{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":17,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":17,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"1d579b4f1f06","filters":{"venue":"Journal of Mechanical Engineering"}},"results":[{"id":"W2515449754","doi":"10.3901/jme.2016.14.079","title":"Discuss on Approximate Optimization Strategies Using Design of Computer Experiments and Metamodels for Flight Vehicle Design","year":2016,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Education and Child Care; Simon Fraser University","funders":"","keywords":"Computer science; Design of experiments; Computer experiment; Simulation; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.03737155520179079,"gpt":0.2508192529536036,"spread":0.2134476977518128,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002790175,0.0001043718,0.0001945464,0.00004941048,0.00002749794,0.00001444315,0.0001248463,0.00005741306,0.00001315267],"category_scores_gemma":[0.00003969464,0.0000625759,0.00004307201,0.00006293226,0.00002866186,0.0003639415,0.00004722086,0.00005584071,3.177201e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006225097,"about_ca_system_score_gemma":0.000006489326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.82616e-7,"about_ca_topic_score_gemma":1.70111e-8,"domain_scores_codex":[0.9993069,0.00002195258,0.0002614618,0.0001114586,0.0001571385,0.0001410962],"domain_scores_gemma":[0.9995615,0.0001565655,0.0001403074,0.00008065193,0.00001434452,0.0000466238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003760271,0.00002112174,9.620428e-7,0.000004642386,0.00001140956,0.000001403357,0.00001216689,0.6297969,0.3677444,0.0005928394,0.000003592525,0.001772895],"study_design_scores_gemma":[0.0004057625,0.0003156957,0.000003282672,0.00006607011,0.00001233464,0.000008393753,0.00001978576,0.726484,0.2708628,0.001746683,0.000005563787,0.00006965661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01257783,0.00003492583,0.9870957,0.00004877937,0.00006565296,0.000152464,9.939693e-7,0.00002145841,0.000002225931],"genre_scores_gemma":[0.4749469,0.00001978511,0.5250018,0.000005110768,0.00001280849,0.000002869982,3.872286e-8,0.000008935092,0.000001798336],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.462369,"threshold_uncertainty_score":0.2551771,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2621621247","doi":"10.3329/jme.v46i1.32520","title":"Non-Revenue Water (NRW) is a challenge for Global Water Supply System Management: A case study of Dhaka Water Supply System Management","year":2017,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Sewerage; Non-revenue water; Water supply; Business; Revenue; Water industry; Government (linguistics); Water resource management; Sanitation; Potable water; Environmental planning; Finance; Natural resource economics; Environmental engineering; Water resources; Water conservation; Engineering; Environmental science; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.01075794180397772,"gpt":0.215936016081646,"spread":0.2051780742776683,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008393251,0.0003861099,0.0007639187,0.0001985559,0.0001686335,0.0001730383,0.0005662916,0.0001591278,0.0000130372],"category_scores_gemma":[0.000002795177,0.0002431911,0.0002692643,0.00004139169,0.000008034808,0.0003611669,0.0002411227,0.0001995181,0.00001572929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003319368,"about_ca_system_score_gemma":0.000003246155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005561396,"about_ca_topic_score_gemma":0.00003587967,"domain_scores_codex":[0.9974629,0.00002676402,0.001149956,0.0002768015,0.0004553228,0.0006282934],"domain_scores_gemma":[0.998869,0.00001022501,0.000156792,0.0006278304,0.0001487447,0.0001873864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004935978,0.0009503401,0.0001804065,0.04878905,0.007884128,0.02795747,0.01392148,0.8815028,0.009363038,0.003559616,0.002275801,0.003122281],"study_design_scores_gemma":[0.01544373,0.001853901,0.0001639937,0.005513415,0.001833063,0.00718934,0.01216534,0.8681682,0.07691211,0.00005625913,0.009052551,0.001648101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8261778,0.0001421262,0.1660444,0.0001561031,0.004407922,0.002313253,0.00007961187,0.0001826847,0.0004959982],"genre_scores_gemma":[0.9968897,0.00002032284,0.002315004,0.000004065808,0.0003741458,0.0001027178,0.0000055976,0.00008747612,0.0002010258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1707118,"threshold_uncertainty_score":0.9917043,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200515333","doi":"10.15407/pmach2021.04.027","title":"Retrospective