{"meta":{"query_hash":"4c516f860663","filters":{"venue":"International Journal of Robotics and Automation"},"cohort_total":519,"direct_labels_cover":0,"predictions_cover":519,"exported":519,"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/4c516f860663","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Robotics+and+Automation"},"results":[{"id":"W189989800","doi":"10.2316/journal.206.2009.4.206-3233","title":"TWO FUSION PREDICTORS FOR MULTISENSOR DISCRETETIME LINEAR SYSTEM","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fusion; Computer science; Philosophy","score_opus":0.01144433066409002,"score_gpt":0.27353941635654555,"score_spread":0.26209508569245554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W189989800","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":[0.026877522,0.000093644114,0.9688372,0.0021621857,0.0017730423,0.00008457277,0.00001120152,0.00006385361,0.00009675258],"genre_scores_gemma":[0.75423414,0.0000360839,0.24515934,0.00008467205,0.00044810097,4.7734727e-7,0.000010755494,0.0000036979977,0.00002273338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989941,0.000028225124,0.00040000153,0.00011851195,0.00036032038,0.00009884072],"domain_scores_gemma":[0.99892545,0.00011017212,0.00035413977,0.00010380135,0.00043714623,0.000069291884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002807083,0.00008404495,0.00012889417,0.00014082453,0.0000733646,0.00016603727,0.0003814304,0.000042184827,0.0000016519833],"category_scores_gemma":[0.00006696522,0.0000676084,0.00006982765,0.000063381376,0.000013279731,0.00043141318,0.0000425709,0.00008691707,0.0000019063935],"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":[0.00016147364,0.0002421217,0.0012728071,0.00004294745,0.00016965886,0.00009807647,0.0009191244,0.4210681,0.006696698,0.25589406,0.003706766,0.30972815],"study_design_scores_gemma":[0.0008549957,0.00016580208,0.0039429087,0.00017471451,0.000013577439,0.00019687129,0.00002831108,0.9921622,0.00043448704,0.00093840517,0.0010023119,0.00008535907],"about_ca_topic_score_codex":0.000002104591,"about_ca_topic_score_gemma":3.4180093e-7,"teacher_disagreement_score":0.7273566,"about_ca_system_score_codex":0.00004145046,"about_ca_system_score_gemma":0.000023100947,"threshold_uncertainty_score":0.27569908},"labels":[],"label_agreement":null},{"id":"W1963765169","doi":"10.2316/journal.206.2009.2.206-3283","title":"TIP TRAJECTORY TRACKING OF FLEXIBLE-JOINT MANIPULATORS DRIVEN BY HARMONIC DRIVES","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Mechanical Engineering and Vibrations Research","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Control theory (sociology); Trajectory; Tracking (education); Harmonic drive; Harmonic; Joint (building); Computer science; Control engineering; Physics; Engineering; Control (management); Artificial intelligence; Acoustics; Structural engineering; Psychology","score_opus":0.02220271684791481,"score_gpt":0.26792459226801524,"score_spread":0.24572187542010043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963765169","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":[0.45507154,0.00060141564,0.543063,0.0004141468,0.00052223116,0.000056071833,0.0000061387213,0.000058069418,0.00020739947],"genre_scores_gemma":[0.99408835,0.00019750184,0.0055827857,0.000010925182,0.00008088095,4.421074e-7,0.0000054004786,0.000008031352,0.000025651001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992082,0.000011757896,0.0003552572,0.000050394832,0.00029248378,0.000081873935],"domain_scores_gemma":[0.999618,0.000030347772,0.00009224899,0.000047644415,0.00015623691,0.00005551515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013293556,0.000070224225,0.00012697338,0.00019189566,0.000016660506,0.00004465118,0.000118605574,0.000044627322,0.000021311414],"category_scores_gemma":[0.000035095585,0.00006560951,0.000054874745,0.00006985458,0.000011757643,0.00019543617,0.000007743851,0.00013486548,0.0000012986342],"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":[0.0000092534665,0.00006378777,0.0000909579,0.000026437352,0.00012818347,0.0000076335755,0.0002727842,0.81514955,0.1294707,0.0051967036,0.00054233446,0.049041644],"study_design_scores_gemma":[0.00039346464,0.00014227304,0.010664364,0.0001508966,0.00001641437,0.000045403784,0.00005098586,0.95149904,0.036177225,0.0006530067,0.000105563944,0.00010135993],"about_ca_topic_score_codex":9.454284e-7,"about_ca_topic_score_gemma":1.6587107e-7,"teacher_disagreement_score":0.53901684,"about_ca_system_score_codex":0.000045102744,"about_ca_system_score_gemma":0.000014910666,"threshold_uncertainty_score":0.2675478},"labels":[],"label_agreement":null},{"id":"W1964556908","doi":"10.2316/journal.206.2004.4.206-2715","title":"VLSI Implementation of a Neuromorphic Spiking Pixel and Investigation of Various Focal-Plane Excitation Schemes","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Neuromorphic engineering; Pixel; Computer science; Synchronization (alternating current); Very-large-scale integration; Artificial intelligence; Computer vision; Electronic engineering; Computer hardware; Embedded system; Artificial neural network; Engineering; Channel (broadcasting); Telecommunications","score_opus":0.012179587902081864,"score_gpt":0.24419763419138027,"score_spread":0.2320180462892984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964556908","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":[0.9614596,0.00012322882,0.03775442,0.00038145462,0.00020412222,0.000045043453,0.000005240157,0.000013605243,0.00001328951],"genre_scores_gemma":[0.9909761,0.00015135211,0.008779849,0.00002004733,0.00005138557,4.205687e-7,0.000011932854,0.0000079102765,9.975829e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.999252,0.000011947063,0.00040164957,0.000048785565,0.00023420015,0.000051423394],"domain_scores_gemma":[0.9993941,0.000034560522,0.00028090642,0.000031159758,0.00023051558,0.000028713092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013263988,0.00006637227,0.000114255236,0.00019565341,0.000015989352,0.000028598944,0.00005246051,0.000026896707,0.00000275463],"category_scores_gemma":[0.000026678776,0.00006691689,0.000023949613,0.00006630041,0.000035470657,0.0002630164,0.000010250975,0.00006481473,2.0476463e-7],"study_design_candidate":"observational","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":[0.000025834282,0.000039628107,0.015615956,0.00024037548,0.00022149197,0.000012747569,0.0035689159,0.4704669,0.46741718,0.011726182,0.000028989889,0.03063577],"study_design_scores_gemma":[0.0044645406,0.00045630243,0.6805532,0.00090177957,0.00021397379,0.00061965745,0.0010528524,0.16441622,0.118592314,0.028293293,0.000090411515,0.0003454247],"about_ca_topic_score_codex":0.00002035924,"about_ca_topic_score_gemma":0.000007530549,"teacher_disagreement_score":0.66493726,"about_ca_system_score_codex":0.000033594475,"about_ca_system_score_gemma":0.000026019672,"threshold_uncertainty_score":0.27287915},"labels":[],"label_agreement":null},{"id":"W1964709544","doi":"10.2316/journal.206.2013.1.206-3654","title":"POSITION-SINGULARITY CHARACTERIZATION OF A SPECIAL CLASS OF THE STEWART PARALLEL MECHANISMS","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Singularity; Position (finance); Mechanism (biology); Class (philosophy); Stewart platform; Base (topology); Characterization (materials science); Constant (computer programming); Orientation (vector space); Geometry; Physics; Mathematics; Computer science; Classical mechanics; Mathematical analysis; Artificial intelligence; Optics; Kinematics; Quantum mechanics","score_opus":0.00510223087129356,"score_gpt":0.19478538946516172,"score_spread":0.18968315859386817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964709544","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":[0.19866757,0.000010581695,0.7993715,0.00048767717,0.0012264741,0.00008683334,0.000008133727,0.000008009679,0.00013323808],"genre_scores_gemma":[0.92738765,0.000049576447,0.072275974,0.0000312653,0.00021715228,9.3572953e-7,0.000009648777,0.000008703738,0.000019083775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915475,0.000018493496,0.00042387127,0.00004046338,0.0003069481,0.00005547153],"domain_scores_gemma":[0.9991939,0.000020483476,0.00032401035,0.00006113272,0.0003741218,0.00002635958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011350864,0.00006650284,0.00013249325,0.00008561681,0.000020162248,0.000036065314,0.00014348143,0.00005151232,0.000034713783],"category_scores_gemma":[0.00002095657,0.00005117195,0.000061960855,0.000055779266,0.000021155518,0.00022239571,0.000024790521,0.000076744465,0.0000010226603],"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":[0.000015615082,0.00009244186,0.00036038013,0.00006372104,0.00017903719,0.0000022988788,0.0004906579,0.45808774,0.2424257,0.29017675,0.00007838909,0.008027276],"study_design_scores_gemma":[0.0005290769,0.0000767644,0.044554334,0.00019935181,0.000042032723,0.00006404194,0.000053337568,0.89066035,0.0067249895,0.056969315,0.0000256633,0.000100749035],"about_ca_topic_score_codex":0.0000042541774,"about_ca_topic_score_gemma":0.0000015543948,"teacher_disagreement_score":0.72872007,"about_ca_system_score_codex":0.000034184603,"about_ca_system_score_gemma":0.000020848802,"threshold_uncertainty_score":0.20867315},"labels":[],"label_agreement":null},{"id":"W1965508435","doi":"10.2316/journal.206.2012.1.206-3536","title":"AUTONOMOUS AND ROBUST MULTI-ROBOT COOPERATION USING AN ARTIFICIAL IMMUNE SYSTEM","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Artificial Immune Systems Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Robot; Computer science; Artificial immune system; Autonomous robot; Artificial intelligence; Mobile robot","score_opus":0.043649751702632876,"score_gpt":0.2768985206414522,"score_spread":0.23324876893881932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965508435","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":[0.41032258,0.00056875974,0.5878494,0.00006344562,0.001028849,0.00008527976,0.0000037605428,0.000054968088,0.00002301156],"genre_scores_gemma":[0.96171016,0.000023120809,0.037808593,0.0000053675176,0.00041720408,0.0000022569968,0.000009700455,0.000018241102,0.00000533422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908054,0.000032964508,0.00054091786,0.0000619148,0.00017057561,0.00011307662],"domain_scores_gemma":[0.9993611,0.000022657598,0.00020675236,0.00007230253,0.00026003813,0.00007712376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034593616,0.00009938537,0.00014864298,0.00015391689,0.000089445784,0.00013485833,0.000090969006,0.000061867264,0.0000033888289],"category_scores_gemma":[0.000020490615,0.00009824893,0.000028268933,0.000060524708,0.000025703906,0.0007657225,0.000021283291,0.000097711294,0.0000037100424],"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":[0.0000052630567,0.00006631971,0.00047202536,0.00002582654,0.0000707837,0.000001934071,0.0007171577,0.8799463,0.10236722,0.008207231,0.000005774225,0.008114166],"study_design_scores_gemma":[0.00018665273,0.000020656731,0.005606304,0.00007467001,0.000034107514,0.00028730062,0.000378673,0.9877922,0.005424111,0.000020475529,0.00006682892,0.0001080291],"about_ca_topic_score_codex":0.000026432379,"about_ca_topic_score_gemma":0.000006906148,"teacher_disagreement_score":0.5513876,"about_ca_system_score_codex":0.00013923772,"about_ca_system_score_gemma":0.000019554853,"threshold_uncertainty_score":0.4006475},"labels":[],"label_agreement":null},{"id":"W1967866750","doi":"10.2316/journal.206.2010.2.206-3386","title":"MULTI-CUE FACIAL FEATURE DETECTION AND TRACKING UNDER VARIOUS ILLUMINATIONS","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Face recognition and analysis","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Feature (linguistics); Tracking (education); Pattern recognition (psychology); Psychology; Linguistics","score_opus":0.012781608414318564,"score_gpt":0.26553186593170686,"score_spread":0.2527502575173883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967866750","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":[0.12367301,0.000034680994,0.8711838,0.004149345,0.0008643579,0.000029468054,0.000002146491,0.00002194495,0.000041251387],"genre_scores_gemma":[0.9295495,0.0000692005,0.070101425,0.0001157371,0.00011656084,5.078916e-7,0.0000025053469,0.0000032550972,0.00004131775],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937236,0.000021404083,0.00019749235,0.00009472607,0.00025088477,0.00006314999],"domain_scores_gemma":[0.99915904,0.000046849298,0.00022159645,0.000049110542,0.0004670577,0.000056370223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019614729,0.000066707995,0.00008662475,0.00025476562,0.000093757124,0.0002921695,0.00016015653,0.0000637207,0.0000056102103],"category_scores_gemma":[0.000085668566,0.000059243146,0.00004790366,0.00010159334,0.000037750662,0.00061917934,0.000038081285,0.00020101163,0.0000017289366],"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":[0.000009856851,0.00017838295,0.0009296989,0.000012260281,0.00023723538,0.000030980307,0.0015989664,0.012322171,0.13978122,0.02248227,0.000050744093,0.82236624],"study_design_scores_gemma":[0.0007201093,0.00004441524,0.04507473,0.00003174075,0.000033212484,0.00055654667,0.00013371411,0.9472497,0.0027449362,0.0027324583,0.0005530751,0.00012534525],"about_ca_topic_score_codex":0.0000052406144,"about_ca_topic_score_gemma":0.00006169946,"teacher_disagreement_score":0.9349275,"about_ca_system_score_codex":0.000021003276,"about_ca_system_score_gemma":0.000027727296,"threshold_uncertainty_score":0.28173974},"labels":[],"label_agreement":null},{"id":"W1968802178","doi":"10.2316/journal.206.2006.4.206-2723","title":"DESIGN OF A SLIDING MODE CONTROLLER BY FUZZY LOGIC","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Mode (computer interface); Control theory (sociology); Computer science; Controller (irrigation); Control engineering; Control (management); Engineering; Artificial intelligence; Operating system","score_opus":0.012783333466009694,"score_gpt":0.24023306499974162,"score_spread":0.22744973153373194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968802178","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":[0.003553915,0.00048795316,0.99321413,0.0015039335,0.00037308695,0.00005934357,0.0000016610048,0.0000128184965,0.0007931397],"genre_scores_gemma":[0.96550626,0.000032290336,0.034212716,0.0000851286,0.00011104102,9.376799e-7,0.0000011250653,0.0000026477915,0.000047830177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900174,0.000054246204,0.00043131298,0.000075275624,0.0003629933,0.000074437405],"domain_scores_gemma":[0.9989485,0.000101619466,0.0005067762,0.000050680752,0.00036644062,0.000025968948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032845358,0.00006634304,0.00016227966,0.00010895185,0.000026492751,0.00010136523,0.00032156822,0.000037335496,8.044025e-7],"category_scores_gemma":[0.000031794567,0.000051480467,0.000048873906,0.000056281195,0.000013837769,0.00032057404,0.000031893876,0.000054311822,0.000001168615],"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":[0.00003843772,0.00010877202,0.00030390394,0.000007858292,0.00009548524,0.000015846068,0.0001324441,0.48171347,0.03273982,0.47419268,0.0016988012,0.00895249],"study_design_scores_gemma":[0.0011746207,0.0001221203,0.00064232224,0.00005320047,0.000011639216,0.000104969506,0.000014518813,0.89027256,0.000599557,0.10683757,0.00009128498,0.000075644406],"about_ca_topic_score_codex":0.000020909634,"about_ca_topic_score_gemma":3.581217e-7,"teacher_disagreement_score":0.9619524,"about_ca_system_score_codex":0.00003419648,"about_ca_system_score_gemma":0.000030856198,"threshold_uncertainty_score":0.20993125},"labels":[],"label_agreement":null},{"id":"W1970415547","doi":"10.2316/journal.206.2007.2.206-2735","title":"CONTINUOUS SPEECH RECOGNITION IN NOISE USING A SPECTRUM-ENTROPY BEAM-FORMER","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Speech recognition; Noise spectrum; Acoustics; Computer science; Noise (video); Spectrum (functional analysis); Artificial intelligence; Physics; Noise reduction","score_opus":0.01736950141857407,"score_gpt":0.2745872323731533,"score_spread":0.2572177309545792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970415547","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":[0.53177404,0.00006471264,0.46693218,0.00063299673,0.00046717766,0.000028343533,4.845756e-7,0.000010245037,0.00008982793],"genre_scores_gemma":[0.78836125,0.000040667135,0.21124204,0.00013445961,0.00020739854,1.0908131e-7,0.0000016393502,0.0000040843706,0.000008340499],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99894524,0.000013893627,0.00043655172,0.00009778237,0.00037023224,0.00013629427],"domain_scores_gemma":[0.99917084,0.00005001565,0.0004019383,0.000049511567,0.0002735131,0.000054200562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059879455,0.00007535575,0.00011942938,0.00038406483,0.00003594481,0.00021602359,0.0002358475,0.000041606145,0.0000059367444],"category_scores_gemma":[0.00007558069,0.0000693376,0.00004083901,0.00016176804,0.000017656721,0.0009670933,0.000043356573,0.00012719753,0.0000032622813],"study_design_candidate":"design_other","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":[0.00009498829,0.00027588833,0.02503533,0.000024352843,0.00009094781,0.00063171785,0.0009244303,0.009456518,0.09147411,0.0015908498,0.00007384714,0.870327],"study_design_scores_gemma":[0.0047504874,0.00040710685,0.13506706,0.0012625548,0.000049125843,0.0056237155,0.00030168082,0.33267826,0.45321307,0.06559008,0.0004019441,0.0006549215],"about_ca_topic_score_codex":0.000013885419,"about_ca_topic_score_gemma":0.000010234805,"teacher_disagreement_score":0.8696721,"about_ca_system_score_codex":0.00011100839,"about_ca_system_score_gemma":0.00005594414,"threshold_uncertainty_score":0.28275052},"labels":[],"label_agreement":null},{"id":"W1970827975","doi":"10.2316/journal.206.2011.3.206-3224","title":"A TELEOPERATION SYSTEM WITH NOVEL HAPTIC DEVICE FOR MICRO-MANIPULATION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Teleoperation; Haptic technology; Computer science; Simulation; Human–computer interaction; Artificial intelligence; Robot","score_opus":0.031446273491517955,"score_gpt":0.23490140409050936,"score_spread":0.2034551305989914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970827975","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":[0.123342715,0.000071112656,0.8758577,0.000054258922,0.0004317374,0.00009549827,0.0000039250945,0.000029562068,0.000113451344],"genre_scores_gemma":[0.93114257,0.000022464068,0.06867072,0.000015463755,0.00011707061,0.0000029840255,0.000006803951,0.000012094961,0.000009804958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941653,0.000005457085,0.0002916674,0.000057155044,0.00016411775,0.000065084554],"domain_scores_gemma":[0.99937093,0.00002081483,0.00012993731,0.000041324154,0.00040500748,0.000031959476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013596773,0.00007656773,0.00009760855,0.00011249894,0.000030863168,0.000060641203,0.00009100362,0.00003624894,0.000003600876],"category_scores_gemma":[0.000012586689,0.000061749015,0.000028033102,0.000037729507,0.00001043052,0.0002677864,0.0000060676107,0.00005194892,0.0000013386023],"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":[0.00007475578,0.000062232095,0.0010289025,0.0001371214,0.0002682958,0.000010524888,0.0012580622,0.9214758,0.036467884,0.02469257,0.00005129223,0.014472553],"study_design_scores_gemma":[0.00043445447,0.00011545939,0.004595698,0.00019413097,0.00003829665,0.000239044,0.00014688386,0.9860098,0.007902542,0.000119838456,0.00009961069,0.00010426204],"about_ca_topic_score_codex":0.0000063237044,"about_ca_topic_score_gemma":0.0000075534927,"teacher_disagreement_score":0.8077999,"about_ca_system_score_codex":0.000064905056,"about_ca_system_score_gemma":0.000016466105,"threshold_uncertainty_score":0.2518052},"labels":[],"label_agreement":null},{"id":"W1971062211","doi":"10.2316/journal.206.2009.4.206-3160","title":"A SINGULARITY-BASED APPROACH TO IMPROVE MOBILE ROBOT MOTION PLANNING","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Motion planning; Mobile robot; Singularity; Motion (physics); Robot; Artificial intelligence; Mathematics","score_opus":0.01524755725142514,"score_gpt":0.27908425723278507,"score_spread":0.26383669998135995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971062211","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058031953,0.00006751793,0.99129707,0.0016615145,0.0008089762,0.000107586544,0.0000014563932,0.000051957486,0.00020075674],"genre_scores_gemma":[0.47486943,0.0000013584878,0.524655,0.0003228412,0.00013421773,0.0000012260464,0.00000356016,0.0000033275776,0.000009031324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866116,0.000043744672,0.0004090134,0.00017915909,0.0005644371,0.00014250477],"domain_scores_gemma":[0.9989189,0.0000549685,0.0003501198,0.00013425962,0.0004293248,0.00011242768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046940363,0.00011570797,0.00016419773,0.00035005307,0.00006473595,0.00033175366,0.0005260643,0.00005900236,5.823706e-7],"category_scores_gemma":[0.00009812614,0.00010699307,0.00006013553,0.00016668421,0.000013060679,0.0005212216,0.000047206053,0.00015867715,0.0000026992006],"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":[0.000008991204,0.00013032429,0.00016279165,0.0000043610016,0.000020693455,0.000025325957,0.0004440525,0.9262501,0.0018640414,0.0041218614,0.00007117409,0.06689628],"study_design_scores_gemma":[0.00049424724,0.00029603418,0.0096042305,0.00009909709,0.000009877289,0.0001526303,0.000024765031,0.98609656,0.0007006791,0.0023297418,0.00007048865,0.00012166898],"about_ca_topic_score_codex":0.0000023307716,"about_ca_topic_score_gemma":2.7913678e-8,"teacher_disagreement_score":0.46906623,"about_ca_system_score_codex":0.00009150883,"about_ca_system_score_gemma":0.00006644672,"threshold_uncertainty_score":0.43630508},"labels":[],"label_agreement":null},{"id":"W1971782254","doi":"10.2316/journal.206.2013.4.206-3769","title":"A POTENTIAL-PSO APPROACH TO COOPERATIVE TARGET SEARCHING OF MULTI-ROBOTS IN UNKNOWN ENVIRONMENTS","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Robot; Artificial intelligence; Particle swarm optimization; Mathematical optimization; Machine learning; Mathematics","score_opus":0.012391936064815244,"score_gpt":0.24045784076700438,"score_spread":0.22806590470218913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971782254","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":[0.2141376,0.0001048933,0.78517175,0.00013385867,0.00021972707,0.00010749479,0.0000022128222,0.000005690154,0.000116754985],"genre_scores_gemma":[0.9205383,0.000099811,0.07924522,0.00002297168,0.000039539238,0.000002655637,0.0000038109004,0.0000089562955,0.00003871008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991717,0.000025377294,0.00037777683,0.00006907883,0.0002652538,0.00009085524],"domain_scores_gemma":[0.9996823,0.000020996675,0.0000906609,0.000046510686,0.00011094176,0.000048604685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016283279,0.00008024566,0.00013812944,0.00020652552,0.000014990599,0.000052745367,0.00015008962,0.000035093195,0.000020573323],"category_scores_gemma":[0.00003903761,0.000070533344,0.000031226908,0.000061731706,0.000017982049,0.00025281456,0.000032868425,0.00011883029,0.000005894327],"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":[0.0000034015054,0.00006994523,0.0004083576,0.000011049492,0.00004376626,0.000003466005,0.00057346513,0.97729754,0.013852916,0.0006034209,0.000036266676,0.0070964117],"study_design_scores_gemma":[0.00022650648,0.00003500423,0.017543213,0.000087700064,0.000004385409,0.000025998599,0.000091107766,0.9780676,0.0035749774,0.00022978884,0.000038553728,0.00007518408],"about_ca_topic_score_codex":0.000018081013,"about_ca_topic_score_gemma":0.0000015630638,"teacher_disagreement_score":0.70640075,"about_ca_system_score_codex":0.000053906264,"about_ca_system_score_gemma":0.000011073327,"threshold_uncertainty_score":0.28762662},"labels":[],"label_agreement":null},{"id":"W1973850740","doi":"10.2316/journal.206.2015.1.206-3971","title":"DGPS-BASED LOCALIZATION AND PATH FOLLOWING APPROACH FOR OUTDOOR WHEELED MOBILE ROBOTS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Mobile robot; Computer science; Path (computing); Robot; Global Positioning System; Artificial intelligence; Real-time computing; Computer vision; Computer network; Telecommunications","score_opus":0.010747829197849168,"score_gpt":0.2602641367266767,"score_spread":0.24951630752882753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973850740","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005710562,0.00010022057,0.99277896,0.00047896846,0.00072140456,0.00013530285,0.0000016294795,0.00003460141,0.00003834044],"genre_scores_gemma":[0.48151252,0.0000067079104,0.5182073,0.00013271102,0.00011046714,0.0000046539617,0.000010047023,0.000006138901,0.000009443015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988999,0.00005359667,0.00037906895,0.0001620107,0.00038944246,0.000115978284],"domain_scores_gemma":[0.9989478,0.00016495945,0.00037563522,0.00009627708,0.0003419029,0.00007341518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006546326,0.00010641089,0.00017754002,0.00018778448,0.000083135,0.00026831415,0.0003038618,0.0000580307,4.1405366e-7],"category_scores_gemma":[0.000170082,0.00009421366,0.00006920855,0.00008276083,0.00001996943,0.00046537086,0.00004626788,0.0000761603,4.5613663e-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":[0.000009242615,0.00006111425,0.0017114017,0.000021803387,0.000050767285,0.000004373171,0.00025141882,0.9594523,0.00023113324,0.004600958,0.00008663639,0.033518903],"study_design_scores_gemma":[0.0009978105,0.0001790314,0.0018713097,0.000083687235,0.000020766209,0.000045760495,0.000019651292,0.99503404,0.00016624777,0.001358775,0.000121155805,0.00010178184],"about_ca_topic_score_codex":0.00000235095,"about_ca_topic_score_gemma":1.1611475e-7,"teacher_disagreement_score":0.47580194,"about_ca_system_score_codex":0.00004226546,"about_ca_system_score_gemma":0.000048047805,"threshold_uncertainty_score":0.38419217},"labels":[],"label_agreement":null},{"id":"W1973919856","doi":"10.2316/journal.206.2012.4.206-3780","title":"SYNCHRONIZED TRIGONOMETRIC S-CURVE TRAJECTORY FOR JERK-BOUNDED TIME-OPTIMAL PICK AND PLACE OPERATION","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Jerk; Bounded function; Trigonometry; Trajectory; Trigonometric functions; Mathematics; Computer science; Control theory (sociology); Mathematical analysis; Artificial intelligence; Geometry; Physics; Acceleration; Classical mechanics","score_opus":0.008603801811350871,"score_gpt":0.22992552160587684,"score_spread":0.22132171979452597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973919856","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":[0.19902353,0.00048606985,0.7992303,0.000143777,0.00089603406,0.00010971667,0.0000085681595,0.000026753089,0.000075279546],"genre_scores_gemma":[0.7888906,0.00015422898,0.2105022,0.000020902795,0.00033229933,0.0000029751986,0.000020020821,0.000016273088,0.000060487248],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992945,0.000015618076,0.0003353942,0.00005738685,0.0001823682,0.00011469313],"domain_scores_gemma":[0.99948955,0.00012268742,0.00012640348,0.000037449343,0.00014734389,0.000076596305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035726037,0.00009484873,0.00015037307,0.00023503286,0.000042370313,0.00011248471,0.00007444287,0.00006095002,0.000020007297],"category_scores_gemma":[0.000069686255,0.000087387976,0.000044838784,0.000057321125,0.000014331825,0.00045346242,0.000013579057,0.000079008736,0.0000026519892],"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":[0.000039826056,0.000047483307,0.00019542304,0.00003652075,0.00014985689,0.0000011120039,0.00033316787,0.97968954,0.00231342,0.0069509265,0.00018741409,0.010055317],"study_design_scores_gemma":[0.0009784128,0.000085683525,0.0018910291,0.000031199303,0.000040075403,0.00007503544,0.000040017614,0.99609596,0.0001946006,0.00031200543,0.00015345198,0.00010253863],"about_ca_topic_score_codex":8.984045e-7,"about_ca_topic_score_gemma":8.716605e-7,"teacher_disagreement_score":0.58986706,"about_ca_system_score_codex":0.000104035826,"about_ca_system_score_gemma":0.000024208479,"threshold_uncertainty_score":0.3563578},"labels":[],"label_agreement":null},{"id":"W1976060146","doi":"10.2316/journal.206.2011.4.206-3519","title":"SYNCHRONIZATION CONTROL OF A PARALLEL MANIPULATOR WITH REDUNDANT ACTUATION IN THE TASK SPACE","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Electric Power Systems and Control","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Synchronization (alternating current); Task (project management); Computer science; Control (management); Parallel manipulator; Space (punctuation); Control theory (sociology); Engineering; Artificial intelligence; Robot; Computer network; Operating system","score_opus":0.007273159836706879,"score_gpt":0.19249418711708677,"score_spread":0.1852210272803799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976060146","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":[0.12751794,0.00033858165,0.87129813,0.0002622749,0.00023667641,0.00010639755,0.0000016538993,0.000009177191,0.0002291619],"genre_scores_gemma":[0.99836653,0.00006569587,0.0014769074,0.000019663215,0.00005716749,0.0000020955092,0.0000016605828,0.000005859954,0.0000044381236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993696,0.00002195944,0.00028596979,0.000035824614,0.00023116777,0.0000554801],"domain_scores_gemma":[0.99954396,0.00003388016,0.00019884389,0.000043346703,0.00016503553,0.000014951122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002257557,0.00005690036,0.000105174586,0.00011840444,0.000010980475,0.000024103228,0.00010498386,0.000027539489,0.0000035424894],"category_scores_gemma":[0.00001857983,0.00003755019,0.00002176749,0.00007012962,0.000011312,0.00017168283,0.0000027886763,0.000068258734,4.1823535e-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":[0.0003449832,0.00026698623,0.018346556,0.00010795132,0.0007400388,0.00008975549,0.009775865,0.86109734,0.0077215782,0.052278593,0.00027688858,0.048953477],"study_design_scores_gemma":[0.0018979656,0.0002299198,0.06764852,0.00019632673,0.000051998035,0.0002237513,0.00021309979,0.9280252,0.00027331195,0.0010457899,0.000098740464,0.00009536175],"about_ca_topic_score_codex":0.00001654102,"about_ca_topic_score_gemma":0.000014526937,"teacher_disagreement_score":0.87084854,"about_ca_system_score_codex":0.000038725604,"about_ca_system_score_gemma":0.000022762091,"threshold_uncertainty_score":0.15312524},"labels":[],"label_agreement":null},{"id":"W1976486555","doi":"10.2316/journal.206.2005.3.206-2559","title":"Fitted Stratified Manipulation with Decomposed Path Planning on Submanifolds","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Computer science; Motion planning; Mathematics; Artificial intelligence; Programming language; Robot","score_opus":0.01635721014134598,"score_gpt":0.2525508890633339,"score_spread":0.23619367892198792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976486555","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":[0.7021932,0.00007406005,0.29543447,0.0006245469,0.00039685395,0.00006584347,5.553848e-7,0.00008452283,0.0011259541],"genre_scores_gemma":[0.98908156,0.000017448003,0.010503413,0.00007355951,0.00026860324,5.664905e-7,0.000014453261,0.0000145103695,0.000025886755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923074,0.000016754335,0.0003062495,0.000061567305,0.00030765156,0.000077051765],"domain_scores_gemma":[0.9995568,0.000043614247,0.00016481112,0.000043234995,0.00014757285,0.000044007444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000120864526,0.00009355937,0.00010267369,0.00019281638,0.000038757393,0.000110509405,0.00008223118,0.000042742708,0.000024899675],"category_scores_gemma":[0.000013863326,0.000080269136,0.000027299566,0.000055289245,0.00000835557,0.0003126505,0.000005752384,0.0001385771,0.000005588483],"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":[0.000028782528,0.00001741122,0.0016925666,0.000005766546,0.000054021944,0.000012219127,0.00027849062,0.9865138,0.00094508566,0.0018742008,0.00013738182,0.008440283],"study_design_scores_gemma":[0.00062775094,0.00008554533,0.07785361,0.00013355272,0.000013202017,0.00007894784,0.000062844454,0.9202026,0.00037847046,0.00010374666,0.000363333,0.00009637795],"about_ca_topic_score_codex":8.659999e-7,"about_ca_topic_score_gemma":0.0000019230258,"teacher_disagreement_score":0.2868884,"about_ca_system_score_codex":0.0000684794,"about_ca_system_score_gemma":0.000011719897,"threshold_uncertainty_score":0.32732803},"labels":[],"label_agreement":null},{"id":"W1976997124","doi":"10.2316/journal.206.2011.1.206-3379","title":"INFORMATION SURFING FOR RADIATION MAP BUILDING","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"U.S. Department of Energy","keywords":"Computer science; Situation awareness; Metric (unit); Mobile robot; Process (computing); Real-time computing; SIGNAL (programming language); Planar; Wireless sensor network; Human–computer interaction; Computer vision; Robot; Artificial intelligence; Computer network; Engineering; Computer graphics (images)","score_opus":0.018385583727572364,"score_gpt":0.25205020487683355,"score_spread":0.23366462114926118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976997124","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":[0.008291496,0.000062230756,0.9886093,0.0009863235,0.0018358186,0.00010242378,0.0000059412423,0.000026476742,0.000079995545],"genre_scores_gemma":[0.8803398,0.000014860398,0.119409256,0.00008383532,0.00013055823,0.0000025885606,0.000009257888,0.0000028241034,0.000007007049],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990936,0.000029097608,0.0004551643,0.000051057697,0.00028775207,0.000083343904],"domain_scores_gemma":[0.99858093,0.000082752296,0.0006154486,0.0000666744,0.0006113767,0.000042828586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005973583,0.000064788306,0.00009835204,0.00021905618,0.000044976816,0.00023240736,0.00034374508,0.0000372176,0.0000021090514],"category_scores_gemma":[0.00016287676,0.000060262886,0.000054262924,0.000058484577,0.0000082844435,0.0021878327,0.000036197565,0.00004927841,0.0000033886497],"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":[0.00010220054,0.00011820573,0.0030241099,0.00006736842,0.00033235946,0.000009241024,0.0047111297,0.030847182,0.0023520824,0.53243876,0.0014684888,0.42452887],"study_design_scores_gemma":[0.0014540326,0.00011102039,0.016540488,0.00010395409,0.000020038013,0.0000812696,0.00008544139,0.967886,0.0015132175,0.008144544,0.003930321,0.0001296995],"about_ca_topic_score_codex":0.000008153565,"about_ca_topic_score_gemma":4.9272137e-7,"teacher_disagreement_score":0.9370388,"about_ca_system_score_codex":0.00007103555,"about_ca_system_score_gemma":0.000041267285,"threshold_uncertainty_score":0.24574493},"labels":[],"label_agreement":null},{"id":"W1977206137","doi":"10.2316/journal.206.2011.1.206-3384","title":"COOPERATIVE ATTITUDE SYNCHRONIZATION FOR RIGID-BODY SPACECRAFT &lt;em&gt;VIA&lt;/em&gt; VARYING COMMUNICATION TOPOLOGY","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Backstepping; Control theory (sociology); Synchronization (alternating current); Quaternion; Piecewise; Nonlinear system; Stability theory; Lyapunov function; Topology (electrical circuits); Lyapunov stability; Spacecraft; Mathematics; Stability (learning theory); Computer science; Control (management); Adaptive control; Engineering; Physics; Mathematical analysis","score_opus":0.021562792328747006,"score_gpt":0.2723593289366953,"score_spread":0.25079653660794826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977206137","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":[0.012534155,0.0003404435,0.9839967,0.0014954393,0.0010746367,0.00028734523,0.000013956736,0.000052438623,0.00020489334],"genre_scores_gemma":[0.92390287,0.00010214476,0.075559326,0.00013223576,0.00017028429,0.000011904592,0.000046427962,0.0000122645,0.00006257338],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828726,0.00015806808,0.00070630404,0.00020199132,0.00046506262,0.00018133012],"domain_scores_gemma":[0.99700236,0.00019918614,0.0008910223,0.00021738,0.0016019034,0.00008811977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068085035,0.00016673225,0.00026185688,0.00026482204,0.00016891187,0.00031511227,0.0008489631,0.00010584494,0.000016359278],"category_scores_gemma":[0.0002083767,0.00015612315,0.000092445676,0.00014874729,0.00004932512,0.0011687558,0.00014391226,0.0001360595,0.000009857498],"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":[0.0003446695,0.0013727383,0.0030079358,0.00013825136,0.0019070765,0.0000879813,0.014291842,0.14341584,0.037351783,0.71130025,0.0025935175,0.08418811],"study_design_scores_gemma":[0.0018384043,0.00021754371,0.0069227065,0.00015328031,0.000056545705,0.00018370342,0.00007662871,0.9843103,0.001250684,0.004034121,0.0007520616,0.00020400752],"about_ca_topic_score_codex":0.000013657148,"about_ca_topic_score_gemma":0.000028815884,"teacher_disagreement_score":0.91136867,"about_ca_system_score_codex":0.00019984595,"about_ca_system_score_gemma":0.000108395834,"threshold_uncertainty_score":0.6366517},"labels":[],"label_agreement":null},{"id":"W1977805544","doi":"10.2316/journal.206.2008.1.206-2970","title":"AN AUTOMATIC BI-CHANNEL COMPRESSION TECHNIQUE FOR MEDICAL IMAGES","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Channel (broadcasting); Computer vision; Compression (physics); Artificial intelligence; Materials science; Computer network; Composite material","score_opus":0.02311617149244193,"score_gpt":0.32728090693707623,"score_spread":0.3041647354446343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977805544","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":[0.0071513583,0.00009729997,0.9899942,0.0019492466,0.00063323556,0.0000909624,0.0000016965977,0.00003998205,0.00004200649],"genre_scores_gemma":[0.5316142,0.00006928903,0.46792203,0.00018820545,0.00017793276,0.000003132288,0.0000026924495,0.000005383808,0.000017180782],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986961,0.00009154565,0.0004059029,0.000109411245,0.0006015628,0.00009549108],"domain_scores_gemma":[0.9987511,0.00019238214,0.0003037019,0.00010207054,0.0005498272,0.000100929254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008403947,0.0000835518,0.0001506946,0.00022486184,0.00010196487,0.00012747828,0.0005935272,0.000067726854,0.0000058542787],"category_scores_gemma":[0.00022001045,0.000067006724,0.00006347499,0.00007295842,0.000045181056,0.0008032802,0.00006113034,0.000112612375,9.5286e-7],"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":[0.00020008572,0.0014669826,0.0008130217,0.0001827294,0.00040639454,0.001265546,0.0040280367,0.04960351,0.22439183,0.040622637,0.0090524675,0.6679668],"study_design_scores_gemma":[0.00097204396,0.00025808805,0.0029467393,0.0002002686,0.0000093627805,0.0021349925,0.000011976262,0.95761544,0.02133119,0.014266489,0.00013822629,0.00011518458],"about_ca_topic_score_codex":0.0000031718123,"about_ca_topic_score_gemma":1.9691707e-7,"teacher_disagreement_score":0.9080119,"about_ca_system_score_codex":0.000028626293,"about_ca_system_score_gemma":0.00010678082,"threshold_uncertainty_score":0.27324548},"labels":[],"label_agreement":null},{"id":"W1978092224","doi":"10.2316/journal.206.2008.4.206-3124","title":"A NEW APPROACH FOR AN AUTOMATED INSPECTION SYSTEM OF THE MANUFACTURED PARTS","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Automated X-ray inspection; Engineering drawing; Manufacturing engineering; Reliability engineering; Engineering; Artificial intelligence; Image processing","score_opus":0.01570365264414469,"score_gpt":0.23744281173784934,"score_spread":0.22173915909370465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978092224","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":[0.08246097,0.00006034335,0.9160054,0.00007212227,0.0007993779,0.000119857024,0.0000048726683,0.00024758527,0.00022952682],"genre_scores_gemma":[0.95980436,0.0000354318,0.039979294,0.0000066978228,0.0001399304,0.0000013706823,0.000009325238,0.000008956283,0.000014656892],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941844,0.000010867947,0.00027638633,0.000048453356,0.00019629546,0.000049550148],"domain_scores_gemma":[0.9995189,0.000013951455,0.00020192083,0.000051448736,0.00018196498,0.000031853273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000090967296,0.00006311151,0.000099773395,0.000087933666,0.00004888248,0.000028372453,0.00012008859,0.0000436043,0.0000010722331],"category_scores_gemma":[0.000014381089,0.000046217356,0.000043528828,0.000041122355,0.000012373235,0.0002102352,0.000008744629,0.00005158005,1.4733291e-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":[0.0000126795085,0.00001423646,0.00014096883,0.000058200396,0.000045938155,4.410187e-7,0.00030045747,0.99643964,0.0002172019,0.00048026108,0.0009138927,0.0013760899],"study_design_scores_gemma":[0.00039381045,0.000029330275,0.00805175,0.000050903996,0.000018781597,0.00013219661,0.000043319636,0.9863471,0.00474743,0.00005768975,0.00008022598,0.00004747883],"about_ca_topic_score_codex":0.0000060495554,"about_ca_topic_score_gemma":0.0000011192305,"teacher_disagreement_score":0.87734336,"about_ca_system_score_codex":0.00004886055,"about_ca_system_score_gemma":0.000026255746,"threshold_uncertainty_score":0.1884689},"labels":[],"label_agreement":null},{"id":"W1978330498","doi":"10.2316/journal.206.2006.2.206-2791","title":"PHYSICAL ROBOT AGENTS: COORDINATED INTELLIGENT AND RATIONAL AGENTS FOR COLLABORATIVE ROBOTS","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Robot; Computer science; Human–computer interaction; Artificial intelligence","score_opus":0.021139501539043974,"score_gpt":0.2969094722501553,"score_spread":0.2757699707111113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978330498","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":[0.020317076,0.00011391216,0.97477585,0.0036023126,0.00090817595,0.00015983879,0.000012474424,0.000028316344,0.00008206162],"genre_scores_gemma":[0.6886605,0.000032832868,0.31059113,0.00013530687,0.00039391135,0.000005670658,0.000030318866,0.000009605587,0.00014068131],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873155,0.000050821767,0.00044266993,0.00018119722,0.00045857456,0.00013517537],"domain_scores_gemma":[0.9981206,0.0001942172,0.00048157186,0.00007881168,0.0010534743,0.00007131957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002955172,0.00013574172,0.0001992524,0.00021104989,0.00009522311,0.00031657264,0.00032831111,0.000049749247,0.0000020381058],"category_scores_gemma":[0.00011325599,0.00012203898,0.000056733683,0.0001536934,0.000048448725,0.0006423535,0.00008619301,0.00009918315,0.0000019537101],"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":[0.00004008806,0.00030764967,0.0013455924,0.000017835791,0.00020392165,0.00004903838,0.00080880953,0.87940174,0.0014140543,0.08901136,0.0037462604,0.023653666],"study_design_scores_gemma":[0.00088326103,0.00017351404,0.016741684,0.000078940335,0.00002345129,0.00012986407,0.000044332115,0.9691968,0.00092677993,0.0112391915,0.0004253528,0.0001368165],"about_ca_topic_score_codex":0.000007297111,"about_ca_topic_score_gemma":0.000001086987,"teacher_disagreement_score":0.6683435,"about_ca_system_score_codex":0.00008707689,"about_ca_system_score_gemma":0.00008894142,"threshold_uncertainty_score":0.49766052},"labels":[],"label_agreement":null},{"id":"W1978498250","doi":"10.2316/journal.206.2011.3.206-3440","title":"APPLYING WAVE-VARIABLE-BASED SLIDING MODE IMPEDANCE CONTROL FOR ROBOT TELEOPERATION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Teleoperation; Control theory (sociology); Mode (computer interface); Impedance control; Computer science; Electrical impedance; Variable (mathematics); Sliding mode control; Robot; Control (management); Engineering; Mathematics; Physics; Artificial intelligence; Electrical engineering; Mathematical analysis; Human–computer interaction","score_opus":0.02548275765012957,"score_gpt":0.24285172262893948,"score_spread":0.21736896497880992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978498250","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":[0.014991959,0.000108136,0.9829862,0.00011429709,0.0011952709,0.0002313631,0.000009794617,0.000051009225,0.00031198293],"genre_scores_gemma":[0.9242748,0.000020785683,0.07527516,0.00008950373,0.00027695537,0.000024756308,0.000008889522,0.000014910448,0.000014236804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917424,0.00001681939,0.00044050015,0.00006837228,0.00020652557,0.00009354247],"domain_scores_gemma":[0.999272,0.00006875676,0.00015885425,0.000049410275,0.00040308223,0.000047917158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002594423,0.00009500247,0.00015043681,0.00014777837,0.00005111387,0.000106229236,0.00009156581,0.00005461055,0.000016240816],"category_scores_gemma":[0.000058584923,0.000088005094,0.000049977443,0.000043674852,0.000008341191,0.00031459008,0.0000047012704,0.00007165888,0.0000014864721],"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":[0.000044346878,0.000029993646,0.0003449757,0.000042552176,0.0001225105,0.0000037293405,0.0003819005,0.94236124,0.021394033,0.020934457,0.00012549735,0.014214747],"study_design_scores_gemma":[0.0012153328,0.000051700663,0.00064275024,0.00009605892,0.000026793161,0.000047830305,0.000057767276,0.99405843,0.002892026,0.00042809156,0.00038590241,0.00009728984],"about_ca_topic_score_codex":0.000005564123,"about_ca_topic_score_gemma":0.0000032919404,"teacher_disagreement_score":0.90928286,"about_ca_system_score_codex":0.0000682341,"about_ca_system_score_gemma":0.000037248443,"threshold_uncertainty_score":0.35887438},"labels":[],"label_agreement":null},{"id":"W1979014032","doi":"10.2316/journal.206.2004.3.206-2728","title":"Position Analysis of a Class of Translational Parallel Mechanisms","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Class (philosophy); Position (finance); Kinematics; Tetrahedron; Translational symmetry; Computer science; Symmetry (geometry); Algorithm; Topology (electrical circuits); Theoretical computer science; Mathematics; Geometry; Artificial intelligence; Classical mechanics; Combinatorics; Physics","score_opus":0.0065013497189638034,"score_gpt":0.2249589200684146,"score_spread":0.2184575703494508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979014032","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":[0.050238483,0.00007256461,0.9489712,0.00030966074,0.0002612261,0.00003217631,0.000016733782,0.000009622966,0.00008829097],"genre_scores_gemma":[0.74656844,0.00007591177,0.25329596,0.00001106889,0.00002118422,3.042041e-7,0.000020185844,0.000005005625,0.0000019554507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990468,0.000009078533,0.0004941957,0.00004593289,0.00035138134,0.000052630323],"domain_scores_gemma":[0.99933887,0.00003053889,0.00025530608,0.0000440633,0.00029899844,0.00003222543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014893862,0.00006767459,0.00020115048,0.0004066976,0.000011294734,0.000015484198,0.00009678091,0.000051297266,0.0000142557],"category_scores_gemma":[0.000011809244,0.00006379547,0.00011747517,0.00016413817,0.000016310725,0.00015687359,0.00000706008,0.000059305963,2.7379517e-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":[0.000010735408,0.000030416897,0.000051352446,0.0000114308,0.0005094283,0.000002463092,0.00015120872,0.77933043,0.0060626282,0.2127141,0.0000014335344,0.0011243834],"study_design_scores_gemma":[0.00060731074,0.000073792486,0.0072999424,0.00006921508,0.00031305262,0.000026314567,0.000035191762,0.92685485,0.0011782483,0.06347467,0.0000027359374,0.00006467078],"about_ca_topic_score_codex":0.0000049888363,"about_ca_topic_score_gemma":0.0000060587513,"teacher_disagreement_score":0.69632995,"about_ca_system_score_codex":0.00003676243,"about_ca_system_score_gemma":0.000026441545,"threshold_uncertainty_score":0.26015037},"labels":[],"label_agreement":null},{"id":"W1979845727","doi":"10.2316/journal.206.2013.2.206-3928","title":"MOTION SYNTHESIS FOR A DIGITAL PREGNANT WOMAN MULTIBODY SYSTEM","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion (physics); Computer science; Multibody system; Computer vision; Physics; Classical mechanics","score_opus":0.005718129725832672,"score_gpt":0.2123717386153493,"score_spread":0.20665360888951664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979845727","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":[0.20637587,0.0002383698,0.79003435,0.0010516397,0.0015807746,0.00034798423,0.000028571396,0.00009835888,0.00024410554],"genre_scores_gemma":[0.9832254,0.000037188034,0.01655797,0.0000090879785,0.00012009888,0.000012003074,0.0000066204716,0.0000140686425,0.000017555374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992952,0.000007811331,0.0003618665,0.000055988858,0.00019820417,0.00008095727],"domain_scores_gemma":[0.9991739,0.00012378437,0.00014012115,0.000047881782,0.00046255684,0.000051778043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104562896,0.000080465776,0.000117503725,0.00013835228,0.000029893326,0.00020214406,0.00010470909,0.000045841272,0.000004273095],"category_scores_gemma":[0.000096241594,0.00006629888,0.00006734022,0.00003270384,0.00001901232,0.00038389137,0.00001258343,0.000051175553,0.000005781906],"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":[0.000013044999,0.00010276093,0.0009769474,0.0002971835,0.00027200967,0.0000045429847,0.0005129939,0.8332507,0.004802329,0.009138492,0.00055421673,0.15007477],"study_design_scores_gemma":[0.00033290253,0.00005640043,0.004834879,0.0003184976,0.000021615399,0.00006475244,0.00020601184,0.99232036,0.00070289354,0.00089429284,0.00015442572,0.000092948976],"about_ca_topic_score_codex":0.0000011485131,"about_ca_topic_score_gemma":2.1167448e-7,"teacher_disagreement_score":0.77684957,"about_ca_system_score_codex":0.00008174735,"about_ca_system_score_gemma":0.000010135082,"threshold_uncertainty_score":0.27035898},"labels":[],"label_agreement":null},{"id":"W1979953055","doi":"10.2316/journal.206.2007.4.206-3059","title":"AN ART GALLERY-BASED APPROACH: ROADMAP CONSTRUCTION AND PATH PLANNING IN GLOBAL ENVIRONMENTS","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Plan (archaeology); Computer science; Path (computing); Robot; Artificial intelligence; Computer vision; Mathematical optimization; Geography; Mathematics; Programming