{"bounty":{"chain_id":8453,"hub_address":"0x8f80d1183cd983b01b0c9ac6777cc732ec9800de","bounty_id":"4","poster":"0xcbc4f2b3f0de63396d865b704b25e22472d15ad9","status":"open","winner":null,"submission_deadline":1795564740,"judging_deadline_at":1795694340,"settlement_timeout_at":1795823940,"escrow":{"token_address":"0x833589fcd6edb6e08f4c7c32d4f71b54bda02913","amount":"20000000"},"guardian_roster_hash":"0x717091d098f69dc975abcb7775556cf24cc8c01d901ebf03f573f0f703954fc5","guardian_roster":[{"name":"Dark Tang","account":"0xbaf7d9d21447db598c502bbb8ddcf25d279adc60","encryption_public_key":"MoZYm0-WvaMQAozZ6wKbXySs4g2tr3wPmmt5kfv1TUk"},{"name":"Rare Mussel","account":"0xa4a3f99b302c61412bd87f5f5d7703d5c2cea849","encryption_public_key":"b3NG1NbiNsLXeyD4SVeQkztlFssbOnJw5tHjDpCelgs"},{"name":"Loud Abalone","account":"0x84e981caab8db3c8e0e4508a0ecac97b8fe39073","encryption_public_key":"0H3apAAV3y5crIsfZGt_jy2fSXYMkwCnC3EoxKFiFGc"}],"payout_scheme":"0x36d304993cb1575a2f9b8a0388b18aa5ec6d7a61","treasury_recipient":"0xd3ce7873ba9b86385f0c1226c3c585a9bca0d277","treasury_fee_bps":0,"guardian_fee_recipient":"0xd3ce7873ba9b86385f0c1226c3c585a9bca0d277","guardian_fee_bps":1000,"spec_commitment":"0x6016f98e8679690d7b072e37aa6c07a12b406400db094c81177440f8bbd47632","submissions":[{"solver":"0x115979d1fbd1ff1a5ac771be68ff020105233535","submission_commitment":"0x66ccd28c3f2a2797601ec30e83f90b31f318c0cb904446ab4c35fb60412cc12d"},{"solver":"0x1d4c28113002718859d9e808d81ccd3b7763e9b8","submission_commitment":"0x3b88a1fe958dad8f5e701ce09a0009bb7262e6968663d460a4c3bd0037af4b1d"},{"solver":"0x1e3623906579c43ccc6d4e2975ef1f8b42c61d09","submission_commitment":"0xbacc53dc9707e0ec07617d5566f35c28e95387473cec2a9c0d10319f50a3dfbf"},{"solver":"0x2d98ee4949f391f957d10588c00d467ab1749fce","submission_commitment":"0x90996040d0d29abc4b5b164b361950b3a51e540620bcea15a6cd75fc010306fc"},{"solver":"0x351d79bc02b4276ce9014d3bbe141d899ab91376","submission_commitment":"0xc5d3a4cac34a77c5dc49afca5802931bdfe15a5d1bad52f0b97deee7a0e8bd40"},{"solver":"0x5d8390f6e564b2b6c26b482cbbd762a819df7f9f","submission_commitment":"0xe8c23eb7c9bbb0b394eb2801acb26fd986815b263ae1780e2e9149de3af11b93"},{"solver":"0x7152f226f565c3b86943ce7b4f38e77110bd4c07","submission_commitment":"0xfb0ffded80b07f1ca6fcbcc812b2334e77b93149051f834dd502e9b2ac318a31"},{"solver":"0x8b36c13824705c65c3579825f5877b225abb231b","submission_commitment":"0x4cdc129b30ceb8b854fffb6e1159ad3daefe91745811be14d560d8fdfed7b62f"},{"solver":"0xbfce2a2b806d09c69abaff494d33f86e6de627d5","submission_commitment":"0x748f23e4733af0236f9e88b1de973a6dea0d4220f9f314de4fe2d63be7bdb148"},{"solver":"0xf9f56e60828204a07203ba6bda77f49e4925837a","submission_commitment":"0x6a9d2cd443cb8948e6a96ce099ac68a0ae9eba258853da8fa333743bd54dcee1"}],"submission_count":10},"challenge":"---\nprofile: elgora_markdown_bounty_challenge_v1\nescrow_amount: \"20000000\"\nsubmission_deadline: 1795564740\npayout_policy: winner_take_all\n---\n\n# Evidence-level map for 10 research peptides\n\n## Summary\nBuild one CSV that classifies the published PubMed evidence base for 10 named\nresearch peptides: for each qualifying PubMed record, what kind of study it is\n(human randomized trial, other human study, animal, in vitro, or review only),\nin which species or system, with how many subjects, and what the study says it\nmeasured. Every row is checked against its PubMed record. This is a\nbibliographic map of what kind of evidence exists, not a judgment of whether\nany peptide works or is safe.\n\n## Challenge details\n\n### What is being mapped\nThe 10 peptides are fixed by `peptides.csv` (reproduced under Inputs). A\npeptide's *accepted names* are the names in its `accepted_names` field; a\nrecord that names the peptide under any accepted name, as a salt or acetate\nform, or (for GHK) as its copper complex, names that peptide.