Review of a Two-Phase Mechanically Pumped Loop for Spacecraft Thermal Control Systems","year":2021,"lang":"en","type":"review","venue":"Journal of Mechanical Engineering","topic":"Rocket and propulsion systems research","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Spacecraft; Aerospace engineering; Payload (computing); Aerospace; Engineering; Mechanical engineering; Environmental science; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03940682802387865,"gpt":0.3502396585595903,"spread":0.3108328305357116,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003296082,0.000657222,0.005700919,0.0004165809,0.0000363598,0.0000683107,0.0007480989,0.0004981398,0.00009634935],"category_scores_gemma":[0.001416836,0.0005082377,0.00205012,0.0006297904,0.0000118128,0.0001563837,0.00008503808,0.001440877,0.000007143234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004193244,"about_ca_system_score_gemma":0.0003272001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002160367,"about_ca_topic_score_gemma":2.345251e-7,"domain_scores_codex":[0.9946945,0.0002890956,0.003063856,0.0003235064,0.001039781,0.0005892566],"domain_scores_gemma":[0.99641,0.0007012551,0.0009738011,0.0005328552,0.00097667,0.0004054774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005208506,0.0001555385,5.748611e-8,0.5284925,0.003406298,0.000279836,0.00001655015,0.002376927,0.003699251,0.001149119,0.001458785,0.458913],"study_design_scores_gemma":[0.003454031,0.0007350479,3.358145e-8,0.3983901,0.002128614,0.0009009463,0.00001538267,0.03172357,0.0004840637,0.00001456812,0.5613507,0.000803015],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000006804651,0.8711852,0.1254029,0.0000200927,0.001686061,0.001487587,0.0001176715,0.00005973125,0.00003391349],"genre_scores_gemma":[0.0004745946,0.99656,0.001454846,0.000008358353,0.001038418,0.0001760224,0.00001690093,0.000212957,0.00005791445],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5598919,"threshold_uncertainty_score":0.9997369,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4252868466","doi":"10.3901/jme.2021.22.237","title":"Research on Deep Reinforcement Learning-based Intelligent Car-following Control and Energy Management Strategy for Hybrid Electric Vehicles","year":2021,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Reinforcement learning; Energy management; Control (management); Computer science; Automotive engineering; Reinforcement; Control engineering; Engineering; Artificial intelligence; Energy (signal processing)","retraction":null,"screen_n_in":null,"score":{"opus":0.01948515240296394,"gpt":0.2591826360482493,"spread":0.2396974836452853,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007563993,0.0001836484,0.0003387728,0.0004283178,0.00008139595,0.00006686209,0.0001902889,0.00008566157,0.000005696797],"category_scores_gemma":[0.0001521886,0.0001768935,0.000165649,0.0003617087,0.000008235986,0.00007169197,0.00003271708,0.000671864,0.000001080563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002235825,"about_ca_system_score_gemma":0.00003646302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001804312,"about_ca_topic_score_gemma":7.466403e-7,"domain_scores_codex":[0.9984244,0.00003652513,0.0004593003,0.0001697865,0.0004271292,0.0004829342],"domain_scores_gemma":[0.9991108,0.0004204948,0.00005768064,0.0001412051,0.000145814,0.0001239997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004927217,0.00002527678,0.000003099437,0.0001114895,0.0001952883,0.0002335784,0.000003647272,0.9391657,0.01974638,0.008924065,0.00007928516,0.03146297],"study_design_scores_gemma":[0.0008894132,0.0006229521,0.00002008892,0.000118012,0.0000530966,0.000038531,0.00004832866,0.7899002,0.2063578,0.0003559265,0.0014412,0.0001544608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1070573,0.003262925,0.8889992,0.000120229,0.0001867976,0.0001084402,4.928984e-7,0.0001653923,0.00009925287],"genre_scores_gemma":[0.9974239,0.0008890696,0.001442426,0.00003267384,0.00009538625,0.00002511652,0.000001681989,0.00004351418,0.00004624412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8903666,"threshold_uncertainty_score":0.7213506,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3151645610","doi":"10.3901/jme.2015.01.131","title":"Planetary Gearbox Fault Diagnosis under Time-variant Conditions Based on Iterative Generalized Synchrosqueezing Transform","year":2015,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"Program for New Century Excellent