{"meta":{"query_hash":"6dafa500ee0f","filters":{"venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/6dafa500ee0f","api":"https://metacan.xera.ac/api/v1/cohort?venue=Proceedings+of+the+15th+International+Conference+on+Informatics+in+Control%2C+Automation+and+Robotics"},"results":[{"id":"W2885467593","doi":"10.5220/0006855202990306","title":"LightByte: Communicating Wirelessly with an Underwater Robot using Light","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Underwater; Computer science; Robot; Mobile robot; Artificial intelligence; Computer vision; Geology; Oceanography","score_opus":0.028555336252778857,"score_gpt":0.26626804835738327,"score_spread":0.2377127121046044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885467593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8951357,0.000046377645,0.03964855,0.0055552484,0.00040804874,0.0007968852,0.000015612437,0.0007514277,0.05764214],"genre_scores_gemma":[0.9413744,0.000081031365,0.058376063,0.00010643212,0.000019782627,0.0000110783,0.0000024902708,0.00001581105,0.000012910695],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988753,0.000010175952,0.00056848384,0.0000816948,0.0002964884,0.00016782197],"domain_scores_gemma":[0.99890006,0.00005615741,0.00026923855,0.00024595915,0.00048939855,0.000039161583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025587095,0.00016794629,0.00021267975,0.0001959801,0.00014373183,0.00016428772,0.00085679087,0.00011559975,0.000010358661],"category_scores_gemma":[0.000078147445,0.00011853831,0.000024564924,0.00019695872,0.00025523358,0.0006329428,0.00016147237,0.00030440395,0.000003684413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111159454,0.00013440227,0.004218073,0.00023175629,0.00014587562,1.6804798e-7,0.0049797823,0.070261516,0.0079834,0.90391797,0.000041064155,0.007974849],"study_design_scores_gemma":[0.0006193563,0.000108995206,0.001110537,0.00038457138,0.000011791622,0.000007168714,0.0014577078,0.98604816,0.006088431,0.003962518,0.00004512826,0.000155604],"about_ca_topic_score_codex":0.000005141248,"about_ca_topic_score_gemma":0.000018301638,"teacher_disagreement_score":0.9157867,"about_ca_system_score_codex":0.00009139782,"about_ca_system_score_gemma":0.000024528365,"threshold_uncertainty_score":0.48338518},"labels":[],"label_agreement":null},{"id":"W2886007972","doi":"10.5220/0006832301030110","title":"Autonomous Trail Following using a Pre-trained Deep Neural Network","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Artificial neural network; Artificial intelligence","score_opus":0.03358950275421544,"score_gpt":0.30793274119516384,"score_spread":0.2743432384409484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886007972","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3165581,0.00002091248,0.66787523,0.002497731,0.0021778317,0.000512018,0.0000043870537,0.00016804527,0.010185749],"genre_scores_gemma":[0.87566715,0.000005727523,0.12369032,0.000494257,0.000103106475,0.0000063564326,8.1744645e-7,0.0000064350847,0.000025817542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984515,0.000025447598,0.00069147453,0.00015077207,0.0004324058,0.00024841042],"domain_scores_gemma":[0.99873567,0.00012098414,0.0005390593,0.0001392029,0.00041415586,0.000050917813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009668722,0.00016859834,0.00025612387,0.00016213996,0.0001918594,0.00032047677,0.0008552408,0.00008815837,0.0000054920065],"category_scores_gemma":[0.00028042635,0.00012975752,0.000087386106,0.00030450246,0.00010545887,0.00090619706,0.00016716636,0.0001992142,0.0000018537386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000862726,0.00009520289,0.020205678,0.00011544552,0.00015604263,9.2904423e-7,0.009860005,0.11960887,0.0010124261,0.8133364,0.000056665365,0.03546607],"study_design_scores_gemma":[0.0008238089,0.00008223495,0.017838998,0.00015823377,0.000011313759,0.000012302332,0.00014100263,0.96838903,0.0001208944,0.012263591,0.000021579144,0.00013699518],"about_ca_topic_score_codex":0.000008140958,"about_ca_topic_score_gemma":0.000008723312,"teacher_disagreement_score":0.84878016,"about_ca_system_score_codex":0.000067337096,"about_ca_system_score_gemma":0.000065437824,"threshold_uncertainty_score":0.5291358},"labels":[],"label_agreement":null},{"id":"W2886566182","doi":"10.5220/0006909704560464","title":"Design of a Saw Cutting Machine for Wood and Aluminum","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Aluminium; Computer science; Materials