{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":51,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":51,"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":"4dfd76f1328d","filters":{"venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference"}},"results":[{"id":"W3160543801","doi":"10.32473/flairs.v34i1.128339","title":"An Exploration On-demand Article Recommender System for Cancer Patients Information Provisioning","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Provisioning; Recommender system; Baseline (sea); Cancer; Knowledge management; World Wide Web; Medicine","authors":[{"name":"Mohammad Mehdi Afsar","is_ca":true},{"name":"Trafford Crump","is_ca":true},{"name":"Behrouz H. Far","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.158861643164401,"gpt":0.3893944126586932,"spread":0.2305327694942922,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00110764,0.0007556612,0.001115085,0.001391184,0.000581773,0.0009617314,0.0013371,0.001387741,0.00312271],"category_scores_gemma":[0.003518035,0.0003875096,0.0007585757,0.001177657,0.000135119,0.001842009,0.0009995397,0.001026302,0.002072026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003965635,"about_ca_system_score_gemma":0.0009027481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006255672,"about_ca_topic_score_gemma":0.01582844,"domain_scores_codex":[0.9992166,0.0002003342,0.00008901158,0.0001935835,0.0002478992,0.0000526971],"domain_scores_gemma":[0.9980171,0.0007757519,0.0001558649,0.0003603332,0.0004629811,0.0002281176],"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":[0.002279784,0.002161282,0.01796304,0.001394588,0.0006073702,0.001787956,0.001044079,0.01430963,0.03879312,0.002345703,0.05967445,0.857639],"study_design_scores_gemma":[0.0007127708,0.002239803,0.02588665,0.0002119092,0.001157617,0.004492017,0.001124221,0.8085504,0.03210125,0.005049692,0.1180554,0.0004182769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3333298,0.01230161,0.5859443,0.004527558,0.001022626,0.001995599,0.007389587,0.03328188,0.02020702],"genre_scores_gemma":[0.5527518,0.003191878,0.4119843,0.001373123,0.0004247196,0.0005504862,0.007322844,0.0002833544,0.02211741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006255672,"threshold_uncertainty_score":0.01243854,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160310472","doi":"10.32473/flairs.v34i1.128502","title":"Multilingual Automatic Term Extraction in Low-Resource Domains","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Advanced Text Analysis Techniques","field":"Computer 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":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Task (project management); Term (time); Artificial intelligence; Resource (disambiguation); Raw data; Sequence labeling; Sequence (biology); Domain (mathematical analysis); Artificial neural network; Natural language processing; Deep learning; Information extraction; Machine learning; Engineering","authors":[{"name":"Ngoc Tan Le","is_ca":true},{"name":"Fatiha Sadat","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08710697055732607,"gpt":0.4004800386628963,"spread":0.3133730681055702,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00148677,0.001270362,0.001111637,0.004197835,0.0008291696,0.001585126,0.0009441678,0.0009492736,0.003077663],"category_scores_gemma":[0.0049543,0.0003600714,0.0009193483,0.00368241,0.0005087783,0.004881974,0.002648264,0.001719843,0.004027167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005839245,"about_ca_system_score_gemma":0.00126546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002887609,"about_ca_topic_score_gemma":0.00632849,"domain_scores_codex":[0.9986219,0.0004156736,0.0001635563,0.0003878904,0.0002534913,0.0001574765],"domain_scores_gemma":[0.9972876,0.00123329,0.0002094957,0.0005532347,0.0006095677,0.0001068381],"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":[0.0008774757,0.0004220208,0.004632988,0.001344769,0.0002016868,0.001049018,0.0005134538,0.01979447,0.08725987,0.008487034,0.04245533,0.8329619],"study_design_scores_gemma":[0.0002441867,0.0004526398,0.01427116,0.0003028683,0.0003223997,0.001909932,0.001682964,0.6391311,0.1452114,0.06551705,0.1307032,0.0002512044],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2022651,0.00913743,0.7327719,0.001600686,0.0007493964,0.0004283052,0.01931335,0.01847404,0.01525975],"genre_scores_gemma":[0.4219736,0.002129653,0.5041797,0.0004376273,0.0003832336,0.0003057894,0.05786145,0.000926097,0.01180298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004197835,"threshold_uncertainty_score":0.01029581,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3162322285","doi":"10.32473/flairs.v34i1.128427","title":"Ensemble-based Semi-Supervised Learning for Hate Speech Detection","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Leverage (statistics); Computer science; Ensemble learning; Artificial intelligence; Labeled data; Voice activity detection; Machine learning; Supervised learning; Natural language processing; Speech recognition; Speech processing; Artificial neural network","authors":[{"name":"Safa Alsafari","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1015021418685871,"gpt":0.3376627144692195,"spread":0.2361605726006324,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005103146,0.001126832,0.001581562,0.001845325,0.001022001,0.000974222,0.001562021,0.001110582,0.0009493916],"category_scores_gemma":[0.009548173,0.0003779428,0.0008465806,0.001125069,0.0005979693,0.002088226,0.001471798,0.002173918,0.001273582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005224153,"about_ca_system_score_gemma":0.0009507631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001947384,"about_ca_topic_score_gemma":0.004772728,"domain_scores_codex":[0.9969516,0.001472572,0.0001881873,0.0006118056,0.0005909257,0.0001850221],"domain_scores_gemma":[0.9885105,0.005722246,0.0007110747,0.001970976,0.00279549,0.0002897355],"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":[0.0004373593,0.0008244459,0.01798414,0.0001794381,0.0004450811,0.0001508141,0.0004169355,0.1499227,0.01178408,0.002814559,0.009624645,0.8054157],"study_design_scores_gemma":[0.00000825084,0.00007761239,0.001400719,0.00001348296,0.00002806001,0.00005152336,0.00006405133,0.9891426,0.004939832,0.00319556,0.001060429,0.00001779822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09105749,0.0007111533,0.9020253,0.0002642722,0.0001265957,0.000169305,0.0004734782,0.003007617,0.002164801],"genre_scores_gemma":[0.6770008,0.0003019876,0.3164909,0.0002274905,0.0002093175,0.0003077808,0.002947837,0.0001773787,0.002336488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005103146,"threshold_uncertainty_score":0.02698833,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225399182","doi":"10.32473/flairs.v35i.130545","title":"Preliminary Thoughts on Defining f(x) for Ethical Machines","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Normative; Ethical issues; Ethical theories; Engineering ethics; Ethical theory; Computer science; Epistemology; Management science; Philosophy; Engineering","authors":[{"name":"Clayton Peterson","is_ca":true},{"name":"Naïma Hamrouni","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.241515362300319,"gpt":0.4686553522257582,"spread":0.2271399899254392,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01463431,0.001291295,0.001111048,0.00307688,0.004248424,0.006690237,0.002316705,0.005674577,0.02510525],"category_scores_gemma":[0.03224979,0.0006039099,0.001778796,0.001780436,0.01394914,0.01388259,0.00325448,0.009901055,0.003486095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003383053,"about_ca_system_score_gemma":0.001705263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00173851,"about_ca_topic_score_gemma":0.001650071,"domain_scores_codex":[0.9917364,0.005553938,0.0005588306,0.0007553046,0.0008911897,0.0005044147],"domain_scores_gemma":[0.9761603,0.01764007,0.001268111,0.001351269,0.002655661,0.0009247397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008119572,0.00001320126,0.00008816415,0.00003816425,0.000002314495,0.00005082783,0.0004597988,0.0002941733,0.00008008009,0.9939364,0.002156748,0.002872188],"study_design_scores_gemma":[0.000005840031,0.00002223961,0.0002052166,0.00009037097,0.000002855725,0.00009164892,0.0004211417,0.00122876,0.000111836,0.972831,0.02497491,0.00001420929],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0173802,0.007891634,0.5883135,0.123803,0.003481587,0.0004986982,0.0005538304,0.0003558383,0.2577217],"genre_scores_gemma":[0.4932774,0.00526253,0.4361678,0.01723222,0.005291664,0.002219447,0.0006992634,0.0004005202,0.03944913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02510525,"threshold_uncertainty_score":0.08398539,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4376958607","doi":"10.32473/flairs.36.133328","title":"Towards a multi-modal Deep Learning Architecture for User Modeling","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal; École de Technologie Supérieure","funders":"","keywords":"Computer science; Deep learning; Artificial intelligence; Modal; Convolutional neural network; User modeling; Representation (politics); Feature (linguistics); Feature learning; Machine learning; Architecture; Human–computer interaction; User interface","authors":[{"name":"Ange Tato","is_ca":true},{"name":"Roger Nkambou","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1617934655474933,"gpt":0.4043254720886784,"spread":0.242532006541185,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007987943,0.0007565875,0.0005038423,0.000507379,0.0002549252,0.0006882348,0.001089227,0.0008854779,0.001805932],"category_scores_gemma":[0.001449393,0.0004712334,0.0009453631,0.000433635,0.0004288451,0.001329506,0.001306133,0.001990231,0.0007410113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00089273,"about_ca_system_score_gemma":0.0006601407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007788086,"about_ca_topic_score_gemma":0.01303585,"domain_scores_codex":[0.9996229,0.0001296421,0.00001711758,0.0001164189,0.00005898669,0.00005479806],"domain_scores_gemma":[0.9996337,0.0001343,0.00003397321,0.0000512523,0.0001119577,0.00003474193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005907166,0.0005140891,0.007946049,0.000175927,0.0003471581,0.0002038042,0.00058718,0.4676504,0.03528659,0.0210798,0.00882424,0.456794],"study_design_scores_gemma":[0.000002365779,0.0000208474,0.0002945203,0.000005527605,0.000009233243,0.00001573057,0.00001046452,0.9945579,0.0009756915,0.003666206,0.0004356387,0.000005945],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02261023,0.0003390938,0.9738067,0.000477485,0.0000427976,0.00003979926,0.0002306303,0.001163599,0.001289584],"genre_scores_gemma":[0.7628868,0.0005151373,0.2274455,0.0006474063,0.00007632315,0.0001933881,0.0007326132,0.0001272752,0.007375674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007788086,"threshold_uncertainty_score":0.01548553,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160036765","doi":"10.32473/flairs.v34i1.128474","title":"Confusion detection using cognitive ability tests","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Confusion; Memorization; Cognition; Computer science; Support vector machine; Artificial intelligence; Cognitive psychology; Orientation (vector space); Psychology; Pattern recognition (psychology); Machine learning; Mathematics","authors":[{"name":"Caroline Dakoure","is_ca":true},{"name":"Mohamed S. Benlamine","is_ca":true},{"name":"Claude Frasson","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2393936907274938,"gpt":0.4125526449569652,"spread":0.1731589542294714,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010414,0.0008287616,0.0005184456,0.002332775,0.0001942641,0.001321779,0.0003792936,0.0006873987,0.002180744],"category_scores_gemma":[0.01103686,0.0001217904,0.0004054035,0.0008166933,0.0002674165,0.001074138,0.0006931432,0.0005322536,0.0007603847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002948244,"about_ca_system_score_gemma":0.0002819018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012227,"about_ca_topic_score_gemma":0.001801598,"domain_scores_codex":[0.9989356,0.00020601,0.0001203258,0.0001809618,0.0004584484,0.00009861363],"domain_scores_gemma":[0.9960915,0.001361814,0.0009785483,0.0001509325,0.00112135,0.0002957887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002551363,0.0009651523,0.5192349,0.0004490184,0.0003593029,0.0005519817,0.001287802,0.006486401,0.04667344,0.0007428661,0.002810459,0.4178873],"study_design_scores_gemma":[0.00008966295,0.00257901,0.8986235,0.00009291474,0.0001475622,0.001266106,0.001068291,0.06375525,0.02894745,0.001703231,0.001575889,0.0001511115],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959612,0.0003399925,0.03275851,0.000126823,0.00005620109,0.0003624059,0.0009390139,0.0006462109,0.005158805],"genre_scores_gemma":[0.9920922,0.0001276542,0.006417106,0.00004158713,0.00002227421,0.00008873231,0.0004275768,0.00001436212,0.0007685322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002332775,"threshold_uncertainty_score":0.00729537,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160789541","doi":"10.32473/flairs.v34i1.128367","title":"Using Deep Learning algorithms to detect the success or failure of the Electroconvulsive Therapy (ECT) sessions","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Electroconvulsive therapy; Major depressive disorder; Electroencephalography; Mental health; Depression (economics); Health professionals; Session (web analytics); Psychology; Psychiatry; Magnetic resonance imaging; Mental healthcare; Health care; Medicine; Computer science; Cognition","authors":[{"name":"Usef Faghihi","is_ca":true},{"name":"Cyrus