You are a general-purpose AI scientist tasked with predicting experimental outcomes across scientific disciplines. Your goal is to produce the most accurate, scientifically grounded predictions possible from the information provided and any permitted information you can obtain. For this task, predict only the ordering of experimental outcomes within each specified comparison group. Absolute outcome values are not required.
You may use all computational tools and search resources available in your environment, including web search, scientific literature, databases, code execution, statistical modeling, machine learning, and numerical simulation. Select and combine methods appropriate to the task, and actively perform calculations when they can improve your predictions. Proactively check the available CPUs, GPUs, and software, and identify key prediction problems they could help address; whether to use a GPU should depend on the suitability of the method. For scientifically grounded methods that may be useful but whose benefits are uncertain, prioritize small-scale trial calculations before deciding whether to expand the computation. You may download any software, code, models, and data you consider necessary from the internet, subject to the following restrictions: do not search for, access, or use the original study, its supplementary materials, or data that can directly reveal the experimental results, and do not use the results of the target experiments or experiments of the same type.
Ground your analysis in the experimental setup, measurement definitions, controls, and relevant scientific mechanisms. Gather supporting evidence from permitted sources, assess its applicability to the specific experiments, and evaluate alternative explanations. Check assumptions, units, and consistency, and refine your predictions as new permitted evidence becomes available. Use general scientific knowledge to make new predictions. Do not retrieve, reconstruct, or use specific experimental results or rankings from your model memory or training data. After forming an initial ranking, continue to look for and actually try methods that could improve key judgments within the time budget, prioritizing resources for the most uncertain comparisons.
Clearly distinguish experimental observations, computational results, and scientific inference. Assess uncertainty and methodological limitations. Do not fabricate sources, data, tool outputs, or calculations, and do not present computational proxies as experimentally measured values.
Follow the task-specific instructions and output format exactly. When explanations are permitted, provide a concise summary of your methods, key computational results, and supporting rationale. Keep supporting analysis separate from any final submission that requires a restricted format.
You have a strict time limit of 8 hours (28,800 seconds). Submit the required files before the deadline.
Pull-off adhesion of additional six-monomer hydrogel formulations
Prediction question
Hydrogels with varied neutral, polar, charged and aromatic monomer feed proportions are prepared by one common photopolymerization and solvent-exchange protocol. Predict their mean normal pull-off strengths against glass while immersed in physiological-concentration saline.
Rank each comparison group from lowest to highest using that group's specified endpoint and unit. Submit rankings only; absolute values are not required.
Experimental definition
Read /workspace/public/experiment.md, protocol.json and targets.csv. The common conditions in protocol.json apply to every item unless that item's setting explicitly overrides the same field. Expand both parts together. Public sequences, structures and other supplied assets are part of the definition. Do not obtain missing details from the prohibited original study.
Use the stated feed proportions, photopolymerization and saline-equilibration process. Perform the common submerged10 N,10 s tack test against glass with a15 mm specimen, and rank the reported mean peak-detachment stress across formulations.
Outcome definitions by group:
g1— reported mean normal pull-off adhesive strength (kPa): Fa_ave, the reported mean normal pull-off adhesive strength from the specified tack protocol, read directly from the original formulation workbooks. It is not Fa_max, the largest value selected among repeated tests for model training. For items explicitly marked as two-summary records, the ranking target is the descriptive arithmetic mean of their two reported central summaries; the underlying samples are not assumed independent or disjoint.
Comparison groups
g1: Additional formulations under one saline-glass tack protocol; 271 items; weight 1.0; ascending reported mean normal pull-off adhesive strength (kPa).
Allowed and prohibited information
The original study, all its supplementary materials (including methods), source data, related reporting, summaries, mirrors and caches are prohibited. The same restriction covers external values, rankings, qualitative comparisons, equivalent endpoints and predictors fitted to target or same-type experimental results. Measured pull-off adhesion, formulation rankings, optimized recipes and experimental or fitted adhesion outcomes for copolymer hydrogels containing these six functional monomers in saline against glass are prohibited.
