{"meta":{"query_hash":"2a8861ba62c2","filters":{"venue":"Proceedings - IEEE Aerospace Conference"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/2a8861ba62c2","api":"https://metacan.xera.ac/api/v1/cohort?venue=Proceedings+-+IEEE+Aerospace+Conference"},"results":[{"id":"W1990324444","doi":"10.1109/aero.2008.4526425","title":"A Novel Precoder Design for OFDM Receivers in Unknown Fading Channels","year":2008,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"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 Toronto","funders":"","keywords":"Orthogonal frequency-division multiplexing; Pairwise error probability; Estimator; Precoding; Fading; Bit error rate; Channel (broadcasting); Computer science; Mean squared error; Minimum mean square error; Algorithm; Upper and lower bounds; Mathematics; Electronic engineering; Telecommunications; Statistics; Engineering; MIMO","score_opus":0.0866683532166508,"score_gpt":0.2690753940988212,"score_spread":0.1824070408821704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990324444","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.098725885,0.00015534104,0.8965998,0.00019180501,0.00018240993,0.0010621147,0.000006739381,0.0010714242,0.0020044576],"genre_scores_gemma":[0.8567187,0.0009952837,0.1411801,0.00003108278,0.000037203576,0.00062103284,0.0000028789273,0.000062866355,0.00035081577],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99873847,0.0000058801297,0.00030299765,0.00033481696,0.00015612124,0.00046169077],"domain_scores_gemma":[0.9991669,0.00013435038,0.00010081941,0.00020364563,0.00029800256,0.000096247786],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002191157,0.00028099527,0.0003238588,0.00018356834,0.00013503355,0.00005353116,0.00051704014,0.000161844,0.000011256528],"category_scores_gemma":[0.00014473118,0.00032497928,0.000053085834,0.00038619468,0.00010363493,0.0006544267,0.00004856829,0.00030958673,0.000008353298],"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":[0.000121942845,0.00017124064,0.0017419837,0.00050426036,0.0000690293,0.0000028268705,0.013449696,0.06643036,0.8962665,0.0077136103,0.0072468147,0.0062817116],"study_design_scores_gemma":[0.001144058,0.00013297526,0.00026514853,0.00046035025,0.000013111327,0.00003115157,0.0004297702,0.31711313,0.6740509,0.0017680293,0.0037496388,0.0008416919],"about_ca_topic_score_codex":0.0000123278505,"about_ca_topic_score_gemma":0.000008987368,"teacher_disagreement_score":0.75799286,"about_ca_system_score_codex":0.00019015279,"about_ca_system_score_gemma":0.00004797069,"threshold_uncertainty_score":0.99992025},"labels":[],"label_agreement":null},{"id":"W2018564725","doi":"10.1109/aero.2008.4526260","title":"The CloudSat Mission and the A-Train: A Revolutionary Approach to Observing Earth's Atmosphere","year":2008,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Space Agency; U.S. Air Force; California Institute of Technology; National Aeronautics and Space Administration","keywords":"Satellite; Remote sensing; Lidar; Constellation; Radar; Environmental science; Meteorology; Atmosphere (unit); Profiling (computer programming); Cloud computing; Satellite constellation; Computer science; Aerospace engineering; Geology; Geography; Engineering; Telecommunications; Physics","score_opus":0.022383981367608354,"score_gpt":0.2097406853633147,"score_spread":0.18735670399570634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018564725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95074385,0.00073085335,0.001909108,0.006124529,0.00015473244,0.00078034383,0.000001630839,0.00010633562,0.03944862],"genre_scores_gemma":[0.982592,0.0010379979,0.0070465454,0.00080643076,0.00010975924,0.000091273665,7.101264e-7,0.000028013246,0.008287274],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99792165,0.000036059897,0.0002780314,0.0006179826,0.0005606441,0.0005856158],"domain_scores_gemma":[0.9990936,0.00012708342,0.00015784564,0.00027559616,0.000067767396,0.0002780866],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005749461,0.00030716514,0.00027487206,7.184234e-7,0.0017881278,0.00012685476,0.0007199091,0.000113983275,0.0001323623],"category_scores_gemma":[0.00018319