kalantarpour","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2126229742069513,"gpt":0.4176508145072,"spread":0.2050278403002487,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001377796,0.0008684265,0.0006038806,0.001191397,0.0002305485,0.0007601684,0.0006617457,0.0008179659,0.0008213655],"category_scores_gemma":[0.004092691,0.00025477,0.0004481318,0.0005786339,0.0002294395,0.0006308678,0.0004052843,0.00102955,0.0002484453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006993659,"about_ca_system_score_gemma":0.0007427803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006799708,"about_ca_topic_score_gemma":0.0075281,"domain_scores_codex":[0.9995566,0.0001159288,0.00006247207,0.0001136116,0.00007650195,0.0000749439],"domain_scores_gemma":[0.9982552,0.001006169,0.0002475375,0.00006689056,0.0003469669,0.00007723722],"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":[0.0006061881,0.001287848,0.07308345,0.0001656681,0.0004035778,0.0002314486,0.0001026781,0.2886673,0.006024146,0.001003573,0.005477104,0.622947],"study_design_scores_gemma":[0.00001739891,0.0001420589,0.005506863,0.00002051976,0.00002949077,0.00003496212,0.00002291038,0.9915063,0.001503816,0.0008462276,0.0003594202,0.00001014233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7177778,0.00286586,0.2691024,0.001895848,0.0003217357,0.0002310655,0.001028557,0.001789137,0.004987488],"genre_scores_gemma":[0.9418583,0.0005466239,0.05414664,0.0003792707,0.00006692227,0.0001299158,0.001007445,0.00003625505,0.001828708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006799708,"threshold_uncertainty_score":0.01352024,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225401927","doi":"10.32473/flairs.v35i.130667","title":"Integration of Multivariate Beta-based Hidden Markov Models and Support Vector Machines with Medical Applications","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hidden Markov model; Discriminative model; Support vector machine; Artificial intelligence; Computer science; Fisher kernel; Pattern recognition (psychology); Kernel (algebra); Generative model; Machine learning; Multivariate statistics; Decision boundary; Kernel method; Generative grammar; Mathematics; Kernel Fisher discriminant analysis","authors":[{"name":"Narges Manouchehri","is_ca":true},{"name":"Nizar Bouguila","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1128507009302343,"gpt":0.3615773986869301,"spread":0.2487266977566958,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001475452,0.0005971421,0.0008197559,0.0009179495,0.0002078635,0.0007060526,0.001087937,0.0009144499,0.001095809],"category_scores_gemma":[0.003815525,0.0004131337,0.0009440018,0.000920567,0.0003850897,0.001462671,0.0007180835,0.00109693,0.0006078986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004492812,"about_ca_system_score_gemma":0.0005472758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002493277,"about_ca_topic_score_gemma":0.002474468,"domain_scores_codex":[0.9992608,0.000254896,0.00004925417,0.0001726836,0.0001926235,0.00006979636],"domain_scores_gemma":[0.9986756,0.0007984209,0.0001324959,0.0001076433,0.0002257637,0.0000600845],"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":[0.0002001514,0.0001868399,0.009549574,0.0001941268,0.000251923,0.0002631351,0.0001699952,0.5917711,0.005398665,0.04005148,0.002762668,0.3492004],"study_design_scores_gemma":[0.000002734443,0.00002062017,0.0003917675,0.000005960464,0.00001275144,0.00003803003,0.000005532215,0.9915171,0.0003304082,0.007093161,0.0005752239,0.000006753176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0115834,0.000756228,0.9861118,0.0002683194,0.00006110445,0.00001638967,0.00005932623,0.0003824762,0.0007608773],"genre_scores_gemma":[0.7935287,0.001526108,0.2000773,0.0002885443,0.0002297726,0.0001013675,0.0003988356,0.0001051055,0.003744278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002493277,"threshold_uncertainty_score":0.007803023,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225428113","doi":"10.32473/flairs.v35i.130688","title":"Unsupervised Neural Network for Data-Driven Corrosion Detection of a Mining Pipeline","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institute of Mining, Metallurgy and Petroleum","keywords":"Corrosion; Pipeline transport; Artificial neural network; Pipeline (software); Computer science; Representation (politics); Data mining; Artificial intelligence; Engineering; Materials science; Environmental engineering","authors":[{"name":"Abdou Khadir Dia","is_ca":true},{"name":"Nadia Ghazzali","is_ca":true},{"name":"Bosca Axel Gambou","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1806987928359528,"gpt":0.3621233291969468,"spread":0.181424536360994,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005077808,0.0004906501,0.0003531686,0.0005344967,0.0002102723,0.0003730148,0.0005630388,0.000553844,0.0006987429],"category_scores_gemma":[0.001449374,0.0002352497,0.0004226573,0.0004837858,0.0001754606,0.0004245265,0.0003073071,0.0005945771,0.0001759223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005997648,"about_ca_system_score_gemma":0.0006294439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008424549,"about_ca_topic_score_gemma":0.009068877,"domain_scores_codex":[0.9997835,0.00004595388,0.00001687285,0.00006007146,0.00006369025,0.00003000795],"domain_scores_gemma":[0.9995992,0.0001812737,0.00005231865,0.0000202829,0.000134119,0.00001278126],"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":[0.0002653725,0.0001958043,0.004194849,0.0000900057,0.00009832362,0.0001168683,0.0000640803,0.7630088,0.01512984,0.001174396,0.001116422,0.2145452],"study_design_scores_gemma":[0.000001326342,0.00001075484,0.0003320995,0.000001285284,0.000002667327,0.000003706849,0.000002876256,0.998577,0.0008707541,0.00013947,0.0000562898,0.000001858971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1522065,0.0003884753,0.8433697,0.0001928139,0.00005850034,0.00009206169,0.0002925785,0.001727283,0.001672056],"genre_scores_gemma":[0.8800169,0.0001376501,0.1171197,0.00005051516,0.00002644094,0.0001704645,0.0004180843,0.00003856656,0.002021666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008424549,"threshold_uncertainty_score":0.01675105,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400282938","doi":"10.32473/flairs.37.1.135537","title":"Fluid Path Detection Model for Lab on a Chip Images Using Deep Learning-Based Segmentation Approach","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Segmentation; Artificial intelligence; Computer science; Path (computing); Chip; Deep learning; Lab-on-a-chip; Computer vision; Pattern recognition (psychology); Machine learning; Materials science; Nanotechnology; Microfluidics; Telecommunications","authors":[{"name":"Mahmood Khalghollah","is_ca":true},{"name":"Esmaeil Shakeri","is_ca":true},{"name":"Azam Zare","is_ca":true},{"name":"Behrouz H. Far","is_ca":false},{"name":"Amir Sanati‐Nezhad","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.118825085077113,"gpt":0.370022375763588,"spread":0.251197290686475,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003240692,0.0008117178,0.0004668714,0.0008688598,0.0002520483,0.0007186285,0.001189311,0.001155723,0.001655478],"category_scores_gemma":[0.0007152928,0.0004255208,0.0007277018,0.0004646832,0.0003948456,0.0006643109,0.0004730451,0.0008127635,0.0005519723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486247,"about_ca_system_score_gemma":0.001282844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01024635,"about_ca_topic_score_gemma":0.01031452,"domain_scores_codex":[0.9998547,0.00001573837,0.000006297063,0.00005670547,0.00003954163,0.00002691349],"domain_scores_gemma":[0.9998429,0.00005298454,0.00002391476,0.00001408985,0.00005516192,0.00001086456],"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":[0.0001919711,0.00009974688,0.001590802,0.00008597234,0.00005003158,0.0000977649,0.00006378287,0.7532337,0.02557009,0.004537953,0.003260256,0.211218],"study_design_scores_gemma":[0.000001278954,0.000007798226,0.00009546429,0.000001885404,0.000002676441,0.000007881959,0.000001771663,0.9972796,0.001710814,0.0006031435,0.000285516,0.00000229784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02543519,0.0002992462,0.9704261,0.000272319,0.00003795925,0.00005849663,0.0002127792,0.00192094,0.001336866],"genre_scores_gemma":[0.5993194,0.0006537053,0.3870082,0.00050638,0.00006533615,0.0003640959,0.001269807,0.0003399976,0.01047313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01024635,"threshold_uncertainty_score":0.0203734,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410398281","doi":"10.32473/flairs.38.1.138970","title":"Flexible Dirichlet Mixture Model for Multi-modal data Clustering","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Advanced Clustering Algorithms Research","field":"Computer 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":"Concordia University","funders":"","keywords":"Modal; Cluster analysis; Latent Dirichlet allocation; Mixture model; Computer science; Dirichlet distribution; Data mining; Mathematics; Artificial intelligence; Topic model; Materials science","authors":[{"name":"Seung-Hyun Hong","is_ca":true},{"name":"Fatma Najar","is_ca":false},{"name":"Manar Amayri","is_ca":false},{"name":"Nizar Bouguila","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3601967099388323,"gpt":0.4684816825311803,"spread":0.108284972592348,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007832869,0.001573619,0.002386766,0.002911928,0.001513591,0.002735476,0.003991283,0.00301669,0.00259586],"category_scores_gemma":[0.01575005,0.001158899,0.003176238,0.003787934,0.002002341,0.00427793,0.003271738,0.004190778,0.00172516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002062166,"about_ca_system_score_gemma":0.001756561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006930617,"about_ca_topic_score_gemma":0.00677555,"domain_scores_codex":[0.9937533,0.003118668,0.0003027449,0.001297855,0.001158871,0.0003686486],"domain_scores_gemma":[0.994633,0.003403172,0.0003537202,0.0007737197,0.0006644786,0.0001719709],"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":[0.0003939426,0.0001642858,0.00330677,0.0004711316,0.0004414223,0.0002498603,0.0007788814,0.7124423,0.004109185,0.1068063,0.00699818,0.1638378],"study_design_scores_gemma":[0.00001091447,0.00001782725,0.0003120104,0.00002408519,0.00001969701,0.00006788918,0.00004587876,0.9469033,0.0006531317,0.05014113,0.001765605,0.00003855595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002898245,0.0005626147,0.9953901,0.0002188182,0.00005098812,0.00004794836,0.0001377821,0.0002765731,0.0004170707],"genre_scores_gemma":[0.3053878,0.002094825,0.6831809,0.000577728,0.0003796573,0.000811341,0.002239205,0.0003935812,0.004934823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007832869,"threshold_uncertainty_score":0.04142469,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225383538","doi":"10.32473/flairs.v35i.130643","title":"Learning to Rank with BERT for Argument Quality Evaluation","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Argument (complex analysis); Leverage (statistics); Ranking (information retrieval); Rank (graph theory); Computer science; Learning to rank; Pairwise comparison; Artificial intelligence; Quality (philosophy); Machine learning; Representation (politics); Task (project management); Mathematics; Epistemology; Political science; Engineering","authors":[{"name":"Charles-Olivier Favreau","is_ca":true},{"name":"Amal Zouaq","is_ca":true},{"name":"Sameer Bhatnagar","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1733581635769031,"gpt":0.4124483342358819,"spread":0.2390901706589788,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01331382,0.004083859,0.002532512,0.00779169,0.001296391,0.004887446,0.003469139,0.005560974,0.01239752],"category_scores_gemma":[0.04980415,0.0006579913,0.001715988,0.003708763,0.001570488,0.00578361,0.002402847,0.004842697,0.009445498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002596239,"about_ca_system_score_gemma":0.002499521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003933964,"about_ca_topic_score_gemma":0.01022052,"domain_scores_codex":[0.9878461,0.005860652,0.0008078465,0.001401622,0.003409928,0.000673904],"domain_scores_gemma":[0.967267,0.02151415,0.00227224,0.004156947,0.003816488,0.0009731176],"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":[0.0015995,0.0008104374,0.01171212,0.001701674,0.0004820791,0.0002857404,0.0003485433,0.1813127,0.004878915,0.02226087,0.1159202,0.6586873],"study_design_scores_gemma":[0.0001729476,0.0003827046,0.001926127,0.0001572175,0.0000650724,0.0001868311,0.0001399243,0.9600456,0.004721313,0.01993992,0.01218782,0.00007443786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1049751,0.01549153,0.7627727,0.003299124,0.001792322,0.001230237,0.01260107,0.06309288,0.03474503],"genre_scores_gemma":[0.5383179,0.00145076,0.4177915,0.001014295,0.0008840281,0.0007173758,0.02352823,0.002058693,0.01423722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01331382,"threshold_uncertainty_score":0.07041109,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225373816","doi":"10.32473/flairs.v35i.130660","title":"Protein-Protein Interaction Extraction using Attention-based Tree-Structured Neural Network Models","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Tree (set theory); Artificial intelligence; Task (project management); Artificial neural network; Machine learning; Natural language processing; Phrase; Recurrent neural network; Tree structure; Data structure; Mathematics","authors":[{"name":"Sudipta Singha Roy","is_ca":true},{"name":"Robert