language; Archaeology","score_opus":0.013694953221485902,"score_gpt":0.271157602140425,"score_spread":0.2574626489189391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979953055","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":[0.07826128,0.00004386236,0.92083555,0.00024696314,0.00041815528,0.00004024392,0.0000014352662,0.00001366045,0.00013881655],"genre_scores_gemma":[0.5482858,0.000006467418,0.45158663,0.000057194888,0.000054975902,2.5219393e-7,0.0000040309947,0.0000022234033,0.00000244067],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989276,0.000039694954,0.00036902603,0.00013947814,0.00040848932,0.00011574089],"domain_scores_gemma":[0.99943,0.00005243298,0.00031046043,0.00007567363,0.000060185586,0.00007127027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006346234,0.00008735049,0.000115992734,0.00018646501,0.000034922054,0.00014484827,0.0002370346,0.00005481046,7.522274e-7],"category_scores_gemma":[0.000038625487,0.00008349317,0.000020809697,0.00008608162,0.000040220573,0.00056775776,0.00003471659,0.00011058333,9.1451875e-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":[0.00003466305,0.00017719087,0.10012599,0.000008411086,0.00003979575,0.00017533173,0.00049213174,0.8262566,0.0006274053,0.0055159125,0.00004814262,0.066498436],"study_design_scores_gemma":[0.00055782776,0.000090684574,0.18684493,0.00008906864,0.0000044844573,0.00043783255,0.00007957553,0.8106226,0.00005716129,0.0010801984,0.000053369225,0.00008227705],"about_ca_topic_score_codex":0.0000028033992,"about_ca_topic_score_gemma":2.879737e-7,"teacher_disagreement_score":0.4700245,"about_ca_system_score_codex":0.000101637386,"about_ca_system_score_gemma":0.0000379623,"threshold_uncertainty_score":0.34047526},"labels":[],"label_agreement":null},{"id":"W1980221990","doi":"10.2316/journal.206.2010.2.206-3281","title":"A NOVEL AUTONOMOUS LOCALIZATION TECHNIQUE OF SUBSEA IN-PIPE ROBOT","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Subsea; Robot; Marine engineering; Computer science; Artificial intelligence; Engineering","score_opus":0.011149726839187026,"score_gpt":0.2632213375001877,"score_spread":0.2520716106610007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980221990","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":[0.011478943,0.000024330624,0.9865071,0.0008256604,0.0009859145,0.00007712354,0.0000017051535,0.00002175919,0.00007743596],"genre_scores_gemma":[0.5733044,0.000009143545,0.42658785,0.000031257245,0.00005512378,0.0000011710538,0.0000018449293,0.0000038112742,0.000005357113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882376,0.000023475905,0.0005429436,0.00011252568,0.00040227463,0.000094993135],"domain_scores_gemma":[0.9986925,0.00008227462,0.0005489463,0.000121517456,0.0005061364,0.000048601836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005524518,0.00008580316,0.00016014479,0.0004121055,0.00002226117,0.00008558067,0.0005196064,0.00007904398,0.000002290323],"category_scores_gemma":[0.00017062038,0.00008019441,0.00004205838,0.00019188249,0.00003831274,0.00052342087,0.00008049315,0.0002130572,8.630111e-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":[0.000018272323,0.00038548472,0.01063569,0.000030758976,0.00006944503,0.0000750742,0.0010209532,0.68752486,0.20177887,0.052763455,0.000047304944,0.045649808],"study_design_scores_gemma":[0.0005191151,0.000077622724,0.032404613,0.00012511692,0.000006145045,0.0005644822,0.000012065872,0.9537073,0.009703196,0.0027366304,0.00004919785,0.00009456389],"about_ca_topic_score_codex":0.00001989382,"about_ca_topic_score_gemma":0.000004704067,"teacher_disagreement_score":0.5618255,"about_ca_system_score_codex":0.000042504507,"about_ca_system_score_gemma":0.00011829099,"threshold_uncertainty_score":0.32702333},"labels":[],"label_agreement":null},{"id":"W1981302373","doi":"10.2316/journal.206.2012.3.206-3558","title":"PHYSICAL HUMAN–ROBOT INTERACTION BY OBSERVING ACTUATOR CURRENTS","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Actuator; Robot; Computer science; Human–computer interaction; Artificial intelligence","score_opus":0.016991539995863184,"score_gpt":0.28511617126364075,"score_spread":0.2681246312677776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981302373","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":[0.9502826,0.00041132557,0.044781473,0.00017339144,0.0039318353,0.00005783075,0.0000074857103,0.00007891243,0.00027516566],"genre_scores_gemma":[0.99773496,0.00007247037,0.0013940841,0.000017902303,0.00072729477,0.0000011017006,0.000017410519,0.000018326615,0.000016453554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990866,0.000020980262,0.00037192667,0.000054085343,0.00032849758,0.00013790473],"domain_scores_gemma":[0.99945116,0.000039608636,0.0002074914,0.00005432614,0.00015699766,0.00009041069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016282605,0.00011436003,0.00015913257,0.00012400367,0.000041979372,0.00011859285,0.00014512018,0.000047500493,0.0000096151325],"category_scores_gemma":[0.000022457072,0.00010354797,0.00006501171,0.00005334654,0.000012735295,0.0006821529,0.000025383839,0.00015555293,0.000010253486],"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":[0.000019667163,0.0006358023,0.0134345675,0.00017538233,0.00088972686,0.00001368699,0.003064328,0.58824134,0.32607514,0.0047471435,0.010573491,0.05212975],"study_design_scores_gemma":[0.0008258089,0.00007793634,0.011980789,0.00039684176,0.00007170892,0.00020338385,0.0002845823,0.9714425,0.011181557,0.0003982351,0.0028188971,0.00031776406],"about_ca_topic_score_codex":0.0000028407412,"about_ca_topic_score_gemma":2.8149464e-7,"teacher_disagreement_score":0.38320118,"about_ca_system_score_codex":0.00009829596,"about_ca_system_score_gemma":0.0000065097306,"threshold_uncertainty_score":0.42225638},"labels":[],"label_agreement":null},{"id":"W1981558234","doi":"10.2316/journal.206.2014.4.206-3984","title":"UPPER LIMB MOTOR REHABILITATION INTEGRATED WITH VIDEO GAMES FOCUSING ON TRAINING FINGERS’ FINE MOVEMENTS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Physical medicine and rehabilitation; Rehabilitation; Movement (music); Upper limb; Robot; Computer science; Training (meteorology); Psychology; Medicine; Physical therapy; Artificial intelligence; Physics","score_opus":0.012020603610508608,"score_gpt":0.268624357375322,"score_spread":0.25660375376481337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981558234","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":[0.9595362,0.000040351573,0.0339991,0.005398019,0.00056064385,0.00012773197,0.0000033848398,0.000019979943,0.00031456482],"genre_scores_gemma":[0.95573336,0.000019009636,0.043403786,0.00038541228,0.00027119406,0.0000022202344,0.000013602791,0.000012650174,0.00015875489],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99886906,0.0000509238,0.00040620624,0.00011223943,0.0004727382,0.00008885149],"domain_scores_gemma":[0.9984481,0.00045691401,0.00033541428,0.00006561167,0.0006218476,0.000072142815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036323714,0.0001056093,0.00020536219,0.00041741444,0.000035265406,0.00006180925,0.00005763788,0.000052069965,0.000028030261],"category_scores_gemma":[0.00087762607,0.00007429095,0.00009764314,0.00008117694,0.000048453883,0.00020576749,0.000009294314,0.00014835331,0.000002970152],"study_design_candidate":"observational","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":[0.0040291008,0.0009993148,0.13584732,0.00022841997,0.0011012742,0.00004040289,0.006809675,0.044200543,0.03447471,0.006873737,0.0010557114,0.7643398],"study_design_scores_gemma":[0.0059728445,0.008733414,0.83501524,0.0031513572,0.00013230972,0.00028796186,0.0017752871,0.13788715,0.0013398277,0.001493942,0.0039449073,0.00026575133],"about_ca_topic_score_codex":0.000004663779,"about_ca_topic_score_gemma":0.0000023942844,"teacher_disagreement_score":0.764074,"about_ca_system_score_codex":0.00011874869,"about_ca_system_score_gemma":0.00007064398,"threshold_uncertainty_score":0.3029497},"labels":[],"label_agreement":null},{"id":"W1982974016","doi":"10.2316/journal.206.2011.1.206-3376","title":"GLOBAL ROBUST STABILIZATION FOR A CLASS OF TIME-VARYING OUTPUT FEEDBACK SYSTEMS","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Class (philosophy); Output feedback; Computer science; Artificial intelligence; Control (management)","score_opus":0.025165810970967525,"score_gpt":0.22809379451297607,"score_spread":0.20292798354200853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982974016","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":[0.12662312,0.00059051794,0.86952406,0.00006128654,0.001744894,0.00014572871,0.000032678538,0.00008098626,0.0011967052],"genre_scores_gemma":[0.98964536,0.000062137486,0.010191789,0.0000025784998,0.00006827252,0.000001926868,0.000004819016,0.000007440239,0.000015684394],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931294,0.000008119321,0.00039615575,0.000046615667,0.00017054444,0.000065609376],"domain_scores_gemma":[0.99930185,0.000025755508,0.00024026821,0.000048221154,0.00036239056,0.000021538579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001556204,0.00006758702,0.00014309278,0.00010776818,0.000014330632,0.00003489727,0.00012884248,0.00006114955,0.0000028099448],"category_scores_gemma":[0.000048784623,0.000060199447,0.000044522043,0.000057491052,0.000017836768,0.00020656151,0.000016429638,0.00003471565,8.399862e-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":[0.0000326397,0.00005196369,0.0037295467,0.00018278768,0.00028815045,0.0000052140135,0.00034583997,0.96936595,0.0012093661,0.015244376,0.0006733419,0.008870797],"study_design_scores_gemma":[0.0005711943,0.00010433407,0.004032196,0.00027694198,0.00003190092,0.00011425833,0.00014579137,0.9922593,0.0007731853,0.0013062186,0.00028777937,0.000096855045],"about_ca_topic_score_codex":0.000008651392,"about_ca_topic_score_gemma":0.0000014867605,"teacher_disagreement_score":0.8630222,"about_ca_system_score_codex":0.000070961745,"about_ca_system_score_gemma":0.00001573992,"threshold_uncertainty_score":0.24548623},"labels":[],"label_agreement":null},{"id":"W1983745170","doi":"10.2316/journal.206.2011.2.206-3350","title":"POSITION-SINGULARITY ANALYSIS OF 6-3 STEWART-GOUGH PARALLEL MANIPULATORS FOR SPECIAL ORIENTATIONS","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Position (finance); Singularity; Control theory (sociology); Mathematics; Computer science; Mathematical analysis; Artificial intelligence; Economics","score_opus":0.020634595350291714,"score_gpt":0.2493280620028839,"score_spread":0.2286934666525922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983745170","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":[0.067427665,0.000024028377,0.9311833,0.00005349457,0.0009380281,0.000058330985,0.000021894753,0.000012429428,0.0002808474],"genre_scores_gemma":[0.6634441,0.00004155708,0.33624652,0.000013209006,0.00020168455,0.0000011084127,0.000033085824,0.000007747086,0.000010981463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992491,0.000008757626,0.00041898445,0.000053291667,0.0002054993,0.00006434522],"domain_scores_gemma":[0.99931455,0.000036525784,0.00021346298,0.000050120798,0.0003459898,0.000039350383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013273787,0.00006870836,0.0001694072,0.00031456666,0.000027601549,0.000028426046,0.00009773605,0.00004453127,0.00003506161],"category_scores_gemma":[0.000023433779,0.00006661371,0.00012044872,0.00012689734,0.000016135571,0.00018195846,0.000010481755,0.00004898962,4.0204907e-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":[0.000022697477,0.00005292656,0.0011477642,0.000013834228,0.00087393564,0.0000037015457,0.0006453948,0.82714975,0.00023910344,0.16797692,0.00005374193,0.0018202503],"study_design_scores_gemma":[0.00045333503,0.000077172146,0.033045933,0.000030563217,0.0005211131,0.000019511363,0.00012880811,0.94396967,0.00017677492,0.021460023,0.000025643276,0.00009142732],"about_ca_topic_score_codex":0.000006022698,"about_ca_topic_score_gemma":0.000012471978,"teacher_disagreement_score":0.5960164,"about_ca_system_score_codex":0.000042459647,"about_ca_system_score_gemma":0.000015828819,"threshold_uncertainty_score":0.27164283},"labels":[],"label_agreement":null},{"id":"W1984086509","doi":"10.2316/journal.206.2011.2.206-3373","title":"FINITE FLIESS FUNCTIONAL EXPANSION AND ITS APPLICATION TO FLIGHT CONTROL OF MISSILES","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Decoupling (probability); Control theory (sociology); Nonlinear system; Piecewise; Taylor series; Mathematics; Tracking error; Computer science; Control (management); Engineering; Mathematical analysis; Control engineering; Physics","score_opus":0.017506678000808622,"score_gpt":0.22473712175193541,"score_spread":0.20723044375112679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984086509","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":[0.1550128,0.0005541165,0.8433665,0.000254862,0.00052357034,0.00010994471,0.00001365613,0.00001951073,0.00014500652],"genre_scores_gemma":[0.99609447,0.000057028185,0.0036062193,0.000028796416,0.00018487855,0.0000025929894,0.0000035620028,0.000009152251,0.000013278196],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928135,0.000015174758,0.0003603457,0.000058581285,0.00022996376,0.000054597327],"domain_scores_gemma":[0.99920607,0.000067875946,0.00017868906,0.000038031947,0.00045168132,0.000057635698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015455153,0.00007466074,0.00014281787,0.00017107931,0.00001655735,0.000015712667,0.000078193625,0.00004090885,0.000009084724],"category_scores_gemma":[0.000054890777,0.000066898814,0.00003063072,0.00004142449,0.000010117704,0.00018942214,0.000012894819,0.000057878577,0.000003235014],"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":[0.00030031285,0.00012664175,0.0033177321,0.00010942494,0.0005451978,0.000015068934,0.0015793066,0.7804309,0.15170966,0.014777871,0.00021907684,0.04686877],"study_design_scores_gemma":[0.0008803525,0.00009832457,0.041145753,0.00013004086,0.000034056644,0.000055443954,0.00006212222,0.9518178,0.0047983467,0.0003472307,0.000534711,0.00009581415],"about_ca_topic_score_codex":0.0000021933984,"about_ca_topic_score_gemma":0.0000020112273,"teacher_disagreement_score":0.8410817,"about_ca_system_score_codex":0.000027002938,"about_ca_system_score_gemma":0.00001376918,"threshold_uncertainty_score":0.27280545},"labels":[],"label_agreement":null},{"id":"W1987502100","doi":"10.2316/journal.206.2014.4.206-3877","title":"DYNAMIC ANALYSIS OF FIXED GEOMETRY TRACKED ROBOTS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Robot; Geometry; Computer vision; Artificial intelligence; Mathematics","score_opus":0.003997653204405644,"score_gpt":0.21756088626042594,"score_spread":0.2135632330560203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987502100","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":[0.42106873,0.00010660781,0.5778564,0.00020742386,0.0005962353,0.000023687788,0.0000057317593,0.000014679099,0.00012049921],"genre_scores_gemma":[0.99592096,0.0000674153,0.003918993,0.000016596665,0.00004668865,3.6666827e-7,0.000009032943,0.0000068938466,0.000013070617],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991255,0.000018720757,0.00045498455,0.000047748432,0.00029080515,0.00006223909],"domain_scores_gemma":[0.9993717,0.00007695531,0.00023429378,0.000055073015,0.00021954019,0.000042456144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002996158,0.00006647233,0.00024106835,0.00039461232,0.000010537868,0.00003856269,0.00014349425,0.000046600442,0.000010305012],"category_scores_gemma":[0.00005214243,0.000058600326,0.00012239075,0.00017050895,0.000009734169,0.00010959763,0.000011479321,0.00007027425,8.996245e-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":[0.0000073692736,0.000021564249,0.00048671753,0.000012454992,0.00096489995,0.0000017198032,0.00003881417,0.96483374,0.006043955,0.004397326,0.000011393965,0.02318007],"study_design_scores_gemma":[0.00033381904,0.000038652026,0.025096964,0.00003643747,0.00020673824,0.000009147505,0.000012980563,0.9733383,0.000084752544,0.00072577636,0.00006174966,0.00005469694],"about_ca_topic_score_codex":0.0000036653917,"about_ca_topic_score_gemma":0.000009242249,"teacher_disagreement_score":0.5748522,"about_ca_system_score_codex":0.000045728706,"about_ca_system_score_gemma":0.0000068336067,"threshold_uncertainty_score":0.2389652},"labels":[],"label_agreement":null},{"id":"W1987557759","doi":"10.2316/journal.206.2010.3.206-3345","title":"FORMATION CONTROL AND SWITCHING FOR MULTIPLE ROBOTS IN UNCERTAIN ENVIRONMENTS","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Control theory (sociology); Obstacle; Control (management); Computer science; Obstacle avoidance; Point (geometry); Tracking (education); Collision avoidance; Mobile robot; Artificial intelligence; Collision; Mathematics; Law; Computer security; Psychology","score_opus":0.009979738713702762,"score_gpt":0.24764624478156883,"score_spread":0.23766650606786607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987557759","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":[0.12294828,0.00003623213,0.87437487,0.0018324645,0.00064572174,0.00014267991,0.0000060718035,0.000007421725,0.000006277177],"genre_scores_gemma":[0.9617846,0.000014286461,0.03802407,0.000073757095,0.000085388274,0.0000046989635,0.0000050672998,0.0000035163512,0.0000046160603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915016,0.000027305465,0.00039646245,0.00009022728,0.00024541968,0.000090424895],"domain_scores_gemma":[0.9992194,0.0001985141,0.00037655456,0.0000634052,0.00010263855,0.00003948415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000477687,0.00007159824,0.0001214549,0.00016185651,0.000037440142,0.00018978918,0.00023552179,0.000045335128,5.3557415e-7],"category_scores_gemma":[0.00021594971,0.00006447449,0.000032047832,0.000035142686,0.000010362219,0.0009120576,0.00003201871,0.00010441765,6.240403e-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":[0.00016659974,0.00036372963,0.033051357,0.00006876821,0.00024532716,0.00004957214,0.0023470432,0.29972318,0.2996333,0.07880668,0.00017871117,0.28536573],"study_design_scores_gemma":[0.0021307762,0.000040210904,0.028060753,0.00005165018,0.0000063984144,0.000082824954,0.000024510338,0.96702236,0.0003206769,0.0019791387,0.00021665759,0.000064051],"about_ca_topic_score_codex":0.0000106409025,"about_ca_topic_score_gemma":0.000020383877,"teacher_disagreement_score":0.8388363,"about_ca_system_score_codex":0.000045999153,"about_ca_system_score_gemma":0.000018499166,"threshold_uncertainty_score":0.2629193},"labels":[],"label_agreement":null},{"id":"W1987916013","doi":"10.2316/journal.206.2009.3.206-3274","title":"A QUALITATIVE MODEL OF DYNAMIC SCENE ANALYSIS AND INTERPRETATION IN AMBIENT INTELLIGENCE SYSTEMS","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Interpretation (philosophy); Computer science; Ambient intelligence; Spatial intelligence; Artificial intelligence; Machine learning","score_opus":0.020338160905148554,"score_gpt":0.3319495610846746,"score_spread":0.31161140017952604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987916013","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":[0.057465736,0.00012807205,0.9415406,0.0006711437,0.00012627154,0.00004302399,0.0000035415035,0.0000053519134,0.000016245009],"genre_scores_gemma":[0.8815071,0.00015930852,0.11828038,0.000028693064,0.000006290567,3.655257e-7,0.000004740507,0.0000011731884,0.000011973349],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990658,0.00004939781,0.0004484454,0.00009864636,0.0002828347,0.00005486364],"domain_scores_gemma":[0.999207,0.000046562825,0.00040379557,0.00006647486,0.00025014687,0.000026009347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053408986,0.00005967505,0.00015347377,0.0006262486,0.00001257531,0.00014072678,0.00026835655,0.000019402305,3.4356682e-7],"category_scores_gemma":[0.000042598724,0.000053020314,0.000036890073,0.00026366048,0.000019732797,0.0007597314,0.000053308675,0.000055327913,2.0168753e-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":[0.000020347226,0.00014306269,0.00032743148,0.000018645007,0.00023430964,0.000008736935,0.0072337803,0.73720074,0.0007559784,0.06273964,0.000004973192,0.19131233],"study_design_scores_gemma":[0.00015318267,0.00006819807,0.00706097,0.000086197186,0.000031155385,0.000005939145,0.00034080792,0.98535943,0.000069489884,0.0067755324,5.237771e-7,0.00004856032],"about_ca_topic_score_codex":0.0000110488545,"about_ca_topic_score_gemma":0.000007195337,"teacher_disagreement_score":0.8240413,"about_ca_system_score_codex":0.000042092634,"about_ca_system_score_gemma":0.000016752017,"threshold_uncertainty_score":0.21621056},"labels":[],"label_agreement":null},{"id":"W1988636477","doi":"10.2316/journal.206.2008.1.206-3047","title":"FEEDFORWARD CONTROL OF FLEXIBLE LINK SYSTEMS USING PARALLEL SOLUTION SCHEME","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Feed forward; Inverse dynamics; Computer science; Cartesian coordinate system; Link (geometry); Torque; Kinematics; Mathematics; Physics; Control engineering; Engineering; Classical mechanics; Control (management); Geometry","score_opus":0.0161050363139497,"score_gpt":0.23126977633086654,"score_spread":0.21516474001691685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988636477","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":[0.125657,0.0010185174,0.8715137,0.0001818936,0.0014381536,0.00006732572,0.000005944134,0.000022281962,0.00009517836],"genre_scores_gemma":[0.9927039,0.00016263692,0.0067852624,0.000009689386,0.00030444603,8.957375e-7,0.0000022947086,0.000009746209,0.000021095208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990085,0.000017248783,0.00051626103,0.000047675454,0.00032582675,0.00008451832],"domain_scores_gemma":[0.99925166,0.000035085945,0.00028357052,0.000046600017,0.00033453113,0.00004855972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020697761,0.000076714045,0.000205876,0.00012366811,0.000027891696,0.000032768643,0.000114217844,0.0000616961,0.0000030910796],"category_scores_gemma":[0.000021320013,0.00006939862,0.00007237822,0.00004390164,0.000016778988,0.00018724625,0.000010485225,0.00008532044,0.0000012751104],"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":[0.000023169381,0.00001930353,0.00059581554,0.000025835623,0.00022535368,0.000011381932,0.000060167407,0.9772495,0.00960915,0.010383181,0.00003362522,0.0017635062],"study_design_scores_gemma":[0.0009092963,0.000048096244,0.0012874581,0.0001412723,0.000023256314,0.00023480179,0.000020387512,0.99683297,0.000065483866,0.00023541563,0.00013602119,0.00006552315],"about_ca_topic_score_codex":0.000017395829,"about_ca_topic_score_gemma":4.963219e-7,"teacher_disagreement_score":0.86704695,"about_ca_system_score_codex":0.000083964405,"about_ca_system_score_gemma":0.000026970833,"threshold_uncertainty_score":0.28299937},"labels":[],"label_agreement":null},{"id":"W1989033557","doi":"10.2316/journal.206.2013.2.206-3800","title":"GENERAL VEGETATION DETECTION USING AN INTEGRATED VISION SYSTEM","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Vegetation (pathology); Computer vision; Computer science; Artificial intelligence; Remote sensing; Geography; Medicine; Pathology","score_opus":0.01319967427085003,"score_gpt":0.24025293900056266,"score_spread":0.22705326472971263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989033557","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":[0.9370747,0.00005655199,0.061585777,0.00009308526,0.0010134872,0.000042185202,0.0000013423089,0.000017373908,0.00011546224],"genre_scores_gemma":[0.98448116,0.000019695979,0.015169799,0.000029761279,0.0002685333,2.2311415e-8,0.00001881085,0.0000023742523,0.00000982196],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927634,0.0000619704,0.00027104554,0.00006827832,0.0002558883,0.00006649433],"domain_scores_gemma":[0.9992478,0.00002447216,0.00024739784,0.00003664298,0.00038093544,0.00006274369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018976294,0.0000635002,0.00008599163,0.00016044655,0.00006286365,0.00022705538,0.000071436436,0.000044076616,0.00002186108],"category_scores_gemma":[0.000020971496,0.000046362715,0.000029320558,0.00006006027,0.000015231877,0.0007068732,0.0000030327014,0.00007706355,0.000009553983],"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":[0.00001877319,0.000016534279,0.0067764134,0.000010474983,0.000032247044,0.0000096752265,0.00018540295,0.5094169,0.0028072367,0.000043916563,0.000008418716,0.48067403],"study_design_scores_gemma":[0.00018034501,0.000099539946,0.18229389,0.00007038115,0.000011084878,0.0002555819,0.00013024923,0.81649864,0.00023059503,0.000139922,0.000043060965,0.00004671781],"about_ca_topic_score_codex":0.000749529,"about_ca_topic_score_gemma":0.000108047556,"teacher_disagreement_score":0.48062733,"about_ca_system_score_codex":0.000018133505,"about_ca_system_score_gemma":0.000022799977,"threshold_uncertainty_score":0.21895002},"labels":[],"label_agreement":null},{"id":"W1989978677","doi":"10.2316/journal.206.2008.1.206-3048","title":"STRATEGIC FUNCTIONS FOR FEEDBACK STABILIZATION OF BILINEAR SYSTEMS","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Stability and Controllability of Differential Equations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bilinear interpolation; Control theory (sociology); Computer science; Artificial intelligence; Control (management)","score_opus":0.030587162691496177,"score_gpt":0.23959406297539093,"score_spread":0.20900690028389476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989978677","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":[0.5961218,0.0002177345,0.40228486,0.00018326132,0.0009321382,0.00012513938,0.000036958958,0.000021719852,0.00007640799],"genre_scores_gemma":[0.9972855,0.0001028975,0.002413991,0.0000037752022,0.00014488235,0.000003460344,0.000023414485,0.000007150227,0.000014956126],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918944,0.000019061295,0.00046550264,0.000052011288,0.000216474,0.000057517125],"domain_scores_gemma":[0.9988768,0.0001437385,0.00016596908,0.000054110224,0.00072650803,0.000032862994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016822871,0.000064300606,0.00014779871,0.00012667097,0.000040969673,0.00002914704,0.00008001207,0.000048746904,0.000008933854],"category_scores_gemma":[0.000093696835,0.00006006154,0.00006927228,0.00006419535,0.00004136843,0.00018417131,0.000006039254,0.000056136156,7.8423324e-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":[0.000037392463,0.00008845839,0.0013187663,0.00008704461,0.0001481023,5.5456354e-7,0.00027815875,0.9848392,0.0037807666,0.0076269675,0.00007202883,0.0017225372],"study_design_scores_gemma":[0.0008917807,0.00013145372,0.006353627,0.000052466286,0.00004315793,0.000035503363,0.0003646683,0.989004,0.0003632278,0.00255611,0.00012936679,0.00007462583],"about_ca_topic_score_codex":0.0000045663187,"about_ca_topic_score_gemma":0.0000061472747,"teacher_disagreement_score":0.40116367,"about_ca_system_score_codex":0.000044821973,"about_ca_system_score_gemma":0.000045089328,"threshold_uncertainty_score":0.24492384},"labels":[],"label_agreement":null},{"id":"W1990068001","doi":"10.2316/journal.206.2011.4.206-3590","title":"SEMG-BASED NEURO-FUZZY CONTROLLER FOR A PARALLEL ANKLE EXOSKELETON WITH PROPRIOCEPTION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Exoskeleton; Proprioception; Ankle; Computer science; Rigidity (electromagnetism); Physical medicine and rehabilitation; Motion (physics); Mechanism (biology); Control theory (sociology); Engineering; Artificial intelligence; Simulation; Medicine; Control (management); Structural engineering; Anatomy; Physics","score_opus":0.012560203414734525,"score_gpt":0.2198654275510273,"score_spread":0.2073052241362928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990068001","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":[0.050517507,0.00009853197,0.94769096,0.00068945764,0.00047482614,0.00023599122,0.000006786944,0.00004245518,0.00024348394],"genre_scores_gemma":[0.88725543,0.00003584178,0.11251023,0.00007527202,0.00008217704,0.000006862356,0.0000061766636,0.000015994268,0.00001202637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999312,0.000012578568,0.00030632145,0.000066651046,0.00021596407,0.000086525855],"domain_scores_gemma":[0.99920577,0.00006387281,0.00016373757,0.00004465557,0.00047324886,0.00004873507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015404732,0.00009306048,0.0001281244,0.00014155668,0.000030472123,0.0000481876,0.00009691014,0.00004685832,0.000007866185],"category_scores_gemma":[0.00003942798,0.000071241506,0.000056740082,0.000042902153,0.000031762018,0.00015002493,0.0000064842366,0.00007704174,0.0000011922393],"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":[0.00017291155,0.00010737386,0.00095642894,0.000058667065,0.0001286827,0.000007252197,0.0004463404,0.9756515,0.0017609465,0.0076248012,0.0002825533,0.012802531],"study_design_scores_gemma":[0.0023447766,0.00052193593,0.00917714,0.00009947519,0.000046869245,0.00005699194,0.000056936,0.9814745,0.0005736271,0.005088289,0.00042126066,0.00013816674],"about_ca_topic_score_codex":0.000001245322,"about_ca_topic_score_gemma":0.0000020004602,"teacher_disagreement_score":0.83673793,"about_ca_system_score_codex":0.000030912237,"about_ca_system_score_gemma":0.000028766304,"threshold_uncertainty_score":0.2905144},"labels":[],"label_agreement":null},{"id":"W1992207713","doi":"10.2316/journal.206.2014.1.206-3896","title":"DESIGN BY APPLYING COMPENSATION TECHNOLOGY TO ACHIEVE BIPED ROBOTS WITH STABLE GAIT","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Gait; Compensation (psychology); Robot; Computer science; Biped robot; Control engineering; Physical medicine and rehabilitation; Artificial intelligence; Engineering; Psychology; Medicine","score_opus":0.009915759588288152,"score_gpt":0.2325106509285963,"score_spread":0.22259489134030813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992207713","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":[0.032936886,0.00007662049,0.9656974,0.00074358296,0.00026749866,0.00010911277,0.0000013947089,0.0000488902,0.00011861943],"genre_scores_gemma":[0.8906503,0.000058460784,0.10911301,0.00006430104,0.00006783214,0.0000043587793,0.0000046370674,0.000014202008,0.000022917602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992504,0.000019886746,0.00027960874,0.000078946025,0.00026683696,0.00010431235],"domain_scores_gemma":[0.9994528,0.00004824748,0.00011984177,0.00006337849,0.00026027806,0.000055415832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023486635,0.00009640701,0.00013617138,0.00024607425,0.00003771626,0.00008970628,0.000162837,0.000051219395,0.000009085991],"category_scores_gemma":[0.000030747982,0.00008126192,0.000016421784,0.00011551617,0.000017087903,0.00018368314,0.000017879525,0.00011204133,0.000005926439],"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":[0.000018947181,0.000014704055,0.00019350453,0.000007191249,0.000048703994,0.000002640425,0.00009780573,0.94196725,0.012908158,0.0016567069,0.00028211976,0.042802278],"study_design_scores_gemma":[0.00033803695,0.00025758828,0.0005102183,0.00013119726,0.000018719127,0.00010955826,0.0000521076,0.9807088,0.014722188,0.0018579976,0.0011370834,0.00015653108],"about_ca_topic_score_codex":0.000003214852,"about_ca_topic_score_gemma":0.0000019526565,"teacher_disagreement_score":0.8577134,"about_ca_system_score_codex":0.000055558576,"about_ca_system_score_gemma":0.000012258605,"threshold_uncertainty_score":0.3313765},"labels":[],"label_agreement":null},{"id":"W1994043892","doi":"10.2316/journal.206.2012.1.206-3589","title":"MOTION PLANNING OF A WALKING ROBOT USING ATTITUDE GUIDANCE","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Motion (physics); Computer vision; Motion planning; Physical medicine and rehabilitation; Artificial intelligence; Robot; Psychology; Medicine","score_opus":0.03653006357864191,"score_gpt":0.31809773772399824,"score_spread":0.28156767414535633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994043892","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":[0.10595395,0.0003699205,0.89200854,0.00023382886,0.0013388357,0.000029076446,7.3754455e-7,0.000016075244,0.000049020415],"genre_scores_gemma":[0.5878046,0.000007768046,0.411987,0.000022686301,0.00017053053,1.5585634e-7,7.030917e-7,0.0000033325375,0.0000032018506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987691,0.000052745414,0.00047407043,0.00008034239,0.0004892322,0.00013448787],"domain_scores_gemma":[0.9986673,0.00007876967,0.0007201171,0.0000915221,0.00037735663,0.00006494855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069666497,0.00008429717,0.00015273961,0.00023825216,0.000043177562,0.000083114835,0.00037015733,0.000043631393,0.0000015250001],"category_scores_gemma":[0.00012793555,0.00007807609,0.000050103212,0.000113550566,0.000022908767,0.0010971564,0.00009319101,0.00010431768,9.60137e-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":[0.00000849777,0.00009988028,0.041912876,0.000021710917,0.00010627634,0.000020901736,0.0019442247,0.90386796,0.010965774,0.007562024,0.000032408283,0.033457454],"study_design_scores_gemma":[0.00029940566,0.000036821002,0.14870305,0.00033352256,0.00001604256,0.00043369635,0.00003157133,0.84791595,0.0015167573,0.0006117028,0.000015613543,0.00008588047],"about_ca_topic_score_codex":0.000005063128,"about_ca_topic_score_gemma":4.9344557e-8,"teacher_disagreement_score":0.48185065,"about_ca_system_score_codex":0.00007262829,"about_ca_system_score_gemma":0.000037607853,"threshold_uncertainty_score":0.31838506},"labels":[],"label_agreement":null},{"id":"W1996123965","doi":"10.2316/journal.206.2004.1.206-2029","title":"Placement of Robot Manipulators to Maximize Dexterity","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot manipulator; Computer science; Robot; Control theory (sociology); Artificial intelligence; Control engineering; Engineering; Control (management)","score_opus":0.008908404543246007,"score_gpt":0.22908267998219556,"score_spread":0.22017427543894955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996123965","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":[0.16170232,0.000037816844,0.83700335,0.00033518576,0.0007730877,0.000044744505,0.0000027205988,0.000014699558,0.000086056265],"genre_scores_gemma":[0.75375783,0.000054679047,0.24607904,0.00003338664,0.000058473703,4.5497174e-7,0.0000020834136,0.0000074662435,0.000006558453],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999253,0.000005278936,0.00035856428,0.000046654208,0.00026860135,0.000067917004],"domain_scores_gemma":[0.99959433,0.000013275422,0.00011693236,0.00004943921,0.00016461255,0.00006139935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012768844,0.000070941685,0.00012652493,0.00014249484,0.000012966879,0.000032101732,0.00011734378,0.000033894536,0.000011121011],"category_scores_gemma":[0.000021573296,0.000065966524,0.000041533796,0.00004789988,0.000008236483,0.0001175923,0.00002446227,0.00006008086,0.0000021692122],"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":[0.000010754452,0.000024077839,0.000092989714,0.000013473965,0.000050299906,0.0000058296087,0.00012854794,0.9759784,0.004679067,0.016431991,0.00001624249,0.0025683604],"study_design_scores_gemma":[0.0022073374,0.0003560178,0.021469204,0.0004739618,0.00006560425,0.00029147853,0.00018117583,0.94109505,0.007710444,0.025758807,0.00009113286,0.00029979157],"about_ca_topic_score_codex":0.0000046672794,"about_ca_topic_score_gemma":0.0000026418213,"teacher_disagreement_score":0.59205556,"about_ca_system_score_codex":0.00008729954,"about_ca_system_score_gemma":0.00001784349,"threshold_uncertainty_score":0.2690037},"labels":[],"label_agreement":null},{"id":"W1997182461","doi":"10.2316/journal.206.2015.1.206-4161","title":"FEEDFORWARD INERTIAL ACTUATION FOR ROLL STABILIZATION OF AN UNDERACTUATED UNDERWATER VEHICLE","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Underactuation; Control theory (sociology); Feed forward; Inertial frame of reference; Controller (irrigation); Torque; Rotor (electric); Underwater; Computer science; Control engineering; Engineering; Control (management); Physics; Artificial intelligence","score_opus":0.007410225985386579,"score_gpt":0.2295426628925014,"score_spread":0.22213243690711482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997182461","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":[0.4018987,0.000011511754,0.59729683,0.00025548539,0.0004225243,0.00006136302,0.0000040806253,0.0000142638,0.000035201265],"genre_scores_gemma":[0.99591863,0.000014201926,0.0038065598,0.000025328543,0.00018251981,0.0000015067973,0.000034425244,0.000011396463,0.0000054346174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924237,0.000018912275,0.00040382583,0.000050608498,0.00022236686,0.000061911625],"domain_scores_gemma":[0.99926543,0.00007009334,0.00020409016,0.00004319646,0.00037758632,0.000039586714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030366797,0.00006509337,0.00013561889,0.00010180401,0.000017717653,0.000057130794,0.00009481779,0.000051706847,0.000005222329],"category_scores_gemma":[0.00006186727,0.000056142675,0.00004547653,0.00003336704,0.000007966587,0.00028723068,0.000007430797,0.00004410681,7.008999e-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":[0.00005989966,0.000044138404,0.000096805496,0.00003126481,0.00009586125,3.1211744e-7,0.00012974409,0.89771146,0.05730606,0.008263449,0.000020339441,0.03624066],"study_design_scores_gemma":[0.0009753179,0.00016793296,0.0012758692,0.00003966707,0.000024018622,0.000006362659,0.000026833357,0.98778784,0.0026921888,0.006790134,0.00015520822,0.000058626785],"about_ca_topic_score_codex":0.000004263513,"about_ca_topic_score_gemma":0.00001070703,"teacher_disagreement_score":0.5940199,"about_ca_system_score_codex":0.0000553892,"about_ca_system_score_gemma":0.000013504555,"threshold_uncertainty_score":0.22894318},"labels":[],"label_agreement":null},{"id":"W1998011262","doi":"10.2316/journal.206.2010.4.206-3195","title":"DOOR-OPENING BEHAVIOUR BY HOME SERVICE ROBOT IN A HOUSE","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Service (business); Business; Computer science; Advertising; Marketing","score_opus":0.007232801541762493,"score_gpt":0.2451160360485622,"score_spread":0.2378832345067997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998011262","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":[0.509956,0.000082303755,0.47902068,0.0086325845,0.0021747288,0.000043828502,0.0000016630528,0.00003380252,0.000054391243],"genre_scores_gemma":[0.8904287,0.000033329983,0.10921641,0.0001716219,0.00012305967,9.853751e-7,0.0000024307371,0.000008425228,0.000014990407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910706,0.000012761036,0.0003391112,0.00010083938,0.0003364586,0.00010375273],"domain_scores_gemma":[0.9992387,0.00006752989,0.0001999166,0.000087854045,0.0003349194,0.000071073126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000325588,0.000081433456,0.00010693366,0.00022368033,0.00002882195,0.0002430005,0.00048956,0.00004833748,0.000005520732],"category_scores_gemma":[0.000050753373,0.00007832577,0.000029636636,0.00014843179,0.000009476838,0.000661709,0.00008001861,0.00024041385,0.0000039434194],"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":[0.000019843497,0.00053363,0.05030356,0.000038188977,0.00012794958,0.000103577855,0.003293342,0.7100816,0.069864616,0.13029452,0.0013261351,0.034013055],"study_design_scores_gemma":[0.000913831,0.000060369344,0.16284205,0.00013317727,0.000011927484,0.00044444783,0.00006669826,0.829251,0.00097559585,0.0045218165,0.0005221752,0.00025690123],"about_ca_topic_score_codex":0.00002918531,"about_ca_topic_score_gemma":0.00002432192,"teacher_disagreement_score":0.38047275,"about_ca_system_score_codex":0.00003901714,"about_ca_system_score_gemma":0.00006563475,"threshold_uncertainty_score":0.31940323},"labels":[],"label_agreement":null},{"id":"W1998146576","doi":"10.2316/journal.206.2011.3.206-3418","title":"MULTI-VIEW RECONSTRUCTION OF ANNULAR OUTDOOR SCENES FROM BINOCULAR VIDEO USING GLOBAL RELAXATION ITERATION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Relaxation (psychology); Binocular disparity; Binocular vision; Computer graphics (images); Medicine; Internal medicine","score_opus":0.039543704338097764,"score_gpt":0.2619011962873237,"score_spread":0.22235749194922597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998146576","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":[0.6557211,0.0003311631,0.34162444,0.000013726504,0.0021719474,0.00006647072,0.000013245384,0.000022709077,0.000035162448],"genre_scores_gemma":[0.9557443,0.000115140494,0.04386249,0.0000060947677,0.0002525473,6.2636036e-7,0.000008023155,0.0000086828695,0.0000020857738],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989027,0.000047137495,0.0006408229,0.00007821442,0.0002679246,0.00006321592],"domain_scores_gemma":[0.9989109,0.000018128738,0.00047560968,0.00006070114,0.0004967775,0.00003785405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025220914,0.00009590489,0.00017748658,0.00016699737,0.000033837932,0.000054334232,0.00007474825,0.00011064897,0.000018234892],"category_scores_gemma":[0.00006744382,0.00008970677,0.00007390003,0.00010751038,0.000018661643,0.00056448823,0.000011815802,0.00008481052,0.000001952271],"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":[0.00021588587,0.00017204486,0.038309466,0.00012207795,0.0008478647,0.00003131867,0.0020390048,0.4539408,0.1318805,0.0011821777,0.00008248237,0.37117636],"study_design_scores_gemma":[0.0012341556,0.000104800114,0.048564214,0.0006361774,0.00009090853,0.00026477454,0.00018117257,0.9295478,0.0181445,0.00095772767,0.00010648602,0.00016731709],"about_ca_topic_score_codex":0.00010189146,"about_ca_topic_score_gemma":0.000006595134,"teacher_disagreement_score":0.47560695,"about_ca_system_score_codex":0.000121456316,"about_ca_system_score_gemma":0.000024012916,"threshold_uncertainty_score":0.36581358},"labels":[],"label_agreement":null},{"id":"W1998944623","doi":"10.2316/journal.206.2014.1.206-3788","title":"BEHAVIOUR TREE BASED CONTROL FOR EFFICIENT NAVIGATION OF HOLONOMIC ROBOTS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Holonomic; Robot; Tree (set theory); Computer science; Control (management); Holonomic constraints; Artificial intelligence; Mathematics; Physics","score_opus":0.010756191554105359,"score_gpt":0.2611460735523263,"score_spread":0.25038988199822093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998944623","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":[0.07573156,0.000024125009,0.9220124,0.0012519008,0.0008518197,0.00008757804,0.000005164245,0.00001530015,0.000020147083],"genre_scores_gemma":[0.7314346,0.0000010836505,0.2684118,0.000051827665,0.00008612314,0.0000015459864,0.000005218053,0.000004064363,0.000003747842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989649,0.000048374943,0.000460819,0.00010647874,0.00033114193,0.00008830216],"domain_scores_gemma":[0.99836093,0.00024527698,0.0006827463,0.00009895758,0.00056313764,0.000048945578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006591153,0.000079432735,0.00016963799,0.00019197508,0.00003421472,0.00007992672,0.00037449252,0.00004430678,5.997035e-7],"category_scores_gemma":[0.00013817503,0.00007209988,0.00007776734,0.00005706013,0.000025330428,0.00018283352,0.000018690955,0.00006617833,8.4234625e-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":[0.000017651164,0.00007018504,0.0017837512,0.000009855289,0.000029914594,0.0000025978704,0.00010274941,0.9686485,0.0014659258,0.006751373,0.00003254474,0.021084981],"study_design_scores_gemma":[0.0014232098,0.00019804956,0.034142304,0.00011290738,0.000022126276,0.000035171248,0.000005530755,0.96175075,0.0013193097,0.0009127461,0.00001244433,0.000065474764],"about_ca_topic_score_codex":0.0000030814242,"about_ca_topic_score_gemma":1.7195181e-7,"teacher_disagreement_score":0.65570307,"about_ca_system_score_codex":0.00004973854,"about_ca_system_score_gemma":0.000058621685,"threshold_uncertainty_score":0.29401478},"labels":[],"label_agreement":null},{"id":"W1999755059","doi":"10.2316/journal.206.2004.2.206-2562","title":"Building Environment Maps using Neural Networks","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Sonar; Representation (politics); Workspace; Mobile robot; Computer vision; Robot; Artificial intelligence; Grid; Artificial neural network; Grid reference; Motion planning; Geography","score_opus":0.017048969076474244,"score_gpt":0.26294515987016603,"score_spread":0.2458961907936918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999755059","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040360503,0.00013702354,0.957087,0.0012361428,0.0011235557,0.000027762411,5.400859e-7,0.000017351944,0.000010165497],"genre_scores_gemma":[0.4821397,0.000019714396,0.5176126,0.00006853813,0.00015380846,1.08151355e-7,6.5854135e-7,0.000003218587,0.0000016418213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907744,0.000023187737,0.00031154617,0.0000982942,0.00038417306,0.00010537639],"domain_scores_gemma":[0.99940604,0.00003654637,0.00032970533,0.00007691477,0.0000910068,0.000059800674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025224418,0.00007798544,0.00010049779,0.00014188401,0.00005174832,0.00018136729,0.0003751173,0.000036328405,0.0000010019855],"category_scores_gemma":[0.000024938101,0.000071346934,0.00004293858,0.000056400193,0.00002105845,0.0005341798,0.000098987046,0.0001210891,9.0394803e-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":[0.0000018034098,0.000020582813,0.00021671012,0.0000013127504,0.000025935617,0.00006088694,0.00010081033,0.97672284,0.0003498058,0.010193964,0.0000064504884,0.012298884],"study_design_scores_gemma":[0.000393098,0.00004600256,0.0028066237,0.000054204298,0.000008803715,0.000717061,0.00000542715,0.98780614,0.00009203325,0.007976446,0.000022973794,0.000071210074],"about_ca_topic_score_codex":0.0000050004724,"about_ca_topic_score_gemma":5.792447e-8,"teacher_disagreement_score":0.4417792,"about_ca_system_score_codex":0.00012974486,"about_ca_system_score_gemma":0.000029347237,"threshold_uncertainty_score":0.29094437},"labels":[],"label_agreement":null},{"id":"W2001157267","doi":"10.2316/journal.206.2014.4.206-4048","title":"FUZZY REACTIVE NAVIGATION OF MOBILE ROBOT IN UNKNOWN ENVIRONMENTS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Mobile robot; Fuzzy logic; Artificial intelligence; Mobile robot navigation; Robot; Robot control","score_opus":0.007807915682928216,"score_gpt":0.2525341690265569,"score_spread":0.24472625334362869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001157267","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":[0.13695525,0.000053777283,0.8617153,0.00038433116,0.0006136403,0.00005864154,9.860397e-7,0.000008137771,0.0002099461],"genre_scores_gemma":[0.846857,0.000022298134,0.15301201,0.000023857465,0.00006129214,0.0000011579201,0.0000032380265,0.0000035219844,0.000015637217],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988687,0.00006544602,0.00045479822,0.000102774335,0.00043023904,0.0000780348],"domain_scores_gemma":[0.9990423,0.00013887079,0.0005648824,0.000092620525,0.00012916727,0.00003215927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050301466,0.00007247917,0.00014981306,0.00021333995,0.000017017128,0.000047474274,0.00033796942,0.000043854103,8.969911e-7],"category_scores_gemma":[0.00009653462,0.000067246874,0.000035033903,0.00009302019,0.000027878305,0.0005236776,0.0000637422,0.00011109321,0.000002237067],"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":[0.0000123873915,0.00016976072,0.0039157374,0.000011278346,0.000053013548,0.000021567006,0.0012203107,0.87720364,0.009620614,0.021621814,0.0000230913,0.08612675],"study_design_scores_gemma":[0.000732246,0.00024356268,0.06270921,0.00034264592,0.00000988078,0.00014852479,0.000044983266,0.9198988,0.0034124372,0.012205527,0.00013879334,0.00011337108],"about_ca_topic_score_codex":0.000008232782,"about_ca_topic_score_gemma":3.64687e-7,"teacher_disagreement_score":0.70990175,"about_ca_system_score_codex":0.000073366085,"about_ca_system_score_gemma":0.000027909791,"threshold_uncertainty_score":0.2742248},"labels":[],"label_agreement":null},{"id":"W2001308153","doi":"10.2316/journal.206.2012.4.206-3631","title":"GENERATION OF OBSTACLE AVOIDANCE BASED ON IMAGE FEATURES AND EMBODIMENT","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Obstacle avoidance; Computer vision; Image (mathematics); Artificial intelligence; Obstacle; Computer science; Robot; Geography; Mobile robot","score_opus":0.024088768570057265,"score_gpt":0.2802116752092864,"score_spread":0.25612290663922915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001308153","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":[0.5293069,0.0003985875,0.4687378,0.000622001,0.00051093526,0.000060650706,0.0000069924695,0.000022708557,0.00033341182],"genre_scores_gemma":[0.9821303,0.000056372945,0.01759352,0.00005656092,0.00014094611,9.974461e-7,0.000007897368,0.000005494171,0.000007931765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995699,0.000008633886,0.00018654963,0.000030031764,0.0001621359,0.000042784177],"domain_scores_gemma":[0.9996586,0.000035905246,0.00009207301,0.000035884354,0.00014379132,0.000033783872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011903086,0.00004590824,0.000060534643,0.000095331125,0.000018674697,0.00002528674,0.000036903966,0.000024038587,0.0000051620123],"category_scores_gemma":[0.000021762005,0.00004220159,0.00001868565,0.000025203874,0.000011454495,0.00014916972,0.0000048137367,0.00004917904,7.261589e-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":[0.0000054998472,0.00003778485,0.0006159697,0.000009578134,0.000022233462,2.2011147e-7,0.00018814967,0.9687253,0.01931601,0.0035326493,0.00030636042,0.0072402298],"study_design_scores_gemma":[0.00028990477,0.000019578087,0.01829181,0.00003261321,0.000011180759,0.000011852797,0.000017291757,0.97149074,0.0095053185,0.0001548797,0.00013161245,0.000043235916],"about_ca_topic_score_codex":0.0000010608113,"about_ca_topic_score_gemma":5.829248e-7,"teacher_disagreement_score":0.45282337,"about_ca_system_score_codex":0.000026609221,"about_ca_system_score_gemma":0.000006960118,"threshold_uncertainty_score":0.1720931},"labels":[],"label_agreement":null},{"id":"W2001985730","doi":"10.2316/journal.206.2012.4.206-3651","title":"MARKET-BASED MULTI-ROBOT TASK ALLOCATION USING ENERGY-BASED BID CALCULATIONS","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Task (project management); Robot; Artificial intelligence; Engineering; Systems engineering","score_opus":0.014575674672024643,"score_gpt":0.25481525663974514,"score_spread":0.2402395819677205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001985730","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":[0.0071802884,0.00038404303,0.9909747,0.00020120914,0.0010767073,0.00006178231,0.000006222309,0.00005556487,0.00005945673],"genre_scores_gemma":[0.8387079,0.000018439076,0.1609061,0.000054428707,0.00025781733,0.000002418828,0.000020676493,0.00002018634,0.000012032377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901867,0.000039760176,0.00044745358,0.000061956234,0.0003037619,0.00012838344],"domain_scores_gemma":[0.9991173,0.00006866857,0.00027581182,0.00007080032,0.0003871333,0.00008026776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021807951,0.00011548342,0.00013655171,0.00029235115,0.000047924674,0.00006273757,0.00009892031,0.00006788893,0.0000124289945],"category_scores_gemma":[0.00006189651,0.00011618663,0.000059204012,0.00010715751,0.000017309516,0.0005458714,0.000008316466,0.00007656577,0.0000012428281],"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":[0.000009459241,0.000040967567,0.0011962908,0.000012459077,0.00005414387,0.0000013308277,0.000034350574,0.98630166,0.008355693,0.00055316003,0.000037285863,0.003403196],"study_design_scores_gemma":[0.0008137011,0.00001285202,0.00520724,0.00009565877,0.000037698082,0.000023567687,0.0000126671475,0.9924178,0.00094856584,0.00004033043,0.0002773825,0.00011252216],"about_ca_topic_score_codex":0.000008563014,"about_ca_topic_score_gemma":0.0000035947535,"teacher_disagreement_score":0.8315276,"about_ca_system_score_codex":0.0002097909,"about_ca_system_score_gemma":0.00004139646,"threshold_uncertainty_score":0.47379535},"labels":[],"label_agreement":null},{"id":"W2003188682","doi":"10.2316/journal.206.2014.4.206-3891","title":"A