{"submission_id":"0e72fe06-2891-4e40-be59-60de359a5ba0","submission_revision_id":"5b0e7469-c6b3-4d2a-85dc-47910f593fc6","revision_version":1,"submission_status":"under_review","submitted_at":"2026-09-03T00:15:19.047925Z","submitter_name":"Tianyi Zhang","submitter_email":"tzhang62@usc.edu","task":{"status":"submitted","version":1,"extra_fields":{"difficulty_self_test":{"model":"Claude Opus 5 (anthropic/claude-opus-5)","estimated_score":"<1%"}},"submitted_at":"2026-09-03T00:15:19.047925+00:00","industry_domain":"Education & Information Services — Library & Information Science","task_short_name":"chinese_caoshu_transcription_instance_1","operating_system":"MacOS","task_description":"Objective: Transcribe 16 isolated Chinese characters written in highly cursive Chinese brush calligraphy (草书) into modern Unicode Chinese characters.\n\nStarting State: The input directory contains 16 PNG images named 001.png through 016.png. Each image contains one primary handwritten Chinese character. The reference answers are not available to the agent.\n\nInstructions and Rules:\n\nVisually inspect every image in filename order.\n\nIdentify the single Chinese character represented in each image.\n\nReturn exactly one prediction for every image.\n\nDo not rename, edit, enhance, replace, or omit any input image.\n\nDo not use or attempt to access the hidden reference answers.\n\nEach prediction must contain exactly one Unicode Chinese character. If the character genuinely cannot be identified, return the string UNKNOWN.\n\nSave the final output as predictions.json.\n\nThe output must be a valid JSON object whose keys are the complete image filenames and whose values are the predicted characters.\n\nRequired output format:\n\n{\n\"001.png\": \"字\",\n\"002.png\": \"字\",\n\"003.png\": \"字\",\n\"004.png\": \"字\",\n\"005.png\": \"字\",\n\"006.png\": \"字\",\n\"007.png\": \"字\",\n\"008.png\": \"字\",\n\"009.png\": \"字\",\n\"010.png\": \"字\",\n\"011.png\": \"字\",\n\"012.png\": \"字\",\n\"013.png\": \"字\",\n\"014.png\": \"字\",\n\"015.png\": \"字\",\n\"016.png\": \"字\"\n}\n\nDo not include explanations, alternatives, confidence scores, Markdown formatting, or any text outside the JSON object.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Validate that predictions.json is a parseable JSON object containing exactly the 16 required image filenames, with no missing or additional entries.\n\nFor each filename, strip surrounding whitespace from the submitted value and compare it with the corresponding answer in reference/answers.json using exact Unicode string equality.\n\nA prediction is correct only when it exactly matches the reference character. UNKNOWN, missing entries, multiple-character answers, explanations, and malformed values are incorrect.\n\nCalculate accuracy as:\n\naccuracy = number of exactly correct predictions / 16\n\nReport the result as both the number correct and the percentage, for example: 12/16 (75.0%).\n\nDo not apply a pass threshold. Preserve the per-image comparison results so that every prediction can be audited.","software_and_version":"Python 3.9 or later for structured output validation; any PNG-compatible image viewer","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"c4bf7fc4-27bb-4fde-869d-9f32ac6017ee","filename":"002.png","category":"input_materials","content_type":"image/png","size_bytes":63746},{"file_id":"c0ae1973-1041-47b8-94e2-502aaa67f66f","filename":"001.png","category":"input_materials","content_type":"image/png","size_bytes":58107},{"file_id":"4487c63d-120a-4186-930d-f5013102bfd6","filename":"009.png","category":"input_materials","content_type":"image/png","size_bytes":63310},{"file_id":"e48ca571-0a92-4e2a-b998-0cd379c795a1","filename":"007.png","category":"input_materials","content_type":"image/png","size_bytes":49970},{"file_id":"b1b8da92-855f-4097-9c23-cb9ed9b4c899","filename":"006.png","category":"input_materials","content_type":"image/png","size_bytes":65659},{"file_id":"b5e49da5-05c2-4515-b7c7-66c6764f03d7","filename":"004.png","category":"input_materials","content_type":"image/png","size_bytes":61794},{"file_id":"c542ebd5-d2c6-4cf8-b68b-eff7aaf11c70","filename":"015.png","category":"input_materials","content_type":"image/png","size_bytes":111381},{"file_id":"0702e617-0517-4e8f-93d