546,0.00017581652,0.00008273195,0.00041555235,0.0012128492,0.0002879382,0.000474689,0.00033960736,0.00012379717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016698372,0.0005132682,0.4974742,0.00020753869,0.00016701117,0.000021997887,0.058887217,0.0022653514,0.047611453,0.06572922,0.3013822,0.024070699],"study_design_scores_gemma":[0.0054847347,0.00063268386,0.6224354,0.00037160242,0.00015368054,0.00085481897,0.01813804,0.105666615,0.003517947,0.006738841,0.23329887,0.0027067682],"about_ca_topic_score_codex":0.0002722314,"about_ca_topic_score_gemma":0.000028337025,"teacher_disagreement_score":0.12496123,"about_ca_system_score_codex":0.00007566665,"about_ca_system_score_gemma":0.000041548996,"threshold_uncertainty_score":0.9995114},"labels":[],"label_agreement":null},{"id":"W2099115424","doi":"10.1109/aero.2002.1036878","title":"Discrete-space particle filters for reflecting diffusions","year":2003,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Pacific Institute for the Mathematical Sciences","keywords":"Discretization; Markov chain; Conditional probability distribution; State space; Particle filter; Mathematics; Filter (signal processing); Filtering problem; Boundary (topology); Markov process; Nonlinear filter; Stochastic differential equation; Amplitude; Noise (video); Applied mathematics; Algorithm; Mathematical analysis; Computer science; Kalman filter; Physics; Artificial intelligence; Statistics; Extended Kalman filter","score_opus":0.1985286500346553,"score_gpt":0.27603218853786865,"score_spread":0.07750353850321334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099115424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9547666,0.00017478412,0.016298337,0.0012699828,0.00036940683,0.0004692181,0.000036294186,0.00007350021,0.026541878],"genre_scores_gemma":[0.989839,0.00011030537,0.0049723275,0.00019680326,0.00005726381,0.00018503987,0.000005644547,0.00003546297,0.0045981165],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985351,0.000004866518,0.00041020976,0.0005552186,0.00004038438,0.00045423556],"domain_scores_gemma":[0.9992738,0.000060854793,0.00033403977,0.0001508136,0.000038656526,0.00014188494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000513272,0.00020211689,0.00030730417,0.00005391288,0.0002901566,0.00016667895,0.0001805609,0.000098333716,0.0003720451],"category_scores_gemma":[0.00032630595,0.0002375178,0.000104758066,0.00013775523,0.00008419646,0.00048061987,0.000031920637,0.00013106012,0.0003100265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025200123,0.00011107145,0.28279957,0.00006578594,0.00004545342,2.9554602e-7,0.003201786,0.00009793173,0.01750699,0.6932727,0.0026743074,0.00019888337],"study_design_scores_gemma":[0.01264133,0.0019905637,0.17893447,0.00042571774,0.00020094038,0.00005008681,0.02101503,0.091592826,0.2687204,0.30414942,0.11405054,0.006228698],"about_ca_topic_score_codex":0.00004257423,"about_ca_topic_score_gemma":0.0000141330975,"teacher_disagreement_score":0.38912332,"about_ca_system_score_codex":0.00015089462,"about_ca_system_score_gemma":0.000016819913,"threshold_uncertainty_score":0.9685695},"labels":[],"label_agreement":null},{"id":"W2114590489","doi":"10.1109/aero.2002.1036115","title":"Greedy adaptive Fano coding","year":2003,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Algorithms and Data Compression","field":"Computer Science","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":"Carleton University","funders":"","keywords":"Huffman coding; Computer science; Algorithm; Decoding methods; Greedy algorithm; Adaptive coding; Binary number; Binary code; Theoretical computer science; Coding (social sciences); Shannon–Fano coding; Data compression; Lossless