Allowed examples:
- General copolymerization, network swelling and polymer interfacial interactions.
- Chemical identities and basic physicochemical properties of the input monomers independent of hydrogel adhesion measurements.
Forbidden examples:
- Adhesion tables or rankings for these six-monomer hydrogel formulations.
- Predictors trained on their experimental pull-off strength.
Use audited tools for all searches, downloads and code-initiated network requests. Check both requests and returned content before use. Do not circumvent access controls or ask another model/service for forbidden results. If a permitted query unexpectedly exposes prohibited external results, immediately stop prediction and further search; record only the triggering step, source and stopping reason in report.md without restating results. Do not retrieve or reconstruct specific experimental results from your own model memory; briefly disclose a noticed recollection in your report and continue using permitted inputs and reasoning.
Tools, resources and deadline
You have 8 CPU cores, 16,384 MiB system RAM and one NVIDIA H20 GPU, shared by all local processes. Remote model APIs, databases and services do not consume the local compute quota; their calls and waits consume the same 28,800-second wall-clock budget. Record service identity, requests and usage. All compute and network activity must follow the information policy. The 8-hour clock starts at first delivery of the task inputs; retries do not reset it.
Submission
Write UTF-8 JSON to /logs/artifacts/rankings.json (at most 1 MiB, unique object keys). Include the exact task identity and exactly one entry per group; each order must contain every assigned item once, from lowest to highest. The following is a format example in public display order, not a predicted answer:
{
"task_id": "hydrogel-additional-formulation-adhesion",
"task_version": "1.0.0",
"rankings": [
{
"group_id": "g1",
"order": [
"exp_6804ee59325d",
"exp_dcf861599698",
"exp_f7f06396eb7e",
"exp_7fe19795658c",
"exp_95b3ebd396a2",
"exp_869f37b38dec",
"exp_ff7e84109b19",
"exp_647ddc57268b",
"exp_e2a79c506a31",
"exp_1f44e27b2ed4",
"exp_6f5b07ab1c21",
"exp_1ecea68f432e",
"exp_34d656c5e166",
"exp_cb395fa5eae5",
"exp_cba708a54ed4",
"exp_9727c3fe8adf",
"exp_4bb6ff8fd628",
"exp_0995a53afd45",
"exp_90b6a2425025",
"exp_f333c804582c",
"exp_72898e991286",
"exp_743e5a62f446",
"exp_047eb0bd93a1",
"exp_7aacd90745f0",
"exp_316cd63f2e87",
"exp_8bcc34da4727",
"exp_84b84d3272fa",
"exp_e8f213fb93c0",
"exp_27e9e9016fc2",
"exp_57a803619fd9",
"exp_58880e4773b6",
"exp_d7c0bea44280",
"exp_e44fde53bf78",
"exp_98ae173c6e1a",
"exp_5e6aaef95eb6",
"exp_20aa8f0cfdf7",
"exp_ccf1189db4bc",
"exp_8a0d3916775d",
"exp_e4f01e9ac827",
"exp_d906339bb77f",
"exp_5f0625844799",
"exp_90b028667e66",
"exp_1a0b968cf3c5",
"exp_d017049f5dbf",
"exp_3a2277a31a68",
"exp_180a362a3bf9",
"exp_4f6492ac0e2b",
"exp_892af10fb0a0",
"exp_33a3388dcd8d",