BIO-INSPIRED CASCADED APPROACH FOR THREE-DIMENSIONAL TRACKING CONTROL OF UNMANNED UNDERWATER VEHICLES","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Underwater; Tracking (education); Computer science; Control (management); Artificial intelligence; Geology; Oceanography; Psychology","score_opus":0.015438404530680539,"score_gpt":0.2287831883018149,"score_spread":0.21334478377113436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003188682","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":[0.061544824,0.00009456311,0.93755496,0.0002735971,0.0003174902,0.00007849148,0.000013360307,0.000018622879,0.00010409696],"genre_scores_gemma":[0.9750748,0.000007899799,0.02466564,0.000037470272,0.00017791461,0.0000014158475,0.000016628695,0.000011004503,0.00000722651],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992624,0.000011452717,0.00038449993,0.000054220825,0.00020974393,0.00007770605],"domain_scores_gemma":[0.9993347,0.0000982792,0.0001830997,0.00003854001,0.0003101572,0.000035204244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002634357,0.00007707527,0.0001634365,0.00011398199,0.00002401424,0.000040723782,0.0000887163,0.000053340267,0.000005290254],"category_scores_gemma":[0.000053644162,0.00006407871,0.00006331118,0.000024351215,0.000028140124,0.00010892151,0.000008991054,0.00006479293,2.1733993e-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":[0.00004045796,0.00004874681,0.0011161045,0.00006430116,0.00017617071,0.0000020956122,0.00006152703,0.96512127,0.0035001386,0.0054152915,0.00013729717,0.024316581],"study_design_scores_gemma":[0.0010021762,0.000067504174,0.005574721,0.00005185119,0.000042229047,0.00003934704,0.000008457815,0.98906887,0.001209422,0.002699295,0.00016547162,0.00007068513],"about_ca_topic_score_codex":0.0000045022384,"about_ca_topic_score_gemma":0.0000029732546,"teacher_disagreement_score":0.91353,"about_ca_system_score_codex":0.00002316896,"about_ca_system_score_gemma":0.000012294017,"threshold_uncertainty_score":0.26130542},"labels":[],"label_agreement":null},{"id":"W2003618165","doi":"10.2316/journal.206.2010.4.206-3347","title":"ROBUST ADAPTIVE TRACKING AND REGULATION OF WHEELED MOBILE ROBOTS VIOLATING KINEMATIC CONSTRAINT","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Constraint (computer-aided design); Kinematics; Mobile robot; Computer science; Tracking (education); Robot; Control theory (sociology); Artificial intelligence; Engineering; Control (management); Physics; Psychology","score_opus":0.00892076112615187,"score_gpt":0.21649500437547473,"score_spread":0.20757424324932286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003618165","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":[0.72366935,0.00018666378,0.27506837,0.00009992428,0.0006523588,0.00011533998,0.0000049864066,0.000027021812,0.00017599044],"genre_scores_gemma":[0.9590042,0.00006107063,0.040783398,0.0000060462394,0.00012410352,0.0000018536472,0.000004076074,0.000010689936,0.000004551844],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911517,0.0000137528905,0.0004913469,0.00006680544,0.00023552714,0.000077396886],"domain_scores_gemma":[0.99910057,0.00012713046,0.00030766582,0.000051015126,0.00036448456,0.00004913845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002617303,0.000096848285,0.00019134434,0.00017488525,0.000027700777,0.00006205386,0.00008556043,0.00006548025,0.000013853219],"category_scores_gemma":[0.000073586416,0.00009020192,0.000048346454,0.00004573426,0.000044284723,0.00031241676,0.000019752095,0.00017800339,3.3415395e-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":[0.00001137818,0.00001899708,0.00052300823,0.000029221343,0.000075315445,0.000002928909,0.00018167726,0.89382595,0.05445976,0.002986548,0.000005514375,0.0478797],"study_design_scores_gemma":[0.00060018804,0.00006110937,0.022674492,0.00018256067,0.000031848504,0.00014263841,0.00008530873,0.9740756,0.0005522888,0.0015035368,0.0000065745985,0.000083857194],"about_ca_topic_score_codex":0.0000037794537,"about_ca_topic_score_gemma":0.00001450294,"teacher_disagreement_score":0.23533486,"about_ca_system_score_codex":0.000021527641,"about_ca_system_score_gemma":0.000021277194,"threshold_uncertainty_score":0.36783275},"labels":[],"label_agreement":null},{"id":"W2004367268","doi":"10.2316/journal.206.2012.1.206-3535","title":"ANALYTICAL MODELLING OF DEFORMABLE OBJECTS FOR HAPTICS VIRTUAL ENVIRONMENTS","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","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":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Haptic technology; Computer science; Human–computer interaction; Artificial intelligence","score_opus":0.018257100002461033,"score_gpt":0.22880095826067176,"score_spread":0.21054385825821073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004367268","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":[0.11028229,0.00013087766,0.8890588,0.000026525531,0.00036982406,0.00003019145,0.0000033921199,0.000006327395,0.00009177517],"genre_scores_gemma":[0.96842575,0.00016429342,0.03123903,0.000007717436,0.00012028979,5.5800797e-7,0.0000055251567,0.000007409594,0.000029437024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994769,0.0000031858897,0.00025373892,0.000025131807,0.00016923397,0.00007179316],"domain_scores_gemma":[0.99972594,0.000034369103,0.00011730835,0.000024003235,0.000066856315,0.00003153348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012836093,0.00005099011,0.000085491076,0.00008923403,0.0000149728185,0.000020057887,0.000058165733,0.00003337129,0.000004858552],"category_scores_gemma":[0.000018193263,0.000046026747,0.000032631626,0.000017672306,0.000009986854,0.00030722568,0.000009414379,0.000042966734,4.416687e-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":[0.000008747263,0.000020463627,0.00022746905,0.000021889247,0.000053467153,1.6499311e-7,0.00017189825,0.99270946,0.00008728686,0.0032249247,0.000015618523,0.0034586217],"study_design_scores_gemma":[0.00022565504,0.000033554865,0.0003200303,0.000036596994,0.000027470243,0.000013282127,0.00003400995,0.99624985,0.0024974076,0.00036724817,0.0001496749,0.000045207256],"about_ca_topic_score_codex":4.7989437e-7,"about_ca_topic_score_gemma":9.094678e-8,"teacher_disagreement_score":0.85814345,"about_ca_system_score_codex":0.000033207507,"about_ca_system_score_gemma":0.0000061946575,"threshold_uncertainty_score":0.18769163},"labels":[],"label_agreement":null},{"id":"W2006435262","doi":"10.2316/journal.206.2014.3.206-4072","title":"ROBUST CONTROL FOR RIGID ROBOTIC MANIPULATORS USING NONLINEAR DISTURBANCE OBSERVER","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Nonlinear system; Robot manipulator; Disturbance (geology); Computer science; Control engineering; Control (management); Engineering; Artificial intelligence; Physics; Geology","score_opus":0.015947770814485403,"score_gpt":0.22864431416797412,"score_spread":0.21269654335348873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006435262","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":[0.089135244,0.00021028135,0.9088325,0.00026962592,0.0013858466,0.000093863055,0.0000067484484,0.000030166833,0.00003570565],"genre_scores_gemma":[0.9520388,0.000038133257,0.04734386,0.000051814834,0.00048389577,0.000001641048,0.000007906715,0.000018374685,0.000015536265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919724,0.000013723874,0.00038477284,0.000075243166,0.00021582584,0.00011318335],"domain_scores_gemma":[0.9992966,0.00010993279,0.00017869651,0.00006080569,0.00029509308,0.000058877602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021637604,0.000110027526,0.00019834418,0.00010747529,0.00003837858,0.000091732705,0.00014709102,0.000053634107,0.0000035797245],"category_scores_gemma":[0.0000712939,0.00010079929,0.00009463072,0.00003484116,0.00001692433,0.00025092968,0.000012136812,0.00008826198,0.000001039952],"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":[0.000017801443,0.00001834888,0.0010025179,0.000022823513,0.000100733516,0.0000020576172,0.00001754925,0.9908906,0.0006050487,0.0023509988,0.00003733399,0.0049341824],"study_design_scores_gemma":[0.0012419559,0.00004680298,0.0072225444,0.00008303202,0.000054911747,0.000042402695,0.0000057168822,0.9897946,0.00003269954,0.0011090648,0.00026038868,0.00010584501],"about_ca_topic_score_codex":0.0000031316551,"about_ca_topic_score_gemma":0.0000042570437,"teacher_disagreement_score":0.8629036,"about_ca_system_score_codex":0.00007733417,"about_ca_system_score_gemma":0.000014672185,"threshold_uncertainty_score":0.41104758},"labels":[],"label_agreement":null},{"id":"W2008221568","doi":"10.2316/journal.206.2010.2.206-3331","title":"STRUCTURAL SYNTHESIS AND VARIATION ANALYSIS OF A FAMILY OF 6-DOF PARALLEL MECHANISMS WITH THREE LIMBS","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Variation (astronomy); Computer science; Physics","score_opus":0.007140592033990006,"score_gpt":0.21125737221989518,"score_spread":0.20411678018590518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008221568","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":[0.42500103,0.000018969971,0.57469976,0.00004974908,0.00016752435,0.000025166963,0.0000075703633,0.000005896967,0.00002433935],"genre_scores_gemma":[0.7237486,0.000039899405,0.27617657,0.000004453876,0.000020044741,4.8865115e-7,0.0000029114885,0.000005741218,0.0000012592983],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992068,0.000008744492,0.00037529986,0.000058316804,0.00029509366,0.000055780813],"domain_scores_gemma":[0.999208,0.0000833588,0.00031381298,0.00006298446,0.00029492966,0.000036952337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017526944,0.00008097142,0.0002300235,0.0003165353,0.00001565253,0.000030533025,0.00009773155,0.000055875724,0.000010958427],"category_scores_gemma":[0.000039044702,0.00006393398,0.00005291284,0.0001225094,0.000023711793,0.00016153573,0.000015317613,0.00009061248,7.5315015e-8],"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":[0.000026305528,0.000019153216,0.0008380818,0.000022719081,0.00086983835,0.000002700051,0.00016240252,0.87905693,0.022326062,0.09164125,0.0000011937399,0.0050333585],"study_design_scores_gemma":[0.00022768923,0.00007624884,0.10526224,0.00003797435,0.000354184,0.000025053814,0.000034963075,0.8832368,0.00036659464,0.010317714,4.6568587e-7,0.000060067472],"about_ca_topic_score_codex":0.000015313966,"about_ca_topic_score_gemma":0.000044972134,"teacher_disagreement_score":0.29874763,"about_ca_system_score_codex":0.000012808905,"about_ca_system_score_gemma":0.000016765167,"threshold_uncertainty_score":0.26071522},"labels":[],"label_agreement":null},{"id":"W2008447832","doi":"10.2316/journal.206.2013.1.206-3657","title":"EVALUATION OF MOTION MAPPINGS FROM A HAPTIC DEVICE TO AN INDUSTRIAL ROBOT FOR EFFECTIVE MASTER–SLAVE MANIPULATION","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Master/slave; Computer science; Haptic technology; Workspace; Inertia; Motion (physics); Robot; Set (abstract data type); Simulation; Boundary (topology); Artificial intelligence; Mathematics; Programming language; Operating system","score_opus":0.06693305840735711,"score_gpt":0.29040512538773566,"score_spread":0.22347206698037855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008447832","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":[0.5785413,0.00003645484,0.41970018,0.00023721273,0.0009062147,0.0005087743,0.000008748509,0.000018099608,0.000043023378],"genre_scores_gemma":[0.98721474,0.0000038468374,0.012232,0.000026767686,0.0004399854,0.000028933115,0.000035954123,0.000012801742,0.000004965926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987196,0.00007021518,0.0005052668,0.00008497216,0.00055064907,0.0000693324],"domain_scores_gemma":[0.99803615,0.00008657498,0.00024014442,0.000058981375,0.0015173961,0.00006073669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006472556,0.00009290619,0.0001599905,0.00023281566,0.000024271785,0.000116314106,0.00009454541,0.00007656513,0.000036222063],"category_scores_gemma":[0.00017452346,0.00008884335,0.00004371074,0.00006353863,0.000007998386,0.00055358256,0.000009890293,0.00006293431,0.00000581221],"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":[0.00002027771,0.00003567619,0.0006990247,0.00001389948,0.00017741956,2.8005553e-7,0.0010013497,0.74981195,0.03265606,0.00041733874,0.00009188856,0.21507482],"study_design_scores_gemma":[0.001199367,0.00013263576,0.040161893,0.00013937749,0.00009234114,0.000009709468,0.00020480681,0.9551206,0.0017512343,0.0010668354,0.00003660844,0.000084584266],"about_ca_topic_score_codex":0.00005321397,"about_ca_topic_score_gemma":0.000020250625,"teacher_disagreement_score":0.40867347,"about_ca_system_score_codex":0.00015832455,"about_ca_system_score_gemma":0.00002668447,"threshold_uncertainty_score":0.36229268},"labels":[],"label_agreement":null},{"id":"W2009853478","doi":"10.2316/journal.206.2014.3.206-3915","title":"MECHATRONIC SYSTEM BASED ON THE MICRO-MACRO-KINEMATIC PRINCIPLE","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Workspace; Macro; Mechatronics; Kinematics; Computer science; Control engineering; Artificial intelligence; Simulation; Engineering; Robot; Physics; Programming language","score_opus":0.00866488459087403,"score_gpt":0.23425837765494406,"score_spread":0.22559349306407003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009853478","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":[0.06537178,0.0000686237,0.9319357,0.00093664706,0.00065645576,0.00007872112,0.0000011246051,0.000086591965,0.000864321],"genre_scores_gemma":[0.980751,0.000017830662,0.01899927,0.00008637096,0.00012554669,0.0000023455164,0.0000015210021,0.000008322222,0.000007811864],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994234,0.000028661463,0.00022621464,0.00003820953,0.0002193535,0.0000641932],"domain_scores_gemma":[0.99956083,0.000096241274,0.00012940094,0.00006122047,0.00013121683,0.000021072163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046695556,0.0000657188,0.0000926591,0.00010915496,0.000028217231,0.000030967218,0.00013041148,0.000030361827,0.0000046612995],"category_scores_gemma":[0.00006713992,0.000044459575,0.00003860179,0.000031463074,0.000013310284,0.00007142339,0.000008062268,0.000100699355,0.0000023507694],"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":[0.000018496708,0.000030805408,0.0004497102,0.0000755619,0.00010766189,0.0000043139,0.000056096193,0.9029812,0.020219805,0.068226986,0.00031908107,0.0075102327],"study_design_scores_gemma":[0.00032550027,0.00007877723,0.0009388553,0.00021684176,0.000022224956,0.000029258064,0.000019110521,0.9874784,0.008421343,0.001245386,0.0011621562,0.00006217172],"about_ca_topic_score_codex":1.8971917e-7,"about_ca_topic_score_gemma":3.5319476e-7,"teacher_disagreement_score":0.9153792,"about_ca_system_score_codex":0.000076966884,"about_ca_system_score_gemma":0.0000088327115,"threshold_uncertainty_score":0.18130088},"labels":[],"label_agreement":null},{"id":"W2010056799","doi":"10.2316/journal.206.2013.3.206-3792","title":"FEATURE-BASED 3D OUTDOOR SLAM WITH LOCAL FILTERS","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Extended Kalman filter; Simultaneous localization and mapping; Kalman filter; Computer vision; Feature (linguistics); Artificial intelligence; Computer science; Lidar; Remote sensing; Geography; Robot; Mobile robot","score_opus":0.004429338821219532,"score_gpt":0.1923214344774815,"score_spread":0.18789209565626197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010056799","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":[0.04156419,0.00007589668,0.955354,0.0020833968,0.00054127065,0.0000778983,0.0000029045054,0.000043675635,0.00025680396],"genre_scores_gemma":[0.96562386,0.00003215505,0.033985198,0.00015701765,0.00012931386,0.0000015418535,0.000017667988,0.000017797058,0.00003542878],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927837,0.00001365202,0.00022057506,0.000063131774,0.0003283892,0.00009590832],"domain_scores_gemma":[0.9993024,0.000040037325,0.000121631645,0.000055804387,0.00041384026,0.00006630087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074104246,0.00010493585,0.00012143922,0.00016641698,0.000026575777,0.0001409062,0.00010752664,0.00005532405,0.000027980535],"category_scores_gemma":[0.000016286393,0.000082730876,0.00003665835,0.00006711803,0.00003385938,0.00025889155,0.000007215573,0.00011632364,0.000008276434],"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":[0.000010060705,0.000017793287,0.00045645022,0.0000143526695,0.00006326513,0.000010839902,0.000042065625,0.9842211,0.0007823709,0.00053078675,0.0011850954,0.012665799],"study_design_scores_gemma":[0.00062054856,0.00009118833,0.0038028273,0.00010246063,0.000021059896,0.000055144577,0.00003438984,0.99333155,0.0011304737,0.000172205,0.0005313827,0.000106742504],"about_ca_topic_score_codex":0.000005709697,"about_ca_topic_score_gemma":0.000003350963,"teacher_disagreement_score":0.9240597,"about_ca_system_score_codex":0.0000693912,"about_ca_system_score_gemma":0.000026267659,"threshold_uncertainty_score":0.33736673},"labels":[],"label_agreement":null},{"id":"W2010124866","doi":"10.2316/journal.206.2006.2.206-2795","title":"FUZZY REINFORCEMENT LEARNING FOR EMBEDDED SOCCER AGENTS IN A MULTI-AGENT CONTEXT","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reinforcement learning; Computer science; Fuzzy logic; Context (archaeology); Artificial intelligence; Reinforcement; Machine learning; Engineering","score_opus":0.03483910685198837,"score_gpt":0.30849806606312313,"score_spread":0.27365895921113476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010124866","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":[0.0077207335,0.00004978112,0.98993194,0.0011371727,0.00074201194,0.00014804395,2.835257e-7,0.00002053605,0.00024951],"genre_scores_gemma":[0.9138546,0.00004148812,0.08533664,0.00024038457,0.0000711937,0.000003786661,0.000009998437,0.00000717938,0.00043474595],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868596,0.000045571167,0.00059237203,0.00011251557,0.00042882707,0.00013475354],"domain_scores_gemma":[0.9986573,0.000080759186,0.0005656063,0.00007082856,0.0005891662,0.00003638141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051424094,0.00010034713,0.00014304339,0.00026632764,0.000048140748,0.00024450492,0.0003389928,0.00004359551,0.000003639423],"category_scores_gemma":[0.00017394587,0.000093328585,0.00005761569,0.00011369688,0.000016814038,0.0005582566,0.00008785961,0.00014718284,0.0000031733675],"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":[0.000010855594,0.000037727226,0.0021553356,0.000008149954,0.000030907777,0.00000970397,0.00039359948,0.9575871,0.00016351043,0.035028413,0.00021946522,0.004355224],"study_design_scores_gemma":[0.0015884537,0.00011359212,0.014533644,0.00009704919,0.000007267307,0.000026247606,0.00005809929,0.9813913,0.00015130336,0.0009143032,0.0010237122,0.00009500883],"about_ca_topic_score_codex":0.000018972603,"about_ca_topic_score_gemma":0.00000725642,"teacher_disagreement_score":0.90613383,"about_ca_system_score_codex":0.0001359486,"about_ca_system_score_gemma":0.000073266485,"threshold_uncertainty_score":0.38058293},"labels":[],"label_agreement":null},{"id":"W2010769377","doi":"10.2316/journal.206.2008.1.206-3083","title":"TARGET TRACKING ROBOTIC MANIPULATION THEORIES APPLIED TO FORCE/POSITION CONTROL IN PEG-IN-HOLE ASSEMBLY TASKS","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Tracking (education); Position (finance); Position tracking; Computer science; Control (management); PEG ratio; Computer vision; Artificial intelligence; Control theory (sociology); Control engineering; Engineering; Actuator; Psychology","score_opus":0.012469046692253408,"score_gpt":0.24152964204810964,"score_spread":0.22906059535585624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010769377","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":[0.31540608,0.00006361759,0.683017,0.0005055012,0.00044104035,0.000121039,4.670342e-7,0.000034384324,0.00041087365],"genre_scores_gemma":[0.993842,0.000029548806,0.005827171,0.000107344335,0.00014531593,0.0000033520917,0.000011697179,0.000016996646,0.000016540656],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989299,0.000032581574,0.0005186798,0.00008835521,0.00030614994,0.00012431967],"domain_scores_gemma":[0.9995477,0.000069108544,0.00015033636,0.00004629276,0.00013801259,0.000048531816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028217642,0.0001095939,0.00018852274,0.00048679675,0.00004099037,0.00007342284,0.00010111103,0.00006322387,0.000012337546],"category_scores_gemma":[0.000047825695,0.00011390236,0.00003880792,0.00014394434,0.000012042228,0.00040422028,0.000010761673,0.00018062613,0.0000054697653],"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":[0.000030062301,0.000022729902,0.008511954,0.000009717337,0.000021729596,0.00002723868,0.0007801425,0.97960466,0.0042460016,0.005077382,0.00002093723,0.0016474524],"study_design_scores_gemma":[0.00080539205,0.000028212371,0.23025922,0.00008641846,0.0000063730677,0.000067515924,0.00008570566,0.7670514,0.00026468228,0.0012267808,0.000018937268,0.00009934636],"about_ca_topic_score_codex":0.0000056230847,"about_ca_topic_score_gemma":0.000012640063,"teacher_disagreement_score":0.678436,"about_ca_system_score_codex":0.00015836408,"about_ca_system_score_gemma":0.000017866565,"threshold_uncertainty_score":0.46448034},"labels":[],"label_agreement":null},{"id":"W2011371349","doi":"10.2316/journal.206.2008.3.206-3052","title":"AN APPROACH TO OUTPUT FEEDBACK ADAPTIVE CONTROL FOR ROBOT MANIPULATORS","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Robot manipulator; Computer science; Adaptive control; Control (management); Control engineering; Feedback control; Robot; Engineering; Artificial intelligence","score_opus":0.02848700602558801,"score_gpt":0.24972245796962736,"score_spread":0.22123545194403935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011371349","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":[0.056428857,0.00011144994,0.94210875,0.00017697588,0.00075710216,0.000189339,0.000016465114,0.00003897164,0.00017210543],"genre_scores_gemma":[0.9273421,0.0000131032,0.071926184,0.000062029445,0.00059779565,0.0000050274452,0.0000069518715,0.000020861637,0.00002591419],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991237,0.000019852685,0.00038400313,0.00008475973,0.00028187217,0.00010579744],"domain_scores_gemma":[0.99912715,0.0000554678,0.00014862427,0.00006065098,0.0005024457,0.00010566036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017903895,0.000110872636,0.00020437318,0.00018299576,0.000039230723,0.000045331275,0.00017622106,0.00005207057,0.0000011671088],"category_scores_gemma":[0.00003905862,0.00010183929,0.00006976982,0.00004301315,0.000014444243,0.00030184802,0.000008130132,0.00008127478,0.000003173653],"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":[0.000063891355,0.00004768138,0.00037919692,0.000007503606,0.00017017589,0.0000062665213,0.00025624444,0.99306357,0.0009900894,0.001689622,0.0002697845,0.0030559679],"study_design_scores_gemma":[0.0012231055,0.00016974338,0.017141536,0.00003507342,0.000023772804,0.00019151931,0.00008266271,0.9804146,0.000086435364,0.00013027442,0.00038810103,0.000113164024],"about_ca_topic_score_codex":0.0000025808315,"about_ca_topic_score_gemma":0.0000011852306,"teacher_disagreement_score":0.87091327,"about_ca_system_score_codex":0.0000935082,"about_ca_system_score_gemma":0.000023862163,"threshold_uncertainty_score":0.41528857},"labels":[],"label_agreement":null},{"id":"W2011445483","doi":"10.2316/journal.206.2004.4.206-2802","title":"Active Sensing of Visual and Tactile Stimuli by Brain-based Devices","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Neuroscience; Neurophysiology; Neuromorphic engineering; Artificial intelligence; Sensory system; Artificial neural network; Psychology","score_opus":0.015447783094633922,"score_gpt":0.2911577708925445,"score_spread":0.2757099877979106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011445483","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":[0.95726764,0.000018973635,0.03861112,0.0036607117,0.00033896757,0.000041961546,0.000010473812,0.0000073826177,0.00004275828],"genre_scores_gemma":[0.997844,0.000020594842,0.0015644046,0.0005027486,0.000051694646,1.0209819e-7,0.000003194651,0.000005238741,0.000008038184],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993153,0.000026975633,0.00023166013,0.00008584285,0.00028362265,0.000056572066],"domain_scores_gemma":[0.99919426,0.00020408657,0.00037098106,0.000023763476,0.00017012577,0.000036804642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009215093,0.000063087464,0.000096059375,0.000117363525,0.000042489522,0.00006267267,0.000057808462,0.000029228457,0.0000032633714],"category_scores_gemma":[0.00021584795,0.000054308897,0.000029244178,0.000057682144,0.000048654496,0.00026087894,0.000017428349,0.000079442165,3.855938e-7],"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":[0.00010960686,0.00011548776,0.00025858384,0.000017210523,0.0000242234,0.000019749092,0.00015597043,0.063625425,0.8941739,0.0017028438,0.000065371234,0.039731596],"study_design_scores_gemma":[0.0022153014,0.0006126732,0.009549457,0.00024782354,0.00003263837,0.0002897492,0.00011412835,0.5554211,0.4271098,0.003944041,0.00029294856,0.00017029609],"about_ca_topic_score_codex":0.000010929117,"about_ca_topic_score_gemma":0.000002883666,"teacher_disagreement_score":0.4917957,"about_ca_system_score_codex":0.00003898962,"about_ca_system_score_gemma":0.00003750795,"threshold_uncertainty_score":0.22146524},"labels":[],"label_agreement":null},{"id":"W2012339379","doi":"10.2316/journal.206.2011.1.206-3417","title":"DEVELOPMENT OF A COMPREHENSIVE SOFTWARE SYSTEM FOR IMPLEMENTING COOPERATIVE CONTROL OF MULTIPLE UNMANNED AERIAL VEHICLES","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Software deployment; Software; Architecture; Focus (optics); Computer science; Software architecture; Real-time computing; Embedded system; Control (management); Systems engineering; Control software; Engineering; Software engineering; Operating system; Artificial intelligence","score_opus":0.03729884440725432,"score_gpt":0.26582143965573907,"score_spread":0.22852259524848476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012339379","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":[0.17239201,0.00004739055,0.8267305,0.000044982422,0.0005447637,0.00018598618,0.00003521003,0.0000126087,0.000006552419],"genre_scores_gemma":[0.82042474,0.0000014506343,0.17950048,0.000008343893,0.000047921603,0.0000046707332,0.0000071768463,0.00000385064,0.000001338899],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985921,0.00004808326,0.00083879865,0.00009390249,0.00032407814,0.00010304167],"domain_scores_gemma":[0.99698,0.00016966306,0.0011716466,0.00006895743,0.0015714242,0.00003831136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034802544,0.000087735854,0.0002595748,0.00013547436,0.00005142,0.0000454499,0.00034528627,0.000033464832,0.000001046694],"category_scores_gemma":[0.00008541019,0.000076388686,0.00006990805,0.000054108517,0.000021737986,0.00029267388,0.00006149909,0.000038213024,3.4514133e-7],"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":[0.0021014938,0.001504315,0.02541897,0.0014663488,0.007084366,0.00006803044,0.0412273,0.08235282,0.42762992,0.21679233,0.00027664265,0.19407746],"study_design_scores_gemma":[0.010332594,0.00034925353,0.022042057,0.000824704,0.000079712605,0.00007722476,0.0019332094,0.88678116,0.07677751,0.00024315319,0.00032671427,0.00023270557],"about_ca_topic_score_codex":0.000009283924,"about_ca_topic_score_gemma":0.0000046670716,"teacher_disagreement_score":0.80442834,"about_ca_system_score_codex":0.00006270422,"about_ca_system_score_gemma":0.00011281702,"threshold_uncertainty_score":0.31150404},"labels":[],"label_agreement":null},{"id":"W2012533933","doi":"10.2316/journal.206.2005.2.206-2785","title":"Colour Image Watermarking using a Visual Sub-Band Decompositino","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Digital watermarking; Image (mathematics); Computer science; Computer vision; Artificial intelligence","score_opus":0.010310040829121531,"score_gpt":0.29055396688929663,"score_spread":0.2802439260601751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012533933","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":[0.3395252,0.000051961993,0.6592508,0.00081124494,0.00024572187,0.000027932054,5.7458783e-7,0.000033668617,0.000052906587],"genre_scores_gemma":[0.70343554,0.000049331316,0.29625806,0.00009451195,0.00015504491,3.066921e-7,9.932278e-7,0.0000037808647,0.000002435615],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912614,0.000035797977,0.00034570604,0.000096426564,0.00028819282,0.000107719745],"domain_scores_gemma":[0.9992013,0.00004234902,0.00033611667,0.000059524315,0.0003127914,0.00004792978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025830348,0.00008644102,0.000113822534,0.00025008956,0.000078231526,0.0002830839,0.00033680352,0.000037392154,0.000001367933],"category_scores_gemma":[0.000014403071,0.00007504274,0.000062833715,0.00007595627,0.000029149433,0.0011904452,0.00007492222,0.000102576305,7.371705e-7],"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":[0.00011549762,0.0003823028,0.00739141,0.000037905233,0.00032673622,0.00030562928,0.0019033112,0.055383116,0.54031944,0.020689512,0.0002860413,0.3728591],"study_design_scores_gemma":[0.00064140116,0.00012362293,0.005442062,0.00020802606,0.00001922771,0.001140952,0.000013378435,0.83077455,0.15407999,0.0067718425,0.0005907241,0.00019424458],"about_ca_topic_score_codex":0.0000016868203,"about_ca_topic_score_gemma":7.428319e-7,"teacher_disagreement_score":0.7753914,"about_ca_system_score_codex":0.000060062946,"about_ca_system_score_gemma":0.000027724684,"threshold_uncertainty_score":0.3060154},"labels":[],"label_agreement":null},{"id":"W2013068785","doi":"10.2316/journal.206.2010.2.206-3359","title":"A MULTI-OBJECTIVE GA BASED ALGORITHM FOR 2D FORM AND FORCE CLOSURE GRASP OF PRISMATIC OBJECTS","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"GRASP; Closure (psychology); Boundary (topology); Algorithm; Object (grammar); Computer science; Mathematics; Geometry; Artificial intelligence; Mathematical analysis; Programming language","score_opus":0.006565564977742109,"score_gpt":0.23159407018205488,"score_spread":0.22502850520431278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013068785","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":[0.08811995,0.00009296578,0.9110748,0.000079301884,0.0004713431,0.00010928907,0.000010349874,0.000017385699,0.00002459866],"genre_scores_gemma":[0.7122174,0.0000393971,0.2876351,0.000011649946,0.000064048945,0.0000025828838,0.0000074028944,0.000008955901,0.0000134878155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994472,0.000004592838,0.00027556258,0.000055255085,0.00015533235,0.00006202085],"domain_scores_gemma":[0.9993366,0.00006973106,0.00020058999,0.000035904097,0.0003230244,0.000034173467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015356351,0.00007590018,0.000121565376,0.00014486129,0.000025684474,0.00004630414,0.00007003595,0.000056295754,0.0000034479128],"category_scores_gemma":[0.000048880604,0.00006693059,0.00003876283,0.00003114449,0.000017899314,0.0002060341,0.000009429815,0.00009482656,9.7229034e-8],"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":[0.000043741125,0.00012892127,0.001056012,0.00052743906,0.00032656512,0.000004752303,0.0019256924,0.72025514,0.0063558435,0.000878833,0.000073283,0.2684238],"study_design_scores_gemma":[0.0008912084,0.00006311996,0.005705203,0.00008817043,0.000032807,0.00002419508,0.000042412532,0.9837622,0.008480372,0.00081129,0.0000313949,0.000067618894],"about_ca_topic_score_codex":0.0000018177832,"about_ca_topic_score_gemma":0.000009374561,"teacher_disagreement_score":0.62409747,"about_ca_system_score_codex":0.00001526233,"about_ca_system_score_gemma":0.000020821031,"threshold_uncertainty_score":0.27293503},"labels":[],"label_agreement":null},{"id":"W2013280834","doi":"10.2316/journal.206.2011.4.206-3515","title":"AUTOMATIC TOOL TRUING FOR AN LED LENS CAVITY LAPPING SYSTEM","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Lapping; Lens (geology); Computer science; Optics; Materials science; Physics; Metallurgy","score_opus":0.023949538165609113,"score_gpt":0.23481421274022962,"score_spread":0.21086467457462052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013280834","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":[0.4169741,0.00004313009,0.58171713,0.00003043363,0.0007967262,0.00008155988,0.000003870811,0.00009321592,0.00025985079],"genre_scores_gemma":[0.9418896,0.000028770874,0.05790077,0.000009846416,0.00014239959,0.0000029599,0.0000067032506,0.000012970934,0.0000059791055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993524,0.000010860081,0.00034002168,0.000058027654,0.00016049604,0.00007819537],"domain_scores_gemma":[0.9994923,0.00002678095,0.00017285475,0.000046380675,0.00023076493,0.000030958996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021952324,0.00007998867,0.00012247139,0.0001349547,0.000041378225,0.000080132035,0.000112648624,0.000045106848,0.000008244516],"category_scores_gemma":[0.000028121152,0.00007352178,0.00004024592,0.000028566203,0.000007920284,0.0005358486,0.000009531378,0.000059653066,7.2875713e-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":[0.000022987691,0.00004567098,0.0005402398,0.00039066884,0.00018349924,0.000007311424,0.0022900493,0.9296911,0.00093145965,0.005644809,0.00006227792,0.060189962],"study_design_scores_gemma":[0.0003646925,0.000055180382,0.0047015045,0.00018583634,0.000029273553,0.000060377424,0.000107536674,0.9921523,0.001891758,0.00031712002,0.000047482925,0.000086947526],"about_ca_topic_score_codex":0.0000045741094,"about_ca_topic_score_gemma":0.0000026022535,"teacher_disagreement_score":0.5249155,"about_ca_system_score_codex":0.00006757407,"about_ca_system_score_gemma":0.000013984162,"threshold_uncertainty_score":0.29981312},"labels":[],"label_agreement":null},{"id":"W2013454774","doi":"10.2316/journal.206.2007.1.206-1009","title":"DESIGN, DEVELOPMENT AND LOCOMOTION CONTROL OF BIO-FISH ROBOT WITH UNDULATING ANAL FINS","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Biomimetic flight and propulsion mechanisms","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Servomotor; Propulsion; Robot; Fish fin; Hydraulic cylinder; Modular design; Fin; Marine engineering; Piston (optics); Engineering; Actuator; Buoyancy; Control system; Simulation; Mechanical engineering; Computer science; Fish <Actinopterygii>; Electrical engineering; Aerospace engineering","score_opus":0.012401005734349742,"score_gpt":0.2206650786541383,"score_spread":0.20826407291978857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013454774","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":[0.1866014,0.000066334294,0.812902,0.00016279679,0.00018069008,0.00004439152,8.597298e-7,0.000010327106,0.000031218366],"genre_scores_gemma":[0.8449438,0.000021605303,0.15495892,0.000018403549,0.000043722728,2.4553444e-7,0.0000023591988,0.0000059670856,0.0000049230275],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930483,0.000011810413,0.00034290555,0.00004437486,0.00022888379,0.00006720959],"domain_scores_gemma":[0.99950576,0.000056565557,0.00017583935,0.000024056268,0.00019656918,0.000041198713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039000675,0.0000689985,0.00011038199,0.00016907071,0.000025084593,0.000031853877,0.00005418266,0.000042262778,0.000008199315],"category_scores_gemma":[0.000012216513,0.000054604996,0.000014740523,0.00005336502,0.000016780827,0.00011800766,0.000007978938,0.000065482185,2.981357e-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":[0.00022202393,0.000101606995,0.0043892395,0.00010811843,0.0005523052,0.000049919916,0.0012536066,0.4991049,0.13499843,0.0027032513,0.00007477416,0.35644186],"study_design_scores_gemma":[0.0028561994,0.0003981773,0.06303384,0.0004995259,0.000078730234,0.00030626383,0.00016694571,0.6821709,0.24877606,0.0012184642,0.00023919907,0.00025563315],"about_ca_topic_score_codex":0.000001370677,"about_ca_topic_score_gemma":0.0000037888378,"teacher_disagreement_score":0.6583424,"about_ca_system_score_codex":0.00003221294,"about_ca_system_score_gemma":0.000017604068,"threshold_uncertainty_score":0.2226727},"labels":[],"label_agreement":null},{"id":"W2014143213","doi":"10.2316/journal.206.2011.1.206-0001","title":"PREFACE: SPECIAL ISSUE ON NEW ADVANCES IN NONLINEAR AND OPTIMAL CONTROLS OF ROBOTIC AND AUTONOMOUS SYSTEMS","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Nonlinear system; Control engineering; Engineering; Physics","score_opus":0.015118927941882451,"score_gpt":0.2557618711183249,"score_spread":0.24064294317644241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014143213","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":[0.14831045,0.0033847792,0.84144294,0.0014591806,0.003953235,0.00048093317,0.00001816353,0.000033889904,0.0009164177],"genre_scores_gemma":[0.97708744,0.0002640351,0.021907518,0.000024374438,0.00066384237,0.0000011555113,0.0000017938429,0.0000051433285,0.00004468445],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988658,0.000049746777,0.0005442104,0.00013138879,0.00031248666,0.000096369964],"domain_scores_gemma":[0.9990176,0.00008603001,0.00053811475,0.00007607801,0.00020461433,0.000077539764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002869317,0.000101283185,0.0002554457,0.00020960682,0.000019585685,0.00012745326,0.00025244695,0.00004787633,0.000003601929],"category_scores_gemma":[0.00007189667,0.00008753179,0.00002822452,0.000060547904,0.000032725042,0.0006804942,0.000053319156,0.00009321744,0.0000013259145],"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":[0.0003615703,0.00050600484,0.010782645,0.00014616842,0.0003427659,0.00016964211,0.0043819556,0.63109624,0.0011732307,0.09451031,0.00028905208,0.25624043],"study_design_scores_gemma":[0.0023665447,0.00038430217,0.02589878,0.00035103955,0.000019860763,0.00019576841,0.0001013549,0.96879476,0.00018634631,0.00053902896,0.0010372845,0.00012489969],"about_ca_topic_score_codex":0.000031602773,"about_ca_topic_score_gemma":0.000005906233,"teacher_disagreement_score":0.828777,"about_ca_system_score_codex":0.00004402705,"about_ca_system_score_gemma":0.000059509366,"threshold_uncertainty_score":0.3569443},"labels":[],"label_agreement":null},{"id":"W2017705302","doi":"10.2316/journal.206.2007.1.206-1000","title":"SOFT TISSUE DEFORMATION WITH NEURAL DYNAMICS FOR SURGERY SIMULATION","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Isotropy; Artificial neural network; Deformation (meteorology); Computer science; Haptic technology; Stability (learning theory); Lyapunov function; Control theory (sociology); Artificial intelligence; Classical mechanics; Physics; Control (management); Nonlinear system; Optics; Machine learning","score_opus":0.011175591507452327,"score_gpt":0.2562654609720601,"score_spread":0.24508986946460778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017705302","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":[0.2236912,0.00004683086,0.7757662,0.000161049,0.0002592567,0.000027594853,0.0000031972816,0.000023951363,0.000020703927],"genre_scores_gemma":[0.9907084,0.000017340344,0.009032105,0.000018882689,0.00016814299,4.169977e-7,0.000036121302,0.000009837054,0.000008740631],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993534,0.0000045905335,0.0003276697,0.000037517297,0.0002036808,0.00007312268],"domain_scores_gemma":[0.99927264,0.00015766844,0.00015089186,0.000027910344,0.00035818154,0.000032704935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031414008,0.000062934625,0.00010275672,0.00022264982,0.000029686536,0.00006045352,0.000049668364,0.000034763856,0.000001825386],"category_scores_gemma":[0.000040227576,0.00005274143,0.00004180703,0.000058699927,0.000008328912,0.00030070325,0.0000040142922,0.000053495492,5.028757e-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":[0.000017762623,0.0000074516474,0.00062156556,0.000013705368,0.00005248978,0.000002307236,0.000064794105,0.91635185,0.00008905675,0.00013039203,0.000018138044,0.08263046],"study_design_scores_gemma":[0.00018046566,0.000026097807,0.0019305112,0.000042820033,0.00003091472,0.000033908025,0.000040637005,0.9970863,0.0002176145,0.00029911465,0.000049472175,0.00006215638],"about_ca_topic_score_codex":0.0000015683313,"about_ca_topic_score_gemma":0.000013571362,"teacher_disagreement_score":0.76701725,"about_ca_system_score_codex":0.00007158394,"about_ca_system_score_gemma":0.000010452839,"threshold_uncertainty_score":0.21507332},"labels":[],"label_agreement":null},{"id":"W2019375826","doi":"10.2316/journal.206.2013.2.206-3539","title":"A NOVEL MOBILITY MODEL FOR MOBILE SENSORS DEPLOYMENT IN SURVEILLANCE SYSTEMS","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Software deployment; Computer science; Mobility model; Computer security; Real-time computing; Computer network; Operating system","score_opus":0.014915731312916717,"score_gpt":0.25220849802767464,"score_spread":0.23729276671475794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019375826","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":[0.27734396,0.000082690865,0.72147053,0.00040925213,0.00051334786,0.00015305773,0.0000019355866,0.000014559947,0.000010648934],"genre_scores_gemma":[0.9170136,0.000037716956,0.08279356,0.00003573345,0.00006624651,0.000016274613,0.0000018223247,0.00000546528,0.00002957594],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989595,0.000026552587,0.00044971338,0.00012812622,0.00032026015,0.00011585705],"domain_scores_gemma":[0.99882,0.00014816456,0.00032019938,0.00010056064,0.00056330214,0.00004777783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003904408,0.000079754354,0.0001431984,0.00014899106,0.000024460463,0.00019612674,0.00032621733,0.000043825217,6.600829e-7],"category_scores_gemma":[0.000043705557,0.00006991947,0.00004501339,0.000078956764,0.000016820488,0.00040000095,0.00005482499,0.00007522634,8.4997384e-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":[0.000004249369,0.000097522854,0.0006507165,0.000007699573,0.000015953312,0.000001341385,0.00014692922,0.98897225,0.0007773933,0.006570053,0.000050791983,0.002705118],"study_design_scores_gemma":[0.00048194875,0.0000433477,0.0041492013,0.000054608234,0.0000015947066,0.000044183114,0.000022088825,0.99464214,0.00006566684,0.0004020639,0.000023261631,0.00006991876],"about_ca_topic_score_codex":0.000031813142,"about_ca_topic_score_gemma":0.000008599857,"teacher_disagreement_score":0.63966966,"about_ca_system_score_codex":0.00010300445,"about_ca_system_score_gemma":0.00003689989,"threshold_uncertainty_score":0.28512335},"labels":[],"label_agreement":null},{"id":"W2019873548","doi":"10.2316/journal.206.2005.2.206-2781","title":"Colour Histogram Algorithms for Visual Robot Control","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Histogram; Color histogram; Histogram matching; Color normalization; Computer science; Video tracking; Object (grammar); Visual servoing; Adaptive histogram equalization; Robot; Histogram equalization; Pattern recognition (psychology); Color image; Image (mathematics); Image processing","score_opus":0.013238296494919437,"score_gpt":0.3233278162896373,"score_spread":0.3100895197947179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019873548","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00095952256,0.00015067893,0.98834926,0.009625425,0.0007867931,0.000065416636,0.0000015594796,0.000023623621,0.00003773993],"genre_scores_gemma":[0.4934755,0.000031276293,0.5056289,0.0005432514,0.00026579216,0.0000011940348,0.000001207749,0.0000036758595,0.000049224207],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921405,0.000015840358,0.0003177457,0.000087955326,0.00027489045,0.00008953934],"domain_scores_gemma":[0.99898183,0.00009190797,0.00031095356,0.00004721386,0.0005105363,0.000057550078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000235652,0.00006639855,0.00011070064,0.00014523407,0.000052766027,0.00016369096,0.0002822044,0.000024504618,0.000003556482],"category_scores_gemma":[0.00007633923,0.00005791131,0.00006256374,0.000047883113,0.000017508624,0.00074406364,0.00003386075,0.00006930731,0.0000024083483],"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":[0.00001908061,0.0000916189,0.00010565159,0.0000031665368,0.00004625407,0.0000055527826,0.00013968219,0.06662096,0.0018535927,0.012851734,0.0005178526,0.9177449],"study_design_scores_gemma":[0.0011862866,0.00012034366,0.0012404457,0.000029997398,0.000007725764,0.000113187445,0.000012555886,0.9856316,0.00038066233,0.002116673,0.009092951,0.00006760216],"about_ca_topic_score_codex":7.6130556e-7,"about_ca_topic_score_gemma":5.987196e-7,"teacher_disagreement_score":0.9190106,"about_ca_system_score_codex":0.00006970807,"about_ca_system_score_gemma":0.0000409232,"threshold_uncertainty_score":0.23615547},"labels":[],"label_agreement":null},{"id":"W2023454443","doi":"10.2316/journal.206.2013.3.206-3808","title":"SEMI-ACTIVE FUZZY OPTIMAL CONTROL OF A VEHICULAR MULTI-DIMENSIONAL VIBRATION ISOLATOR","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Isolator; Vibration isolation; Fuzzy logic; Computer science; Fuzzy control system; Vibration; Control theory (sociology); Control (management); Structural engineering; Automotive engineering; Acoustics; Engineering; Physics; Electrical engineering; Artificial intelligence","score_opus":0.004337561550152886,"score_gpt":0.20125142882152156,"score_spread":0.19691386727136867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023454443","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":[0.69560385,0.00019668629,0.30307057,0.00034951032,0.0005802004,0.00011964971,0.000014120301,0.000019031848,0.000046368612],"genre_scores_gemma":[0.99522364,0.000023185758,0.0045599327,0.00003476259,0.00012681859,0.0000035030691,0.000007214609,0.000011019161,0.000009917607],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991191,0.000021546119,0.00044044567,0.000056788285,0.00028511154,0.00007702974],"domain_scores_gemma":[0.9990555,0.00004572719,0.0002537791,0.00004437869,0.0005493473,0.000051250125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011988288,0.00008837334,0.00017651958,0.00012767322,0.000020071977,0.000058305588,0.00009654359,0.000059564372,0.00001639643],"category_scores_gemma":[0.000024286033,0.00007855061,0.00006962218,0.00003936403,0.000017796856,0.0003713892,0.000011440728,0.00009701652,0.0000038670296],"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":[0.000018343251,0.00003812678,0.00051647465,0.000013535821,0.0002473856,0.0000042580155,0.00011780668,0.933956,0.05946239,0.00087883865,0.00004529402,0.004701489],"study_design_scores_gemma":[0.0011483381,0.00005658689,0.017877793,0.000064509884,0.000024706844,0.0000587151,0.000041105617,0.9799139,0.0005553122,0.00016082116,0.000025979363,0.000072247014],"about_ca_topic_score_codex":0.000013198102,"about_ca_topic_score_gemma":0.0000015702585,"teacher_disagreement_score":0.2996198,"about_ca_system_score_codex":0.00005350265,"about_ca_system_score_gemma":0.00002249154,"threshold_uncertainty_score":0.3203201},"labels":[],"label_agreement":null},{"id":"W2023889025","doi":"10.2316/journal.206.2013.4.206-3702","title":"SUBDIVISION-BASED CORRIDOR MAP METHOD FOR PATH PLANNING","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Subdivision; Path (computing); Computer science; Geography; Archaeology; Computer network","score_opus":0.01748591853544828,"score_gpt":0.3005014314257354,"score_spread":0.2830155128902871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023889025","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012077361,0.000044726952,0.99388635,0.0036177773,0.0010871796,0.00008976927,0.0000037954642,0.000019017114,0.000043621756],"genre_scores_gemma":[0.1555584,0.0000059431572,0.843719,0.0004274587,0.00018647421,0.0000036770257,0.000015441861,0.0000046457694,0.00007892344],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926376,0.000020437852,0.00025861477,0.00008968235,0.00028904693,0.000078444406],"domain_scores_gemma":[0.9990706,0.0001532067,0.00028277008,0.00007320005,0.00037790212,0.000042334035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003596765,0.00006204982,0.00008856562,0.00016176433,0.000043106807,0.00042942344,0.0004357979,0.000020700874,0.000008913584],"category_scores_gemma":[0.000055790835,0.000050688446,0.000046149766,0.000046950547,0.000008078332,0.0008590608,0.00006797863,0.00004983921,0.000005478753],"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":[0.000021927975,0.00018453678,0.0018798257,0.000057872738,0.00019526976,0.0000365835,0.00037140617,0.106878266,0.0007419038,0.14897865,0.03524932,0.70540446],"study_design_scores_gemma":[0.00044924035,0.00007367699,0.0036960377,0.00006644731,0.000007270022,0.000010509535,0.00001679341,0.98531586,0.00015058988,0.007964189,0.0021889538,0.00006042174],"about_ca_topic_score_codex":0.0000049120536,"about_ca_topic_score_gemma":1.02657616e-7,"teacher_disagreement_score":0.8784376,"about_ca_system_score_codex":0.000021692787,"about_ca_system_score_gemma":0.000025831601,"threshold_uncertainty_score":0.414094},"labels":[],"label_agreement":null},{"id":"W2024529901","doi":"10.2316/journal.206.2006.1.206-2726","title":"PD CONTROL OF ROBOT WITH VELOCITY ESTIMATION AND UNCERTAINTIES COMPENSATION","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Observer (physics); Compensation (psychology); Lyapunov function; Computer science; Artificial neural network; State observer; Robot; Stability (learning theory); Control (management); Mathematics; Artificial intelligence; Physics; Nonlinear system; Machine