{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":20,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":20,"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":"548c6572a53e","filters":{"venue":"AIAA Atmospheric Flight Mechanics Conference"}},"results":[{"id":"W2332806700","doi":"10.2514/6.2015-2558","title":"Aero structural modeling of a wing using CATIA V5 and XFLR5 software and experimental validation using the Price- Païdoussis wing tunnel","year":2015,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec","funders":"","keywords":"Wing; Software; Computer science; Simulation; Structural engineering; Aerospace engineering; Engineering; Aeronautics; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.04802658543943406,"gpt":0.2579645333508146,"spread":0.2099379479113805,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000205075,0.0002413459,0.0002499606,0.00000701317,0.0002848616,0.00007571972,0.0002592191,0.0001094002,0.00004149181],"category_scores_gemma":[0.00009929106,0.0001863929,0.00003181528,0.0002589488,0.0001467657,0.0005459333,0.0004486922,0.0001558238,0.000001296065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001689234,"about_ca_system_score_gemma":0.00004343566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003688624,"about_ca_topic_score_gemma":0.00001072825,"domain_scores_codex":[0.9986113,0.00005678961,0.0002982717,0.000414833,0.0003146883,0.0003041189],"domain_scores_gemma":[0.9993297,0.00005168072,0.0001908825,0.0002916486,0.00003979777,0.00009627824],"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":[0.00008093649,0.00005934386,0.006676299,0.00005691732,0.00007114915,0.00001632479,0.009869059,0.2864504,0.6769318,0.00446574,0.00001075215,0.01531128],"study_design_scores_gemma":[0.0003069591,0.00006444364,0.00008406263,0.00005467429,0.00003269251,0.00004055888,0.003706338,0.959349,0.0261959,0.009899396,0.00001140086,0.0002545344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6193621,0.0002609294,0.3800108,0.00002726611,0.00007309221,0.000174715,0.00000144275,0.00005811612,0.00003155334],"genre_scores_gemma":[0.8209419,0.00002495381,0.1789549,0.00002948131,0.00001188045,0.000007018229,0.000001458337,0.00001904493,0.000009322426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6728987,"threshold_uncertainty_score":0.7600881,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2081436025","doi":"10.2514/6.2012-4639","title":"Design and Experimental Validation of a Control System for a Morphing Wing","year":2012,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aeroelasticity and Vibration Control","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Morphing; Wing; Computer science; Aerospace engineering; Computer graphics (images); Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01827543334343302,"gpt":0.2113302311860645,"spread":0.1930547978426315,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002618471,0.000162772,0.0002609146,0.000006096628,0.00007980909,0.00003795633,0.00009140382,0.00008781384,0.00002600211],"category_scores_gemma":[0.00003084362,0.000163456,0.0000402818,0.00007948042,0.00001138969,0.0003552003,0.00001570231,0.00006472653,0.000004579393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005304018,"about_ca_system_score_gemma":0.00002223452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004083137,"about_ca_topic_score_gemma":2.047852e-7,"domain_scores_codex":[0.9991571,0.00004717796,0.0002783474,0.0001328521,0.0001250948,0.0002594295],"domain_scores_gemma":[0.9994298,0.0001988663,0.00008244844,0.0001232023,0.00007283635,0.00009287746],"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":[0.0001372684,0.00006633466,0.00007103296,0.0003653548,0.0001765247,0.000001050522,0.00259398,0.1083231,0.7913446,0.09550847,0.00007698345,0.001335279],"study_design_scores_gemma":[0.0007916512,0.00007037921,0.000005807868,0.00005549129,0.00004330693,0.00000523581,0.0003468631,0.7425216,0.2558805,0.00008438055,0.0000587147,0.0001360408],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07658247,0.000491016,0.9217528,0.00001559321,0.0003869826,0.0005440647,0.000005188129,0.0001490389,0.00007281395],"genre_scores_gemma":[0.9546067,0.000007621881,0.04511131,0.00001845151,0.00007263052,0.0001452616,0.000003362142,0.00002627656,0.000008370458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8780242,"threshold_uncertainty_score":0.6665543,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2171845426","doi":"10.2514/6.2009-5938","title":"New Identification Method Based on Neural Network for Helicopters from Flight Test Data","year":2009,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Flight test; Identification (biology); Artificial neural network; Computer science; Test (biology); Artificial