Talents in University","keywords":"Fault (geology); Algorithm; Time–frequency analysis; Computer science; Applied mathematics; Mathematics; Control theory (sociology); Artificial intelligence; Geology; Computer vision; Seismology","retraction":null,"screen_n_in":null,"score":{"opus":0.01295122275532782,"gpt":0.2528054428021835,"spread":0.2398542200468557,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005511133,0.0003294785,0.0005269764,0.0003617941,0.00003833439,0.00007003915,0.0002811651,0.0001942858,0.0001728871],"category_scores_gemma":[0.0002088132,0.0002983867,0.0002153081,0.0002399915,0.00001272716,0.0002274672,0.00001731598,0.0006901824,0.0000220562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000306341,"about_ca_system_score_gemma":0.00005524667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000872741,"about_ca_topic_score_gemma":0.000003472791,"domain_scores_codex":[0.9982448,0.00005233211,0.0006782889,0.0001658153,0.0005091258,0.0003496461],"domain_scores_gemma":[0.9987956,0.000388181,0.00009921876,0.0002112904,0.0001221561,0.0003835897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003163675,0.00009527281,0.000008672577,0.00004746703,0.000123075,0.0001856119,0.00005988069,0.9848091,0.0091543,0.0009907275,0.004086614,0.0004076454],"study_design_scores_gemma":[0.001296018,0.000410084,0.00006702953,0.0004143701,0.00008160052,0.0001287134,0.00001139732,0.94857,0.04591513,0.00053039,0.002217753,0.0003575456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.217293,0.0008444493,0.7743165,0.002180119,0.001706836,0.0008171901,0.0002319542,0.001386712,0.001223276],"genre_scores_gemma":[0.9764303,0.00008574424,0.0226686,0.0003124735,0.0003209399,0.00005330996,0.00003328995,0.0000877523,0.000007602751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7591373,"threshold_uncertainty_score":0.9999468,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4251890761","doi":"10.3901/jme.2021.06.142","title":"Path Following Control for Four-wheel Drive Electric Intelligent Vehicle Based on Coordination between Steering and Direct Yaw Moment System","year":2021,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Torque steering; Electric vehicle; Moment (physics); Control (management); Automotive engineering; Motor coordination; Steering wheel; Yaw; Steering linkage; Control theory (sociology); Computer science; Engineering; Physics; Psychology; Artificial intelligence; Power (physics); Neuroscience","retraction":null,"screen_n_in":null,"score":{"opus":0.01045459809809729,"gpt":0.1990093229217987,"spread":0.1885547248237014,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008137433,0.0002032901,0.0005775275,0.0002137964,0.00006140457,0.00004429746,0.0001282094,0.0002441748,0.000001518133],"category_scores_gemma":[0.0002601944,0.000196327,0.0002271464,0.0002264114,0.000003156002,0.00009395731,0.00001361176,0.0004430495,9.840828e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000359265,"about_ca_system_score_gemma":0.00003565185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001191033,"about_ca_topic_score_gemma":3.423962e-7,"domain_scores_codex":[0.9986237,0.00004248975,0.0006044115,0.0001563293,0.0002589798,0.0003141117],"domain_scores_gemma":[0.9990571,0.0004525684,0.0001235803,0.0001364044,0.0001075723,0.0001227538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001327299,0.00005622384,0.000269887,0.0006157675,0.001077226,0.0002614267,0.00005111221,0.6815947,0.2861737,0.007181412,0.00006482056,0.02252103],"study_design_scores_gemma":[0.002353009,0.0003331186,0.00009359626,0.0006103946,0.0001737844,0.00002991478,0.00005295963,0.9357855,0.05977171,0.00002604809,0.0005703124,0.0001997019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1652587,0.0006023418,0.8322873,0.0001702584,0.001108953,0.0003243925,0.000008209752,0.0001876033,0.00005221148],"genre_scores_gemma":[0.9985394,0.000009305885,0.0009648632,0.0000138375,0.0003901527,0.0000306852,0.000001489984,0.00004297374,0.000007283824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8332807,"threshold_uncertainty_score":0.8005981,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3139602628","doi":"10.3901/jme.2013.17.110","title":"A Novel Precision-characterization Model of a Revolute Joint Based on the Concept of Spatial Mechanisms with Redundant Elastic Constraints","year":2013,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Revolute joint; Characterization (materials science); Joint (building); Computer science; Structural engineering; Artificial intelligence; Materials