{"meta":{"query_hash":"ab553d08acef","filters":{"venue":"Proceedings of International Conference on Artificial Life and Robotics"},"cohort_total":5,"direct_labels_cover":0,"predictions_cover":5,"exported":5,"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/ab553d08acef","api":"https://metacan.xera.ac/api/v1/cohort?venue=Proceedings+of+International+Conference+on+Artificial+Life+and+Robotics"},"results":[{"id":"W4221126921","doi":"10.5954/icarob.2022.os23-5","title":"Recommendation an Emergency Patient Destinations by LightGBM","year":2022,"lang":"en","type":"article","venue":"Proceedings of International Conference on Artificial Life and Robotics","topic":"Innovation in Digital Healthcare Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Defence Medical Centre","funders":"","keywords":"Destinations; Medical emergency; Computer science; Medicine; Geography","score_opus":0.13995388058108035,"score_gpt":0.4163656937983438,"score_spread":0.2764118132172635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221126921","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":[0.7799294,0.00001800939,0.0009640017,0.027598202,0.0047022933,0.0011948348,0.0005158539,0.00015061385,0.1849268],"genre_scores_gemma":[0.997537,0.000029736246,0.00049167057,0.00066738593,0.00019393074,0.00016356318,0.00023135147,0.00001751269,0.0006678355],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99812424,0.000051357292,0.0009083794,0.00026648943,0.00044087245,0.00020867253],"domain_scores_gemma":[0.9975581,0.000058717604,0.00064543786,0.000058965124,0.001563033,0.000115718125],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00047579638,0.00012290475,0.0001626506,0.00021889756,0.00081657287,0.000024824378,0.00019741549,0.00006894798,0.0016915028],"category_scores_gemma":[0.00031720006,0.00012647705,0.000025645366,0.00025607372,0.00003560009,0.0003145335,0.00014730696,0.00040029152,0.00001958927],"study_design_candidate":"theoretical_or_conceptual","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":[0.00013863201,0.0003489441,0.023249326,0.00008509783,0.000023899845,1.9310306e-7,0.0026612084,0.00007428233,0.0033817098,0.9445033,0.016988447,0.008544944],"study_design_scores_gemma":[0.003489847,0.010981287,0.030886495,0.00086602074,0.000110217254,0.000034400655,0.3121664,0.1884511,0.0048878687,0.22631691,0.21841218,0.0033972738],"about_ca_topic_score_codex":0.00007029186,"about_ca_topic_score_gemma":0.000012482265,"teacher_disagreement_score":0.7181864,"about_ca_system_score_codex":0.00014100767,"about_ca_system_score_gemma":0.00015764756,"threshold_uncertainty_score":0.9992211},"labels":[],"label_agreement":null},{"id":"W4384159314","doi":"10.5954/icarob.2023.os7-3","title":"Design of a Database-Driven Control System for a Web Conveyor","year":2023,"lang":"en","type":"article","venue":"Proceedings of International Conference on Artificial Life and Robotics","topic":"Industrial Automation and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; University of Tokushima; University of Alberta","keywords":"Database; Computer science; Database design; Web application; World Wide Web","score_opus":0.07413000913128082,"score_gpt":0.26648494059300815,"score_spread":0.19235493146172733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384159314","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":[0.58764243,0.0001941123,0.34358633,0.008740769,0.010935619,0.009309841,0.0028911366,0.0032555456,0.033444226],"genre_scores_gemma":[0.9989745,0.00002050402,0.0006815623,0.0000204675,0.00018081215,0.000051566654,0.000015554719,0.000014436106,0.00004061085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991161,0.000005673769,0.0004222314,0.00011905966,0.0002100234,0.00012691847],"domain_scores_gemma":[0.99918634,0.00010445337,0.00014518987,0.00003737692,0.00046949493,0.00005714771