{"id":"W4393769898","doi":"10.5281/zenodo.10124594","title":"Tensile2d: 2D quasistatic non-linear structural mechanics solutions, under geometrical variations","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Structural Analysis and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Quasistatic process; Classical mechanics; Mathematics; Statistical physics; Mechanics; Mathematical analysis; Physics; Thermodynamics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003862344,0.0003418152,0.0003774632,0.0009530252,0.001958401,0.0006659692,0.0009649091,0.0002606009,0.005638584],"category_scores_gemma":[0.0006319084,0.0003463301,0.000146242,0.00229763,0.00006094576,0.0002110943,0.0007164987,0.0006284303,0.01331281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003211589,"about_ca_system_score_gemma":0.000007227469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009752855,"about_ca_topic_score_gemma":0.000005045923,"domain_scores_codex":[0.9976538,0.0001651838,0.0005276779,0.0004945248,0.0006018296,0.0005570178],"domain_scores_gemma":[0.9983187,0.00006547706,0.0001461164,0.0006646713,0.0005934694,0.0002115231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006068316,0.00001478323,3.454714e-8,0.0001103711,0.0001831421,0.000007219778,0.00003903659,0.08211682,0.00006387081,0.0004008653,0.9152506,0.001807211],"study_design_scores_gemma":[0.0002733852,0.00006437303,0.0001007863,0.00003450035,0.0001753885,0.00004100232,0.0001055732,0.2487382,0.000006287533,0.0003415327,0.7497204,0.000398611],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009617011,0.0001252128,0.05701694,0.0002256578,0.0007501407,0.0005226801,0.9391376,0.001661717,0.0004638615],"genre_scores_gemma":[0.002661974,0.0005272178,0.000647917,0.00006316217,0.000330158,1.565601e-7,0.9943252,0.001282566,0.0001616038],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1666214,"threshold_uncertainty_score":0.9998989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03774147324368043,"score_gpt":0.2482568261300894,"score_spread":0.210515352886409,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}