\n\nA PubMed record is **qualifying** for a peptide when its PubMed title or\nabstract shows either:\n- a **primary study** in which that peptide is a tested agent: it is\n  administered, applied, or added to the study system, alone, in a\n  formulation, or loaded in or conjugated to a carrier; or\n- a **review** (narrative review, systematic review, meta-analysis, overview\n  or editorial without new primary data) whose title names the peptide, or\n  whose abstract discusses the peptide as one of its subjects.\n\nA record is **not qualifying** for a peptide when, judged from its PubMed title\nand abstract, the peptide is only measured as an endogenous molecule,\nbiomarker or gene product (for example blood levels of LL-37 or MOTS-c), when\nthe matched text is an unrelated use of the same letters (for example \"GHK\" as\nan acronym for a programme name), when the study tests only a peptide with a\ndifferent amino-acid sequence, or when the work is purely computational.\n\nAll facts in a row are read from the record as displayed on PubMed\n(https://pubmed.ncbi.nlm.nih.gov/{pmid}/): its title, abstract, DOI,\npublication date and publication types. Full texts are not needed and do not\noverride the PubMed record.\n\n### Evidence levels\nEach row gets exactly one `evidence_level`. When a record fits more than one,\nuse the first that applies in this order:\n\n| `evidence_level` | Applies when the title or abstract shows |\n|---|---|\n| `human_randomized_trial` | human participants received the peptide and were allocated to groups at random (the abstract says random or randomized, or PubMed lists the publication type Randomized Controlled Trial) |\n| `human_nonrandomized_or_observational` | human participants received or were treated with the peptide without random allocation: open-label or single-arm trials, cohort studies, case series, case reports, post hoc or registry analyses of treated patients |\n| `animal` | living non-human animals received the peptide |\n| `in_vitro` | the peptide was tested only on cells, tissues or organs outside a living body (human or animal), or in a cell-free or biochemical system |\n| `review_only` | the record is a review as defined above and reports no new primary data |\n\n### Result meaning\nThe dataset records what kind of evidence each publication is and what it\nsays it measured. It does not establish that any reported result is correct,\nthat any peptide is effective or safe, or that the list of publications outside\nthe checks below is complete.\n\n## What you need to submit (Deliverables)\n\n| File | Required | Format | Purpose |\n|---|---:|---|---|\n| `evidence.csv` | yes | UTF-8 CSV, comma-separated, RFC 4180 quoting, header row, schema below | the evidence map |\n| `provenance.md` | yes | UTF-8 Markdown | every PMID from the completeness snapshot (see Inputs) that is not a row of `evidence.csv` for its peptide, with its reason code |\n| `method.md` | no | UTF-8 Markdown | how the records were found; informational only, not scored |\n\n`evidence.csv` columns, in this order:\n`peptide,pmid,doi,publication_year,evidence_level,species_or_system,sample_size,primary_outcome_as_stated,section_or_page`\n\n- `peptide` is the `peptide` value from `peptides.csv`, written exactly as\n  there (for example `GHK`, `MOTS-c`).\n- `pmid` is the PubMed identifier, digits only.\n- `doi` is the DOI shown on the PubMed record, lowercase, without a\n  `https://doi.org/` prefix; blank when the PubMed record shows no DOI.\n- `publication_year` is the four-digit year of the record's publication date\n  as shown on PubMed.\n- `evidence_level` is one of the five values in the table above.\n- `species_or_system` is `human` for the two human levels; the common name of\n  the animal species for `animal` (for example `rat`, `mouse`, `zebrafish`;\n  several species separated by `;`); for `in_vitro`, the cell line, cell type,\n  tissue or system as the abstract names it; `not_applicable` for\n  `review_only`.\n- `sample_size` is the total number of participants (human levels) or animals\n  (`animal`) that the abstract states were enrolled, randomized or included;\n  when the abstract states more than one such total, the largest. It is blank\n  when the abstract states no such total, and always blank for `in_vitro` and\n  `review_only`. Integer, no separators.