{"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25983495,0.0071656597,0.68724513,0.004456581,0.0013817672,0.0012987993,0.009836344,0.012681257,0.016099513],"genre_scores_gemma":[0.6990687,0.0011935908,0.28025725,0.0010616867,0.00037088024,0.00039224498,0.006600407,0.00012832823,0.010926968],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911696,0.0001519365,0.00006631609,0.00021312763,0.00032282257,0.00012882391],"domain_scores_gemma":[0.9993067,0.000163582,0.00006783664,0.00010828661,0.0002801756,0.00007343646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000595824,0.00086181914,0.0010991571,0.0031800233,0.0007236945,0.00093471806,0.0014925324,0.0014441541,0.004387633],"category_scores_gemma":[0.00226178,0.00034902873,0.001000522,0.0027636755,0.00019278587,0.0012542449,0.0008320969,0.000681753,0.0021078766],"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":[0.0011992805,0.0007267936,0.03279171,0.0006781838,0.00028436826,0.00039871066,0.00030242302,0.04396578,0.014890271,0.0029091688,0.061864745,0.83998847],"study_design_scores_gemma":[0.00023805078,0.00034464287,0.012766864,0.00010754623,0.000185269,0.0003813903,0.00034721263,0.9488244,0.008837602,0.0037329304,0.024150113,0.00008389283],"about_ca_topic_score_codex":0.03464499,"about_ca_topic_score_gemma":0.044163764,"teacher_disagreement_score":0.03464499,"about_ca_system_score_codex":0.00094063376,"about_ca_system_score_gemma":0.0012403829,"threshold_uncertainty_score":0.0688867},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02271897,0.00025316037,0.9660855,0.00020250432,0.00017153683,0.000479154,0.00013994754,0.0061445436,0.0038047237],"genre_scores_gemma":[0.77374184,0.00017875654,0.21772169,0.0003464855,0.00014982975,0.0008417606,0.0002722858,0.000118054224,0.006629326],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99930966,0.0000623394,0.000055938584,0.00025355897,0.00025805793,0.000060425915],"domain_scores_gemma":[0.9995435,0.00006380261,0.00004351997,0.0000569729,0.0002477676,0.00004452072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061570393,0.00047449052,0.0006947195,0.00062289415,0.00061487383,0.0012528307,0.0020395226,0.0008275254,0.0038907179],"category_scores_gemma":[0.0006497143,0.00030512048,0.0003767343,0.00031466226,0.00032298258,0.00066670164,0.00049712247,0.00050409685,0.0013179509],"study_design_candidate":"bench_or_experimental","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":[0.0012377711,0.00068325776,0.0031841188,0.00065370987,0.00022690068,0.001187371,0.00064770936,0.0625825,0.3869834,0.021873308,0.01317923,0.50756073],"study_design_scores_gemma":[0.00052774855,0.0011154748,0.0024487355,0.000044490986,0.0001211496,0.0009465345,0.00007761409,0.82087994,0.14424789,0.0020800906,0.02738579,0.00012455774],"about_ca_topic_score_codex":0.0026313285,"about_ca_topic_score_gemma":0.0012149811,"teacher_disagreement_score":0.0038907179,"about_ca_system_score_codex":0.0005447055,"about_ca_system_score_gemma":0.00081884715,"threshold_uncertainty_score":0.013015747},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019537061,0.00046471143,0.97705805,0.00015584123,0.000070478534,0.0001655457,0.00011589401,0.00060912914,0.0018232507],"genre_scores_gemma":[0.23781368,0.00034329537,0.75605494,0.00014171458,0.00006053626,0.0007210614,0.00062978256,0.0000841117,0.0041508353],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957234,0.00008451942,0.0000382578,0.000095334544,0.00016372412,0.000045795092],"domain_scores_gemma":[0.99960595,0.0001343906,0.000040343373,0.000032588814,0.0001701076,0.000016473161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072980195,0.00067088066,0.00074841833,0.001407971,0.00047799852,0.00075033505,0.00081153406,0.00078092323,0.0025853873],"category_scores_gemma":[0.001763725,0.00025863445,0.0007269117,0.0012308488,0.0003015596,0.0006857321,0.0005