learning","score_opus":0.006097094882885569,"score_gpt":0.2102367346062417,"score_spread":0.20413963972335614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024529901","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":[0.272337,0.00024428422,0.7268208,0.00027123222,0.00017912767,0.000057812686,0.000005500093,0.000015699938,0.00006850787],"genre_scores_gemma":[0.9780539,0.000021580232,0.021776339,0.000007996678,0.000118296935,6.645987e-7,0.0000070286146,0.0000075501675,0.000006595109],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930567,0.00001788869,0.00033915558,0.000042617146,0.00024549558,0.000049148442],"domain_scores_gemma":[0.9992094,0.0000736663,0.0002603112,0.000029739882,0.00040690746,0.000019961131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015339094,0.00007200575,0.00015469948,0.00012323473,0.000017696606,0.000041830226,0.000052672396,0.000031751777,0.000001824123],"category_scores_gemma":[0.000023954373,0.00005988207,0.00002099074,0.000034968663,0.000032184907,0.00024250781,0.000005667218,0.00005775275,3.5522416e-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":[0.00003348313,0.000016156788,0.002125897,0.000022874052,0.00008690019,0.000003289192,0.00006551989,0.98525417,0.002336312,0.003073875,0.000022759166,0.006958737],"study_design_scores_gemma":[0.00093721814,0.00007666387,0.06117021,0.00010707725,0.000029672752,0.000067262896,0.00003436639,0.9365058,0.00035633383,0.00061985326,0.000038902366,0.00005663904],"about_ca_topic_score_codex":0.000019300032,"about_ca_topic_score_gemma":0.000014599633,"teacher_disagreement_score":0.70571697,"about_ca_system_score_codex":0.00004552974,"about_ca_system_score_gemma":0.000016239448,"threshold_uncertainty_score":0.24419199},"labels":[],"label_agreement":null},{"id":"W2025233594","doi":"10.2316/journal.206.2010.2.206-3211","title":"UNIFICATION AND SIMPLIFICATION OF DYNAMICS OF LIMITED-DOF PARALLEL MANIPULATORS WITH LINEAR ACTIVE LEGS","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Unification; Dynamics (music); Computer science; Control theory (sociology); Applied mathematics; Mathematics; Physics; Artificial intelligence; Programming language","score_opus":0.006996841579453723,"score_gpt":0.22169371926982936,"score_spread":0.21469687769037565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025233594","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":[0.4791619,0.00001659013,0.5202509,0.000201605,0.00021714084,0.000052280953,0.000008501526,0.000010015585,0.00008104728],"genre_scores_gemma":[0.88610613,0.00013149469,0.113680035,0.000004520099,0.000039488765,5.680229e-7,0.000021935432,0.000010086364,0.0000057163406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992785,0.000008687047,0.0003720732,0.000059374466,0.00022850548,0.000052883406],"domain_scores_gemma":[0.9990681,0.000048233105,0.00035902098,0.00007174084,0.0004134918,0.00003942403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001311433,0.00007875201,0.00014208369,0.000166715,0.00001580918,0.000018517501,0.000095602256,0.0000656115,0.0000036852564],"category_scores_gemma":[0.000031006293,0.00006766508,0.000025433592,0.000065984575,0.000040473744,0.00020459715,0.000012500343,0.0001285555,1.8898066e-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":[0.00004246462,0.00004808945,0.0014888425,0.000050783143,0.00011912286,0.0000017421982,0.00023820998,0.8215027,0.017086163,0.14586307,0.0000044343637,0.013554395],"study_design_scores_gemma":[0.0003692432,0.000085246706,0.026045876,0.000059116523,0.000036045887,0.000060091454,0.00012278394,0.96877897,0.001091992,0.0032751076,0.000007172945,0.00006834994],"about_ca_topic_score_codex":0.0000061139094,"about_ca_topic_score_gemma":0.00001806983,"teacher_disagreement_score":0.40694427,"about_ca_system_score_codex":0.000025966325,"about_ca_system_score_gemma":0.000020922955,"threshold_uncertainty_score":0.2759302},"labels":[],"label_agreement":null},{"id":"W2025673320","doi":"10.2316/journal.206.2007.4.206-3036","title":"ON THE DYNAMIC TIP-OVER STABILITY OF WHEELED MOBILE MANIPULATORS","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Measure (data warehouse); Computer science; Stability (learning theory); Code (set theory); Control theory (sociology); MATLAB; Mobile robot; Moment (physics); Robot; Serial manipulator; Motion (physics); Simulation; Artificial intelligence; Parallel manipulator; Control (management)","score_opus":0.006820552175676471,"score_gpt":0.23538613248141563,"score_spread":0.22856558030573915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025673320","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":[0.8259751,0.00006310997,0.1726234,0.00024249022,0.0006213504,0.0000829393,0.0000020061896,0.00001576519,0.00037384595],"genre_scores_gemma":[0.9991872,0.000030883108,0.000676897,0.000041997024,0.000045248253,7.2225635e-7,0.0000014124607,0.000006512173,0.0000091657885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925107,0.000015154941,0.00035195705,0.00003853362,0.00028090514,0.000062362255],"domain_scores_gemma":[0.99946064,0.0001405316,0.00014605979,0.00006076795,0.00016252534,0.000029492303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039904914,0.00006124963,0.000097260934,0.00009296236,0.000017012655,0.00002521696,0.000116574185,0.000032349104,0.00006679634],"category_scores_gemma":[0.000041703388,0.000042902473,0.00005377803,0.000045599627,0.000021662512,0.00009146951,0.000009530679,0.000098653385,0.0000020850332],"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":[0.00006554087,0.00013763204,0.0026099293,0.000030383748,0.00026950845,0.000010990654,0.00052626187,0.92365915,0.010395229,0.031873856,0.00023225699,0.030189274],"study_design_scores_gemma":[0.0007911629,0.00011331152,0.062272925,0.00008524129,0.000024427029,0.000031052943,0.00015853185,0.93000394,0.0028528983,0.0034559132,0.00012032762,0.000090277514],"about_ca_topic_score_codex":0.0000016731107,"about_ca_topic_score_gemma":0.000004591724,"teacher_disagreement_score":0.17321207,"about_ca_system_score_codex":0.00006961047,"about_ca_system_score_gemma":0.000010077953,"threshold_uncertainty_score":0.17495121},"labels":[],"label_agreement":null},{"id":"W2025979857","doi":"10.2316/journal.206.2012.1.206-3581","title":"DYNAMIC PERFORMANCE EVALUATION OF A THREE TRANSLATIONAL DEGREES OF FREEDOM PARALLEL ROBOT","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Degrees of freedom (physics and chemistry); Computer science; Robot; Artificial intelligence; Physics","score_opus":0.022183480372223126,"score_gpt":0.25847025646039307,"score_spread":0.23628677608816995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025979857","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":[0.33272085,0.0005398818,0.66577846,0.000071050825,0.0006878939,0.000066368186,0.000006341629,0.000008781893,0.0001203663],"genre_scores_gemma":[0.7773509,0.00014367767,0.22242482,0.0000017935366,0.00005778156,9.785324e-7,0.00000991438,0.000007828096,0.0000022901988],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998654,0.000019389247,0.00052040437,0.000041636908,0.0006770918,0.00008745056],"domain_scores_gemma":[0.99899143,0.000048161404,0.00029479165,0.00005716127,0.0005658697,0.000042613654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006286046,0.00008495865,0.00016314903,0.0001771347,0.000015999005,0.000013042701,0.00012340574,0.000055417502,0.00002692336],"category_scores_gemma":[0.00003359608,0.00007712323,0.00006224831,0.000060989147,0.000027405133,0.00038862618,0.000011288096,0.000079468606,7.628447e-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":[0.000013055909,0.000042011823,0.0036893804,0.000028628418,0.00010463202,1.94975e-7,0.00017760457,0.9694823,0.001483896,0.006521973,0.000005596378,0.018450724],"study_design_scores_gemma":[0.0005360463,0.000041087966,0.13011156,0.00009434658,0.00006925351,0.00003235939,0.000021628946,0.86804265,0.00007234742,0.0009167556,0.000002547026,0.000059421625],"about_ca_topic_score_codex":0.0000031640318,"about_ca_topic_score_gemma":0.000008106554,"teacher_disagreement_score":0.44463006,"about_ca_system_score_codex":0.000046549794,"about_ca_system_score_gemma":0.000038082166,"threshold_uncertainty_score":0.3144994},"labels":[],"label_agreement":null},{"id":"W2026435861","doi":"10.2316/journal.206.2013.3.206-3818","title":"AN IMMUNE SMALL WORLD ALGORITHM FOR MOTION PLANNING OF THE MOBILE MANIPULATOR","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Mobile manipulator; Motion planning; Motion (physics); Manipulator (device); Artificial intelligence; Algorithm; Mobile robot; Robot","score_opus":0.019171233038172364,"score_gpt":0.27398062117937094,"score_spread":0.2548093881411986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026435861","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034923084,0.00010518903,0.9630355,0.00049695023,0.0012345404,0.0001664531,0.000002678075,0.000016539214,0.000019039018],"genre_scores_gemma":[0.4864089,0.0000037831876,0.51336503,0.00004185174,0.00013225037,0.0000052358064,0.000002948442,0.0000052504406,0.000034771685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990011,0.000040065726,0.00044943084,0.00009863778,0.00031585232,0.00009493757],"domain_scores_gemma":[0.99853116,0.00009194234,0.00060670095,0.00014172947,0.0005837547,0.000044699205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000331829,0.00008037603,0.00013364012,0.00017783607,0.00005778517,0.00016111232,0.00064371084,0.000034435998,0.0000026765092],"category_scores_gemma":[0.00003671469,0.000059212613,0.00007201393,0.00010879015,0.000024844676,0.00060058566,0.00006665091,0.00009338136,9.912966e-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":[0.0000041665744,0.00013272658,0.0022889704,0.000014818748,0.000097343924,0.000004646859,0.0007910813,0.49649426,0.0037135517,0.0047454266,0.000110969144,0.49160203],"study_design_scores_gemma":[0.00034057716,0.00010043041,0.04273589,0.0001121307,0.000010195305,0.00007003318,0.00003966168,0.95220256,0.0014954298,0.0027878792,0.00004336776,0.00006186351],"about_ca_topic_score_codex":0.000013601394,"about_ca_topic_score_gemma":3.527277e-7,"teacher_disagreement_score":0.49154016,"about_ca_system_score_codex":0.000041620173,"about_ca_system_score_gemma":0.000036785183,"threshold_uncertainty_score":0.24146204},"labels":[],"label_agreement":null},{"id":"W2026591771","doi":"10.2316/journal.206.2005.2.206-2780","title":"Combination of Multiple Pixel Classifiers for Microscopic Image Segmentation","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Pixel; Pattern recognition (psychology); Computer vision; Segmentation; Computer science; Image (mathematics); Image segmentation","score_opus":0.011030773208612609,"score_gpt":0.28067204569341325,"score_spread":0.26964127248480063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026591771","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":[0.10198216,0.00009979124,0.89678866,0.00074684335,0.00016786039,0.00009505392,0.000010122618,0.000031446736,0.0000780785],"genre_scores_gemma":[0.7222036,0.00007889959,0.27759644,0.000020023173,0.00006366378,0.0000043252016,0.0000146242955,0.000006725971,0.000011658001],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949,0.0000045699726,0.00029731664,0.000039008013,0.000121819394,0.000047236706],"domain_scores_gemma":[0.99937105,0.00003983743,0.0001845859,0.00003159136,0.00035447895,0.000018449096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112415764,0.00005162401,0.00007772384,0.00011618526,0.000024763121,0.00004442461,0.00008535784,0.000030710613,0.000002840205],"category_scores_gemma":[0.000029450917,0.00005135217,0.000033886245,0.000038581627,0.000021439439,0.00029309926,0.000007730393,0.00004520957,5.126477e-7],"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":[0.000021625954,0.00012430419,0.00051114464,0.00011337955,0.00008864755,3.7653075e-7,0.00041081928,0.046853412,0.7971905,0.00427925,0.0014094074,0.14899713],"study_design_scores_gemma":[0.0009117153,0.000055383207,0.0018233627,0.000092743816,0.000026462185,0.000017427914,0.00006394917,0.8230419,0.1699011,0.002809582,0.0011764093,0.00007992455],"about_ca_topic_score_codex":7.23261e-7,"about_ca_topic_score_gemma":9.4009715e-7,"teacher_disagreement_score":0.7761885,"about_ca_system_score_codex":0.000055810346,"about_ca_system_score_gemma":0.000013404766,"threshold_uncertainty_score":0.20940807},"labels":[],"label_agreement":null},{"id":"W2028650465","doi":"10.2316/journal.206.2013.4.206-3613","title":"DECENTRALIZED FORMATION CONTROL OF MULTIPLE AUTONOMOUS UNDERWATER VEHICLES","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Underwater; Control (management); Computer science; Marine engineering; Geology; Oceanography; Artificial intelligence; Engineering","score_opus":0.01111570930684065,"score_gpt":0.2174532818518221,"score_spread":0.20633757254498147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028650465","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":[0.47303954,0.00027982323,0.52555305,0.0007362601,0.00018518491,0.000099088036,0.0000039286915,0.000029741681,0.000073379095],"genre_scores_gemma":[0.99272615,0.00020246551,0.0069701253,0.000034139957,0.00004141637,0.0000026824125,0.0000061859305,0.00000820737,0.000008654858],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991696,0.000027917682,0.0005021967,0.000032913606,0.00019720309,0.000070209055],"domain_scores_gemma":[0.9992678,0.000057087145,0.00022399664,0.000059989798,0.00035272693,0.00003836918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012478376,0.00006729794,0.00013406863,0.00011699667,0.000019855672,0.000081548475,0.00015720629,0.000039714163,0.000017762055],"category_scores_gemma":[0.000006219633,0.000056220666,0.000048439368,0.00003254502,0.000018524606,0.00048306095,0.000014809491,0.000062556624,0.0000065441955],"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":[0.00004887822,0.00015043518,0.010709847,0.00014858565,0.00062350894,0.0000043169703,0.0024464775,0.51008564,0.33458132,0.0021184562,0.0005299943,0.13855255],"study_design_scores_gemma":[0.0014956194,0.000042017364,0.0131222205,0.00010352671,0.00002082666,0.00007297324,0.00019106542,0.9578226,0.02414324,0.0016248708,0.001267119,0.000093927],"about_ca_topic_score_codex":0.000016449616,"about_ca_topic_score_gemma":0.000003137924,"teacher_disagreement_score":0.5196866,"about_ca_system_score_codex":0.000049809296,"about_ca_system_score_gemma":0.000009768095,"threshold_uncertainty_score":0.22926122},"labels":[],"label_agreement":null},{"id":"W2029451281","doi":"10.2316/journal.206.2005.3.206-2810","title":"Estimating the Gravity Terms in Robot Manipulatiors for PD Control","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Robot; Compensation (psychology); Controller (irrigation); Torque; Computer science; Closed loop; Control engineering; Control (management); Engineering; Physics; Artificial intelligence","score_opus":0.011592308044095142,"score_gpt":0.2552315756119306,"score_spread":0.24363926756783547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029451281","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":[0.18335657,0.00009135641,0.81291896,0.0023116977,0.0010567567,0.00014029955,0.00000364042,0.000023275383,0.000097421675],"genre_scores_gemma":[0.9769917,0.0000067423434,0.022450471,0.00007646288,0.00044791645,0.000003451251,0.0000026420907,0.0000069260145,0.000013647125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993717,0.000013341366,0.0003617271,0.000037729125,0.00015449485,0.00006099875],"domain_scores_gemma":[0.99964267,0.00007935148,0.000112042806,0.000034411365,0.00011051367,0.000021010186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002834189,0.00005704296,0.000095722186,0.000090960166,0.000028692599,0.000091418435,0.00009609819,0.000027947093,0.000005071233],"category_scores_gemma":[0.000049339495,0.000041921972,0.000034945915,0.000029466206,0.000009903624,0.00019629605,0.0000048561033,0.00006750827,0.0000014590963],"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":[0.0000050523972,0.000010346706,0.0014429857,0.000006966653,0.000027278651,9.640663e-7,0.0002589354,0.9795767,0.0006770059,0.0016303116,0.000067447516,0.016296],"study_design_scores_gemma":[0.0006720089,0.000016659927,0.022458661,0.000051038798,0.000008688856,0.00005281267,0.000027185104,0.97575015,0.00008491616,0.00050605857,0.00032608936,0.000045745757],"about_ca_topic_score_codex":0.000003216291,"about_ca_topic_score_gemma":0.00002253948,"teacher_disagreement_score":0.7936352,"about_ca_system_score_codex":0.000058279238,"about_ca_system_score_gemma":0.000007644654,"threshold_uncertainty_score":0.17095284},"labels":[],"label_agreement":null},{"id":"W2030227900","doi":"10.2316/journal.206.2006.2.206-2797","title":"A SENSOR-BASED NAVIGATION ALGORITHM FOR A MOBILE ROBOT USING FUZZY LOGIC","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Mobile robot; Fuzzy logic; Computer science; Mobile robot navigation; Robot; Position (finance); Obstacle; Obstacle avoidance; Navigation system; Algorithm; Computer vision; Fuzzy control system; Real-time computing; Artificial intelligence; Robot control","score_opus":0.0205579265631916,"score_gpt":0.2929484168507384,"score_spread":0.2723904902875468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030227900","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007847129,0.00010329285,0.99016756,0.0006617576,0.0010048782,0.00014259965,0.000008100197,0.000041665913,0.000023043465],"genre_scores_gemma":[0.12879728,0.0000035288426,0.87071776,0.00009610899,0.00033902278,0.0000036729905,0.000018656314,0.000008058445,0.000015936344],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987177,0.000041303232,0.00048659887,0.0001530702,0.00046048625,0.00014083646],"domain_scores_gemma":[0.9983969,0.00013591324,0.00057922176,0.000098107856,0.00074109755,0.00004881468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041140075,0.000116746654,0.00016537236,0.00024402949,0.00008190168,0.00025447516,0.00034201267,0.00006469242,9.116772e-7],"category_scores_gemma":[0.00003543628,0.00010740065,0.000087790904,0.00012892841,0.000028273847,0.00048765072,0.000038378308,0.00009574217,0.0000013709234],"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":[0.000005507093,0.00007563073,0.00018043965,0.000008557727,0.000028488072,0.00003537907,0.00005570781,0.9407489,0.0014262422,0.0032732917,0.000054120108,0.054107767],"study_design_scores_gemma":[0.00078294287,0.00013819562,0.0012726664,0.000116687355,0.000018696192,0.00033021998,0.000018565586,0.98838073,0.00058010087,0.008164749,0.00008148452,0.00011498123],"about_ca_topic_score_codex":0.000018495472,"about_ca_topic_score_gemma":1.7744438e-7,"teacher_disagreement_score":0.12095015,"about_ca_system_score_codex":0.000117263204,"about_ca_system_score_gemma":0.00010208301,"threshold_uncertainty_score":0.43796715},"labels":[],"label_agreement":null},{"id":"W2030438743","doi":"10.2316/journal.206.2007.3.206-3034","title":"INTEGRAL SLIDING MODE CONTROL OF A BIPEDAL LEAP","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Integral sliding mode; Sliding mode control; Control (management); Mode (computer interface); Control theory (sociology); Computer science; Physics; Artificial intelligence; Operating system; Nonlinear system","score_opus":0.00667414474484851,"score_gpt":0.24613987276132968,"score_spread":0.23946572801648117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030438743","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":[0.10315223,0.00015452347,0.89494956,0.00035840628,0.0008679177,0.000040551153,0.0000028608194,0.000023442182,0.00045050835],"genre_scores_gemma":[0.99284154,0.000052848034,0.0068366323,0.000042656193,0.00019973493,2.821301e-7,0.0000017480708,0.000008372833,0.000016204873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991221,0.0000113811775,0.00047016828,0.000040417937,0.00026988517,0.00008609342],"domain_scores_gemma":[0.99936473,0.00007636329,0.00018286925,0.000037985512,0.00028706877,0.000050950584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031837693,0.000072784074,0.00015054274,0.00021741957,0.000014482809,0.000032884618,0.000116622046,0.000044470577,0.000012887288],"category_scores_gemma":[0.00005268848,0.000063689324,0.00006876175,0.000050311017,0.000015905693,0.00018565916,0.000008175,0.000110748435,0.000001498513],"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":[0.000063703104,0.000055650642,0.0019619802,0.000023422093,0.00027604913,0.000023568731,0.00041527877,0.8906939,0.022893643,0.024038834,0.00013067899,0.05942328],"study_design_scores_gemma":[0.0015006779,0.00006585531,0.0066271196,0.000100806,0.000033108605,0.000121580146,0.0001251888,0.98720956,0.002768947,0.0011717315,0.00019199241,0.00008343853],"about_ca_topic_score_codex":0.000003925981,"about_ca_topic_score_gemma":0.0000036280362,"teacher_disagreement_score":0.88968927,"about_ca_system_score_codex":0.000051970914,"about_ca_system_score_gemma":0.000015678088,"threshold_uncertainty_score":0.25971752},"labels":[],"label_agreement":null},{"id":"W2031310371","doi":"10.2316/journal.206.2006.3.206-2804","title":"RANDOMIZED MOTION PLANNING: A TUTORIAL","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion (physics); Computer science; Artificial intelligence","score_opus":0.013129193613313182,"score_gpt":0.2688556370359988,"score_spread":0.25572644342268563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031310371","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":[0.01035657,0.0001472816,0.9838263,0.0017967464,0.0033835745,0.00006291503,7.5162785e-7,0.000040587052,0.0003852667],"genre_scores_gemma":[0.70087767,0.000011806745,0.29801387,0.00005245363,0.0009773608,0.0000011557631,0.000004814116,0.0000048679562,0.00005601781],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869627,0.00008452012,0.00050223985,0.000101353064,0.00052296853,0.0000926415],"domain_scores_gemma":[0.9987641,0.00019085634,0.00053364446,0.00007564974,0.0003966491,0.000039113245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007470515,0.000085885535,0.00021203999,0.00023561984,0.000042260133,0.00026072786,0.00036231065,0.000048383037,0.0000017736235],"category_scores_gemma":[0.00016917859,0.00007114472,0.0000822934,0.00008290101,0.00003480833,0.00057448173,0.00005352866,0.00010438305,0.0000030597105],"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":[0.0009973969,0.00013996533,0.00094389945,0.000009004895,0.00016078049,0.00019210979,0.0006328523,0.788573,0.0006241768,0.18609814,0.0013455275,0.020283092],"study_design_scores_gemma":[0.024836365,0.000039201364,0.0034440537,0.00007991992,0.000019593928,0.00038210937,0.000008250009,0.9445631,0.00020618443,0.026126975,0.00019627364,0.00009797929],"about_ca_topic_score_codex":0.000012731172,"about_ca_topic_score_gemma":1.08135005e-7,"teacher_disagreement_score":0.69052106,"about_ca_system_score_codex":0.00005095113,"about_ca_system_score_gemma":0.000044365708,"threshold_uncertainty_score":0.29011974},"labels":[],"label_agreement":null},{"id":"W2032413192","doi":"10.2316/journal.206.2014.4.206-4137","title":"SEARCHING FOR SPECIAL CASES OF THE 6R SERIAL MANIPULATORS USING MUTABLE SMART BEE OPTIMIZATION ALGORITHM","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Algorithm; Optimization algorithm; Serial manipulator; Artificial intelligence; Mathematical optimization; Mathematics; Robot","score_opus":0.013848417151545021,"score_gpt":0.24183499417486864,"score_spread":0.22798657702332362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032413192","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050497882,0.000011700456,0.9472949,0.00006849704,0.0019950191,0.00007114868,0.0000062227136,0.000008475183,0.00004614477],"genre_scores_gemma":[0.42100805,0.00002167905,0.57776135,0.000014712858,0.0011610432,5.552586e-7,0.000006168436,0.000015686246,0.000010743385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993221,0.000013935827,0.0003123695,0.000045856108,0.00023293076,0.00007280861],"domain_scores_gemma":[0.9994713,0.00006251444,0.00018453455,0.00003899217,0.00021473707,0.000027903498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002344855,0.00006564003,0.00011452828,0.00008797484,0.000049813727,0.00006142932,0.00011463334,0.00003984275,0.0000075854373],"category_scores_gemma":[0.00006020541,0.000052804662,0.000059268466,0.000044155357,0.000014433086,0.00017273943,0.00002353519,0.00006322708,1.1290198e-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":[0.0000067176397,0.000009651889,0.000057392466,0.000015302798,0.000037811045,8.3140003e-7,0.00005979156,0.9837046,0.0009384826,0.0058729104,0.0000140145685,0.009282488],"study_design_scores_gemma":[0.000355982,0.00003816974,0.00024242964,0.00007476625,0.0000276333,0.00008815681,0.00002630443,0.99599963,0.000624979,0.002436604,0.000032608645,0.00005271243],"about_ca_topic_score_codex":0.000008376822,"about_ca_topic_score_gemma":0.000003554324,"teacher_disagreement_score":0.3705102,"about_ca_system_score_codex":0.00005186354,"about_ca_system_score_gemma":0.00002221742,"threshold_uncertainty_score":0.21533117},"labels":[],"label_agreement":null},{"id":"W2032636259","doi":"10.2316/journal.206.2006.1.206-2842","title":"EXACT LINEARIZATION AND SLIDING MODE OBSERVER FOR A QUADROTOR UNMANNED AERIAL VEHICLE","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Observer (physics); Estimator; Linearization; Feedback linearization; Controller (irrigation); Sliding mode control; Mode (computer interface); Computer science; Noise (video); Control engineering; Engineering; Nonlinear system; Mathematics; Control (management); Artificial intelligence; Physics","score_opus":0.011865598899562037,"score_gpt":0.2474265275974805,"score_spread":0.23556092869791845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032636259","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":[0.49327677,0.00019808926,0.50514483,0.0003117032,0.00085207395,0.00013236233,0.000014626084,0.000031915206,0.0000376443],"genre_scores_gemma":[0.9854775,0.000026604019,0.013467478,0.000012235659,0.000958861,0.0000027529304,0.000016102087,0.000014634577,0.000023819845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993655,0.0000128438005,0.00032863492,0.000055580185,0.00016739682,0.00007002067],"domain_scores_gemma":[0.99945235,0.00006907767,0.00015407524,0.000028693956,0.00026706595,0.000028735583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014188614,0.00007472589,0.0001231244,0.000099253106,0.000029123285,0.0000976155,0.00006135566,0.000046415964,0.00000177182],"category_scores_gemma":[0.000049218124,0.00007105598,0.00003778246,0.000028884744,0.000007501844,0.00028920182,0.000010308464,0.0000506353,5.9430255e-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":[0.000082905,0.000034377816,0.0015567726,0.000047155292,0.00012815636,0.0000064728147,0.00012282566,0.94140005,0.0447523,0.006712878,0.0002856217,0.004870478],"study_design_scores_gemma":[0.0010648429,0.000052016545,0.007486136,0.000068370646,0.000019549007,0.00002636597,0.000016316722,0.98894733,0.00095609896,0.00071998086,0.0005691576,0.000073817624],"about_ca_topic_score_codex":0.000010966739,"about_ca_topic_score_gemma":0.000010102294,"teacher_disagreement_score":0.49220073,"about_ca_system_score_codex":0.000055164764,"about_ca_system_score_gemma":0.000013320598,"threshold_uncertainty_score":0.2897579},"labels":[],"label_agreement":null},{"id":"W2034344214","doi":"10.2316/journal.206.2011.1.206-3399","title":"ADAPTIVE NEURAL NETWORK FREQUENCY CONTROL FOR THERMOPOWER GENERATORS POWER SYSTEM","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Induction Heating and Inverter Technology","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Power (physics); Control theory (sociology); Electric power system; Automatic frequency control; Control (management); Computer science; Seebeck coefficient; Electrical engineering; Physics; Artificial intelligence; Telecommunications; Engineering; Electrical resistivity and conductivity","score_opus":0.014899255742056064,"score_gpt":0.20957898949024348,"score_spread":0.19467973374818742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034344214","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":[0.27165535,0.0003994979,0.71978056,0.00023982202,0.0062591205,0.00015083552,0.000011633243,0.00017137101,0.001331777],"genre_scores_gemma":[0.9797041,0.000009613666,0.019929009,0.000045531935,0.00029211416,0.0000030146157,0.0000013542385,0.000011140694,0.000004146961],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946755,0.000013590329,0.00027844447,0.000047249632,0.000106275445,0.00008691816],"domain_scores_gemma":[0.99951583,0.000022299822,0.00012450149,0.000039208862,0.000271484,0.000026673997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013134762,0.00006961617,0.00010868505,0.00009012524,0.000033910615,0.000021632266,0.000096671516,0.00006311351,0.000010791158],"category_scores_gemma":[0.000013106838,0.000059802845,0.000047152855,0.000032711563,0.000018420578,0.00014869512,0.0000051893053,0.00008840886,0.0000013138705],"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":[0.00014856696,0.00009103059,0.004289059,0.00006046076,0.0012875707,0.0000492668,0.0020863772,0.6948891,0.005692215,0.24367517,0.0045143566,0.04321682],"study_design_scores_gemma":[0.00065408857,0.00020211394,0.0021354477,0.00007430469,0.000030865147,0.00020674457,0.00016154956,0.9927765,0.0006184363,0.0029667208,0.00007222216,0.00010099373],"about_ca_topic_score_codex":0.0000029128153,"about_ca_topic_score_gemma":7.0552596e-7,"teacher_disagreement_score":0.7080487,"about_ca_system_score_codex":0.000058432724,"about_ca_system_score_gemma":0.000010343147,"threshold_uncertainty_score":0.24386892},"labels":[],"label_agreement":null},{"id":"W2035004726","doi":"10.2316/journal.206.2012.3.206-3626","title":"DYNAMIC OBJECT MANIPULATION BY A FLEXIBLE ROBOTIC ARM: THEORY AND EXPERIMENT","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robotic arm; Computer science; Object (grammar); Human–computer interaction; Control engineering; Artificial intelligence; Engineering","score_opus":0.01225435186162318,"score_gpt":0.26773439345898664,"score_spread":0.2554800415973635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035004726","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":[0.23873794,0.003135092,0.7561282,0.0002667614,0.0012019569,0.000074807256,5.9228427e-7,0.00007320897,0.00038145704],"genre_scores_gemma":[0.9940547,0.0002454822,0.005449373,0.00003886934,0.00010036849,0.0000011163162,0.000013322044,0.000014815781,0.00008195672],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993,0.000040637984,0.0002847633,0.00005113759,0.00021992266,0.00010354728],"domain_scores_gemma":[0.99962455,0.000061345825,0.00012959288,0.000038396334,0.000077832236,0.0000682571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033401474,0.00009091574,0.00010910019,0.00014996273,0.00003873897,0.00008361839,0.000059842318,0.00004424515,0.000036705238],"category_scores_gemma":[0.00003378871,0.00008559954,0.00002962899,0.000043211672,0.00001598416,0.0004615355,0.000016899774,0.00010548825,0.000004197725],"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":[0.000020491121,0.000051523304,0.0019941954,0.000022545652,0.00011707901,0.0000020423427,0.0010325414,0.96172196,0.009042966,0.013041822,0.0002655767,0.012687271],"study_design_scores_gemma":[0.0005253325,0.0000512018,0.03003418,0.000086191474,0.000035034536,0.00016614654,0.00023566846,0.9658874,0.00092066155,0.0013951753,0.00050597393,0.00015702184],"about_ca_topic_score_codex":0.0000015005127,"about_ca_topic_score_gemma":3.304086e-7,"teacher_disagreement_score":0.75531673,"about_ca_system_score_codex":0.00007745083,"about_ca_system_score_gemma":0.0000057616207,"threshold_uncertainty_score":0.34906477},"labels":[],"label_agreement":null},{"id":"W2035256876","doi":"10.2316/journal.206.2005.4.206-2874","title":"Development of Hybrid Joints for the Compliant Arm of Human-Symbiotic Mobile Manipulator","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mobile manipulator; Human arm; Manipulator (device); Computer science; Robotic arm; Artificial intelligence; Mobile robot; Robot","score_opus":0.03157350880321492,"score_gpt":0.28418020537646466,"score_spread":0.25260669657324974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035256876","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":[0.6158373,0.00023072187,0.38312256,0.00016949017,0.00041238937,0.00012080219,0.0000014278635,0.000014221036,0.00009108247],"genre_scores_gemma":[0.97385514,0.000022897357,0.02597817,0.000011621796,0.00009927012,0.0000014643284,0.0000052191385,0.000008227285,0.000018002143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992017,0.00000678,0.0004950233,0.000035927624,0.00020761618,0.00005295037],"domain_scores_gemma":[0.99939185,0.00005714981,0.00026763696,0.000040277948,0.000222428,0.000020663745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001978904,0.000058584355,0.00011724142,0.00010205062,0.000037227477,0.000021148726,0.000113253685,0.000015775837,0.000023580447],"category_scores_gemma":[0.000017382286,0.000046044453,0.000048912992,0.000026483875,0.000015879452,0.00010023868,0.000013639246,0.0000608453,0.0000011202548],"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":[0.000006151229,0.000043256827,0.00018685212,0.00003394545,0.000106774714,5.117434e-7,0.000400579,0.9732526,0.010001918,0.0015205072,0.00007987088,0.014367065],"study_design_scores_gemma":[0.0004977126,0.000058327223,0.01263994,0.00013613529,0.000025314093,0.00003601809,0.00013364304,0.9651896,0.020122396,0.00015736907,0.00093663525,0.000066922614],"about_ca_topic_score_codex":6.7567015e-7,"about_ca_topic_score_gemma":0.0000019298336,"teacher_disagreement_score":0.35801783,"about_ca_system_score_codex":0.00004316865,"about_ca_system_score_gemma":0.000015895255,"threshold_uncertainty_score":0.18776383},"labels":[],"label_agreement":null},{"id":"W2036346066","doi":"10.2316/journal.206.2007.2.206-2896","title":"TIME-OPTIMAL FEEDRATES ALONG CURVED PATHS FOR CARTESIAN CNC MACHINES WITH PRESCRIBED BOUNDS ON AXIS VELOCITIES AND ACCELERATIONS","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cartesian coordinate system; Tree traversal; Acceleration; Path (computing); Control theory (sociology); Computer science; Mathematics; Horizontal axis; Geometry; Physics; Engineering; Algorithm; Structural engineering; Classical mechanics; Control (management); Artificial intelligence","score_opus":0.007563034714953333,"score_gpt":0.25089514298048826,"score_spread":0.24333210826553492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036346066","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":[0.3639674,0.0001385518,0.6351482,0.0004047542,0.00008393294,0.00008189933,0.000010563491,0.00006414757,0.00010053729],"genre_scores_gemma":[0.9226921,0.000056727757,0.07702715,0.00003400352,0.00011680643,0.000003012863,0.000018685496,0.000013734597,0.000037737493],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993503,0.000007899667,0.0002890499,0.00006934398,0.00019381284,0.00008956218],"domain_scores_gemma":[0.99939764,0.00012525398,0.0001252078,0.00003805267,0.00026770175,0.00004613428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015793163,0.00010019772,0.00014078434,0.00017646482,0.00005965187,0.00010770568,0.0000743203,0.000036084595,0.000004503725],"category_scores_gemma":[0.000042185948,0.00008008504,0.000036522044,0.000059606235,0.000041722153,0.00031315073,0.000010217112,0.00008322802,4.014106e-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":[0.00024279181,0.00012554108,0.003672379,0.00006510067,0.0007213284,0.0000296781,0.0013868907,0.8658063,0.016029326,0.0054032826,0.00045476842,0.10606263],"study_design_scores_gemma":[0.0006706388,0.0003866603,0.01742355,0.00013455872,0.000069715046,0.00007745265,0.000114297945,0.9700047,0.008566344,0.0018215188,0.00052567956,0.00020490104],"about_ca_topic_score_codex":0.0000044566955,"about_ca_topic_score_gemma":0.000012551713,"teacher_disagreement_score":0.55872476,"about_ca_system_score_codex":0.00005022222,"about_ca_system_score_gemma":0.00001063183,"threshold_uncertainty_score":0.3265773},"labels":[],"label_agreement":null},{"id":"W2036793860","doi":"10.2316/journal.206.2008.2.206-3081","title":"ADAPTIVE NON-LINEAR TRACKING CONTROL OF KINEMATICALLY REDUNDANT ROBOT MANIPULATORS1","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Bounding overwatch; Controller (irrigation); Task (project management); Robot; Computer science; Control engineering; Tracking (education); Adaptive control; Quaternion; Control (management); Engineering; Artificial intelligence; Mathematics","score_opus":0.016005829159338375,"score_gpt":0.23290226345330337,"score_spread":0.216896434293965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036793860","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":[0.05286991,0.00007474865,0.9460723,0.00014084573,0.00061730517,0.00006118187,0.0000042748175,0.000018583456,0.00014086594],"genre_scores_gemma":[0.8318412,0.00011899701,0.16786909,0.000019381494,0.00012666565,4.879391e-7,0.0000024130316,0.000012619796,0.000009189187],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889016,0.00001303868,0.0005806837,0.000059203612,0.00036639028,0.000090541034],"domain_scores_gemma":[0.9991627,0.000064698506,0.00026102542,0.000058789938,0.00039314176,0.000059682916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016989459,0.000101241545,0.0002346949,0.00015282084,0.000028785695,0.000019721001,0.00013688856,0.000057509496,0.000011665928],"category_scores_gemma":[0.000048425347,0.000089429726,0.00007816944,0.00005343585,0.00003236975,0.00020331197,0.000013821826,0.00012165764,0.000001747089],"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":[0.000019378987,0.00003371971,0.00019680608,0.000020154457,0.00013029297,0.000036308105,0.0001720851,0.98532623,0.003913875,0.008258147,0.000021232294,0.0018717635],"study_design_scores_gemma":[0.0007038711,0.00010048602,0.005718912,0.00015279179,0.000032944437,0.00035364702,0.000037827198,0.99066037,0.0005640174,0.0015853662,0.000005332062,0.000084431675],"about_ca_topic_score_codex":0.000002798519,"about_ca_topic_score_gemma":8.6769313e-7,"teacher_disagreement_score":0.77897125,"about_ca_system_score_codex":0.000044304412,"about_ca_system_score_gemma":0.000029685498,"threshold_uncertainty_score":0.36468384},"labels":[],"label_agreement":null},{"id":"W2037000075","doi":"10.2316/journal.206.2006.4.206-2826","title":"AN EXPONENTIAL CLASS OF VISUAL SERVOING CONTROLLERS IN THE PRESENCE OF UNCERTAIN CAMERA CALIBRATION","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visual servoing; Class (philosophy); Calibration; Artificial intelligence; Exponential function; Computer science; Computer vision; Camera resectioning; Mathematics; Control theory (sociology); Image (mathematics); Control (management); Statistics; Mathematical analysis","score_opus":0.009808692641430333,"score_gpt":0.2968900069864005,"score_spread":0.2870813143449702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037000075","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":[0.22170642,0.000045571098,0.7766982,0.001278275,0.00019142659,0.000040409504,8.629175e-7,0.0000036114327,0.00003523684],"genre_scores_gemma":[0.96834576,0.000014939186,0.031509236,0.00006246787,0.000060210594,3.929707e-7,0.000002288986,0.0000019042178,0.0000027746503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989961,0.000081832426,0.00041756683,0.00006284932,0.00038793098,0.000053756343],"domain_scores_gemma":[0.99911094,0.00011101648,0.00045882235,0.000059934733,0.00024465716,0.000014624173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003589874,0.000047184014,0.0001008345,0.00015489061,0.000021190039,0.0000727058,0.0003187931,0.000018089713,0.000001497638],"category_scores_gemma":[0.000042112028,0.000034848574,0.000031858108,0.000101789265,0.000030136454,0.0008811173,0.000025521236,0.00006609616,6.927409e-8],"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":[0.00004596002,0.00022345604,0.003855991,0.000011579338,0.000019219782,0.00001490501,0.0011926418,0.8780326,0.05376694,0.03586569,0.000052923904,0.026918042],"study_design_scores_gemma":[0.0005466918,0.0000852727,0.011685078,0.000066564746,0.0000032068224,0.000026844787,0.00016747795,0.9816739,0.0028147774,0.0028798915,0.000016440863,0.000033882392],"about_ca_topic_score_codex":0.000043293167,"about_ca_topic_score_gemma":0.000008649749,"teacher_disagreement_score":0.7466394,"about_ca_system_score_codex":0.000018493001,"about_ca_system_score_gemma":0.000040366613,"threshold_uncertainty_score":0.14210835},"labels":[],"label_agreement":null},{"id":"W2037347151","doi":"10.2316/journal.206.2011.3.206-3383","title":"SWARM AGGREGATION AND FORMATION CONTROL FOR ROBOTS WITH LIMITED PERCEPTION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Swarm robotics; Aggregate (composite); Robot; Swarm behaviour; Perception; Computer science; Set (abstract data type); Simple (philosophy); Control (management); Collective behavior; Range (aeronautics); Human–computer interaction; Artificial intelligence; Engineering; Psychology; Neuroscience; Nanotechnology; Sociology","score_opus":0.020547990892956676,"score_gpt":0.23599936880700012,"score_spread":0.21545137791404345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037347151","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":[0.055141907,0.00004661462,0.9431016,0.001070772,0.00035894092,0.00019943314,0.000006067241,0.000027550266,0.000047144975],"genre_scores_gemma":[0.9234165,0.00003762292,0.07633455,0.00008856545,0.00009132536,0.0000063726734,0.000010905361,0.000005175817,0.000008995134],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908227,0.00003824687,0.00037905117,0.000106202286,0.00030301925,0.000091196656],"domain_scores_gemma":[0.99845695,0.00006617924,0.0005618735,0.00007311296,0.00078402535,0.000057870802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003344787,0.000091770686,0.00013475538,0.00019427863,0.000058797483,0.00019479835,0.0002077385,0.000046365793,0.0000014071935],"category_scores_gemma":[0.00006222656,0.00007372999,0.00003744561,0.00006448596,0.000021354546,0.0014136214,0.00002034607,0.000057386318,0.0000011931874],"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":[0.0010442849,0.0005915642,0.011776862,0.00018666608,0.0009779801,0.00005817707,0.011170954,0.0885007,0.01066214,0.16217342,0.00059429015,0.7122629],"study_design_scores_gemma":[0.0029048459,0.00033752457,0.03990258,0.00014052104,0.0000426066,0.00030651747,0.00011239776,0.95326036,0.00050301134,0.0022827936,0.00009319423,0.0001136281],"about_ca_topic_score_codex":0.000008002139,"about_ca_topic_score_gemma":0.000004636654,"teacher_disagreement_score":0.86827457,"about_ca_system_score_codex":0.00006444888,"about_ca_system_score_gemma":0.000028046215,"threshold_uncertainty_score":0.3006622},"labels":[],"label_agreement":null},{"id":"W2040356167","doi":"10.2316/journal.206.2012.3.206-3624","title":"HILL CLIMBING OF AN INVERTED PENDULUM ROBOT USING AN ATTITUDE REFERENCE SYSTEM","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inverted pendulum; Climbing; Robot; Computer science; Control theory (sociology); Physical medicine and rehabilitation; Artificial intelligence; Engineering; Physics; Medicine; Structural engineering; Control (management)","score_opus":0.02282245415110222,"score_gpt":0.26248397489057873,"score_spread":0.2396615207394765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040356167","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":[0.83529925,0.00022895011,0.16320272,0.000029104287,0.0009912761,0.00004920056,0.000006732157,0.000039651793,0.00015309143],"genre_scores_gemma":[0.98544526,0.000041898817,0.014246539,0.00000925757,0.00022934582,4.6593416e-7,0.000012252752,0.000012943215,0.0000020151263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990455,0.000042455064,0.00045720936,0.000055423232,0.0002852295,0.0001142033],"domain_scores_gemma":[0.99923676,0.000032637417,0.00025580486,0.000075185715,0.00029184954,0.00010775519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041479623,0.00009192316,0.00017335863,0.00017572516,0.00002801494,0.00005163855,0.00016131929,0.00006200868,0.000005635382],"category_scores_gemma":[0.000024082452,0.00008676673,0.000040188104,0.00004504644,0.000015423417,0.0008937355,0.000023358074,0.00011578031,7.9532833e-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":[0.000014579077,0.00007880553,0.0021147039,0.00004845312,0.000093718525,0.0000050075396,0.00019070646,0.962628,0.018778762,0.0030908731,0.0000032639066,0.0129531],"study_design_scores_gemma":[0.0004058767,0.00005400869,0.019032396,0.00017076971,0.00003725677,0.00017393977,0.0001469837,0.979458,0.00034340442,0.00008014709,0.000009291676,0.000087951],"about_ca_topic_score_codex":0.00002235948,"about_ca_topic_score_gemma":0.000013783425,"teacher_disagreement_score":0.15014601,"about_ca_system_score_codex":0.0000913388,"about_ca_system_score_gemma":0.000019587686,"threshold_uncertainty_score":0.3538245},"labels":[],"label_agreement":null},{"id":"W2040788263","doi":"10.2316/journal.206.2014.4.206-3885","title":"FORCE FEEDBACK AND CONTROL FOR WAVE-VARIABLE TELEOPERATION SYSTEMS WITH TIME DELAYS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National High-tech Research and Development Program; Jiangxi Provincial Department of Science and Technology; Natural Science Foundation of Jiangxi Province; Education Department of Jiangxi Province; National Natural Science Foundation of China","keywords":"Teleoperation; Variable (mathematics); Computer science; Control theory (sociology); Haptic technology; Telerobotics; Feedback control; Control (management); Control engineering; Simulation; Robot; Engineering; Mobile robot; Artificial intelligence; Mathematics","score_opus":0.0034715332710003504,"score_gpt":0.1787397639277701,"score_spread":0.17526823065676975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040788263","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":[0.026820129,0.0001432128,0.971951,0.00028106582,0.00043607497,0.00013588108,0.000008544364,0.000020176265,0.00020391171],"genre_scores_gemma":[0.9912887,0.00002330135,0.0082937945,0.000036228335,0.00024719108,0.0000045391835,0.0000069393577,0.000011919116,0.000087363915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994012,0.000015481688,0.00028062766,0.00005564989,0.0001734486,0.000073601776],"domain_scores_gemma":[0.9994048,0.00009503586,0.00012962478,0.00003451085,0.00028844888,0.000047607926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003121447,0.00007520299,0.0001603404,0.00005867492,0.000029778328,0.00016748327,0.00005677524,0.000044930523,0.0000016960121],"category_scores_gemma":[0.000031756685,0.000058030382,0.000021793827,0.000018022552,0.000007719264,0.00018714924,0.0000051762413,0.000050579467,8.7067946e-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":[0.00006191299,0.000015152324,0.000071790964,0.000055502976,0.00022309933,0.0000016606767,0.00003708642,0.94489676,0.00898045,0.036185298,0.00010443509,0.009366836],"study_design_scores_gemma":[0.0014839981,0.00016588019,0.00023292271,0.00011256244,0.000036201407,0.0001132851,0.0000112158295,0.9963942,0.000035617435,0.0008112671,0.00053136377,0.00007146172],"about_ca_topic_score_codex":0.0000032814758,"about_ca_topic_score_gemma":0.0000017302094,"teacher_disagreement_score":0.9644686,"about_ca_system_score_codex":0.00003811338,"about_ca_system_score_gemma":0.0000111481195,"threshold_uncertainty_score":0.23664103},"labels":[],"label_agreement":null},{"id":"W2040990256","doi":"10.2316/journal.206.2013.3.206-3917","title":"A SIMULATED ANNEALING APPROACH FOR INTEGRATING CELL FORMATION WITH MACHINE LAYOUT AND CELL LAYOUT","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Simulated annealing; Computer science; Standard cell; Page layout; Integrated circuit; Operating system; Machine learning","score_opus":0.009288013179657531,"score_gpt":0.2117691719021308,"score_spread":0.20248115872247327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040990256","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":[0.45048973,0.00013743866,0.54857874,0.000044535474,0.00023393013,0.00018603362,0.000005477768,0.000030636344,0.00029346862],"genre_scores_gemma":[0.980153,0.000019085222,0.019598704,0.000015190143,0.00015926691,0.0000034788984,0.000018840003,0.0000139770755,0.000018448332],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992817,0.000016958393,0.0003709887,0.00006246786,0.00018601665,0.00008187326],"domain_scores_gemma":[0.99927175,0.00005662638,0.00022873843,0.00003469806,0.00036255547,0.000045631026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020781223,0.00009755247,0.00013659341,0.00016715251,0.00005324989,0.00019355661,0.000054361324,0.00006903606,0.0000034253244],"category_scores_gemma":[0.00002095868,0.00007329014,0.00003270814,0.000056032863,0.000008945156,0.0004989905,0.000009775577,0.00012103818,8.304178e-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":[0.00003106833,0.00002049536,0.00032060203,0.00010163573,0.00004043152,0.0000012106527,0.00065651454,0.98005223,0.008266397,0.00007766645,0.00013906333,0.010292704],"study_design_scores_gemma":[0.001034523,0.000118929114,0.00035061224,0.000086499254,0.000018221057,0.000058302146,0.00035456158,0.99474263,0.0029895748,0.00007517895,0.000084397296,0.00008658702],"about_ca_topic_score_codex":0.000022697997,"about_ca_topic_score_gemma":0.0000015660399,"teacher_disagreement_score":0.52966326,"about_ca_system_score_codex":0.000044347278,"about_ca_system_score_gemma":0.000009503933,"threshold_uncertainty_score":0.2988685},"labels":[],"label_agreement":null},{"id":"W2041557901","doi":"10.2316/journal.206.2007.2.206-2937","title":"ROBUST CONTROL DESIGN FOR A PLANAR PARALLEL ROBOT","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Planar; Control (management); Control theory (sociology); Artificial intelligence; Operating system","score_opus":0.021814575754313364,"score_gpt":0.23808772938264222,"score_spread":0.21627315362832886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041557901","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00076528225,0.00011694685,0.9976191,0.00032850882,0.00095672585,0.00010613872,0.000004800186,0.000029433138,0.000073080395],"genre_scores_gemma":[0.23596972,0.00007212765,0.76361305,0.000068304966,0.00023842366,0.0000012803016,0.000005256869,0.000013412892,0.00001843831],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992474,0.000008563237,0.0003716586,0.000053233245,0.00020623826,0.00011293393],"domain_scores_gemma":[0.99935424,0.00017623285,0.00013924966,0.000039362032,0.00022797515,0.00006292901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005173769,0.000083261984,0.00013325535,0.00013920339,0.000027759203,0.000060649552,0.00011921776,0.00005689025,0.000004707063],"category_scores_gemma":[0.000052196803,0.0000748766,0.00005487983,0.000031108688,0.000010320391,0.00015047147,0.0000045417705,0.000075268814,0.0000011294401],"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":[0.00004744982,0.000015183418,0.000051035906,0.000009469764,0.00009466948,0.000011815737,0.0000456511,0.97274804,0.00074290857,0.020005396,0.00021838206,0.006009977],"study_design_scores_gemma":[0.0010674462,0.00008920293,0.0012616519,0.000041199917,0.000029235667,0.00011066716,0.000027938635,0.9892147,0.00007601076,0.007913497,0.00008454998,0.00008385998],"about_ca_topic_score_codex":0.0000010090519,"about_ca_topic_score_gemma":0.0000023028908,"teacher_disagreement_score":0.23520444,"about_ca_system_score_codex":0.00005426345,"about_ca_system_score_gemma":0.000016538284,"threshold_uncertainty_score":0.30533794},"labels":[],"label_agreement":null},{"id":"W2041694308","doi":"10.2316/journal.206.2011.2.206-3458","title":"DEVELOPMENT