"exp_bc1b948cc1ad",
"exp_a093b1416490",
"exp_b2f50bdee8ef",
"exp_4ae78dd4ae26",
"exp_4e499a3857c8",
"exp_28f22e8d5502",
"exp_ae0c1c946ba2",
"exp_7dddaf3b4353",
"exp_1d0dcfe8d379",
"exp_f55f404deefe",
"exp_7c5f89f143e4",
"exp_94578e81d8a0",
"exp_0ac531d290aa",
"exp_a66bbd17edd9",
"exp_f464b17dc0fa",
"exp_fdfe60da3d16",
"exp_23f0c28cf63a",
"exp_654ea5f673af",
"exp_b0f95decc922",
"exp_c050862543b1",
"exp_1575abda79e4",
"exp_035aeaec2de4",
"exp_a97b4609fd5d",
"exp_455d5af6aa5a",
"exp_9d66aac7398a",
"exp_46474e87d72c",
"exp_52ca78a2133d",
"exp_3e65ea977936",
"exp_b02b0c16cb48",
"exp_b8da68158cc2",
"exp_a6e3ec38c6a0",
"exp_1ca05130381c",
"exp_28fbac44bca9",
"exp_ea475ca42ca9",
"exp_d79bee8c75b9",
"exp_98b2f0061db4",
"exp_cc93a9cff409",
"exp_ae186d0f1cd7",
"exp_d135151d0a58",
"exp_88a128155bfc",
"exp_a72d2352b8bb",
"exp_05eea4cf2154",
"exp_5603041b4670",
"exp_90393ba5bc3d",
"exp_dea65d6de50a",
"exp_45920467b50c",
"exp_afcea84eca50",
"exp_83cacbbc0e7a",
"exp_b94bdc3577d7",
"exp_3533cf1456e4",
"exp_d968a5e9882a",
"exp_a2fbb2b21fae",
"exp_66883603c639",
"exp_f4820fd26a5b",
"exp_3ff375dfb2c3",
"exp_e21544c9c1d9",
"exp_10242487e1aa",
"exp_8811bda5ae53",
"exp_989680d757fe",
"exp_ab5fb5e804b9",
"exp_69b79bc6d346",
"exp_75e6f1a7f788",
"exp_f0c29eb6a11c",
"exp_536be5f61860",
"exp_ccdc0f654738",
"exp_80ed5de849f1",
"exp_a2824dc91f34",
"exp_af75827bc605",
"exp_bc4912b37165",
"exp_198cac99b82c",
"exp_28ee423543ac",
"exp_a25503360924",
"exp_fffff7ca2ebd",
"exp_fb5e9364511f",
"exp_9f1a06e139a0",
"exp_7db9a8037cea",
"exp_a822581fe77d",
"exp_77b1c2325aa3",
"exp_3cab19bd4b5d",
"exp_91d9d371d716",
"exp_63e7d3e53c52",
"exp_219e9076acc5",
"exp_c520be306212",
"exp_ad84c2fb0e0a",
"exp_b060a3076376",
"exp_395b6c0f8189",
"exp_66fbe7ba3df9",
"exp_14619730e126",
"exp_bb432f302bff",
"exp_e400a3b9af63",
"exp_6ff3c01579ec",
"exp_25b01ffcf76f",
"exp_6302f9293cb0",
"exp_ca0be88a011a",
"exp_b3a881a05492",
"exp_0c69d961e048",
"exp_fa4d42ee7b56",
"exp_c680afbaa6b2",
"exp_27299fbdb8f7",
"exp_43e68d66b2e6",
"exp_a22ee2fa903f",
"exp_b7c4ad9f5a54",
"exp_6431f784872f",
"exp_2bf0fab4eef0",
"exp_19920863e0f7",
"exp_fc8e20bb395a",
"exp_a92c1c37d03f",
"exp_dc9c1a75ca89",
"exp_5ec404972d54",
"exp_aa711b6a3714",
"exp_511c11fa949b",
"exp_e51f6240afcb",
"exp_159644421a7b",
"exp_0fd57d9c2cda",
"exp_469486363893",
"exp_3db6158d4ca4",
"exp_ff7dbed373fc",
"exp_b9808d3f4c47",
"exp_f88a75bc0b4d",
"exp_35bd39e6b083",
"exp_dbe0cfa3e6db",
"exp_347c29d94daf",
"exp_fb8215d01adb",
"exp_31a9e398c761",
"exp_d3dced279aff",
"exp_de71f0839e81",
"exp_64c602434925",
"exp_a7886913722c",
"exp_43b64ffe1f1a",
"exp_16e4902880e9",
"exp_7e972eeba684",
"exp_e3b29ddcee07",
"exp_dfee91c8221d",
"exp_a336ef444353",
"exp_162ce8509ceb",
"exp_50b597511b78",
"exp_709423f83bbc",
"exp_895554824cbe",
"exp_76e897dd18a4",
"exp_42bbf3c26f48",
"exp_c878f32a1590",
"exp_aad258c21b50",
"exp_f9c56273320a",
"exp_fc70877ec551",
"exp_1ca7700ea390",
"exp_5018708ecbb1",
"exp_bca1606ac0fa",