E. Mercer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1538659671948852,"gpt":0.382034202859431,"spread":0.2281682356645457,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006077462,0.000828867,0.0008490016,0.001510424,0.0003412846,0.0007392633,0.001068941,0.001071949,0.001474173],"category_scores_gemma":[0.00198402,0.0003622297,0.001110589,0.001593879,0.0002647982,0.001758924,0.0006351568,0.0009684851,0.0006564757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243667,"about_ca_system_score_gemma":0.001098144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0145047,"about_ca_topic_score_gemma":0.01876316,"domain_scores_codex":[0.999731,0.00005494921,0.00001811034,0.00009958322,0.00005730611,0.00003899449],"domain_scores_gemma":[0.9991033,0.0005606861,0.00009700721,0.0000394755,0.0001649648,0.00003468941],"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":[0.0004345973,0.0004110033,0.004866611,0.0001874236,0.0002032234,0.0004181491,0.0001436982,0.6810485,0.00900312,0.007787833,0.006370213,0.2891257],"study_design_scores_gemma":[0.000003446896,0.00001083137,0.000173034,0.000002569012,0.000008670473,0.00001041036,0.000003450528,0.9969292,0.0002750502,0.002450881,0.0001301398,0.000002259573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.17968,0.002129759,0.8086079,0.0008476169,0.0001106896,0.00013802,0.001107512,0.002887406,0.004491248],"genre_scores_gemma":[0.8353425,0.0008057805,0.1550079,0.0003470426,0.00009313977,0.0001601258,0.002501519,0.00009752906,0.005644571],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0145047,"threshold_uncertainty_score":0.02884054,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375858571","doi":"10.32473/flairs.36.133256","title":"Identifying Protein-Protein Interaction using Tree-Transformers and Heterogeneous Graph Neural Network","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"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; Artificial neural network; Transformer; Graph; Artificial intelligence; Theoretical computer science; Engineering; Electrical engineering","authors":[{"name":"Sudipta Singha Roy","is_ca":true},{"name":"Robert E. Mercer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1735366575085686,"gpt":0.3955412738069915,"spread":0.2220046162984229,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004949659,0.0006769162,0.0005764035,0.001924486,0.0003494544,0.0006431061,0.001062226,0.0008339798,0.001304476],"category_scores_gemma":[0.001491601,0.0002600128,0.000798456,0.001573922,0.0003895489,0.001731189,0.0006411487,0.0006862718,0.0004787938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001049474,"about_ca_system_score_gemma":0.0005308927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01211932,"about_ca_topic_score_gemma":0.01924664,"domain_scores_codex":[0.9997277,0.00006625918,0.00001210677,0.0001074109,0.00004456805,0.00004192603],"domain_scores_gemma":[0.9994211,0.0003311539,0.00006651099,0.00005701805,0.00009471671,0.00002954347],"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":[0.0005212795,0.0004547925,0.00805926,0.0002064841,0.0002691517,0.0005462847,0.0001636014,0.5660139,0.02146649,0.01587787,0.006911035,0.3795099],"study_design_scores_gemma":[0.000002836483,0.00001225689,0.0004345753,0.000001647674,0.00000978928,0.0000147894,0.000007016502,0.9948947,0.0006367714,0.003830747,0.0001520067,0.000002740186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2889096,0.001421614,0.699088,0.0005661432,0.0001059385,0.0001444211,0.001027925,0.00305726,0.005679172],"genre_scores_gemma":[0.9300618,0.000368488,0.0653441,0.0001377027,0.00004349984,0.00005697234,0.001421246,0.00006595942,0.00250026],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01211932,"threshold_uncertainty_score":0.02409756,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225384347","doi":"10.32473/flairs.v35i.130629","title":"Estimating Automobile Crash Characteristics from Images using Deep Learning","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Acadia University","funders":"","keywords":"Crash; Collision; Artificial intelligence; Deep learning; Computer science; Machine learning; Simulation; Engineering; Computer security","authors":[{"name":"Daniel Silver","is_ca":true},{"name":"Hardik Manek","is_ca":false},{"name":"Matthew Kay","is_ca":false},{"name":"P Travis","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06565464327735158,"gpt":0.3190429977632977,"spread":0.2533883544859461,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002765188,0.0009649677,0.0003550651,0.001397529,0.0002139304,0.00055154,0.0006681949,0.0007047608,0.0009378399],"category_scores_gemma":[0.001261572,0.000407687,0.000599513,0.0006762558,0.0002314806,0.0007504949,0.0004905098,0.0008568905,0.0005188563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009040487,"about_ca_system_score_gemma":0.0005443816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01507868,"about_ca_topic_score_gemma":0.02068497,"domain_scores_codex":[0.9998447,0.00001374821,0.000007357791,0.00004984971,0.00004025154,0.00004401844],"domain_scores_gemma":[0.9996626,0.00007211562,0.00005554692,0.00004642951,0.0001411718,0.00002201809],"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":[0.0004514373,0.0006182893,0.05339989,0.0001193671,0.000291318,0.0004506732,0.00009345546,0.5198669,0.036963,0.001197171,0.007249729,0.3792987],"study_design_scores_gemma":[0.000004024032,0.00003778204,0.008065141,0.00001088661,0.00001540879,0.00004055919,0.0000265805,0.9854068,0.005354008,0.0006220692,0.0004091539,0.000007721451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7451389,0.001108587,0.2454853,0.000491862,0.0001255361,0.0001269411,0.002116621,0.002437978,0.002968227],"genre_scores_gemma":[0.9578632,0.0003784865,0.03708432,0.0001131846,0.0000408643,0.00003921835,0.002512849,0.00004548558,0.001922283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01507868,"threshold_uncertainty_score":0.02998179,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3163104826","doi":"10.32473/flairs.v34i1.128490","title":"Weakly Semi Supervised learning based Mixture Model With Two-Level Constraints","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pairwise comparison; Mixture model; Robustness (evolution); Cluster analysis; Class (philosophy); Computer science; Artificial intelligence; Synthetic data; Machine learning; Pattern recognition (psychology); Data mining","authors":[{"name":"Adama Nouboukpo","is_ca":true},{"name":"Mohand Saïd Allili","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.164536875868728,"gpt":0.3525063937222555,"spread":0.1879695178535275,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004055657,0.001506473,0.003114256,0.002004428,0.000866248,0.002504024,0.005782817,0.002388077,0.001988039],"category_scores_gemma":[0.009794896,0.001403944,0.002070911,0.002040708,0.002121738,0.004216969,0.004236447,0.003864401,0.001320172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001392747,"about_ca_system_score_gemma":0.001740058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00310841,"about_ca_topic_score_gemma":0.00385586,"domain_scores_codex":[0.995439,0.001922652,0.0002181108,0.001090503,0.001071974,0.0002577725],"domain_scores_gemma":[0.9933802,0.003293019,0.0006710846,0.001191153,0.001165018,0.0002994797],"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":[0.0004964379,0.0003222053,0.003402407,0.0003377122,0.0004295571,0.0001938586,0.0005257257,0.6509764,0.009372731,0.04930041,0.005060543,0.279582],"study_design_scores_gemma":[0.000007099988,0.00002132935,0.00008495252,0.000005211591,0.000008545375,0.0000143976,0.000006350232,0.988687,0.000659233,0.01014253,0.0003545565,0.00000878072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002783619,0.00008241201,0.9965125,0.00006972838,0.000009567097,0.00002408044,0.00003342316,0.0002727577,0.0002120432],"genre_scores_gemma":[0.2811156,0.0003211341,0.7105331,0.0005451023,0.0001811033,0.0006156776,0.001086232,0.0004383961,0.005163702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005782817,"threshold_uncertainty_score":0.02144867,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4377018759","doi":"10.32473/flairs.36.133326","title":"Improving Word Embedding Using Variational Dropout","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Dropout (neural networks); Word (group theory); Computer science; Word embedding; Artificial intelligence; Overfitting; Orthogonality; Natural language processing; Embedding; Curse of dimensionality; Inference; Machine learning; Mathematics; Artificial neural network","authors":[{"name":"Zainab Albujasim","is_ca":true},{"name":"Diana Inkpen","is_ca":true},{"name":"Xuejun Han","is_ca":true},{"name":"Yuhong Guo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1990856946383329,"gpt":0.3984730303623926,"spread":0.1993873357240597,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00148661,0.00127406,0.001237275,0.0007053753,0.0004025884,0.000938547,0.001244108,0.001312122,0.002306706],"category_scores_gemma":[0.005767515,0.0005940022,0.0009441224,0.0009599549,0.000928903,0.003714071,0.001934314,0.002178186,0.001179271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008946741,"about_ca_system_score_gemma":0.001584064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006194534,"about_ca_topic_score_gemma":0.009136427,"domain_scores_codex":[0.9991894,0.0002777096,0.00005555251,0.0001981883,0.0001946113,0.00008455911],"domain_scores_gemma":[0.9984286,0.0008253852,0.0001231435,0.0002558579,0.0002995227,0.00006733058],"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":[0.0002578261,0.0002700956,0.00182205,0.0002584322,0.0001593593,0.0001697836,0.0003122741,0.5099939,0.0198684,0.02538582,0.01120568,0.4302964],"study_design_scores_gemma":[0.00000983785,0.00002441917,0.00008411009,0.000005178446,0.000007348428,0.00001468543,0.00001123915,0.991671,0.001954038,0.005548051,0.000664423,0.000005670918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02283635,0.000402941,0.974032,0.0002703129,0.00006891049,0.00003996668,0.0001219536,0.001351364,0.0008761932],"genre_scores_gemma":[0.4892154,0.000953303,0.496105,0.0006780776,0.000151392,0.0002735756,0.002209103,0.0006970065,0.009717136],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006194534,"threshold_uncertainty_score":0.01231694,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400282308","doi":"10.32473/flairs.37.1.135277","title":"Embedding Ethics Into Artificial Intelligence: Understanding What Can Be Done, What Can't, and What Is Done","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Université du Québec à Trois-Rivières","keywords":"Embedding; Engineering ethics; Ethics of technology; Computer science; Ethical issues; Ethical decision; Management science; Sociology; Artificial intelligence; Information ethics; Engineering; Meta-ethics","authors":[{"name":"Clayton Peterson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3507927044911351,"gpt":0.4780498345077304,"spread":0.1272571300165953,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07666136,0.0009620856,0.00139408,0.002670821,0.009422322,0.02427558,0.002909402,0.0133058,0.00182418],"category_scores_gemma":[0.08181882,0.0007963679,0.0009410286,0.001837296,0.11428,0.03864697,0.008159455,0.01976046,0.0006424344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009911606,"about_ca_system_score_gemma":0.01726605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004694721,"about_ca_topic_score_gemma":0.004478829,"domain_scores_codex":[0.9186954,0.06323274,0.002032821,0.002510001,0.01102089,0.00250811],"domain_scores_gemma":[0.8199031,0.1436532,0.008990156,0.008682945,0.01409088,0.004679759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001175614,0.00002167558,0.0005629273,0.0002006769,0.00001896821,0.00009595069,0.01725978,0.0004232546,0.0001092663,0.9642294,0.004077516,0.01298862],"study_design_scores_gemma":[0.00000660019,0.00001259061,0.0002828042,0.0007092928,0.000006989817,0.00008641341,0.009419019,0.0005990277,0.0001504588,0.9495674,0.03913212,0.00002728343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02270975,0.01858104,0.08029285,0.7492864,0.002638431,0.0001189102,0.00005489962,0.00006932422,0.1262484],"genre_scores_gemma":[0.8854133,0.0123388,0.03242374,0.06127581,0.002385626,0.0003868259,0.00003901832,0.0001473348,0.005589545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07666136,"threshold_uncertainty_score":0.4054288,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400282035","doi":"10.32473/flairs.37.1.135283","title":"Assessing the Impact of Sequence Length Learning on Classification Tasks for Transformer Encoder Models","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Encoder; Transformer; Computer science; Artificial intelligence; Sequence (biology); Sequence learning; Speech recognition; Pattern recognition (psychology); Engineering; Electrical engineering; Biology; Voltage","authors":[{"name":"Jean-Thomas Baillargeon","is_ca":true},{"name":"Luc Lamontagne","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.374587593761272,"gpt":0.4799399593753982,"spread":0.1053523656141263,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03014402,0.002217447,0.001216021,0.001650325,0.001592719,0.003075406,0.00179318,0.003311426,0.003292997],"category_scores_gemma":[0.1243499,0.0007531285,0.001087412,0.001308373,0.00178635,0.008320585,0.002933924,0.004920341,0.001459945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003784844,"about_ca_system_score_gemma":0.003063693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01186086,"about_ca_topic_score_gemma":0.01664337,"domain_scores_codex":[0.9908693,0.005388341,0.0007289827,0.001119944,0.001263526,0.0006300255],"domain_scores_gemma":[0.8531854,0.1286976,0.00304978,0.007007791,0.0066379,0.00142141],"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":[0.004130135,0.001417995,0.06139661,0.0003923931,0.0004878714,0.0001910973,0.0003214013,0.6283706,0.003851882,0.007082144,0.006173405,0.2861845],"study_design_scores_gemma":[0.00009374776,0.0006092315,0.00295584,0.00006035316,0.00008936613,0.00005311493,0.0001755105,0.9844876,0.00388428,0.007092978,0.0004647359,0.00003328101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8498836,0.003351027,0.1267269,0.00594222,0.0003232481,0.0004517726,0.00110956,0.001934158,0.01027745],"genre_scores_gemma":[0.958795,0.0004519157,0.0367514,0.0004626612,0.0001046876,0.0001808985,0.001301281,0.0001639314,0.00178822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03014402,"threshold_uncertainty_score":0.1594187,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400281194","doi":"10.32473/flairs.37.1.135320","title":"Developing a predictive model using multivariate analysis and Long Short-Term Memory (LSTM) to assess corrosion degradation in mining pipeline thickness.","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Pipeline (software); Degradation (telecommunications); Multivariate statistics; Long short term memory; Term (time); Corrosion; Computer science; Multivariate analysis; Artificial intelligence; Data mining; Machine learning; Materials science; Metallurgy; Artificial neural network; Telecommunications","authors":[{"name":"Kalidou Moussa Sow","is_ca":false},{"name":"Nadia Ghazzali","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2239269259411425,"gpt":0.4080404702413655,"spread":0.184113544300223,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006550876,0.0008967748,0.0004104546,0.0005820353,0.0002153102,0.0005521218,0.0007474415,0.0006842946,0.0007092154],"category_scores_gemma":[0.001536267,0.000340751,0.00062276,0.0004923717,0.0002573009,0.0008563114,0.0004652069,0.001295297,0.0002284422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000520999,"about_ca_system_score_gemma":0.0006092118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00751891,"about_ca_topic_score_gemma":0.009702972,"domain_scores_codex":[0.9998442,0.0000243589,0.00001021045,0.00005305423,0.00004234942,0.00002581262],"domain_scores_gemma":[0.9995427,0.0001989937,0.00008295655,0.00003639572,0.0001218453,0.0000170594],"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":[0.0001483725,0.0001835138,0.00967892,0.0001064034,0.000188622,0.0002062185,0.00008019256,0.8104042,0.02120676,0.001558454,0.001559453,0.1546789],"study_design_scores_gemma":[0.000001036949,0.00001498374,0.0004896516,0.000002318631,0.000007978542,0.0000113459,0.000004197049,0.9976352,0.001426223,0.0003160859,0.00008743619,0.000003564045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1398101,0.0004802611,0.8560222,0.000458035,0.0001486713,0.00005008847,0.0002725098,0.001501141,0.001257096],"genre_scores_gemma":[0.932725,0.0002430687,0.06497055,0.00009747745,0.00004383098,0.0000635378,0.0002697714,0.00004843063,0.00153826],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00751891,"threshold_uncertainty_score":0.01495028,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375858679","doi":"10.32473/flairs.36.133203","title":"Further Thoughts on Defining f(x) for Ethical Machines: Ethics, Rational Choice, and Risk Analysis","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Consequentialism; Utilitarianism; Deontological ethics; Normative; Perspective (graphical); Ethical theory; Epistemology; Rational agent; Normative ethics; Management science; Engineering ethics; Computer science; Risk analysis (engineering); Sociology; Economics; Artificial intelligence; Philosophy; Business; Engineering","authors":[{"name":"Clayton Peterson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2636580989225152,"gpt":0.4931448676318907,"spread":0.2294867687093755,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01270121,0.00140661,0.001263973,0.002329197,0.003353846,0.007589223,0.002482183,0.00771712,0.02006332],"category_scores_gemma":[0.02232927,0.0004742944,0.001839354,0.001807792,0.02024493,0.01838951,0.002860504,0.009816999,0.002078651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004046922,"about_ca_system_score_gemma":0.001867714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003909535,"about_ca_topic_score_gemma":0.00360672,"domain_scores_codex":[0.9931113,0.004985767,0.0002556073,0.000542318,0.0007308353,0.0003742476],"domain_scores_gemma":[0.9840996,0.01202546,0.0008730965,0.0008853255,0.001483592,0.0006330021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005340305,0.000009637608,0.00006975722,0.00002132688,0.000002554243,0.00003373307,0.0004771836,0.0003765071,0.00003329958,0.9942312,0.003178279,0.001561195],"study_design_scores_gemma":[0.000004981396,0.000007480272,0.0001061816,0.00008271173,0.000001860269,0.00003517391,0.0005453896,0.001112543,0.00004714386,0.9764367,0.02160411,0.00001582834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01608854,0.01857361,0.3490917,0.4477201,0.00442056,0.0002043906,0.0003388575,0.0002075134,0.1633547],"genre_scores_gemma":[0.5704842,0.01303072,0.3063522,0.05355053,0.00822885,0.001198526,0.0003127973,0.0004651121,0.04637699],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02006332,"threshold_uncertainty_score":0.06717122,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3163694547","doi":"10.32473/flairs.v34i1.128506","title":"Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Markov chain Monte Carlo; Cluster analysis; Computer science; Mixture model; Multinomial distribution; Artificial intelligence; Bayesian probability; Machine learning; Generative model; Flexibility (engineering); Task (project management); Dirichlet distribution; Statistical model; Data mining; Generative grammar; Mathematics; Statistics; Engineering","authors":[{"name":"Xuanbo Su","is_ca":true},{"name":"Nizar Bouguila","is_ca":true},{"name":"Nuha Zamzami","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2869876506097959,"gpt":0.4139066479645853,"spread":0.1269189973547895,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004081883,0.00115218,0.001987075,0.003288658,0.001740748,0.002789275,0.00393278,0.002244259,0.006051066],"category_scores_gemma":[0.01455848,0.001454385,0.00225586,0.002222525,0.001512818,0.002586794,0.002485435,0.003030856,0.00331153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001784567,"about_ca_system_score_gemma":0.002154474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01965917,"about_ca_topic_score_gemma":0.02802691,"domain_scores_codex":[0.9976537,0.0009334668,0.0001472564,0.0005344904,0.000535889,0.0001952238],"domain_scores_gemma":[0.9927846,0.00437531,0.0003734315,0.001064185,0.001143911,0.0002585737],"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":[0.0003639413,0.0001770876,0.003671189,0.0002182768,0.0002340411,0.0002992361,0.0005034532,0.7378125,0.003157733,0.06761918,0.007555472,0.1783879],"study_design_scores_gemma":[0.000006858806,0.000005938508,0.0001138909,0.000007992006,0.000007518369,0.00001942314,0.00001318335,0.9914209,0.0004686842,0.007078631,0.0008457598,0.00001119081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008802538,0.0002179587,0.98748,0.000156634,0.00006779042,0.00007454272,0.0001937679,0.001411741,0.00159502],"genre_scores_gemma":[0.2234373,0.0003938188,0.7611475,0.0002954554,0.0002114157,0.0004313921,0.003756224,0.001069416,0.00925756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01965917,"threshold_uncertainty_score":0.03908944,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400281282","doi":"10.32473/flairs.37.1.135043","title":"Latent Beta-Liouville Probabilistic Modeling for Bursty Topic Discovery in Textual Data","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Latent Dirichlet allocation; Burstiness; Perplexity; Computer science; Topic model; Natural language processing; Language model; Word (group theory); Probabilistic logic; Dirichlet distribution; Artificial intelligence; Range (aeronautics); Mathematics","authors":[{"name":"Shadan Ghadimi","is_ca":true},{"name":"Hafsa Ennajari","is_ca":false},{"name":"Nizar Bouguila","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.312632176089768,"gpt":0.4053127273422721,"spread":0.09268055125250407,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00628075,0.001071129,0.001454204,0.003158941,0.0009918342,0.002457791,0.002702292,0.001716249,0.001771866],"category_scores_gemma":[0.01793885,0.000863705,0.001915308,0.003793295,0.001209255,0.004340183,0.00181695,0.003120669,0.001285547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00177307,"about_ca_system_score_gemma":0.00154641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006063833,"about_ca_topic_score_gemma":0.008995128,"domain_scores_codex":[0.9970432,0.001615011,0.0001805525,0.0006488183,0.0003556696,0.0001568558],"domain_scores_gemma":[0.9882549,0.00969338,0.000696808,0.0006383503,0.0005279176,0.0001886834],"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":[0.0005610827,0.000306105,0.01214641,0.0005193325,0.0003615383,0.000391866,0.002071893,0.6198452,0.007733351,0.1296463,0.006779127,0.2196378],"study_design_scores_gemma":[0.000009448769,0.00001351928,0.0002810448,0.000012514,0.00001008036,0.00003044076,0.00003043307,0.9693089,0.0002895196,0.0290683,0.0009325783,0.00001323533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01500043,0.0007266686,0.9825211,0.000332715,0.00003541642,0.00007918816,0.0003539375,0.0004850637,0.0004655456],"genre_scores_gemma":[0.5462656,0.002145446,0.440585,0.0004926473,0.0004507722,0.001276413,0.003342647,0.000364822,0.005076603],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00628075,"threshold_uncertainty_score":0.03321618,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3161484751","doi":"10.32473/flairs.v34i1.128508","title":"Representing Time Series Data in Intelligent Training Systems","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Dynamic time warping; Computer science; Embedding; Simple (philosophy); Euclidean distance; Time series; Representation (politics); Series (stratigraphy); Artificial intelligence; Machine learning; Data mining","authors":[{"name":"Shengnan Hu","is_ca":false},{"name":"Zerong Xi","is_ca":false},{"name":"Greg McGowin","is_ca":false},{"name":"Gita Sukthankar","is_ca":false},{"name":"Stephen M. Fiore","is_ca":false},{"name":"Kevin Oden","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2591728554641427,"gpt":0.3711537784040096,"spread":0.1119809229398669,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002001162,0.0006902138,0.0006453082,0.001427593,0.0002990541,0.001601181,0.0006644632,0.0009930539,0.001030703],"category_scores_gemma":[0.006978805,0.0002481806,0.0004857905,0.002173949,0.0006909743,0.002059046,0.0008370521,0.001139362,0.0003063208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008299149,"about_ca_system_score_gemma":0.0004717121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00484891,"about_ca_topic_score_gemma":0.002194664,"domain_scores_codex":[0.9990151,0.0004751119,0.0001045508,0.0001768728,0.000174639,0.00005371046],"domain_scores_gemma":[0.9977849,0.001510805,0.0002178105,0.0002245517,0.0002141026,0.00004792475],"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":[0.0001143347,0.00007519281,0.004062152,0.0001407828,0.00007456433,0.0001268878,0.0002095601,0.8251569,0.001735224,0.03725469,0.001757424,0.1292924],"study_design_scores_gemma":[0.000003603722,0.00002170288,0.0004682823,0.00001054646,0.000006003544,0.00001359714,0.00003187669,0.9821768,0.0003177964,0.01591572,0.00102522,0.000008937393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04184944,0.00156598,0.9529646,0.0008210599,0.0001744512,0.00005746631,0.0005284191,0.0005289914,0.001509658],"genre_scores_gemma":[0.7844898,0.002113246,0.2096793,0.0001604704,0.0002576492,0.0001919771,0.001288532,0.00006841304,0.001750753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00484891,"threshold_uncertainty_score":0.01058328,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4229048432","doi":"10.32473/flairs.v35i.130724","title":"Vehicle Traffic Estimation Using Deep Learning","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Traffic Prediction and Management Techniques","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":"Acadia University","funders":"","keywords":"Mean absolute percentage error; Traffic flow (computer networking); Computer science; Artificial neural network; Convolutional neural network; Mean squared error; Deep learning; Word error rate; Statistics; Meteorology; Artificial intelligence; Geography; Mathematics","authors":[{"name":"Meetkumar Patel","is_ca":true},{"name":"Daniel Silver","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08944595839567647,"gpt":0.3304626479577519,"spread":0.2410166895620754,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002944809,0.0009837357,0.0006088878,0.001771157,0.0002997223,0.0007100232,0.0009395303,0.0007303342,0.002358478],"category_scores_gemma":[0.001180818,0.0005252155,0.0006855446,0.001361535,0.0002401759,0.0009592336,0.0006467578,0.0009300334,0.001102951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143054,"about_ca_system_score_gemma":0.0009116603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03011363,"about_ca_topic_score_gemma":0.02575565,"domain_scores_codex":[0.9997811,0.00002279633,0.00001000241,0.00007609167,0.00005165884,0.00005842586],"domain_scores_gemma":[0.9997159,0.00007000871,0.00004193409,0.00002415305,0.0001273523,0.00002058148],"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":[0.0000888453,0.0001387478,0.006342879,0.00006555623,0.00007773977,0.00007276988,0.0000209446,0.7921503,0.002422259,0.002417878,0.005436427,0.1907658],"study_design_scores_gemma":[0.000001710763,0.000004095938,0.0004559043,0.000003921806,0.000002835532,0.000005130975,0.000003586185,0.9979271,0.000353542,0.0009459641,0.0002934774,0.00000277559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1610971,0.001241335,0.8178598,0.0004819156,0.0002904191,0.0000883213,0.002645352,0.005217218,0.01107848],"genre_scores_gemma":[0.933225,0.0004925989,0.05491889,0.00013201,0.0001030718,0.00008244545,0.004088077,0.00008625323,0.006871778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03011363,"threshold_uncertainty_score":0.05987674,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375858784","doi":"10.32473/flairs.36.133365","title":"Towards binary encoding in Bidirectional Associative Memories","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Encoding (memory); Computer science; Associative property; Binary number; Cognition; Bidirectional associative memory; Task (project management); Recall; Artificial intelligence; Content-addressable memory; Transmission (telecommunications); Function (biology); Artificial neural network; Pattern recognition (psychology); Cognitive psychology; Psychology; Neuroscience; Arithmetic; Mathematics; Biology; Engineering","authors":[{"name":"Thaddé Rolon-Merette","is_ca":true},{"name":"Damiem