\n- `primary_outcome_as_stated` is a verbatim quote, at most 300 characters,\n  from the record's title or abstract that states the study's primary outcome\n  or endpoint; when no primary outcome or endpoint is stated, the sentence or\n  clause stating the study's aim, objective or what was measured; for\n  `review_only`, the stated aim of the review, or its title when the abstract\n  states none. Parts of one sentence may be omitted with `...`; every other\n  character matches PubMed apart from whitespace and letter case. The quote\n  describes what was measured or aimed for, not a result value.\n- `section_or_page` is where the quote appears: `title`; `abstract` for an\n  unstructured abstract; or `abstract:` followed by the heading of a\n  structured abstract under which the quote appears, as PubMed prints it (for\n  example `abstract:OBJECTIVE`).\n\nA record that is qualifying for two peptides (for example a study of both\nsemax and selank) is one row per peptide. No two rows share the same\n`peptide` and `pmid`.\n\n`provenance.md` lists each such PMID with its peptide and one reason code:\n`not_qualifying_endogenous_or_biomarker`, `not_qualifying_unrelated_term`,\n`not_qualifying_different_sequence`, `not_qualifying_computational`, or\n`not_qualifying_other` followed by a one-sentence reason.\n\n## Inputs, Materials and References\n\n| Input | Why it is needed | How to get it | SHA-256 content hash |\n|---|---|---|---|\n| `peptides.csv` | the fixed list and numbering of the 10 peptides and their accepted names | reproduced in full below | none: the text on this page is the input |\n| completeness snapshot | the fixed PMID list per peptide used by the completeness check | reproduced in full below | none: the text on this page is the input |\n| PubMed | the record of each PMID | https://pubmed.ncbi.nlm.nih.gov/ ; no sign-in | none: the record as displayed on PubMed |\n| drand `quicknet` beacon | the seed that picks the checked rows and peptides | public at https://api.drand.sh/52db9ba70e0cc0f6eaf7803dd07447a1f5477735fd3f661792ba94600c84e971/public/{round}; no sign-in | none: each value is checked by its drand signature |\n\n### `peptides.csv`\n```csv\npeptide_number,peptide,accepted_names\n1,thymosin beta-4,thymosin beta-4; thymosin beta4; thymosin beta 4; Tbeta4\n2,GHK,GHK; GHK-Cu; glycyl-histidyl-lysine; glycyl-L-histidyl-L-lysine; copper tripeptide\n3,BPC-157,BPC-157; BPC 157; BPC157; pentadecapeptide BPC 157\n4,KPV,KPV; Lys-Pro-Val; lysine-proline-valine\n5,epitalon,epitalon; epithalon; epithalone; AEDG; Ala-Glu-Asp-Gly\n6,semax,semax\n7,selank,selank\n8,MOTS-c,MOTS-c; MOTSc\n9,elamipretide,elamipretide; SS-31; Bendavia; MTP-131\n10,LL-37,LL-37; LL37\n```\n\n### Completeness snapshot\nFor each peptide the Poster ran the PubMed query below on 9 November 2026 and\nrecorded every returned PMID. The query restricts to human-study publication\ntypes up to 31 October 2026. The PMID list that follows, not a later re-run of\nthe query, is the snapshot; it deliberately includes records that are not\nqualifying (for example LL-37 and MOTS-c measured only as biomarkers, or\n\"SS-31\" and \"GHK\" used for unrelated things).\n\n| peptide_number | peptide | PubMed query | PMIDs in snapshot |\n|---:|---|---|---:|\n| 1 | thymosin beta-4 | `(\"thymosin beta-4\"[tiab] OR \"thymosin beta4\"[tiab] OR \"thymosin beta 4\"[tiab] OR \"Tbeta4\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 10 |\n| 2 | GHK | `(\"GHK-Cu\"[tiab] OR \"glycyl-L-histidyl-L-lysine\"[tiab] OR \"glycyl-histidyl-lysine\"[tiab] OR \"copper tripeptide\"[tiab] OR \"GHK\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 4 |\n| 3 | BPC-157 | `(\"BPC 157\"[tiab] OR \"BPC-157\"[tiab] OR \"BPC157\"[tiab] OR \"pentadecapeptide BPC\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 0 |\n| 4 | KPV | `(\"KPV\"[tiab] OR \"Lys-Pro-Val\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 0 |\n| 5 | epitalon | `(\"epitalon\"[tiab] OR \"epithalon\"[tiab] OR \"epithalone\"[tiab] OR \"Ala-Glu-Asp-Gly\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 1 |\n| 6 | semax | `(\"semax\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 4 |\n| 7 | selank | `(\"selank\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 3 |\n| 8 | MOTS-c | `(\"MOTS-c\"[tiab] OR \"MOTSc\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 8 |\n| 9 | elamipretide | `(\"elamipretide\"[tiab] OR \"SS-31\"[tiab] OR \"Bendavia\"[tiab] OR \"MTP-131\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 22 |\n| 10 | LL-37 | `(\"LL-37\"[tiab] OR \"LL37\"[tiab]) AND (clinical trial[pt] OR randomized controlled trial[pt] OR controlled clinical trial[pt] OR clinical study[pt] OR observational study[pt]) AND (\"1900/01/01\"[dp] : \"2026/10/31\"[dp])` | 80 |\n\n```csv\npeptide_number,peptide,pmid\n1,thymosin beta-4,17495250\n1,thymosin beta-4,20536470\n1,thymosin beta-4,20536472\n1,thymosin beta-4,24882420\n1,thymosin beta-4,25826322\n1,thymosin beta-4,26022762\n1,thymosin beta-4,27288307\n1,thymosin beta-4,29482481\n1,thymosin beta-4,34346165\n1,thymosin beta-4,34607232\n2,GHK,16847171\n2,GHK,29482481\n2,GHK,39636875\n2,GHK,41872954\n5,epitalon,12195242\n6,semax,10741256\n6,semax,11517472\n6,semax,18379501\n6,semax,29798983\n7,selank,18454096\n7,selank,25176261\n7,selank,26356395\n8,MOTS-c,32052315\n8,MOTS-c,34351816\n8,MOTS-c,34413391\n8,MOTS-c,36490309\n8,MOTS-c,38314601\n8,MOTS-c,39111290\n8,MOTS-c,40008510\n8,MOTS-c,40674654\n9,elamipretide,405283\n9,elamipretide,22328192\n9,elamipretide,26586786\n9,elamipretide,27286183\n9,elamipretide,27392509\n9,elamipretide,28534645\n9,elamipretide,28916603\n9,elamipretide,29217757\n9,elamipretide,29500292\n9,elamipretide,32068002\n9,elamipretide,32096613\n9,elamipretide,33077895\n9,elamipretide,34264994\n9,elamipretide,36056411\n9,elamipretide,37041653\n9,elamipretide,37268435\n9,elamipretide,37923251\n9,elamipretide,38602181\n9,elamipretide,39217569\n9,elamipretide,39574155\n9,elamipretide,40281531\n9,elamipretide,40785393\n10,LL-37,17039460\n10,LL-37,17568755\n10,LL-37,19114868\n10,LL-37,19878298\n10,LL-37,19943126\n10,LL-37,20436715\n10,LL-37,20610636\n10,LL-37,20695797\n10,LL-37,20806415\n10,LL-37,21249386\n10,LL-37,22246800\n10,LL-37,22455725\n10,LL-37,22531915\n10,LL-37,22574737\n10,LL-37,22805498\n10,LL-37,23361158\n10,LL-37,23553300\n10,LL-37,23590701\n10,LL-37,24398649\n10,LL-37,24763694\n10,LL-37,24771854\n10,LL-37,25041740\n10,LL-37,25089537\n10,LL-37,25268344\n10,LL-37,25354286\n10,LL-37,25435436\n10,LL-37,25931489\n10,LL-37,26086941\n10,LL-37,26375724\n10,LL-37,26394045\n10,LL-37,26545199\n10,LL-37,26732025\n10,LL-37,26921215\n10,LL-37,27377698\n10,LL-37,27488327\n10,LL-37,27641738\n10,LL-37,28094872\n10,LL-37,28218580\n10,LL-37,28228596\n10,LL-37,28526374\n10,LL-37,28956425\n10,LL-37,29044786\n10,LL-37,29091380\n10,LL-37,29273721\n10,LL-37,29402723\n10,LL-37,31046155\n10,LL-37,31264287\n10,LL-37,31330899\n10,LL-37,31797399\n10,LL-37,31848359\n10,LL-37,32291809\n10,LL-37,32799924\n10,LL-37,32867053\n10,LL-37,33620550\n10,LL-37,33678493\n10,LL-37,33966252\n10,LL-37,34102559\n10,LL-37,34374425\n10,LL-37,34687253\n10,LL-37,36329435\n10,LL-37,37276169\n10,LL-37,37480520\n10,LL-37,37605995\n10,LL-37,37708314\n10,LL-37,38483248\n10,LL-37,38706151\n10,LL-37,39097930\n10,LL-37,39155711\n10,LL-37,39181322\n10,LL-37,39838042\n10,LL-37,39940396\n10,LL-37,40581810\n10,LL-37,40810749\n10,LL-37,40853451\n10,LL-37,41299581\n10,LL-37,41655688\n10,LL-37,41953980\n10,LL-37,42118446\n10,LL-37,42598364\n10,LL-37,42685028\n```\n\n## Acceptance Criteria\n\n1. **Schema.** `evidence.csv` has exactly the header above; every `peptide`\n   value is in `peptides.csv`; every `evidence_level` is one of the five\n   values; no two rows share the same `peptide` and `pmid`. The header is not\n   a data row.\n2. **Coverage per peptide.** Each of the 10 peptides has at least 10 rows,\n   of which at least 5 have an `evidence_level` other than `review_only`.