{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":8,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":8,"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","author_layer_release":"2026-06-26"},"query_hash":"7e39c9b3d563","filters":{"venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)"}},"results":[{"id":"W3192778027","doi":"10.1109/wacv51458.2022.00016","title":"Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Deblurring; Computer science; Artificial intelligence; Computer vision; Task (project management); Autofocus; Pixel; Image (mathematics); Image quality; Reflection (computer programming); Image restoration; Image processing; Focus (optics); Optics","authors":[{"name":"Abdullah Abuolaim","is_ca":true},{"name":"Mahmoud Afifi","is_ca":true},{"name":"Michael S. Brown","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02019366797951767,"gpt":0.2666047463247991,"spread":0.2464110783452815,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001153208,0.001716055,0.0009254369,0.0006401537,0.0004061673,0.0007544527,0.001431687,0.001546242,0.00146367],"category_scores_gemma":[0.003717778,0.0003768773,0.0007271306,0.0004815946,0.0005306668,0.002035224,0.00115051,0.001804396,0.0008231594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005418982,"about_ca_system_score_gemma":0.000650547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004681342,"about_ca_topic_score_gemma":0.005978723,"domain_scores_codex":[0.9994841,0.0001192056,0.00002074154,0.0002066457,0.00009722889,0.00007207406],"domain_scores_gemma":[0.9988862,0.0004897735,0.000101712,0.0002223569,0.0002216449,0.00007840226],"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":[0.0007913035,0.0005745184,0.003377338,0.0003681697,0.0002133425,0.0002634232,0.0002523444,0.2685699,0.06206239,0.003265822,0.01235863,0.6479027],"study_design_scores_gemma":[0.0000368137,0.0001696498,0.0007144591,0.00001994099,0.00003619522,0.0001083652,0.0000413857,0.9768201,0.01661258,0.003432627,0.001987742,0.00002011281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1775475,0.00438818,0.8072966,0.001145036,0.0002122671,0.0001057631,0.0005321078,0.00406708,0.004705352],"genre_scores_gemma":[0.6085175,0.0009360011,0.3804168,0.0007482441,0.0001834832,0.00009194474,0.002043705,0.0003495137,0.006712765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004681342,"threshold_uncertainty_score":0.009308219,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4212935147","doi":"10.1109/wacv51458.2022.00382","title":"Self-Supervised Shape Alignment for Sports Field Registration","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Association des Radiologistes du Québec","funders":"University of British Columbia","keywords":"Homography; Computer science; Artificial intelligence; Pairwise comparison; Image registration; Field (mathematics); Process (computing); Computer vision; Transformation (genetics); Enhanced Data Rates for GSM Evolution; Image (mathematics); Pattern recognition (psychology); Mathematics","authors":[{"name":"Feng Shi","is_ca":true},{"name":"Paul Marchwica","is_ca":true},{"name":"Juan Camilo Gamboa Higuera","is_ca":true},{"name":"Mike Jamieson","is_ca":true},{"name":"Mehrsan Javan","is_ca":true},{"name":"Parthipan Siva","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0188087235784151,"gpt":0.2942318517673893,"spread":0.2754231281889742,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001052187,0.0009605688,0.001138939,0.0009371726,0.0005000581,0.0006664374,0.00232344,0.001190354,0.002840968],"category_scores_gemma":[0.002523962,0.0006670716,0.0008604443,0.001005644,0.0007558798,0.00153094,0.001511958,0.001464996,0.002428695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005198937,"about_ca_system_score_gemma":0.0007648654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002558144,"about_ca_topic_score_gemma":0.00559849,"domain_scores_codex":[0.9990906,0.0001749137,0.00003360592,0.0003893283,0.0002209454,0.00009072216],"domain_scores_gemma":[0.9989049,0.0001829652,0.0001617076,0.0003886773,0.0003031317,0.0000584671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002754228,0.0002873124,0.002006451,0.000106529,0.0001085664,0.00009590251,0.0001566005,0.2167886,0.0466068,0.002978017,0.0058106,0.7247792],"study_design_scores_gemma":[0.00000735855,0.00005820135,0.0006701618,0.000005752725,0.000007172231,0.00007247795,0.00002519992,0.9851945,0.01061324,0.002154477,0.001181616,0.00000989512],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01818908,0.00009860047,0.9777431,0.00005677737,0.00002874688,0.00005325192,0.00008568869,0.00269884,0.00104584],"genre_scores_gemma":[0.4716151,0.0001770507,0.5171975,0.0002594623,0.00008964905,0.0001872717,0.001353391,0.0007428387,0.008377743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002840968,"threshold_uncertainty_score":0.009503961,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4212898032","doi":"10.1109/wacv51458.2022.00291","title":"One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detection","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Computer