science; Engineering; Nanotechnology; Robot","retraction":null,"screen_n_in":null,"score":{"opus":0.02576103861854495,"gpt":0.2093095006139127,"spread":0.1835484619953678,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005631264,0.0001970618,0.0004661611,0.0002120347,0.00001790968,0.000008861877,0.0002666902,0.000171786,0.00004021217],"category_scores_gemma":[0.000888038,0.0001309522,0.0001168565,0.0001611144,0.00006131139,0.0001043459,0.0000318087,0.0004867976,8.800554e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004708667,"about_ca_system_score_gemma":0.00004558351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002618342,"about_ca_topic_score_gemma":2.46127e-7,"domain_scores_codex":[0.9987083,0.00002452079,0.0006538857,0.0001057498,0.0003046615,0.0002028981],"domain_scores_gemma":[0.9988615,0.000392167,0.0002461229,0.0002468418,0.0001845977,0.00006880242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001761273,0.00002024038,2.320478e-7,0.00003692171,0.00004163133,0.000001310737,0.00002092975,0.5012375,0.4903473,0.007285038,0.000003533537,0.0009878183],"study_design_scores_gemma":[0.0003898983,0.000292775,0.00009747367,0.0004649054,0.00003403807,0.00003163451,0.00001711322,0.71369,0.2841138,0.0007671406,0.000002508355,0.00009861111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06830598,0.00002114585,0.9309971,0.0001153721,0.0002574146,0.0001926189,0.00001542536,0.00008302186,0.00001197095],"genre_scores_gemma":[0.73272,0.0000108149,0.2671958,0.00001087097,0.00002266269,0.000009614561,0.000001023575,0.00002719742,0.000002116691],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.664414,"threshold_uncertainty_score":0.5340077,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2318096545","doi":"10.3901/jme.2014.11.060","title":"Kinematic Analysis of a New Coaxial Hybrid Mechanism","year":2014,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mechanism (biology); Kinematics; Coaxial; Physics; Mechanical engineering; Engineering; Classical mechanics","retraction":null,"screen_n_in":null,"score":{"opus":0.00697457376739413,"gpt":0.1956789091764592,"spread":0.1887043354090651,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006602241,0.0002068662,0.0008320911,0.0005473699,0.00001455372,0.00002267413,0.00030907,0.00009656648,0.0001179234],"category_scores_gemma":[0.0002742291,0.0001870051,0.0004381179,0.0005335969,0.000005127421,0.0001157137,0.00003707865,0.0003070699,0.000003885794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005662669,"about_ca_system_score_gemma":0.00002558933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004605466,"about_ca_topic_score_gemma":0.00000206798,"domain_scores_codex":[0.9982784,0.00002039693,0.0009015712,0.0001083346,0.0004301603,0.0002611627],"domain_scores_gemma":[0.9990236,0.0001568533,0.000206113,0.0002465123,0.00008910288,0.0002778098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007694774,0.0000176419,9.706807e-7,0.0000733464,0.0006495537,0.000009984529,0.00003016751,0.9061553,0.03112336,0.06049399,0.00006579777,0.001372224],"study_design_scores_gemma":[0.0004569318,0.0001523223,0.0000281966,0.0000882002,0.0008278784,0.00005128595,0.00001109829,0.9855502,0.007439964,0.005127398,0.00009046122,0.0001760476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03567731,0.00005960238,0.9632494,0.00003448793,0.0007796409,0.00005501111,0.000003035008,0.00006584589,0.00007564502],"genre_scores_gemma":[0.7697175,0.00003764073,0.2299264,0.00002033503,0.0002321308,9.586722e-7,0.000002074677,0.00004285305,0.00002021332],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7340401,"threshold_uncertainty_score":0.7625847,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2102126059","doi":"10.3329/jme.v45i1.24385","title":"DEVELOPING GROUP LEADERSHIP AND COMMUNICATION SKILLS FOR MONITORING EVM IN PROJECT MANAGEMENT","year":2015,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Earned value management; Schedule; Scope (computer science); Project management; Work (physics); Project management triangle; Warning system; Project planning; Process management; Computer science; Senior management; Engineering management; Project charter; Operations management; Business; Engineering; Systems engineering; Telecommunications; Public