{"meta":{"query_hash":"869af113a74e","filters":{"venue":"AIAA AVIATION 2020 FORUM"},"cohort_total":18,"direct_labels_cover":0,"predictions_cover":18,"exported":18,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/869af113a74e","api":"https://metacan.xera.ac/api/v1/cohort?venue=AIAA+AVIATION+2020+FORUM"},"results":[{"id":"W3034259591","doi":"10.2514/6.2020-2646","title":"Mainstream Flow Prediction for the Thermal Risk Assessment of Aircraft Systems in Conceptual Design","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Conceptual design; Computer science; Risk assessment; Thermal; Systems engineering; Engineering; Mechanical engineering; Meteorology","score_opus":0.018325564742757934,"score_gpt":0.24071805732336932,"score_spread":0.2223924925806114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034259591","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024299303,0.00036334406,0.9725601,0.000052550953,0.000036628688,0.00006053223,0.000053325388,0.00016028642,0.0024139066],"genre_scores_gemma":[0.77952313,0.00090211467,0.21508354,0.000037661423,0.000071442846,0.00023515098,0.00019064931,0.00015020813,0.0038060744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994917,0.00022390227,0.000023559323,0.000057159657,0.0001718407,0.000031854215],"domain_scores_gemma":[0.99855787,0.0009539401,0.00013593289,0.00007833779,0.0002286506,0.00004519795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015830178,0.0013053692,0.00074087933,0.0011383302,0.00038766087,0.001030033,0.0006084165,0.0006547559,0.0021729057],"category_scores_gemma":[0.004218796,0.0004300667,0.0008096282,0.0005642521,0.0007697087,0.0016995764,0.0010265156,0.0009013651,0.00028410973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036816004,0.000015181505,0.00067156926,0.000052310323,0.000009276541,0.000025398569,0.000047554833,0.9629329,0.0018895878,0.01072717,0.00017469564,0.023417627],"study_design_scores_gemma":[0.0000025882964,0.000022698805,0.00009129595,0.000007306898,0.0000032687074,0.000006188251,0.0000072141916,0.995449,0.00046598964,0.0035226592,0.00041772795,0.0000039748893],"about_ca_topic_score_codex":0.0040186746,"about_ca_topic_score_gemma":0.0026532349,"teacher_disagreement_score":0.0040186746,"about_ca_system_score_codex":0.00089731714,"about_ca_system_score_gemma":0.0009305705,"threshold_uncertainty_score":0.008371949},"labels":[],"label_agreement":null},{"id":"W3034398297","doi":"10.2514/6.2020-3152","title":"An efficient application of Bayesian optimization to an industrial MDO framework for aircraft design.","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Bayesian optimization; Solver; Set (abstract data type); Bayesian probability; Aviation; Global optimization","score_opus":0.0265716939448896,"score_gpt":0.29424118991350096,"score_spread":0.26766949596861134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034398297","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026141014,0.00018475858,0.9934098,0.00013569911,0.00002421322,0.000055003467,0.00007066129,0.00019311486,0.0033126478],"genre_scores_gemma":[0.19280188,0.00035675993,0.80222327,0.0001859438,0.000049123544,0.00054108165,0.00037311003,0.00028090566,0.0031880087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947447,0.00025638493,0.000018213239,0.000038958093,0.00017466735,0.000037292455],"domain_scores_gemma":[0.9990972,0.00058255,0.00006479881,0.00005403383,0.00015472708,0.000046750076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016640082,0.0008883088,0.0009099373,0.0006799265,0.0004073257,0.00076268194,0.0010739957,0.0011770187,0.0038068697],"category_scores_gemma":[0.0042129443,0.000667805,0.00080148,0.0006107361,0.000581116,0.00069505227,0.0014947897,0.0014674761,0.0007224634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002451995,0.000025709189,0.0001952571,0.000057173773,0.000025128586,0.000023589197,0.000023492797,0.9611466,0.0005093812,0.01649794,0.0009864033,0.02048492],"study_design_scores_gemma":[0.000005637489,0.000007745524,0.00003213169,0.000006609265,0.0000029667274,0.0000044982853,0.000003019839,0.995865,0.00008456495,0.003333605,0.0006520181,0.000002159946],"about_ca_topic_score_codex":0.008315826,"about_ca_topic_score_gemma":0.010996683,"teacher_disagreement_score":0.008315826,"about_ca_system_score_codex":0.0006296359,"about_ca_system_score_gemma":0.0017269555,"threshold_uncertainty_score":0.016534865},"labels":[],"label_agreement":null},{"id":"W3034589746","doi":"10.2514/6.2020-2539","title":"Aerodynamic and acoustic investigation of the liner-type porous treatment for the trailing-edge of the flat plate.","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Trailing edge; Airfoil; Acoustics; Materials science; Particle image velocimetry; Boundary layer; Directivity; Noise (video); Aerodynamics; Mechanics; Physics; Composite material; Engineering; Turbulence; Computer