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026246402,0.000106233325,0.0002509563,0.00017377308,0.000035703295,0.000043672113,0.00014102344,0.00007411917,0.000008061947],"category_scores_gemma":[0.00013709944,0.0000985907,0.000041068768,0.00011277169,0.000036054822,0.00009437197,0.000014537918,0.000064770895,0.000010966614],"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":[0.00036189836,0.0000374791,0.00034621204,0.000464467,0.00021674411,6.4251975e-7,0.0002453745,0.05031201,0.43534777,0.5100775,0.0018209786,0.00076893927],"study_design_scores_gemma":[0.00073478435,0.000099645,0.000058411686,0.0002095804,0.000023569413,0.0000011430345,0.00073393947,0.9923143,0.0054377425,0.00020550641,0.00008517257,0.000096247],"about_ca_topic_score_codex":0.0000035704186,"about_ca_topic_score_gemma":7.851697e-7,"teacher_disagreement_score":0.94200224,"about_ca_system_score_codex":0.000021352378,"about_ca_system_score_gemma":0.000046425404,"threshold_uncertainty_score":0.4020412},"labels":[],"label_agreement":null},{"id":"W4384159338","doi":"10.5954/icarob.2023.os25-2","title":"Multi Chaotic Flow Direction Algorithm for Feature Selection","year":2023,"lang":"en","type":"article","venue":"Proceedings of International Conference on Artificial Life and Robotics","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Algorithm; Feature selection; Chaotic; Feature (linguistics); Computer science; Selection (genetic algorithm); Flow (mathematics); Pattern recognition (psychology); Artificial intelligence; Mathematics; Geometry","score_opus":0.05668885262158308,"score_gpt":0.3010376655827179,"score_spread":0.2443488129611348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384159338","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014901546,0.000025404215,0.9569374,0.02405016,0.0014863369,0.0007343999,0.000050959512,0.00046940384,0.00134443],"genre_scores_gemma":[0.619988,0.0002482374,0.37754175,0.00035180902,0.0007201717,0.00008896824,0.00003966012,0.000018322511,0.0010030628],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926436,0.000002412207,0.00017028896,0.00025177427,0.00017547536,0.00013566327],"domain_scores_gemma":[0.99933785,0.000038605318,0.000112402515,0.000038234222,0.00040979704,0.00006308844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012346327,0.00009360986,0.000109519206,0.0001305479,0.00014432923,0.00015294165,0.00022637176,0.00006015055,0.0000027630942],"category_scores_gemma":[0.00005320485,0.00008560871,0.00004099081,0.00030157104,0.000029293085,0.0002120277,0.0000608962,0.000096652184,0.0000072348375],"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":[0.000028616967,0.00017957033,0.00047312467,0.000032241096,0.000054963923,3.6797374e-7,0.00029164646,0.004917003,0.03234179,0.69231486,0.0045275586,0.26483822],"study_design_scores_gemma":[0.0001122927,0.00008560823,0.0013928129,0.00002368647,0.000005166913,0.0000019490003,0.000052477717,0.98952526,0.0028971187,0.00538445,0.00042733442,0.00009182995],"about_ca_topic_score_codex":0.000003891853,"about_ca_topic_score_gemma":0.0000031498103,"teacher_disagreement_score":0.9846083,"about_ca_system_score_codex":0.000013717887,"about_ca_system_score_gemma":0.00002331292,"threshold_uncertainty_score":0.3491022},"labels":[],"label_agreement":null},{"id":"W4395659980","doi":"10.5954/icarob.2024.os14-2","title":"Robotic Food Handling Utilizing Temperature Dependent Variable-Stiffness Material","year":2024,"lang":"en","type":"article","venue":"Proceedings of International Conference on Artificial Life and Robotics","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Stiffness; Variable (mathematics); Environmental science; Computer science; Materials science; Composite material; Mathematics; Mathematical