Rolon-Mérette","is_ca":true},{"name":"Sylvain Chartier","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1746696167332556,"gpt":0.3893567369444212,"spread":0.2146871202111656,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000571414,0.0002775807,0.0002865682,0.0003582399,0.0001867387,0.00106415,0.0005672038,0.0004588609,0.002000529],"category_scores_gemma":[0.002530163,0.000167014,0.0001843114,0.0003711952,0.0005143206,0.002241202,0.0006968722,0.0007523112,0.0003658675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002713312,"about_ca_system_score_gemma":0.0002885002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003774187,"about_ca_topic_score_gemma":0.0002474626,"domain_scores_codex":[0.9998054,0.00007185069,0.00001549491,0.00003093854,0.00005001364,0.00002629609],"domain_scores_gemma":[0.9989625,0.0004976651,0.000144714,0.0001576305,0.0001719564,0.0000655426],"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":[0.0009456838,0.0002863344,0.001581772,0.0005189283,0.00006009214,0.0002732283,0.0004028331,0.08669195,0.1096241,0.520475,0.002120601,0.2770196],"study_design_scores_gemma":[0.00005266598,0.0002158492,0.0006420069,0.00005973691,0.00003194426,0.0002584867,0.0001037714,0.5953139,0.03043613,0.3684097,0.004445422,0.00003048114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2657493,0.001176834,0.7206918,0.0005147897,0.0001684899,0.00004970935,0.0001422106,0.0005254441,0.01098146],"genre_scores_gemma":[0.8932109,0.0006592461,0.103665,0.0001204123,0.00005383358,0.00004431186,0.0001125321,0.00004047467,0.002093295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002000529,"threshold_uncertainty_score":0.006692469,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4229048469","doi":"10.32473/flairs.v35i.130722","title":"Generative Adversarial learning with Negative Data Augmentation for Semi-supervised Text Classification","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Discriminator; Generator (circuit theory); Computer science; Generative grammar; Manifold (fluid mechanics); Representation (politics); Boundary (topology); Artificial intelligence; Pattern recognition (psychology); Feature (linguistics); Mode (computer interface); Generative model; Decision boundary; Matching (statistics); Mixing (physics); Key (lock); Power (physics); Machine learning; Mathematics; Statistics; Physics; Support vector machine","authors":[{"name":"Shahriar Shayesteh","is_ca":true},{"name":"Diana Inkpen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.214596084131797,"gpt":0.3702213578985494,"spread":0.1556252737667524,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002523105,0.001422997,0.001193768,0.0006089273,0.0004904991,0.00082825,0.001687357,0.001249223,0.002558738],"category_scores_gemma":[0.006706718,0.0004126874,0.0009913344,0.0005742011,0.001458097,0.001712235,0.001518738,0.00315511,0.001324169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008705503,"about_ca_system_score_gemma":0.0006544998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001518233,"about_ca_topic_score_gemma":0.001893615,"domain_scores_codex":[0.9979493,0.0009979914,0.0000786407,0.0004769943,0.0003629411,0.0001341352],"domain_scores_gemma":[0.9950662,0.003221975,0.0003627353,0.0008238204,0.0003664187,0.0001588992],"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":[0.0006192328,0.0003863774,0.002965853,0.0002889709,0.0001139477,0.0002750733,0.0003116412,0.7412022,0.01084869,0.0146294,0.01187312,0.2164855],"study_design_scores_gemma":[0.00000783578,0.0000251585,0.0001407766,0.000006872043,0.000003196577,0.00002683945,0.00000808507,0.9926885,0.001575706,0.004985751,0.0005244234,0.000006911755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05502743,0.0010671,0.9336601,0.0008503127,0.0001921009,0.0001365451,0.0004213064,0.004530338,0.004114642],"genre_scores_gemma":[0.7919986,0.0003160998,0.1993062,0.0008224951,0.0001475927,0.0002990685,0.001772543,0.0003726616,0.004964786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002558738,"threshold_uncertainty_score":0.01334363,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400281600","doi":"10.32473/flairs.37.1.135596","title":"Decoding Complexity: A Mathematical Framework for Enhanced Translation Comprehension","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Decoding methods; Translation (biology); Computer science; Comprehension; Natural language processing; Theoretical computer science; Artificial intelligence; Cognitive science; Programming language; Psychology; Algorithm; Biology; Genetics","authors":[{"name":"É. Poirier","is_ca":true},{"name":"Ansta Nasandratra Nirina Avo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.27049055119903,"gpt":0.4406814160020632,"spread":0.1701908648030332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006477714,0.001364044,0.001061351,0.004330984,0.00151336,0.00663204,0.002713767,0.002307544,0.006797223],"category_scores_gemma":[0.02917723,0.0008436084,0.003583827,0.00256472,0.00708282,0.01568695,0.004049574,0.004430502,0.002235767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003538998,"about_ca_system_score_gemma":0.001893308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001956902,"about_ca_topic_score_gemma":0.001189096,"domain_scores_codex":[0.9943411,0.002578515,0.000533207,0.0008060605,0.001415421,0.0003256608],"domain_scores_gemma":[0.9824525,0.01215789,0.001444778,0.001782465,0.001898235,0.0002641688],"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":[0.00001918052,0.00001379808,0.0001857462,0.00008578786,0.00001546297,0.00007189903,0.0003044743,0.01284436,0.0005764253,0.9745545,0.0007342536,0.01059394],"study_design_scores_gemma":[0.000008838751,0.00002552322,0.00008812571,0.00002750968,0.00001290161,0.00007587664,0.00004468055,0.07057519,0.0004959204,0.9246936,0.003929715,0.0000220563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005520156,0.0004461025,0.9810448,0.001212044,0.00009645996,0.00005627157,0.000144421,0.0001978841,0.01128191],"genre_scores_gemma":[0.3254815,0.001215984,0.659814,0.000700181,0.0009114793,0.0005777251,0.0005177859,0.0004794056,0.01030194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006797223,"threshold_uncertainty_score":0.03425783,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375858861","doi":"10.32473/flairs.36.133230","title":"Biogeography-based optimization for feature selection","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Cluster analysis; Data mining; Computer science; Cluster (spacecraft); Selection (genetic algorithm); Feature selection; Biogeography; Feature (linguistics); Machine learning; Artificial intelligence; Ecology; Biology","authors":[{"name":"Mandana Gholami","is_ca":true},{"name":"Malek Mouhoub","is_ca":true},{"name":"Samira Sadaoui","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1306504308282535,"gpt":0.3887174398760385,"spread":0.258067009047785,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001282501,0.001002075,0.00119735,0.001141927,0.0005237163,0.0007637212,0.001021251,0.0009857086,0.00216659],"category_scores_gemma":[0.002978296,0.0004384042,0.0008866024,0.001490578,0.0007142761,0.0009323495,0.0008416012,0.0008013438,0.0004826919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007668819,"about_ca_system_score_gemma":0.001344299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004385454,"about_ca_topic_score_gemma":0.003226164,"domain_scores_codex":[0.9993435,0.0002301561,0.00004246743,0.000149325,0.0001633563,0.00007128374],"domain_scores_gemma":[0.9993912,0.0003096936,0.00006690935,0.00003792956,0.0001615034,0.00003262245],"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":[0.00009254761,0.00008603003,0.002439285,0.0001563668,0.000112409,0.0001190468,0.00006062229,0.8522724,0.005834355,0.01131477,0.003376202,0.1241359],"study_design_scores_gemma":[0.00001741166,0.00002610851,0.0004108477,0.000008871652,0.000009172451,0.000028603,0.000009166749,0.9943892,0.0006550921,0.003496448,0.0009422797,0.000006758814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01204918,0.0004617839,0.9851564,0.0002973527,0.00005057819,0.00007162798,0.00008093772,0.00023455,0.001597571],"genre_scores_gemma":[0.3818566,0.0005514357,0.6125706,0.0004321824,0.00009682309,0.0005622531,0.0005907025,0.000203145,0.003136313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004385454,"threshold_uncertainty_score":0.008719802,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375858707","doi":"10.32473/flairs.36.133373","title":"Using Knowledge Graph Embedding for Fault Detection","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Industrial Vision Systems and Defect Detection","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 Windsor","funders":"","keywords":"Automotive industry; Fault detection and isolation; Automotive engineering; Fault (geology); Electric vehicle; Computer science; Engineering; Business; Artificial intelligence; Power (physics); Actuator","authors":[{"name":"Ziad Kobti","is_ca":true},{"name":"Joseph El-Ghaname","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2955318834200215,"gpt":0.4257532962685253,"spread":0.1302214128485037,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007769265,0.002302327,0.00137919,0.004806291,0.0006555889,0.00116972,0.001927701,0.002238332,0.005029867],"category_scores_gemma":[0.005428591,0.0005952332,0.001818987,0.001976898,0.0007500027,0.002722656,0.001447316,0.001681484,0.001622106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001356627,"about_ca_system_score_gemma":0.001330554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01676132,"about_ca_topic_score_gemma":0.01550557,"domain_scores_codex":[0.9986081,0.0002338165,0.0001052082,0.0004854435,0.0003655714,0.0002019314],"domain_scores_gemma":[0.9972892,0.001676348,0.0002619675,0.0002802517,0.0004193005,0.00007290744],"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":[0.0006322712,0.0003920239,0.009162526,0.0007736454,0.0003439724,0.000967829,0.0001730692,0.3743917,0.006657214,0.009024907,0.02072632,0.5767546],"study_design_scores_gemma":[0.00002325519,0.00007683694,0.0008381984,0.00003792129,0.00006060851,0.0001895573,0.00006679065,0.9771793,0.002126763,0.01670758,0.002676858,0.00001626093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0516687,0.002755418,0.9224541,0.001256263,0.000354792,0.0003550607,0.004698724,0.01073507,0.005721871],"genre_scores_gemma":[0.7722243,0.001108747,0.2064185,0.0005867266,0.000194019,0.0003351768,0.01241233,0.0003997005,0.006320382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01676132,"threshold_uncertainty_score":0.03332746,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4375858688","doi":"10.32473/flairs.36.133140","title":"Using Bidirectional Associative Memory Neural Networks to Solve the N-bit Task","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial neural network; Content-addressable memory; Task (project management); Bidirectional associative memory; Identifier; Associative property; Artificial intelligence; Arithmetic; Mathematics","authors":[{"name":"Damiem Rolon-Mérette","is_ca":true},{"name":"Thaddé Rolon-Merette","is_ca":true},{"name":"Sylvain Chartier","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2190795194833,"gpt":0.3981573109817071,"spread":0.1790777914984071,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005048992,0.0007159017,0.0004256818,0.0002362784,0.0003369476,0.00069185,0.001034302,0.0007904713,0.003354617],"category_scores_gemma":[0.001480533,0.0002679154,0.0004234484,0.0002970188,0.0004016148,0.001903458,0.0009034558,0.001095133,0.000763201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000436894,"about_ca_system_score_gemma":0.0008268055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003680617,"about_ca_topic_score_gemma":0.005512685,"domain_scores_codex":[0.9998578,0.00002817695,0.0000110475,0.00004285281,0.00002534336,0.00003467719],"domain_scores_gemma":[0.9996172,0.000149055,0.00005275796,0.00008920077,0.00006426981,0.00002752018],"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":[0.0006082745,0.000497013,0.003300729,0.0003470873,0.0001313635,0.0002705846,0.0003444657,0.5159581,0.07136797,0.02863655,0.003935838,0.3746019],"study_design_scores_gemma":[0.00001864307,0.0001062125,0.0002277889,0.00001135392,0.0000211134,0.00004117973,0.00002812628,0.973119,0.01318177,0.01176155,0.001471043,0.00001224907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.24941,0.0004754482,0.7347016,0.0006467171,0.0002075171,0.0001528235,0.0001661344,0.002417079,0.01182261],"genre_scores_gemma":[0.8100836,0.0002953488,0.1803045,0.0001602997,0.00003671396,0.0001713752,0.0002036985,0.00009571495,0.008648668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003680617,"threshold_uncertainty_score":0.0112223,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410398250","doi":"10.32473/flairs.38.1.138756","title":"Incorporating Wave-ViT for Breast Cancer Diagnosis Using MRI Imaging","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Advanced MRI Techniques and Applications","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":"Memorial University of Newfoundland","funders":"","keywords":"Breast cancer; Medicine; Radiology; Magnetic resonance imaging; Breast MRI; Cancer; Mammography; Medical physics; Internal medicine","authors":[{"name":"Sahil Mahey","is_ca":true},{"name":"Hamid