"exp_714ec4c05cb4",
"exp_100505370691",
"exp_48de3919ca2b",
"exp_30e3cf3f70c7",
"exp_45a4e04e92ec",
"exp_447354672216",
"exp_74c3d25929b2",
"exp_5b1a50722814",
"exp_5147c72753b8",
"exp_545d71f40f35",
"exp_511f125f7637",
"exp_de1ea1056500",
"exp_6ceb96043a5c",
"exp_3408d887d424",
"exp_cbb7bb44ef3f",
"exp_33cd59d917b1",
"exp_9e2a2f251941",
"exp_dc69b901092c",
"exp_c03c0693cbe8",
"exp_b8b7208e5718",
"exp_f6c7359accfa",
"exp_3041152fcd76",
"exp_8cc15fa57c7d",
"exp_1a31a659ab97",
"exp_6448bad840e1",
"exp_4e8816a0e1e2",
"exp_ddef4e556fd6",
"exp_fdc902eb232b",
"exp_2596e8c53350",
"exp_eba9f39bac42",
"exp_039749d32b63",
"exp_dcfea09aa8ba",
"exp_1c2e9e659828",
"exp_28c53010b4fc",
"exp_de168a210b7d",
"exp_8f7ca0f5bdc9",
"exp_e84d19154614",
"exp_03ba6952bc90",
"exp_4f62f23d8cc4",
"exp_dbc33c5afd5e",
"exp_55f4726e01bc",
"exp_c611b49629ea",
"exp_5f809cda4deb",
"exp_4dca8fbbfbac",
"exp_45588ba0524c",
"exp_f5615e1cd6a6",
"exp_507c6817bddb",
"exp_dd0d30e9e159",
"exp_f792554549db",
"exp_5c028c6eb7b6",
"exp_f4225cf7314d",
"exp_12f9225a62e5",
"exp_83744f5ad07e",
"exp_f0b81c853611",
"exp_f3fee0c5af3d",
"exp_4e1afdf33cd8",
"exp_a4f89b766469",
"exp_6185965fb07e",
"exp_d212a4108a95",
"exp_558827f2032b",
"exp_6389e9fca5f9",
"exp_799426e53b6c",
"exp_d8ad8bdbd1ea",
"exp_d43b29586fe2",
"exp_66471bf57c9f",
"exp_ccf74d3a07c9",
"exp_697a66365678",
"exp_9a84a424251a",
"exp_1eb8ea1cab1b",
"exp_2ded1acdd71c",
"exp_8dd3a0f3a26b",
"exp_8cea00915a0b",
"exp_ddd446683115",
"exp_cc6893ea31f7",
"exp_c3148198ef1d"
]
}
]
}
Write an English account of scientific reasoning, calculations, assumptions and uncertainty to /logs/artifacts/report.md; source records to /logs/artifacts/sources.json; supporting scripts and calculations to /logs/artifacts/analysis/. The evaluator uses the last submission received before the deadline. Empty or missing submissions receive core -1 and auxiliary 0.
Ranking scores
The primary score is standard Spearman rank correlation, from -1 to 1, computed separately in each group and combined with fixed group weights. Equal measured values receive average true ranks; predictions remain strict permutations. Correct/reverse rankings score 1/-1 when true values have no ties; with true ties the best strict ranking can score less than 1. Random complete rankings have expected correlation 0.
The auxiliary score counts each decidable pair equally within its group, combines group accuracies using the same weights, then applies one whole-task random 95th-percentile threshold. Known uncertainty uses the declared difference-error rule; unknown uncertainty uses reported values with epsilon and does not exclude unequal results. The threshold is hidden. Core and auxiliary scores are recorded separately; neither meaning of zero proves the absence of predictive ability. Detailed algorithms and all format penalties are in the following authoritative public contract, from which the companion files are generated.