9-f3d08daf43ab","filename":"016.png","category":"input_materials","content_type":"image/png","size_bytes":73608},{"file_id":"d8e498c2-e2c9-478c-9b7a-3be97c68b2e5","filename":"011.png","category":"input_materials","content_type":"image/png","size_bytes":103096},{"file_id":"9915f180-d09f-412b-afe2-529280c08a03","filename":"005.png","category":"input_materials","content_type":"image/png","size_bytes":64905},{"file_id":"6d57b5e5-16ec-4bf7-b0f8-bf97ec179dfa","filename":"008.png","category":"input_materials","content_type":"image/png","size_bytes":54905},{"file_id":"260da0dc-5814-429c-8c78-baa805f60f1f","filename":"013.png","category":"input_materials","content_type":"image/png","size_bytes":108616},{"file_id":"996f8a7d-eb71-4635-aae6-5e3d9c7badde","filename":"003.png","category":"input_materials","content_type":"image/png","size_bytes":58653},{"file_id":"1b903a3a-bd84-498f-b41b-fa8a21da2b69","filename":"answers.json","category":"reference_output","content_type":"application/json","size_bytes":910},{"file_id":"5c61c9f0-7505-46d8-8ae8-c635de7487e9","filename":"010.png","category":"input_materials","content_type":"image/png","size_bytes":61188},{"file_id":"509e0e47-5f2e-451a-a2ba-a98b21497be8","filename":"012.png","category":"input_materials","content_type":"image/png","size_bytes":104836},{"file_id":"6cf33639-242e-4032-8891-8e1a3395b1fc","filename":"014.png","category":"input_materials","content_type":"image/png","size_bytes":80724},{"file_id":"85678c28-2894-460c-a44b-d81c12f89af4","filename":"evidence.png","category":"difficulty_self_test_evidence","content_type":"image/png","size_bytes":230605}],"deep_review":{"overall_verdict":"Strong Accept","review_text":"**Overall Verdict:** Strong Accept — The submission is complete, internally consistent, objectively evaluable, and fully reachable with appropriately separated solver and evaluator assets.\n\n**Completeness Check:**\n- Instruction: Complete — Clearly defines the 16 ordered inputs, one-character transcription requirement, `UNKNOWN` exception, exact output filename, and JSON structure.\n- Inputs: Complete — `001.png` through `016.png` are readable isolated cursive Chinese glyphs with consistent filenames and no visible answer annotations.\n- Toolchain: Complete — Python 3.9 or later and a PNG-compatible viewer are legally obtainable and sufficient on macOS.\n- Reference output: Complete — `answers.json` parses successfully and uniquely maps all 16 filenames to single CJK Unicode characters. Its internal audit schema differs from the solver artifact but supports deterministic evaluation and agrees with the self-test evidence.\n- Rubric: Complete — Exact filename and Unicode comparisons, malformed-output handling, per-image audit results, and count/percentage scoring are fully specified without an arbitrary pass threshold.\n\n**File and Task Reachability:**\nThe attachment classification is `reachable`, and the end-to-end task classification is `reachable`. All manifest attachments were inspected: `001.png` through `016.png`, `answers.json`, and `evidence.png`; no content was left unreviewed. All 17 PNG files matched their declared byte counts and actual formats, decoded successfully, had valid container structure and checksums, and contained non-interlaced RGBA imagery. The task images range from 124–384 pixels wide and 174–420 pixels high; the self-test image is 514 × 512 pixels. The 910-byte UTF-8 JSON reference is parseable and structurally complete. The self-test image documents 0/16 accuracy and displays expected labels consistent with the reference; both answer-bearing attachments are categorized separately from solver-visible inputs. A solver can inspect the 16 images, produce `predictions.json`, validate its exact key set, and be evaluated through 16 auditable exact-match comparisons. No material tooling limitation was encountered. 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\n\n**Recommended Changes:**\nThe submission already provides usable inputs, coherent instructions, complete ground truth, and an objective scoring path. No contributor changes are required. Preserve evaluator-only access controls for `answers.json` and `evidence.png`, since both contain the protected answers.","reviewed_at":"2026-09-03T00:23:00.011776Z"},"claim":null}