata catalogs, and ten blinded cases. Each case contains nine\ncamera streams, command/observation JSONL, force/torque JSONL, event logs, and\nredacted run metadata. Source task labels are hidden; recorded sensor and video\npayloads are unchanged.\n\nInstructions and Rules: Compare each manifest with the available metadata.\nInspect every case using video and recorded signals. Classify it as pick or\nplace, mark accept or exclude, locate the gripper-close or gripper-open step,\nreport data-row count and commanded end-effector Z extrema, and write\nresults.jsonl, normalized_manifest.jsonl, and qc_report.json using the supplied\nschema. Do not interpolate missing records or modify measured values. The task\nmust be completed offline without access to the physical robot.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Run `evaluation_dependencies/grade_submission.py` against the candidate output.\nThe grader has a 100-point scale. It checks exact case coverage; exact pick/place\nlabels; exact accept/exclude decisions; exact gripper event type; gripper event\nstep within plus or minus three recorded steps; exact data-row counts; minimum\nand maximum commanded end-effector Z within 1e-4 meters; and exact\ncollection-manifest reconciliation. Passing requires at least 90 points and no\nmissing or malformed required output file.","software_and_version":"VLC 3.0.16; JupyterLab 4.4.7; Python 3.13.9; FFmpeg/FFprobe 4.4.2","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"10fc98ad-9aa9-4ae1-815c-fe7fc3cf9716","filename":"UPLOAD_1_INPUT_MATERIALS.tar.gz","category":"input_materials","content_type":"application/gzip","size_bytes":205894322},{"file_id":"a994b57d-de6b-4f2d-a3e4-a516e8bd79c1","filename":"UPLOAD_2_REFERENCE_EVALUATION_AND_DOCS.tar.gz","category":"reference_output","content_type":"application/x-gzip","size_bytes":17936131},{"file_id":"89d5f272-8919-46e1-a4e6-93ed08d25ea1","filename":"UPLOAD_3_GEMINI_SELF_TEST_EVIDENCE.tar.gz","category":"difficulty_self_test_evidence","content_type":"application/x-gzip","size_bytes":111261}],"deep_review":{"overall_verdict":"Accept","review_text":"**Overall Verdict:** Accept — The revision is complete, coherent, and objectively gradable; only a reviewer-environment limitation prevented independent full-video playback.\n\n**Completeness Check:**\n- Instruction: Complete — Solver-visible instructions and JSON Schema define all three deliverables, fields, enums, integrity rules, and reconciliation requirements.\n- Inputs: Complete — Ten cases contain all nine expected streams and required records; all structured files parsed successfully and all 305 submitted input checksums verified.\n- Toolchain: Complete — The workflow uses legally obtainable open-source tools, permits compatible alternatives, runs offline on one ordinary machine, and requires neither robot access nor external services.\n- Reference output: Complete — Exact reference deliverables, evaluator-only ground truth, provenance, and 30 case-spanning visual frames are present and mutually consistent with independently derived signal values.\n- Rubric: Complete — The static grader implements the documented 100-point weighting, tolerances, hard failures, cross-file checks, and 90-point threshold; regression source and recorded passing reports are included.\n\n**File and Task Reachability:**\nAttachment classification: `partially_reachable` due solely to reviewer tooling. `UPLOAD_1_INPUT_MATERIALS.tar.gz`, `UPLOAD_2_REFERENCE_EVALUATION_AND_DOCS.tar.gz`, and `UPLOAD_3_GEMINI_SELF_TEST_EVIDENCE.tar.gz` were all inspected. Their declared sizes matched, gzip and tar structures were valid, and their 333, 124, and 50 members contained no traversal paths, links, device entries, duplicate archive names, encryption barriers, or unexplained installers. JSON, JSONL, schemas, manifests, checksums, documentation, reference outputs, provenance, grader source, and self-test records were inspected. All 90 input videos were recognized as ISO MP4 containers, and the 30 supplied 640x480 reference frames covering every case were visually inspected. Full temporal decoding was not independently performed because this reviewer environment lacks a media decoder; uploaded Python and bytecode were not executed under the evidence-safety policy. No attachment was omitted.\n\nTask classification: `reachable`. A solver can inspect the videos and signals, derive the ten case records, reconcile the two manifest sets, write the three specified outputs, and receive deterministic evaluation entirely offline. The approximately 225 MB expanded input is practical on one machine. Reference assets are cleanly separated from solver-visible inputs. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.\n\n**Special Screening:**\nNone. The evidence supports genuine laboratory-robot recordings and naturally occurring catalog discrepancies rather than AI-fabricated core material or a synthetic defect fixture. No affirmative public-benchmark evidence was found; external public-identifiability search was not performed under the offline review boundary.\n\n**Recommended Changes:**\nThe revision provides complete solver instructions, intact multimodal inputs, consistent references, provenance, rights confirmation, and a deterministic evaluator. No material changes are required.","reviewed_at":"2026-08-15T17:53:38.108291Z"},"claim":null}