{
"task_id": "hydrogel-additional-formulation-adhesion",
"task_version": "1.0.0",
"groups": [
{
"group_id": "g1",
"label": "Additional formulations under one saline-glass tack protocol",
"item_ids": [
"exp_6804ee59325d",
"exp_dcf861599698",
"exp_f7f06396eb7e",
"exp_7fe19795658c",
"exp_95b3ebd396a2",
"exp_869f37b38dec",
"exp_ff7e84109b19",
"exp_647ddc57268b",
"exp_e2a79c506a31",
"exp_1f44e27b2ed4",
"exp_6f5b07ab1c21",
"exp_1ecea68f432e",
"exp_34d656c5e166",
"exp_cb395fa5eae5",
"exp_cba708a54ed4",
"exp_9727c3fe8adf",
"exp_4bb6ff8fd628",
"exp_0995a53afd45",
"exp_90b6a2425025",
"exp_f333c804582c",
"exp_72898e991286",
"exp_743e5a62f446",
"exp_047eb0bd93a1",
"exp_7aacd90745f0",
"exp_316cd63f2e87",
"exp_8bcc34da4727",
"exp_84b84d3272fa",
"exp_e8f213fb93c0",
"exp_27e9e9016fc2",
"exp_57a803619fd9",
"exp_58880e4773b6",
"exp_d7c0bea44280",
"exp_e44fde53bf78",
"exp_98ae173c6e1a",
"exp_5e6aaef95eb6",
"exp_20aa8f0cfdf7",
"exp_ccf1189db4bc",
"exp_8a0d3916775d",
"exp_e4f01e9ac827",
"exp_d906339bb77f",
"exp_5f0625844799",
"exp_90b028667e66",
"exp_1a0b968cf3c5",
"exp_d017049f5dbf",
"exp_3a2277a31a68",
"exp_180a362a3bf9",
"exp_4f6492ac0e2b",
"exp_892af10fb0a0",
"exp_33a3388dcd8d",
"exp_bc1b948cc1ad",
"exp_a093b1416490",
"exp_b2f50bdee8ef",
"exp_4ae78dd4ae26",
"exp_4e499a3857c8",
"exp_28f22e8d5502",
"exp_ae0c1c946ba2",
"exp_7dddaf3b4353",
"exp_1d0dcfe8d379",
"exp_f55f404deefe",
"exp_7c5f89f143e4",
"exp_94578e81d8a0",
"exp_0ac531d290aa",
"exp_a66bbd17edd9",
"exp_f464b17dc0fa",
"exp_fdfe60da3d16",
"exp_23f0c28cf63a",
"exp_654ea5f673af",
"exp_b0f95decc922",
"exp_c050862543b1",
"exp_1575abda79e4",
"exp_035aeaec2de4",
"exp_a97b4609fd5d",
"exp_455d5af6aa5a",
"exp_9d66aac7398a",
"exp_46474e87d72c",
"exp_52ca78a2133d",
"exp_3e65ea977936",
"exp_b02b0c16cb48",
"exp_b8da68158cc2",
"exp_a6e3ec38c6a0",
"exp_1ca05130381c",
"exp_28fbac44bca9",
"exp_ea475ca42ca9",
"exp_d79bee8c75b9",
"exp_98b2f0061db4",
"exp_cc93a9cff409",
"exp_ae186d0f1cd7",
"exp_d135151d0a58",
"exp_88a128155bfc",
"exp_a72d2352b8bb",
"exp_05eea4cf2154",
"exp_5603041b4670",
"exp_90393ba5bc3d",
"exp_dea65d6de50a",
"exp_45920467b50c",
"exp_afcea84eca50",
"exp_83cacbbc0e7a",
"exp_b94bdc3577d7",
"exp_3533cf1456e4",
"exp_d968a5e9882a",
"exp_a2fbb2b21fae",
"exp_66883603c639",
"exp_f4820fd26a5b",
"exp_3ff375dfb2c3",
"exp_e21544c9c1d9",
"exp_10242487e1aa",
"exp_8811bda5ae53",
"exp_989680d757fe",
"exp_ab5fb5e804b9",
"exp_69b79bc6d346",
"exp_75e6f1a7f788",
"exp_f0c29eb6a11c",
"exp_536be5f61860",
"exp_ccdc0f654738",
"exp_80ed5de849f1",
"exp_a2824dc91f34",
"exp_af75827bc605",
"exp_bc4912b37165",
"exp_198cac99b82c",
"exp_28ee423543ac",
"exp_a25503360924",
"exp_fffff7ca2ebd",
"exp_fb5e9364511f",
"exp_9f1a06e139a0",
"exp_7db9a8037cea",
"exp_a822581fe77d",
"exp_77b1c2325aa3",
"exp_3cab19bd4b5d",
"exp_91d9d371d716",
"exp_63e7d3e53c52",
"exp_219e9076acc5",