science","score_opus":0.01320417604530153,"score_gpt":0.20850928263829546,"score_spread":0.19530510659299394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034589746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9851715,0.00039640244,0.012222317,0.000037517475,0.000044099732,0.00003644317,0.000113789,0.000101690166,0.0018762202],"genre_scores_gemma":[0.99320626,0.000109479,0.0047492534,0.00001377297,0.0000058538635,0.000013265119,0.00006637957,0.000012725106,0.0018231376],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987507,0.000010547492,0.000003033503,0.000024904524,0.000068404705,0.00001801065],"domain_scores_gemma":[0.99988115,0.00002776246,0.000028979804,0.000015387666,0.000034853354,0.000011963396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015428435,0.00025169214,0.0001834458,0.0001921564,0.00020957155,0.00018399024,0.0002076832,0.00027241601,0.001182945],"category_scores_gemma":[0.00022157755,0.00010081076,0.00017604177,0.00010571327,0.0003307674,0.00012694205,0.00014230383,0.00027643185,0.00017914802],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089666995,0.000032251468,0.00035565507,0.00007199018,0.0000045230613,0.000084880354,0.00003451989,0.0024755194,0.9926918,0.0001360435,0.00008492334,0.0039381622],"study_design_scores_gemma":[0.000015138153,0.0007456904,0.01114489,0.000010329399,0.000024198822,0.0001527742,0.00008234636,0.017580537,0.9678949,0.000052577572,0.002279343,0.000017129089],"about_ca_topic_score_codex":0.0012786875,"about_ca_topic_score_gemma":0.0017254805,"teacher_disagreement_score":0.0012786875,"about_ca_system_score_codex":0.00020210362,"about_ca_system_score_gemma":0.0002265903,"threshold_uncertainty_score":0.003957331},"labels":[],"label_agreement":null},{"id":"W3034633156","doi":"10.2514/6.2020-2514","title":"Large-Eddy Simulation of a Single Airfoil Tip-Leakage Flow","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec; Université de Sherbrooke","funders":"","keywords":"Airfoil; Trailing edge; Leading edge; Mechanics; Turbulence; Aerodynamics; Large eddy simulation; Acoustics; Camber (aerodynamics); Leakage (economics); Vortex; Mach number; Reynolds number; Chord (peer-to-peer); Tip clearance; Physics; Materials science; Structural engineering; Engineering; Computer science","score_opus":0.008934182377998066,"score_gpt":0.2083524202016048,"score_spread":0.19941823782360674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034633156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98208964,0.0000734365,0.010925418,0.00014273777,0.00003314256,0.00006652619,0.00032072782,0.00016023542,0.0061881333],"genre_scores_gemma":[0.995271,0.000028731178,0.0033881299,0.000023057259,0.000005418425,0.00004310503,0.0001893215,0.000021376056,0.0010298578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986696,0.000029133073,0.000007428589,0.000019150537,0.000031592874,0.00004580999],"domain_scores_gemma":[0.99940884,0.0002864887,0.00006081795,0.000037207097,0.00010215033,0.00010458461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032430072,0.00042346693,0.000748423,0.0003547066,0.00056043186,0.0007119315,0.00079284015,0.0013957216,0.0020668358],"category_scores_gemma":[0.0011332062,0.0002408878,0.00059404864,0.00033042542,0.0006155616,0.00044941675,0.00041454763,0.0006105752,0.00017060206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014834818,0.000119469805,0.0022324307,0.000035495814,0.00002067497,0.00020123717,0.000055047298,0.9906957,0.0043949103,0.00063461706,0.0001928659,0.0012691101],"study_design_scores_gemma":[0.000027302971,0.000048817943,0.00095553097,0.000004145854,0.000004839724,0.000012892498,0.000025514391,0.99800354,0.00073220354,0.00008052334,0.00009893731,0.0000057591988],"about_ca_topic_score_codex":0.015317994,"about_ca_topic_score_gemma":0.0061828704,"teacher_disagreement_score":0.015317994,"about_ca_system_score_codex":0.0006614944,"about_ca_system_score_gemma":0.0009663298,"threshold_uncertainty_score":0.030457675},"labels":[],"label_agreement":null},{"id":"W3034671049","doi":"10.2514/6.2020-2825","title":"Ice Crystal Environment Modular Axial Compressor Rig: Characterization of Particle Fracture and Melt Across One Rotor Using Laser Shadowgraphy","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Shadowgraph; Icing; Materials science; Shadowgraphy; Mechanics; Aerospace