intelligence; Simulation; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.02160724213896558,"gpt":0.252395968874714,"spread":0.2307887267357485,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000214102,0.0003264403,0.0003425707,0.00001074351,0.0001243182,0.0001197682,0.0009667083,0.0002553228,0.0002074865],"category_scores_gemma":[0.0001321333,0.0003331915,0.00007083948,0.0004087253,0.00000880556,0.0002670337,0.00005667646,0.000240954,0.00008951096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006814788,"about_ca_system_score_gemma":0.00007306403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004241012,"about_ca_topic_score_gemma":0.00003921492,"domain_scores_codex":[0.9982554,0.00003225944,0.0004106122,0.0006215338,0.00022759,0.0004526369],"domain_scores_gemma":[0.9980667,0.0002551949,0.0001389115,0.001317312,0.00008665105,0.0001352718],"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":[0.00009773792,0.0001573304,0.0001285061,0.00004945524,0.0001168387,0.00001280484,0.000205711,0.2221281,0.05804505,0.05421646,0.09439774,0.5704443],"study_design_scores_gemma":[0.0005164378,0.0001619914,0.0002475393,0.00004123856,0.00005608976,9.479883e-7,0.00002116053,0.9646878,0.0111028,0.01050373,0.01230172,0.0003584919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001409237,0.0002038112,0.9935513,0.002426979,0.0008422201,0.0004567437,0.0001008784,0.0007887433,0.0002201128],"genre_scores_gemma":[0.6422266,0.00009164349,0.3553583,0.001018367,0.0003084044,0.00004076232,0.0005644541,0.0000544196,0.0003370883],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7425597,"threshold_uncertainty_score":0.999912,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1997117988","doi":"10.2514/6.2014-2187","title":"Control strategies for an experimental morphing wing model","year":2014,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aeroelasticity and Vibration Control","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec","funders":"","keywords":"Morphing; Wing; Computer science; Control (management); Artificial intelligence; Engineering; Aerospace engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02040630956541888,"gpt":0.2280964220723011,"spread":0.2076901125068822,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001892288,0.0002905294,0.0003261908,0.000006478598,0.0001896746,0.0002376878,0.0002987435,0.000154354,0.00007456452],"category_scores_gemma":[0.00003053656,0.000299161,0.00008241673,0.00008413543,0.00002005341,0.0008010046,0.00002190579,0.0001700922,0.00001894103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004104545,"about_ca_system_score_gemma":0.00007374076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001217945,"about_ca_topic_score_gemma":0.0000233265,"domain_scores_codex":[0.9987172,0.00003797773,0.0003162562,0.0003211965,0.0001936319,0.0004137157],"domain_scores_gemma":[0.9992671,0.0001151392,0.00006178714,0.0002955437,0.0001051161,0.0001553266],"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":[0.00003109278,0.00002775753,0.000001383485,0.00002418522,0.00002810376,4.415224e-7,0.0004572151,0.4959759,0.1342095,0.3680561,0.0001295646,0.001058724],"study_design_scores_gemma":[0.001108339,0.0002253391,0.000001563962,0.00002229078,0.00002758747,0.000002198992,0.0003528431,0.9735637,0.01008549,0.0136793,0.0005765752,0.0003547319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04987485,0.00006760439,0.947372,0.00006695341,0.0003935165,0.0003835369,0.00001182403,0.0004907823,0.001338919],"genre_scores_gemma":[0.9671156,0.000006218333,0.03209786,0.0003269405,0.0001650948,0.0001773388,0.0000132345,0.00005817053,0.00003957533],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9172407,"threshold_uncertainty_score":0.9999461,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1974879620","doi":"10.2514/6.2009-6046","title":"New Methodologies for Aircraft Stability Derivatives Determination from Its Geometrical Data","year":2009,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Stability (learning theory); Aerospace engineering; Engineering; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.100602529217477,"gpt":0.3010768837643213,"spread":0.2004743545468443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002739628,0.0002646041,0.0003820795,0.00001575365,0.00008367086,0.00006567356,0.0008672633,0.0002821131,0.0002668712],"category_scores_gemma":[0.00101894,0.0002594253,0.00005529018,0.0005410501,0.00001623343,0.0004840473,0.0001433627,0.0002095147,0.00002919185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007874526,"about_ca_system_score_gemma":0.00008180159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001744447,"about_ca_topic_score_gemma":0.00002489199,"domain_scores_codex":[0.9985089,0.00005394814,0.0003534807,0.0005289764,0.0001917417,0.0003629621],"domain_scores_gemma":[0.9983131,0.0005113715,0.00009915311,0.0008273757,0.0001499751,0.000098991],"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":[0.0000491493,0.00006542257,0.0001112498,0.0000526629,0.00009317267,0.000005105213,0.0005737154,0.0005218914,0.1070156,0.04710242,0.003948181,0.8404614],"study_design_scores_gemma":[0.0006404657,0.0002578401,0.001035612,0.00002747245,0.00006357719,0.000001914734,0.0002639215,0.7107521,0.1808843,0.09837303,0.007149923,0.000549846],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02102569,0.0006415325,0.9756101,0.0009923734,0.0003484215,0.0003890649,0.00007802416,0.0007985457,0.0001162386],"genre_scores_gemma":[0.5621556,0.0002586246,0.4372335,0.00008834088,0.00005777787,0.00001955886,0.000100371,0.00001856137,0.00006772605],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8399116,"threshold_uncertainty_score":0.9999858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2570923155","doi":"10.2514/6.2017-0937","title":"Cessna