"exp_c520be306212",
"exp_ad84c2fb0e0a",
"exp_b060a3076376",
"exp_395b6c0f8189",
"exp_66fbe7ba3df9",
"exp_14619730e126",
"exp_bb432f302bff",
"exp_e400a3b9af63",
"exp_6ff3c01579ec",
"exp_25b01ffcf76f",
"exp_6302f9293cb0",
"exp_ca0be88a011a",
"exp_b3a881a05492",
"exp_0c69d961e048",
"exp_fa4d42ee7b56",
"exp_c680afbaa6b2",
"exp_27299fbdb8f7",
"exp_43e68d66b2e6",
"exp_a22ee2fa903f",
"exp_b7c4ad9f5a54",
"exp_6431f784872f",
"exp_2bf0fab4eef0",
"exp_19920863e0f7",
"exp_fc8e20bb395a",
"exp_a92c1c37d03f",
"exp_dc9c1a75ca89",
"exp_5ec404972d54",
"exp_aa711b6a3714",
"exp_511c11fa949b",
"exp_e51f6240afcb",
"exp_159644421a7b",
"exp_0fd57d9c2cda",
"exp_469486363893",
"exp_3db6158d4ca4",
"exp_ff7dbed373fc",
"exp_b9808d3f4c47",
"exp_f88a75bc0b4d",
"exp_35bd39e6b083",
"exp_dbe0cfa3e6db",
"exp_347c29d94daf",
"exp_fb8215d01adb",
"exp_31a9e398c761",
"exp_d3dced279aff",
"exp_de71f0839e81",
"exp_64c602434925",
"exp_a7886913722c",
"exp_43b64ffe1f1a",
"exp_16e4902880e9",
"exp_7e972eeba684",
"exp_e3b29ddcee07",
"exp_dfee91c8221d",
"exp_a336ef444353",
"exp_162ce8509ceb",
"exp_50b597511b78",
"exp_709423f83bbc",
"exp_895554824cbe",
"exp_76e897dd18a4",
"exp_42bbf3c26f48",
"exp_c878f32a1590",
"exp_aad258c21b50",
"exp_f9c56273320a",
"exp_fc70877ec551",
"exp_1ca7700ea390",
"exp_5018708ecbb1",
"exp_bca1606ac0fa",
"exp_714ec4c05cb4",
"exp_100505370691",
"exp_48de3919ca2b",
"exp_30e3cf3f70c7",
"exp_45a4e04e92ec",
"exp_447354672216",
"exp_74c3d25929b2",
"exp_5b1a50722814",
"exp_5147c72753b8",
"exp_545d71f40f35",
"exp_511f125f7637",
"exp_de1ea1056500",
"exp_6ceb96043a5c",
"exp_3408d887d424",
"exp_cbb7bb44ef3f",
"exp_33cd59d917b1",
"exp_9e2a2f251941",
"exp_dc69b901092c",
"exp_c03c0693cbe8",
"exp_b8b7208e5718",
"exp_f6c7359accfa",
"exp_3041152fcd76",
"exp_8cc15fa57c7d",
"exp_1a31a659ab97",
"exp_6448bad840e1",
"exp_4e8816a0e1e2",
"exp_ddef4e556fd6",
"exp_fdc902eb232b",
"exp_2596e8c53350",
"exp_eba9f39bac42",
"exp_039749d32b63",
"exp_dcfea09aa8ba",
"exp_1c2e9e659828",
"exp_28c53010b4fc",
"exp_de168a210b7d",
"exp_8f7ca0f5bdc9",
"exp_e84d19154614",
"exp_03ba6952bc90",
"exp_4f62f23d8cc4",
"exp_dbc33c5afd5e",
"exp_55f4726e01bc",
"exp_c611b49629ea",
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"exp_4dca8fbbfbac",
"exp_45588ba0524c",
"exp_f5615e1cd6a6",
"exp_507c6817bddb",
"exp_dd0d30e9e159",
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"exp_f0b81c853611",
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"exp_6185965fb07e",
"exp_d212a4108a95",
"exp_558827f2032b",
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"exp_799426e53b6c",
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"exp_d43b29586fe2",
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"exp_697a66365678",
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"exp_ddd446683115",
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],