engineering; Engineering; Optics; Meteorology; Physics; Laser","score_opus":0.011945744742940724,"score_gpt":0.2040752781094861,"score_spread":0.1921295333665454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034671049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.970759,0.000100169906,0.022792093,0.00003355825,0.000011303558,0.00018356298,0.0019205678,0.0005808782,0.0036189414],"genre_scores_gemma":[0.9761538,0.00010466638,0.020505583,0.000026301546,0.0000057763277,0.00010389297,0.0010976368,0.000096462645,0.0019059094],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999734,0.000010395174,0.00000993125,0.00003686074,0.00018361493,0.000025196361],"domain_scores_gemma":[0.9996043,0.00009914846,0.000052854375,0.00005408064,0.00014907643,0.00004057683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037076866,0.00021679609,0.00022380716,0.0006548651,0.0004613316,0.0002937274,0.000479392,0.00030647704,0.0025711714],"category_scores_gemma":[0.0005242364,0.00016575199,0.00014906317,0.000565829,0.00033059085,0.00026676638,0.00032012395,0.00036126358,0.0003471553],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067461235,0.00023238795,0.0293585,0.00019336745,0.000019873829,0.0003793461,0.0005034989,0.011446251,0.89853936,0.0008000287,0.0019503029,0.055902433],"study_design_scores_gemma":[0.00007361088,0.0009439235,0.1461754,0.000026428972,0.000019407953,0.00042508938,0.0003253376,0.123259425,0.72305775,0.0002283537,0.005418525,0.000046766367],"about_ca_topic_score_codex":0.0069527673,"about_ca_topic_score_gemma":0.011867426,"teacher_disagreement_score":0.0069527673,"about_ca_system_score_codex":0.00037497128,"about_ca_system_score_gemma":0.00043886853,"threshold_uncertainty_score":0.013824582},"labels":[],"label_agreement":null},{"id":"W3034671848","doi":"10.2514/6.2020-2607","title":"Large Eddy Simulation of an Outflow butterfly valve","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec; Université de Sherbrooke","funders":"","keywords":"Butterfly valve; Aerodynamics; Acoustics; Noise (video); Schlieren; Transonic; Large eddy simulation; Wind tunnel; Aerospace engineering; Computer science; Mechanics; Physics; Engineering; Mechanical engineering; Turbulence","score_opus":0.007609323749449287,"score_gpt":0.22621268367967617,"score_spread":0.2186033599302269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034671848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98632413,0.00006498446,0.008235746,0.00012733717,0.000029450559,0.000029263818,0.0001871539,0.0001434153,0.00485856],"genre_scores_gemma":[0.9964965,0.000021605441,0.0021941115,0.000016980053,0.0000041958338,0.000016647915,0.00012932888,0.00001615023,0.0011045198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999076,0.000019949897,0.0000053900308,0.000014718987,0.000020552516,0.00003186793],"domain_scores_gemma":[0.9996039,0.00021958307,0.000040594274,0.000021275,0.000052836866,0.0000617563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023108964,0.0003222515,0.00041290873,0.00025422015,0.00041652942,0.0006583077,0.00046656156,0.0009997627,0.0013647284],"category_scores_gemma":[0.0008591032,0.00016383047,0.0003332127,0.00021050197,0.0005431269,0.0003325754,0.00042133644,0.00040666436,0.00009641441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024298465,0.00013529537,0.0046009943,0.000038189042,0.000021055386,0.0002826324,0.000070236645,0.9829826,0.008292349,0.0010757158,0.0003278999,0.0019299511],"study_design_scores_gemma":[0.000023805582,0.00005072667,0.0014716109,0.000003200266,0.000003471521,0.000010870806,0.000037094876,0.99725,0.0008809327,0.000106168736,0.00015699687,0.00000516941],"about_ca_topic_score_codex":0.011876948,"about_ca_topic_score_gemma":0.0050889645,"teacher_disagreement_score":0.011876948,"about_ca_system_score_codex":0.00047767555,"about_ca_system_score_gemma":0.0006347827,"threshold_uncertainty_score":0.023615599},"labels":[],"label_agreement":null},{"id":"W3034937672","doi":"10.2514/6.2020-2823","title":"Ice Crystal Environment - Modular Axial Compressor Rig: Overview of Altitude Icing Commissioning","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Icing; Gas compressor; Altitude (triangle); Engineering; Environmental science; Marine engineering; Project commissioning; Ice crystals; Aerospace engineering; Meteorology; Mechanical engineering; Physics","score_opus":0.02294938495423907,"score_gpt":0.22733713473012254,"score_spread":0.20438774977588348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034937672","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38180372,0.02365269,0.31673038,0.001523455,0.00051472516,0.0059832083,0.018866103,0.013847891,0.23707785],"genre_scores_gemma":[0.74638486,0.009791881,0.20434435,0.00018062073,0.0001568476,0.0008134853,0.01347108,0.00093294133,0.023923978],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984156,0.00009606824,0.00005135884,0.0001001763,0.0012259522,0.000110789086],"domain_scores_gemma":[0.99909914,0.00009197988,0.000058553185,0.00012506664,0.00051988714,0.00010533443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016482405,0.00058018765,0.00050651666,0.0015844594,0.00079444685,0.0011036872,0.0010682385,0.00064392644,0.002842207],"category_scores_gemma":[0.0012841125,0.0003574786,0.00033908046,0.0017555776,0.00052411377,0.0007813169,0.0006319649,0.0009564821,0.0012887568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010757853,0.00062151835,0.021036193,0.0031945216,0.00007491078,0.0010888058,0.00070821604,0.118810475,0.25151306,0.0105405105,0.031054344,0.5602817],"study_design_scores_gemma":[0.00020159855,0.002449224,0.07133716,0.00076156907,0.00008531857,0.0018962795,0.0005515297,0.12578204,0.2674437,0.0025282688,0.5266477,0.00031559792],"about_ca_topic_score_codex":0.030678961,"about_ca_topic_score_gemma":0.033860903,"teacher_disagreement_score":0.030678961,"about_ca_system_score_codex":0.0021004505,"about_ca_system_score_gemma":0.003212364,"threshold_uncertainty_score":0.061000764},"labels":[],"label_agreement":null},{"id":"W3034989401","doi":"10.2514/6.2020-3058","title":"Towards