compression; Mathematics","score_opus":0.03740021934181804,"score_gpt":0.24360750396902078,"score_spread":0.20620728462720275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114590489","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018322412,0.00014243001,0.935679,0.0005763733,0.00085871224,0.00033619528,0.0000068438267,0.0004892977,0.043588728],"genre_scores_gemma":[0.9188123,0.0000728739,0.079745024,0.00021013693,0.000071414506,0.00003797869,0.0000011811986,0.000017745546,0.001031386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978279,0.000020542815,0.0002612207,0.0008085739,0.00048728226,0.00059447635],"domain_scores_gemma":[0.99862075,0.000061054816,0.0002049294,0.00036224723,0.0004977246,0.00025328578],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003631201,0.0003122784,0.00029245927,0.00010207417,0.0003420184,0.00063572504,0.0012170628,0.00012166599,0.00006210546],"category_scores_gemma":[0.0001361141,0.00028397134,0.00006874162,0.000536537,0.00010395088,0.0018569017,0.00026559105,0.00032207437,0.00015915859],"study_design_candidate":"theoretical_or_conceptual","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":[0.00001412224,0.00009797959,0.0015906435,0.000037416547,0.000025159925,0.000013680091,0.0018427542,0.000009505169,0.028941017,0.9442399,0.0124144545,0.010773373],"study_design_scores_gemma":[0.0039661643,0.001505755,0.005812238,0.0011955022,0.000084400366,0.00043076163,0.0024810624,0.338587,0.48795915,0.068623476,0.08487515,0.004479347],"about_ca_topic_score_codex":0.000038141476,"about_ca_topic_score_gemma":0.000005028959,"teacher_disagreement_score":0.90048987,"about_ca_system_score_codex":0.000067697845,"about_ca_system_score_gemma":0.00014606697,"threshold_uncertainty_score":0.99996126},"labels":[],"label_agreement":null},{"id":"W2134756217","doi":"10.1109/aero.2008.4526516","title":"Target Localization from 3D data for On-Orbit Autonomous Rendezvous & Docking","year":2008,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Neptec Design Group (Canada)","funders":"","keywords":"Computer science; Rendezvous; Spacecraft; Computer vision; Point cloud; Artificial intelligence; Ranging; Pose; Real-time computing; Engineering","score_opus":0.0816552758887681,"score_gpt":0.2584139915629676,"score_spread":0.17675871567419954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134756217","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07897403,0.0001789646,0.9156995,0.00024685758,0.000803228,0.00059682655,0.00025484446,0.0008348919,0.0024108433],"genre_scores_gemma":[0.9703947,0.00033629203,0.027521236,0.00018947142,0.0003270201,0.00005040037,0.00073771813,0.000111633366,0.00033154682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980905,0.000007545856,0.00039413018,0.00067204214,0.00033989246,0.00049589184],"domain_scores_gemma":[0.9987719,0.00009184287,0.00013326817,0.00047064872,0.00036578492,0.00016657513],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015027986,0.00037208485,0.00037034147,0.00010962451,0.00030247562,0.00019376577,0.0005744779,0.00021648892,0.000071864066],"category_scores_gemma":[0.0001717912,0.00040044347,0.000052410523,0.00029164637,0.00008395292,0.0004893082,0.000066317734,0.0002375505,0.00006923253],"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":[0.00014882219,0.00020191076,0.0051741353,0.00042316504,0.00021061307,0.000011748721,0.0034611775,0.8370933,0.025981355,0.005360288,0.1184791,0.0034543953],"study_design_scores_gemma":[0.000594584,0.00007214313,0.0001735339,0.00013669733,0.000037482892,0.000011280487,0.00005508467,0.9504819,0.009879681,0.00053183315,0.037481897,0.0005439122],"about_ca_topic_score_codex":0.00007353263,"about_ca_topic_score_gemma":0.000036352605,"teacher_disagreement_score":0.89142066,"about_ca_system_score_codex":0.00013095715,"about_ca_system_score_gemma":0.00008171813,"threshold_uncertainty_score":0.99984473},"labels":[],"label_agreement":null},{"id":"W2145172950","doi":"10.1109/aero.2008.4526429","title":"Modeling and Interpretation of Multifunction Radars with Stochastic Grammar","year":2008,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Military Defense Systems Analysis","field":"Engineering","cited_by":10,"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 British Columbia","funders":"","keywords":"Computer science; Radar; SIGNAL (programming language); Estimator; Markov chain; Statistical signal processing; Artificial intelligence; Hidden Markov model; Representation (politics); Markov process; Algorithm; Signal processing; Machine