Citation X Stall Characteristics Identification from Flight Data using Neural Networks","year":2017,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec","funders":"","keywords":"Artificial neural network; Stall (fluid mechanics); Computer science; Identification (biology); Aerospace engineering; Artificial intelligence; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04504115603311332,"gpt":0.2539877969525385,"spread":0.2089466409194252,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001748969,0.0002920477,0.0003253265,0.00001025695,0.0004112375,0.0004925188,0.001508692,0.0002882158,0.0001636137],"category_scores_gemma":[0.0001245996,0.0003173396,0.00004171274,0.0001404399,0.00004729207,0.001026,0.0003577651,0.0003175112,0.00005413248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007664273,"about_ca_system_score_gemma":0.00003788779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001061332,"about_ca_topic_score_gemma":0.00008227099,"domain_scores_codex":[0.9983641,0.00003252589,0.0004645126,0.0005216564,0.000244054,0.0003731735],"domain_scores_gemma":[0.997251,0.00004659219,0.0003962684,0.002043728,0.000168373,0.00009400756],"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":[0.0001269287,0.0003383358,0.008474526,0.0003405682,0.0009882807,0.0001817653,0.002209514,0.08488181,0.4368198,0.1149229,0.005434048,0.3452816],"study_design_scores_gemma":[0.0002274773,0.00001517197,0.003171212,0.00003662869,0.00006650675,0.00000246094,0.00007013531,0.9909614,0.00209593,0.001980746,0.001021081,0.0003512119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.295915,0.0001688345,0.701249,0.0002210563,0.001670166,0.0001930088,0.00009810573,0.0003835634,0.00010131],"genre_scores_gemma":[0.9911739,0.0004029666,0.007414489,0.00005179052,0.0002185763,0.0000157832,0.0005707882,0.00005843608,0.00009322151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9060796,"threshold_uncertainty_score":0.9999279,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2621291201","doi":"10.2514/6.2017-3893","title":"Adaptive State Estimation for Flight Path Reconstruction and Aircraft System Identification","year":2017,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Identification (biology); Path (computing); Computer science; State (computer science); Estimation; Adaptive system; Aerospace engineering; Control theory (sociology); Artificial intelligence; Engineering; Algorithm; Systems engineering; Control (management)","retraction":null,"screen_n_in":null,"score":{"opus":0.01069712351549414,"gpt":0.2056617947124012,"spread":0.194964671196907,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001734586,0.0002027368,0.0002384228,0.00001049043,0.000399965,0.0001950136,0.0002457474,0.0001682303,0.00001207447],"category_scores_gemma":[0.00005964804,0.0002109389,0.00004095958,0.00006900917,0.00004201679,0.0005223023,0.00004610887,0.0001230876,0.00003361341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075346,"about_ca_system_score_gemma":0.0000335311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001989578,"about_ca_topic_score_gemma":0.00002786853,"domain_scores_codex":[0.9989873,0.00001644406,0.0003147907,0.0003195839,0.0001220811,0.0002397641],"domain_scores_gemma":[0.9989733,0.00003213631,0.0002526359,0.000495046,0.0001820222,0.00006491953],"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":[0.00006430454,0.00003614396,0.0002841211,0.0006156925,0.0002066958,0.000008306731,0.001035147,0.005986356,0.0420639,0.4213071,0.0008250003,0.5275672],"study_design_scores_gemma":[0.0003622105,0.00006356868,0.0003732786,0.0001056631,0.00003728988,0.000017472,0.0002961842,0.9682867,0.01850855,0.01136923,0.0003281422,0.0002517046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06601415,0.0001212639,0.931527,0.0001908632,0.0008603301,0.0004899105,0.00002569845,0.0005240802,0.0002467547],"genre_scores_gemma":[0.9625187,0.0002020057,0.0367847,0.000008566452,0.00002983131,0.0001653606,0.0000150456,0.0000326199,0.0002431969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9623004,"threshold_uncertainty_score":0.8601838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2145685177","doi":"10.2514/6.2010-7927","title":"Investigating Nonlinear Control Architecture Options for Aerial Refueling","year":2010,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Architecture; Computer science; Nonlinear system; Control (management); Artificial intelligence; Physics; Geography; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.007067249848769476,"gpt":0.1952424593512914,"spread":0.188175209502522,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002955806,0.0003804783,0.0004401192,0.00001100807,0.0001847277,0.0001388076,0.0003792466,0.0002898041,0.00006866761],"category_scores_gemma":[0.0002186112,0.0003741074,0.0001453382,0.000215477,0.00002689237,0.00011945,0.0000296833,0.0006241551,0.00003353846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004548012,"about_ca_system_score_gemma":0.00008400454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002680198,"about_ca_topic_score_gemma":0.00009878004,"domain_scores_codex":[0.9983844,0.00002616074,0.0004235134,0.0003633926,0.0002206275,0.0005819181],"domain_scores_gemma":[0.9988684,0.0001638104,0.00008687836,0.0004702068,0.000169447