{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":9,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":9,"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":"93c8171891f5","filters":{"venue":"2019 Conference on Cognitive Computational Neuroscience"}},"results":[{"id":"W2970617179","doi":"10.32470/ccn.2019.1079-0","title":"Gestalt-based Contour Weights Improve Scene Categorization by CNNs","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Categorization; Gestalt psychology; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Psychology; Perception","authors":[{"name":"Morteza Rezanejad","is_ca":true},{"name":"Gabriel Downs","is_ca":true},{"name":"John Wilder","is_ca":true},{"name":"Dirk B. Walther","is_ca":true},{"name":"Allan Jepson","is_ca":true},{"name":"Sven Dickinson","is_ca":true},{"name":"Kaleem Siddiqi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01981683765844714,"gpt":0.2861278843841405,"spread":0.2663110467256933,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000228158,0.0003119892,0.0002582535,0.000216071,0.000239359,0.0004007475,0.0009487426,0.00008139434,0.00004196636],"category_scores_gemma":[0.000275482,0.0002923599,0.00007663703,0.0007218628,0.0002250017,0.001306917,0.0001772304,0.0002821108,0.0003241287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006275878,"about_ca_system_score_gemma":0.0004517958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001255396,"about_ca_topic_score_gemma":6.208245e-7,"domain_scores_codex":[0.9971375,0.0001373517,0.0003331446,0.001096596,0.0008414899,0.0004538682],"domain_scores_gemma":[0.9977844,0.0004952243,0.0002732973,0.0003478561,0.0009137585,0.0001854013],"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":[0.0002778738,0.001352347,0.003451881,0.0001117568,0.00002031118,0.00007980259,0.0003026622,0.003372809,0.2669561,0.5121137,0.003848325,0.2081125],"study_design_scores_gemma":[0.001523403,0.001594016,0.008348023,0.000185437,0.000008828112,0.0000116015,0.00002057178,0.8146034,0.1350043,0.03657532,0.001306236,0.0008187837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01268785,0.00003473239,0.9822513,0.0008316335,0.0005979679,0.0006768566,0.0001024448,0.0003327651,0.002484433],"genre_scores_gemma":[0.9840372,0.00003237611,0.01057133,0.004249567,0.0000328372,0.00003015101,0.00007603253,0.00001871425,0.0009517842],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.97168,"threshold_uncertainty_score":0.9999529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970420303","doi":"10.32470/ccn.2019.1424-0","title":"Visualizing Representational Dynamics with Multidimensional Scaling Alignment","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":4,"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; Dynamics (music); Multidimensional scaling; Scaling; Visualization; Theoretical computer science; Human–computer interaction; Artificial intelligence; Machine learning; Mathematics; Physics; Geometry","authors":[{"name":"Baihan Lin","is_ca":false},{"name":"Marieke Mur","is_ca":true},{"name":"Tim C. Kietzmann","is_ca":false},{"name":"Nikolaus Kriegeskorte","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05745793673580415,"gpt":0.3213291460818171,"spread":0.263871209346013,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002746693,0.0003438254,0.0002746613,0.0002544126,0.0004855701,0.0001637365,0.0003033624,0.00005222469,0.0001675292],"category_scores_gemma":[0.002721934,0.0003048628,0.00007729995,0.0006346551,0.0005722966,0.000551088,0.0002188067,0.0003086569,0.0007277944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001365987,"about_ca_system_score_gemma":0.0003335451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001324316,"about_ca_topic_score_gemma":0.000004874455,"domain_scores_codex":[0.9957216,0.0002551214,0.000322541,0.001501827,0.001730689,0.0004681975],"domain_scores_gemma":[0.9919131,0.006959309,0.0002394707,0.0002092053,0.000527459,0.0001514052],"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":[0.