analysis","score_opus":0.03837912810923181,"score_gpt":0.25511348658828475,"score_spread":0.21673435847905295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395659980","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":[0.9309288,0.0010445759,0.028592514,0.0013493632,0.010101077,0.00055638247,0.00014319428,0.00076421496,0.02651988],"genre_scores_gemma":[0.9971649,0.0003608958,0.0018374042,0.00004116764,0.00044596675,0.000008882004,0.000013793302,0.000031190713,0.00009580759],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883085,0.0000031179784,0.0003797172,0.00027217163,0.00030844938,0.00020565928],"domain_scores_gemma":[0.99951315,0.000030977804,0.00004256699,0.000053080774,0.00025991077,0.00010033351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014632025,0.00020176038,0.00021955009,0.00017237637,0.00007325404,0.0004932275,0.0002106542,0.00012622154,0.00011774396],"category_scores_gemma":[0.00006510762,0.00018146329,0.000042273718,0.00012787378,0.00005128968,0.00023252654,0.000056147786,0.00024959803,0.000011973589],"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":[0.000054524437,0.000041779254,0.00007724562,0.00038377792,0.00015211864,0.0000044031995,0.00032055113,0.08031795,0.1651596,0.750053,0.00017562634,0.0032594276],"study_design_scores_gemma":[0.00014037003,0.00019193493,0.00013880055,0.0011302718,0.00006848064,0.000030308573,0.00090892834,0.8810527,0.10149987,0.013980381,0.00032331236,0.0005346956],"about_ca_topic_score_codex":0.000005395511,"about_ca_topic_score_gemma":0.0000030410984,"teacher_disagreement_score":0.8007347,"about_ca_system_score_codex":0.000033080676,"about_ca_system_score_gemma":0.000042783377,"threshold_uncertainty_score":0.73998576},"labels":[],"label_agreement":null},{"id":"W4409913388","doi":"10.5954/icarob.2025.os8-6","title":"Accurate Brain Age Prediction Through Advanced Preprocessing and 3D ResNet-50 Modeling","year":2025,"lang":"en","type":"article","venue":"Proceedings of International Conference on Artificial Life and Robotics","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science and Technology Council; National Science Council","keywords":"Residual neural network; Computer science; Preprocessor; Artificial intelligence; Deep learning","score_opus":0.09843435204345852,"score_gpt":0.33403367909365594,"score_spread":0.23559932705019743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409913388","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":[0.85279536,0.000081394915,0.05245243,0.022558162,0.0010477834,0.0005480344,0.000032630873,0.00024361268,0.070240594],"genre_scores_gemma":[0.9968095,0.0002599396,0.0012425793,0.0011375515,0.000071251576,0.000014467695,0.0000031613117,0.000008690966,0.0004529037],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988252,0.000011082931,0.00037019255,0.000413658,0.0002481299,0.00013174707],"domain_scores_gemma":[0.9993708,0.00007572633,0.00018419966,0.000055580294,0.00026150295,0.0000522046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016548556,0.00012862019,0.00014545623,0.0001419515,0.00020289181,0.00020043038,0.00014684554,0.00007543534,0.000010843443],"category_scores_gemma":[0.0010965014,0.00012434504,0.00002403275,0.00018052326,0.00013993662,0.00046453925,0.000069163434,0.00018075721,0.0000020593188],"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":[0.000298665,0.00008668482,0.00019164989,0.00008125019,0.000011464741,6.1168794e-7,0.00051891257,0.0048034135,0.4962388,0.490524,0.00010382221,0.0071407324],"study_design_scores_gemma":[0.00038215742,0.00012237455,0.00051712675,0.0002730743,0.0000159383,0.0000058706096,0.0011039402,0.88734144,0.0710903,0.038360085,0.00061383535,0.00017384237],"about_ca_topic_score_codex":0.0000054103243,"about_ca_topic_score_gemma":0.0000027852952,"teacher_disagreement_score":0.882538,"about_ca_system_score_codex":0.00002572195,"about_ca_system_score_gemma":0.000051041818,"threshold_uncertainty_score":0.5070644},"labels":[],"label_agreement":null}]}