,0.0002412666],"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":[0.00002222343,0.00003019942,0.0000388411,0.0002253319,0.0001794948,0.000004189395,0.0005963043,0.252859,0.6695364,0.06730963,0.0004441014,0.008754364],"study_design_scores_gemma":[0.00114468,0.00006250276,0.00001221353,0.00006617718,0.00005115769,0.00001539678,0.0000542274,0.9758024,0.002856158,0.002217566,0.0172529,0.0004646617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08543063,0.0002166606,0.9085134,0.0002727516,0.003545913,0.0006530143,0.00005177556,0.0009754208,0.0003404703],"genre_scores_gemma":[0.8771933,0.00001998865,0.1212507,0.00007283922,0.000911359,0.0002787774,0.00002143136,0.0000996947,0.0001519781],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7917627,"threshold_uncertainty_score":0.9998711,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2620786698","doi":"10.2514/6.2017-3550","title":"Method to Calculate Cessna Citation X Aircraft Climb and Cruise Trajectory using an Aero-Propulsive Model","year":2017,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec","funders":"Korea Disease Control and Prevention Agency","keywords":"Climb; Cruise; Trajectory; Aerospace engineering; Aeronautics; Computer science; Marine engineering; Engineering; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.04142971159560006,"gpt":0.2795425835963596,"spread":0.2381128720007595,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002530937,0.0002966146,0.0002872298,0.00001780357,0.0003750236,0.0002939164,0.0003792404,0.0001458798,0.00005532543],"category_scores_gemma":[0.0000306943,0.0003134289,0.00004539052,0.0001268452,0.00002042726,0.0006700029,0.0001073698,0.000151464,0.00001142541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007450527,"about_ca_system_score_gemma":0.00003826118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005199285,"about_ca_topic_score_gemma":0.00008077646,"domain_scores_codex":[0.998636,0.00004992939,0.0002848235,0.0004457624,0.0002329711,0.0003505161],"domain_scores_gemma":[0.9989716,0.00002309237,0.0001152842,0.000540557,0.0001497109,0.0001997136],"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":[0.00002167168,0.0000239036,0.00002107934,0.00007071639,0.00004093401,0.000007166286,0.001083238,0.9560575,0.005565064,0.009862828,0.00005800943,0.02718791],"study_design_scores_gemma":[0.0003344466,0.00007389481,0.000141155,0.00005042603,0.00007501902,0.000001892329,0.0001788993,0.9955329,0.001043035,0.001989839,0.0001761763,0.000402312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1151192,0.00005264969,0.882893,0.00008771776,0.0002551338,0.0004110533,0.000004801794,0.0002477998,0.0009286763],"genre_scores_gemma":[0.6203686,0.00008012378,0.3792122,0.00006510731,0.00003806699,0.00002422516,0.00001063523,0.00004330859,0.0001576895],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5052494,"threshold_uncertainty_score":0.9999318,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2329707621","doi":"10.2514/6.2011-6208","title":"SUPPRESSION OF BENDING-TORSION FLUTTER IN ACCELERATED FLIGHT WITH AERO-SERVO-VISCOELASTIC CONTROLS","year":2011,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Flutter; Viscoelasticity; Torsion (gastropod); Control theory (sociology); Structural engineering; Servomotor; Aeroelasticity; Materials science; Computer science; Physics; Aerodynamics; Mechanics; Engineering; Mechanical engineering; Composite material; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.01612436115444472,"gpt":0.1870316428171978,"spread":0.1709072816627531,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002671863,0.000469309,0.0007885611,0.00002891882,0.00005794646,0.00005453269,0.0005901214,0.0002942037,0.0005842186],"category_scores_gemma":[0.00002851069,0.0003711255,0.0001045757,0.0004855562,0.00002608088,0.0003025555,0.00009643798,0.0003667771,0.00005022532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001217493,"about_ca_system_score_gemma":0.00007028018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001603708,"about_ca_topic_score_gemma":0.0001690547,"domain_scores_codex":[0.9975796,0.00008872306,0.0007831933,0.0004825553,0.0004363539,0.0006295975],"domain_scores_gemma":[0.9987789,0.00007993379,0.0002060499,0.0005444576,0.0001850731,0.0002055965],"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":[0.001401001,0.0007995922,0.002499684,0.000737854,0.0006164932,0.0003096681,0.002501473,0.01200145,0.7780604,0.1916365,0.0004901066,0.008945699],"study_design_scores_gemma":[0.002596512,0.0005392717,0.0007768964,0.0006833582,0.00008013233,0.00001444461,0.0001379764,0.9669908,0.02488053,0.002134665,0.0005000678,0.000665295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6636166,0.0003937563,0.3282401,0.00006762761,0.001345591,0.001048239,0.0000228807,0.0003507533,0.0049145],"genre_scores_gemma":[0.9959174,0.00009181589,0.003579685,0.00004429399,0.00004663966,0.00009238256,0.00001479745,0.00008096766,0.0001319717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9549894,"threshold_uncertainty_score":0.9998741,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2312715718","doi":"10.2514/6.2012-4418","title":"Simulation Tool for Testing and Validating UAV Autopilots in Wind Gust Environments","year":2012,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Reliability