001277784,0.001073535,0.02446175,0.00005933424,0.0000309343,0.0001454137,0.0005022556,0.1740691,0.09492677,0.6982293,0.0008046817,0.004419231],"study_design_scores_gemma":[0.00275929,0.001254567,0.09562398,0.0004138965,0.00002241121,0.0001862883,0.0005724633,0.8698795,0.01960871,0.008418916,0.0003018206,0.0009581027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9297379,0.000008467468,0.05259984,0.003833235,0.00102916,0.001004357,0.0002735392,0.0001866565,0.01132688],"genre_scores_gemma":[0.9876055,0.000008806676,0.0009604032,0.01019755,0.00005267711,0.00003710258,0.00004505136,0.00002977393,0.001063158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6958105,"threshold_uncertainty_score":0.9999403,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970563709","doi":"10.32470/ccn.2019.1372-0","title":"Models of allocentric coding for reaching in naturalistic visual scenes","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Coding (social sciences); Artificial intelligence; Predictive coding; Computer vision; Cognitive psychology; Cognitive science; Psychology; Mathematics","authors":[{"name":"Parisa Abedi Khoozani","is_ca":true},{"name":"Paul Schrater","is_ca":false},{"name":"Dominik Endres","is_ca":false},{"name":"Katja Fiehler","is_ca":false},{"name":"Gunnar Blohm","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0596247366605132,"gpt":0.3466593736083317,"spread":0.2870346369478184,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002799613,0.0001647589,0.0002243913,0.0003407034,0.0001008175,0.0001212701,0.0005619263,0.00003116092,0.000004839901],"category_scores_gemma":[0.0004018631,0.000158375,0.00005488781,0.0005958434,0.0001091742,0.001018293,0.0001704737,0.0001751975,0.00001560671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003513516,"about_ca_system_score_gemma":0.0001942479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006405656,"about_ca_topic_score_gemma":5.513859e-7,"domain_scores_codex":[0.9981756,0.00008047376,0.0003146493,0.0006394207,0.0004789912,0.0003108828],"domain_scores_gemma":[0.998208,0.0009162307,0.0001961716,0.0001309972,0.0004755001,0.00007304697],"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":[0.0001155425,0.0003187945,0.002258948,0.00008590557,0.000003916971,0.00001070184,0.0005462543,0.1371087,0.01555135,0.7728518,0.00003275481,0.07111531],"study_design_scores_gemma":[0.0006929381,0.0001867061,0.009163587,0.0002665167,0.000001665088,0.000004434908,0.00004048465,0.9564841,0.0007546176,0.03222229,0.000007591881,0.0001750657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07145305,0.00002321835,0.9265592,0.0002740152,0.0004395086,0.000435426,0.0000189739,0.00004190851,0.000754676],"genre_scores_gemma":[0.9824409,0.00001862224,0.01638824,0.001031977,0.00001114721,0.00001039874,0.000009682159,0.000007999456,0.00008102906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9109879,"threshold_uncertainty_score":0.6458346,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970637111","doi":"10.32470/ccn.2019.1187-0","title":"An overview of functional alignment in artificial and biological neural networks: Current recommendations and open questions","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Current (fluid); Computer science; Artificial neural network; Artificial intelligence; Machine learning; Engineering; Electrical engineering","authors":[{"name":"Elizabeth DuPré","is_ca":true},{"name":"Jean‐Baptiste