relations; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.2108608606408789,"gpt":0.3803848347948246,"spread":0.1695239741539457,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003964953,0.00008124806,0.0001904597,0.000505459,0.00003318767,0.0001083964,0.0003320029,0.00004067433,0.000002320909],"category_scores_gemma":[0.000688692,0.00006619015,0.00004707399,0.0004359491,0.00000928005,0.000457852,0.0001138533,0.0001601578,0.000001355585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009668456,"about_ca_system_score_gemma":0.00002516927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002481265,"about_ca_topic_score_gemma":0.000003006027,"domain_scores_codex":[0.9986474,0.00003916341,0.0005881182,0.0001138799,0.0004584971,0.0001529543],"domain_scores_gemma":[0.9991421,0.0003199156,0.0001989848,0.0001451887,0.000138399,0.00005547095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003117392,0.0001271254,0.008886272,0.000297589,0.0001506022,0.00003020146,0.00243318,0.009991302,0.0007887087,0.09464516,0.001005992,0.8813321],"study_design_scores_gemma":[0.02346783,0.001834771,0.05312973,0.005653718,0.0002631241,0.0006892259,0.05435813,0.4453606,0.01111647,0.1128241,0.2888007,0.002501635],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4268158,0.00108566,0.5685406,0.001195799,0.001495928,0.0005400781,7.785444e-7,0.00003275251,0.0002925841],"genre_scores_gemma":[0.8411123,0.0001625109,0.1584938,0.00002311915,0.0000984658,0.00001067665,2.532061e-7,0.000007780999,0.00009117358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8788305,"threshold_uncertainty_score":0.2699156,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2440724966","doi":"10.3329/jme.v45i2.28977","title":"Mathematical Modeling for Measures of Supply Chain Flexibility","year":2016,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Supply chain; Flexibility (engineering); Service management; Supply chain risk management; Linkage (software); Industrial organization; Production (economics); Business; Demand chain; Commodity; Supply chain management; Competitive advantage; Product (mathematics); Measure (data warehouse); Operations management; Risk analysis (engineering); Microeconomics; Computer science; Marketing; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.03602853096189799,"gpt":0.2438623239882651,"spread":0.2078337930263671,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001409826,0.0001291447,0.0003346483,0.000216637,0.00002958316,0.00003145956,0.0002926978,0.00006192342,0.0001422709],"category_scores_gemma":[0.0009952522,0.00007784921,0.0002302382,0.0001420207,0.00001374068,0.0004337909,0.0000810482,0.00008905937,0.00001211333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003625909,"about_ca_system_score_gemma":0.00001537353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004510824,"about_ca_topic_score_gemma":0.000001017911,"domain_scores_codex":[0.9986195,0.000005048116,0.0006343197,0.0001273624,0.0003840279,0.0002297472],"domain_scores_gemma":[0.9991656,0.0001614257,0.000237461,0.0001616616,0.0002481738,0.00002565749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008742535,0.0006434571,0.0002677423,0.002450551,0.0004186375,0.00003445159,0.00008629625,0.279486,0.1301084,0.481799,0.001365949,0.1024652],"study_design_scores_gemma":[0.001487155,0.000106291,0.00004243732,0.0006811728,0.0001233354,0.000009586962,0.0001213151,0.9529874,0.004731338,0.03448429,0.004982932,0.0002427262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1083075,0.0000826559,0.8901498,0.0008657257,0.0002598091,0.000186023,0.000001507719,0.00002733515,0.0001197133],"genre_scores_gemma":[0.9923091,0.00001954313,0.006891151,0.00006173181,0.0006441829,0.000007193329,3.056653e-7,0.00002076608,0.0000460307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8840016,"threshold_uncertainty_score":0.3174599,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4235797168","doi":"10.3901/jme.2021.22.255","title":"Improved Traffic Sign Detection Algorithm Based on Libra R-CNN","year":2021,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Sign (mathematics); Artificial intelligence; Algorithm; Pattern recognition (psychology); Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.006433507263719421,"gpt":0.1810736075888656,"spread":0.1746401003251462,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002594307,0.0001853081,0.0002850635,0.0001901433,0.00002504955,0.00005149857,0.0001037325,0.000172685,0.00007555594],"category_scores_gemma":[0.0001426821,0.0001910343,0.0001913936,0.0003023531,0.000003379311,0.0002088133,0.00001149254,0.0006356369,0.00001431345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001415919,"about_ca_system_score_gemma":0.00003502764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.559156e-7,"about_ca_topic_score_gemma":5.619175e-7,"domain_scores_codex":[0.9988697,0.00002737953