engineering; Environmental science; Meteorology; Aerospace engineering; Systems engineering; Simulation; Aeronautics; Engineering; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.03200544260348995,"gpt":0.2426186299421155,"spread":0.2106131873386255,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003494223,0.0002116269,0.0002090512,0.000003788389,0.0002105556,0.0000417792,0.0001442387,0.00008088176,0.0002600602],"category_scores_gemma":[0.0003330848,0.0001975515,0.00002896951,0.0001816314,0.00004103097,0.0004373815,0.0002468464,0.0001054538,0.00006352139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001071542,"about_ca_system_score_gemma":0.000008816635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005950176,"about_ca_topic_score_gemma":0.000008812065,"domain_scores_codex":[0.9986102,0.0000412992,0.0002872608,0.0003503848,0.0002193084,0.0004915571],"domain_scores_gemma":[0.9992354,0.0003735407,0.0001174759,0.0001760225,0.000007992345,0.00008955746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000541859,0.0005147316,0.6185191,0.0001096196,0.00005647004,0.000007986167,0.005206311,0.07398435,0.06774338,0.005998058,0.0002076166,0.2275982],"study_design_scores_gemma":[0.0009404593,0.0001664172,0.1105159,0.00009093849,0.00003936496,0.000003643365,0.0002365443,0.8735747,0.002115198,0.003260113,0.008411474,0.0006452423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9393535,0.0001059254,0.05880593,0.00009914226,0.000215559,0.0005167825,0.000004929894,0.00004200307,0.0008562118],"genre_scores_gemma":[0.9650716,0.00001893024,0.03424147,0.000127864,0.00006983554,0.00003685823,0.000003459247,0.00001963595,0.0004103676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7995903,"threshold_uncertainty_score":0.8055917,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2320183949","doi":"10.2514/6.2014-0194","title":"Development of a Flight Data System and Experimental Determination of Aerodynamic Loads on a Wing Spar","year":2014,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spar; Wing; Aerodynamics; Aerospace engineering; Aeronautics; Fixed wing; Wing loading; Marine engineering; Airplane; Computer science; Engineering; Structural engineering; Angle of attack","retraction":null,"screen_n_in":null,"score":{"opus":0.01485266031525488,"gpt":0.2155883674947067,"spread":0.2007357071794518,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001856132,0.0001850001,0.0003169667,0.00001431472,0.00004930924,0.00001356154,0.000349288,0.0001294106,0.00001743128],"category_scores_gemma":[0.00002302155,0.0001828765,0.00001976356,0.00015658,0.00002369178,0.0001332445,0.0001534282,0.00009150809,0.000009475466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006878276,"about_ca_system_score_gemma":0.00003507754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000610557,"about_ca_topic_score_gemma":0.00002055147,"domain_scores_codex":[0.9989369,0.00002364121,0.0003847525,0.0002805526,0.0001939974,0.0001801728],"domain_scores_gemma":[0.9992015,0.00003800358,0.0001472331,0.0005113831,0.00005652147,0.00004531127],"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":[0.00003308184,0.0001162871,0.0001032795,0.0006998287,0.00009445074,0.000003787171,0.0025884,0.0006733814,0.8276782,0.1185113,0.00006437577,0.04943359],"study_design_scores_gemma":[0.0003230452,0.00009269234,0.00006770939,0.0002063253,0.00001669289,0.000003970998,0.0005760278,0.6973404,0.3005779,0.00007324237,0.0005305175,0.0001914065],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6211883,0.000128253,0.377391,0.00001666085,0.0002006706,0.0001751602,0.000007029084,0.0001786411,0.0007142597],"genre_scores_gemma":[0.9499093,0.00001999547,0.04996744,0.000007634932,0.000011263,0.00001754005,0.00001935741,0.00002302814,0.00002439824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6966671,"threshold_uncertainty_score":0.7457488,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2314639152","doi":"10.2514/6.2009-5709","title":"Adaptive Spatial Filtering for Aeroservoelastic Response Suppression","year":2009,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Structural Health Monitoring Techniques","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":"Canadian Standards Association","funders":"National Aeronautics and Space Administration","keywords":"Computer science; Adaptive filter; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.02192212459707356,"gpt":0.2564252606918286,"spread":0.2345031360947551,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002221989,0.0003515347,0.00034132,0.00001300811,0.0001539486,0.00006099347,0.0004095626,0.0002122276,0.0001138453],"category_scores_gemma":[0.0001269881,0.0003435248,0.0000855042,0.0001950671,0.00001407999,0.0002013874,0.00005429623,0.0002632293,0.00002889456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002059103,"about_ca_system_score_gemma":0.00007024209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002306008,"about_ca_topic_score_gemma":0.000005275871,"domain_scores_codex":[0.9983442,0.00006150702,0.0003878753,0.0003812844,0.0002412263,0.0005838363],"domain_scores_gemma":[0.9988945,0.0002521553,0.00008053375,0.0004416573,0.0001503902,0.000180829],"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":[0.002