"direction": "ascending",
"group_weight": 1.0,
"k": 2,
"epsilon": 0,
"uncertainty_model": "optional_reported_uncertainty",
"difference_standard_error": "sem_sum_upper_bound",
"endpoint": {
"name": "reported mean normal pull-off adhesive strength",
"unit": "kPa",
"definition_en": "Fa_ave, the reported mean normal pull-off adhesive strength from the specified tack protocol, read directly from the original formulation workbooks. It is not Fa_max, the largest value selected among repeated tests for model training. For items explicitly marked as two-summary records, the ranking target is the descriptive arithmetic mean of their two reported central summaries; the underlying samples are not assumed independent or disjoint."
}
}
],
"scoring_method": "spearman",
"primary_score": "task_spearman",
"spearman_range": [
-1,
1
],
"spearman_tie_method": "average",
"spearman_undefined_policy": "task_error",
"spearman_aggregation": "Pearson correlation of true average ranks and submitted positions, separately within each group, then fixed group-weighted sum; do not pool groups or clip negative groups.",
"secondary_scoring_method": "equal_pair_inversion_random95",
"ranking_reward_range": [
0,
1
],
"random_quantile": 0.95,
"unknown_uncertainty_policy": "use_reported_value",
"pair_rule": "For each unordered pair, count it iff abs(mu_i-mu_j)>k*s_ij+epsilon for known uncertainty, or >epsilon for unknown uncertainty. Each counted pair has equal weight within its group. Unknown uncertainty is not zero uncertainty.",
"ranking_reward_formula": "Validate finite 0.5<=q<1 and 0<=A<=1; if A==1 return 1; else if A<=q+1e-12 return 0; otherwise clamp((A-q)/(1-q),0,1). A is the fixed weighted sum of group pair accuracies; q is the whole-task random 95th percentile.",
"format_errors": {
"whole_task": "Core=-1; auxiliary=0 for malformed/oversized/non-UTF8 JSON, duplicate object keys, wrong/missing identity, invalid top-level/rankings, unknown or unassignable group.",
"known_group": "Missing/duplicate known group or invalid item permutation: raw group Spearman=null, aggregation value=-1, group pair accuracy=0; preserve group weight and apply auxiliary threshold after aggregation."
},
"max_submission_bytes": 1048576,
"minimum_conditions_per_group": 2,
"time_limit_sec": 28800,
"solver_resources": {
"cpus": 8,
"memory_mb": 16384,
"gpus": 1,
"gpu_types": [
"H20"
]
},
"submission_path": "/logs/artifacts/rankings.json",
"report_path": "/logs/artifacts/report.md",
"sources_path": "/logs/artifacts/sources.json",
"analysis_path": "/logs/artifacts/analysis/",
"forbidden_result_scope": "Measured pull-off adhesion, formulation rankings, optimized recipes and experimental or fitted adhesion outcomes for copolymer hydrogels containing these six functional monomers in saline against glass are prohibited."
}