,0.0004508993,0.0001253004,0.0002706249,0.0002561214],"domain_scores_gemma":[0.999323,0.0001792948,0.00007288017,0.0001329822,0.0001128983,0.0001789315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001319204,0.00003345978,6.786697e-8,0.00004238887,0.00004157912,0.0001042701,0.00000844058,0.5632475,0.291556,0.000008607059,0.00001440624,0.1449301],"study_design_scores_gemma":[0.0005550763,0.0001449406,0.00001339132,0.000112077,0.00002959918,0.0001575483,0.00001033259,0.7211468,0.277258,0.00001249243,0.0004182022,0.0001415858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.144774,0.0001556737,0.8531125,0.00007427709,0.001464615,0.00007489778,0.000005028387,0.000272563,0.00006636091],"genre_scores_gemma":[0.9705983,0.00004694832,0.02876585,0.00004201658,0.0004631051,0.000003756189,0.000002965439,0.00007030141,0.000006779635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8258242,"threshold_uncertainty_score":0.7790152,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375842599","doi":"10.3901/jme.2022.24.211","title":"Dual Attention Network for the Classification of Road Surface Conditions Based on EfficientNet","year":2022,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Dual (grammatical number); Dual purpose; Environmental science; Surface (topology); Computer science; Engineering; Mathematics; Art; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.01051413754290047,"gpt":0.2245541054014847,"spread":0.2140399678585842,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005414826,0.00008849492,0.0001517823,0.0000576255,0.00009755032,0.00001067545,0.0001364512,0.00003394056,0.00002354778],"category_scores_gemma":[0.00006546397,0.00007093909,0.0001375283,0.0001691803,0.000006401348,0.00004118708,0.00001546874,0.0003124016,3.430947e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001116073,"about_ca_system_score_gemma":0.00001782311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.335028e-7,"about_ca_topic_score_gemma":2.001102e-7,"domain_scores_codex":[0.9991654,0.00001646377,0.0003368144,0.00005909377,0.0002540644,0.0001682145],"domain_scores_gemma":[0.9994398,0.0002229435,0.0001155743,0.0001140656,0.00007109252,0.00003655694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002553936,0.00001272211,0.000008824222,0.00002175801,0.00003177742,0.000001454769,0.00001339499,0.921918,0.07478335,0.002029811,0.0006737334,0.0004796294],"study_design_scores_gemma":[0.0004206424,0.0001731771,0.002709618,0.00005167172,0.00004106471,0.00001523236,0.00007267389,0.9917622,0.002540016,0.00006790428,0.002071894,0.00007391322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3292375,0.0001485512,0.6663085,0.0001866673,0.003790338,0.0002159435,0.00003109346,0.00004768639,0.00003369437],"genre_scores_gemma":[0.9963009,0.000006215016,0.003252171,0.00001615011,0.0003779849,0.00001244258,0.000005850436,0.00002188521,0.00000634982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6670635,"threshold_uncertainty_score":0.2892812,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200335911","doi":"10.15407/pmach2021.04.061","title":"Strength and Service Life of a Steam Turbine Stop and Control Valve Body","year":2021,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Advanced Power Generation Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Response Biomedical (Canada)","funders":"","keywords":"Creep; Control valves; Steam turbine; Mechanics; Service life; Turbine; Ball valve; Structural engineering; Boiler (water heating); Finite element method; Materials science; Engineering; Mechanical engineering; Composite material; Physics; Waste management","retraction":null,"screen_n_in":null,"score":{"opus":0.005446732882729647,"gpt":0.1990985864199361,"spread":0.1936518535372065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001348036,0.0001226552,0.0003261055,0.00009144923,0.00001243477,0.00001453507,0.00008142793,0.00009452657,0.00001212092],"category_scores_gemma":[0.0003614885,0.0001168565,0.00005395789,0.0001526376,0.000007986012,0.0001372782,0.00004190217,0.0002915609,3.145855e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002328578,"about_ca_system_score_gemma":0.00002258708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.616351e-7,"about_ca_topic_score_gemma":0.000001114327,"domain_scores_codex":[0.9992412,0.000009867883,0.0003848287,0.00008235075,0.0001493693,0.00013242],"domain_scores_gemma":[0.9994464,0.0001197994,0.00007980216,0.0001125319,0.0001320996,0.0001093839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001646504,0.00002871859,0.00001669504