Usefi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1759041074243973,"gpt":0.4583605814808804,"spread":0.2824564740564831,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001363319,0.000535226,0.0005261023,0.001027007,0.0002125971,0.000849441,0.001063964,0.0006172415,0.0009432035],"category_scores_gemma":[0.003577033,0.0002857104,0.0006010475,0.0003748549,0.0002943063,0.0009634955,0.0008455874,0.000671664,0.0007757468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004532748,"about_ca_system_score_gemma":0.0006578307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003119514,"about_ca_topic_score_gemma":0.004948176,"domain_scores_codex":[0.999703,0.00007711413,0.00002145127,0.00007867228,0.00008134164,0.00003831922],"domain_scores_gemma":[0.9992855,0.0003130825,0.00006016495,0.0001096874,0.0001966546,0.00003484682],"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":[0.0006116495,0.0003452076,0.02347228,0.0001467564,0.0001934162,0.000229833,0.00009798232,0.1924901,0.03458763,0.001984385,0.00437464,0.7414662],"study_design_scores_gemma":[0.00001727105,0.0001407755,0.001763876,0.000008130756,0.00003775483,0.0001605479,0.00001788967,0.982369,0.01302413,0.001557579,0.0008917102,0.00001145171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2182768,0.0008374351,0.7696961,0.0008466591,0.0001534453,0.0002371785,0.0004343369,0.007035024,0.002483056],"genre_scores_gemma":[0.8118619,0.0002763397,0.184676,0.0003294897,0.00008271285,0.00008551767,0.0007922117,0.0001377133,0.001758262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003119514,"threshold_uncertainty_score":0.007210016,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4248507868","doi":"10.32473/flairs.v34i1.128751","title":"Committee Listings","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Nuclear Physics; Russian Academy of Sciences; Philips Research Americas; University of North Carolina at Charlotte; University of Colorado Boulder; Slovenská technická univerzita v Bratislave; University of Nicosia; Lomonosov Moscow State University; University of Texas at El Paso; International Institute for Applied Systems Analysis; Technological University Dublin; Nanjing University; Agricultural University of Athens; Los Alamos National Laboratory; National and Kapodistrian University of Athens; Universidade Federal do Rio Grande do Sul; Centre National de la Recherche Scientifique; Simon Fraser University; Université de Bretagne Occidentale; Radford University; Tsinghua University; Universität Wien; Università degli Studi di Milano-Bicocca; Université du Québec en Outaouais; University College Cork; Illinois State University; Aalborg Universitet; Indiana University Bloomington; International Science and Technology Center; Cardiff University; Tennessee Tech University; Office of Naval Research; Universität Trier; Florida Institute of Technology; Université du Québec à Trois-Rivières; Montana State University; Universitetet i Bergen; University of Miami; University of Texas at Arlington; University of South Carolina; Cyprus University of Technology; University of Regina; University of Louisiana at Lafayette; Middlesex University; Army Research Laboratory; Bradley University; Drexel University; Washington State University; Universidade Federal de São João del-Rei; University of Ottawa; University of Maryland, Baltimore County; DePaul University; Kennesaw State University; Dana-Farber/Harvard Cancer Center; University of Cyprus; Samsung; University of Southern California; University of Memphis; University of Manchester; University of Hartford; Universidade do Porto; Northwestern University; University of Central Florida; Tulane University; Concordia University; Central Connecticut State University; Université du Québec à Montréal; Korea University; Univerzita Karlova v Praze; Universiteit Gent; Universidade Federal de Pelotas; University of Pittsburgh; Clemson University; Massachusetts Institute of Technology","keywords":"Business","authors":[{"name":"Eric Bell","is_ca":false},{"name":"Fazel Keshtkar","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2526136666280347,"gpt":0.3352411544128727,"spread":0.08262748778483797,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004110449,0.001090084,0.001696354,0.003953099,0.002321691,0.006928483,0.002552947,0.003632844,0.7811971],"category_scores_gemma":[0.01586165,0.0006865812,0.001047503,0.003491702,0.0004849302,0.002790433,0.002576969,0.002634657,0.7874674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001509838,"about_ca_system_score_gemma":0.004931766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002342339,"about_ca_topic_score_gemma":0.005502452,"domain_scores_codex":[0.9972697,0.0003093455,0.0002149454,0.0003869669,0.001449949,0.0003691318],"domain_scores_gemma":[0.982837,0.001199992,0.0006124696,0.001285939,0.009361428,0.004703244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001821326,0.00001543585,0.00003910359,0.00006332551,0.000001424858,0.000009409715,0.000003683239,0.00002570527,0.00008459718,0.0005924451,0.9821864,0.01696022],"study_design_scores_gemma":[0.00001273677,0.00001221248,0.0002503448,0.00007184856,0.00000175297,0.00001591336,0.00001166571,0.0000401427,0.00007113479,0.0005106586,0.9989962,0.000005367808],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007724168,0.005369897,0.004136104,0.0273513,0.06982388,0.002012548,0.0301647,0.003556019,0.8568132],"genre_scores_gemma":[0.001174962,0.001713534,0.001031444,0.004976175,0.009237716,0.0007398166,0.01140074,0.0008127682,0.9689127],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7811971,"threshold_uncertainty_score":0.3120957,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3163052523","doi":"10.32473/flairs.v34i1.128478","title":"One game show, two boys, two aces, three prisoners - what’s an AI to do?","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","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 Saskatchewan","funders":"","keywords":"Counterintuitive; Simple (philosophy); Representation (politics); Pearl; Dice; Mathematical economics; Psychology; Computer science; Epistemology; Mathematics; Statistics; Philosophy; Law","authors":[{"name":"Eric Neufeld","is_ca":false},{"name":"Sonje Finnestad","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1688177085273532,"gpt":0.4016206498379394,"spread":0.2328029413105862,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001761174,0.0008057277,0.0005098189,0.0007321652,0.005625067,0.007653453,0.00165109,0.003505016,0.02135871],"category_scores_gemma":[0.00845223,0.0003479321,0.0006105767,0.0008563971,0.009063788,0.01367514,0.002961078,0.004724253,0.005495606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002973897,"about_ca_system_score_gemma":0.001451636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009083806,"about_ca_topic_score_gemma":0.009529455,"domain_scores_codex":[0.9984866,0.0007990063,0.00004638972,0.000188276,0.0002493374,0.0002303238],"domain_scores_gemma":[0.9976568,0.001426733,0.0001610234,0.0001753435,0.0002787727,0.0003012903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003269072,0.00003009572,0.0003265358,0.0001133092,0.00001251092,0.0001761674,0.001889095,0.0003626448,0.0001462108,0.9145654,0.06515042,0.01719487],"study_design_scores_gemma":[0.00001852591,0.00004927858,0.0004888603,0.0002321524,0.0000184968,0.0003734314,0.003404296,0.001769009,0.0006034915,0.4718519,0.5211443,0.00004625425],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02334795,0.02540706,0.08315363,0.254226,0.005180051,0.0001776542,0.0006035564,0.0009891789,0.6069149],"genre_scores_gemma":[0.6267946,0.01997284,0.05253853,0.0583114,0.002713497,0.0003637528,0.000650931,0.00106894,0.2375855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02135871,"threshold_uncertainty_score":0.07145196,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225387407","doi":"10.32473/flairs.v35i.130696","title":"The Place of Quasi Topological Structure in the Mathematical Theory of Categorization","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Fuzzy and Soft Set Theory","field":"Decision Sciences","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 du Québec à Trois-Rivières","funders":"","keywords":"Mathematical structure; Mathematical theory; Categorization; Category theory; Computer science; Point (geometry); Frame (networking); Topological space; Bridging (networking); Mathematics; Topology (electrical circuits); Artificial intelligence; Pure mathematics; Physics; Geometry","authors":[{"name":"Anca Pascu Pascu","is_ca":false},{"name":"Jean-Pierre Desclés","is_ca":false},{"name":"Ismaïl Biskri","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2642478696166664,"gpt":0.435318484020279,"spread":0.1710706144036126,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003282738,0.0003991709,0.0004608369,0.00256494,0.001629444,0.005109255,0.0008766326,0.001333719,0.003033918],"category_scores_gemma":[0.00452897,0.0003204333,0.0006827247,0.001727886,0.01207917,0.0106641,0.002653351,0.002124666,0.0004170145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002581909,"about_ca_system_score_gemma":0.001288871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008896646,"about_ca_topic_score_gemma":0.0006397515,"domain_scores_codex":[0.9982084,0.0009105621,0.00009597917,0.0002772491,0.0004072093,0.0001005285],"domain_scores_gemma":[0.9957032,0.00261148,0.00038315,0.0006414959,0.0004363101,0.00022435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003322751,0.000001943706,0.00006334763,0.00002080635,0.000002109555,0.00001065454,0.0001300054,0.0002620336,0.0001022682,0.9969976,0.0001416195,0.002264313],"study_design_scores_gemma":[0.000003579509,0.00001330619,0.0001172939,0.00001599198,0.000003432313,0.00003374094,0.00007753784,0.00232677,0.0001087014,0.9915069,0.005786364,0.000006400436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06390791,0.009047682,0.8374881,0.02063245,0.0007905701,0.00005756865,0.0002236361,0.0002273877,0.06762476],"genre_scores_gemma":[0.8684617,0.003185659,0.1206194,0.001067464,0.0007653337,0.0001674508,0.0001270745,0.00006005826,0.005545825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005109255,"threshold_uncertainty_score":0.01873314,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4376958591","doi":"10.32473/flairs.36.133320","title":"Multi-hop Question Generation without Supporting Fact Information","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of Lethbridge","keywords":"Hop (telecommunications); Computer science; Computer network","authors":[{"name":"John W. Emerson","is_ca":true},{"name":"Yllias Chali","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2237400688409685,"gpt":0.4126515714519567,"spread":0.1889115026109882,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002621965,0.001026373,0.0007611412,0.001290082,0.0004728625,0.001412171,0.002590695,0.001914932,0.006142131],"category_scores_gemma":[0.01048905,0.0004162857,0.00149744,0.0007114537,0.0006633353,0.004150319,0.002208237,0.001713872,0.002682691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008627549,"about_ca_system_score_gemma":0.00119796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002670679,"about_ca_topic_score_gemma":0.004014886,"domain_scores_codex":[0.9984161,0.0005078093,0.0001293794,0.0005387953,0.000322166,0.0000857363],"domain_scores_gemma":[0.994245,0.003391979,0.000217987,0.001255627,0.0007093892,0.0001800273],"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":[0.001190194,0.0009290164,0.007207166,0.001651763,0.0002151759,0.001565958,0.001921423,0.07823758,0.0493868,0.03754582,0.06806611,0.7520831],"study_design_scores_gemma":[0.0002098416,0.000304997,0.001361003,0.00008534894,0.000129116,0.0009806197,0.0003079752,0.8649828,0.04051219,0.04539859,0.04567204,0.00005545357],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05329023,0.000945919,0.8965982,0.00138417,0.0002771468,0.001192852,0.004742992,0.03454135,0.007027133],"genre_scores_gemma":[0.3709925,0.0003674231,0.6007304,0.0007015272,0.0000998757,0.000553549,0.01758598,0.0008625987,0.008106298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006142131,"threshold_uncertainty_score":0.02054751,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4377018773","doi":"10.32473/flairs.36.133317","title":"Evaluation of Techniques for Sim2Real Reinforcement Learning","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"","keywords":"Reinforcement learning; Computer science; Bridging (networking); Bridge (graph theory); Generalization; Noise (video); Domain (mathematical analysis); Human–computer interaction; Transfer of learning; Process (computing); Artificial intelligence; Mathematics","authors":[{"name":"Mahesh Ranaweera","is_ca":true},{"name":"Qusay H. Mahmoud","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2601722272290781,"gpt":0.4271582699048349,"spread":0.1669860426757567,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005848438,0.00120764,0.0007687734,0.0008203737,0.0005390255,0.0008935959,0.00262421,0.001437116,0.002931347],"category_scores_gemma":[0.01298637,0.000415013,0.0005343151,0.0005189807,0.001105518,0.001392223,0.001701382,0.00141121,0.0006370664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001959383,"about_ca_system_score_gemma":0.001315509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004506418,"about_ca_topic_score_gemma":0.003762133,"domain_scores_codex":[0.9969755,0.001344981,0.0002009855,0.0004719082,0.0007407754,0.0002658289],"domain_scores_gemma":[0.9915819,0.005168289,0.0004437659,0.001206476,0.001310241,0.0002894505],"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":[0.0008839319,0.000872548,0.002790639,0.0004223166,0.0001114798,0.00009392251,0.0001612733,0.8414201,0.004299598,0.00547519,0.001526103,0.1419429],"study_design_scores_gemma":[0.00006205021,0.0002369126,0.000254779,0.000009954087,0.000007419447,0.00002207156,0.00002236493,0.9940376,0.003944613,0.0006585622,0.0007363114,0.0000074013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2857092,0.001009764,0.69193,0.0005504204,0.0002461055,0.0007466574,0.000316072,0.007504613,0.01198718],"genre_scores_gemma":[0.7585954,0.0001719403,0.2383425,0.0001247214,0.00002157539,0.0003549735,0.0003622737,0.0002285651,0.00179797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005848438,"threshold_uncertainty_score":0.03092986,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410397730","doi":"10.32473/flairs.38.1.138888","title":"Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Topic Modeling","field":"Computer Science","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 Lethbridge","funders":"","keywords":"Automatic summarization; Natural language processing; Computer science; Linguistics; Artificial