an hybrid computational strategy based on Deep Learning for incompressible flows","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Council of Prairie and Pacific University Libraries","funders":"Agence Nationale de la Recherche","keywords":"Solver; Computer science; Artificial neural network; Compressibility; Applied mathematics; Acceleration; Incompressible flow; Convolutional neural network; Computational fluid dynamics; Flow (mathematics); Mathematical optimization; Algorithm; Artificial intelligence; Mathematics; Mechanics; Physics; Classical mechanics","score_opus":0.020133479393862248,"score_gpt":0.2681650172900993,"score_spread":0.24803153789623703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034989401","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02952646,0.00022284116,0.9660106,0.00019135672,0.00003384237,0.000036727353,0.000040095365,0.0005499893,0.003388053],"genre_scores_gemma":[0.5165328,0.00021130932,0.47645727,0.0002562549,0.000049188766,0.00017692265,0.00021076592,0.00018924456,0.005916217],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984574,0.000032640994,0.000007765518,0.00002848008,0.000060467617,0.000024891351],"domain_scores_gemma":[0.9997346,0.000101313315,0.000027472384,0.000038828748,0.000071555325,0.000026212982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044605506,0.0006573269,0.00050752336,0.00042523633,0.0002973319,0.00071885035,0.001357931,0.0007703284,0.0016827408],"category_scores_gemma":[0.00087980396,0.00035912808,0.00042008478,0.00029240473,0.00051104865,0.00090211956,0.0013412111,0.0009528143,0.0004726807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008327502,0.00009020284,0.00086601125,0.000063140586,0.00005241497,0.000067197296,0.000057308476,0.90510225,0.009911196,0.015902696,0.0009246067,0.06687967],"study_design_scores_gemma":[0.0000018563364,0.000007560022,0.000023350887,0.0000017658739,0.0000014063302,0.0000036068102,0.0000017287224,0.99843484,0.00044510583,0.00088889594,0.00018870752,0.000001184869],"about_ca_topic_score_codex":0.005575334,"about_ca_topic_score_gemma":0.0065196757,"teacher_disagreement_score":0.005575334,"about_ca_system_score_codex":0.0006515737,"about_ca_system_score_gemma":0.00085291156,"threshold_uncertainty_score":0.011085749},"labels":[],"label_agreement":null},{"id":"W3035122175","doi":"10.2514/6.2020-2773","title":"Airfoils Generation Using Neural Networks, CST Curves and Aerodynamic Coefficients","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec","funders":"","keywords":"Airfoil; Aerodynamics; Computer science; Lift-to-drag ratio; Lift (data mining); Lift coefficient; Angle of attack; Pitching moment; Drag coefficient; Drag; Aerospace engineering; Engineering; Mechanics; Data mining; Physics","score_opus":0.012774976074194377,"score_gpt":0.21065607515970378,"score_spread":0.1978810990855094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035122175","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35181844,0.00041662712,0.6342494,0.0002625971,0.00009523761,0.000160604,0.00023422093,0.0014460689,0.011316787],"genre_scores_gemma":[0.9081364,0.0001372709,0.08934855,0.000024718647,0.000010731859,0.000108531196,0.00015286099,0.00005783629,0.002023025],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999025,0.000022122313,0.0000052942064,0.000022168308,0.00003479452,0.000013109285],"domain_scores_gemma":[0.99962556,0.00019904757,0.000040743347,0.000029082988,0.000093104354,0.0000124291955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031981585,0.0005899784,0.0002227965,0.0005284411,0.0001999149,0.000418556,0.0004381857,0.0005527378,0.0015639747],"category_scores_gemma":[0.0011298491,0.00020297457,0.00038074615,0.000353772,0.00021743224,0.00048165984,0.00029356196,0.00042086118,0.00020348615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004828322,0.00003683166,0.00063844235,0.000053578966,0.000011911156,0.000029682922,0.000025029947,0.9544811,0.0049615386,0.0007933629,0.00019940652,0.03872079],"study_design_scores_gemma":[0.000002831239,0.000019261386,0.0001616336,0.0000034351,0.0000026145178,0.000004583037,0.000004199483,0.99698275,0.002426121,0.00024690715,0.0001434995,0.0000021734895],"about_ca_topic_score_codex":0.0051277415,"about_ca_topic_score_gemma":0.004872157,"teacher_disagreement_score":0.0051277415,"about_ca_system_score_codex":0.0005567123,"about_ca_system_score_gemma":0.00030234724,"threshold_uncertainty_score":0.010195792},"labels":[],"label_agreement":null},{"id":"W3035212369","doi":"10.2514/6.2020-2652","title":"Lessons