297031,0.0006518777,0.00057949877],"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":[0.00021324746,0.000111148125,0.002044646,0.00017133573,0.000086082386,0.00010200664,0.00011312446,0.16758606,0.017740143,0.008005539,0.0058596153,0.7979671],"study_design_scores_gemma":[0.00004925567,0.00010353385,0.0008562544,0.0000127866315,0.000016043154,0.000108254375,0.000027523467,0.9848867,0.0056400294,0.0029144303,0.0053670537,0.000018082412],"about_ca_topic_score_codex":0.0025127456,"about_ca_topic_score_gemma":0.0020823157,"teacher_disagreement_score":0.0025853873,"about_ca_system_score_codex":0.00042700738,"about_ca_system_score_gemma":0.0010595531,"threshold_uncertainty_score":0.008648992},"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":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73498005,0.00076683064,0.25713697,0.0000970738,0.00011416576,0.00006926505,0.000043338387,0.0007119676,0.006080308],"genre_scores_gemma":[0.9294017,0.00018542907,0.0674985,0.00003848698,0.000012918945,0.00002862189,0.000029348625,0.00004494129,0.0027599924],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998859,0.000011667767,0.0000074800146,0.000034023808,0.000045273908,0.000015545864],"domain_scores_gemma":[0.99982446,0.000038312395,0.00006189517,0.000039087645,0.00002184922,0.000014480909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014581085,0.00028146512,0.00020432661,0.00013859384,0.00019987562,0.00033986382,0.00043397347,0.00033143026,0.00064231874],"category_scores_gemma":[0.00022333437,0.00018540422,0.00022144004,0.00008434584,0.0003089083,0.00060343294,0.00039391546,0.00021851191,0.00035894135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008584239,0.000034702054,0.0002927094,0.00009766284,0.000007820821,0.00020283471,0.000048830418,0.007673288,0.9766575,0.0008191387,0.00009665169,0.0139830345],"study_design_scores_gemma":[0.00003915449,0.00084799965,0.003114897,0.000019110075,0.000018886805,0.0008108053,0.000035243662,0.08309714,0.9040484,0.0010357266,0.006876685,0.00005606253],"about_ca_topic_score_codex":0.000075369215,"about_ca_topic_score_gemma":0.00012641019,"teacher_disagreement_score":0.00064231874,"about_ca_system_score_codex":0.000120560515,"about_ca_system_score_gemma":0.000101555335,"threshold_uncertainty_score":0.002148807},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18157561,0.0009397404,0.8064563,0.0004935093,0.00020585176,0.000119047334,0.0012893692,0.0063414215,0.0025791256],"genre_scores_gemma":[0.79972047,0.0005297133,0.19352718,0.00025503073,0.000048468493,0.00018684068,0.0019852542,0.00022352031,0.0035235398],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998204,0.00003574808,0.000011561359,0.000063090825,0.00004028766,0.000028945231],"domain_scores_gemma":[0.99967027,0.00011368438,0.000041966698,0.0000438585,0.000113839735,0.000016412938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081748515,0.0012132284,0.0005031274,0.0008482509,0.00022443713,0.0005721203,0.0011401984,0.00078970083,0.0013082966],"category_scores_gemma":[0.0017872356,0.00042027823,0.00097372883,0.00038500785,0.0002818244,0.00075294153,0.0005845201,0.00085298106,0.00078961387],"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":[0.00016884216,0.000103506754,0.006862417,0.0000679564,0.0001113734,0.00018583427,0.00007484406,0.7993778,0.011752523,0.0022762378,0.0041459897,0.17487273],"study_design_scores_gemma":[0.0000028781278,0.000020649586,0.00078512024,0.000006017229,0.000011522726,0.000030315607,0.000004669685,0.9943995,0.0031574846,0.0010307641,0.0005437153,0.00000739384],"about_ca_topic_score_codex":0.016317181,"about_ca_topic_score_gemma":0.024384014,"teacher_disagreement_score":0.016317181,"about_ca_system_score_codex":0.0007820097,"about_ca_system_score_gemma":0.0010307526,"threshold_uncertainty_score":0.032444417},"labels":[],"label_agreement":null}]}