,0.0002465649,0.0002520469,0.00003408617,0.00008224178,0.2034207,0.7899288,0.002644151,0.00005083728,0.003278684],"study_design_scores_gemma":[0.002565196,0.0002355199,0.0006087837,0.0002609984,0.0001407757,0.0003482235,0.0004082402,0.5471998,0.4456969,0.0005229182,0.001690984,0.0003216598],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7329209,0.007392588,0.2587378,0.000391737,0.0003524829,0.00006093167,0.00001023612,0.0001177769,0.00001552574],"genre_scores_gemma":[0.984745,0.000664028,0.01443341,0.00005367882,0.00007618157,0.000001446727,5.805275e-7,0.00002205442,0.000003625753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3442319,"threshold_uncertainty_score":0.4765269,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375842873","doi":"10.3901/jme.2022.20.350","title":"Study on Dynamic Tensile Mechanical Behavior and Deformation Mechanisms of CrCoNi Medium Entropy Alloy at Room and Cryogenic Temperature","year":2022,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"High Entropy Alloys Studies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Impact","funders":"","keywords":"Materials science; Alloy; Ultimate tensile strength; Cryogenic temperature; Deformation (meteorology); Composite material; Metallurgy","retraction":null,"screen_n_in":null,"score":{"opus":0.006292318739636695,"gpt":0.2092683443199267,"spread":0.20297602558029,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005906157,0.0002951776,0.0006059151,0.0002624851,0.0001379819,0.00003174994,0.0002146815,0.0001070313,0.00004549451],"category_scores_gemma":[0.0001144952,0.0002675619,0.0001284282,0.0001935341,0.00001193242,0.0002055332,0.0002847321,0.0007498267,0.000001016233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003244767,"about_ca_system_score_gemma":0.00001882583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001666939,"about_ca_topic_score_gemma":0.000004906031,"domain_scores_codex":[0.997974,0.00006587826,0.000758085,0.0001982928,0.0006838843,0.0003198358],"domain_scores_gemma":[0.9992372,0.0001233496,0.0001757164,0.0001896098,0.00008589673,0.0001882386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008754987,0.0001694004,0.00004026289,0.00006030644,0.0002578789,0.0001364801,0.0003702074,0.05105333,0.9457414,0.001963672,0.00004678915,0.00007276663],"study_design_scores_gemma":[0.01519687,0.01510784,0.0153782,0.0004864521,0.002320275,0.005958955,0.008557308,0.4209873,0.5113126,0.001307081,0.0008255651,0.002561513],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916375,0.0004042434,0.006554545,0.00009139148,0.000847583,0.0003570532,0.00002326565,0.0000823333,0.000002037456],"genre_scores_gemma":[0.9975796,0.0001204676,0.002095312,0.00002290094,0.0000597501,0.00004177663,0.000003271819,0.00006174663,0.00001516258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4344287,"threshold_uncertainty_score":0.9999776,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4297359709","doi":"10.24191/jmeche.v19i3.19802","title":"Variation of the Urban Heat Island Intensity over One Year in Putrajaya, Malaysia","year":2022,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Universiti Kebangsaan Malaysia","keywords":"Urban heat island; Precinct; Environmental science; Wind speed; Relative humidity; Intensity (physics); Geography; Air temperature; Population; Meteorology; Physical geography","retraction":null,"screen_n_in":null,"score":{"opus":0.005831861396757125,"gpt":0.1706735262649617,"spread":0.1648416648682046,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004362969,0.00004924836,0.0001227687,0.00003707636,0.00002224149,0.000004418349,0.0001468507,0.00002623114,0.000610228],"category_scores_gemma":[0.00008175326,0.00003975578,0.00005272695,0.0002271038,0.000007138988,0.00008911726,0.0001228602,0.0002795091,0.000001707774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002108616,"about_ca_system_score_gemma":0.000009341074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005222163,"about_ca_topic_score_gemma":0.00001000444,"domain_scores_codex":[0.9992355,0.00003047952,0.0002546044,0.00006265734,0.0003240742,0.00009270029],"domain_scores_gemma":[0.9997649,0.00003283954,0.00007261024,0.00008882212,0.000009020289,0.00003176328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00007654841,0.0001596072,0.02411308,0.00001254345,0.0000243766,0.000008885077,0.000632686,0.4902613,0.4830195,0.0008161581,0.0007241683,0.0001511378],"study_design_scores_gemma":[0.00144843,0.0003364467,0.7605206,0.00008383653,0.00004800756,0.0000823538,0.00007983338,0.2187122,0.01640961,0.001016779,0.001074947,0.0001868967],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945883,0.00001448778,0.004820592,0.0001710524,0.0002734224,0.00006285941,0.000002773067,0.000003349126,0.00006316788],"genre_scores_gemma":[0.999214,0.000002820432,0.0006637158,0.00003777967,0.00004480036,0.000001422356,3.660364e-7,0.000006186182,0.00002890255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7364076,"threshold_uncertainty_score":0.6681568,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4417478901","doi":"10.3901/jme.2024.10.273","title":"High-performance