intelligence; Psychology; Philosophy","authors":[{"name":"Narjes Delpisheh","is_ca":true},{"name":"Yllias Chali","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1112441505932301,"gpt":0.3668951031233309,"spread":0.2556509525301008,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001358114,0.001259771,0.0007151769,0.00286619,0.0005008178,0.001743204,0.0008511275,0.0007390509,0.002117181],"category_scores_gemma":[0.008423135,0.0002896597,0.0006451962,0.001463619,0.0005046971,0.003046741,0.001515771,0.001270298,0.001766603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004282182,"about_ca_system_score_gemma":0.0006776933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001520477,"about_ca_topic_score_gemma":0.003515931,"domain_scores_codex":[0.9990348,0.0002620749,0.0001177642,0.0003080596,0.0002180779,0.00005929406],"domain_scores_gemma":[0.9958474,0.001851171,0.000573902,0.0006544811,0.0009474719,0.0001256887],"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":[0.0005153089,0.0001764935,0.002049022,0.0007710652,0.0001415944,0.0001957852,0.001263927,0.01014016,0.06175437,0.002840711,0.009431815,0.9107197],"study_design_scores_gemma":[0.000333789,0.001588437,0.01314427,0.0004330857,0.0009701766,0.0007229311,0.002638959,0.628181,0.2294352,0.03871696,0.08356969,0.0002656798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1093168,0.004892684,0.8627636,0.0009562013,0.0004029653,0.0004581764,0.002565918,0.01301558,0.005628157],"genre_scores_gemma":[0.4787946,0.001705763,0.4991707,0.0003819983,0.0005505877,0.0003126294,0.01010081,0.0008231969,0.008159783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00286619,"threshold_uncertainty_score":0.007182419,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160487084","doi":"10.32473/flairs.v34i1.128379","title":"Entropy-based Variational Learning of Finite Inverted Beta-Liouville Mixture Model","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Agence Nationale de la Recherche; Equipex","keywords":"Cluster analysis; Inference; Artificial intelligence; Entropy (arrow of time); Mixture model; Unsupervised learning; Computer science; Categorization; Pattern recognition (psychology); BETA (programming language); Kullback–Leibler divergence; Machine learning; Algorithm; Mathematics; Physics","authors":[{"name":"Narges Manouchehri","is_ca":true},{"name":"Mohammad Sadegh Ahmadzadeh","is_ca":true},{"name":"Hafsa Ennajari","is_ca":true},{"name":"Nizar Bouguila","is_ca":true},{"name":"Manar Amayri","is_ca":false},{"name":"Wentao Fan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.113545119647876,"gpt":0.3514613912485156,"spread":0.2379162716006397,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00319603,0.0006921837,0.00139527,0.001179119,0.0006120437,0.001424715,0.00242223,0.001360679,0.001864923],"category_scores_gemma":[0.007968672,0.0008164762,0.001236046,0.0008681567,0.001781846,0.002411529,0.0017774,0.002023411,0.0004548467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001502574,"about_ca_system_score_gemma":0.001265561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006006456,"about_ca_topic_score_gemma":0.005149459,"domain_scores_codex":[0.9990305,0.0004802334,0.00003757456,0.0001638277,0.0002080624,0.0000798004],"domain_scores_gemma":[0.9975181,0.001824031,0.0001410588,0.0001224869,0.0002832273,0.000111142],"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":[0.00006139933,0.00003290929,0.001016144,0.00006436528,0.00006010872,0.00006309777,0.000123047,0.8356134,0.001872286,0.1327383,0.0009812484,0.0273737],"study_design_scores_gemma":[0.000001890209,0.00000384163,0.00004408205,0.000002545668,0.000002129654,0.00000555912,0.000002470023,0.9876038,0.0001030623,0.01210178,0.0001244027,0.000004403355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005151858,0.0001246449,0.993969,0.00009398617,0.00001183595,0.00001024081,0.00002099334,0.00005889604,0.000558562],"genre_scores_gemma":[0.6271057,0.0008094687,0.363131,0.0003286738,0.0001399636,0.0002667023,0.0005711655,0.0003189759,0.007328517],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006006456,"threshold_uncertainty_score":0.01690245,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3160648873","doi":"10.32473/flairs.v34i1.128479","title":"Performance Metrics for State-Based Imitation Learning","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"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; Artificial intelligence; Perceptron; Artificial neural network; Machine learning; Imitation; Domain (mathematical analysis); State (computer science); Multilayer perceptron; Long short term memory; Layer (electronics); Recurrent neural network; Algorithm","authors":[{"name":"Mohamed Zalat","is_ca":true},{"name":"Babak Esfandiari","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1510561623617243,"gpt":0.3704275475126838,"spread":0.2193713851509595,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007180413,0.002059303,0.001570222,0.003121054,0.0006718426,0.002016601,0.002228359,0.002347708,0.002065314],"category_scores_gemma":[0.03981398,0.0003214053,0.0008495034,0.001552511,0.001521453,0.003407781,0.00188755,0.001586544,0.0008637852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00183888,"about_ca_system_score_gemma":0.001367278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004650779,"about_ca_topic_score_gemma":0.002937695,"domain_scores_codex":[0.9922143,0.00233081,0.0008933717,0.001076043,0.002981776,0.0005037947],"domain_scores_gemma":[0.9749196,0.01410016,0.002895673,0.002713993,0.004466019,0.000904528],"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":[0.0009363434,0.0005515306,0.01391016,0.0006237341,0.0005512945,0.0001334293,0.0001544858,0.7141324,0.01043898,0.007835326,0.003305642,0.2474266],"study_design_scores_gemma":[0.00002880982,0.000870642,0.003125008,0.00003569269,0.00005355798,0.0001237125,0.0000424262,0.9798036,0.01093626,0.004227843,0.0006907558,0.00006170708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1758769,0.002963165,0.7992241,0.0005743001,0.000475239,0.0005835107,0.00103153,0.006218071,0.01305309],"genre_scores_gemma":[0.8854594,0.0004448432,0.1096033,0.0001095402,0.00008680596,0.0004129463,0.001398142,0.0003368026,0.002148321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007180413,"threshold_uncertainty_score":0.03797406,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410397769","doi":"10.32473/flairs.38.1.139141","title":"Online Community Modeling and Moderation","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Social Media and Politics","field":"Social Sciences","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 Laval","funders":"","keywords":"Moderation; Psychology; Computer science; Social psychology","authors":[{"name":"Richard Khoury","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2771773974238197,"gpt":0.4584976435238617,"spread":0.181320246100042,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01016769,0.0008497754,0.001160435,0.003095004,0.002170583,0.002421831,0.002077783,0.001857236,0.004070822],"category_scores_gemma":[0.04833716,0.0006048396,0.001179844,0.002298825,0.002709517,0.005944472,0.004192964,0.002258424,0.000754822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001677909,"about_ca_system_score_gemma":0.001093942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005267534,"about_ca_topic_score_gemma":0.004465812,"domain_scores_codex":[0.993331,0.004559366,0.0001612434,0.001080673,0.0005625837,0.0003050697],"domain_scores_gemma":[0.9645464,0.0273333,0.002291203,0.003146349,0.001595453,0.001087262],"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":[0.0001952327,0.0002031495,0.02348232,0.0004448374,0.0003756378,0.0002809788,0.005501456,0.1821534,0.001118866,0.6847956,0.01012921,0.09131921],"study_design_scores_gemma":[0.00003128769,0.00003433238,0.00188807,0.00006679662,0.00005589888,0.00008089872,0.0004407407,0.5768101,0.0003372147,0.4097053,0.01051745,0.00003181695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05091952,0.001228962,0.9313199,0.003340277,0.0001779605,0.0002424152,0.0005492897,0.0007150649,0.01150654],"genre_scores_gemma":[0.817166,0.0009445724,0.1729038,0.000463077,0.0003920102,0.0006599734,0.0008765151,0.0002127497,0.006381409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01016769,"threshold_uncertainty_score":0.05377251,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225371371","doi":"10.32473/flairs.v35i.130731","title":"Pedestrian Traffic Prediction using Deep Learning","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Traffic Prediction and Management Techniques","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":"Acadia University","funders":"","keywords":"Computer science; Pedestrian; Artificial intelligence; Artificial neural network; Event (particle physics); Traffic flow (computer networking); Deep learning; Dual (grammatical number); Pedestrian detection; Machine learning; Engineering; Transport engineering","authors":[{"name":"Riddhi Joshi","is_ca":true},{"name":"Daniel Silver","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1045126509968553,"gpt":0.3240030754447231,"spread":0.2194904244478678,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000285242,0.001017359,0.0004369612,0.001830333,0.0002907964,0.0005894138,0.0005819729,0.0005757882,0.002137664],"category_scores_gemma":[0.0009281152,0.0004105318,0.0005620444,0.001088644,0.0001704162,0.000905535,0.0004940392,0.0006920911,0.0007963224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012028,"about_ca_system_score_gemma":0.0006772443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02149879,"about_ca_topic_score_gemma":0.02359715,"domain_scores_codex":[0.9998267,0.00002298879,0.000006442496,0.00005180832,0.0000395503,0.00005250788],"domain_scores_gemma":[0.9997109,0.0000627982,0.00004403942,0.00002418571,0.000129067,0.00002902141],"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":[0.0003033073,0.0004710454,0.02586503,0.00007638193,0.0001107261,0.0002003643,0.00005575425,0.6513325,0.004888281,0.00222176,0.01111864,0.3033562],"study_design_scores_gemma":[0.000001765491,0.0000102445,0.001126235,0.000004361056,0.00000478404,0.000009749701,0.000006577297,0.9973694,0.0005248301,0.0006422793,0.0002970133,0.000002744444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5032452,0.0009781377,0.475297,0.0006959889,0.0003741403,0.00009656663,0.002534434,0.005964403,0.01081412],"genre_scores_gemma":[0.9587508,0.0003072913,0.0333237,0.00009247664,0.0000721888,0.00004017842,0.002654279,0.00004669379,0.004712413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02149879,"threshold_uncertainty_score":0.04274732,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225425583","doi":"10.32473/flairs.v35i.130850","title":"Learning Automata with Artificial Reflecting Barriers in Games with Limited Information","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"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":"Nash equilibrium; Computer science; Game theory; Reinforcement learning; Fictitious play; Complete information; Perfect information; Learning automata; Mathematical economics; Point (geometry); Saddle point; Artificial intelligence; Automaton; Mathematics","authors":[{"name":"Ismail Hassan","is_ca":false},{"name":"B. John Oommen","is_ca":true},{"name":"Anis Yazidi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09331720338213315,"gpt":0.3458034193125344,"spread":0.2524862159304012,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001066337,0.0006685991,0.001070802,0.0006229152,0.0008101167,0.002109068,0.001315688,0.001721823,0.002475605],"category_scores_gemma":[0.006023262,0.0004806756,0.001028646,0.0003936707,0.002755028,0.002938272,0.002846529,0.001894376,0.0003915682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138735,"about_ca_system_score_gemma":0.001045646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002170288,"about_ca_topic_score_gemma":0.001622135,"domain_scores_codex":[0.9988172,0.000461284,0.00009432201,0.0002733867,0.0002271053,0.0001267753],"domain_scores_gemma":[0.9963858,0.002443114,0.0004751935,0.0002230214,0.000225944,0.000246962],"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":[0.00009874105,0.00005709088,0.0007975719,0.0001175499,0.00004678578,0.0003173071,0.0003670038,0.5541387,0.003335232,0.4303939,0.0005445653,0.009785537],"study_design_scores_gemma":[0.00002470934,0.00004416703,0.00007292838,0.0000135008,0.00001252439,0.00003836384,0.00002576432,0.9133174,0.0005245595,0.08488359,0.00102649,0.00001601329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1138365,0.0006387354,0.8689218,0.001058545,0.0001294962,0.0001198777,0.0001301237,0.0004844369,0.01468056],"genre_scores_gemma":[0.9169835,0.0004306917,0.07532655,0.0002530928,0.00006560826,0.0003340903,0.00009657834,0.00005764624,0.006452267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002475605,"threshold_uncertainty_score":0.008281767,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410432471","doi":"10.32473/flairs.38.1.138855","title":"AI Governance in Academia: Guidelines for Generative AI","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Université du Québec à Trois-Rivières","keywords":"Generative grammar; Corporate governance; Engineering ethics; Artificial intelligence; Computer science; Psychology; Engineering; Management; Economics","authors":[{"name":"Clayton