866454,0.00006770553,0.00002026853,0.0002843025,0.00007445681,0.0000479614,0.001408384,0.008630523,0.3538184,0.02229988,0.002480293,0.6080014],"study_design_scores_gemma":[0.0005895567,0.001038441,0.001763572,0.0003028119,0.00002822857,0.00001656416,0.00005370491,0.8570777,0.1183207,0.01708099,0.003100004,0.0006278062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2172453,0.00009809949,0.7786357,0.0001606222,0.001626138,0.0006903025,0.00001100259,0.001361037,0.0001717503],"genre_scores_gemma":[0.8886532,0.0000656155,0.1107886,0.00006915056,0.0001756747,0.0001103743,0.00000778003,0.00005001471,0.0000796004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8484471,"threshold_uncertainty_score":0.9999017,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2316523013","doi":"10.2514/6.2010-8120","title":"Application of Artificial Neural Networks in Aerodynamics Prediction of Low-Reynolds-Number Figure-Eight Motion of an Airfoil","year":2010,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Biomimetic flight and propulsion mechanisms","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":"Airfoil; Aerodynamics; Lift (data mining); Reynolds number; Flapping; Computational fluid dynamics; Artificial neural network; Lift coefficient; Aerodynamic center; Computer science; Mechanics; Angle of attack; Aerospace engineering; Physics; Artificial intelligence; Engineering; Pitching moment; Wing; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.006208581933427092,"gpt":0.1960390210874378,"spread":0.1898304391540107,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003483685,0.0002656902,0.0004488035,0.00002542271,0.00003324687,0.00001386023,0.0003582673,0.0004446034,0.0002166561],"category_scores_gemma":[0.00002551116,0.0002664115,0.00009038179,0.0006014961,0.00005032728,0.0002176332,0.00004747342,0.0004059563,0.000006258518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000333255,"about_ca_system_score_gemma":0.00003403156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001055784,"about_ca_topic_score_gemma":0.0002260408,"domain_scores_codex":[0.998127,0.00006292074,0.0008710498,0.0003285147,0.0003223894,0.0002881249],"domain_scores_gemma":[0.9987637,0.00004633168,0.0002894301,0.0005653889,0.0002400577,0.00009502716],"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":[0.00009516518,0.0002809338,0.0005147083,0.0002860482,0.00003575312,0.000002055289,0.0003297543,0.04117599,0.8146053,0.05825064,0.0000197188,0.08440394],"study_design_scores_gemma":[0.0002926252,0.0001045,0.0007198056,0.00004081554,0.00002749521,0.00000343439,0.0000354048,0.8457844,0.1481296,0.004659942,0.00003091055,0.0001711523],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5662642,0.0000222458,0.4323225,0.00001772412,0.0008338604,0.0002873342,0.00002921079,0.00006632718,0.0001566507],"genre_scores_gemma":[0.9870073,0.00004908715,0.01265689,0.000008611971,0.00007618851,0.0000404179,0.0001037144,0.00004188618,0.00001587062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8046083,"threshold_uncertainty_score":0.9999788,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2323114621","doi":"10.2514/6.2016-1039","title":"Parameter Estimation for Extending Flight Models into Post-Stall Regime - Invited","year":2016,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Stall (fluid mechanics); Computer science; Aerospace engineering; Control theory (sociology); Engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.01323486928820713,"gpt":0.2118193759571609,"spread":0.1985845066689537,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001481596,0.0003354187,0.0003439058,0.0000226908,0.000122014,0.00006416983,0.0003778505,0.0003237842,0.0001190223],"category_scores_gemma":[0.0001522807,0.0002680405,0.0001033576,0.0002821807,0.00003379311,0.0006196746,0.00007823885,0.000141739,0.00009387433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001595316,"about_ca_system_score_gemma":0.00003731604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001475111,"about_ca_topic_score_gemma":0.0000197389,"domain_scores_codex":[0.9984556,0.0000234598,0.0003978376,0.0004332104,0.0002019631,0.0004878817],"domain_scores_gemma":[0.9988296,0.0001836389,0.000124083,0.000520957,0.0002262241,0.0001155181],"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":[0.00005817055,0.00006010079,0.00001380465,0.0001633899,0.0001611091,0.00001017616,0.0008378908,0.008493607,0.3373351,0.4660202,0.003681546,0.1831649],"study_design_scores_gemma":[0.0005326351,0.0001250831,0.000006300792,0.00009908032,0.00003290894,0.000005930876,0.00005674644,0.8029064,0.04045568,0.1515411,0.003828698,0.000409427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03348312,0.000199426,0.9619185,0.002355926,0.0004413617,0.0004788239,0.00001915508,0.0009534379,0.0001503051],"genre_scores_gemma":[0.8646992,0.0002568781,0.1339842,0.0002807187,0.00004172717,0.0002223496,0.00002872713,0.00007541585,0.0004107031],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8312162,"threshold_uncertainty_score":0.9999772,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2329567341","doi":"10.2514/6.2015-0525","title":"Spatial Parameterization of Blunt Body Dynamics under Parachutes","year":2015,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace Engineering