OF A NEW JELLYFISH-TYPE UNDERWATER MICROROBOT","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Jellyfish; Underwater; Marine engineering; Fishery; Computer science; Geology; Oceanography; Biology; Engineering","score_opus":0.041161001908362596,"score_gpt":0.2472778534576797,"score_spread":0.20611685154931708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041694308","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":[0.3139291,0.00022158418,0.6842869,0.000071609546,0.000947932,0.000034326753,5.985212e-7,0.000017756574,0.00049019186],"genre_scores_gemma":[0.83304816,0.000110628076,0.16670863,0.00001540036,0.000057602756,1.14733496e-7,0.0000017598013,0.0000074833947,0.000050179966],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993303,0.0000050566423,0.00038086667,0.000041465686,0.00018093862,0.00006141032],"domain_scores_gemma":[0.9995789,0.0000085376,0.00012170954,0.000039153645,0.00020645499,0.000045229106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010632684,0.00006555806,0.00010069455,0.00011192954,0.000012717265,0.000019926996,0.00013399476,0.000034476023,0.000064212814],"category_scores_gemma":[0.000009917299,0.000055919998,0.000027886677,0.000038787726,0.000012680896,0.00013096869,0.0000185563,0.00006283391,0.0000051387074],"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":[0.00011808803,0.0002312268,0.003499441,0.00014222808,0.0011272503,0.000059785445,0.023833547,0.34649584,0.12538783,0.009170346,0.0018617713,0.48807263],"study_design_scores_gemma":[0.0015709798,0.00030376346,0.050419815,0.0007968262,0.00011557734,0.0005540561,0.00063465536,0.19445151,0.73059964,0.01086896,0.00897254,0.00071168365],"about_ca_topic_score_codex":0.000005216607,"about_ca_topic_score_gemma":0.0000049375235,"teacher_disagreement_score":0.6052118,"about_ca_system_score_codex":0.000030530427,"about_ca_system_score_gemma":0.000043283115,"threshold_uncertainty_score":0.22803514},"labels":[],"label_agreement":null},{"id":"W2042039855","doi":"10.2316/journal.206.2013.4.206-3923","title":"DESIGN AND CONTROL OF A VARIABLE-RADIUS PULLEY-BASED PNEUMATIC ARTIFICIAL MUSCLE ACTUATION SYSTEM","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Pulley; Control theory (sociology); RADIUS; Variable (mathematics); Pneumatic actuator; Artificial muscle; Actuator; Computer science; Control (management); Engineering; Structural engineering; Mathematics; Artificial intelligence; Mathematical analysis","score_opus":0.007485500826692444,"score_gpt":0.20077195842871207,"score_spread":0.19328645760201962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042039855","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":[0.11203229,0.00011422409,0.8867654,0.00046604322,0.00040824723,0.00016451678,0.000003158412,0.000022587192,0.000023492737],"genre_scores_gemma":[0.93732554,0.000020586334,0.062568806,0.00001915171,0.00004706011,0.000004000951,0.0000028403667,0.000010085933,0.0000019588401],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990845,0.000036662233,0.0004984385,0.00005430406,0.00025464845,0.00007148104],"domain_scores_gemma":[0.998975,0.00021056144,0.00024933516,0.000050103296,0.00046587666,0.00004912877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031847126,0.00008275226,0.00016292174,0.00017944,0.00002706341,0.000083006875,0.00007864622,0.000054197404,0.000009406655],"category_scores_gemma":[0.000067488916,0.000071684124,0.000031543517,0.000057705638,0.00003305717,0.00018519702,0.000006819941,0.00007168429,0.0000019602812],"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":[0.000008347174,0.000028812468,0.00007232119,0.00009652004,0.0000615325,0.0000011367354,0.00016498871,0.9615128,0.02529709,0.004186512,0.000020217236,0.008549699],"study_design_scores_gemma":[0.00052135973,0.00009035303,0.003339252,0.00018326174,0.00003461724,0.000023415601,0.00008517493,0.9924618,0.0010247774,0.0021593682,0.000009697216,0.000066914334],"about_ca_topic_score_codex":0.0000044150456,"about_ca_topic_score_gemma":2.0805055e-7,"teacher_disagreement_score":0.82529324,"about_ca_system_score_codex":0.000054792843,"about_ca_system_score_gemma":0.000034482746,"threshold_uncertainty_score":0.29231936},"labels":[],"label_agreement":null},{"id":"W2043752190","doi":"10.2316/journal.206.2010.3.206-3339","title":"WEIGHT OPTIMIZATION AND STRUCTURESPECIFIED ROBUST H ∞ LOOP-SHAPING CONTROL OF A PNEUMATIC SERVO SYSTEM USING GENETIC ALGORITHM","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Computer science; Genetic algorithm; Loop (graph theory); Servomechanism; Servo; Robust optimization; Optimization algorithm; Control engineering; Control (management); Engineering; Mathematical optimization; Mathematics; Artificial intelligence; Machine learning","score_opus":0.011817047146832318,"score_gpt":0.21760017109873758,"score_spread":0.20578312395190526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043752190","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":[0.20202936,0.0002315772,0.79643416,0.00004008132,0.0011234508,0.000079879195,0.000006696527,0.00002040061,0.00003436767],"genre_scores_gemma":[0.8763564,0.000058589423,0.123344235,0.0000068755508,0.00021528162,6.756739e-7,0.0000025306763,0.00001372997,0.0000016708959],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892426,0.000028375784,0.0006084461,0.00006481706,0.00029466173,0.00007945295],"domain_scores_gemma":[0.99916375,0.00007067005,0.00036149615,0.00006321944,0.00028357646,0.000057283436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021097722,0.00010563344,0.00023173582,0.0001900798,0.000032547574,0.000080314334,0.000109834604,0.000076874276,0.000011143579],"category_scores_gemma":[0.000027621329,0.00009350994,0.00003818148,0.00005759353,0.000025706298,0.00018405667,0.000013035929,0.0001219671,3.457923e-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":[0.0000037603772,0.000006326209,0.00025910992,0.00012402712,0.00011707465,0.0000066141206,0.00020876375,0.9874201,0.004647179,0.00034950586,0.000004940186,0.006852613],"study_design_scores_gemma":[0.0006342903,0.000019788935,0.0018794584,0.0003373138,0.000048459322,0.0006580179,0.00010180305,0.995914,0.0002283163,0.00008843816,0.000007937566,0.000082188366],"about_ca_topic_score_codex":0.0000075423345,"about_ca_topic_score_gemma":0.0000011999465,"teacher_disagreement_score":0.6743271,"about_ca_system_score_codex":0.000041396037,"about_ca_system_score_gemma":0.000022806378,"threshold_uncertainty_score":0.38132244},"labels":[],"label_agreement":null},{"id":"W2045034378","doi":"10.2316/journal.206.2012.3.206-3691","title":"CALCULATING SUPPORT REACTION FORCES IN PHYSICS-BASED SEATED POSTURE PREDICTION FOR PREGNANT WOMEN","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Physics","score_opus":0.015538293027567925,"score_gpt":0.3088014714164664,"score_spread":0.2932631783888985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045034378","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":[0.97412395,0.000089180336,0.02314494,0.00046200727,0.0015620918,0.00016133414,0.000018782295,0.000011421505,0.00042627048],"genre_scores_gemma":[0.9980735,0.000018567214,0.0013187297,0.00008947055,0.00036611455,0.000012680733,0.00007312781,0.0000100405605,0.00003777371],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992808,0.000026542068,0.00033481,0.00007263318,0.0001411025,0.00014408433],"domain_scores_gemma":[0.9993477,0.00005587664,0.0003273785,0.000041516698,0.00017719691,0.000050354458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033936277,0.000074108364,0.00010971423,0.0001357747,0.000030023348,0.000029284234,0.00006449442,0.00006372807,0.00002001889],"category_scores_gemma":[0.000037810347,0.00006714879,0.000056821555,0.000050028906,0.000014432484,0.00030786666,0.000008923606,0.0000878448,0.0000012954391],"study_design_candidate":"observational","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":[0.0015482527,0.0024355429,0.31317607,0.00022495676,0.0012037093,0.000014913778,0.019949486,0.1304567,0.03783488,0.05330576,0.001140218,0.4387095],"study_design_scores_gemma":[0.0031381012,0.00048586162,0.90906554,0.00018333056,0.00004452177,0.000039783252,0.0011006959,0.0824184,0.0002476048,0.0019384122,0.0011718258,0.00016594496],"about_ca_topic_score_codex":0.000017082968,"about_ca_topic_score_gemma":0.0000048083016,"teacher_disagreement_score":0.59588945,"about_ca_system_score_codex":0.000124285,"about_ca_system_score_gemma":0.000028428496,"threshold_uncertainty_score":0.2738248},"labels":[],"label_agreement":null},{"id":"W2045366815","doi":"10.2316/journal.206.2006.1.206-2806","title":"A MODEL FOR OPTIMIZATION AND CONTROL OF SPATIAL COMPLIANT MANIPULATORS","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Computer science; Inverse kinematics; Compliant mechanism; Sensitivity (control systems); Control engineering; Control theory (sociology); Parallel manipulator; Inverse; Robot; Control (management); Finite element method; Engineering; Artificial intelligence; Mathematics","score_opus":0.0073078793312217945,"score_gpt":0.20776783596344123,"score_spread":0.20045995663221944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045366815","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":[0.034588683,0.00019451018,0.96482533,0.0001402683,0.00014504947,0.00006281891,0.000010257143,0.000009282014,0.000023794193],"genre_scores_gemma":[0.98270756,0.000044510674,0.017114254,0.000014346983,0.0001012588,0.0000011854588,0.0000052465834,0.0000066410307,0.0000050110525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995199,0.000003970284,0.0002701129,0.000033467957,0.00012427135,0.000048281978],"domain_scores_gemma":[0.9995997,0.000033712,0.00014139805,0.000019481111,0.00018701646,0.000018714536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007782108,0.00005207047,0.00011145899,0.00009060937,0.000014195566,0.000025831121,0.00004484583,0.00002919479,0.0000013543576],"category_scores_gemma":[0.000012250633,0.00004709363,0.000030600648,0.00001740824,0.000009998371,0.0001053362,0.0000037669643,0.000032382104,4.4326544e-8],"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":[0.000017151378,0.000012852205,0.0004252205,0.00001026671,0.000044318273,5.994767e-7,0.000020617259,0.9837514,0.00074036326,0.0025686906,0.0000334319,0.012375052],"study_design_scores_gemma":[0.0009771878,0.000036031262,0.001106247,0.000023026087,0.000030168801,0.00001976464,0.0000036050897,0.9957686,0.00011200333,0.0018677938,0.000011961893,0.000043576325],"about_ca_topic_score_codex":0.0000071679196,"about_ca_topic_score_gemma":0.000002737828,"teacher_disagreement_score":0.94811887,"about_ca_system_score_codex":0.000022874516,"about_ca_system_score_gemma":0.000011420728,"threshold_uncertainty_score":0.19204223},"labels":[],"label_agreement":null},{"id":"W2046592036","doi":"10.2316/journal.206.2007.2.206-2921","title":"A CONTROL LAW FOR ROBOTIC MANIPULATORS BASED ON A FILTERED SIGNAL TO GENERATE PD ACTION AND VELOCITY ESTIMATES","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); SIGNAL (programming language); Action (physics); Trajectory; Control signal; Robot manipulator; Tracking (education); Harmonic; Torque; Adaptive control; Computer science; Instability; Robot; Control (management); Control engineering; Engineering; Artificial intelligence; Control system; Physics; Acoustics; Mechanics","score_opus":0.023950337606892465,"score_gpt":0.2780939686843311,"score_spread":0.25414363107743865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046592036","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":[0.114215575,0.000044776578,0.88451946,0.00042779342,0.0005781361,0.00015360076,0.000007711442,0.000027214477,0.000025714306],"genre_scores_gemma":[0.96597236,0.000002458374,0.03347807,0.00017782993,0.00034110143,0.0000025309052,0.0000058295095,0.000015426182,0.000004385788],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923843,0.000012220028,0.00034348835,0.000076226665,0.00022431262,0.00010529986],"domain_scores_gemma":[0.9992515,0.00020355632,0.00014026643,0.000036635603,0.00028503957,0.00008304232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033615212,0.0001050558,0.00016738917,0.00017592673,0.00003946634,0.00008693953,0.0000692282,0.000047753696,0.000002844268],"category_scores_gemma":[0.000055535795,0.00009659098,0.00004542715,0.000035386332,0.000012257428,0.00014978912,0.000006202386,0.00007476621,0.0000012048692],"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":[0.0001416695,0.000020091902,0.00020088017,0.000020183816,0.00009357419,0.000009003865,0.000034535857,0.98505425,0.007960876,0.0015429176,0.00005192516,0.004870114],"study_design_scores_gemma":[0.00125841,0.0001843146,0.008021544,0.00010491534,0.000032134496,0.00003566063,0.0000129478185,0.9879479,0.001969248,0.00022359606,0.00011802007,0.00009130634],"about_ca_topic_score_codex":0.000005403615,"about_ca_topic_score_gemma":0.000016976303,"teacher_disagreement_score":0.8517568,"about_ca_system_score_codex":0.00010281928,"about_ca_system_score_gemma":0.000013424639,"threshold_uncertainty_score":0.3938866},"labels":[],"label_agreement":null},{"id":"W2048522717","doi":"10.2316/journal.206.2006.2.206-2793","title":"A SOM-BASED MULTI-AGENT ARCHITECTURE FOR MULTIROBOT SYSTEMS","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Robot; Computer science; Mobile robot; Task (project management); Motion planning; Set (abstract data type); Artificial intelligence; Real-time computing; Distributed computing; Engineering","score_opus":0.01444730200824279,"score_gpt":0.24633625105144175,"score_spread":0.23188894904319896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048522717","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":[0.023531001,0.00048285126,0.9742673,0.00027451274,0.0012573741,0.00011331344,0.000011859214,0.000033994034,0.00002776905],"genre_scores_gemma":[0.926697,0.000030340692,0.072870076,0.000025122981,0.00030562902,0.000004244987,0.000014685915,0.000014777958,0.000038123766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926,0.0000110166875,0.00036057824,0.000062860265,0.00021417573,0.00009137194],"domain_scores_gemma":[0.9994769,0.000053378455,0.00013380511,0.00004797322,0.00025262186,0.000035331286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013510924,0.00009244729,0.0001233606,0.00014500812,0.00002937342,0.000101410944,0.00012375043,0.00004702404,0.0000032524313],"category_scores_gemma":[0.000022445663,0.00007857391,0.00006753849,0.0000315598,0.0000147578285,0.000082556864,0.000007410294,0.000080206046,0.0000013780327],"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":[0.000007924436,0.000034303634,0.00019678845,0.000036441066,0.000040394603,0.0000062276786,0.000037635647,0.9885989,0.0029495163,0.0011573471,0.0002630122,0.0066715092],"study_design_scores_gemma":[0.0005260782,0.000036000965,0.0016955266,0.00009466932,0.00001631183,0.00004740479,0.000013874935,0.99414676,0.0014407329,0.00029092326,0.0016025497,0.00008917624],"about_ca_topic_score_codex":0.000013606732,"about_ca_topic_score_gemma":0.000007979785,"teacher_disagreement_score":0.903166,"about_ca_system_score_codex":0.00005528733,"about_ca_system_score_gemma":0.000015888478,"threshold_uncertainty_score":0.3204151},"labels":[],"label_agreement":null},{"id":"W2050805266","doi":"10.2316/journal.206.2010.2.206-3308","title":"HEAVY OBJECT MANIPULATION BY A HYBRID SERIAL-PARALLEL MOBILE ROBOT","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Object (grammar); Computer hardware; Parallel computing; Embedded system; Artificial intelligence","score_opus":0.0100511505903455,"score_gpt":0.26092761506907597,"score_spread":0.25087646447873047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050805266","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":[0.06652304,0.000088296496,0.9284943,0.0014471251,0.0032097592,0.000090607755,0.0000043827963,0.000050677103,0.00009183864],"genre_scores_gemma":[0.6264633,0.000031773332,0.37302852,0.000099647106,0.00029512303,0.0000024100848,0.00001262892,0.0000076940805,0.00005892484],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986398,0.00004030261,0.00047631038,0.00015906834,0.0005485908,0.00013591384],"domain_scores_gemma":[0.99876636,0.000084104395,0.00049258315,0.00014696422,0.00041681214,0.0000931917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043755048,0.000120498364,0.00016494504,0.00019126154,0.000069906055,0.00035035695,0.0005583669,0.00005859499,0.000009105832],"category_scores_gemma":[0.00008859011,0.00011068065,0.00006154896,0.000087774,0.0000294392,0.000864341,0.00009079915,0.00024118714,0.000009359749],"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":[0.00004992034,0.0003064318,0.0020568857,0.000019314492,0.00020364061,0.00015647463,0.00087474205,0.83824974,0.04316508,0.014417554,0.0045335945,0.095966645],"study_design_scores_gemma":[0.0007274822,0.00016023203,0.0067186537,0.000051407627,0.000013388889,0.0009993195,0.000015789918,0.9847573,0.0023535306,0.0033486823,0.0006900897,0.00016409096],"about_ca_topic_score_codex":0.0000125277165,"about_ca_topic_score_gemma":0.000001247466,"teacher_disagreement_score":0.5599402,"about_ca_system_score_codex":0.000044345765,"about_ca_system_score_gemma":0.00007177895,"threshold_uncertainty_score":0.4513426},"labels":[],"label_agreement":null},{"id":"W2053627786","doi":"10.2316/journal.206.2014.2.206-3872","title":"UNILATERAL CONTROL OF TELEOPERATED HYDRAULIC MANIPULATORS FOR LIVE-LINE MAINTENANCE: COMPARATIVE STUDY","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Manitoba Hydro; University of Manitoba; University of Calgary","funders":"","keywords":"Teleoperation; Computer science; Line (geometry); Control (management); Control theory (sociology); Control engineering; Geology; Engineering; Artificial intelligence; Mathematics","score_opus":0.01757897426050831,"score_gpt":0.2647853125469838,"score_spread":0.24720633828647548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053627786","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":[0.6373624,0.00004577395,0.36149478,0.00012510935,0.00064311596,0.00018353765,0.000005873531,0.000016577258,0.00012278461],"genre_scores_gemma":[0.99856263,0.000011866251,0.0012012029,0.000024393934,0.00016203472,0.000003361279,0.0000058193737,0.000009161161,0.000019535335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990627,0.00003883561,0.00055763486,0.000053443116,0.00021157769,0.00007579684],"domain_scores_gemma":[0.9991327,0.000113418726,0.00024265551,0.0000487048,0.0004229674,0.000039544357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033878072,0.00009188448,0.0002744474,0.000115167364,0.000020558611,0.000035982255,0.00011843628,0.000034425168,0.0000066304833],"category_scores_gemma":[0.00004368613,0.0000734397,0.000049973372,0.00004267588,0.000017116823,0.00012712037,0.0000072272137,0.00006322468,0.000001720541],"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":[0.000038389535,0.0000798034,0.003995333,0.000039392744,0.0003385111,0.000002383365,0.0017055941,0.98897535,0.0010945343,0.0012197744,0.00016345273,0.002347512],"study_design_scores_gemma":[0.0017795641,0.0003089333,0.012292109,0.00012029578,0.00003905177,0.000037108082,0.00041105185,0.9841774,0.00026553133,0.00029870163,0.00019460174,0.00007563646],"about_ca_topic_score_codex":0.0000064581795,"about_ca_topic_score_gemma":0.000003966295,"teacher_disagreement_score":0.36120018,"about_ca_system_score_codex":0.000035041317,"about_ca_system_score_gemma":0.000012237645,"threshold_uncertainty_score":0.29947844},"labels":[],"label_agreement":null},{"id":"W2053870186","doi":"10.2316/journal.206.2006.2.206-2794","title":"A NOVEL HYBRID NAVIGATION SCHEME FOR RECONFIGURABLE MULTI-AGENT TEAMS","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Control reconfiguration; Computer science; Robustness (evolution); Scheme (mathematics); Task (project management); Distributed computing; Imperfect; Human–computer interaction; Real-time computing; Embedded system; Engineering; Systems engineering","score_opus":0.01997880030245743,"score_gpt":0.27687740529053956,"score_spread":0.25689860498808215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053870186","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013988716,0.00008070036,0.9827526,0.0016909445,0.001282795,0.000097947355,0.000008303858,0.000033310604,0.000064650274],"genre_scores_gemma":[0.23637572,0.0000079753845,0.76318103,0.0000624577,0.00023588665,0.0000028380562,0.000019616517,0.000006210119,0.0001082909],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989293,0.000015347005,0.00045357543,0.00013183922,0.0003527695,0.00011715998],"domain_scores_gemma":[0.9986659,0.00009004105,0.0004998046,0.00008717486,0.00061182963,0.000045231718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041048482,0.000092270646,0.00012838209,0.00015923427,0.00006519795,0.00023899382,0.00036736854,0.000035112847,0.0000012795327],"category_scores_gemma":[0.00007670621,0.00008532145,0.00006542346,0.00006581156,0.000017876137,0.0005915488,0.000029012444,0.000088913446,0.0000029952694],"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":[0.000035999405,0.00067335524,0.0019626992,0.000056767472,0.00023473988,0.000079573976,0.00043567087,0.7975136,0.06229867,0.04826178,0.0032074181,0.08523971],"study_design_scores_gemma":[0.001037818,0.00007014746,0.0046061114,0.00012701376,0.0000090996855,0.00049636525,0.000011347071,0.9872162,0.0032438815,0.002584476,0.0004968703,0.00010070918],"about_ca_topic_score_codex":0.00002031374,"about_ca_topic_score_gemma":5.295997e-7,"teacher_disagreement_score":0.222387,"about_ca_system_score_codex":0.00009690787,"about_ca_system_score_gemma":0.00007147015,"threshold_uncertainty_score":0.3479308},"labels":[],"label_agreement":null},{"id":"W2055452100","doi":"10.2316/journal.206.2014.3.206-4006","title":"INTELLIGENT RELAY NODE PLACEMENT IN HETEROGENEOUS WIRELESS SENSOR NETWORKS FOR ENERGY EFFICIENCY","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Relay; Wireless sensor network; Computer network; Computer science; Key distribution in wireless sensor networks; Node (physics); Efficient energy use; Wireless; Wireless network; Telecommunications; Electrical engineering; Engineering; Physics; Power (physics)","score_opus":0.00957006792615912,"score_gpt":0.23964468340458683,"score_spread":0.23007461547842772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055452100","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":[0.04574449,0.00013951746,0.951587,0.0009036569,0.0014895718,0.00005890259,6.801439e-7,0.000022936512,0.00005325058],"genre_scores_gemma":[0.92545456,0.00017469104,0.07380205,0.0002617297,0.00025570445,0.000003290936,0.0000047639887,0.00001081714,0.00003242225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985066,0.00007878821,0.00060916285,0.00019268792,0.000415,0.0001977471],"domain_scores_gemma":[0.9986819,0.00028280148,0.0004573631,0.0001370547,0.00036561696,0.00007526731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005267787,0.00013213838,0.00019521061,0.00028184746,0.000051640378,0.00017077698,0.00052243116,0.000078203695,0.0000018293831],"category_scores_gemma":[0.000058018933,0.00011984227,0.0000826248,0.000135645,0.000028414583,0.00018553332,0.00009921827,0.00011512147,6.015897e-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":[0.000021756503,0.000090001166,0.00018390546,0.000004088185,0.000026684775,0.000010656562,0.000105879546,0.95416015,0.0001440178,0.019630317,0.000050085568,0.02557244],"study_design_scores_gemma":[0.0006001899,0.00014864096,0.00021369054,0.00011455903,0.0000068539875,0.000108370434,0.0000116595365,0.9968858,0.0008726012,0.00024259185,0.0006732937,0.00012177366],"about_ca_topic_score_codex":0.0000073925917,"about_ca_topic_score_gemma":0.000010964157,"teacher_disagreement_score":0.87971,"about_ca_system_score_codex":0.00011780183,"about_ca_system_score_gemma":0.000029073222,"threshold_uncertainty_score":0.4887026},"labels":[],"label_agreement":null},{"id":"W2055936046","doi":"10.2316/journal.206.2011.4.206-3561","title":"NON-OSCILLATORY MULTI-ROBOT MOTION FOR STABLE TARGET CAPTURE","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Motion (physics); Robot; Motion capture; Artificial intelligence; Computer vision","score_opus":0.03232351263454092,"score_gpt":0.2673620389499561,"score_spread":0.23503852631541516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055936046","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002301169,0.000099597586,0.9949265,0.00047748807,0.0019385288,0.000098061384,0.0000049987184,0.000030321584,0.00012330548],"genre_scores_gemma":[0.2993852,0.00001294532,0.70030475,0.000087166976,0.00012312616,0.0000017897004,0.0000039938736,0.0000065144345,0.00007453018],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898046,0.000021285066,0.00038317707,0.00013935454,0.00034274638,0.00013294554],"domain_scores_gemma":[0.99867535,0.000047436184,0.00044610558,0.000107777385,0.0006455658,0.000077780875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043600108,0.0001038799,0.00014926959,0.0002085198,0.000062803156,0.00011643595,0.00046586612,0.00006729206,0.000005344488],"category_scores_gemma":[0.00008089714,0.000092155686,0.00006768331,0.00007567851,0.000023452205,0.0007327003,0.00006430837,0.00011015915,0.0000033328058],"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":[0.00011397684,0.0009780652,0.021577096,0.00012267151,0.0007339275,0.00022331097,0.014614375,0.81892914,0.0071779364,0.040474813,0.003500781,0.091553934],"study_design_scores_gemma":[0.00076000224,0.00009337782,0.027940148,0.00006915272,0.000012808629,0.00014790127,0.0000480711,0.96680665,0.001072386,0.0027835846,0.0001512642,0.000114636794],"about_ca_topic_score_codex":0.000011628343,"about_ca_topic_score_gemma":5.7150413e-7,"teacher_disagreement_score":0.29708403,"about_ca_system_score_codex":0.00006578063,"about_ca_system_score_gemma":0.000070109636,"threshold_uncertainty_score":0.37579998},"labels":[],"label_agreement":null},{"id":"W2056782819","doi":"10.2316/journal.206.2008.1.206-3041","title":"RESOLVE REDUNDANCY WITH CONSTRAINTS FOR OBSTACLE AND SINGULARITY AVOIDANCE SUBGOALS","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Obstacle; Redundancy (engineering); Obstacle avoidance; Computer science; Singularity; Artificial intelligence; Mathematics; Geometry; Political science; Operating system; Law","score_opus":0.011034118652367891,"score_gpt":0.21901511599888537,"score_spread":0.20798099734651748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056782819","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":[0.16738519,0.00018802572,0.8317363,0.00021506885,0.00030054647,0.000060567556,0.000007771894,0.000018451128,0.00008807476],"genre_scores_gemma":[0.6856909,0.00018594618,0.3139929,0.000024315812,0.00007480135,8.1407893e-7,0.0000038122948,0.000008504024,0.000018047616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994691,0.000006436812,0.00022536729,0.000056816258,0.00016911924,0.00007313688],"domain_scores_gemma":[0.9995195,0.00005745969,0.00011012166,0.00003619351,0.00022890409,0.00004778629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001186083,0.000069665526,0.000115084586,0.00006750858,0.000049579794,0.00004547783,0.00006047917,0.00003671842,0.000003021369],"category_scores_gemma":[0.000041353163,0.00005981894,0.000023288589,0.00002618724,0.00005647839,0.00016898518,0.000008809623,0.00007187574,2.2814476e-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":[0.0000876845,0.00006787219,0.0037217638,0.0000933958,0.00027184846,0.000102259706,0.00088248216,0.89650106,0.003279335,0.06961322,0.000256509,0.025122583],"study_design_scores_gemma":[0.0016457966,0.00022387232,0.021124506,0.0002538723,0.000038744067,0.002099346,0.00009160399,0.9602932,0.0006863949,0.01320105,0.00014087396,0.00020075223],"about_ca_topic_score_codex":0.0000012926819,"about_ca_topic_score_gemma":0.000002450199,"teacher_disagreement_score":0.51830566,"about_ca_system_score_codex":0.00003075983,"about_ca_system_score_gemma":0.000025076273,"threshold_uncertainty_score":0.24393456},"labels":[],"label_agreement":null},{"id":"W2058300813","doi":"10.2316/journal.206.2008.2.206-3095","title":"COMBINED ADAPTIVE-ROBUST AND NEURAL NETWORK CONTROL OF TWO RLED COOPERATING ROBOTS USING BACKSTEPPING DESIGN","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Backstepping; Control theory (sociology); Computer science; Actuator; Artificial neural network; Control engineering; Adaptive control; Object (grammar); Robot manipulator; Robot; Control (management); Artificial intelligence; Engineering","score_opus":0.048338901903332405,"score_gpt":0.25495612569859594,"score_spread":0.20661722379526354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058300813","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":[0.2489088,0.00021132284,0.7503571,0.00006513073,0.00035092916,0.00006041089,2.9739928e-7,0.000019558245,0.000026451416],"genre_scores_gemma":[0.92738646,0.0000607868,0.07231562,0.00003134676,0.0001851926,3.6586724e-7,0.0000017713555,0.000013456067,0.0000050003578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907726,0.000066936795,0.00046830412,0.00006397973,0.00022332018,0.00010022329],"domain_scores_gemma":[0.9992007,0.00013701404,0.0002758338,0.000035445308,0.0003017934,0.000049221686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002581294,0.000101092766,0.00020614426,0.00012611842,0.00008351264,0.00005002777,0.00007426488,0.000038112816,0.000008511242],"category_scores_gemma":[0.000050726485,0.00009841993,0.000036796857,0.00007821157,0.00003407051,0.00031135025,0.000015802918,0.00014211531,2.9525017e-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":[0.000031161107,0.000009207615,0.004602326,0.000008305947,0.00009066746,0.0000133787635,0.00018917189,0.9898417,0.0035194315,0.0005924718,0.000019649846,0.0010825031],"study_design_scores_gemma":[0.0014125641,0.000068936024,0.012640365,0.00014081491,0.000026457164,0.00018818717,0.000031481955,0.98521394,0.000112938615,0.000075208605,0.0000016572272,0.00008747549],"about_ca_topic_score_codex":0.0000047375906,"about_ca_topic_score_gemma":7.2995016e-7,"teacher_disagreement_score":0.67847764,"about_ca_system_score_codex":0.00003827565,"about_ca_system_score_gemma":0.000022267537,"threshold_uncertainty_score":0.40134484},"labels":[],"label_agreement":null},{"id":"W2058303310","doi":"10.2316/journal.206.2012.4.206-3801","title":"A DESIGN AND BIO-INSPIRED CONTROL OF A NOVEL REDUNDANT MANIPULATOR WITH M-DOFS LINKS","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Manipulator (device); Control (management); Computer science; Control theory (sociology); Robot manipulator; Control engineering; Engineering; Artificial intelligence; Robot","score_opus":0.020837097215513693,"score_gpt":0.23755694350845585,"score_spread":0.21671984629294216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058303310","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":[0.16893527,0.00044874413,0.83013135,0.00014682209,0.00024994145,0.000057116882,0.0000022195825,0.000010857343,0.000017653792],"genre_scores_gemma":[0.94831,0.00012861984,0.051423352,0.000023957104,0.00009751704,7.795777e-7,0.0000010610163,0.000009533509,0.000005156472],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993718,0.000010889161,0.00028466477,0.000041260377,0.00020994783,0.000081418315],"domain_scores_gemma":[0.9995159,0.00004323336,0.00015619172,0.00003965939,0.00018568248,0.00005931555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021604565,0.000075851545,0.00013299295,0.000110441164,0.000016455635,0.000034721324,0.00007279659,0.00005162341,0.0000046249243],"category_scores_gemma":[0.000018129991,0.000057974186,0.000021726342,0.000035161982,0.000026740132,0.0002198107,0.000008856557,0.000100260055,3.9345477e-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":[0.00006714341,0.00009583332,0.0031552445,0.000041433952,0.00028806576,0.0000070990054,0.0006044165,0.95149636,0.025658507,0.004664738,0.00002915649,0.013892025],"study_design_scores_gemma":[0.00083138444,0.00012695423,0.010326189,0.00017056442,0.000047516864,0.000325638,0.000036051882,0.9818212,0.006013504,0.00011381255,0.00008980772,0.0000973938],"about_ca_topic_score_codex":0.0000028743682,"about_ca_topic_score_gemma":4.3013472e-7,"teacher_disagreement_score":0.7793748,"about_ca_system_score_codex":0.000023881534,"about_ca_system_score_gemma":0.000013440568,"threshold_uncertainty_score":0.23641187},"labels":[],"label_agreement":null},{"id":"W2058436584","doi":"10.2316/journal.206.2014.3.206-4020","title":"FUZZY-BASED CLUSTERING AND DATA AGGREGATION FOR MULTIMODAL WSN (C-DAMM)","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Fuzzy logic; Cluster analysis; Data mining; Fuzzy clustering; Artificial intelligence","score_opus":0.029618650663596237,"score_gpt":0.3330842169728543,"score_spread":0.30346556630925803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058436584","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030562577,0.000035799898,0.9918856,0.004639599,0.00020799664,0.00009288221,0.000008127656,0.00003315825,0.00004059968],"genre_scores_gemma":[0.46920058,0.000016467317,0.5304848,0.00016556868,0.00010404962,0.000002542153,0.000018583181,0.0000033925658,0.0000040055534],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992756,0.000017768436,0.00027959055,0.00014766253,0.00021436636,0.000065002525],"domain_scores_gemma":[0.9989445,0.00018937388,0.00031313195,0.00014646049,0.00036291752,0.00004362297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033196234,0.00006745473,0.00008957684,0.0001178988,0.00007025917,0.00016858896,0.00047257237,0.000029768931,3.6445851e-7],"category_scores_gemma":[0.000104830084,0.00006280638,0.000023126775,0.000053517404,0.000021812219,0.0005918482,0.00013752375,0.000055914374,3.5377286e-7],"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":[0.000017395309,0.00006069484,0.00017202707,0.000023202187,0.0000347785,0.0000013748489,0.00008786483,0.2112753,0.0011779673,0.21381062,0.00020531518,0.57313347],"study_design_scores_gemma":[0.00043621566,0.000061345105,0.0012656141,0.000048540365,0.000006819782,0.000034984914,0.000003567606,0.9421931,0.00034142623,0.053894628,0.0016489187,0.00006487151],"about_ca_topic_score_codex":0.0000019781198,"about_ca_topic_score_gemma":0.0000019059263,"teacher_disagreement_score":0.7309178,"about_ca_system_score_codex":0.00002401124,"about_ca_system_score_gemma":0.0000321737,"threshold_uncertainty_score":0.25611696},"labels":[],"label_agreement":null},{"id":"W2058593943","doi":"10.2316/journal.206.2014.3.206-3838","title":"REAL-TIME VELOCITY AND DIRECTION ANGLE CONTROL OF AN AUTOMATED GUIDED VEHICLE","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Robustness (evolution); Fuzzy logic; PID controller; Fuzzy control system; Computer science; Mobile robot; Smoothness; Robot; Control engineering; Engineering; Mathematics; Control (management); Artificial intelligence; Temperature control","score_opus":0.004409226325561745,"score_gpt":0.2300286325299264,"score_spread":0.22561940620436466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058593943","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":[0.94348323,0.000067943525,0.055419777,0.00023588074,0.00035118306,0.000055063996,0.0000071760164,0.00011635417,0.00026338696],"genre_scores_gemma":[0.9943894,0.00010654182,0.0053564757,0.00001298424,0.00010902714,7.194272e-7,0.0000063566945,0.000009341663,0.000009147711],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931693,0.0000317634,0.00033569834,0.000057249592,0.0001931695,0.000065197695],"domain_scores_gemma":[0.99937725,0.00007085701,0.00017467095,0.000048938407,0.00027354617,0.000054707554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028380446,0.00007399274,0.00016566635,0.0001249536,0.00002313153,0.000044956494,0.00007745586,0.00004914924,0.00000480369],"category_scores_gemma":[0.000056988196,0.00006935721,0.00003295107,0.000038024944,0.000021925958,0.00026807806,0.0000111545905,0.00005694005,8.349468e-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":[0.000038511418,0.00005427509,0.00085739774,0.00002544878,0.00014228247,0.0000039164074,0.00011407397,0.8531066,0.084223665,0.0010670058,0.00010754165,0.060259268],"study_design_scores_gemma":[0.0009882968,0.00009018822,0.05595721,0.000043255586,0.000025077406,0.000048790425,0.000005923134,0.9416971,0.00044237098,0.0006014451,0.00003865224,0.00006164615],"about_ca_topic_score_codex":0.000017683227,"about_ca_topic_score_gemma":0.0000044858634,"teacher_disagreement_score":0.08859053,"about_ca_system_score_codex":0.000035270543,"about_ca_system_score_gemma":0.00001061329,"threshold_uncertainty_score":0.28283048},"labels":[],"label_agreement":null},{"id":"W2060079488","doi":"10.2316/journal.206.2014.1.206-3765","title":"PROPOSITION OF GENERIC VALIDATION CRITERIA USING STEREO-VISION FOR ON-ROAD OBSTACLE DETECTION","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Obstacle; Advanced driver assistance systems; Computer science; Reliability (semiconductor); Computer vision; Artificial intelligence; Stereopsis; Proposition; Function (biology); Real-time computing; Geography","score_opus":0.02665079621782569,"score_gpt":0.3376326517888777,"score_spread":0.310981855571052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060079488","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":[0.14346577,0.000014470508,0.8552209,0.00043075107,0.0007670234,0.000065242006,0.0000012291098,0.000011428405,0.000023169976],"genre_scores_gemma":[0.78223765,0.00000947818,0.21757537,0.000057453904,0.00010900086,5.909636e-7,0.0000025477684,0.00000420264,0.0000037334626],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914545,0.000044480137,0.00035665938,0.00009961554,0.00029058036,0.00006322321],"domain_scores_gemma":[0.99875325,0.00006040778,0.0005063228,0.00007513492,0.0005736703,0.00003121364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003173829,0.00006605455,0.00010465605,0.00022265183,0.00005733674,0.00012433126,0.00017017926,0.000027579734,0.0000013527243],"category_scores_gemma":[0.00009721199,0.00005824231,0.000049389742,0.00007729131,0.000015170976,0.000821933,0.000033788245,0.00004764931,4.953002e-7],"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":[0.00006120136,0.00008282244,0.000076627184,0.000024378065,0.000024302633,7.2523295e-7,0.00018515775,0.05269926,0.2218131,0.0054449537,0.000016116008,0.71957135],"study_design_scores_gemma":[0.00049309654,0.0003619036,0.0031017342,0.00013039954,0.000008613077,0.000049932823,0.000012186509,0.95081973,0.040565412,0.0043205293,0.00007765446,0.00005880022],"about_ca_topic_score_codex":0.0000019777779,"about_ca_topic_score_gemma":2.6977767e-7,"teacher_disagreement_score":0.89812046,"about_ca_system_score_codex":0.000055235716,"about_ca_system_score_gemma":0.000019052557,"threshold_uncertainty_score":0.23750524},"labels":[],"label_agreement":null},{"id":"W2061713759","doi":"10.2316/journal.206.2013.4.206-3883","title":"ADAPTIVE TRACKING CONTROL OF NONHOLONOMIC SYSTEMS BASED ON FEEDBACK ERROR LEARNING","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Computer science; Tracking error; Nonholonomic system; Nonlinear system; Adaptive control; Artificial neural network; Lyapunov function; Bounded function; Lyapunov stability; Stability (learning theory); Mobile robot; Robot; Artificial intelligence; Mathematics; Control (management); Machine learning","score_opus":0.007204113756880741,"score_gpt":0.2076222257782725,"score_spread":0.20041811202139176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061713759","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":[0.29251528,0.00027863233,0.7051261,0.00040176243,0.0010883374,0.00015968394,0.000006586977,0.000036598944,0.00038699692],"genre_scores_gemma":[0.99834615,0.000023217308,0.0014644911,0.000019396637,0.00011845635,0.0000026898913,0.0000026764217,0.000011512635,0.000011393985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925816,0.0000245958,0.00037424706,0.000051502746,0.00021645475,0.00007502934],"domain_scores_gemma":[0.99919915,0.00014148353,0.00025160032,0.000038924576,0.00032856074,0.000040266536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016212436,0.00008342808,0.00017549413,0.00017652797,0.000018809747,0.00006977851,0.00010398408,0.00004447746,0.00001046648],"category_scores_gemma":[0.00004269583,0.000074939664,0.000062115345,0.000028690156,0.000015264806,0.00021434682,0.0000062423323,0.00013846628,0.000004997404],"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":[0.000024519923,0.000020370455,0.00076251035,0.000013003074,0.0000787216,0.000002923998,0.000038836588,0.9848289,0.0017261729,0.00040613126,0.000021846325,0.012076088],"study_design_scores_gemma":[0.0010267395,0.00012727313,0.018232299,0.00018579411,0.00001876761,0.00001716456,0.000052809122,0.9801052,0.000049304734,0.00009832869,0.00002118872,0.00006512056],"about_ca_topic_score_codex":0.00001068486,"about_ca_topic_score_gemma":0.0000010048711,"teacher_disagreement_score":0.7058309,"about_ca_system_score_codex":0.00006571148,"about_ca_system_score_gemma":0.00001701361,"threshold_uncertainty_score":0.3055951},"labels":[],"label_agreement":null},{"id":"W2061957606","doi":"10.2316/journal.206.2006.2.206-2796","title":"AGENT-BASED SUPPORT FOR BALANCING TELEOPERATION AND AUTONOMY IN URBAN SEARCH AND RESCUE","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Teleoperation; Search and rescue; Forcing (mathematics); Rescue robot; Task (project management); Autonomy; Computer science; Robot; Urban search and rescue; Human–computer interaction; Artificial intelligence; Mobile robot; Engineering; Systems engineering; Political science","score_opus":0.010299703812474692,"score_gpt":0.24540733742304038,"score_spread":0.2351076336105657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061957606","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":[0.59143263,0.00020057477,0.4076329,0.0003779411,0.0002056938,0.0000826196,0.000003989316,0.00001168109,0.00005200506],"genre_scores_gemma":[0.9852046,0.00005763989,0.014553495,0.000026681417,0.00011180298,0.0000017771113,0.000012006849,0.000007303804,0.000024702873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945456,0.00000986931,0.00027187367,0.00006119591,0.00013022732,0.000072260096],"domain_scores_gemma":[0.9997629,0.00003349329,0.000031417516,0.000025814757,0.00011924519,0.000027141343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023733174,0.00006064393,0.00008962357,0.00015593787,0.00002417011,0.00009750418,0.00004437853,0.000034028068,0.0000041071457],"category_scores_gemma":[0.00001579818,0.00005689599,0.000016229858,0.000029399029,0.000014983594,0.00017070299,0.000008427848,0.00006576147,2.4843214e-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":[0.000010785631,0.00001640957,0.007439669,0.000037048096,0.000015813235,0.000008160399,0.0001815263,0.97068125,0.0029369036,0.0024574331,0.000083626466,0.016131347],"study_design_scores_gemma":[0.00039451435,0.000047129033,0.040663082,0.00005784229,0.0000061324968,0.000033175238,0.000023331904,0.95585084,0.0023666744,0.00022062179,0.00027354324,0.000063130465],"about_ca_topic_score_codex":0.000028030472,"about_ca_topic_score_gemma":0.00003891746,"teacher_disagreement_score":0.39377198,"about_ca_system_score_codex":0.000057200345,"about_ca_system_score_gemma":0.00002993473,"threshold_uncertainty_score":0.23201512},"labels":[],"label_agreement":null},{"id":"W2062800039","doi":"10.2316/journal.206.2011.1.206-3374","title":"EXACT TIP TRAJECTORY TRACKING CONTROL OF A FLEXIBLE ROBOT ARM","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Tracking (education); Robotic arm; Control theory (sociology); Computer science; Robot; Control (management); Artificial intelligence; Physics; Psychology","score_opus":0.015611419897515143,"score_gpt":0.22353021394960546,"score_spread":0.20791879405209032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062800039","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":[0.11747827,0.00060097955,0.8787958,0.00009672835,0.0016475365,0.00007520095,0.000006856256,0.00003617899,0.001262478],"genre_scores_gemma":[0.9970763,0.000056540957,0.0026864659,0.000017100463,0.00013542992,9.355719e-7,0.0000010489748,0.000010417987,0.000015801601],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918354,0.000015862173,0.0004368271,0.000046486333,0.00024122861,0.00007603919],"domain_scores_gemma":[0.9994257,0.000042001873,0.00022371674,0.000045147845,0.00021595717,0.00004745745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023612563,0.000074009135,0.0001778841,0.00012199474,0.000011460526,0.000028174365,0.00013671903,0.000046565674,0.000031859727],"category_scores_gemma":[0.00002128976,0.000065286564,0.000078848876,0.000034724908,0.000011687183,0.00017657917,0.000006997958,0.000089126304,0.0000015538977],"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":[0.00020717672,0.0003826431,0.002517174,0.00011497895,0.0014737889,0.000073839474,0.0016342312,0.7139692,0.045396786,0.06253848,0.00010514101,0.17158656],"study_design_scores_gemma":[0.0016895873,0.00022761115,0.021756984,0.00022094461,0.00007011607,0.000121279925,0.00010100285,0.97092,0.001870825,0.0027747035,0.00010962379,0.00013729291],"about_ca_topic_score_codex":0.00000869728,"about_ca_topic_score_gemma":0.000002204172,"teacher_disagreement_score":0.879598,"about_ca_system_score_codex":0.0000422567,"about_ca_system_score_gemma":0.000015515301,"threshold_uncertainty_score":0.26623088},"labels":[],"label_agreement":null},{"id":"W2063170154","doi":"10.2316/journal.206.2015.1.206-4105","title":"REAL-TIME STEALTH CORRIDOR PATH PLANNING FOR FLEETS OF UNMANNED AERIAL VEHICLES IN LOW-ALTITUDE PENETRATION","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Low altitude; Aeronautics; Penetration (warfare); Aerospace engineering; Altitude (triangle); Computer science; Engineering; Operations research","score_opus":0.009401472917203727,"score_gpt":0.2581124119016744,"score_spread":0.24871093898447066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063170154","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":[0.9722738,0.00003468447,0.026893975,0.000097468044,0.00048546784,0.000063772364,0.000006348425,0.000013598289,0.00013086465],"genre_scores_gemma":[0.99181324,0.00009041899,0.00782017,0.000011694824,0.00023340502,0.0000012558415,0.000012577488,0.000008394466,0.000008856617],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993065,0.00001516319,0.00039001022,0.000046210684,0.00016887805,0.000073250216],"domain_scores_gemma":[0.999514,0.0000740263,0.00019075,0.00003522036,0.00015147538,0.000034545206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003129479,0.0000621484,0.00012961008,0.00014137787,0.000021177251,0.00002885807,0.000086353975,0.000043897897,0.0000052512205],"category_scores_gemma":[0.00004159297,0.00005742033,0.000029098099,0.000040047933,0.000009767855,0.00019425819,0.000008664465,0.0000624132,6.258478e-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":[0.00006688534,0.000031353196,0.0030803515,0.000077597186,0.000025717822,0.0000015805955,0.00036697532,0.9559222,0.030403998,0.00061491603,0.00018031485,0.0092281],"study_design_scores_gemma":[0.0008085536,0.000110275534,0.035126742,0.0003686374,0.0000065934432,0.000012114848,0.00002508188,0.9605499,0.0025136196,0.00031361735,0.000105058956,0.000059809106],"about_ca_topic_score_codex":0.0000062605527,"about_ca_topic_score_gemma":0.0000020995308,"teacher_disagreement_score":0.03204639,"about_ca_system_score_codex":0.00004128812,"about_ca_system_score_gemma":0.000025199957,"threshold_uncertainty_score":0.2341533},"labels":[],"label_agreement":null},{"id":"W2065499315","doi":"10.2316/journal.206.2013.3.206-3598","title":"ROBOT PATH PLANNING IN NARROW PASSAGES BASED ON PROBABILISTIC ROADMAPS","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Probabilistic roadmap; Workspace; Probabilistic logic; Path (computing); Motion planning; Robot; Computer science; Artificial intelligence; Space (punctuation); Computer network","score_opus":0.014591589384702841,"score_gpt":0.26023319484782276,"score_spread":0.24564160546311992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065499315","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":[0.04178069,0.00008894136,0.94980663,0.006706347,0.0011559036,0.0001527311,0.0000013788139,0.00004630293,0.00026108185],"genre_scores_gemma":[0.80264825,0.0000031107054,0.19700167,0.00022567209,0.00009077235,0.0000036787537,0.000002801608,0.0000058464893,0.000018201279],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985812,0.000076069475,0.00046522426,0.00015583182,0.0005750819,0.00014660675],"domain_scores_gemma":[0.99887645,0.00021968452,0.0003798297,0.00012479007,0.00032360293,0.000075619566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043611732,0.000118147,0.00016520159,0.0003757664,0.000038185713,0.00029447497,0.0005020409,0.000055629433,0.0000062349673],"category_scores_gemma":[0.00024619492,0.00010058126,0.000043906562,0.00014118238,0.000023675775,0.0006031017,0.000050202467,0.00019670528,0.000009537459],"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":[0.0000049769847,0.000082872284,0.004280583,0.000007800067,0.0000122124375,0.00008333623,0.00028999854,0.97973675,0.000237221,0.0017185629,0.00032560813,0.013220111],"study_design_scores_gemma":[0.000484542,0.00013512115,0.11633833,0.0002814142,0.0000032729213,0.000072094335,0.000019780618,0.8793559,0.000064960994,0.003128164,0.000022074713,0.00009433144],"about_ca_topic_score_codex":0.000012692574,"about_ca_topic_score_gemma":2.7432898e-7,"teacher_disagreement_score":0.76086754,"about_ca_system_score_codex":0.000103813516,"about_ca_system_score_gemma":0.00008040502,"threshold_uncertainty_score":0.41015846},"labels":[],"label_agreement":null},{"id":"W2065839897","doi":"10.2316/journal.206.2011.4.206-3490","title":"CONSTRUCTION ROBOT TELE-OPERATION WITH A VR-AIDED DISPLAY: WORKSPACE VIEWPOINT MANIPULATION EFFECT","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Workspace; Computer science; Robot; Human–computer interaction; Computer graphics (images); Simulation; Artificial