Poline","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1223743743487374,"gpt":0.3921920490278917,"spread":0.2698176746791542,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002202002,0.00009993029,0.0001134958,0.00005612016,0.00007147841,0.0000720701,0.0001431935,0.00003792343,0.00002599914],"category_scores_gemma":[0.000134127,0.00009099545,0.00001405259,0.000103071,0.0001764903,0.00002909966,0.0001841155,0.0001141317,0.000002747268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000537205,"about_ca_system_score_gemma":0.00006524838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007588306,"about_ca_topic_score_gemma":0.000007117726,"domain_scores_codex":[0.9991044,0.0001423258,0.0002099194,0.0003075363,0.0001200104,0.0001157969],"domain_scores_gemma":[0.999537,0.00009202121,0.0001104624,0.0000791028,0.0001230733,0.0000583316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007764457,0.001639526,0.2731096,0.0001122357,0.00002255338,0.000002756115,0.0003601648,0.2515398,0.03987633,0.2065918,0.0004175105,0.2255512],"study_design_scores_gemma":[0.0004001965,0.0007777894,0.3791279,0.00009202089,0.000003432603,0.000008951792,0.00005625743,0.6175635,0.00009637388,0.001578543,0.0001528493,0.0001421358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712344,0.0001757909,0.02723434,0.0003944252,0.0002539055,0.0004141525,0.00008224462,0.000005932783,0.0002047732],"genre_scores_gemma":[0.9983423,0.0004111732,0.0004568624,0.0005149598,0.0000201271,0.00001319849,0.0002248938,0.000003747648,0.00001271241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3660237,"threshold_uncertainty_score":0.3710687,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970639473","doi":"10.32470/ccn.2019.1279-0","title":"High-resolution population receptive field mapping of human high-level visual areas","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Receptive field; Computer science; Field (mathematics); Population; Computer vision; Artificial intelligence; Resolution (logic); Mathematics; Medicine","authors":[{"name":"Charlotte Leferink","is_ca":true},{"name":"Claudia Damiano","is_ca":true},{"name":"Dirk B. Walther","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1214141301484443,"gpt":0.3579357721503654,"spread":0.2365216420019212,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002470843,0.00025236,0.0002871465,0.0003355631,0.00035235,0.0001526471,0.0003226397,0.000102412,0.0005342657],"category_scores_gemma":[0.0007593445,0.0002528381,0.00007129942,0.000637217,0.0002055056,0.0006096749,0.0001101191,0.000285542,0.0003511447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004734828,"about_ca_system_score_gemma":0.0001252165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008926063,"about_ca_topic_score_gemma":0.000004128869,"domain_scores_codex":[0.9972156,0.0002787503,0.0004269903,0.0008563414,0.0008953447,0.0003269827],"domain_scores_gemma":[0.9983567,0.0005705018,0.0003923591,0.0001370699,0.0004300541,0.0001133446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000227167,0.0003957201,0.001482093,0.00005619371,0.000002972027,0.000005575473,0.0003823279,0.004239881,0.8651065,0.1119005,0.00008945722,0.01611163],"study_design_scores_gemma":[0.00324027,0.004842393,0.4969428,0.001572462,0.00002608842,0.00003107265,0.0005691424,0.1720591,0.2452336,0.07423797,0.00002273478,0.00122241],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9291296,0.000002157435,0.06810805,0.000268612,0.0008108051,0.0004307757,0.00009892962,0.00008758993,0.001063467],"genre_scores_gemma":[0.9962997,0.00001058834,0.0005159694,0.002450495,0.00005599745,0.00001398211,0.0000811318,0.00001850955,0.0005535796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6198729,"threshold_uncertainty_score":0.9999924,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2971242498","doi":"10.32470/ccn.2019.1124-0","title":"Learning to evoke complex motor outputs with spatiotemporal neurostimulation using a hierarchical and adaptive optimization algorithm.","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Neurostimulation; Computer science; Optimization algorithm; Algorithm; Artificial intelligence; Neuroscience; Mathematical optimization; Psychology; Mathematics; Stimulation","authors":[{"name":"Samuel Laferrière","is_ca":true},{"name":"Guillaume Lajoie","is_ca":true},{"name":"Numa Dancause","is_ca":true},{"name":"Marco