\n   These minimums come from PubMed counts the Poster ran on 9 November 2026:\n   every peptide had at least 65 PubMed records matching its names that are\n   not indexed as reviews (selank, the smallest, had 68 records in total).\n3. **Spot check.** B is the `randomness` value, in lowercase hex, of the\n   first `quicknet` round whose scheduled time is at or after\n   `submission_deadline`: round = ceil((submission_deadline − 1692803367) ÷\n   3) + 1 = 34253792. No other round's value is B. With R data rows in\n   `evidence.csv`, numbered from 1 in file order after the header, 20\n   distinct rows are checked. For j = 1, 2, 3 and so on, n is the first 12\n   hex digits of the SHA-256 of the text `B:row:j`, read as a hexadecimal\n   number, and row (n mod R) + 1 is picked. A row already picked is skipped.\n   Picking stops at 20 distinct rows. A checked row is correct when its PubMed\n   record is qualifying for its `peptide` and every column matches that record\n   under the rules in Deliverables: `doi`, `publication_year`,\n   `evidence_level`, `species_or_system`, `sample_size`, and a\n   `primary_outcome_as_stated` quote found at `section_or_page`. At most 1 of\n   the 20 checked rows may be incorrect.\n4. **Completeness check.** 3 distinct peptides are checked, drawn only from\n   the 7 peptides with at least 3 PMIDs in the completeness snapshot. For this\n   check they are numbered 1 thymosin beta-4, 2 GHK, 3 semax, 4 selank,\n   5 MOTS-c, 6 elamipretide and 7 LL-37. For j = 1, 2, 3 and so on, n is the\n   first 12 hex digits of the SHA-256 of the text `B:peptide:j`, read as a\n   hexadecimal number, and peptide (n mod 7) + 1 of that numbering is picked.\n   A peptide already picked is skipped. Picking stops at 3 distinct peptides.\n   Every snapshot PMID of a checked peptide is either a row of `evidence.csv`\n   for that peptide, or listed in `provenance.md` for that peptide with a\n   reason code that holds for that record. A snapshot PMID that is qualifying\n   but only listed in `provenance.md`, or not qualifying but only listed as a\n   row, counts as missing. At most 1 snapshot PMID may be missing across the 3\n   checked peptides.\n\n## How is the winner selected?\n- Valid Submissions are those meeting every acceptance criterion and no\n  disqualification condition.\n- The valid Submission with the lowest `submission_call_count` wins:\n  ElgoraHub's bounty-wide count of accepted submissions at that call, so the\n  earliest active valid Submission wins. Resubmitting replaces the active\n  Submission and gives it a later count. The number of rows does not rank.\n- If none is valid, the outcome is `no_valid_submission`.\n\n## Disqualification Conditions\n- A submitted file states a dose, concentration, amount, route of\n  administration, schedule, source of supply, or any instruction or\n  recommendation for using a peptide. Quotes in `primary_outcome_as_stated`\n  must omit such details with `...`.\n- A submitted file states, in the Solver's own words, that a peptide is\n  effective, safe or suitable for any use. Classifying a record's study type\n  is not such a claim, and a verbatim PubMed quote in\n  `primary_outcome_as_stated` is attributed to its source, not to the Solver.\n\n## Out Of Scope\n- Medical advice, and any claim about efficacy, safety or appropriate use of\n  any peptide. The dataset classifies publications only.\n- Dosing, routes of administration, protocols, product sources and any\n  instructions for use.\n- Full-text reading, risk-of-bias or quality grading, and judging whether\n  study results are scientifically correct.\n- Records outside PubMed, and preprints not indexed in PubMed.\n\n## Evaluation Procedure\nCorrectness is decided only on the 20 checked rows, by comparing each with its\nPubMed record as displayed on PubMed. Completeness is decided only on the 3\nchecked peptides, by comparing their snapshot PMIDs with `evidence.csv` and\n`provenance.md`. Coverage and schema are decided on the whole of\n`evidence.csv`.\n","verification_record":null,"verification_record_error":null}