Learned from the Design, Manufacturing, and Test of an All-Electric General Aviation Aircraft","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Aviation; Multidisciplinary approach; General aviation; Engineering; Point (geometry); Systems engineering; Test (biology); Aeronautics; Computer science; Aerospace engineering","score_opus":0.04465611417250725,"score_gpt":0.28271626724042925,"score_spread":0.238060153067922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035212369","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18736772,0.06102922,0.24705237,0.25466174,0.0068619475,0.0003131329,0.0002953002,0.0013324225,0.24108607],"genre_scores_gemma":[0.65829426,0.04789915,0.14039847,0.01953257,0.0013408916,0.00016828768,0.00021833902,0.00055209594,0.13159597],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99715024,0.00109837,0.00009829798,0.00022831131,0.0012440839,0.0001807504],"domain_scores_gemma":[0.9963696,0.0015250521,0.000118051845,0.00049118284,0.0011055917,0.0003905768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006087297,0.0006691572,0.00038899117,0.0003505161,0.0016192294,0.0036003958,0.0014411104,0.0018225462,0.0036052933],"category_scores_gemma":[0.0060146693,0.00028004646,0.00034140845,0.00032690357,0.003843845,0.0053000995,0.0022619166,0.0038913388,0.0014027322],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001474873,0.00032408437,0.0036555552,0.0015597875,0.00004332832,0.0017571808,0.0169082,0.017294988,0.0140097095,0.08634923,0.0675735,0.79037684],"study_design_scores_gemma":[0.000046750654,0.0010376851,0.002653739,0.00143948,0.000039908482,0.002886081,0.02358148,0.004774833,0.01454792,0.13200642,0.81685364,0.00013206092],"about_ca_topic_score_codex":0.0027798142,"about_ca_topic_score_gemma":0.006531503,"teacher_disagreement_score":0.006087297,"about_ca_system_score_codex":0.0018007451,"about_ca_system_score_gemma":0.0024642,"threshold_uncertainty_score":0.032193124},"labels":[],"label_agreement":null},{"id":"W3035401587","doi":"10.2514/6.2020-2763","title":"Effect of Leading-Edge Tubercles on Rotor Blades","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Stall (fluid mechanics); Mach number; Leading edge; Drag; Airfoil; Transonic; Physics; Trailing edge; Aerodynamics; Mechanics","score_opus":0.0038773410895224145,"score_gpt":0.21130527836646587,"score_spread":0.20742793727694345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035401587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994221,0.00016892809,0.0035511807,0.000024636844,0.000041960633,0.000010187259,0.000029453588,0.00016305088,0.0017896597],"genre_scores_gemma":[0.9978072,0.00005909556,0.0015895878,0.00002111156,0.0000038546946,0.0000035769901,0.00002920113,0.000030262323,0.0004562161],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983287,0.000020431187,0.000012387085,0.000034948058,0.0000539679,0.000045347035],"domain_scores_gemma":[0.9994823,0.00018000443,0.000078877776,0.00007266805,0.00011484577,0.00007125436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020692617,0.000272328,0.00035649264,0.00021490843,0.00027644794,0.0006550405,0.00032611043,0.00042759758,0.00129311],"category_scores_gemma":[0.0012377917,0.00018727298,0.0002720415,0.00016456319,0.0003632133,0.00027858926,0.00051134685,0.00033079198,0.0002735383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014262486,0.00017242465,0.014534748,0.00032761978,0.000053304644,0.0022587941,0.00021180943,0.11874694,0.8110088,0.0009086167,0.0006631761,0.04968759],"study_design_scores_gemma":[0.000106371495,0.0060050343,0.07112522,0.00011061424,0.00015753105,0.0021435125,0.00067424116,0.35999984,0.5487215,0.00052416144,0.010319429,0.000112595364],"about_ca_topic_score_codex":0.00075459044,"about_ca_topic_score_gemma":0.0012233788,"teacher_disagreement_score":0.00129311,"about_ca_system_score_codex":0.00013400256,"about_ca_system_score_gemma":0.00019916394,"threshold_uncertainty_score":0.0043259263},"labels":[],"label_agreement":null},{"id":"W3035441133","doi":"10.2514/6.2020-2826","title":"Ice Crystal Environment-Modular Axial Compressor Rig: Evaluation of Measured Water Content and Melt","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Modular design; Gas compressor; Materials science; Water content; Environmental science; Ice crystals; Mechanical engineering; Computer science; Geology; Engineering; Geotechnical