Bonizzato","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07289709315034598,"gpt":0.3103070735806086,"spread":0.2374099804302626,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001621255,0.0003228587,0.0002765956,0.0003307908,0.0003880679,0.0003966966,0.0002791232,0.00005837105,0.00004740846],"category_scores_gemma":[0.0004098871,0.0002918511,0.00003876352,0.0005692672,0.0003502557,0.0006129885,0.0001934803,0.0004047126,0.00005879538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004183376,"about_ca_system_score_gemma":0.0001982684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001661232,"about_ca_topic_score_gemma":0.00000103184,"domain_scores_codex":[0.9969484,0.000355807,0.0003011144,0.001185447,0.0008110495,0.0003981802],"domain_scores_gemma":[0.9981262,0.0008956917,0.0002153088,0.0001273288,0.0004043188,0.0002311525],"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":[0.000390452,0.0001286308,0.001226214,0.00001254117,0.000003007591,0.00002400104,0.0004846675,0.935533,0.04893538,0.00267968,0.00001019907,0.01057226],"study_design_scores_gemma":[0.0008040451,0.002472148,0.02224253,0.0001689126,0.00000761413,0.00005750535,0.00006817036,0.9712857,0.002241308,0.0002759653,0.00002497254,0.0003511242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4937953,0.000001645819,0.5045354,0.0003427993,0.0001878185,0.0006395367,0.00006711449,0.00007622867,0.0003542115],"genre_scores_gemma":[0.9760755,0.000003557594,0.02068588,0.002899946,0.00004735607,0.00001229007,0.00002183957,0.00002868956,0.0002249794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4838495,"threshold_uncertainty_score":0.9999534,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2971069477","doi":"10.32470/ccn.2019.1359-0","title":"FEF Biases the Persistence of Expectation","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Queen's University","funders":"","keywords":"Persistence (discontinuity); Computer science; Engineering","authors":[{"name":"Brandon Caie","is_ca":true},{"name":"Paul Schrater","is_ca":false},{"name":"Aarlenne Z. Khan","is_ca":true},{"name":"Gunnar Blohm","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3589947543367379,"gpt":0.4263165555109981,"spread":0.06732180117426018,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009959036,0.0001667889,0.0002549405,0.0002663352,0.0002261226,0.0003216741,0.001045244,0.00004260493,0.0004899115],"category_scores_gemma":[0.004448229,0.0001086666,0.0001302296,0.0008027992,0.0005447163,0.0004532858,0.0001592339,0.0001662602,0.00152684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002169047,"about_ca_system_score_gemma":0.000275621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009446856,"about_ca_topic_score_gemma":0.000003372211,"domain_scores_codex":[0.996748,0.0002303797,0.0005624388,0.0007255232,0.001513867,0.0002197595],"domain_scores_gemma":[0.9919176,0.005845508,0.0004967566,0.0003509215,0.001308539,0.00008068734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006165155,0.001028605,0.06268315,0.00001418401,0.00001610245,0.00002646098,0.00358978,0.1055934,0.01572794,0.04654238,0.003732206,0.7604293],"study_design_scores_gemma":[0.001109595,0.001416242,0.508273,0.0003630857,0.00002538267,0.00004522342,0.005958928,0.3528129,0.002278247,0.126252,0.000853544,0.0006119222],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854675,0.00001006064,0.007162692,0.000613386,0.0008363168,0.0003048405,0.00009488465,0.00002107629,0.005489251],"genre_scores_gemma":[0.9980292,0.000007694433,0.0002245512,0.001004066,0.00002130251,0.000007928181,0.000007777932,0.000007254721,0.000690227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7598174,"threshold_uncertainty_score":0.9992506,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970781318","doi":"10.32470/ccn.2019.1384-0","title":"Functional Decoding using Convolutional Networks on Brain Graphs","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Decoding methods; Computer science; Convolutional code; Convolutional neural network; Sequential decoding; Artificial intelligence; Algorithm","authors":[{"name":"Yu Zhang","is_ca":true},{"name":"Pierre