intelligence","score_opus":0.012355224191867619,"score_gpt":0.21544254767256618,"score_spread":0.20308732348069855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065839897","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":[0.13225183,0.00015061084,0.86615765,0.00015408483,0.0007307493,0.00011312401,0.0000012973711,0.00004746565,0.00039316993],"genre_scores_gemma":[0.9450917,0.00020560175,0.054484412,0.000025087975,0.0001498684,0.0000027318229,0.0000094665875,0.000016922588,0.00001421092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990912,0.000033207838,0.00037567466,0.0000925823,0.00030955172,0.00009780319],"domain_scores_gemma":[0.99940777,0.000032993583,0.00019735878,0.00007055416,0.00023449703,0.0000568239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022068006,0.00013384923,0.00016503134,0.00017157232,0.000045264413,0.000096027565,0.00010763579,0.00006416539,0.000036934198],"category_scores_gemma":[0.000023374547,0.00010342104,0.000044784007,0.00007262237,0.000034459405,0.00049086724,0.000013411043,0.0001480792,0.000006242994],"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":[0.000095953175,0.00003388865,0.003030641,0.00003982569,0.0001927009,0.000031860174,0.00070298056,0.8856223,0.0022794865,0.009726405,0.000045543547,0.09819837],"study_design_scores_gemma":[0.00075190334,0.0003895787,0.028527956,0.00036348033,0.000089966,0.0009445509,0.000110074805,0.95563483,0.011427714,0.0013907773,0.00010922976,0.00025994834],"about_ca_topic_score_codex":0.00000978651,"about_ca_topic_score_gemma":0.000011085582,"teacher_disagreement_score":0.81283987,"about_ca_system_score_codex":0.000076256096,"about_ca_system_score_gemma":0.000016020764,"threshold_uncertainty_score":0.42173877},"labels":[],"label_agreement":null},{"id":"W2066268309","doi":"10.2316/journal.206.2011.1.206-3412","title":"DISCRETE-TIME OPTIMAL CONTROL OF NONHOLONOMIC MOBILE ROBOT FORMATIONS USING LINEARLY PARAMETERIZED NEURAL NETWORKS","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Artificial neural network; Parameterized complexity; Controller (irrigation); Computer science; Optimal control; Discrete time and continuous time; Mobile robot; Lyapunov stability; Nonlinear system; Nonholonomic system; Kinematics; Lyapunov function; Dynamic programming; Stability (learning theory); Robot; Mathematics; Mathematical optimization; Control (management); Artificial intelligence; Algorithm","score_opus":0.015170453927309292,"score_gpt":0.25193749398421583,"score_spread":0.23676704005690655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066268309","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":[0.14310566,0.00007963707,0.85616636,0.00008811694,0.00041294622,0.00011657813,0.00000465964,0.000018641911,0.0000074164886],"genre_scores_gemma":[0.74157584,0.00000957829,0.2583068,0.000031164764,0.00006380944,0.0000019842485,0.0000027457463,0.0000053499407,0.0000027372644],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988653,0.00006052367,0.00059747003,0.000101772755,0.00024593217,0.00012899245],"domain_scores_gemma":[0.99847436,0.00010276315,0.0008228576,0.000113716145,0.0004247676,0.00006155556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031570482,0.000106355896,0.00022614088,0.00018514284,0.000045766727,0.00012053809,0.0004967137,0.00005113507,0.000005429902],"category_scores_gemma":[0.000038673268,0.000094354844,0.000100927486,0.00007197717,0.00006009338,0.00095635984,0.00006750112,0.00012449406,0.0000011106653],"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":[0.0000699835,0.00009394934,0.00047741362,0.000003076132,0.00015905517,0.000010530822,0.0005620754,0.97103775,0.0014329888,0.0018128195,0.0000024906558,0.024337871],"study_design_scores_gemma":[0.0010518365,0.0002951854,0.0025986189,0.00003069416,0.000031617175,0.00011351714,0.000020494117,0.9954609,0.00007664567,0.00022700471,0.0000083690065,0.00008507249],"about_ca_topic_score_codex":0.000010699203,"about_ca_topic_score_gemma":4.499597e-7,"teacher_disagreement_score":0.5984702,"about_ca_system_score_codex":0.000053414995,"about_ca_system_score_gemma":0.00004276177,"threshold_uncertainty_score":0.3847679},"labels":[],"label_agreement":null},{"id":"W2068769351","doi":"10.2316/journal.206.2010.4.206-3434","title":"BALANCING CONTROL OF LEG EXOSKELETON USING ZMP-BASED JACOBIAN COMPENSATION","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Computing and Algorithms","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Exoskeleton; Jacobian matrix and determinant; Compensation (psychology); Control theory (sociology); Computer science; Control (management); Control engineering; Engineering; Mathematics; Simulation; Artificial intelligence; Psychology","score_opus":0.013389256390185041,"score_gpt":0.31459855541000703,"score_spread":0.30120929901982196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068769351","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":[0.518678,0.00001757607,0.47886482,0.0011186477,0.001135152,0.0000381935,0.000001984578,0.000010079787,0.00013556117],"genre_scores_gemma":[0.9536198,0.000006866878,0.045870442,0.000059439935,0.0004295257,1.2642067e-7,0.0000016561274,0.000004021669,0.000008141509],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912065,0.00005046007,0.00030505398,0.0000545765,0.0003915197,0.000077757686],"domain_scores_gemma":[0.9986675,0.00014141567,0.0005187945,0.000034843146,0.00059067446,0.000046813522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005427679,0.00005033726,0.00011259709,0.0001258784,0.00010345091,0.00005849983,0.00012877744,0.0000454697,0.000010847361],"category_scores_gemma":[0.00020526374,0.000048177888,0.00004683157,0.0000635389,0.000071283226,0.00020410687,0.000008681158,0.00012603082,4.1539323e-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":[0.000060374885,0.000168215,0.022545354,0.000022476017,0.00011671159,0.000017302651,0.0025186439,0.7017021,0.09779374,0.0547393,0.00003361578,0.12028214],"study_design_scores_gemma":[0.0011262194,0.00006257543,0.013223123,0.00015175695,0.000029515482,0.000022001743,0.00041736665,0.9793507,0.0013409144,0.0034907728,0.00068076636,0.00010428327],"about_ca_topic_score_codex":0.00008204989,"about_ca_topic_score_gemma":0.00003186063,"teacher_disagreement_score":0.4349418,"about_ca_system_score_codex":0.000044246568,"about_ca_system_score_gemma":0.00013012314,"threshold_uncertainty_score":0.19646373},"labels":[],"label_agreement":null},{"id":"W2070446356","doi":"10.2316/journal.206.2013.2.206-3742","title":"AN OPTIMAL CONTROL OF BIPED ROBOT FOR HUMAN-LIKE WALKING","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Biped robot; Computer science; Robot; Control (management); Control theory (sociology); Physical medicine and rehabilitation; Artificial intelligence; Medicine","score_opus":0.005755550627634037,"score_gpt":0.2400922191433377,"score_spread":0.23433666851570367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070446356","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":[0.22086714,0.00018497756,0.7779965,0.00020328329,0.0005495539,0.00012630595,0.0000073946426,0.000023696979,0.00004115496],"genre_scores_gemma":[0.97603774,0.000035933183,0.023681011,0.000026050904,0.00018389474,0.0000053252884,0.000009103123,0.000012393567,0.00000856885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992496,0.0000112236585,0.00040672437,0.00005402456,0.00019218991,0.00008625771],"domain_scores_gemma":[0.99914646,0.00007597311,0.00019649426,0.000053360898,0.0004758295,0.00005187914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016117028,0.000081499056,0.00016943576,0.00015473094,0.000025754864,0.000075521486,0.00015278177,0.000046139783,0.000017770633],"category_scores_gemma":[0.000022573171,0.00007450493,0.0000716936,0.000025347805,0.000016701035,0.0003832378,0.00000841827,0.000066595094,8.001246e-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":[0.000015643926,0.000034782493,0.00023571176,0.000017305794,0.00011497327,0.0000012380444,0.00007425054,0.928503,0.03570652,0.0012857829,0.000042948464,0.033967856],"study_design_scores_gemma":[0.0012977906,0.00013708185,0.009470453,0.000053274267,0.000030437794,0.000023399645,0.000033249093,0.9871816,0.0003218056,0.0013288719,0.000045281,0.00007673457],"about_ca_topic_score_codex":0.0000063338334,"about_ca_topic_score_gemma":0.000002921896,"teacher_disagreement_score":0.7551706,"about_ca_system_score_codex":0.00003214051,"about_ca_system_score_gemma":0.000012169258,"threshold_uncertainty_score":0.3038223},"labels":[],"label_agreement":null},{"id":"W2070835050","doi":"10.2316/journal.206.2007.1.206-1005","title":"A CARBON NANOTUBE-BASED RADIATION SENSOR","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materials science; Carbon nanotube; Ionization; Dosimeter; Electrode; Radiation; Optoelectronics; Voltage; Ionization chamber; Nanotechnology; Optics; Electrical engineering; Chemistry; Physics","score_opus":0.008386943382015427,"score_gpt":0.2636955993197489,"score_spread":0.25530865593773344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070835050","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":[0.9465155,0.00018969672,0.049772456,0.0010848485,0.0020678944,0.000052878582,0.0000032477337,0.000025444844,0.0002880345],"genre_scores_gemma":[0.97912127,0.000018824014,0.02028159,0.00015123418,0.00039757363,3.4674645e-7,0.000003433468,0.000008099958,0.000017626142],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988037,0.00003166716,0.00045048888,0.00008846044,0.0005186095,0.000107103944],"domain_scores_gemma":[0.9988358,0.00020316413,0.00040477197,0.000066625675,0.00043214572,0.000057472396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007569882,0.000080260645,0.00011972218,0.00025663598,0.000032303644,0.00011377477,0.00016570296,0.0000511367,0.000022042812],"category_scores_gemma":[0.00015149458,0.00007235912,0.000050801103,0.000074649906,0.000038161663,0.00017363232,0.000025341584,0.00007528507,0.0000036670529],"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":[0.00013724335,0.000088367815,0.0048858086,0.000011603821,0.000030960142,0.000066282584,0.0002185483,0.03657197,0.9395372,0.0020974197,0.000069484726,0.016285082],"study_design_scores_gemma":[0.002056083,0.0002607241,0.028240979,0.00019192795,0.00006176476,0.00042584713,0.00007729976,0.1799312,0.78594637,0.0014293083,0.0011119446,0.0002665709],"about_ca_topic_score_codex":0.000013613219,"about_ca_topic_score_gemma":0.000004073101,"teacher_disagreement_score":0.15359087,"about_ca_system_score_codex":0.000120616634,"about_ca_system_score_gemma":0.000058208472,"threshold_uncertainty_score":0.29507193},"labels":[],"label_agreement":null},{"id":"W2071289785","doi":"10.2316/journal.206.2014.4.206-4086","title":"A SPARSE BASED RAIN REMOVAL ALGORITHM FOR IMAGE SEQUENCES","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Image (mathematics); Computer science; Artificial intelligence; Algorithm; Pattern recognition (psychology); Computer vision","score_opus":0.015402499606297962,"score_gpt":0.30038902350213015,"score_spread":0.2849865238958322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071289785","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00041728216,0.000019378745,0.9950043,0.0038745732,0.00049481017,0.000071007795,0.000002522874,0.00003830307,0.000077853525],"genre_scores_gemma":[0.023934692,0.000013985424,0.97521377,0.0006196831,0.00018057674,0.0000024361873,0.0000047041135,0.0000039634774,0.000026219192],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903923,0.000051886258,0.0003302927,0.0000937454,0.00040991246,0.000074950476],"domain_scores_gemma":[0.99881357,0.00018304911,0.00034322884,0.000069653455,0.00052871526,0.00006181101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075156236,0.00006348456,0.00010208519,0.00016703177,0.000036215453,0.00021760508,0.0003817402,0.000030237856,0.000007123612],"category_scores_gemma":[0.00026757363,0.00005370061,0.000052870644,0.000060606155,0.000040428957,0.00057347224,0.00003492634,0.000062353,0.0000014216868],"study_design_candidate":"design_other","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":[0.0000046009595,0.00004388153,0.000016432552,0.000008833968,0.000025511372,0.000022235636,0.00008922954,0.0008307023,0.005506948,0.008032698,0.00086875533,0.9845502],"study_design_scores_gemma":[0.0005480799,0.00012440656,0.00018144604,0.000060277256,0.0000066869334,0.00014887295,0.000009249782,0.9764096,0.012021785,0.009858957,0.00056776445,0.000062877414],"about_ca_topic_score_codex":0.0000025960999,"about_ca_topic_score_gemma":3.6994763e-7,"teacher_disagreement_score":0.9844873,"about_ca_system_score_codex":0.000037878464,"about_ca_system_score_gemma":0.00006064716,"threshold_uncertainty_score":0.21898472},"labels":[],"label_agreement":null},{"id":"W2072501440","doi":"10.2316/journal.206.2011.2.206-3303","title":"AN OPTICAL DEVICE FOR CLOSE OBJECT DETECTION","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Object (grammar); Artificial intelligence","score_opus":0.04043680297886931,"score_gpt":0.30967057825045213,"score_spread":0.2692337752715828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072501440","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":[0.10151945,0.000062383566,0.896985,0.000021780861,0.0010844739,0.000047475325,0.0000010779769,0.000039970095,0.0002383888],"genre_scores_gemma":[0.7775022,0.00003550956,0.2222338,0.0000140872235,0.00020038118,0.0000016480242,0.0000010617424,0.0000078594785,0.0000034907168],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999507,0.000012869379,0.00022457841,0.000046088775,0.00015173378,0.000057705678],"domain_scores_gemma":[0.99951196,0.00003261128,0.000082937135,0.00003523306,0.0002922481,0.00004503703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027104618,0.00005683986,0.00007472748,0.000119821794,0.000025719766,0.000029747469,0.00006819722,0.00003820044,0.0000060791435],"category_scores_gemma":[0.000058464186,0.00005290843,0.00003742887,0.00003507955,0.0000098720575,0.000340822,0.000003832272,0.00006651314,7.988352e-7],"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":[0.0001898784,0.00009550828,0.00038031067,0.000040838913,0.00018921324,0.0000072674875,0.00069441093,0.15144475,0.20282805,0.0038785161,0.000028505114,0.6402227],"study_design_scores_gemma":[0.0011345408,0.00047967845,0.0104231965,0.000058248996,0.00006686232,0.0001561556,0.0001569052,0.7311117,0.24128966,0.014099968,0.00083171384,0.0001913657],"about_ca_topic_score_codex":6.671867e-7,"about_ca_topic_score_gemma":0.0000033056945,"teacher_disagreement_score":0.6759827,"about_ca_system_score_codex":0.000040316147,"about_ca_system_score_gemma":0.0000080038035,"threshold_uncertainty_score":0.2157543},"labels":[],"label_agreement":null},{"id":"W2073304635","doi":"10.2316/journal.206.2010.1.206-3334","title":"FIRST-ORDER KINEMATIC CONTROL OF MANIPULATORS WITH AN INACTIVE LAST JOINT","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Joint (building); Order (exchange); Control theory (sociology); Control (management); Computer science; Engineering; Physics; Economics; Structural engineering; Artificial intelligence; Classical mechanics; Finance","score_opus":0.006042188183627975,"score_gpt":0.20800731228946534,"score_spread":0.20196512410583736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073304635","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":[0.27153242,0.000009612744,0.72767967,0.0001485219,0.00048375034,0.000047403835,0.0000026885361,0.0000138359665,0.000082101695],"genre_scores_gemma":[0.85601246,0.000013624931,0.14386392,0.000013810574,0.00007887463,6.594555e-7,0.0000025073386,0.000010687512,0.0000034549994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993127,0.000007539921,0.00031660844,0.00004719882,0.00025342157,0.00006254413],"domain_scores_gemma":[0.99927294,0.000033017903,0.00021350806,0.000059949045,0.00036790306,0.000052706127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013263318,0.000080544225,0.00015675847,0.00013538543,0.000018340417,0.000039867286,0.00009437198,0.000045235614,0.000018271814],"category_scores_gemma":[0.000033694192,0.00006253855,0.000027963175,0.00004730819,0.000021554426,0.0002454651,0.00000813237,0.00013769495,7.0676464e-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":[0.000016173324,0.00003929463,0.0005356111,0.000028615264,0.0001021564,0.000007921353,0.00014879486,0.97180283,0.003733274,0.022541963,0.0000052097535,0.0010381367],"study_design_scores_gemma":[0.0006736375,0.0001541268,0.010365119,0.00009029911,0.000032861375,0.00014844746,0.00006964172,0.9855928,0.00028989435,0.0025026288,0.000008345636,0.000072188726],"about_ca_topic_score_codex":0.000004253601,"about_ca_topic_score_gemma":0.00003538125,"teacher_disagreement_score":0.58448005,"about_ca_system_score_codex":0.00002227988,"about_ca_system_score_gemma":0.00001860478,"threshold_uncertainty_score":0.2550248},"labels":[],"label_agreement":null},{"id":"W2075119906","doi":"10.2316/journal.206.2014.4.206-3759","title":"ORION: PARROT VIRTUAL MACHINE EXTENSION FOR MOBILE ROBOT PROGRAMMING","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Extension (predicate logic); Computer science; Mobile robot; Robot; Embedded system; Operating system; Artificial intelligence; Programming language","score_opus":0.01372379579855083,"score_gpt":0.2771710887953172,"score_spread":0.2634472929967664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075119906","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005274033,0.00010979422,0.9912334,0.0014349094,0.0017528903,0.00013092806,0.0000016203679,0.00004410539,0.000018323284],"genre_scores_gemma":[0.44075647,0.00001770547,0.55876964,0.00010071686,0.00030551737,0.0000050638964,0.000006415855,0.000006689746,0.000031772946],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987985,0.000045704746,0.00042715797,0.00015500847,0.0004422667,0.00013135445],"domain_scores_gemma":[0.99857885,0.00019623095,0.00044954722,0.00012104399,0.0005749552,0.000079401834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007105573,0.00010540692,0.00016815362,0.00017573415,0.00008003741,0.0002384674,0.00044231024,0.00005091328,0.00000151245],"category_scores_gemma":[0.00020448053,0.000089221336,0.00007065587,0.0000806871,0.000023393404,0.00049625075,0.000083694176,0.00010816355,0.000002637467],"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":[0.000019593535,0.00009320869,0.00034870126,0.000010820011,0.00005709538,0.000014594769,0.00035751698,0.37817562,0.0010746501,0.019561682,0.00019024646,0.6000963],"study_design_scores_gemma":[0.0006983925,0.0004976991,0.0021567396,0.00010337753,0.0000131015,0.00028668728,0.000019934836,0.99163944,0.00029340354,0.0020398148,0.0021449947,0.000106416206],"about_ca_topic_score_codex":0.000002888789,"about_ca_topic_score_gemma":3.7656628e-7,"teacher_disagreement_score":0.6134638,"about_ca_system_score_codex":0.00004499474,"about_ca_system_score_gemma":0.000041119743,"threshold_uncertainty_score":0.36383405},"labels":[],"label_agreement":null},{"id":"W2075229264","doi":"10.2316/journal.206.2014.1.206-3807","title":"UNIFIED STIFFNESS MODEL OF LOWER MOBILITY PARALLEL MANIPULATORS WITH LINEAR ACTIVE LEGS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Stiffness; Computer science; Control theory (sociology); Structural engineering; Engineering; Artificial intelligence","score_opus":0.011178911552378443,"score_gpt":0.22363865217139264,"score_spread":0.2124597406190142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075229264","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":[0.2927573,0.000006841051,0.70675623,0.00006695903,0.00023916914,0.000033146534,0.0000031750928,0.000013072994,0.00012405944],"genre_scores_gemma":[0.8834372,0.00002458245,0.11644575,0.000011886687,0.000052092757,5.013885e-7,0.0000040331593,0.000010140271,0.000013804088],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992906,0.000011252215,0.00030085404,0.000059078637,0.00027221,0.000065989974],"domain_scores_gemma":[0.9993653,0.000037098416,0.00017769737,0.00006664271,0.00030789568,0.000045321965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014131574,0.00008470742,0.00015357434,0.00009193832,0.00001569472,0.000021587002,0.00011283675,0.000047331236,0.000004694511],"category_scores_gemma":[0.00002254745,0.00006772217,0.000037427028,0.0000382341,0.000022174429,0.00018584702,0.000015216311,0.00009641312,4.8855384e-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":[0.00005291404,0.000037112026,0.000059594808,0.000018817107,0.00006858334,0.0000019836205,0.00007961324,0.969352,0.0009979457,0.026270142,0.000005102821,0.0030561967],"study_design_scores_gemma":[0.000456591,0.00007905404,0.0023635207,0.000063560576,0.00002294932,0.000022698461,0.000027994984,0.99122554,0.00020809138,0.00545365,0.000004861353,0.00007151068],"about_ca_topic_score_codex":0.000003150758,"about_ca_topic_score_gemma":0.0000031043087,"teacher_disagreement_score":0.5906799,"about_ca_system_score_codex":0.00003867968,"about_ca_system_score_gemma":0.000021007656,"threshold_uncertainty_score":0.27616298},"labels":[],"label_agreement":null},{"id":"W2075285717","doi":"10.2316/journal.206.2004.2.206-2725","title":"An Extended G-Code to be used on Networked Industrial Robots","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Code (set theory); Robot; Programming language; Embedded system; Artificial intelligence","score_opus":0.025893596861110334,"score_gpt":0.2672260486280539,"score_spread":0.24133245176694354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075285717","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":[0.20190115,0.000013899091,0.79383147,0.0020087033,0.0019916208,0.0000818538,0.0000059896174,0.00005544362,0.00010983685],"genre_scores_gemma":[0.90797484,0.000029609619,0.09117334,0.0002530366,0.00052778004,0.0000010897955,0.000010858028,0.00001897999,0.000010483278],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990698,0.000014280372,0.00034418248,0.00008118944,0.00037879008,0.00011172842],"domain_scores_gemma":[0.9995161,0.000028844226,0.00010725182,0.00007883643,0.00014045314,0.0001285089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001942665,0.00010580737,0.00014052013,0.00018721151,0.00003084165,0.00011762782,0.00018112668,0.00007821108,0.000010312831],"category_scores_gemma":[0.000036654907,0.00009685467,0.000042457712,0.00007586456,0.00000866667,0.00022375309,0.000013808956,0.00015264751,0.0000036446088],"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":[0.000024625982,0.000046470195,0.000021832924,0.0000019303043,0.000044966207,0.000018445633,0.00016644466,0.9666284,0.0013200924,0.022598203,0.00008242095,0.009046172],"study_design_scores_gemma":[0.0017332674,0.00044643893,0.0016126274,0.00015353491,0.000025677171,0.000091213995,0.0000648668,0.98592323,0.0007233108,0.008877422,0.00016303043,0.00018536409],"about_ca_topic_score_codex":0.0000035640157,"about_ca_topic_score_gemma":0.0000105239515,"teacher_disagreement_score":0.70607364,"about_ca_system_score_codex":0.000120716075,"about_ca_system_score_gemma":0.000032254575,"threshold_uncertainty_score":0.39496186},"labels":[],"label_agreement":null},{"id":"W2078805444","doi":"10.2316/journal.206.2008.3.206-3065","title":"AUTOMATED REAL-TIME MOTION PLANNING AND CONTROL OF CONSTRUCTION EQUIPMENT MECHANISM","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"BIM and Construction Integration","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mechanism (biology); Computer science; Motion (physics); Control (management); Real-time computing; Artificial intelligence","score_opus":0.008226281094036055,"score_gpt":0.22200889318183334,"score_spread":0.21378261208779728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078805444","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":[0.65356725,0.00013771855,0.34495342,0.00013839388,0.00079040974,0.000057832636,0.00000716395,0.00010270496,0.00024509375],"genre_scores_gemma":[0.98880845,0.00027924223,0.010796864,0.000008212927,0.0000858676,8.784085e-7,0.000006337169,0.0000070892474,0.0000070465107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924934,0.000019036721,0.00039419063,0.000052811694,0.00022801472,0.000056578487],"domain_scores_gemma":[0.999379,0.000031903917,0.00023518864,0.000030972482,0.00028666266,0.00003630277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011943066,0.00007679121,0.00013803756,0.00020104424,0.00003815942,0.000025047742,0.000046839064,0.00005909488,0.000012789547],"category_scores_gemma":[0.00001805457,0.00007247172,0.000031426574,0.00004670374,0.00004821767,0.00026855295,0.0000072596995,0.00007068085,9.879478e-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":[0.00014497944,0.00008816767,0.010271249,0.00010476196,0.000795735,0.00005223356,0.0018703912,0.45487988,0.39234295,0.06430369,0.0003768573,0.07476909],"study_design_scores_gemma":[0.0009472919,0.00007759328,0.015487887,0.00012436544,0.000035533263,0.001244313,0.000102240636,0.9704883,0.008943827,0.0024351752,0.000024081792,0.000089392655],"about_ca_topic_score_codex":0.000003626896,"about_ca_topic_score_gemma":2.1692678e-7,"teacher_disagreement_score":0.51560843,"about_ca_system_score_codex":0.00004690498,"about_ca_system_score_gemma":0.000018047811,"threshold_uncertainty_score":0.29553106},"labels":[],"label_agreement":null},{"id":"W2079556685","doi":"10.2316/journal.206.2004.3.206-2635","title":"Neural Network Adaptive Impedance Control of Constrained Robots","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Computer science; Impedance control; Electrical impedance; Control (management); Robot; Adaptive control; Control theory (sociology); Artificial intelligence; Engineering; Electrical engineering","score_opus":0.010995501099297216,"score_gpt":0.23250130562958235,"score_spread":0.22150580453028512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079556685","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":[0.10521468,0.0002660455,0.8928196,0.00052655046,0.0008274158,0.000050555645,0.0000011377721,0.000029520414,0.00026449945],"genre_scores_gemma":[0.98529226,0.000049419883,0.014383999,0.00003910984,0.00021748093,3.6437598e-7,0.000002182158,0.00000814052,0.0000070258743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929214,0.000015494717,0.000368482,0.000041340434,0.00020795278,0.00007462049],"domain_scores_gemma":[0.999424,0.000050007264,0.00022369581,0.000030981777,0.0002342581,0.00003705952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013581355,0.00006957516,0.00013651869,0.00008572216,0.000020248399,0.000029301085,0.00008474311,0.000035029356,0.000009375421],"category_scores_gemma":[0.000033350876,0.00006574545,0.00005002788,0.00005383847,0.00002720129,0.00019927227,0.000007356386,0.000111551184,0.0000011205885],"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":[0.000015777268,0.000009046804,0.00048852374,0.000005409221,0.00007857919,0.00000959354,0.00014727755,0.9866829,0.0011243477,0.007559877,0.000030545565,0.003848111],"study_design_scores_gemma":[0.0011527949,0.00006529042,0.010783931,0.00009912369,0.000018297256,0.00011273176,0.00005883881,0.9865643,0.00015048226,0.0008995975,0.000030595358,0.00006405402],"about_ca_topic_score_codex":0.0000032033995,"about_ca_topic_score_gemma":0.0000020612229,"teacher_disagreement_score":0.8800776,"about_ca_system_score_codex":0.000045492256,"about_ca_system_score_gemma":0.000023501572,"threshold_uncertainty_score":0.26810217},"labels":[],"label_agreement":null},{"id":"W2080781583","doi":"10.2316/journal.206.2005.4.206-2913","title":"Feasibility of 2-D Multifingered Grasps","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.024792401462830238,"score_gpt":0.27764663282909563,"score_spread":0.2528542313662654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080781583","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":[0.74210906,0.0002517345,0.2555051,0.0008115552,0.00069391826,0.00004851809,9.042289e-7,0.000038884737,0.0005403113],"genre_scores_gemma":[0.985153,0.000056417244,0.014605691,0.000016174661,0.00014160396,1.5078919e-7,0.0000024786643,0.0000056440513,0.000018803237],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993942,0.000012713224,0.00032715438,0.00003360757,0.00018971153,0.000042651467],"domain_scores_gemma":[0.99955046,0.000033243457,0.00015046519,0.00003513557,0.00020323311,0.000027462687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016129899,0.000047168687,0.00008936629,0.00011784257,0.000012471804,0.00002517405,0.00007504001,0.000028139948,0.000026256954],"category_scores_gemma":[0.00005436664,0.00004425377,0.000038808794,0.000037006528,0.000014285169,0.00020410623,0.00000889219,0.00007766639,0.0000023974221],"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":[0.000006197102,0.000018370807,0.0046522454,0.0000092941955,0.00003255946,0.000001048476,0.00022225833,0.9695264,0.0033710727,0.0008148443,0.00008560311,0.021260101],"study_design_scores_gemma":[0.0004071449,0.000015919413,0.07069142,0.000046664692,0.000009016714,0.0000293834,0.00003410561,0.9271153,0.0010076176,0.00024518438,0.0003494338,0.00004877932],"about_ca_topic_score_codex":0.0000013248792,"about_ca_topic_score_gemma":0.0000022947881,"teacher_disagreement_score":0.24304399,"about_ca_system_score_codex":0.00004185818,"about_ca_system_score_gemma":0.000008641219,"threshold_uncertainty_score":0.18046165},"labels":[],"label_agreement":null},{"id":"W2081264158","doi":"10.2316/journal.206.2010.4.206-3325","title":"REACHABLE GRASPS ON A POLYGON OF A ROBOT ARM: FINDING CONVEX ROPES WITHOUT TRIANGULATION","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Regular polygon; Simple polygon; Vertex (graph theory); Polygon (computer graphics); Convex hull; Convex polygon; Polygon covering; Combinatorics; Mathematics; Robot; Minimum-weight triangulation; Computer science; Artificial intelligence; Delaunay triangulation; Geometry; Constrained Delaunay triangulation","score_opus":0.020892876619404244,"score_gpt":0.2969573623987184,"score_spread":0.27606448577931414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081264158","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":[0.118154235,0.000021742457,0.8763492,0.0037638678,0.0010412979,0.00010571612,0.000001987636,0.00002569186,0.0005362671],"genre_scores_gemma":[0.8985166,0.00003352696,0.101169504,0.00008320508,0.00010271517,7.968832e-7,0.0000040766977,0.000005157525,0.000084432555],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884117,0.000045781417,0.00042702918,0.00010243073,0.00049553945,0.00008802796],"domain_scores_gemma":[0.99866074,0.000106693195,0.0005303363,0.000102219674,0.00053724844,0.00006277444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000544747,0.00007777922,0.00014709432,0.00034400157,0.000048707538,0.00016007178,0.00033544927,0.000053204025,0.000018907827],"category_scores_gemma":[0.00022233672,0.00006538662,0.000052695945,0.00012690695,0.000033886274,0.0005684965,0.00005069902,0.00017947267,0.0000027087353],"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":[0.00014600065,0.0005601953,0.0062111686,0.00003526152,0.00021556832,0.000022877275,0.0022435235,0.44968158,0.078019574,0.3539675,0.00036407725,0.10853268],"study_design_scores_gemma":[0.0011707804,0.00027897145,0.009750361,0.0001557442,0.000010273387,0.00009372145,0.0000273256,0.973694,0.008288609,0.0062257736,0.00020076497,0.00010362454],"about_ca_topic_score_codex":0.000009155118,"about_ca_topic_score_gemma":0.000004369291,"teacher_disagreement_score":0.78036237,"about_ca_system_score_codex":0.000024614867,"about_ca_system_score_gemma":0.00006976473,"threshold_uncertainty_score":0.2666389},"labels":[],"label_agreement":null},{"id":"W2082071900","doi":"10.2316/journal.206.2011.2.206-3415","title":"GENERATING NEAR-OPTIMAL REFERENCE TRAJECTORIES FOR SMALL FIXED-WING UAVs","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fixed wing; Wing; Computer science; Trajectory; Control theory (sociology); Aerospace engineering; Artificial intelligence; Engineering; Physics","score_opus":0.030946395994098836,"score_gpt":0.23606921092527222,"score_spread":0.20512281493117338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082071900","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15822637,0.000069750946,0.8405005,0.00004594377,0.0009149598,0.000044271776,0.0000050137187,0.000029076095,0.00016412845],"genre_scores_gemma":[0.4213936,0.000045539935,0.57835907,0.000018159904,0.00015047674,0.0000013505191,0.0000060440098,0.000010405412,0.000015343023],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993905,0.0000074631807,0.000316636,0.000057357698,0.00013805833,0.000089991445],"domain_scores_gemma":[0.99950665,0.00004230105,0.00012766634,0.00004011034,0.0002402831,0.000043008193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016093736,0.0000816416,0.000112388414,0.000066238295,0.000049486913,0.000096472264,0.000116975985,0.000049671013,0.000011520147],"category_scores_gemma":[0.00004444334,0.00007447836,0.00004371608,0.000027458074,0.000013408835,0.00018521858,0.000014135665,0.0000854362,7.7922635e-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":[0.000012382814,0.000014575686,0.00014008743,0.000020303167,0.00007107895,0.000005735148,0.00064259087,0.964714,0.0025482217,0.018323423,0.000032447304,0.013475158],"study_design_scores_gemma":[0.00028481823,0.000078351986,0.001010545,0.00005724511,0.000020711132,0.00005801669,0.00008353227,0.9957537,0.0006164231,0.0018849157,0.00006452328,0.0000871965],"about_ca_topic_score_codex":0.00000453232,"about_ca_topic_score_gemma":0.000004989876,"teacher_disagreement_score":0.26316723,"about_ca_system_score_codex":0.000035307905,"about_ca_system_score_gemma":0.000023327348,"threshold_uncertainty_score":0.30371395},"labels":[],"label_agreement":null},{"id":"W2083862901","doi":"10.2316/journal.206.2013.3.206-3756","title":"A NOVEL PATH PLANNING APPROACH FOR MULTI-ROBOT BASED TRANSPORTATION","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Motion planning; Path (computing); Object (grammar); Computer science; Simulation; Mobile robot; Artificial intelligence","score_opus":0.04439924878649739,"score_gpt":0.29346257659803504,"score_spread":0.24906332781153764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083862901","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002667133,0.000049006998,0.99571,0.00082286005,0.00053340127,0.0001594883,0.0000062522745,0.000034853365,0.000016976743],"genre_scores_gemma":[0.25736567,0.0000021577493,0.74237615,0.000124355,0.000085860695,0.0000075632474,0.000020354215,0.0000060957163,0.000011800392],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893355,0.000017138367,0.0004219136,0.00013912642,0.00036808988,0.000120162],"domain_scores_gemma":[0.9987026,0.000096183714,0.00043873492,0.000081112994,0.00061105844,0.0000703342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002883442,0.00010259332,0.00014319915,0.00020313617,0.000055816698,0.00023721321,0.0003958604,0.00005419768,0.0000014518475],"category_scores_gemma":[0.000069527574,0.000090382215,0.00006917111,0.00008223659,0.000018072336,0.0007289781,0.000012674497,0.00009735395,0.0000011315476],"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":[0.000007616084,0.00015953778,0.0010532164,0.00002038699,0.000057202462,0.000006275627,0.0005732651,0.9773177,0.0033845243,0.0025253403,0.00018440616,0.014710514],"study_design_scores_gemma":[0.0011188446,0.00007956252,0.03883471,0.00008084179,0.0000116451365,0.000050004484,0.000039340433,0.9591718,0.00021236157,0.00027944465,0.000025597968,0.00009586733],"about_ca_topic_score_codex":0.000010056803,"about_ca_topic_score_gemma":1.02491065e-7,"teacher_disagreement_score":0.25469854,"about_ca_system_score_codex":0.000042368098,"about_ca_system_score_gemma":0.00006597533,"threshold_uncertainty_score":0.36856797},"labels":[],"label_agreement":null},{"id":"W2084236904","doi":"10.2316/journal.206.2007.1.206-1002","title":"SLIDING-MODE CONTROL FOR TELE-ROBOTIC NEUROSURGICAL SYSTEM","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Control theory (sociology); Computer science; Mode (computer interface); Constant (computer programming); Set (abstract data type); Sliding mode control; Control (management); The Internet; Lyapunov function; Linear matrix inequality; Mathematical optimization; Mathematics; Artificial intelligence; Nonlinear system","score_opus":0.009836633012479539,"score_gpt":0.2528420591332922,"score_spread":0.2430054261208127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084236904","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":[0.055580888,0.0001097536,0.9407926,0.00032466193,0.002695997,0.00011389247,0.000005158516,0.0000667321,0.00031029937],"genre_scores_gemma":[0.99462414,0.000016576094,0.0047148108,0.000043151624,0.0005592388,0.0000014969303,0.000003562541,0.000013106391,0.00002392561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908555,0.0000123992,0.00049905037,0.000055182987,0.00024728753,0.00010053219],"domain_scores_gemma":[0.99929446,0.00015106554,0.0001408127,0.00003906398,0.00030793325,0.00006665059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040972116,0.0000802623,0.00015931236,0.00015700966,0.000033849,0.000101546604,0.00009985554,0.000051297153,0.000003348841],"category_scores_gemma":[0.000053021777,0.000070472604,0.00006552384,0.000037187405,0.000009008266,0.00015517097,0.000005176112,0.00007183946,0.0000027659844],"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":[0.000053510994,0.00002927069,0.0008420607,0.000082057595,0.00016982252,0.000037422476,0.00020401513,0.9201622,0.0068400265,0.06354364,0.00042966972,0.0076063178],"study_design_scores_gemma":[0.0012808009,0.00006411064,0.0037726269,0.00010687861,0.000029562154,0.0004973114,0.00010815182,0.99240106,0.00049335463,0.00008379965,0.0010726727,0.000089661735],"about_ca_topic_score_codex":0.0000013684117,"about_ca_topic_score_gemma":0.000002246252,"teacher_disagreement_score":0.9390432,"about_ca_system_score_codex":0.00008364151,"about_ca_system_score_gemma":0.000013668487,"threshold_uncertainty_score":0.28737894},"labels":[],"label_agreement":null},{"id":"W2084360204","doi":"10.2316/journal.206.2009.3.206-3273","title":"TARGET TRACKING BY USING PARTICLE FILTER IN SENSOR NETWORKS","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Tracking (education); Particle filter; Particle (ecology); Wireless sensor network; Computer science; Filter (signal processing); Computer vision; Computer network; Geology; Psychology","score_opus":0.017592583184117053,"score_gpt":0.2687234748759303,"score_spread":0.25113089169181324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084360204","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":[0.13905689,0.00027200885,0.858209,0.0017446511,0.0006455245,0.000027695021,0.0000016392879,0.000019298644,0.000023252605],"genre_scores_gemma":[0.8932181,0.000074729265,0.10619881,0.00033263312,0.00016063095,1.0312128e-7,0.0000036262484,0.0000032761727,0.000008082779],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903834,0.000045292232,0.00039719103,0.00010746572,0.0002839824,0.00012770167],"domain_scores_gemma":[0.99938744,0.000067422116,0.00025179517,0.00008081578,0.00015906614,0.000053441418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031322104,0.00007553507,0.000116837065,0.000097478856,0.0000393911,0.00025089164,0.0002922459,0.00004831843,0.0000060564653],"category_scores_gemma":[0.00003983238,0.00006813695,0.000036503203,0.00011615251,0.000013112084,0.00068033155,0.000034625657,0.00014798882,7.3621607e-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":[0.00001580646,0.00008687791,0.0029093528,0.0000013413315,0.000014876655,0.000056023993,0.00021111504,0.93731207,0.0022311949,0.0025876495,0.0008063971,0.053767268],"study_design_scores_gemma":[0.00036881017,0.000045287463,0.008063614,0.00007341162,0.0000034175118,0.00014663773,0.000014459736,0.9892631,0.00060557574,0.0011111032,0.0002264446,0.00007812385],"about_ca_topic_score_codex":0.0000039305855,"about_ca_topic_score_gemma":5.477882e-7,"teacher_disagreement_score":0.75416124,"about_ca_system_score_codex":0.000039299503,"about_ca_system_score_gemma":0.000016202714,"threshold_uncertainty_score":0.2778544},"labels":[],"label_agreement":null},{"id":"W2085575617","doi":"10.2316/journal.206.2012.2.206-3390","title":"A BIOLOGICALLY INSPIRED CONTROLLER FOR TRAJECTORY TRACKING OF FLEXIBLE-JOINT MANIPULATORS","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Trajectory; Computer science; Tracking (education); Control theory (sociology); Joint (building); Controller (irrigation); Control engineering; Artificial intelligence; Engineering; Control (management); Physics; Biology; Psychology; Structural engineering","score_opus":0.04408146751199043,"score_gpt":0.2727071038061958,"score_spread":0.22862563629420535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085575617","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":[0.35436872,0.0004759675,0.6435921,0.00014034679,0.0011024498,0.00009247085,0.000001287969,0.00003890685,0.00018774568],"genre_scores_gemma":[0.9909173,0.000034178687,0.00873461,0.000030193041,0.00025475767,0.0000016334051,0.000004207771,0.000009848001,0.000013246519],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928504,0.000016252954,0.0004176634,0.000036829242,0.000154466,0.00008974206],"domain_scores_gemma":[0.99942654,0.000065556436,0.00022669826,0.000025796548,0.0002101218,0.00004530001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002782132,0.000070051756,0.0001536692,0.00016747277,0.00002032078,0.00002635143,0.00006701436,0.00005127015,0.00001843267],"category_scores_gemma":[0.00007196414,0.000059543305,0.000079835525,0.000038618735,0.000014100877,0.00023703932,0.000007313054,0.000074682575,9.007302e-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":[0.000035690307,0.000044779194,0.0060992935,0.000028928383,0.00017819525,8.3075383e-7,0.0006161641,0.95266134,0.011456435,0.008331084,0.00008395562,0.020463292],"study_design_scores_gemma":[0.001405812,0.000101596466,0.26500508,0.00012291851,0.000045727207,0.000055930886,0.00019387437,0.7297354,0.002192664,0.00046378167,0.0005386813,0.00013855957],"about_ca_topic_score_codex":0.0000010630755,"about_ca_topic_score_gemma":2.1231938e-7,"teacher_disagreement_score":0.6365486,"about_ca_system_score_codex":0.00003738095,"about_ca_system_score_gemma":0.000007835395,"threshold_uncertainty_score":0.24281055},"labels":[],"label_agreement":null},{"id":"W2086043887","doi":"10.2316/journal.206.2007.4.206-2956","title":"OPTIMAL MANIPULATOR TOLERANCE DESIGN USING HYBRID EVOLUTIONARY OPTIMIZATION TECHNIQUE","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Differential evolution; Process (computing); Optimal design; Selection (genetic algorithm); Computer science; Evolutionary algorithm; Manipulator (device); Mathematical optimization; Noise (video); Control theory (sociology); Task (project management); Engineering; Algorithm; Mathematics; Artificial intelligence; Robot; Machine learning","score_opus":0.014166173042490062,"score_gpt":0.24119911527553525,"score_spread":0.22703294223304518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086043887","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011549625,0.00013895302,0.98722655,0.00004674664,0.00084506493,0.00009136826,0.0000026290213,0.00004433761,0.000054718916],"genre_scores_gemma":[0.333138,0.00005946376,0.6666183,0.000014407246,0.00014819582,5.126732e-7,0.0000046288906,0.000012119213,0.0000043815307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991226,0.0000131357,0.0004114486,0.00006491253,0.00028124746,0.00010661239],"domain_scores_gemma":[0.9994154,0.00004117048,0.00016500763,0.000049273927,0.00027211136,0.00005706552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003711245,0.00009515081,0.00011562394,0.0002064954,0.000038870447,0.000054184835,0.00011667337,0.000052929117,0.000012051822],"category_scores_gemma":[0.000025383024,0.00009547182,0.00004092668,0.000063063526,0.000015095608,0.00031561448,0.000017422584,0.00010685328,7.3044447e-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":[0.000015643944,0.00001606211,0.000044460754,0.00000836959,0.000033444245,0.000031088362,0.000023519155,0.9932037,0.003306787,0.0018060858,0.000038075676,0.0014727873],"study_design_scores_gemma":[0.00022201907,0.00003657011,0.0004576495,0.00008232566,0.000014816839,0.00065377436,0.000015452853,0.9961808,0.001507612,0.0007172243,0.000015233901,0.000096540156],"about_ca_topic_score_codex":0.0000012416348,"about_ca_topic_score_gemma":1.5113116e-7,"teacher_disagreement_score":0.32158837,"about_ca_system_score_codex":0.00014339006,"about_ca_system_score_gemma":0.00003186776,"threshold_uncertainty_score":0.3893228},"labels":[],"label_agreement":null},{"id":"W2087118732","doi":"10.2316/journal.206.2013.4.206-3716","title":"TRACKING CONTROL OF A MOBILE ROBOT WITH STABILITY ANALYSIS1","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Tracking (education); Computer science; Stability (learning theory); Mobile robot; Control (management); Control theory (sociology); Robot; Artificial intelligence; Psychology; Machine learning","score_opus":0.011314777495964873,"score_gpt":0.24488289857611492,"score_spread":0.23356812108015004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087118732","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":[0.13550906,0.000082739796,0.8633957,0.0006937234,0.00019107827,0.00007973914,0.000001406303,0.000013748742,0.000032803],"genre_scores_gemma":[0.7851775,0.000008658189,0.21472806,0.00003357465,0.000042228785,0.000002052388,9.266614e-7,0.0000030672343,0.000003914925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874514,0.000054562654,0.00048305313,0.00010822228,0.0005175966,0.000091437134],"domain_scores_gemma":[0.99794966,0.0001459424,0.0006399868,0.00012262854,0.0010823632,0.000059428745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039530758,0.000082403836,0.00021157014,0.00018658898,0.00002766556,0.00015726066,0.0004021961,0.000032200096,0.000010960707],"category_scores_gemma":[0.00007204846,0.00006147641,0.000056247547,0.00013561924,0.00004095244,0.00081208244,0.000035811754,0.00009957701,0.0000019060765],"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":[0.000015859192,0.00016290775,0.01955717,0.000016542781,0.00030196903,0.000023201736,0.0009520809,0.9132872,0.004969059,0.0018966321,0.00002764626,0.05878973],"study_design_scores_gemma":[0.00069240236,0.00021385704,0.06146966,0.00008793107,0.000027460002,0.00013506405,0.00007846797,0.93519354,0.001141732,0.00087749655,0.000007234904,0.00007516987],"about_ca_topic_score_codex":0.000020993297,"about_ca_topic_score_gemma":7.640064e-7,"teacher_disagreement_score":0.64966846,"about_ca_system_score_codex":0.000041785064,"about_ca_system_score_gemma":0.00006606287,"threshold_uncertainty_score":0.2506935},"labels":[],"label_agreement":null},{"id":"W2088167214","doi":"10.2316/journal.206.2014.4.206-4054","title":"REAL-TIME OBSTACLE AVOIDANCE FOR AN UNDERACTUATED FLAT-FISH TYPE AUTONOMOUS UNDERWATER VEHICLE IN 3D SPACE","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Underactuation; Control theory (sociology); Obstacle avoidance; Position (finance); Turning radius; Computer science; Underwater; Trajectory; Simulation; Engineering; Aerospace engineering; Artificial intelligence; Physics; Mobile robot; Control (management); Robot; Geology","score_opus":0.01584661628944128,"score_gpt":0.2525776908453961,"score_spread":0.23673107455595482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088167214","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":[0.86918294,0.000034190896,0.12897007,0.0010121472,0.00029931247,0.00010545967,0.0000042030606,0.00006485305,0.00032682862],"genre_scores_gemma":[0.9836181,0.00008481164,0.016008861,0.000050856488,0.00011740188,0.0000019642441,0.000024514018,0.000018671732,0.0000748465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992354,0.00004414862,0.00038165346,0.00007314118,0.00016229569,0.00010338857],"domain_scores_gemma":[0.9993723,0.00008804432,0.00014363385,0.00009665342,0.0002494966,0.000049851726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030748127,0.00008709857,0.00014460999,0.00012964895,0.000033400163,0.00012955828,0.00019224033,0.000056657187,0.00000926993],"category_scores_gemma":[0.000011568777,0.00008238375,0.000029863355,0.00005938578,0.000014101446,0.00035972835,0.000019406945,0.000092374765,0.000008550126],"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":[0.00008261998,0.00010167893,0.0015805954,0.00005880908,0.00015276212,0.0000041346684,0.0016228659,0.75675654,0.2057857,0.0021845202,0.00038371613,0.031286065],"study_design_scores_gemma":[0.0007208603,0.000114231036,0.005013464,0.00008214034,0.0000096961985,0.00003138374,0.000063885185,0.9851671,0.0045130337,0.0017508352,0.0024200492,0.00011331335],"about_ca_topic_score_codex":0.00002217146,"about_ca_topic_score_gemma":0.000033227247,"teacher_disagreement_score":0.22841059,"about_ca_system_score_codex":0.00010835321,"about_ca_system_score_gemma":0.000020639674,"threshold_uncertainty_score":0.33595118},"labels":[],"label_agreement":null},{"id":"W2089588892","doi":"10.2316/journal.206.2006.2.206-2792","title":"A MULTI-AGENT ARCHITECTURE FOR ROBOTIC SYSTEMS IN REAL-TIME ENVIRONMENTS","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Architecture; Computer science; Multi-agent system; Distributed computing; Real-time computing; Artificial intelligence; Embedded system; Human–computer interaction; Computer architecture","score_opus":0.014607182024321447,"score_gpt":0.2583543300796431,"score_spread":0.24374714805532163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089588892","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00929465,0.00013607163,0.9887328,0.00082865305,0.0008294809,0.00013684787,0.000002390993,0.00001706203,0.000022038663],"genre_scores_gemma":[0.32601506,0.000034333756,0.67352295,0.000030324214,0.0002051893,0.00000490875,0.000009205214,0.000009289938,0.0001687662],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988472,0.000045745343,0.0004750665,0.00013459817,0.00036765484,0.00012973764],"domain_scores_gemma":[0.99926025,0.00013279948,0.0003894911,0.0000912549,0.00009088868,0.000035334393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035010892,0.0000987698,0.00016861908,0.0002652954,0.00003114928,0.00016098245,0.000375988,0.000049820686,6.832814e-7],"category_scores_gemma":[0.000052982858,0.00008798498,0.000050326656,0.00006859187,0.000017632692,0.0002624032,0.00005255788,0.000088010915,0.0000037044922],"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":[0.0000052510345,0.0000872349,0.0005789272,0.000007960752,0.000024297513,0.00003680171,0.00012907713,0.99078465,0.003960876,0.0018432192,0.00011060519,0.0024311238],"study_design_scores_gemma":[0.00068589934,0.00006480301,0.026636321,0.00014531432,0.000008051377,0.00018787557,0.00000856927,0.971014,0.0000716687,0.0009915293,0.000099350495,0.000086601896],"about_ca_topic_score_codex":0.000037269812,"about_ca_topic_score_gemma":0.0000013285376,"teacher_disagreement_score":0.3167204,"about_ca_system_score_codex":0.0001200181,"about_ca_system_score_gemma":0.000034159908,"threshold_uncertainty_score":0.35879233},"labels":[],"label_agreement":null},{"id":"W2089601028","doi":"10.2316/journal.206.2005.3.206-2840","title":"Introduction of Logic in Language Modelling: The Minimum Perplexity Criterion","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Perplexity; Computer science; Programming language; Natural language processing; Language