engineering; Meteorology; Physics","score_opus":0.03968317865353547,"score_gpt":0.2122926548092819,"score_spread":0.17260947615574643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035441133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98214173,0.00011796785,0.0106848795,0.00003150876,0.000013812367,0.00020794336,0.0024906567,0.0004824904,0.0038290543],"genre_scores_gemma":[0.99008054,0.000085174215,0.0069649164,0.000021187107,0.0000042117413,0.00008258534,0.0011342405,0.00007073207,0.0015564198],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996371,0.000019531542,0.000013137992,0.000044553173,0.00025595244,0.000029640967],"domain_scores_gemma":[0.9996512,0.00008103855,0.000040793224,0.000031634772,0.0001556732,0.000039793413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048084007,0.00033118675,0.00026118333,0.0007466616,0.0004530598,0.00033655678,0.00043949866,0.0004222832,0.0018098906],"category_scores_gemma":[0.00087511784,0.00015673452,0.0001724745,0.0006713063,0.00038690638,0.00034482064,0.00032759897,0.00033789856,0.00037846772],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011673875,0.00030168495,0.03893228,0.0002535925,0.000030054964,0.00022811804,0.00026782998,0.0076392237,0.90772086,0.00038698126,0.0013933312,0.041678686],"study_design_scores_gemma":[0.00008103922,0.001084359,0.117375135,0.000024019635,0.000030356949,0.00027630327,0.00026497466,0.06784964,0.8084819,0.00013234431,0.004353559,0.00004645501],"about_ca_topic_score_codex":0.008951341,"about_ca_topic_score_gemma":0.013076162,"teacher_disagreement_score":0.008951341,"about_ca_system_score_codex":0.00050038926,"about_ca_system_score_gemma":0.00057450985,"threshold_uncertainty_score":0.017798483},"labels":[],"label_agreement":null},{"id":"W3035448492","doi":"10.2514/6.2020-2541","title":"Numerical study of optimized airfoil trailing-edge serrations for broadband noise reduction","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Airfoil; Reynolds-averaged Navier–Stokes equations; Trailing edge; Drag; Aerodynamics; Noise reduction; Shape optimization; Noise (video); Reduction (mathematics); Leading edge; Computational fluid dynamics; Acoustics; Mathematics; Mechanics; Physics; Structural engineering; Computer science; Engineering; Finite element method; Geometry","score_opus":0.013317677570740094,"score_gpt":0.23518529024317722,"score_spread":0.22186761267243713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035448492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8703517,0.00036156937,0.1121992,0.0002401081,0.00005582843,0.000069396425,0.00017749041,0.00021523889,0.016329544],"genre_scores_gemma":[0.9841649,0.00004964166,0.014546511,0.000019602816,0.0000048558145,0.00003615074,0.000069671485,0.000021306312,0.0010874523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984705,0.000046800247,0.0000050585054,0.000016014843,0.000049681246,0.00003539554],"domain_scores_gemma":[0.9996358,0.00018077651,0.000059452927,0.000022093938,0.00007106503,0.000030758645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054347125,0.0005520833,0.0007203326,0.0003472309,0.000333983,0.00055146276,0.00031784558,0.00076126447,0.0009841585],"category_scores_gemma":[0.0011358465,0.00019245711,0.0005203186,0.0002126873,0.00043624226,0.0002661577,0.00031897755,0.00028287212,0.000112772315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007818397,0.00003249172,0.00058149436,0.00003701983,0.000009517711,0.000079434205,0.000020850579,0.99086094,0.0052429135,0.00091227976,0.00015774617,0.0019870647],"study_design_scores_gemma":[0.000007879596,0.00004039387,0.00022173427,0.00000335391,0.0000028171335,0.000007563792,0.000009845541,0.99843365,0.0010740807,0.000100378275,0.00009490835,0.0000033920699],"about_ca_topic_score_codex":0.003401987,"about_ca_topic_score_gemma":0.002162255,"teacher_disagreement_score":0.003401987,"about_ca_system_score_codex":0.0003766564,"about_ca_system_score_gemma":0.0005927111,"threshold_uncertainty_score":0.006764412},"labels":[],"label_agreement":null},{"id":"W3035536883","doi":"10.2514/6.2020-2691","title":"Novel Parameters for the Performance Evaluations of Leading Edge Tubercles on Airfoils","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Biomimetic flight and propulsion mechanisms","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Airfoil; Enhanced Data Rates for GSM Evolution; Computer science; Aerospace engineering; Engineering; Artificial