Bellec","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1067551455577668,"gpt":0.3105676049136964,"spread":0.2038124593559296,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004149595,0.0004333941,0.0003315494,0.0004490622,0.0008638853,0.000227766,0.0003988316,0.00009949365,0.0004171297],"category_scores_gemma":[0.008065801,0.0004338197,0.0001615692,0.0009740001,0.0007303684,0.000570897,0.0002067222,0.0005649725,0.0008934769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001422392,"about_ca_system_score_gemma":0.0003929893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007358691,"about_ca_topic_score_gemma":0.000001915674,"domain_scores_codex":[0.9954745,0.000382046,0.0003855386,0.001655361,0.001464322,0.0006382357],"domain_scores_gemma":[0.9817174,0.0170936,0.0002693879,0.0002272292,0.0005071536,0.0001851943],"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":[0.0006209926,0.0004525716,0.004657256,0.00001694829,0.000014001,0.0000344307,0.00005860008,0.4756393,0.05194836,0.4589323,0.00587786,0.001747423],"study_design_scores_gemma":[0.001619826,0.0008774934,0.07587209,0.0002318446,0.00001308247,0.0001031374,0.00006447866,0.8967999,0.002897167,0.02039386,0.0004107899,0.0007163491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8500144,0.00002401493,0.1234952,0.007681821,0.005151318,0.001220408,0.0002855525,0.0003046529,0.01182261],"genre_scores_gemma":[0.9581611,0.00001135479,0.000170601,0.04050655,0.0001375782,0.00003013627,0.00002768835,0.00003235573,0.0009226347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4385384,"threshold_uncertainty_score":0.9998844,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970096889","doi":"10.32470/ccn.2019.1172-0","title":"Do sleep and anesthesia share common multifractal EEG dynamics? Insights from adversarial domain adaptation","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Multifractal system; Electroencephalography; Sleep (system call); Adversarial system; Computer science; Adaptation (eye); Domain (mathematical analysis); Artificial intelligence; Psychology; Neuroscience; Mathematics; Fractal","authors":[{"name":"Louis Leconte","is_ca":false},{"name":"Tarek Lajnef","is_ca":true},{"name":"Thomas Thiery","is_ca":true},{"name":"George A. Mashour","is_ca":false},{"name":"Stefanie Blain‐Moraes","is_ca":true},{"name":"Perrine Ruby","is_ca":false},{"name":"Karim Jerbi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03216981166988397,"gpt":0.2628193644557378,"spread":0.2306495527858538,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001079385,0.0003299682,0.0002805197,0.000209493,0.000365527,0.0003942222,0.00033938,0.0001029452,0.0000882848],"category_scores_gemma":[0.0003684273,0.0003108035,0.00006746772,0.000402581,0.0003593918,0.0007808278,0.0001294017,0.0003604298,0.0003075607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006555235,"about_ca_system_score_gemma":0.0001097103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005509765,"about_ca_topic_score_gemma":0.00002230718,"domain_scores_codex":[0.9969791,0.0003008164,0.0003566478,0.001236397,0.0008030558,0.0003240414],"domain_scores_gemma":[0.9975519,0.001559676,0.0002917117,0.0001925854,0.000231046,0.0001731235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002676109,0.00126953,0.01514443,0.00008562428,0.0000222884,0.0004652741,0.002833823,0.03678544,0.5203936,0.3106034,0.0001662934,0.1095541],"study_design_scores_gemma":[0.001227866,0.0004777206,0.08379453,0.0001082781,0.00000883062,0.00004462834,0.0002596928,0.887017,0.0008826415,0.02570327,0.00009395507,0.0003815744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861299,0.000008568787,0.009887304,0.001015325,0.0007172438,0.0006766047,0.0003009294,0.0000935013,0.001170655],"genre_scores_gemma":[0.9957885,0.00002382885,0.0003174641,0.003435182,0.00005168099,0.00001878541,0.0002107007,0.00002528639,0.000128569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8502316,"threshold_uncertainty_score":0.9999344,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}