science; Adversarial system; Novelty; Encoder; Masking (illustration); Class (philosophy); Context (archaeology); Novelty detection; Artificial intelligence; Decoding methods; Speech recognition; Algorithm; Psychology","authors":[{"name":"John Jewell","is_ca":true},{"name":"Vahid Reza Khazaie","is_ca":true},{"name":"Yalda Mohsenzadeh","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02832161546985262,"gpt":0.2784198623457384,"spread":0.2500982468758858,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005796321,0.001169728,0.0007196903,0.0002902469,0.0002657385,0.0005407213,0.001632545,0.001230552,0.003501463],"category_scores_gemma":[0.001346662,0.0003700903,0.0005289115,0.0002423733,0.0007269969,0.0009185252,0.001094239,0.001943214,0.0008175708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007076433,"about_ca_system_score_gemma":0.0008311448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00335708,"about_ca_topic_score_gemma":0.004245409,"domain_scores_codex":[0.9997093,0.00005527556,0.00001125999,0.00008859584,0.00008313829,0.00005237154],"domain_scores_gemma":[0.9995614,0.0001870799,0.00005107348,0.00007708689,0.00009554048,0.00002772956],"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":[0.0004275165,0.0001582825,0.001048159,0.0001308914,0.00009645601,0.0004353592,0.00008934575,0.7111001,0.01775747,0.01160093,0.005345344,0.2518102],"study_design_scores_gemma":[0.000007933478,0.00003930461,0.00006751815,0.000005352111,0.000008390042,0.00004683179,0.000002770999,0.9950799,0.002523691,0.001723901,0.0004885656,0.000005834686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05001616,0.001275635,0.9389244,0.0006374141,0.000227727,0.0001237539,0.0001870589,0.003391299,0.005216557],"genre_scores_gemma":[0.8382403,0.000456699,0.1495317,0.0005112447,0.0001049029,0.0001860008,0.0004134825,0.0001113946,0.01044418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003501463,"threshold_uncertainty_score":0.01171362,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3183877130","doi":"10.1109/wacv51458.2022.00403","title":"Detail Preserving Residual Feature Pyramid Modules for Optical Flow","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Upsampling; Pyramid (geometry); Feature (linguistics); Computer science; Residual; Modular design; Artificial intelligence; Optical flow; Feature extraction; Iterative method; Flow (mathematics); Computer vision; Pattern recognition (psychology); Algorithm; Image (mathematics); Mathematics","authors":[{"name":"Libo Long","is_ca":true},{"name":"Jochen Lang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02115698958245709,"gpt":0.2993427656259109,"spread":0.2781857760434538,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007425323,0.0008946541,0.0005172219,0.0007857816,0.0003392892,0.0004964231,0.001481291,0.0006732037,0.003570132],"category_scores_gemma":[0.001823719,0.0004068902,0.0007825732,0.0008213229,0.0003811627,0.001562636,0.001070506,0.001173207,0.00135934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005325266,"about_ca_system_score_gemma":0.00095351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004093451,"about_ca_topic_score_gemma":0.005616826,"domain_scores_codex":[0.9996582,0.00004324379,0.00001526565,0.00007835593,0.0001562353,0.00004870504],"domain_scores_gemma":[0.9994572,0.0001156457,0.00005297244,0.0001793272,0.0001608034,0.0000339746],"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":[0.000176128,0.0001521822,0.0007474629,0.0001159669,0.00007971447,0.00006013647,0.00008820609,0.1149206,0.1055723,0.008006933,0.005777477,0.7643028],"study_design_scores_gemma":[0.0000199643,0.0001414201,0.0007363768,0.00001056581,0.0000212541,0.00008412655,0.000009500218,0.9491523,0.04104282,0.004132936,0.004626244,0.00002251544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008211757,0.00009355337,0.9887693,0.00004528041,0.00001868428,0.00004063016,0.00006134771,0.002047774,0.0007116867],"genre_scores_gemma":[0.170972,0.0001502032,0.8254552,0.00009904063,0.00004263261,0.0001058626,0.0005484233,0.0003108878,0.002315736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004093451,"threshold_uncertainty_score":0.01194328,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4213125754","doi":"10.1109/wacv51458.2022.00320","title":"Tailor