model","score_opus":0.015418889910876346,"score_gpt":0.28991528264987904,"score_spread":0.27449639273900267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089601028","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":[0.083626114,0.0009280747,0.8945373,0.020613587,0.00022115097,0.000034316396,5.360824e-7,0.000017769307,0.000021106825],"genre_scores_gemma":[0.69933605,0.000055588134,0.30029672,0.000075959004,0.000220651,2.898053e-7,9.75861e-7,0.0000015961499,0.000012156195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993059,0.000033775363,0.0002908248,0.000067793146,0.00025141914,0.00005025997],"domain_scores_gemma":[0.99934006,0.0000343749,0.00028564438,0.00007465756,0.0002518071,0.000013473529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039342383,0.00004772594,0.0000787916,0.0001571786,0.000018415652,0.00007710698,0.00035379137,0.000029746765,0.0000036652548],"category_scores_gemma":[0.00006355886,0.000032480082,0.000028243468,0.00009034035,0.000025356496,0.00053157145,0.00005686685,0.00011305676,4.5195398e-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":[0.000059135793,0.0002563583,0.0003784563,0.00004397317,0.00005349015,0.000029219203,0.008773505,0.39867768,0.028981257,0.30403525,0.00076329126,0.2579484],"study_design_scores_gemma":[0.00016596375,0.000043193435,0.00031770425,0.00005071449,0.0000038875905,0.00012018309,0.00006352251,0.97161335,0.0064107897,0.021007333,0.00015758045,0.000045751396],"about_ca_topic_score_codex":0.0000108375825,"about_ca_topic_score_gemma":0.000003540025,"teacher_disagreement_score":0.61570996,"about_ca_system_score_codex":0.000046054323,"about_ca_system_score_gemma":0.000022247807,"threshold_uncertainty_score":0.13244992},"labels":[],"label_agreement":null},{"id":"W2089698844","doi":"10.2316/journal.206.2007.3.206-2922","title":"APPLICATION AND COMPARISON OF PASSIVITY-BASED AND INTEGRATOR BACKSTEPPING CONTROL METHODS FOR TRAJECTORY TRACKING OF RIGID-LINK ROBOT MANIPULATORS INCORPORATING MOTOR DYNAMICS","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Passivity; Backstepping; Revolute joint; Integrator; Trajectory; Actuator; Computer science; Control engineering; Tracking (education); Controller (irrigation); Robot; Motion control; Engineering; Control (management); Adaptive control; Physics; Artificial intelligence","score_opus":0.011701708783713089,"score_gpt":0.3084170729205331,"score_spread":0.29671536413682004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089698844","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":[0.13725019,0.00039918927,0.861827,0.00010706784,0.00021262442,0.00016935704,0.000010743795,0.000015726542,0.000008085199],"genre_scores_gemma":[0.83613384,0.000023106237,0.16373803,0.000008311434,0.000070460315,0.000002781094,0.000010006501,0.000012787978,7.03533e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988559,0.000032816577,0.00075711444,0.00008927741,0.00017557136,0.000089323476],"domain_scores_gemma":[0.99827296,0.0005588267,0.00063502527,0.00004871385,0.00042698128,0.00005746929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085735996,0.00011902527,0.0003345402,0.0002654676,0.00003527288,0.0000383394,0.00008708028,0.00008620587,3.8588516e-7],"category_scores_gemma":[0.00012193703,0.00011445279,0.00006705121,0.00005899458,0.000046876085,0.00018135138,0.0000120961095,0.00013966992,1.9814616e-8],"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":[0.000090067624,0.000040888375,0.015256214,0.00017366289,0.00013678377,6.9758545e-7,0.000114929215,0.65592813,0.047561817,0.0035576997,8.528398e-7,0.27713826],"study_design_scores_gemma":[0.001201307,0.00013323834,0.025516829,0.00015954593,0.00006571084,0.000010835537,0.000114644,0.969681,0.0020634662,0.00095186726,0.000009178699,0.00009232865],"about_ca_topic_score_codex":0.0000074852555,"about_ca_topic_score_gemma":0.000029599716,"teacher_disagreement_score":0.69888365,"about_ca_system_score_codex":0.0000793274,"about_ca_system_score_gemma":0.000024312727,"threshold_uncertainty_score":0.46672496},"labels":[],"label_agreement":null},{"id":"W2090592005","doi":"10.2316/journal.206.2012.1.206-3517","title":"ROBUST CONTROL OF A RIGID ARTICULATED HOPPER","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Control (management); Computer science; Control theory (sociology); Artificial intelligence","score_opus":0.008478876194662815,"score_gpt":0.20607394157170383,"score_spread":0.19759506537704102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090592005","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":[0.39734405,0.00065957126,0.5997016,0.00043710993,0.0015310673,0.000056257388,0.0000061681485,0.00002085217,0.00024330964],"genre_scores_gemma":[0.9981328,0.00004584603,0.0015896903,0.000023853363,0.00019196744,5.0503127e-7,0.0000014577898,0.000006662973,0.0000071660825],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999325,0.00001310953,0.00034370413,0.000024383458,0.00021711641,0.00007672477],"domain_scores_gemma":[0.99953645,0.000036056885,0.00015246088,0.000032145548,0.00018763488,0.000055223238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002237302,0.000054317643,0.00013343654,0.00007559223,0.000008407191,0.00002422541,0.000075915515,0.000037716316,0.00000963567],"category_scores_gemma":[0.0000274682,0.000044517164,0.00005276936,0.000030525574,0.000008260975,0.0001866916,0.000006850601,0.000060420505,0.0000020539017],"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":[0.000025238838,0.00007168428,0.0029476238,0.000022065049,0.00036546396,0.000004293724,0.00012750519,0.9497526,0.018752519,0.017850557,0.00011200376,0.0099683935],"study_design_scores_gemma":[0.00079315936,0.000034605506,0.008235223,0.00006906475,0.000034681954,0.00006445585,0.000018635475,0.98976475,0.00029666955,0.00036525418,0.0002674815,0.000056041707],"about_ca_topic_score_codex":0.000002053466,"about_ca_topic_score_gemma":6.1670653e-7,"teacher_disagreement_score":0.6007888,"about_ca_system_score_codex":0.000035072004,"about_ca_system_score_gemma":0.00000699082,"threshold_uncertainty_score":0.18153572},"labels":[],"label_agreement":null},{"id":"W2092558212","doi":"10.2316/journal.206.2006.3.206-2944","title":"ON THE DETERMINATION OF OPEN-LOOP MANIPULATOR SINGULARITIES SUBJECT TO UNILATERAL OR NON-UNILATERAL CONSTRAINTS1","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Jacobian matrix and determinant; Gravitational singularity; Workspace; Rank (graph theory); Mathematics; Loop (graph theory); Subject (documents); Rotation (mathematics); Mechanism (biology); Control theory (sociology); Mathematical analysis; Pure mathematics; Computer science; Geometry; Artificial intelligence; Applied mathematics; Physics; Combinatorics; Robot","score_opus":0.013715264883820674,"score_gpt":0.2524656011199741,"score_spread":0.23875033623615344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092558212","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":[0.50319725,0.0000060386924,0.49478418,0.00061320304,0.00076127757,0.00013660766,0.00000889983,0.00001431374,0.00047824092],"genre_scores_gemma":[0.95129293,0.000010595059,0.048368324,0.00008286606,0.00009077336,0.0000013869103,0.0000074766285,0.000012498608,0.0001331581],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991509,0.000018340945,0.00041651865,0.00006138467,0.0002665658,0.000086314474],"domain_scores_gemma":[0.99941653,0.00009705591,0.00016404125,0.000066713736,0.00022291235,0.000032733424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022843313,0.00009734369,0.00014861042,0.00015800526,0.00003856944,0.00018620603,0.0002589026,0.00004444655,0.000028120458],"category_scores_gemma":[0.000039502796,0.0000676461,0.000039198174,0.00006558344,0.000024505567,0.00021818862,0.000041490814,0.000087929,0.0000014733164],"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":[0.000057223308,0.000054990025,0.00029340156,0.000025249177,0.00005322292,0.000033375956,0.0001940662,0.87344104,0.0045734416,0.11494073,0.00021075054,0.0061224992],"study_design_scores_gemma":[0.0005766355,0.00018711279,0.00904877,0.0002817257,0.000023153356,0.00016323468,0.0000709612,0.9723563,0.0024797677,0.014650164,0.000031532083,0.00013060498],"about_ca_topic_score_codex":0.000021236447,"about_ca_topic_score_gemma":0.000019464496,"teacher_disagreement_score":0.44809568,"about_ca_system_score_codex":0.000059804766,"about_ca_system_score_gemma":0.000027343583,"threshold_uncertainty_score":0.2758528},"labels":[],"label_agreement":null},{"id":"W2092854482","doi":"10.2316/journal.206.2007.3.206-2965","title":"VIEW-INVARIANT HUMAN ACTIVITY RECOGNITION BASED ON SHAPE AND MOTION FEATURES","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Invariant (physics); Artificial intelligence; Computer science; Human motion; Computer vision; Motion (physics); Pattern recognition (psychology); Mathematics","score_opus":0.022934384190924924,"score_gpt":0.2847754715261749,"score_spread":0.26184108733524997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092854482","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":[0.3444562,0.000027005937,0.65131116,0.0023795352,0.0006786224,0.000079614845,0.0000034221396,0.000039763112,0.0010246648],"genre_scores_gemma":[0.9907923,0.000034625093,0.008533582,0.00038879242,0.00021966195,5.8466804e-7,0.000009042493,0.000004565825,0.00001688608],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991299,0.00004276446,0.00025592666,0.00012200439,0.00036606632,0.00008337112],"domain_scores_gemma":[0.999136,0.00009450344,0.00034252426,0.000059212252,0.00030496067,0.00006284074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056043296,0.0000851753,0.000097368786,0.00033671845,0.000101304024,0.00022209373,0.00013087406,0.000056422054,0.000016288264],"category_scores_gemma":[0.000050850722,0.00007629364,0.00004200268,0.00007388829,0.000020425377,0.00057199656,0.000025471401,0.00014428316,0.0000033864858],"study_design_candidate":"design_other","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":[0.00004516423,0.0001896934,0.00025822732,0.000014429532,0.000039360228,0.000040403713,0.00014925387,0.0012276989,0.013385405,0.0070263552,0.00012804718,0.97749597],"study_design_scores_gemma":[0.0023953672,0.0007488746,0.43564472,0.00051212095,0.000048685033,0.00054653996,0.00004323381,0.5101168,0.02870715,0.020278307,0.0005853969,0.00037277286],"about_ca_topic_score_codex":0.0000049978935,"about_ca_topic_score_gemma":0.000007817957,"teacher_disagreement_score":0.9771232,"about_ca_system_score_codex":0.000051749128,"about_ca_system_score_gemma":0.000018369617,"threshold_uncertainty_score":0.31111643},"labels":[],"label_agreement":null},{"id":"W2094244990","doi":"10.2316/journal.206.2004.1.206-2729","title":"The Mobile Robot for Outer Surface Inspection of Boiler Tubes","year":2004,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Line Inspection Robots","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Boiler (water heating); Computer science; Mobile robot; Robot; Environmental science; Materials science; Artificial intelligence; Waste management; Engineering","score_opus":0.006674390519182362,"score_gpt":0.2445668151932444,"score_spread":0.23789242467406205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094244990","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":[0.3810566,0.00053705205,0.61317825,0.0012820013,0.0035427269,0.000153698,0.000009179232,0.00007459319,0.00016589322],"genre_scores_gemma":[0.98640764,0.0003356083,0.012971362,0.0000151367085,0.00023416897,0.0000024464052,0.0000028626516,0.000011975975,0.000018827133],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927753,0.0000072530893,0.0003803513,0.00004633617,0.00021707089,0.00007147417],"domain_scores_gemma":[0.9993273,0.000070718204,0.00012495348,0.00005191401,0.00039798085,0.000027152963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017590335,0.00006998599,0.00010003654,0.00008151378,0.00004969638,0.000058652484,0.000120903795,0.000037571535,0.0000024641959],"category_scores_gemma":[0.000039651386,0.00005407567,0.00006555072,0.000052502575,0.000030596755,0.00022589121,0.000012386251,0.00008124077,0.0000013168843],"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":[0.0000135400405,0.000023223445,0.00015022287,0.000009274601,0.00008849836,0.0000012303854,0.0001764283,0.9886945,0.006003308,0.0023238873,0.00025189345,0.0022640298],"study_design_scores_gemma":[0.0036128939,0.000518528,0.018851846,0.00033726176,0.000094810785,0.00043160803,0.00050721935,0.8872316,0.06860178,0.013967397,0.0054996037,0.00034547548],"about_ca_topic_score_codex":0.000005129834,"about_ca_topic_score_gemma":0.0000061483265,"teacher_disagreement_score":0.60535103,"about_ca_system_score_codex":0.0000974297,"about_ca_system_score_gemma":0.000023745679,"threshold_uncertainty_score":0.22051418},"labels":[],"label_agreement":null},{"id":"W2094805678","doi":"10.2316/journal.206.2008.3.206-2854","title":"ON THE DESIGN AND DEVELOPMENTAL METRICS OF A “SKIN-LIKE MULTI-INPUT QUASI-COMPLIANT RHEOLOGICAL GRIPPER SENSOR USING TACTILE MATRIX","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Tactile sensor; Matrix (chemical analysis); Tactile display; Computer science; Rheology; Materials science; Artificial intelligence; Robot; Composite material","score_opus":0.05377084826064075,"score_gpt":0.275809415541038,"score_spread":0.22203856728039725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094805678","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":[0.6074403,0.000051869527,0.39213395,0.000042721433,0.0002736342,0.000030511239,0.0000022930922,0.000011352441,0.000013406244],"genre_scores_gemma":[0.82471836,0.00014532071,0.17504807,0.000022927321,0.000040851395,3.771242e-7,0.0000011803793,0.000007763836,0.000015133566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993143,0.000037017915,0.0003136383,0.000055394834,0.00020708144,0.00007254958],"domain_scores_gemma":[0.9993918,0.0002639761,0.00015207144,0.000029559855,0.00013038554,0.000032202788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017255243,0.00008552106,0.00013922392,0.00012653104,0.000056062985,0.000028627199,0.00007559037,0.000039392067,0.000009852495],"category_scores_gemma":[0.00014557097,0.00005918901,0.000027792481,0.000057871028,0.00004329667,0.00011752672,0.000018529749,0.000076681055,9.911292e-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":[0.000029036348,0.000043926044,0.00031599027,0.000011007159,0.00007679895,0.00003088506,0.00024576206,0.95507777,0.04216531,0.0010716767,0.000050615556,0.0008812399],"study_design_scores_gemma":[0.00062098156,0.00009349762,0.0074651795,0.000121247795,0.000021243142,0.0014183923,0.00011887532,0.97057647,0.018995667,0.00036639784,0.00006598976,0.00013604462],"about_ca_topic_score_codex":0.0000033983686,"about_ca_topic_score_gemma":2.5563753e-7,"teacher_disagreement_score":0.21727811,"about_ca_system_score_codex":0.000049778988,"about_ca_system_score_gemma":0.000014907253,"threshold_uncertainty_score":0.24136578},"labels":[],"label_agreement":null},{"id":"W2095547391","doi":"10.2316/journal.206.2007.4.206-2999","title":"DESIGN FOR HIGH DYNAMIC PERFORMANCE ROBOT BASED ON DYNAMICALLY COUPLED DRIVING AND JOINT STOPS","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Torque; Robot; Actuator; Process (computing); Computer science; Swing; Joint (building); Control theory (sociology); Power (physics); Simulation; Control engineering; Engineering; Control (management); Artificial intelligence","score_opus":0.009327174941416126,"score_gpt":0.2248822002366618,"score_spread":0.21555502529524567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095547391","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":[0.13672176,0.000025013747,0.8622064,0.0002666579,0.0006310368,0.00010266578,0.0000017812357,0.000028692995,0.000016018059],"genre_scores_gemma":[0.6728641,0.00006127816,0.3269571,0.00003938965,0.00004875441,0.0000010376585,0.000006491967,0.0000134929805,0.0000083552495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990937,0.000009357356,0.00041560075,0.00008298215,0.00027041,0.00012793901],"domain_scores_gemma":[0.9993294,0.00016520053,0.00016918947,0.000054314347,0.00021332064,0.000068563604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005785001,0.00011395661,0.00016192923,0.00021770147,0.00004778908,0.00007800424,0.00008609812,0.00006416313,0.0000040324476],"category_scores_gemma":[0.000053683732,0.00010350343,0.00003653863,0.000041662424,0.000017059721,0.00015172073,0.000012212128,0.00011464963,5.487538e-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":[0.00003533985,0.00002200619,0.00006462109,0.000028550769,0.000035768913,0.000005793186,0.000031383588,0.9801185,0.0042515704,0.0027108865,0.0000061000046,0.012689488],"study_design_scores_gemma":[0.0007381173,0.00022130104,0.012285228,0.00017115133,0.000021472073,0.000042226984,0.000011676695,0.98475456,0.00025915503,0.0013848309,0.000002752885,0.00010752257],"about_ca_topic_score_codex":9.019284e-7,"about_ca_topic_score_gemma":0.0000027791355,"teacher_disagreement_score":0.53614235,"about_ca_system_score_codex":0.00011685499,"about_ca_system_score_gemma":0.000022270964,"threshold_uncertainty_score":0.42207474},"labels":[],"label_agreement":null},{"id":"W2103723349","doi":"10.2316/journal.206.2011.2.206-3419","title":"A COORDINATE-FREE METHOD FOR FINDING CONSTRAINT SINGULARITIES IN PARALLEL ROBOTS","year":2011,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Gravitational singularity; Constraint (computer-aided design); Computer science; Robot; Parallel manipulator; Mathematics; Artificial intelligence; Geometry; Mathematical analysis","score_opus":0.025617077959163025,"score_gpt":0.26541951430902877,"score_spread":0.23980243634986576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103723349","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005046878,0.000082830185,0.99348056,0.00020445978,0.00072223175,0.00007452819,0.000006584774,0.000020329828,0.00036161675],"genre_scores_gemma":[0.23367308,0.000051990155,0.766162,0.000025730167,0.00005681096,0.0000021659391,0.000003589065,0.000010314602,0.000014361171],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993118,0.000013845348,0.00036999298,0.000057713543,0.00014735525,0.00009927245],"domain_scores_gemma":[0.999552,0.00007921062,0.00012383069,0.00005113414,0.00015583947,0.00003794561],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033288644,0.00008232117,0.00015061046,0.00020218178,0.000019833937,0.000049748724,0.00015830249,0.000057030196,0.000010677702],"category_scores_gemma":[0.00008821919,0.00007896751,0.00005106916,0.00003832636,0.000015767755,0.00017808675,0.00002254283,0.00009244015,3.4163833e-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":[0.000020218997,0.000026387503,0.00019921463,0.000027542765,0.00006790768,0.000019648784,0.00053618924,0.83678514,0.0004184841,0.15000318,0.000058815243,0.011837261],"study_design_scores_gemma":[0.0008429497,0.000056031447,0.0016693327,0.00011563099,0.00001617359,0.00012256595,0.0001717186,0.92107403,0.00015971271,0.07566477,0.000018208917,0.00008884357],"about_ca_topic_score_codex":0.000008776983,"about_ca_topic_score_gemma":0.000011495482,"teacher_disagreement_score":0.2286262,"about_ca_system_score_codex":0.00005865092,"about_ca_system_score_gemma":0.000019635503,"threshold_uncertainty_score":0.32202017},"labels":[],"label_agreement":null},{"id":"W2129733735","doi":"10.2316/journal.206.2012.2.206-3556","title":"MODELLING AND CONTROL OF A KIND OF PARALLEL MECHANISM DRIVEN BY PIEZOELECTRIC ACTUATORS","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mechanism (biology); Control (management); Actuator; Piezoelectricity; Computer science; Control theory (sociology); Acoustics; Physics; Artificial intelligence","score_opus":0.0056962915853369335,"score_gpt":0.20072185819429658,"score_spread":0.19502556660895964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129733735","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":[0.21098559,0.0008499736,0.7878785,0.000066527835,0.00014105695,0.000040232953,0.000005673374,0.000006405088,0.000026036712],"genre_scores_gemma":[0.9941284,0.00055270694,0.0052115135,0.000015285603,0.000077229466,7.9907556e-7,0.000001863036,0.000008841572,0.0000033548886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925387,0.000013336844,0.00036237706,0.00003729372,0.00023515259,0.000097987395],"domain_scores_gemma":[0.999426,0.00006983264,0.0002592295,0.000031623425,0.00015634003,0.000056988956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016506556,0.00007825361,0.00019070215,0.00015689759,0.000012749281,0.000015007639,0.000082120336,0.000050697887,0.000004488267],"category_scores_gemma":[0.000020500618,0.00006918119,0.000042940173,0.00005400053,0.000013503978,0.00022387652,0.000007472589,0.000086099986,2.0356204e-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":[0.00007979418,0.00014028691,0.003266742,0.000057263278,0.0007828812,0.0000026164748,0.00076853076,0.7586071,0.009965275,0.016588207,0.00018118274,0.20956013],"study_design_scores_gemma":[0.0007568612,0.00006782571,0.00017689806,0.000034049877,0.00005236132,0.000031041658,0.00001642088,0.996326,0.0008148729,0.0016313209,0.00003166765,0.00006067394],"about_ca_topic_score_codex":0.000004174717,"about_ca_topic_score_gemma":1.978494e-7,"teacher_disagreement_score":0.7831428,"about_ca_system_score_codex":0.000028476088,"about_ca_system_score_gemma":0.000014508993,"threshold_uncertainty_score":0.2821127},"labels":[],"label_agreement":null},{"id":"W2144933759","doi":"10.2316/journal.206.2013.3.206-3806","title":"EM-BASED POINT TO PLANE ICP FOR 3D SIMULTANEOUS LOCALIZATION AND MAPPING","year":2013,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Iterative closest point; Metric (unit); Plane (geometry); Point (geometry); Simultaneous localization and mapping; Covariance; Probabilistic logic; Algorithm; Pose; Computer science; Mathematics; Artificial intelligence; Mathematical optimization; Geometry; Point cloud; Robot; Mobile robot; Statistics","score_opus":0.007916446888227955,"score_gpt":0.2185983517382533,"score_spread":0.21068190485002533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144933759","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":[0.05911794,0.00006520913,0.9393193,0.000819177,0.00043614145,0.00017682475,0.000006880119,0.00003340323,0.000025103545],"genre_scores_gemma":[0.92111856,0.000040415463,0.07835625,0.00027542247,0.00014419292,0.0000036121578,0.000032315693,0.0000173872,0.00001187744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925405,0.000011324589,0.0003588486,0.00007541001,0.00020547841,0.000094907955],"domain_scores_gemma":[0.99917257,0.00013190847,0.00011163925,0.000043397486,0.00045937698,0.00008111073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011646735,0.0000962498,0.00012596125,0.00022716596,0.00004066321,0.00016817941,0.00007025168,0.000052966796,0.000011938361],"category_scores_gemma":[0.00012392203,0.00009124535,0.000027834178,0.000064982676,0.000011103289,0.00017779996,0.000010127011,0.000053552925,0.0000031891418],"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":[0.000009143999,0.000013995158,0.00016042295,0.000035024033,0.000034396267,0.0000034390557,0.00018858792,0.97504914,0.001409475,0.00039376516,0.0003459912,0.022356618],"study_design_scores_gemma":[0.0004910819,0.00008337681,0.0007435187,0.00011041496,0.000013677094,0.000028396636,0.00007606171,0.99662197,0.00047945156,0.00057998684,0.000669983,0.00010210346],"about_ca_topic_score_codex":0.0000051380475,"about_ca_topic_score_gemma":0.0000035772794,"teacher_disagreement_score":0.8620006,"about_ca_system_score_codex":0.000057829096,"about_ca_system_score_gemma":0.000014395633,"threshold_uncertainty_score":0.37208772},"labels":[],"label_agreement":null},{"id":"W2295024663","doi":"10.2316/journal.206.2008.1.206-2940","title":"FACE ALIGNMENT BASED ON STATISTICAL MODELS AND GABOR WAVELETS","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Gabor wavelet; Artificial intelligence; Wavelet; Pattern recognition (psychology); Face (sociological concept); Computer science; Computer vision; Wavelet transform; Discrete wavelet transform; Sociology","score_opus":0.02436635618174059,"score_gpt":0.2666760283122777,"score_spread":0.2423096721305371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295024663","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":[0.033539243,0.000028569968,0.9627191,0.0032316255,0.00024779243,0.000033404485,0.0000048903325,0.000011246699,0.00018417067],"genre_scores_gemma":[0.89987767,0.00012084881,0.09960183,0.0003364238,0.00004083052,6.674122e-7,0.0000038392063,0.0000025660963,0.000015325462],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992158,0.000027063128,0.00020673766,0.00008656166,0.00040276322,0.000061096405],"domain_scores_gemma":[0.9994915,0.00008506215,0.00014075298,0.00004900992,0.0001722142,0.00006146716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000115203904,0.000059410213,0.00007858503,0.00011392558,0.00004946208,0.00007233292,0.00013226802,0.000027691298,0.000005495012],"category_scores_gemma":[0.000027824075,0.000048012902,0.00001887396,0.00003100874,0.00002691578,0.0003505185,0.000025149388,0.000064948144,0.000002707471],"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":[0.000089766574,0.0004814309,0.00038967826,0.000017902545,0.00007590692,0.00027161842,0.0014398948,0.6874102,0.0019200502,0.12111168,0.004846673,0.18194523],"study_design_scores_gemma":[0.0004709179,0.00011150051,0.0040266523,0.00009652143,0.0000037761863,0.00014432032,0.000013835561,0.9854128,0.00066063413,0.008923979,0.00007917899,0.000055921053],"about_ca_topic_score_codex":0.000001354958,"about_ca_topic_score_gemma":1.1917971e-7,"teacher_disagreement_score":0.86633843,"about_ca_system_score_codex":0.000028691704,"about_ca_system_score_gemma":0.000038373422,"threshold_uncertainty_score":0.19579093},"labels":[],"label_agreement":null},{"id":"W2314061543","doi":"10.2316/journal.206.2016.2.206-4361","title":"LOCOMOTION SYSTEM DESIGN AND DYNAMICS ANALYSIS OF A NEW TELESCOPIC MINIATURE IN-PIPE ROBOT","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Ratchet; Payload (computing); Crutch; Robot; Mechanism (biology); Engineering; Creep; Simulation; Structural engineering; Computer science; Mechanical engineering; Materials science; Physics; Artificial intelligence; Work (physics)","score_opus":0.005570694634390438,"score_gpt":0.211945300336325,"score_spread":0.20637460570193455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314061543","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":[0.18471484,0.00035081813,0.81423926,0.00034441074,0.00025703252,0.00005670714,0.000005366659,0.000014558212,0.000016978398],"genre_scores_gemma":[0.9820532,0.00031492792,0.017552035,0.0000047014005,0.00005012549,6.6906523e-7,0.0000036735385,0.000006972467,0.000013680066],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992376,0.000021647655,0.0004056201,0.00006491609,0.00020124477,0.00006898641],"domain_scores_gemma":[0.9994543,0.000102382335,0.00019354561,0.000050656872,0.0001509441,0.00004812438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019851782,0.00008237444,0.00022889793,0.0005144162,0.000008993568,0.000031847205,0.00009531553,0.00006147883,0.0000024509673],"category_scores_gemma":[0.000029964529,0.0000619651,0.000056759975,0.00014488351,0.000013922822,0.00019222232,0.000016058744,0.000060594455,2.8266103e-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":[0.000022632628,0.000017089807,0.0043908195,0.000028612885,0.00041483121,0.000009630949,0.00009221318,0.9223662,0.0021585522,0.0017870984,0.000012889337,0.068699434],"study_design_scores_gemma":[0.00071694003,0.00004025747,0.077234015,0.00027522622,0.00014443081,0.000024034616,0.000030318537,0.9210821,0.00007870916,0.00030728846,0.0000052070036,0.000061492545],"about_ca_topic_score_codex":0.000008714179,"about_ca_topic_score_gemma":0.000044207638,"teacher_disagreement_score":0.79733837,"about_ca_system_score_codex":0.00013426338,"about_ca_system_score_gemma":0.000023757779,"threshold_uncertainty_score":0.25268632},"labels":[],"label_agreement":null},{"id":"W2319558462","doi":"10.2316/journal.206.2016.2.206-4665","title":"MECHANISM DESIGN, DYNAMICS MODELLING AND EXPERIMENTS OF BIONIC UNDULATING FINS","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Mechanics and Biomechanics Studies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mechanism (biology); Dynamics (music); Computer science; Mechanics; Physics; Acoustics","score_opus":0.02652723055487427,"score_gpt":0.2423546307442588,"score_spread":0.21582740018938454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2319558462","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":[0.11719004,0.00023371098,0.88197285,0.00018094131,0.00035868373,0.00003149547,0.00000513071,0.0000105169,0.000016638942],"genre_scores_gemma":[0.9559893,0.001072447,0.042877212,0.000005551303,0.000038193466,5.027528e-7,7.3126284e-7,0.000007748396,0.000008291998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994152,0.00000945104,0.0002856541,0.000048816553,0.00017955172,0.00006129934],"domain_scores_gemma":[0.9995773,0.000049755294,0.00015127516,0.000030927255,0.00016370631,0.000027070902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017190455,0.000066609486,0.000108981774,0.00012256799,0.00002275739,0.000022800914,0.000067830195,0.000035619276,0.0000037446644],"category_scores_gemma":[0.000016124774,0.00004774286,0.000024954456,0.000031509306,0.000009315287,0.00012264751,0.000031140153,0.00003402277,2.959312e-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":[0.000029996954,0.00006384353,0.0000934441,0.000065382126,0.0005312546,0.000011308589,0.00060201786,0.47840738,0.23029637,0.22922437,0.00003460183,0.06064001],"study_design_scores_gemma":[0.00028567482,0.00005730136,0.000019607998,0.00016208984,0.000012494308,0.0000219946,0.00005328131,0.9569873,0.017859131,0.024479238,0.000005670514,0.0000561682],"about_ca_topic_score_codex":0.0000015070651,"about_ca_topic_score_gemma":7.636965e-7,"teacher_disagreement_score":0.83909565,"about_ca_system_score_codex":0.000052532567,"about_ca_system_score_gemma":0.000008576487,"threshold_uncertainty_score":0.19468974},"labels":[],"label_agreement":null},{"id":"W2347637477","doi":"10.2316/journal.206.2016.3.206-4334","title":"FUSION OF DRSSI AND AOA FOR AERIAL LOCALIZATION OF AN RF SOURCE WITH UNKNOWN TRANSMITTED POWER","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Non-line-of-sight propagation; Angle of arrival; Fusion; Power (physics); Sight; RF power amplifier; Physics; Computer science; Optics; Telecommunications; Antenna (radio); Wireless","score_opus":0.004643567769642982,"score_gpt":0.2119053647985483,"score_spread":0.20726179702890532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2347637477","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":[0.35884422,0.000041605323,0.6407592,0.00012752299,0.00013461767,0.00004790593,0.000006744758,0.000019637184,0.000018520104],"genre_scores_gemma":[0.9934725,0.00011036625,0.0063453303,0.0000083070545,0.00003903603,8.3733846e-7,0.0000052701075,0.000010037581,0.000008315495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994074,0.000008404069,0.00030902092,0.000048834198,0.00017452725,0.000051777715],"domain_scores_gemma":[0.99932563,0.00004444781,0.00018404494,0.00003998447,0.0003836652,0.000022239286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010739407,0.00006520777,0.00012534164,0.00016117496,0.00001712226,0.000015720376,0.00007499147,0.00005833472,0.000005856562],"category_scores_gemma":[0.000040614366,0.00004339736,0.00002391319,0.00005250799,0.00005350838,0.00021955917,0.000007643208,0.000027153155,6.201563e-8],"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":[0.00072922785,0.00019141372,0.0052672005,0.00027280656,0.00041336438,0.0000054087286,0.0019770565,0.53375274,0.13314399,0.029926272,0.00017830609,0.2941422],"study_design_scores_gemma":[0.0058675935,0.0012091355,0.0075938934,0.0008849114,0.000107748165,0.00011729442,0.00036141853,0.773129,0.20321146,0.0053906655,0.0018400173,0.00028689782],"about_ca_topic_score_codex":0.0000015987207,"about_ca_topic_score_gemma":0.0000030477254,"teacher_disagreement_score":0.6346283,"about_ca_system_score_codex":0.000018205135,"about_ca_system_score_gemma":0.000014526921,"threshold_uncertainty_score":0.17696929},"labels":[],"label_agreement":null},{"id":"W2374900773","doi":"10.2316/journal.206.2016.3.206-4746","title":"ARTIFICIAL IMMUNE NETWORK-BASED MULTI-ROBOT FORMATION PATH PLANNING WITH OBSTACLE AVOIDANCE","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Shandong University","keywords":"Obstacle avoidance; Motion planning; Obstacle; Computer science; Path (computing); Robot; Artificial intelligence; Mobile robot; Computer network; Geography","score_opus":0.020814101877144036,"score_gpt":0.25337927114406866,"score_spread":0.23256516926692464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2374900773","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":[0.024074845,0.00012439853,0.9722685,0.0026048797,0.000779049,0.00008887631,0.000005257394,0.000040989256,0.000013163522],"genre_scores_gemma":[0.92221534,0.0000076158367,0.07749095,0.00006913662,0.00018794936,0.0000025970326,0.00000513643,0.0000063961725,0.000014870465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998608,0.00006433042,0.0005548321,0.00012007081,0.00049754785,0.00015522841],"domain_scores_gemma":[0.99837565,0.00013155962,0.0007763483,0.00012110726,0.000533254,0.000062082414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044178925,0.0001102436,0.00016002991,0.00012513698,0.00007748398,0.0002479663,0.0004101251,0.000043128683,0.0000022903348],"category_scores_gemma":[0.0000749942,0.000073110234,0.000052599687,0.00010248339,0.000026092404,0.0011642198,0.000040626204,0.00008057306,0.0000054583584],"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":[0.00014140736,0.00018466375,0.006056911,0.000021898752,0.00016930891,0.00011557878,0.00043514252,0.82520825,0.021382855,0.017433353,0.00023914338,0.12861149],"study_design_scores_gemma":[0.0015724775,0.00014180578,0.026788505,0.00066131935,0.000014224177,0.00014815068,0.00002103296,0.96739274,0.002286284,0.0006070817,0.00021949981,0.00014687984],"about_ca_topic_score_codex":0.0000032056446,"about_ca_topic_score_gemma":0.0000021634073,"teacher_disagreement_score":0.8981405,"about_ca_system_score_codex":0.000111845104,"about_ca_system_score_gemma":0.00007045841,"threshold_uncertainty_score":0.2981349},"labels":[],"label_agreement":null},{"id":"W2379084512","doi":"10.2316/journal.206.2016.3.206-4774","title":"VARIABLE PITCH HELICAL DRIVE IN-PIPE ROBOT","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Line Inspection Robots","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Computer science; Variable (mathematics); Artificial intelligence; Mathematics; Mathematical analysis","score_opus":0.005811015956798116,"score_gpt":0.22743756542702837,"score_spread":0.22162654947023025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2379084512","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":[0.05832569,0.00013728133,0.93494445,0.0029783759,0.0023447059,0.000050649054,0.000004531708,0.000067971654,0.0011463697],"genre_scores_gemma":[0.97787654,0.00019534396,0.02151773,0.00004801072,0.00029076354,0.0000010062178,0.0000011960398,0.000011845248,0.000057563648],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919736,0.000014054781,0.0003767775,0.00006313014,0.00025289698,0.0000957766],"domain_scores_gemma":[0.9995134,0.000074618045,0.000103320315,0.000049980936,0.00020726703,0.000051435527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016101313,0.000078118144,0.00011843912,0.00023716636,0.000012596469,0.00004394496,0.00013282601,0.000050987124,0.00004821775],"category_scores_gemma":[0.00008112245,0.000059369977,0.00003249807,0.00008190602,0.000017591263,0.00034809424,0.000021554479,0.000099147604,0.000012661919],"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":[0.00003575906,0.000117364005,0.006973283,0.0000200921,0.00019468534,0.000078407014,0.00023135068,0.8333257,0.09439704,0.023294298,0.0015395104,0.039792527],"study_design_scores_gemma":[0.006389173,0.0002828491,0.16225824,0.0014390178,0.00006237411,0.0014385104,0.00008848148,0.740911,0.025612416,0.051907904,0.008858986,0.00075104256],"about_ca_topic_score_codex":0.0000033437977,"about_ca_topic_score_gemma":0.0000033016356,"teacher_disagreement_score":0.91955084,"about_ca_system_score_codex":0.00013814212,"about_ca_system_score_gemma":0.00002502185,"threshold_uncertainty_score":0.24210374},"labels":[],"label_agreement":null},{"id":"W2387166600","doi":"10.2316/journal.206.2016.3.206-4770","title":"DUBINS-RRT PATH PLANNING AND HEADING-VECTOR CONTROL GUIDANCE FOR A UUV RECOVERY","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Particle accelerators and beam dynamics","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China; National Science Fund for Distinguished Young Scholars; National Science Foundation","keywords":"Heading (navigation); Motion planning; Path (computing); Control (management); Control theory (sociology); Computer science; Aeronautics; Engineering; Aerospace engineering; Artificial intelligence; Robot; Operating system","score_opus":0.00969646996854272,"score_gpt":0.2441634222755961,"score_spread":0.23446695230705336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2387166600","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":[0.6023207,0.0002459291,0.39628512,0.0005685841,0.00048447162,0.00004302681,0.00001614031,0.000018302797,0.000017778315],"genre_scores_gemma":[0.99443907,0.000103997125,0.005193554,0.000047340174,0.00018843933,0.0000019777053,0.0000011471668,0.000009225025,0.000015268395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994943,0.00000683639,0.000251428,0.00005064042,0.00011739932,0.0000793649],"domain_scores_gemma":[0.99956906,0.00010654561,0.000108008586,0.000028804307,0.00014478865,0.000042821066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001357656,0.000063968015,0.00010359269,0.00006885565,0.00002468562,0.00006624176,0.00006091589,0.00003192106,0.0000021270355],"category_scores_gemma":[0.00006723391,0.000046623187,0.000031299183,0.000020484631,0.0000128733245,0.0002871106,0.000007876378,0.0000355719,5.027483e-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":[0.00038883925,0.00012978095,0.13202244,0.00015861855,0.0009216314,0.0000720672,0.0007224109,0.3888776,0.27319363,0.013693209,0.0034680509,0.18635172],"study_design_scores_gemma":[0.0025196713,0.00018340943,0.0944231,0.0005009223,0.00003830117,0.0001456504,0.00002083147,0.8954229,0.002502477,0.0031587628,0.00090658205,0.00017740957],"about_ca_topic_score_codex":7.7034156e-7,"about_ca_topic_score_gemma":9.105627e-7,"teacher_disagreement_score":0.5065453,"about_ca_system_score_codex":0.00005064692,"about_ca_system_score_gemma":0.000010284546,"threshold_uncertainty_score":0.19012384},"labels":[],"label_agreement":null},{"id":"W2398289186","doi":"10.2316/journal.206.2015.5.206-4414","title":"DESIGN AND ANALYSIS OF AN INNOVATIVE MODULAR ROBOTIC MANIPULATOR","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Modular design; Robot manipulator; Computer science; Manipulator (device); Control engineering; Parallel manipulator; Robot; Artificial intelligence; Engineering; Programming language","score_opus":0.035799038202323226,"score_gpt":0.27394976313516517,"score_spread":0.23815072493284195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398289186","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":[0.33709863,0.00015854326,0.66243607,0.000049993552,0.00019832757,0.000029173498,0.0000012899874,0.000009231569,0.000018714376],"genre_scores_gemma":[0.9397276,0.00007463811,0.060124427,0.000014417147,0.000039023456,3.9075533e-7,0.000007349632,0.0000072992416,0.0000048257766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992032,0.000028048918,0.00036772477,0.00006140565,0.00028094923,0.00005868368],"domain_scores_gemma":[0.99904305,0.00003075119,0.0001673058,0.000057177534,0.0006339134,0.00006777549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033131998,0.00007581554,0.00019348417,0.00040655016,0.000011495162,0.000048789934,0.00011007558,0.000038753697,0.0000049863265],"category_scores_gemma":[0.000043707347,0.00006707816,0.00002733669,0.00024336303,0.000025045527,0.00029539023,0.000016716953,0.000068997375,3.676615e-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":[0.000010210222,0.000020293412,0.00060466153,0.000005917359,0.000507721,0.000008930762,0.00053477485,0.98721135,0.0014321053,0.0015898147,0.000010356896,0.00806387],"study_design_scores_gemma":[0.00017340633,0.00008522,0.011068314,0.000024208231,0.00012294854,0.00003539033,0.000067770896,0.9856823,0.0017509469,0.0009112459,0.00001170403,0.00006653644],"about_ca_topic_score_codex":0.0000051619613,"about_ca_topic_score_gemma":0.0000012676155,"teacher_disagreement_score":0.602629,"about_ca_system_score_codex":0.00003731206,"about_ca_system_score_gemma":0.000020382395,"threshold_uncertainty_score":0.27353677},"labels":[],"label_agreement":null},{"id":"W2398336359","doi":"10.2316/journal.206.2015.5.206-4391","title":"OPTIMAL CALIBRATION AND IDENTIFICATION OF A 2-DOF PARALLEL MANIPULATOR WITH REDUNDANT ACTUATION","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Youth Innovation Promotion Association; State Key Laboratory of Mechanical System and Vibration; Youth Innovation Promotion Association of the Chinese Academy of Sciences; University of Science and Technology of China; National Natural Science Foundation of China","keywords":"Parallel manipulator; Identification (biology); Calibration; Computer science; Manipulator (device); Control theory (sociology); Artificial intelligence; Mathematics; Robot","score_opus":0.014142688639092174,"score_gpt":0.23167303589393481,"score_spread":0.21753034725484263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398336359","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":[0.42846188,0.00011092333,0.5709544,0.00020101157,0.00017500974,0.00004789788,0.0000022081595,0.000016125308,0.000030564624],"genre_scores_gemma":[0.9757825,0.00013670215,0.023972513,0.0000069388307,0.00006307427,0.0000011997786,0.000015832116,0.000008826124,0.000012412209],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926656,0.00000930106,0.00035124802,0.00005527256,0.00027248208,0.000045147754],"domain_scores_gemma":[0.99929696,0.000015389058,0.00027206988,0.000038369235,0.00033164764,0.000045573473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018313059,0.00006714325,0.00009812055,0.00013840833,0.000016208698,0.00007990121,0.000059196223,0.000036399324,0.0000023148327],"category_scores_gemma":[0.000030381143,0.000056534,0.000013766727,0.000043762855,0.00002060794,0.0004789626,0.000010035101,0.000050871437,1.960011e-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":[0.00003581299,0.000014932713,0.00043757455,0.000029270946,0.000044727614,0.0000016446581,0.00047394144,0.9941755,0.0010679187,0.00072113925,0.000032226333,0.0029653076],"study_design_scores_gemma":[0.00058906456,0.00008020869,0.0072158384,0.00006822499,0.000028613258,0.000070235175,0.00011696172,0.9855658,0.0056130793,0.0005481181,0.000034855668,0.00006899853],"about_ca_topic_score_codex":0.0000033266022,"about_ca_topic_score_gemma":0.000001468248,"teacher_disagreement_score":0.5473206,"about_ca_system_score_codex":0.00003581749,"about_ca_system_score_gemma":0.000026359876,"threshold_uncertainty_score":0.23053896},"labels":[],"label_agreement":null},{"id":"W2398897972","doi":"10.2316/journal.206.2015.5.206-4200","title":"SELECTIVE TOPOLOGICAL APPROACH TO MOBILE ROBOT NAVIGATION WITH RECURRENT NEURAL NETWORKS","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mobile robot; Computer science; Artificial neural network; Artificial intelligence; Topology (electrical circuits); Mobile robot navigation; Robot; Robot control; Mathematics; Combinatorics","score_opus":0.025449795444845807,"score_gpt":0.283942015544546,"score_spread":0.2584922200997002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398897972","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":[0.023845633,0.0000784993,0.97421116,0.0006543985,0.0008785134,0.00014058003,7.3146515e-7,0.00003540427,0.00015505498],"genre_scores_gemma":[0.65100485,0.0000038865956,0.34871328,0.00008188058,0.00017277755,0.000006169744,0.000005123114,0.0000038196217,0.000008181926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878794,0.000070641596,0.00030945503,0.00015895428,0.0005451405,0.00012788038],"domain_scores_gemma":[0.9987025,0.000057446236,0.00029620985,0.00008746917,0.0006979361,0.00015841286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041145124,0.00010432803,0.00014990555,0.00014518153,0.000041069816,0.00020670907,0.00041502778,0.000049776725,3.292074e-7],"category_scores_gemma":[0.000056902412,0.0000778469,0.00003053254,0.00019825358,0.000026266247,0.00048768125,0.000087910215,0.00018471976,0.0000013544001],"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":[0.000026250109,0.00007804796,0.0005542845,0.0000018264867,0.00003182927,0.000018159037,0.0005841404,0.97150314,0.000018659335,0.0025530471,0.00014120905,0.024489427],"study_design_scores_gemma":[0.00043661144,0.0006625191,0.00478765,0.000052516265,0.000008311718,0.0006112383,0.000083494044,0.9926152,0.000025273273,0.00058377994,0.000034966364,0.00009843753],"about_ca_topic_score_codex":0.0000045678426,"about_ca_topic_score_gemma":1.8808865e-7,"teacher_disagreement_score":0.62715924,"about_ca_system_score_codex":0.00011949677,"about_ca_system_score_gemma":0.00006144623,"threshold_uncertainty_score":0.31745043},"labels":[],"label_agreement":null},{"id":"W2399131218","doi":"10.2316/journal.206.2015.4.206-4075","title":"CONTROL OF AN X–Y PLANAR INVERTED PENDULUM USING PSO-BASED SMC","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inverted pendulum; Planar; Control theory (sociology); Double inverted pendulum; Mathematics; Physics; Computer science; Control (management); Artificial intelligence; Nonlinear system","score_opus":0.02419119439180846,"score_gpt":0.25785071317483194,"score_spread":0.2336595187830235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399131218","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":[0.18357575,0.00015165441,0.8153998,0.00010001805,0.00064589694,0.000054595956,0.000007660002,0.000023777357,0.000040839324],"genre_scores_gemma":[0.9791518,0.0000033678245,0.02064596,0.000032643322,0.00014807533,4.3632713e-7,0.000004370497,0.000011407098,0.0000019653694],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991491,0.000035548852,0.0003895341,0.00004400334,0.0003161121,0.0000657132],"domain_scores_gemma":[0.99914896,0.00004224066,0.00025172447,0.00005183056,0.0004293565,0.000075890785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023532523,0.00007287024,0.00016397824,0.00016731322,0.0000103687635,0.000030302055,0.000118853495,0.00004191198,0.0000023140565],"category_scores_gemma":[0.00006175349,0.0000687161,0.000033436096,0.00004287676,0.000016026457,0.00032392604,0.000003532814,0.000071952745,6.881238e-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":[0.000037420945,0.000019042598,0.0004408144,0.0000106198495,0.000081082624,0.000014752147,0.0000673081,0.9798089,0.016455665,0.0005875154,0.000027844844,0.0024490252],"study_design_scores_gemma":[0.001793298,0.00008433741,0.0008975346,0.00007970167,0.000026112124,0.00008257654,0.000039880993,0.9950488,0.0010389743,0.00077502837,0.000069164336,0.000064567284],"about_ca_topic_score_codex":0.000012219313,"about_ca_topic_score_gemma":0.0000041055973,"teacher_disagreement_score":0.79557604,"about_ca_system_score_codex":0.000096344986,"about_ca_system_score_gemma":0.000050164104,"threshold_uncertainty_score":0.28021613},"labels":[],"label_agreement":null},{"id":"W2399757108","doi":"10.2316/journal.206.2015.3.206-4247","title":"A MULTI-AGENT ARCHITECTURE WITH HIERARCHICAL FUZZY CONTROLLER FOR A MOBILE ROBOT","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Architecture; Computer science; Mobile robot; Controller (irrigation); Robot; Artificial intelligence; Geography; Biology","score_opus":0.024999976969936295,"score_gpt":0.2873393838420523,"score_spread":0.26233940687211604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399757108","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004072568,0.00013891178,0.9924643,0.0024641359,0.00062607107,0.00017601239,0.000004050558,0.000029416013,0.00002453109],"genre_scores_gemma":[0.28607166,0.000005924126,0.7135563,0.00014093428,0.00016779409,0.00000791663,0.0000029478344,0.0000063131133,0.000040205177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988461,0.00004484659,0.0003320575,0.00013960621,0.0005065192,0.00013087632],"domain_scores_gemma":[0.9986118,0.00013652345,0.00032960353,0.000086855856,0.0006889912,0.00014619557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043348808,0.000108209206,0.00018488299,0.00019080231,0.00004025246,0.00019505632,0.00042876886,0.000045992856,4.3067504e-7],"category_scores_gemma":[0.00012976007,0.00007742203,0.000057459943,0.000077701676,0.000035329136,0.00027205597,0.00006198704,0.0001446382,0.0000016675622],"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":[0.00008741683,0.00011962315,0.00030534356,0.0000055088217,0.0001301648,0.00004800616,0.0011471914,0.95152974,0.00034495824,0.0024366577,0.00021149847,0.043633882],"study_design_scores_gemma":[0.0031631903,0.0005769208,0.0020714437,0.00008676614,0.000018722858,0.00067086396,0.00004768356,0.9892013,0.00007215198,0.0035168922,0.00046314238,0.00011092006],"about_ca_topic_score_codex":0.0000029140604,"about_ca_topic_score_gemma":7.7432446e-7,"teacher_disagreement_score":0.2819991,"about_ca_system_score_codex":0.00006631028,"about_ca_system_score_gemma":0.00013380102,"threshold_uncertainty_score":0.31571788},"labels":[],"label_agreement":null},{"id":"W2399784374","doi":"10.2316/journal.206.2009.3.206-3271","title":"DESIGN OF COMMON ENVIRONMENTAL INFORMATION FOR DOOR-CLOSING TASKS WITH VARIOUS ROBOTS","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Closing (real estate); Robot; Computer science; Human–computer interaction; Artificial intelligence; Business","score_opus":0.007137067168586826,"score_gpt":0.21649653412151762,"score_spread":0.20935946695293078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399784374","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":[0.009859371,0.000049800623,0.989667,0.00012093009,0.00015863827,0.0000816106,0.0000064507194,0.00001774877,0.000038476424],"genre_scores_gemma":[0.8132965,0.000106324434,0.1865104,0.00002223968,0.000033953518,5.780316e-7,0.000023854842,0.00000420271,0.0000019339486],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994729,0.00000663596,0.00027825776,0.000028854975,0.00015910277,0.000054237345],"domain_scores_gemma":[0.99960774,0.00004530585,0.00021593276,0.000032201766,0.000076680204,0.00002214812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008943389,0.00006550298,0.00009826678,0.00009028781,0.000023388495,0.00003709706,0.00006333705,0.000032925098,0.0000014760832],"category_scores_gemma":[0.000013987154,0.000057202265,0.00001855308,0.00002025716,0.000014084371,0.00041238865,0.0000042628517,0.000053060783,2.383172e-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":[0.0000391055,0.000020148023,0.000029345047,0.0000093382805,0.000031422125,9.736995e-7,0.00015942747,0.97697014,0.0006974698,0.0006421188,0.000022301912,0.02137824],"study_design_scores_gemma":[0.0006948603,0.0002497111,0.0029901199,0.00007026826,0.000029274106,0.00005677259,0.000031747517,0.98916644,0.0039932574,0.0025728995,0.00006429883,0.00008032823],"about_ca_topic_score_codex":5.359676e-7,"about_ca_topic_score_gemma":1.3663028e-7,"teacher_disagreement_score":0.8034372,"about_ca_system_score_codex":0.000052695035,"about_ca_system_score_gemma":0.000008216397,"threshold_uncertainty_score":0.23326407},"labels":[],"label_agreement":null},{"id":"W2401103015","doi":"10.2316/journal.206.2015.2.206-4257","title":"A