science; Metallurgy","score_opus":0.02068782398011679,"score_gpt":0.24517133195908944,"score_spread":0.22448350797897265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886566182","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07308858,0.000047227655,0.9119098,0.0008379464,0.0005766143,0.0010591946,0.000042292766,0.00011336504,0.012324948],"genre_scores_gemma":[0.960815,0.00006800624,0.038991496,0.00005390073,0.000023345134,0.000013249594,0.000002406473,0.0000072873386,0.000025274885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929124,0.0000025740746,0.00041449352,0.000052255687,0.00015208598,0.00008735383],"domain_scores_gemma":[0.999325,0.00006175997,0.00023178612,0.000037440826,0.0003238366,0.00002017058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002566991,0.00009460174,0.0001459596,0.00012365509,0.000049740607,0.000052611605,0.00014830618,0.000054988217,0.0000064331048],"category_scores_gemma":[0.00012728405,0.000073331976,0.000017381168,0.000060133192,0.000066369685,0.00023143204,0.000030041294,0.000072235256,2.958669e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022938049,0.000074629585,0.002278216,0.0020452468,0.0001732129,4.4996128e-8,0.009429575,0.6576089,0.002152669,0.3102101,0.00020319934,0.01559481],"study_design_scores_gemma":[0.00076783,0.000073073745,0.00057708326,0.00021458158,0.0000131900115,0.000001794559,0.00016552181,0.99091744,0.003608707,0.0035657627,0.000022402402,0.00007260204],"about_ca_topic_score_codex":0.0000018059244,"about_ca_topic_score_gemma":9.70229e-7,"teacher_disagreement_score":0.8877264,"about_ca_system_score_codex":0.000019612662,"about_ca_system_score_gemma":0.000012854576,"threshold_uncertainty_score":0.29903913},"labels":[],"label_agreement":null},{"id":"W4231647499","doi":"10.5220/0006909704660474","title":"Design of a Saw Cutting Machine for Wood and Aluminum","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Aluminium; Computer science; Materials science; Composite material","score_opus":0.02068782398011679,"score_gpt":0.24517133195908944,"score_spread":0.22448350797897265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231647499","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07308858,0.000047227655,0.9119098,0.0008379464,0.0005766143,0.0010591946,0.000042292766,0.00011336504,0.012324948],"genre_scores_gemma":[0.960815,0.00006800624,0.038991496,0.00005390073,0.000023345134,0.000013249594,0.000002406473,0.0000072873386,0.000025274885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929124,0.0000025740746,0.00041449352,0.000052255687,0.00015208598,0.00008735383],"domain_scores_gemma":[0.999325,0.00006175997,0.00023178612,0.000037440826,0.0003238366,0.00002017058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002566991,0.00009460174,0.0001459596,0.00012365509,0.000049740607,0.000052611605,0.00014830618,0.000054988217,0.0000064331048],"category_scores_gemma":[0.00012728405,0.000073331976,0.000017381168,0.000060133192,0.000066369685,0.00023143204,0.000030041294,0.000072235256,2.958669e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022938049,0.000074629585,0.002278216,0.0020452468,0.0001732129,4.4996128e-8,0.009429575,0.6576089,0.002152669,0.3102101,0.00020319934,0.01559481],"study_design_scores_gemma":[0.00076783,0.000073073745,0.00057708326,0.00021458158,0.0000131900115,0.000001794559,0.00016552181,0.99091744,0.003608707,0.0035657627,0.000022402402,0.00007260204],"about_ca_topic_score_codex":0.0000018059244,"about_ca_topic_score_gemma":9.70229e-7,"teacher_disagreement_score":0.8877264,"about_ca_system_score_codex":0.000019612662,"about_ca_system_score_gemma":0.000012854576,"threshold_uncertainty_score":0.29903913},"labels":[],"label_agreement":null},{"id":"W4239125530","doi":"10.5220/0006832301130120","title":"Autonomous Trail Following using a Pre-trained Deep Neural Network","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Artificial neural network; Artificial intelligence; Deep learning; Deep neural networks; Machine learning","score_opus":0.016681747588086316,"score_gpt":0.2537759736759077,"score_spread":0.23709422608782138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239125530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55492246,0.000034434255,0.37218872,0.0012576709,0.0033438322,0.001269435,0.000017322833,0.0022408175,0.06472528],"genre_scores_gemma":[0.9864878,0.000018253284,0.013129398,0.00022364043,0.00009011118,0.000012587304,0.0000022191712,0.000011320923,0.000024646777],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989556,0.0000050913413,0.0005296804,0.00007514914,0.00026247604,0.00017197791],"domain_scores_gemma":[0.99952936,0.000025190444,0.0001872603,0.000066398425,0.00015521848,0.000036578214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027626613,0.00014309662,0.00017475503,0.00016065291,0.00009408026,0.000118419506,0.0002971127,0.00007834388,0.000008912129],"category_scores_gemma":[0.000057137582,0.000118437,0.00005871792,0.0001542268,0.000073316856,0.00043086932,0.000055051773,0.00015923288,0.000001366436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007799938,0.000065106506,0.0029277182,0.0002552153,0.00024810777,4.3756856e-7,0.0055149216,0.6537088,0.0014306474,0.31508452,0.001155465,0.019531049],"study_design_scores_gemma":[0.000649406,0.00004782196,0.004120765,0.00016129197,0.00002365467,0.000003993966,0.00028083954,0.9931689,0.00011095717,0.0012375875,0.00008027588,0.000114491],"about_ca_topic_score_codex":0.000002882833,"about_ca_topic_score_gemma":0.000006166414,"teacher_disagreement_score":0.43156534,"about_ca_system_score_codex":0.00007807931,"about_ca_system_score_gemma":0.00001400279,"threshold_uncertainty_score":0.4829721},"labels":[],"label_agreement":null},{"id":"W4252841157","doi":"10.5220/0006861904350442","title":"Finite-Time