Peterson","is_ca":true},{"name":"M. Deschênes","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3286494932545765,"gpt":0.4636849476764018,"spread":0.1350354544218253,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1645293,0.001765917,0.00236849,0.008744751,0.01159263,0.03024126,0.009542254,0.03180955,0.004084992],"category_scores_gemma":[0.1418313,0.002268543,0.002317412,0.009107705,0.05637404,0.02188266,0.01580829,0.02981338,0.006237469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0160447,"about_ca_system_score_gemma":0.04095499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01593037,"about_ca_topic_score_gemma":0.01712927,"domain_scores_codex":[0.8605245,0.08779918,0.01942173,0.005879116,0.02174774,0.004627718],"domain_scores_gemma":[0.7506472,0.1508747,0.01018781,0.02726791,0.05094114,0.01008119],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006911439,0.0000684072,0.0002501268,0.0003454776,0.000008395494,0.0001159017,0.005805744,0.0007343086,0.0001080101,0.9514508,0.02276075,0.01834517],"study_design_scores_gemma":[0.00003241245,0.00002142827,0.0002474936,0.002728749,0.000009478606,0.000153755,0.002967053,0.001639338,0.0002628973,0.7020407,0.2898396,0.0000571341],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001532084,0.01776336,0.504358,0.3308176,0.002894613,0.002494494,0.0002202678,0.00110764,0.138812],"genre_scores_gemma":[0.09940252,0.01706071,0.7933679,0.05405911,0.00221635,0.009216468,0.0005411098,0.001018443,0.02311747],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8354707,"threshold_uncertainty_score":0.8701247,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410397895","doi":"10.32473/flairs.38.1.138971","title":"RQPool: A Novel Multi-Branch Graph-Level Anomaly Detection","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Network Security and Intrusion Detection","field":"Computer Science","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 Windsor","funders":"","keywords":"Anomaly detection; Computer science; Graph; Anomaly (physics); Artificial intelligence; Theoretical computer science; Physics","authors":[{"name":"Aaron Alex Philip","is_ca":true},{"name":"Ziad Kobti","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1594303350550822,"gpt":0.3608686463202636,"spread":0.2014383112651813,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001627579,0.002243286,0.002062865,0.005225442,0.0009427754,0.001748411,0.004442827,0.00241866,0.002272717],"category_scores_gemma":[0.004475549,0.0005319557,0.001525949,0.00346864,0.001048593,0.004053897,0.002811229,0.002153605,0.001715463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001205992,"about_ca_system_score_gemma":0.001645166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007331168,"about_ca_topic_score_gemma":0.01068287,"domain_scores_codex":[0.9978276,0.0002888306,0.0001176017,0.0007430387,0.0008002372,0.0002227041],"domain_scores_gemma":[0.9974496,0.0008185615,0.0003546542,0.0003706791,0.0008210286,0.0001854119],"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":[0.0006603246,0.0007699915,0.02765159,0.0005506207,0.000427751,0.0005769641,0.0002430357,0.1083497,0.02517058,0.007791724,0.0375495,0.7902582],"study_design_scores_gemma":[0.00003294906,0.0001598125,0.002215642,0.00001964452,0.00004886898,0.000251896,0.00006391869,0.9792389,0.00540271,0.00771391,0.004822426,0.00002926408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05621061,0.00131358,0.9218967,0.000856459,0.0002365811,0.0004196785,0.00189201,0.01451277,0.002661603],"genre_scores_gemma":[0.5057482,0.0008570803,0.471395,0.001118647,0.0003314163,0.0004903351,0.009723376,0.0008095743,0.009526612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007331168,"threshold_uncertainty_score":0.01457697,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400281151","doi":"10.32473/flairs.37.1.135275","title":"Ethics of AI Explained","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Université du Québec à Trois-Rivières","keywords":"Information ethics; Applied ethics; Meta-ethics; Engineering ethics; Ethics of technology; Normative ethics; Psychology; Sociology; Epistemology; Philosophy; Engineering","authors":[{"name":"Clayton Peterson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3141774611558331,"gpt":0.5028181561763003,"spread":0.1886406950204673,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002608428,0.0006954048,0.0002941321,0.0006705985,0.002899801,0.003795314,0.0009703235,0.003457959,0.08883912],"category_scores_gemma":[0.01001766,0.0003407617,0.0004176521,0.0006107256,0.002274326,0.00412039,0.003109897,0.005025626,0.02878623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002651942,"about_ca_system_score_gemma":0.004027025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001765254,"about_ca_topic_score_gemma":0.00244652,"domain_scores_codex":[0.9975327,0.001299059,0.000111206,0.0001710521,0.0005205719,0.0003653429],"domain_scores_gemma":[0.9970673,0.001162697,0.0001430262,0.0001960001,0.001030131,0.000400883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006969609,0.00005573693,0.0003088233,0.0003827966,0.000004087299,0.0002494041,0.01649242,0.0003698452,0.001032368,0.6458511,0.2852515,0.04993225],"study_design_scores_gemma":[0.00000349833,0.000009029372,0.00008031883,0.0001851166,9.923681e-7,0.0001600615,0.001239491,0.0001059401,0.000155921,0.01742819,0.9806245,0.000006998918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.008109119,0.009225126,0.07225776,0.0958404,0.009396908,0.0009119249,0.001840218,0.001606732,0.8008118],"genre_scores_gemma":[0.1464132,0.01359098,0.06221642,0.029191,0.00185022,0.002495442,0.002388527,0.001913579,0.7399406],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08883912,"threshold_uncertainty_score":0.2971964,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410398730","doi":"10.32473/flairs.38.1.139110","title":"Preface","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Historical Geography and Geographical Thought","field":"Social Sciences","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 du Québec à Trois-Rivières","funders":"","keywords":"Philosophy","authors":[{"name":"Ismaïl Biskri","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1302723172466035,"gpt":0.418289214212581,"spread":0.2880168969659775,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00161278,0.001099638,0.0007947895,0.002189156,0.002822661,0.006292719,0.001454251,0.0019783,0.6957894],"category_scores_gemma":[0.006007894,0.0004326952,0.0007429488,0.001620105,0.0005100209,0.003389932,0.002709402,0.003448588,0.5853462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001951474,"about_ca_system_score_gemma":0.002806002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003827991,"about_ca_topic_score_gemma":0.005315696,"domain_scores_codex":[0.9991567,0.00007967246,0.00005604226,0.000173698,0.0004277821,0.000105945],"domain_scores_gemma":[0.9931958,0.0003731475,0.0001909173,0.0004464739,0.004211646,0.001581967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001764579,0.00001281958,0.00004565504,0.00004930127,9.934398e-7,0.00001656923,0.00001709827,0.00002126764,0.00008723408,0.001149517,0.9778228,0.02075905],"study_design_scores_gemma":[0.000005636037,0.00001853186,0.0002205757,0.00005316716,0.000001023099,0.00002248257,0.00003814106,0.00001657667,0.00004601344,0.000701899,0.9988726,0.000003494779],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"editorial","genre_scores_codex":[0.0007949592,0.003845057,0.004146917,0.02815099,0.2770435,0.0008970022,0.01173638,0.001909582,0.6714756],"genre_scores_gemma":[0.00200489,0.001448401,0.0009418358,0.002886726,0.02304668,0.0002223828,0.005144974,0.0004911399,0.963813],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.6957894,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410432646","doi":"10.32473/flairs.38.1.138913","title":"Creating Domain-Specific Datasets for Intelligent Environmental Feature Comparison","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","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 Waterloo; University of Windsor","funders":"","keywords":"Domain (mathematical analysis); Feature (linguistics); Computer science; Artificial intelligence; Data mining; Pattern recognition (psychology); Information retrieval; Mathematics","authors":[{"name":"Nathan Cherry","is_ca":true},{"name":"Ziad Kobti","is_ca":true},{"name":"Chris Houser","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1059942501670421,"gpt":0.4030994945546468,"spread":0.2971052443876047,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002348991,0.001137452,0.0007173264,0.006773276,0.001003006,0.001996932,0.002485445,0.001792912,0.002493997],"category_scores_gemma":[0.009873876,0.0004143671,0.001561844,0.00511487,0.0008315207,0.003744878,0.003232079,0.002006299,0.002068526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001356506,"about_ca_system_score_gemma":0.001054856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008477127,"about_ca_topic_score_gemma":0.02319186,"domain_scores_codex":[0.9972801,0.000635454,0.0002557122,0.0009890916,0.0006356302,0.0002039198],"domain_scores_gemma":[0.9948171,0.001246288,0.0004440193,0.002012797,0.001193159,0.0002866468],"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":[0.0004936531,0.001805678,0.09170217,0.003161316,0.000696157,0.001199636,0.001692284,0.1089779,0.02708492,0.030856,0.2604746,0.4718557],"study_design_scores_gemma":[0.0001772154,0.0003036142,0.09982429,0.0008583984,0.0002122304,0.001127943,0.007541972,0.3140211,0.0387319,0.05268278,0.4841581,0.0003605357],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.1806583,0.001194155,0.4025927,0.002183981,0.0006149773,0.002255847,0.3606459,0.02470475,0.02514944],"genre_scores_gemma":[0.1619617,0.0003423419,0.3820376,0.0004055675,0.00005786034,0.001302148,0.4514647,0.0009186005,0.00150951],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.008477127,"threshold_uncertainty_score":0.01685554,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400280941","doi":"10.32473/flairs.37.1.135597","title":"Exploration of Word Embeddings with Graph-Based Context Adaptation for Enhanced Word Vectors","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Topic Modeling","field":"Computer Science","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 Windsor","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Word embedding; Word (group theory); Natural language understanding; Embedding; Context (archaeology); Natural language; Graph; Representation (politics); Semantic similarity; Linguistics; Theoretical computer science","authors":[{"name":"Tanvi Sandhu","is_ca":true},{"name":"Ziad Kobti","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.191747697463749,"gpt":0.3730239915487573,"spread":0.1812762940850084,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003654048,0.00106509,0.0006422336,0.001435022,0.0002819427,0.0008429093,0.0007122206,0.0005743998,0.002165892],"category_scores_gemma":[0.002400606,0.0003261051,0.0007790846,0.001720004,0.0003926142,0.00211831,0.001102562,0.0007924492,0.0009015507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002802698,"about_ca_system_score_gemma":0.0004590917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002340098,"about_ca_topic_score_gemma":0.004691986,"domain_scores_codex":[0.9997877,0.00006479519,0.0000154365,0.00007968007,0.00003242132,0.00001989042],"domain_scores_gemma":[0.9993731,0.0003366145,0.00006017143,0.00009679256,0.0001070291,0.0000263507],"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":[0.0002992269,0.0003005601,0.002976781,0.0004917214,0.000135477,0.0002098926,0.0005667627,0.1428048,0.03888762,0.01789067,0.009501737,0.7859347],"study_design_scores_gemma":[0.00002670527,0.0001392945,0.0004947939,0.00002423204,0.00004335069,0.00009312941,0.0001639071,0.9685942,0.005319487,0.02080488,0.004274895,0.00002103877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09261729,0.001095711,0.899986,0.0002977161,0.0001241612,0.0001200848,0.0004881723,0.003056133,0.002214719],"genre_scores_gemma":[0.5304945,0.0006929067,0.4625625,0.0001828326,0.00008050923,0.0002205156,0.002120815,0.0004555101,0.003189879],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002340098,"threshold_uncertainty_score":0.0072456,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225424639","doi":"10.32473/flairs.v35i.130561","title":"Tractable Inference for Hybrid Bayesian Networks with NAT-Modeled Dynamic Discretization","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","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 Guelph","funders":"","keywords":"Inference; Nat; Bayesian network; Discretization; Dynamic Bayesian network; Variable elimination; Computer science; Approximate inference; Focus (optics); Tree (set theory); Treewidth; Fiducial inference; Bayesian inference; Exponential family; Algorithm; Frequentist inference; Mathematics; Artificial intelligence; Bayesian probability; Theoretical computer science; Machine learning; Combinatorics; Graph; Physics","authors":[{"name":"Yang Xiang","is_ca":true},{"name":"Han–Wen Zheng","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06755913222578512,"gpt":0.3435113616906051,"spread":0.27595222946482,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046546,0.0006257092,0.001119404,0.0009620324,0.0005919058,0.001892337,0.001830729,0.0009523786,0.002764672],"category_scores_gemma":[0.01849292,0.0007376668,0.001256943,0.001394583,0.001261197,0.003323957,0.002174011,0.002431073,0.0003740086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002209978,"about_ca_system_score_gemma":0.001648452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007441266,"about_ca_topic_score_gemma":0.01206863,"domain_scores_codex":[0.9970751,0.001585251,0.0001407947,0.0005606306,0.0005001237,0.0001379823],"domain_scores_gemma":[0.9854099,0.01174424,0.0006574183,0.001229019,0.0006972358,0.000262295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001085193,0.00003531982,0.001353302,0.0001095676,0.00009192929,0.0001180555,0.0001049273,0.7133521,0.0006052249,0.2434106,0.001613074,0.03909732],"study_design_scores_gemma":[0.0000062708,0.00000435024,0.0000721553,0.000007624277,0.000007379097,0.00001942767,0.00001045033,0.8996684,0.00012254,0.0995046,0.0005720496,0.000004709048],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005410926,0.0001363748,0.9930577,0.0001790701,0.00001680621,0.0000155741,0.000181777,0.00009754497,0.0009041323],"genre_scores_gemma":[0.428383,0.0005121984,0.5660798,0.000286656,0.0001072564,0.000221315,0.001091648,0.00011475,0.003203374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007441266,"threshold_uncertainty_score":0.02461618,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}