learning; Mathematics; Statistics","score_opus":0.013938368914027168,"score_gpt":0.18650868891182057,"score_spread":0.1725703199977934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145172950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6761037,0.00014525343,0.32325926,0.000010643229,0.000052768395,0.00012989437,0.0000019862225,0.000108764216,0.00018769935],"genre_scores_gemma":[0.9972724,0.00007822493,0.0025102408,0.000003989459,0.00002357494,0.000022477772,0.0000023183584,0.00002715399,0.000059677175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911237,0.000004325794,0.00024473039,0.00024102489,0.00021385237,0.00018370646],"domain_scores_gemma":[0.9994465,0.000018763207,0.000058711255,0.0000879369,0.0003113902,0.00007668336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010154335,0.00018436159,0.00028839754,0.00012220281,0.00006612314,0.000021480335,0.00007736743,0.00006555675,0.000006521571],"category_scores_gemma":[0.000037063564,0.00016985163,0.00003470076,0.00022554908,0.00007767469,0.00033138707,0.0000123783375,0.00013545391,0.0000037589352],"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":[0.00014720092,0.000028917044,0.0035139914,0.0007346383,0.00023419008,0.0000035125895,0.0154594015,0.9090642,0.06795727,0.00045847398,0.00013580723,0.0022624333],"study_design_scores_gemma":[0.00027168874,0.000071489616,0.00022298218,0.00017075978,0.000052215437,0.00003713289,0.0008805203,0.99657863,0.0014951112,0.000035152596,0.000003147699,0.00018116702],"about_ca_topic_score_codex":0.00019001888,"about_ca_topic_score_gemma":0.00007685349,"teacher_disagreement_score":0.3211686,"about_ca_system_score_codex":0.00003908764,"about_ca_system_score_gemma":0.000019939209,"threshold_uncertainty_score":0.6926349},"labels":[],"label_agreement":null},{"id":"W2158262607","doi":"10.1109/aero.2002.1035656","title":"Antenna and phased array implementations using engineered substrates","year":2003,"lang":"en","type":"article","venue":"Proceedings - IEEE Aerospace Conference","topic":"Microwave Engineering and Waveguides","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":"University of Manitoba","funders":"","keywords":"Phased array; Phase shift module; Materials science; Dielectric; Microstrip; Microstrip antenna; Antenna (radio); Optoelectronics; Substrate (aquarium); Etching (microfabrication); Extremely high frequency; Phase (matter); Electronic engineering; Optics; Electrical engineering; Insertion loss; Engineering; Physics; Nanotechnology","score_opus":0.03223960101909893,"score_gpt":0.24981747409918542,"score_spread":0.2175778730800865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158262607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8698653,0.0005235125,0.12643595,0.00003122879,0.00026178203,0.00019024668,0.000016871682,0.00042006245,0.0022550616],"genre_scores_gemma":[0.98863655,0.00018542049,0.0109521,0.000012762361,0.000048894577,0.000020169444,0.0000035838796,0.000051611187,0.000088910485],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99892455,0.0000040422733,0.00024012823,0.00026947638,0.00012501451,0.00043677856],"domain_scores_gemma":[0.9995277,0.000031113435,0.000039884755,0.000093337985,0.00015018757,0.00015776668],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014833856,0.0002858707,0.00023105202,0.0001100203,0.00010802781,0.00019280518,0.00010870019,0.00008178718,0.000053184125],"category_scores_gemma":[0.000057464105,0.00030844143,0.00003832424,0.0002577943,0.00005385582,0.00029310666,0.0000040785303,0.0001864755,0.000007845134],"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":[0.0000016968254,0.000009453467,0.0010754345,0.000110632776,0.000033574208,7.604e-7,0.00060918124,0.000345193,0.9951985,0.002373089,0.00018161317,0.000060879454],"study_design_scores_gemma":[0.0005710302,0.000038097132,0.00056717504,0.00011386655,0.000044953504,0.00005615914,0.0008559384,0.01968255,0.9757998,0.0002822302,0.0014456778,0.00054252933],"about_ca_topic_score_codex":0.000012536172,"about_ca_topic_score_gemma":0.0000048291254,"teacher_disagreement_score":0.11877126,"about_ca_system_score_codex":0.000047796006,"about_ca_system_score_gemma":0.00003069253,"threshold_uncertainty_score":0.99993676},"labels":[],"label_agreement":null}]}