and Energy Systems","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":"Lockheed Martin (Canada)","funders":"","keywords":"Dynamics (music); Computer science; Blunt; Physics; Acoustics; Materials science","retraction":null,"screen_n_in":null,"score":{"opus":0.01370122961902668,"gpt":0.1897125428052777,"spread":0.176011313186251,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001605079,0.0002776513,0.000363099,0.000009935813,0.00003031102,0.00004218625,0.0002550537,0.000184481,0.00003203217],"category_scores_gemma":[0.00004208027,0.0002775125,0.00006283789,0.0002826118,0.00002047304,0.0001455925,0.00004659,0.000154481,0.00003475033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000153278,"about_ca_system_score_gemma":0.00006992994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002443855,"about_ca_topic_score_gemma":0.00009070955,"domain_scores_codex":[0.9987254,0.00003482039,0.0003775353,0.0002348258,0.0003023417,0.000325101],"domain_scores_gemma":[0.9991344,0.00003986075,0.0000913249,0.0003966052,0.0001602212,0.0001776108],"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":[0.00001424839,0.00003892431,0.000171818,0.0001120802,0.0001078282,0.00000635381,0.0004037908,0.8834264,0.006341443,0.1063537,0.0003418527,0.002681607],"study_design_scores_gemma":[0.0002938892,0.00009270598,0.00007944201,0.00005800035,0.00002737118,0.000007681643,0.000220714,0.9919129,0.004717381,0.001438189,0.0008371489,0.0003145454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0979855,0.0002034092,0.8986458,0.00004412407,0.001357386,0.0001232396,0.00001189741,0.0003977027,0.001230938],"genre_scores_gemma":[0.9912717,0.00007778495,0.008119592,0.00001351331,0.00007730152,0.00002876178,0.00005623474,0.00006307226,0.0002920268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8932862,"threshold_uncertainty_score":0.9999677,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2329898411","doi":"10.2514/6.2016-1040","title":"Semi-Analytical and Empirical Approaches to Aircraft Configuration Effects on Post-Stall Aerodynamics - Invited","year":2016,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","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":"University of Toronto","funders":"Federal Aviation Administration","keywords":"Aerodynamics; Stall (fluid mechanics); Aerospace engineering; Aeronautics; Computer science; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03141371735095647,"gpt":0.2158305245916163,"spread":0.1844168072406598,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001150327,0.0003127152,0.0003422071,0.00002069645,0.00007086206,0.00005384086,0.0002172038,0.0003123624,0.0000645547],"category_scores_gemma":[0.0001623459,0.0002387162,0.00005271625,0.0003081113,0.00003431503,0.0001476245,0.00007627666,0.0002075799,0.000167931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001112034,"about_ca_system_score_gemma":0.00003183715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005300942,"about_ca_topic_score_gemma":0.00002905153,"domain_scores_codex":[0.9986061,0.00004609116,0.0002799035,0.0004472734,0.0002276842,0.0003929688],"domain_scores_gemma":[0.999071,0.0002053055,0.00004946051,0.0003888381,0.00008236929,0.000203037],"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":[0.0001886522,0.0002217195,0.001140454,0.0003058635,0.0004077106,0.00008057247,0.001222596,0.002641954,0.3147624,0.4758264,0.007136168,0.1960654],"study_design_scores_gemma":[0.001505532,0.001181883,0.002213912,0.0002546839,0.0001216742,0.00002585501,0.0002001061,0.9011284,0.07425895,0.007985472,0.009829932,0.001293581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3978608,0.00004455151,0.5904505,0.009950592,0.0002249889,0.0004146798,0.0000127926,0.0005981573,0.0004430258],"genre_scores_gemma":[0.9947609,0.00007801448,0.003583765,0.001133505,0.00004340155,0.00006435456,0.0000139913,0.00004651171,0.000275586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8984864,"threshold_uncertainty_score":0.9734563,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2023354229","doi":"10.2514/6.2010-7799","title":"Identification and validation of a F/A-18 model Using Neural Networks","year":2010,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"National Aeronautics and Space Administration","keywords":"Artificial neural network; Identification (biology); Computer science; Artificial intelligence; Machine learning; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.02517809517330834,"gpt":0.2542183839559546,"spread":0.2290402887826463,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001312398,0.0001598797,0.000188039,0.000006257785,0.0001135427,0.00006664585,0.0001471029,0.00008132485,0.0003363909],"category_scores_gemma":[0.000005058364,0.0001554536,0.00005550842,0.0001718804,0.00003570029,0.0002372318,0.0000606071,0.0002523215,0.000001846247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000634354,"about_ca_system_score_gemma":0.000041915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004468708,"about_ca_topic_score_gemma":0.000002157267,"domain_scores_codex":[0.9990253,0.00003197629,0.0003140677,0.0002909786,0.0001430241,0.0001946044],"domain_scores_gemma":[0.9992148,0.00002285798,0.00024003,0.0002714842,0.0001623608,0.00008851098],"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