intelligence","score_opus":0.03517152914776575,"score_gpt":0.25655406858562047,"score_spread":0.22138253943785471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035536883","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9099509,0.0004479774,0.08504169,0.00005716613,0.000063136926,0.00008279311,0.0002405343,0.0005628243,0.0035529584],"genre_scores_gemma":[0.9905618,0.00006039103,0.008844779,0.000008899067,0.000002962908,0.000035781013,0.00011025491,0.000024333372,0.00035083562],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981946,0.000026374619,0.000016535632,0.000033071625,0.00007722358,0.000027321132],"domain_scores_gemma":[0.999493,0.00020356505,0.00006979408,0.00005256008,0.00015414756,0.00002679861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046855066,0.00058251934,0.0002825301,0.0006338647,0.00013701257,0.0004143402,0.00035344635,0.0004663906,0.0008990732],"category_scores_gemma":[0.0016722,0.00012468333,0.0002577345,0.00031952755,0.00024689673,0.0004334085,0.00029968377,0.00034107256,0.00014689726],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006741622,0.00039660433,0.012652188,0.0006787929,0.000090560454,0.00022583701,0.0001462406,0.57690966,0.25110114,0.00093646755,0.001142325,0.15504614],"study_design_scores_gemma":[0.000028251692,0.0011028764,0.018769607,0.000045495304,0.00005108749,0.00012624286,0.00013946147,0.83718836,0.1406304,0.00038662122,0.0014828213,0.000048779788],"about_ca_topic_score_codex":0.00068828196,"about_ca_topic_score_gemma":0.0010191484,"teacher_disagreement_score":0.0008990732,"about_ca_system_score_codex":0.00022754981,"about_ca_system_score_gemma":0.00015300319,"threshold_uncertainty_score":0.00300771},"labels":[],"label_agreement":null},{"id":"W3035633240","doi":"10.2514/6.2020-2758","title":"Verification and Validation of a High-Fidelity Open-Source Simulation Tool for Supersonic Aircraft Aerodynamic Analysis","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Supersonic speed; Aerodynamics; Solver; Aerospace engineering; Computer science; Airframe; Engineering","score_opus":0.010061996352683565,"score_gpt":0.23877274973284895,"score_spread":0.2287107533801654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035633240","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37193063,0.00040974937,0.5623306,0.00068289053,0.0007461241,0.0011728063,0.0043125288,0.025159122,0.033255693],"genre_scores_gemma":[0.7001641,0.0002740003,0.27762228,0.0002762476,0.00006424251,0.0010105778,0.010169363,0.0038866126,0.0065325815],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99761593,0.00056626624,0.00014601693,0.00017716203,0.001226872,0.00026774942],"domain_scores_gemma":[0.99366474,0.0023561236,0.00032729085,0.001217638,0.0021680666,0.00026619853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043919026,0.0014387963,0.00076432986,0.00080792804,0.0009680123,0.001474831,0.0037447196,0.0017579491,0.0051384754],"category_scores_gemma":[0.009772892,0.00048423157,0.0012129574,0.0005256988,0.0012954329,0.0013373239,0.002037021,0.0020235598,0.0014690785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059868523,0.00090051553,0.007046179,0.0006257072,0.00018730927,0.000635936,0.00042797107,0.8777437,0.03742786,0.015311712,0.013504408,0.045590013],"study_design_scores_gemma":[0.00012426845,0.0001766187,0.00082519697,0.000044914563,0.000015416754,0.00006318571,0.000044398665,0.9733975,0.018486226,0.000808468,0.0059870924,0.000026651685],"about_ca_topic_score_codex":0.007828241,"about_ca_topic_score_gemma":0.006002062,"teacher_disagreement_score":0.007828241,"about_ca_system_score_codex":0.0010631977,"about_ca_system_score_gemma":0.0026843601,"threshold_uncertainty_score":0.023226917},"labels":[],"label_agreement":null},{"id":"W3035727109","doi":"10.2514/6.2020-2521","title":"Tip flow evolution in a turbofan rotor for broadband noise diagnostic","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Aerodynamics and Acoustics in Jet Flows","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec; Université de Sherbrooke","funders":"","keywords":"Turbofan; Mechanics; Vortex; Leading edge; Boundary layer; Physics; Tip clearance; Acoustics; Duct (anatomy); Mean flow; Shock (circulatory); Leakage (economics); Materials science; Aerospace engineering; Engineering; Turbulence","score_opus":0.005439062950439926,"score_gpt":0.19690292472036303,"score_spread":0.1914638617699231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035727109","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98432356,0.00009953793,0.012187737,0.00009893452,0.000021488315,0.00002532372,0.00009037863,0.0002004174,0.0029526392],"genre_scores_gemma":[0.9960742,0.000032405304,0.0029073288,0.000014386502,0.0000037090433,0.00001068046,0.000056524965,0.000013615737,0.0008871745],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992204,0.000022061075,0.0000027648196,0.00001214309,0.00002453023,0.000016474223],"domain_scores_gemma":[0.9997614,0.00011450999,0.000029338791,0.000012859115,0.000052358442,0.000029625462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023623354,0.0004590595,0.00038821928,0.00038752725,0.00041217054,0.00045777802,0.00035041873,0.0010595865,0.0010620473],"category_scores_gemma":[0.0006419111,0.00015543243,0.00039094768,0.00018382893,0.00039779366,0.00029377223,0.0002929815,0.00028912805,0.00015893525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048242632,0.00017799866,0.011435656,0.000093577655,0.00003056382,0.0016228267,0.0003061468,0.8719371,0.09543037,0.0030870233,0.000792034,0.014604279],"study_design_scores_gemma":[0.000013654496,0.00014385613,0.0021524704,0.0000058684145,0.000005439812,0.00006190557,0.000029721434,0.99298006,0.004311704,0.00012985106,0.00015472593,0.000010853223],"about_ca_topic_score_codex":0.0045645298,"about_ca_topic_score_gemma":0.0022941008,"teacher_disagreement_score":0.0045645298,"about_ca_system_score_codex":0.00047884881,"about_ca_system_score_gemma":0.00040290307,"threshold_uncertainty_score":0.00907594},"labels":[],"label_agreement":null},{"id":"W3035747096","doi":"10.2514/6.2020-2810","title":"Development