Altitude and Attitude Tracking of a Tri-Rotor UAV using Modified Super-Twisting Second Order Sliding Mode","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Control theory (sociology); Attitude control; Rotor (electric); Tracking (education); Mode (computer interface); Computer science; Aerospace engineering; Altitude (triangle); Sliding mode control; Engineering; Physics; Artificial intelligence; Nonlinear system; Mathematics; Mechanical engineering; Psychology; Control (management); Geometry","score_opus":0.038451815455912905,"score_gpt":0.28162968115349696,"score_spread":0.24317786569758404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252841157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9069042,0.000042619995,0.07959975,0.00020560676,0.00051846064,0.00080557907,0.00007096278,0.00010558135,0.01174719],"genre_scores_gemma":[0.9851045,0.000014093287,0.014667996,0.000053063086,0.000087183966,0.000008747177,0.0000026049108,0.000017337676,0.000044455268],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984979,0.000010935126,0.00086842576,0.00010484105,0.00034117297,0.00017674392],"domain_scores_gemma":[0.99847966,0.00016854802,0.0004346142,0.00007815894,0.00079230266,0.000046714355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043026434,0.00019074875,0.000359023,0.00030662023,0.00008681935,0.00011352135,0.00027296806,0.00010866476,0.00002150877],"category_scores_gemma":[0.00048628866,0.00016004518,0.000042891334,0.00017798584,0.00011416883,0.0005461793,0.000073745796,0.00019500485,0.0000018211483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002952778,0.00013354106,0.009682971,0.0017613551,0.0005635687,8.30241e-7,0.014431394,0.709943,0.07324932,0.18696667,0.00006803289,0.0029040724],"study_design_scores_gemma":[0.001363813,0.000056892994,0.0012432339,0.00061428384,0.000025984073,0.0000082723045,0.00052655616,0.99444425,0.0010716177,0.0004777222,0.000016313496,0.00015107685],"about_ca_topic_score_codex":0.000008420619,"about_ca_topic_score_gemma":0.000008770872,"teacher_disagreement_score":0.28450125,"about_ca_system_score_codex":0.000073523486,"about_ca_system_score_gemma":0.00004226032,"threshold_uncertainty_score":0.6526453},"labels":[],"label_agreement":null},{"id":"W4255457434","doi":"10.5220/0006855203090316","title":"LightByte: Communicating Wirelessly with an Underwater Robot using Light","year":2018,"lang":"en","type":"article","venue":"Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Underwater; Computer science; Robot; Mobile robot; Computer vision; Artificial intelligence; Geology","score_opus":0.028555336252778857,"score_gpt":0.26626804835738327,"score_spread":0.2377127121046044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255457434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8951357,0.000046377645,0.03964855,0.0055552484,0.00040804874,0.0007968852,0.000015612437,0.0007514277,0.05764214],"genre_scores_gemma":[0.9413744,0.000081031365,0.058376063,0.00010643212,0.000019782627,0.0000110783,0.0000024902708,0.00001581105,0.000012910695],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988753,0.000010175952,0.00056848384,0.0000816948,0.0002964884,0.00016782197],"domain_scores_gemma":[0.99890006,0.00005615741,0.00026923855,0.00024595915,0.00048939855,0.000039161583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025587095,0.00016794629,0.00021267975,0.0001959801,0.00014373183,0.00016428772,0.00085679087,0.00011559975,0.000010358661],"category_scores_gemma":[0.000078147445,0.00011853831,0.000024564924,0.00019695872,0.00025523358,0.0006329428,0.00016147237,0.00030440395,0.000003684413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111159454,0.00013440227,0.004218073,0.00023175629,0.00014587562,1.6804798e-7,0.0049797823,0.070261516,0.0079834,0.90391797,0.000041064155,0.007974849],"study_design_scores_gemma":[0.0006193563,0.000108995206,0.001110537,0.00038457138,0.000011791622,0.000007168714,0.0014577078,0.98604816,0.006088431,0.003962518,0.00004512826,0.000155604],"about_ca_topic_score_codex":0.000005141248,"about_ca_topic_score_gemma":0.000018301638,"teacher_disagreement_score":0.9157867,"about_ca_system_score_codex":0.00009139782,"about_ca_system_score_gemma":0.000024528365,"threshold_uncertainty_score":0.48338518},"labels":[],"label_agreement":null}]}