":[0.0000325068,0.0001026301,0.0006659991,0.00001812271,0.00004562577,4.774539e-7,0.0002310717,0.4803103,0.2147251,0.2745786,0.0001388403,0.02915067],"study_design_scores_gemma":[0.000174804,0.00001378667,0.00001859438,0.000009100294,0.00003299757,0.000002322392,0.00004531338,0.9708052,0.01384228,0.0148801,0.00002637843,0.00014909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4820759,0.0000115869,0.5172685,0.00003874352,0.0002985131,0.0001068246,0.000002711616,0.00001710163,0.00018018],"genre_scores_gemma":[0.9940675,0.00001192302,0.005539584,0.00002208798,0.0001315226,0.0000128631,0.00001534585,0.0000177935,0.0001813213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5119917,"threshold_uncertainty_score":0.6339213,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2335327437","doi":"10.2514/6.2014-0382","title":"Fully-coupled 6 DoF Model for Unmanned Version of the SA160 General Aviation Aircraft","year":2014,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Aerospace and Aviation Technology","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":"Université de Sherbrooke","funders":"","keywords":"Aeronautics; Aerospace engineering; Aviation; Computer science; General aviation; Remotely operated underwater vehicle; Systems engineering; Engineering; Artificial intelligence; Mobile robot; Robot","retraction":null,"screen_n_in":null,"score":{"opus":0.007044731240504858,"gpt":0.1880229075947296,"spread":0.1809781763542247,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001490137,0.0001934189,0.0002521905,0.000007034062,0.0001023737,0.00001722506,0.0003902155,0.0002167084,0.00005690797],"category_scores_gemma":[0.00007732137,0.0001598186,0.0001082094,0.0002339416,0.00002307693,0.0001124343,0.00007075995,0.0001407577,0.00002080629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000608736,"about_ca_system_score_gemma":0.00004786356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001187103,"about_ca_topic_score_gemma":0.0000336062,"domain_scores_codex":[0.9990007,0.00002073572,0.0002892958,0.0002261116,0.0001933998,0.0002697306],"domain_scores_gemma":[0.9991698,0.00005591814,0.0001251724,0.0004367526,0.0001670441,0.0000453315],"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":[0.00005166046,0.00006672232,0.0001918183,0.0001792821,0.00009009527,2.915327e-7,0.0005290659,0.3284438,0.246112,0.4125098,0.003312164,0.008513368],"study_design_scores_gemma":[0.0005243001,0.00006339062,0.00006001774,0.00002475382,0.00003218608,6.266428e-7,0.00002777029,0.9403904,0.03360418,0.02432289,0.000771059,0.0001784477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1610342,0.00003499943,0.8373681,0.0004177248,0.0004122279,0.0003032299,0.000009940307,0.000223609,0.0001959545],"genre_scores_gemma":[0.9752407,0.00006056418,0.02377597,0.0001161993,0.00004117534,0.00005496093,0.00001341049,0.00003383186,0.0006631606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8142065,"threshold_uncertainty_score":0.6517215,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2326841541","doi":"10.2514/6.2010-8119","title":"The Unsteady Aerodynamics of Paired-Plunging Airfoils Using Computational Fluid Dynamics","year":2010,"lang":"en","type":"article","venue":"AIAA Atmospheric Flight Mechanics Conference","topic":"Fluid Dynamics and Turbulent Flows","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":"Toronto Metropolitan University","funders":"","keywords":"Aerodynamics; Airfoil; Computational fluid dynamics; Aerospace engineering; Dynamics (music); Computer science; Mechanics; Physics; Engineering; Acoustics","retraction":null,"screen_n_in":null,"score":{"opus":0.006781735603111834,"gpt":0.1931772432221913,"spread":0.1863955076190794,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003929561,0.0003858555,0.0003780667,0.00001555801,0.0002949967,0.0001340626,0.0006651006,0.0002246557,0.00006869182],"category_scores_gemma":[0.0000574839,0.000334343,0.0001479222,0.0004337134,0.00008805807,0.0001846905,0.0001346971,0.0005343409,0.00001782223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001383025,"about_ca_system_score_gemma":0.0001971852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000602022,"about_ca_topic_score_gemma":0.0003899416,"domain_scores_codex":[0.9979664,0.00004124473,0.0006409217,0.0003431945,0.0004525087,0.0005557087],"domain_scores_gemma":[0.9985391,0.0002377839,0.0001519069,0.0006137406,0.0003130065,0.0001444028],"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":[0.000009145918,0.00003032963,0.0001179386,0.00005423611,0.00009197636,0.000006221646,0.0001114144,0.5619267,0.0115693,0.4203047,0.00006340401,0.005714634],"study_design_scores_gemma":[0.0002806032,0.00003313341,0.00009097059,0.00004565211,0.0000440199,0.00002344863,0.00006175136,0.9898843,0.0002724147,0.008315883,0.0005744123,0.0003733716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4377765,0.0001970909,0.5577309,0.0001105409,0.002464957,0.0002896562,0.00005082134,0.0002590873,0.001120475],"genre_scores_gemma":[0.9662281,0.0001670249,0.03325748,0.00003044361,0.00006773222,0.00001492577,0.00005623373,0.00008155751,0.00009646003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5284516,"threshold_uncertainty_score":0.9999108,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}