Me: An Editing Network for Fashion Attribute Shape Manipulation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Image editing; Computer science; Parsing; RGB color model; Artificial intelligence; Video editing; Pixel; Image (mathematics); Computer vision; Task (project management); Computer graphics (images)","authors":[{"name":"Youngjoong Kwon","is_ca":false},{"name":"Stefano Petrangeli","is_ca":false},{"name":"Dahun Kim","is_ca":true},{"name":"Haoliang Wang","is_ca":false},{"name":"Viswanathan Swaminathan","is_ca":false},{"name":"Henry Fuchs","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03525840182600259,"gpt":0.2884128643373655,"spread":0.2531544625113629,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004423955,0.001084548,0.0004510526,0.0005842037,0.0002844515,0.0005706982,0.001606648,0.0007847142,0.004500964],"category_scores_gemma":[0.00134106,0.0003693205,0.0007463899,0.0003726775,0.0005529654,0.001001534,0.00124537,0.001279168,0.001267305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005450441,"about_ca_system_score_gemma":0.0003202677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002568402,"about_ca_topic_score_gemma":0.00522577,"domain_scores_codex":[0.9997609,0.00003634705,0.000008406045,0.00009543933,0.00006880251,0.00003005103],"domain_scores_gemma":[0.9997106,0.00009608072,0.00002677877,0.0001026323,0.00003866409,0.00002516503],"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":[0.0003862394,0.0002449149,0.001432864,0.0001685708,0.000131884,0.0004168941,0.0001647028,0.3702004,0.05557608,0.01411706,0.01920901,0.5379514],"study_design_scores_gemma":[0.00001357514,0.00007336302,0.0002591796,0.00001158893,0.00002048107,0.0001465292,0.00001824851,0.9720229,0.01503308,0.005794675,0.00659066,0.00001579997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02646628,0.0004683462,0.9561059,0.0002411658,0.0001855337,0.0001501491,0.0006925593,0.009527616,0.00616251],"genre_scores_gemma":[0.437604,0.0006044256,0.5312708,0.0006240125,0.0001076171,0.0002997783,0.003573013,0.001203885,0.02471257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004500964,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3200321642","doi":"10.1109/wacv51458.2022.00101","title":"Auto White-Balance Correction for Mixed-Illuminant Scenes","year":2022,"lang":"en","type":"preprint","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Standard illuminant; Color balance; Computer science; Artificial intelligence; Computer vision; Weighting; Set (abstract data type); Color constancy; Code (set theory); Balance (ability); Color correction; Computer graphics (images); Image (mathematics); Image processing; Color image","authors":[{"name":"Mahmoud Afifi","is_ca":true},{"name":"Marcus A. Brubaker","is_ca":true},{"name":"Michael S. Brown","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0183484252751136,"gpt":0.3053997954409911,"spread":0.2870513701658775,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004056428,0.001211501,0.0006783702,0.001010133,0.0004716286,0.0009917085,0.0009324859,0.0005351405,0.003435987],"category_scores_gemma":[0.001896153,0.0004751798,0.0006960197,0.0007867815,0.0005104734,0.001195415,0.001454194,0.001420767,0.001418902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000417232,"about_ca_system_score_gemma":0.0007731543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00297276,"about_ca_topic_score_gemma":0.006675802,"domain_scores_codex":[0.9995329,0.00004386528,0.00001493435,0.000122131,0.0002351091,0.00005105474],"domain_scores_gemma":[0.9994401,0.00008709459,0.00008615143,0.000158606,0.0001910165,0.00003700493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002749861,0.0001031622,0.002561715,0.0003013032,0.0001405512,0.000157898,0.0003617411,0.03772226,0.3283993,0.006840911,0.004768505,0.6183677],"study_design_scores_gemma":[0.00004870136,0.0001572009,0.005495605,0.00006234847,0.0001094442,0.0008290304,0.0001705772,0.6472034,0.3121074,0.007087617,0.02663534,0.00009328567],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02468635,0.0002380323,0.9707415,0.00006530382,0.00008336697,0.00004480107,0.00007407998,0.002302621,0.001764096],"genre_scores_gemma":[0.2299836,0.0005329393,0.7609484,0.0001562049,0.00006103449,0.00007669113,0.0004292378,0.001465156,0.006346717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003435987,"threshold_uncertainty_score":0.01149458,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4213150508","doi":"10.1109/wacv51458.2022.00203","title":"VCSeg: Virtual Camera Adaptation for Road Segmentation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Segmentation; Mean-shift; Generalization; Camera auto-calibration; Camera resectioning; Image segmentation; Domain (mathematical analysis); Mathematics","authors":[{"name":"Gong Cheng","is_ca":true},{"name":"James H. Elder","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01936086054548443,"gpt":0.2752015544924593,"spread":0.2558406939469749,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009288604,0.001832852,0.001215452,0.001233646,0.0006634535,0.001062166,0.002906236,0.001970458,0.005967201],"category_scores_gemma":[0.002642143,0.0007484404,0.001250767,0.001286903,0.0008594029,0.001774353,0.001833194,0.002304121,0.002387896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000964475,"about_ca_system_score_gemma":0.001338763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0144666,"about_ca_topic_score_gemma":0.02371096,"domain_scores_codex":[0.9992749,0.0001283341,0.00002183194,0.0003363628,0.000139203,0.00009933609],"domain_scores_gemma":[0.999255,0.0001914801,0.00005456667,0.0002617969,0.0001879767,0.0000491739],"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":[0.0001948916,0.0002071984,0.001573079,0.0001810386,0.0001756451,0.0001771392,0.0001711675,0.4083821,0.0170465,0.004835153,0.02072311,0.546333],"study_design_scores_gemma":[0.00001051528,0.00003621198,0.0003593742,0.000008815217,0.000009168211,0.00006790517,0.00002238145,0.9891789,0.004705646,0.002222003,0.003367714,0.00001149024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02710598,0.0005876476,0.95433,0.000211996,0.0001524427,0.0001496119,0.0005235458,0.01323498,0.003703835],"genre_scores_gemma":[0.2671342,0.0003244557,0.7212139,0.00038123,0.00009951431,0.0002290304,0.0031136,0.001359347,0.006144684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0144666,"threshold_uncertainty_score":0.02876484,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4213325824","doi":"10.1109/wacv51458.2022.00176","title":"Towards Durability Estimation of Bioprosthetic Heart Valves Via Motion Symmetry Analysis","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Asymmetry; Symmetry (geometry); Dynamic time warping; Pulsatile flow; Rotational symmetry; Computer science; Diagonal; Artificial intelligence; Computer vision; Mathematics; Algorithm; Physics; Geometry; Cardiology; Medicine","authors":[{"name":"Maryam Alizadeh","is_ca":true},{"name":"Melissa Cote","is_ca":true},{"name":"Alexandra Branzan Albu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01402469646294983,"gpt":0.3367853586677537,"spread":0.3227606622048038,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009275272,0.0007211702,0.0005866463,0.002092564,0.0001635991,0.0008326977,0.0004782851,0.0006258541,0.0006169019],"category_scores_gemma":[0.004066583,0.0002333834,0.0007255956,0.000681287,0.0004052416,0.0008691148,0.0006658613,0.0005594034,0.0002534873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002581816,"about_ca_system_score_gemma":0.0003309661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007205101,"about_ca_topic_score_gemma":0.0004951365,"domain_scores_codex":[0.9995358,0.0001433759,0.00003663337,0.00009665425,0.0001484849,0.00003910041],"domain_scores_gemma":[0.9987019,0.0004993642,0.0003149241,0.000149893,0.0002589319,0.00007498915],"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":[0.0003859221,0.0001985768,0.01394858,0.0003251436,0.0001754845,0.000210673,0.0001833566,0.1834171,0.1078509,0.005275108,0.001215151,0.6868141],"study_design_scores_gemma":[0.000007892408,0.0001092407,0.007066931,0.0000154071,0.00002663916,0.000204464,0.00004181347,0.9722853,0.01730731,0.002450978,0.0004568588,0.00002708521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1181408,0.0003205868,0.8800624,0.00009751885,0.00002672738,0.00004717395,0.0001224748,0.000395312,0.0007869947],"genre_scores_gemma":[0.7944536,0.0003735363,0.2038857,0.0000363796,0.00004963774,0.0000543137,0.0003764949,0.00007504345,0.0006953598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002092564,"threshold_uncertainty_score":0.004905283,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}