Trajectory Optimization for Automated Parking via Half-space Constraining Theory","year":2024,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Trajectory; Trajectory optimization; Collision; Control theory (sociology); Optimization algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.005704050273224012,"gpt":0.1922047715842596,"spread":0.1865007213110356,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006259162,0.0001615861,0.0002520849,0.0001994535,0.00002819728,0.00006227157,0.0001263792,0.0000793889,0.00002504055],"category_scores_gemma":[0.00005275547,0.0001480927,0.0001160464,0.0001559688,0.000006875136,0.0002229253,0.00001364344,0.0002549003,0.000002025449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001007586,"about_ca_system_score_gemma":0.00002093199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.696346e-7,"about_ca_topic_score_gemma":2.557644e-7,"domain_scores_codex":[0.9990722,0.00001122371,0.0004069351,0.0001032763,0.0001632202,0.0002431248],"domain_scores_gemma":[0.9995664,0.0001909542,0.0000443713,0.00007837921,0.00004186746,0.00007797008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001803259,0.000007105514,9.99135e-8,0.0003016365,0.0001866271,0.00001989666,0.00006008558,0.9511736,0.01186288,0.005685136,0.000140207,0.03054468],"study_design_scores_gemma":[0.0004857117,0.00009104029,0.0000127039,0.0003760084,0.00008870314,0.00005600989,0.00002497741,0.994947,0.00204288,0.00004980912,0.001665829,0.0001592962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01591429,0.001026152,0.9791299,0.00007661774,0.002628257,0.0001385297,0.000002237915,0.001033859,0.00005021393],"genre_scores_gemma":[0.9447675,0.0001093247,0.05469533,0.00001166943,0.0003377433,0.00001156686,0.000001868276,0.00005181122,0.0000131189],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9288533,"threshold_uncertainty_score":0.6039045,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4417483965","doi":"10.3901/jme.2025.15.314","title":"Experimental Study on Occupant Secondary Impact Injury for High-speed Trains","year":2025,"lang":"en","type":"article","venue":"Journal of Mechanical Engineering","topic":"Automotive and Human Injury Biomechanics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Education and Child Care","funders":"","keywords":"Train; Impact; Side impact","retraction":null,"screen_n_in":null,"score":{"opus":0.02257027218852375,"gpt":0.3359597986022714,"spread":0.3133895264137477,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004847309,0.000208451,0.0005679265,0.0004000536,0.00005160258,0.00002317587,0.0001483258,0.0001047928,0.0001287671],"category_scores_gemma":[0.000156365,0.0001586968,0.0003332167,0.0001673351,0.000008392876,0.00008506655,0.00004071129,0.0004706739,0.000003395675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002880312,"about_ca_system_score_gemma":0.0001608411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001999831,"about_ca_topic_score_gemma":1.686967e-7,"domain_scores_codex":[0.9987155,0.0000201633,0.0005674222,0.00016948,0.0002765519,0.0002509256],"domain_scores_gemma":[0.9992781,0.0001073521,0.0001443035,0.0001799787,0.0001188677,0.0001713494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003518152,0.003431794,0.00003044745,0.0001159107,0.001269852,0.0001781971,0.0004847571,0.0002358329,0.9700353,0.01446623,0.00206765,0.004165901],"study_design_scores_gemma":[0.01563529,0.05711295,0.006233345,0.0008595194,0.0007128021,0.0001701348,0.00175952,0.01112954,0.9030656,0.001101971,0.001683592,0.0005356821],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668462,0.0001228092,0.03130059,0.0001830954,0.0008922204,0.0005136514,0.00002747474,0.00004102723,0.00007298608],"genre_scores_gemma":[0.9981259,0.000004119267,0.001191365,0.0002273174,0.0003253791,0.000006868237,0.000003181548,0.00002935301,0.00008652278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06696963,"threshold_uncertainty_score":0.6471468,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}