and Validation of a Compact Isokinetic Total Water Content Probe for Differentiating Mixed Phase Environments","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Wind tunnel; Evaporation; Icing; Materials science; Phase (matter); Liquid water content; Enhanced Data Rates for GSM Evolution; Environmental science; Remote sensing; Aerospace engineering; Meteorology; Engineering; Geology; Chemistry; Computer science; Physics","score_opus":0.05734235490632241,"score_gpt":0.27345746740845145,"score_spread":0.21611511250212903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035747096","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23589398,0.0007246513,0.75739473,0.00025089917,0.00011816337,0.0010086318,0.00047781967,0.0023773843,0.0017536873],"genre_scores_gemma":[0.49479535,0.00032629774,0.49982822,0.00015814732,0.0000253819,0.0006909061,0.00041625422,0.00017641137,0.0035830354],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988643,0.00016373083,0.000051206356,0.00024945883,0.00061322673,0.000058089234],"domain_scores_gemma":[0.9986808,0.00038809652,0.00013904263,0.00019103181,0.00052062556,0.000080389014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019678972,0.00054875715,0.000614152,0.0006784972,0.0002856138,0.00072523655,0.001528016,0.0011351682,0.0012366675],"category_scores_gemma":[0.0023865574,0.00032135105,0.0002624299,0.00037176855,0.0009811294,0.0012192461,0.0007192502,0.0005489659,0.00040884013],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001273762,0.00006323609,0.0010447918,0.00012293502,0.0000078810235,0.000050507744,0.00015914618,0.0019511853,0.95650554,0.0007287905,0.0003065991,0.038932055],"study_design_scores_gemma":[0.000057950998,0.001541372,0.006074914,0.00003342292,0.000028035649,0.0006324831,0.00015233236,0.04645783,0.93345654,0.00034577088,0.011154465,0.0000647678],"about_ca_topic_score_codex":0.0016169671,"about_ca_topic_score_gemma":0.0019168541,"teacher_disagreement_score":0.0019678972,"about_ca_system_score_codex":0.0006004605,"about_ca_system_score_gemma":0.0011182379,"threshold_uncertainty_score":0.010407329},"labels":[],"label_agreement":null},{"id":"W4287757067","doi":"10.2514/6.2020-2513","title":"Predicting the Propagation of Acoustic Waves using Deep Convolutional Neural Networks","year":2020,"lang":"en","type":"article","venue":"AIAA AVIATION 2020 FORUM","topic":"Acoustic Wave Phenomena Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Convolutional neural network; Computer science; Artificial neural network; Acoustics; Artificial intelligence; Speech recognition; Geology; Physics","score_opus":0.017284414875744232,"score_gpt":0.23128727615637157,"score_spread":0.21400286128062734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287757067","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29947516,0.00032722007,0.6943478,0.00029246902,0.000106459585,0.00003520367,0.00028200442,0.0016163255,0.0035173723],"genre_scores_gemma":[0.92322844,0.0001893803,0.072901644,0.000043973174,0.000021003241,0.00003575396,0.00034704708,0.00008691242,0.0031457997],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992347,0.000011742149,0.000004122129,0.000017526443,0.000029244035,0.00001384202],"domain_scores_gemma":[0.9996729,0.00016841643,0.000038495487,0.000029884115,0.0000670152,0.000023318873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029220796,0.0006398753,0.00024919095,0.0003123206,0.00022313386,0.00059766736,0.0006418068,0.00062355166,0.0008549307],"category_scores_gemma":[0.001114116,0.0003855871,0.00027610973,0.0002625728,0.00031008266,0.00079419214,0.0005567998,0.0009523269,0.00023040477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028532004,0.000022028593,0.0005159248,0.000012982563,0.000010496008,0.000024897736,0.000009747184,0.9796825,0.006153399,0.0010391454,0.00020534798,0.012294926],"study_design_scores_gemma":[3.7861008e-7,0.0000012911526,0.000026675536,2.952462e-7,3.3028e-7,6.4183865e-7,3.7247378e-7,0.99944085,0.000393748,0.00011442187,0.000020410056,5.643039e-7],"about_ca_topic_score_codex":0.009854652,"about_ca_topic_score_gemma":0.0109379515,"teacher_disagreement_score":0.009854652,"about_ca_system_score_codex":0.0006766272,"about_ca_system_score_gemma":0.0007219865,"threshold_uncertainty_score":0.01959455},"labels":[],"label_agreement":null}]}