STUDY ON THE DYNAMIC CHARACTERISTICS OF THE 2-DOF REDUNDANT PARALLEL MANIPULATOR OF A HYBRID MACHINE TOOL","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Parallel manipulator; Manipulator (device); Computer science; Control engineering; Kinematics; Machine tool; Control theory (sociology); Engineering; Mechanical engineering; Robot; Artificial intelligence; Control (management)","score_opus":0.01804454910020617,"score_gpt":0.24318107634576938,"score_spread":0.2251365272455632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2401103015","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":[0.858421,0.000034029363,0.14003496,0.000481951,0.0008269572,0.00012727387,0.000018097857,0.000007707875,0.00004800643],"genre_scores_gemma":[0.9951061,0.000028329063,0.004774924,0.000022746615,0.000039424445,0.0000010087123,0.0000029138196,0.000009887551,0.000014644177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989619,0.00003257283,0.00047815457,0.000045693978,0.0004248082,0.00005682324],"domain_scores_gemma":[0.99920344,0.000056598805,0.00034680954,0.00011231721,0.00025344267,0.000027392784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034424354,0.0000816304,0.00015976958,0.000068684705,0.000019083396,0.000028512502,0.00023331225,0.000017951477,0.0000036105491],"category_scores_gemma":[0.00009979666,0.000047748432,0.00005810661,0.00004563696,0.000022582088,0.000065279026,0.000039683586,0.000116481904,6.089352e-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":[0.000059789098,0.00024289555,0.0021050237,0.000025649919,0.00029868085,0.000021541531,0.0007694732,0.9682133,0.0017167946,0.02273878,0.000092599446,0.0037154548],"study_design_scores_gemma":[0.0005734171,0.00019656286,0.043028567,0.00011768435,0.000046977784,0.00010771607,0.0002284788,0.95237947,0.00020894279,0.0030379107,0.0000093762255,0.00006491926],"about_ca_topic_score_codex":0.0000036037252,"about_ca_topic_score_gemma":0.000002041279,"teacher_disagreement_score":0.1366851,"about_ca_system_score_codex":0.000051075654,"about_ca_system_score_gemma":0.000030365578,"threshold_uncertainty_score":0.19471245},"labels":[],"label_agreement":null},{"id":"W2401571671","doi":"10.2316/journal.206.2015.3.206-4230","title":"POSITION-BASED VISUAL SERVOING IN ROBOTIC CAPTURE OF MOVING TARGET ENHANCED BY KALMAN FILTER","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual servoing; Kalman filter; Computer vision; Artificial intelligence; Computer science; Position (finance); Extended Kalman filter; Image (mathematics)","score_opus":0.011707926191637744,"score_gpt":0.2672259480799232,"score_spread":0.2555180218882855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2401571671","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":[0.06548606,0.00012543562,0.9319042,0.0016734938,0.000673967,0.00004908198,0.0000024892754,0.000016223832,0.00006905705],"genre_scores_gemma":[0.7374562,0.0000032803307,0.26233402,0.00012473576,0.000050895993,6.4648697e-7,0.000009587962,0.0000051571237,0.000015484828],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998588,0.00007054946,0.00051930506,0.00012619032,0.0005753247,0.000120601],"domain_scores_gemma":[0.99868536,0.00010940753,0.0005150423,0.00008176784,0.0005239981,0.00008442982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046603166,0.00010372125,0.00019525924,0.00029767686,0.000021303083,0.000103842474,0.00038946234,0.00006034793,0.0000023811322],"category_scores_gemma":[0.00013681654,0.00009730533,0.000045300338,0.00015416405,0.000023532824,0.0005885292,0.000058035326,0.00015066739,0.0000018736636],"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":[0.000012798932,0.000096258256,0.0016555979,0.000011696626,0.000028564771,0.000029923824,0.0006902003,0.98921895,0.006107843,0.0004818675,0.00022219685,0.0014440984],"study_design_scores_gemma":[0.00082106807,0.00011998121,0.0035639931,0.0002612883,0.000006930888,0.000054444547,0.00006547918,0.98749894,0.006564322,0.0009370248,0.0000071779305,0.000099358724],"about_ca_topic_score_codex":0.000022220878,"about_ca_topic_score_gemma":0.0000011793989,"teacher_disagreement_score":0.6719701,"about_ca_system_score_codex":0.00011835237,"about_ca_system_score_gemma":0.00014659492,"threshold_uncertainty_score":0.39679962},"labels":[],"label_agreement":null},{"id":"W2403453240","doi":"10.2316/journal.206.2015.4.206-4288","title":"OPTIMIZATION OF CARTESIAN TRAJECTORY FOR ACCOMPANYINGFLIGHT SPACE ROBOT DURING ON-ORBIT DETECTION","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Space Satellite Systems and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cartesian coordinate system; Orbit (dynamics); Trajectory; Trajectory optimization; Computer science; Aerospace engineering; Space (punctuation); Physics; Computer vision; Mathematics; Geometry; Engineering; Astronomy","score_opus":0.011148939696234695,"score_gpt":0.22437171035444645,"score_spread":0.21322277065821174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403453240","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":[0.23711304,0.00034499652,0.7602782,0.00030158352,0.0015859549,0.00013879877,0.0000051778084,0.000037771613,0.00019442364],"genre_scores_gemma":[0.9917323,0.000042922595,0.007930197,0.000005919143,0.00024953892,0.0000023384225,0.000002817176,0.000013484613,0.000020512227],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993177,0.000013495474,0.00030982782,0.000052235708,0.00023186342,0.00007484822],"domain_scores_gemma":[0.9992922,0.000034902252,0.00020157646,0.00004377518,0.00037674358,0.000050783357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017913916,0.00007748536,0.00014212294,0.00019187758,0.000020595717,0.000040830826,0.000073678304,0.000046480374,0.0000019677461],"category_scores_gemma":[0.000035563655,0.000071788,0.000056978348,0.000049220023,0.000008899963,0.00018730893,0.0000055990367,0.000059835096,5.620782e-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":[0.000041517404,0.000014497532,0.00012904937,0.000024567598,0.00007573623,0.0000015739453,0.00023241107,0.9860456,0.008604792,0.0002453042,0.000023732347,0.0045612436],"study_design_scores_gemma":[0.0013429809,0.00012278139,0.0030004152,0.00014119655,0.00002858057,0.00007285168,0.0002009828,0.9771516,0.017577983,0.00012323573,0.00014260155,0.00009480151],"about_ca_topic_score_codex":0.00000446334,"about_ca_topic_score_gemma":0.000004459669,"teacher_disagreement_score":0.75461924,"about_ca_system_score_codex":0.000094416704,"about_ca_system_score_gemma":0.00001907182,"threshold_uncertainty_score":0.29274297},"labels":[],"label_agreement":null},{"id":"W2403621266","doi":"10.2316/journal.206.2015.5.206-4422","title":"INTERNAL FORCES ANALYSIS OF THE ACTIVE OVERCONSTRAINED PARALLEL MANIPULATORS","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Structural engineering; Engineering","score_opus":0.013451448675835682,"score_gpt":0.2385036365353865,"score_spread":0.22505218785955083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403621266","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":[0.27901158,0.000052516905,0.71894103,0.00023062488,0.0011066877,0.00003969855,0.000009584828,0.000012406206,0.00059583934],"genre_scores_gemma":[0.97719634,0.000032868553,0.02266652,0.000018943088,0.00005468518,2.8684693e-7,0.0000036505528,0.000005414724,0.0000212985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999243,0.000014354878,0.00032636157,0.000040681494,0.00032080393,0.0000547702],"domain_scores_gemma":[0.9993244,0.000032590327,0.0002272213,0.000054692642,0.00031444163,0.000046665176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014585127,0.00006570192,0.00015230733,0.00019495962,0.00001233325,0.000033983375,0.00017503901,0.00003620461,0.000008141069],"category_scores_gemma":[0.00005454829,0.000046491725,0.00009705259,0.0001529098,0.000024641486,0.00016407075,0.000028173172,0.00007998552,3.138799e-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":[0.000011218922,0.000011785509,0.0015599587,0.000003494648,0.0007371045,0.0000024063966,0.00027684678,0.976118,0.00023587853,0.018677447,0.00004227058,0.0023235728],"study_design_scores_gemma":[0.00032004886,0.00002749203,0.01975417,0.00003710667,0.00020531636,0.00003158151,0.00018763941,0.9758876,0.00014874285,0.003332319,0.000017520655,0.00005044178],"about_ca_topic_score_codex":0.0000095264895,"about_ca_topic_score_gemma":0.000010696819,"teacher_disagreement_score":0.6981847,"about_ca_system_score_codex":0.000060056693,"about_ca_system_score_gemma":0.000027856278,"threshold_uncertainty_score":0.18958776},"labels":[],"label_agreement":null},{"id":"W2404652880","doi":"10.2316/journal.206.2015.5.206-4325","title":"INTELLIGENT FAULT-TOLERANT CONTROL OF LINEAR DRIVES USING SOFT COMPUTING","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Soft computing; Fault tolerance; Control (management); Fault (geology); Embedded system; Distributed computing; Artificial intelligence; Artificial neural network; Geology; Seismology","score_opus":0.026239028858265272,"score_gpt":0.3042923579365525,"score_spread":0.2780533290782872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404652880","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":[0.09191569,0.00034407913,0.907216,0.000071946815,0.00035920765,0.000028539154,0.000005383295,0.00004051696,0.00001862724],"genre_scores_gemma":[0.7993688,0.000046331435,0.20045014,0.000014354708,0.00010834184,9.231974e-8,0.0000032091282,0.000007960184,7.6381264e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992544,0.000011838046,0.00039019622,0.000042044605,0.00024338953,0.00005811722],"domain_scores_gemma":[0.9991585,0.000042769585,0.00024655942,0.000040330586,0.00046978565,0.000042034517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018760195,0.000066669374,0.00013623963,0.00013284246,0.000015112172,0.000029419849,0.00012957297,0.000032236236,0.000001108854],"category_scores_gemma":[0.0000921773,0.000061026472,0.00002775678,0.00004144667,0.000025876852,0.0002713687,0.000023860883,0.00008898545,3.7761373e-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":[0.000009999757,0.00001532351,0.00035810127,0.000014937514,0.000051059742,0.0000051561833,0.00029585115,0.97251356,0.0044744126,0.00037016536,0.00002621418,0.021865247],"study_design_scores_gemma":[0.0003096523,0.000034321278,0.0001520176,0.00020889928,0.0000129178425,0.00008275745,0.00007371368,0.9906207,0.0069153677,0.0013569702,0.00017572382,0.000056999434],"about_ca_topic_score_codex":0.0000021493915,"about_ca_topic_score_gemma":3.1147482e-7,"teacher_disagreement_score":0.70745313,"about_ca_system_score_codex":0.00006252235,"about_ca_system_score_gemma":0.000023577057,"threshold_uncertainty_score":0.24885873},"labels":[],"label_agreement":null},{"id":"W2404845549","doi":"10.2316/journal.206.2015.5.206-4182","title":"A VISION-BASED THREE-TIERED PATH PLANNING AND COLLISION AVOIDANCE SCHEME FOR MINIATURE AIR VEHICLES","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Collision avoidance; Scheme (mathematics); Motion planning; Computer science; Path (computing); Collision; Real-time computing; Artificial intelligence; Computer vision; Computer network; Computer security; Mathematics","score_opus":0.017706688093827475,"score_gpt":0.2643620356932821,"score_spread":0.24665534759945462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404845549","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":[0.829117,0.00064026075,0.1687551,0.0007718349,0.0005277549,0.00009673515,0.000019972924,0.000039233473,0.000032087217],"genre_scores_gemma":[0.9401898,0.000030735177,0.059506457,0.00005766304,0.00017599615,0.0000022281247,0.00002021335,0.00001354737,0.0000033810934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931437,0.00001123776,0.0002673511,0.0000694832,0.0002577475,0.00007979233],"domain_scores_gemma":[0.9992109,0.000117987656,0.00015429803,0.000034384866,0.00040675723,0.000075677555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023858776,0.00008781361,0.00012328403,0.00013777,0.00003209347,0.00007803357,0.00007052576,0.00007501169,7.34531e-7],"category_scores_gemma":[0.000094424875,0.00008103246,0.000031936328,0.000047880516,0.000015902086,0.00028743825,0.000012026695,0.00010704831,7.662827e-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":[0.00020182149,0.000058268266,0.0039088055,0.00010229182,0.00013484339,0.000027123533,0.0004935744,0.95290124,0.01042172,0.000354691,0.0018138979,0.02958171],"study_design_scores_gemma":[0.001309825,0.00011753612,0.010582741,0.00037713937,0.000018045317,0.00006222671,0.00006201077,0.9840972,0.0014790031,0.0012876538,0.0005119454,0.00009467795],"about_ca_topic_score_codex":9.924642e-7,"about_ca_topic_score_gemma":0.0000012053131,"teacher_disagreement_score":0.11107276,"about_ca_system_score_codex":0.00006075269,"about_ca_system_score_gemma":0.000032993503,"threshold_uncertainty_score":0.33044076},"labels":[],"label_agreement":null},{"id":"W2408178243","doi":"10.2316/journal.206.2015.3.206-3956","title":"LOWER BOUNDS FOR A VEHICLE ROUTING PROBLEM WITH MOTION CONSTRAINTS","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Path (computing); Vehicle routing problem; Motion (physics); Routing (electronic design automation); Set (abstract data type); Mathematical optimization; Computer science; Mathematics; Artificial intelligence; Computer network; Robot","score_opus":0.024318380202568796,"score_gpt":0.2735373691974018,"score_spread":0.249218988994833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2408178243","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":[0.012164175,0.00002527849,0.9845571,0.0022580726,0.0006877964,0.000082443716,0.0000018640209,0.000028194421,0.00019506276],"genre_scores_gemma":[0.5698479,0.0000015829088,0.4299696,0.00005553219,0.00010351132,0.0000011270669,0.0000019481586,0.0000036305053,0.000015156892],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990605,0.000024186342,0.00029025137,0.00010337391,0.0004178209,0.00010383111],"domain_scores_gemma":[0.99853444,0.000068356894,0.00037850803,0.00006518822,0.00087077904,0.000082756356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005651091,0.0000743857,0.000108243665,0.00011999986,0.00004265952,0.00026311417,0.00027538298,0.000034174573,7.583004e-7],"category_scores_gemma":[0.00010354394,0.00005974395,0.000030114144,0.000074654774,0.00003905063,0.0006323908,0.00003922726,0.00007779176,0.0000013617364],"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":[0.000114553244,0.00027529628,0.0056520673,0.000026374852,0.00028517048,0.00014806676,0.0031825805,0.64008826,0.00076630496,0.077369966,0.000831292,0.27126008],"study_design_scores_gemma":[0.0013179766,0.0003450833,0.0027180284,0.00014052939,0.00001300262,0.0005173347,0.00006847958,0.9893855,0.0001483048,0.0051550698,0.0000983768,0.00009232058],"about_ca_topic_score_codex":0.0000024039257,"about_ca_topic_score_gemma":3.1431887e-7,"teacher_disagreement_score":0.5576837,"about_ca_system_score_codex":0.00007800359,"about_ca_system_score_gemma":0.00012898988,"threshold_uncertainty_score":0.25372162},"labels":[],"label_agreement":null},{"id":"W2409440702","doi":"10.2316/journal.206.2009.3.206-3268","title":"STEREO-BASED RECONSTRUCTION UNCERTAINTY AND EGO-MOTION ESTIMATION","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Estimation; Artificial intelligence; Id, ego and super-ego; Computer vision; Motion (physics); Psychology; Economics; Psychoanalysis","score_opus":0.015282105542893509,"score_gpt":0.29338579453815333,"score_spread":0.27810368899525983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2409440702","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":[0.09271767,0.00006791153,0.901967,0.00449524,0.00064101897,0.00003523136,6.9416285e-7,0.000025742513,0.000049482052],"genre_scores_gemma":[0.752293,0.0000361586,0.2474282,0.00016162533,0.00007316293,2.1050248e-7,0.0000022043666,0.0000017246474,0.0000037046264],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918234,0.000068504654,0.00031173334,0.000102144244,0.00026902067,0.00006623088],"domain_scores_gemma":[0.99911577,0.00008289559,0.00034913974,0.0000687936,0.00034068752,0.000042690273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000559774,0.00007076771,0.00010654309,0.00020321683,0.000051409505,0.00023113473,0.00015279984,0.00004112483,0.0000017005864],"category_scores_gemma":[0.000111408335,0.000062630395,0.0000336063,0.00008527704,0.000020485213,0.0007461392,0.000014900515,0.000084559404,7.14465e-7],"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":[0.000010740832,0.000023853012,0.0012241561,0.0000040894156,0.000014008517,0.0000055704813,0.000087744505,0.082014866,0.00043055357,0.009275093,0.000013700294,0.90689564],"study_design_scores_gemma":[0.00049118244,0.00012179431,0.07571958,0.00008403561,0.0000072759813,0.00028758522,0.0000090074045,0.90254223,0.0004610846,0.020160282,0.0000459997,0.000069955895],"about_ca_topic_score_codex":0.0000028354295,"about_ca_topic_score_gemma":0.0000012961028,"teacher_disagreement_score":0.90682566,"about_ca_system_score_codex":0.000043686206,"about_ca_system_score_gemma":0.000036190195,"threshold_uncertainty_score":0.25539935},"labels":[],"label_agreement":null},{"id":"W2464730673","doi":"10.2316/journal.206.2016.4.206-4112","title":"A CONTROL APPROACH FOR HUMAN-MECHATRONIC-HYDRAULICCOUPLED EXOSKELETON IN OVERLOAD-CARRYING CONDITION","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Exoskeleton; Mechatronics; Computer science; Control (management); Control engineering; Engineering; Artificial intelligence; Simulation","score_opus":0.005740779590923214,"score_gpt":0.23669542477373853,"score_spread":0.23095464518281533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2464730673","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":[0.23708856,0.00012690079,0.7618375,0.0002838704,0.00044698227,0.00011617482,0.000013512333,0.000027149741,0.00005938888],"genre_scores_gemma":[0.99314994,0.00010851662,0.0065090107,0.0000153368,0.0001824328,0.000007844694,0.000008492864,0.000012628939,0.0000057884904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993179,0.000008885896,0.00034310832,0.00006772469,0.00016338653,0.00009900021],"domain_scores_gemma":[0.99950683,0.00015190564,0.00010174584,0.000045545483,0.00015873733,0.000035252368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026002282,0.000082020146,0.00014030731,0.00015823876,0.000017736766,0.000036018344,0.00009141492,0.000059399972,0.00000410393],"category_scores_gemma":[0.00010179763,0.00006216472,0.000056631758,0.000032642245,0.000015014208,0.00017763468,0.000007634775,0.00007094964,4.4779497e-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":[0.000015668273,0.00005149967,0.0012809582,0.000056795216,0.000090864894,0.0000036843348,0.0000520774,0.9529555,0.033027936,0.0066405353,0.00013369558,0.0056907907],"study_design_scores_gemma":[0.0030932587,0.00009842974,0.013570256,0.00023635234,0.000027961598,0.000027348704,0.00001626461,0.9766509,0.0015139981,0.0043195616,0.0002961077,0.0001495594],"about_ca_topic_score_codex":0.0000026510386,"about_ca_topic_score_gemma":0.0000018243663,"teacher_disagreement_score":0.7560614,"about_ca_system_score_codex":0.00012976865,"about_ca_system_score_gemma":0.000012325485,"threshold_uncertainty_score":0.25350037},"labels":[],"label_agreement":null},{"id":"W2469846248","doi":"10.2316/journal.206.2016.4.206-4548","title":"HUMAN STAIR ASCENT AND DESCENT SIMULATION USING A HYBRID OPTIMIZATION FORMULATION","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Descent (aeronautics); Computer science; Mathematical optimization; Mathematics; Engineering; Aerospace engineering","score_opus":0.014458478366707089,"score_gpt":0.2595046025070984,"score_spread":0.2450461241403913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2469846248","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":[0.14601813,0.000041054842,0.8533475,0.00015717963,0.00033512522,0.000055202563,0.000003648854,0.000024562361,0.000017591035],"genre_scores_gemma":[0.8980259,0.00009487358,0.10172928,0.000022054126,0.00010579576,3.1221978e-7,0.0000042943757,0.000011951515,0.0000055928404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926513,0.000013095638,0.00034675453,0.00006335116,0.0002360031,0.00007568986],"domain_scores_gemma":[0.9994475,0.00004101224,0.00017705349,0.000040884628,0.00024332223,0.000050200717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014790246,0.00008328819,0.00010073005,0.00015747423,0.00004456956,0.00007437908,0.000053428208,0.0000359538,0.000008048352],"category_scores_gemma":[0.000034332403,0.00006458117,0.000027438882,0.00003049481,0.000011098889,0.00043686983,0.000018203993,0.000042877473,3.5637512e-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":[0.00000545405,0.000012366233,0.00020730612,0.000010203653,0.000032902215,0.000003161752,0.000036554902,0.9819773,0.0031442898,0.003282727,0.000007839856,0.011279913],"study_design_scores_gemma":[0.0005378993,0.00003935047,0.0013667439,0.00013392235,0.0000219543,0.000043734075,0.000011972265,0.9954614,0.00022974609,0.0020580092,0.000014967184,0.00008028282],"about_ca_topic_score_codex":0.0000013478148,"about_ca_topic_score_gemma":6.468243e-7,"teacher_disagreement_score":0.7520077,"about_ca_system_score_codex":0.00012864616,"about_ca_system_score_gemma":0.000011612544,"threshold_uncertainty_score":0.26335436},"labels":[],"label_agreement":null},{"id":"W2475240173","doi":"10.2316/journal.206.2016.4.206-4529","title":"ADAPTIVE ROBUST OUTPUT FEEDBACK TRAJECTORY TRACKING CONTROL FOR SHIPS WITH INPUT NONLINEARITIES","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modeling, Simulation, and Optimization","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Trajectory; Tracking (education); Output feedback; Adaptive control; Feedback control; Computer science; Control (management); Control engineering; Engineering; Artificial intelligence; Physics; Psychology","score_opus":0.05908264225352678,"score_gpt":0.2876160973057896,"score_spread":0.2285334550522628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2475240173","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":[0.053299084,0.000048613958,0.9449767,0.0010965256,0.00030712152,0.00016767655,0.000025379435,0.000022973838,0.000055919645],"genre_scores_gemma":[0.82452524,0.000044266857,0.1748347,0.000055323944,0.0003925642,0.0000028901254,0.0000054538777,0.000018046521,0.00012152757],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988815,0.000038740727,0.0004941029,0.00010628906,0.00037245871,0.00010688314],"domain_scores_gemma":[0.99741864,0.0005373846,0.0005861922,0.000059697977,0.0013477941,0.000050273364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040382348,0.000119260905,0.00020129545,0.00017542602,0.00007089331,0.00009255573,0.00011999306,0.00006833999,0.000010545212],"category_scores_gemma":[0.0002826515,0.00007842464,0.000071250746,0.000037400096,0.000041462707,0.000502767,0.000008889043,0.00007011249,5.870818e-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":[0.0006777169,0.00017916766,0.0021864355,0.000054796936,0.00040479488,0.000006785868,0.0012256305,0.9331244,0.000280846,0.037098683,0.00033057577,0.024430167],"study_design_scores_gemma":[0.004602219,0.00032275432,0.0024098365,0.00052031677,0.00012959684,0.00006973235,0.00022127994,0.9673886,0.00022137439,0.023816336,0.00011391145,0.00018406531],"about_ca_topic_score_codex":0.0000020093757,"about_ca_topic_score_gemma":0.000014024316,"teacher_disagreement_score":0.77122617,"about_ca_system_score_codex":0.00008351497,"about_ca_system_score_gemma":0.000081429826,"threshold_uncertainty_score":0.3198064},"labels":[],"label_agreement":null},{"id":"W2523941652","doi":"10.2316/journal.206.2016.5.206-4706","title":"GENERIC OBJECT RECOGNITION BASED ON FEATURE FUSION IN ROBOT PERCEPTION","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Feature (linguistics); Cognitive neuroscience of visual object recognition; Pattern recognition (psychology); Object (grammar); Fusion; Robot; Invariant (physics); Perception; Point cloud; 3D single-object recognition; Mathematics; Psychology","score_opus":0.018484353771155787,"score_gpt":0.28164930502622926,"score_spread":0.26316495125507344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523941652","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":[0.023329925,0.000032180425,0.9708301,0.0052742893,0.00034586195,0.000054140393,0.0000017879812,0.000032174623,0.00009956427],"genre_scores_gemma":[0.78721654,0.00028547313,0.21205455,0.00030010036,0.00011181151,0.0000011894341,0.0000030096246,0.0000045794604,0.00002272006],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991718,0.00004820565,0.0002400479,0.00011652316,0.00034612315,0.00007732671],"domain_scores_gemma":[0.9992505,0.00008416951,0.00024839208,0.000077873025,0.00030498655,0.00003409976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002659604,0.00007791721,0.000095609954,0.00034699557,0.000025982074,0.00007892659,0.00022166007,0.000053484906,0.000007800853],"category_scores_gemma":[0.00011576529,0.000052789524,0.000044967772,0.00013056782,0.000015204201,0.0007564197,0.000034382356,0.000092063165,0.000004598125],"study_design_candidate":"design_other","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":[0.000046361423,0.00007468224,0.00063226675,0.0000044525455,0.000007039609,0.000030093888,0.000073202486,0.0020814077,0.033897117,0.00067903736,0.0001865723,0.9622878],"study_design_scores_gemma":[0.0046935375,0.0018135698,0.25642818,0.0025238625,0.000024718485,0.00044235907,0.000057910343,0.6169601,0.052178107,0.06287303,0.001348117,0.0006565066],"about_ca_topic_score_codex":0.0000015553737,"about_ca_topic_score_gemma":0.0000011965413,"teacher_disagreement_score":0.96163124,"about_ca_system_score_codex":0.00012835096,"about_ca_system_score_gemma":0.00003462423,"threshold_uncertainty_score":0.21526943},"labels":[],"label_agreement":null},{"id":"W2524369691","doi":"10.2316/journal.206.2016.5.206-4619","title":"SALIENCY-BASED ROBUST FEATURES FOR GLOBAL VISUAL SERVOING","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visual servoing; Computer science; Artificial intelligence; Computer vision; Image (mathematics)","score_opus":0.01703265125648807,"score_gpt":0.26222330041880415,"score_spread":0.2451906491623161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2524369691","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":[0.7499325,0.00036106136,0.24121867,0.0059152977,0.0018947789,0.000094245006,0.00010464836,0.000030453766,0.00044834544],"genre_scores_gemma":[0.9857783,0.000023342276,0.013800352,0.00012366369,0.00019616408,1.3584501e-7,0.000017584693,0.0000013278176,0.000059134367],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99940795,0.000025062269,0.00019013004,0.00006361237,0.00023235996,0.000080882826],"domain_scores_gemma":[0.99941885,0.0001121983,0.0001652778,0.00002187543,0.00023285675,0.00004892621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002314694,0.000058164722,0.00007757884,0.000034960452,0.000052574032,0.00008283111,0.00010894688,0.000032750835,0.00004388879],"category_scores_gemma":[0.000086523956,0.000033754142,0.000050260485,0.000035474906,0.000021781723,0.00023945948,0.0000036265217,0.000029059642,0.0000032441606],"study_design_candidate":"observational","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":[0.0002216037,0.000047824706,0.30938607,0.000024693274,0.000100762554,0.000021750548,0.00009734481,0.13410686,0.00071103073,0.0017434435,0.0011041934,0.55243444],"study_design_scores_gemma":[0.0012518833,0.00030867875,0.9060325,0.00022511654,0.00002208992,0.00013158807,0.00007436703,0.08761494,0.00035643764,0.0030675163,0.0007669123,0.00014798183],"about_ca_topic_score_codex":0.00001893524,"about_ca_topic_score_gemma":0.00011131295,"teacher_disagreement_score":0.5966464,"about_ca_system_score_codex":0.00001177847,"about_ca_system_score_gemma":0.000038637558,"threshold_uncertainty_score":0.13764541},"labels":[],"label_agreement":null},{"id":"W2525123157","doi":"10.2316/journal.206.2016.5.206-4536","title":"COMPLIANCE CONTROL OF A LEGGED ROBOT BASED ON IMPROVED ADAPTIVE CONTROL: METHOD AND EXPERIMENTS","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Basic Research Program of Shaanxi Province; Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Compliance (psychology); Control (management); Computer science; Control theory (sociology); Adaptive control; Robot; Artificial intelligence; Psychology; Social psychology","score_opus":0.017020162760717803,"score_gpt":0.2732183017418283,"score_spread":0.2561981389811105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2525123157","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":[0.0035133709,0.0001303385,0.99440736,0.001305818,0.00038915745,0.00010902883,0.000013390543,0.000020186113,0.000111348374],"genre_scores_gemma":[0.9796559,0.00002985549,0.020059245,0.00015376096,0.00007331201,0.0000031541606,7.134201e-7,0.000010670572,0.000013388983],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915355,0.0000526157,0.00039040824,0.00007669524,0.00024174197,0.00008497303],"domain_scores_gemma":[0.9991291,0.0002192163,0.00024331952,0.000058548365,0.00028904,0.000060783274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023251965,0.00010533993,0.00022802773,0.00013428942,0.000019526877,0.000029546027,0.00010059219,0.000043688004,0.000013945301],"category_scores_gemma":[0.000056518762,0.00007478331,0.000057494704,0.000029648618,0.000031504987,0.00015740389,0.000006720766,0.000066969544,0.0000010717514],"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":[0.0003692766,0.000103150815,0.0005676818,0.000018787186,0.00037812063,0.000008109651,0.000104545004,0.79704595,0.121737055,0.0039534816,0.000047560556,0.075666256],"study_design_scores_gemma":[0.0061409725,0.0002144409,0.007874074,0.00022708632,0.00003283084,0.000019306808,0.000016680939,0.9820964,0.0028438356,0.00041852816,0.00003151746,0.00008436222],"about_ca_topic_score_codex":0.0000021007268,"about_ca_topic_score_gemma":5.8116166e-7,"teacher_disagreement_score":0.9761425,"about_ca_system_score_codex":0.000053672222,"about_ca_system_score_gemma":0.00001934655,"threshold_uncertainty_score":0.3049575},"labels":[],"label_agreement":null},{"id":"W2526095533","doi":"10.2316/journal.206.2016.5.206-4698","title":"A MACHINE-LEARNING-BASED ALGORITHM FOR DETECTING A MOVING OBJECT","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; Object (grammar); Computer vision; Machine learning; Algorithm","score_opus":0.012460027360904345,"score_gpt":0.2451358960149698,"score_spread":0.23267586865406545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526095533","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":[0.020172575,0.00014172753,0.97797346,0.00014160544,0.0013926564,0.000072393086,0.000006950862,0.00005687281,0.00004175244],"genre_scores_gemma":[0.9818175,0.00003313031,0.017639685,0.000012658617,0.00045199355,0.000002766882,0.0000013629322,0.000014657603,0.000026281723],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993219,0.0000221253,0.00032051807,0.000054818356,0.00020190972,0.00007874134],"domain_scores_gemma":[0.99929535,0.00018365732,0.00018492162,0.00002929532,0.00027101723,0.000035739788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035393023,0.00007308549,0.00011216586,0.00020117934,0.00004681197,0.00007033128,0.00006406917,0.000058664173,0.0000063206367],"category_scores_gemma":[0.00015361467,0.00005181164,0.00007314496,0.000047222227,0.000007440831,0.00017111674,0.000007544334,0.00008319989,0.0000015291745],"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":[0.000018211458,0.000007884656,0.0001596833,0.0000109173725,0.00006620327,0.0000044324397,0.00004768614,0.088864066,0.0067477864,0.000059712478,0.000039399958,0.903974],"study_design_scores_gemma":[0.0011192916,0.0001334476,0.00022941649,0.00019850081,0.000013732985,0.00007481894,0.000021860758,0.9899477,0.0060505853,0.00019562451,0.0019366344,0.000078386416],"about_ca_topic_score_codex":0.0000042484426,"about_ca_topic_score_gemma":0.0000016547529,"teacher_disagreement_score":0.9616449,"about_ca_system_score_codex":0.0000850458,"about_ca_system_score_gemma":0.000019677544,"threshold_uncertainty_score":0.21128173},"labels":[],"label_agreement":null},{"id":"W2527346732","doi":"10.2316/journal.206.2016.5.206-4769","title":"IMAGE STITCHING METHOD BASED ON PROJECTIVE INTERPOLATION","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Image stitching; Computer science; Artificial intelligence; Projective test; Interpolation (computer graphics); Computer vision; Image scaling; Homography; Image (mathematics); Computer graphics (images); Mathematics; Image processing; Projective space; Pure mathematics","score_opus":0.014845851552407377,"score_gpt":0.3137911640036843,"score_spread":0.2989453124512769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527346732","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":[0.0006657182,0.000008024064,0.99038285,0.008152932,0.00033026605,0.000053091902,0.000001735398,0.000043435863,0.00036196035],"genre_scores_gemma":[0.52179843,0.000014426938,0.47794086,0.00014658654,0.00007051778,0.0000010529208,5.756596e-7,0.0000032798214,0.000024266821],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912536,0.00006898937,0.00027674343,0.00010351803,0.0003647497,0.000060637783],"domain_scores_gemma":[0.99875474,0.00019273035,0.0003675638,0.00008498594,0.00056646456,0.000033518376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004790638,0.00006775225,0.000084480744,0.00026405198,0.00003470697,0.00015569384,0.000303643,0.000031724972,0.000006673952],"category_scores_gemma":[0.00020895281,0.000043085114,0.00004826394,0.00008673009,0.000018835894,0.0007782423,0.000038235077,0.00006874731,0.0000038018486],"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":[0.000060626793,0.00012883676,0.00038349585,0.000007518392,0.00005207236,0.000016583988,0.00030819932,0.00041908224,0.078745626,0.09135732,0.00022525537,0.8282954],"study_design_scores_gemma":[0.00048380482,0.000187331,0.0051843463,0.00021459073,0.000006508643,0.000047330806,0.000014638038,0.9599507,0.022721598,0.010822135,0.00027754987,0.0000894773],"about_ca_topic_score_codex":0.0000016713502,"about_ca_topic_score_gemma":1.8749778e-7,"teacher_disagreement_score":0.9595316,"about_ca_system_score_codex":0.00008105468,"about_ca_system_score_gemma":0.00005939432,"threshold_uncertainty_score":0.175696},"labels":[],"label_agreement":null},{"id":"W2545198579","doi":"10.2316/journal.206.2016.6.206-4878","title":"LATERAL CONTROL FOR AUTONOMOUS LAND VEHICLES VIA DUAL HEURISTIC PROGRAMMING","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Dual (grammatical number); Heuristic; Computer science; Control (management); Mathematical optimization; Artificial intelligence; Mathematics","score_opus":0.011688396670864853,"score_gpt":0.2579203690090657,"score_spread":0.24623197233820082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2545198579","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":[0.016228177,0.000055660734,0.9779031,0.0046631233,0.0010117543,0.0000881806,0.0000058329024,0.00003656889,0.000007552287],"genre_scores_gemma":[0.74703497,0.00000734791,0.25259584,0.00007371724,0.00024353313,0.0000025191334,0.0000014009203,0.000005187618,0.000035501293],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908775,0.000029648754,0.00035719312,0.00011199625,0.0002844295,0.00012895554],"domain_scores_gemma":[0.9988755,0.00024330411,0.00035182567,0.000070423106,0.0003952742,0.00006368699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000355664,0.00008418043,0.00013778967,0.00013356797,0.00004920228,0.00018152529,0.00027976543,0.000039816525,0.0000010332061],"category_scores_gemma":[0.00012304945,0.000057403784,0.000054571086,0.000037642854,0.000026501995,0.00045618456,0.000037805097,0.000052154013,0.0000026475734],"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":[0.0000834324,0.00016987842,0.014861649,0.000027938422,0.00035103204,0.0001843092,0.000575687,0.043577455,0.00511921,0.0151357455,0.00036084815,0.9195528],"study_design_scores_gemma":[0.0025144473,0.00030334474,0.02744621,0.00018050555,0.000026205737,0.0007074476,0.0000038015562,0.9598263,0.0002817654,0.007896695,0.0006648978,0.0001483933],"about_ca_topic_score_codex":0.0000025071838,"about_ca_topic_score_gemma":3.6114554e-7,"teacher_disagreement_score":0.91940445,"about_ca_system_score_codex":0.000054082233,"about_ca_system_score_gemma":0.000048364815,"threshold_uncertainty_score":0.23408583},"labels":[],"label_agreement":null},{"id":"W2586877469","doi":"10.2316/journal.206.2017.1.206-4661","title":"POSITION AND ORIENTATION MEASUREMENT FOR AUTONOMOUS AERIAL REFUELING BASED ON MONOCULAR VISION","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Orientation (vector space); Computer vision; Monocular; Artificial intelligence; Monocular vision; Position (finance); Computer science; Mathematics; Business; Geometry","score_opus":0.010976672952661914,"score_gpt":0.24854519333058908,"score_spread":0.23756852037792717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586877469","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":[0.12249638,0.000132592,0.8742837,0.0008884497,0.0019702052,0.000118889446,0.0000046145237,0.000033834152,0.000071379545],"genre_scores_gemma":[0.99231166,0.000025621866,0.0073051965,0.000013994776,0.00032177605,0.0000034824598,0.0000045294973,0.0000102403765,0.0000034770935],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994158,0.0000067900423,0.00020967002,0.000057542016,0.000253046,0.000057138303],"domain_scores_gemma":[0.99947846,0.000018883366,0.00016539043,0.000060692662,0.00024182013,0.00003474754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003031157,0.000070010974,0.0000966584,0.00007956026,0.00008468245,0.00021444028,0.00007257632,0.000038856862,6.330843e-7],"category_scores_gemma":[0.00006494808,0.00006546227,0.00003420187,0.000007861648,0.000009103713,0.00021321692,0.000006183433,0.000049897175,3.5507531e-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":[0.000053835254,0.000014733592,0.0001425216,0.00003073213,0.000053083866,0.000002734002,0.0000671681,0.96574366,0.0124832755,0.00067645067,0.000053049243,0.020678727],"study_design_scores_gemma":[0.0011160851,0.00012772487,0.006604022,0.00020539103,0.000021797227,0.000011597877,0.000010335318,0.99019015,0.0012281027,0.00021939313,0.00019848277,0.000066912224],"about_ca_topic_score_codex":0.0000026762984,"about_ca_topic_score_gemma":0.0000011147756,"teacher_disagreement_score":0.8698153,"about_ca_system_score_codex":0.00010016757,"about_ca_system_score_gemma":0.0000126016275,"threshold_uncertainty_score":0.2669474},"labels":[],"label_agreement":null},{"id":"W2587182257","doi":"10.2316/journal.206.2017.1.206-4673","title":"AN ACCURATE PATH PLANNING ALGORITHM BASED ON TRIANGULAR MESHES IN ROBOTIC FIBRE PLACEMENT","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Offset (computer science); Polygon mesh; Algorithm; Path (computing); Computer science; Motion planning; Variable (mathematics); Triangle mesh; Mathematics; Artificial intelligence; Robot; Computer graphics (images); Mathematical analysis","score_opus":0.026088157707085682,"score_gpt":0.31886136966908,"score_spread":0.29277321196199435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587182257","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":[0.010038107,0.00005505746,0.98616713,0.0022266272,0.0013060899,0.0000851758,0.0000030267224,0.000026523412,0.000092239534],"genre_scores_gemma":[0.6286398,0.000011429949,0.37101582,0.00014041043,0.00016608965,0.0000015131978,0.0000060381713,0.0000074831587,0.000011402566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839336,0.00008882761,0.00048722432,0.00020053893,0.0006645613,0.0001654701],"domain_scores_gemma":[0.99843484,0.00012751794,0.0007840666,0.0003125398,0.00024081444,0.00010022546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079070835,0.0001441841,0.00021920752,0.00034416263,0.00014636874,0.0007883044,0.0010810714,0.00006523417,0.0000028965517],"category_scores_gemma":[0.000192635,0.00012755617,0.000054342712,0.000058278252,0.0000322737,0.0011592142,0.00008126883,0.00019747287,0.0000027621493],"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":[0.000019027688,0.000101700876,0.001691428,0.0000048029688,0.000026033662,0.0003098273,0.00030914956,0.9572322,0.00011508938,0.0008000636,0.00007162067,0.039319064],"study_design_scores_gemma":[0.0012488186,0.00028725303,0.048164617,0.0003810087,0.000008193876,0.000073231495,0.00003759631,0.9486786,0.00017617406,0.00079188595,0.000025643425,0.00012698366],"about_ca_topic_score_codex":0.000010025898,"about_ca_topic_score_gemma":3.9432499e-7,"teacher_disagreement_score":0.61860174,"about_ca_system_score_codex":0.000108449174,"about_ca_system_score_gemma":0.000110561734,"threshold_uncertainty_score":0.7601637},"labels":[],"label_agreement":null},{"id":"W2587305830","doi":"10.2316/journal.206.2017.1.206-4779","title":"AN ADAPTIVE FEEDFORWARD CONTROL METHOD FOR UNDER-ACTUATED BIPEDAL WALKING ON THE COMPLIANT GROUND","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Feed forward; Control theory (sociology); Bipedalism; Control (management); Computer science; Control engineering; Engineering; Artificial intelligence; Geology","score_opus":0.03057877781853408,"score_gpt":0.30656478921172287,"score_spread":0.2759860113931888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587305830","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":[0.017171575,0.00002533047,0.9770682,0.004457157,0.0009159537,0.00014659532,0.000010274326,0.000026491722,0.00017843598],"genre_scores_gemma":[0.98368704,0.000018693874,0.015723592,0.000249826,0.00028614487,0.0000041349053,0.000003482598,0.000013112273,0.000013948161],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926955,0.000039683582,0.00028460645,0.00006835457,0.00024238601,0.000095444295],"domain_scores_gemma":[0.99903435,0.00021813871,0.0002844714,0.00011539278,0.00029540434,0.00005223009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004391364,0.00009900265,0.00015279149,0.00008261118,0.00018142146,0.000360098,0.00030565218,0.000043651442,0.000011200063],"category_scores_gemma":[0.00007408493,0.00006908813,0.00007517624,0.000014139862,0.000028305758,0.00029867693,0.000009936488,0.00012006642,0.0000020962461],"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":[0.00011381943,0.000048697362,0.00005602169,0.0000059477734,0.00035768663,0.0000051910697,0.00018150246,0.8557644,0.0028577575,0.06690429,0.00014421128,0.073560506],"study_design_scores_gemma":[0.0013398123,0.00018702725,0.01545266,0.000062801635,0.000041163057,0.000038256465,0.000115135364,0.97589296,0.000209668,0.006466871,0.000112667825,0.00008094765],"about_ca_topic_score_codex":0.0000068115255,"about_ca_topic_score_gemma":0.0000054761545,"teacher_disagreement_score":0.9665155,"about_ca_system_score_codex":0.0000666344,"about_ca_system_score_gemma":0.000017776658,"threshold_uncertainty_score":0.34724334},"labels":[],"label_agreement":null},{"id":"W2587322048","doi":"10.2316/journal.206.2017.1.206-4701","title":"AUTOMATIC MONITORING OF CONTINUOUS RIGID FRAME BRIDGES BY A MAGNETO-ELASTIC EFFECT METHOD","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Rigid frame; Frame (networking); Bridge (graph theory); Term (time); Structural engineering; Magneto; Computer science; Engineering; Physics; Mechanical engineering; Telecommunications","score_opus":0.011505971686543173,"score_gpt":0.29989145406829204,"score_spread":0.2883854823817489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587322048","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":[0.9100842,0.00027887366,0.087497,0.0010793214,0.00080648635,0.000096154,0.00001566677,0.000015580328,0.00012671284],"genre_scores_gemma":[0.95819205,0.00005779699,0.04146858,0.0000138781925,0.00016460451,0.0000038815942,0.0000016737905,0.0000076213123,0.00008992567],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989172,0.000051832794,0.00045602352,0.00009995247,0.00037746417,0.00009753429],"domain_scores_gemma":[0.9984078,0.00016993839,0.00089976186,0.00015186376,0.00031524317,0.000055401342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005183009,0.000094742645,0.00022713389,0.00006721005,0.00012026003,0.00028206056,0.00043377647,0.0000453758,0.00007683288],"category_scores_gemma":[0.00034111564,0.00007341481,0.000056586035,0.000017612323,0.00006754944,0.0002764768,0.00008139172,0.00008037119,0.0000064474107],"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":[0.00006031232,0.00016115038,0.011790129,0.00013412256,0.000093474635,0.000012534813,0.00035355997,0.0048973057,0.8092957,0.0023029007,0.0005737399,0.17032503],"study_design_scores_gemma":[0.0029905688,0.0013682197,0.1803827,0.0012825897,0.00029266858,0.0003732647,0.00020584077,0.39546642,0.41213956,0.0035371652,0.0014932932,0.00046771776],"about_ca_topic_score_codex":0.000051535175,"about_ca_topic_score_gemma":7.246163e-7,"teacher_disagreement_score":0.39715618,"about_ca_system_score_codex":0.000029839508,"about_ca_system_score_gemma":0.000029120369,"threshold_uncertainty_score":0.2993769},"labels":[],"label_agreement":null},{"id":"W2587393540","doi":"10.2316/journal.206.2017.1.206-4889","title":"FINITE ELEMENT SIMULATION OF A PASSIVE MAGNETIC ROBOTIC SYSTEM","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Magnetic Bearings and Levitation Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Finite element method; Computer science; Structural engineering; Engineering","score_opus":0.009936709429726255,"score_gpt":0.2444678429484542,"score_spread":0.23453113351872795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587393540","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":[0.15889081,0.00020557594,0.83766294,0.0004974938,0.0016604798,0.00011837069,0.000008233674,0.000032000145,0.0009240988],"genre_scores_gemma":[0.99223626,0.00007145414,0.00754637,0.0000071177064,0.000097989025,7.8214345e-7,0.0000032661678,0.000008085865,0.000028652776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992132,0.000010657302,0.0004049149,0.000045637258,0.00026620738,0.000059373153],"domain_scores_gemma":[0.99902326,0.00007024766,0.00042103016,0.000086722124,0.0003639755,0.00003478006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013139432,0.00006874804,0.00012966777,0.00012275465,0.00004466755,0.00011243215,0.0001676197,0.000035822006,0.00001756026],"category_scores_gemma":[0.00009276301,0.00006457995,0.00004302417,0.00001885754,0.000025312818,0.00020259948,0.000024173243,0.00006690623,0.0000013441174],"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":[0.0000055156447,0.000010977406,0.0005430079,0.000057491092,0.000041433483,0.0000052936434,0.00012964367,0.9719945,0.00028512094,0.0030800628,0.000013832712,0.023833126],"study_design_scores_gemma":[0.00040429123,0.00006801855,0.025189841,0.0001749277,0.000030483996,0.00001570926,0.00006606518,0.97354853,0.000073194045,0.00027993132,0.000092616996,0.000056412337],"about_ca_topic_score_codex":0.0000054308234,"about_ca_topic_score_gemma":0.0000027336803,"teacher_disagreement_score":0.8333455,"about_ca_system_score_codex":0.000048199414,"about_ca_system_score_gemma":0.000013514883,"threshold_uncertainty_score":0.26334938},"labels":[],"label_agreement":null},{"id":"W2604936231","doi":"10.2316/journal.206.2017.2.206-4572","title":"DESIGN AND IMPLEMENTATION OF THUNNIFORM ROBOTIC FISH WITH VARIABLE BODY STIFFNESS","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Fish <Actinopterygii>; Variable (mathematics); Stiffness; Computer science; Fishery; Structural engineering; Mathematics; Biology; Engineering; Mathematical analysis","score_opus":0.022412581959581263,"score_gpt":0.29214694361500726,"score_spread":0.26973436165542597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604936231","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":[0.83953047,0.0000069098555,0.15858139,0.0015353997,0.00020303675,0.00008104156,0.0000018603786,0.000010932972,0.000048978367],"genre_scores_gemma":[0.93258965,0.000033590666,0.06731957,0.000011111071,0.000025763577,9.5250925e-7,0.0000012491122,0.0000039801203,0.000014140466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993283,0.000015996564,0.00022897146,0.00006904455,0.000293664,0.000063979576],"domain_scores_gemma":[0.9992526,0.000039230825,0.00052560196,0.000089728885,0.00006929494,0.000023522136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030642762,0.000058891706,0.00009619855,0.000049594622,0.00008247425,0.00012838184,0.00023077722,0.000028920856,0.000018026447],"category_scores_gemma":[0.000043745717,0.00004554204,0.00001062469,0.000020323829,0.000107963904,0.0005590636,0.000113433016,0.000054758293,6.3076897e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021700717,0.0002202341,0.42320228,0.00008024038,0.00040122285,0.000047514415,0.0019554312,0.4055304,0.048335087,0.009316627,0.0005624687,0.11013152],"study_design_scores_gemma":[0.0009225159,0.00023615152,0.94780546,0.00011571313,0.000045696008,0.00010161763,0.00025003907,0.027378853,0.016083417,0.0069012297,0.00005016522,0.000109156055],"about_ca_topic_score_codex":0.000102021106,"about_ca_topic_score_gemma":0.000007157079,"teacher_disagreement_score":0.5246032,"about_ca_system_score_codex":0.000051197,"about_ca_system_score_gemma":0.000013273262,"threshold_uncertainty_score":0.18571506},"labels":[],"label_agreement":null},{"id":"W2605264776","doi":"10.2316/journal.206.2017.2.206-5067","title":"AUTOMATIC RECOGNITION OF ADHESION STATES USING AN EXTREME LEARNING MACHINE","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Extreme learning machine; Adhesion; Artificial intelligence; Materials science; Composite material; Artificial neural network","score_opus":0.03989580609484542,"score_gpt":0.2961123697313069,"score_spread":0.25621656363646145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605264776","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":[0.74887127,0.00009827287,0.25057763,0.00009039354,0.00024842584,0.000036683996,0.000008634079,0.00002625226,0.000042405703],"genre_scores_gemma":[0.93563396,0.00026490065,0.063961685,0.000004156957,0.00010174483,5.725207e-7,0.000018103523,0.000010566412,0.000004306537],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993893,0.000011576156,0.00031342078,0.00004866142,0.00018080247,0.000056252746],"domain_scores_gemma":[0.9992209,0.000027577873,0.000395819,0.00006925326,0.0002486016,0.00003782342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014109904,0.00006613309,0.00011032826,0.00010344078,0.00009436252,0.000084750005,0.00013677079,0.000029668301,0.0000132338955],"category_scores_gemma":[0.00004829444,0.00006188036,0.00003141666,0.00002014991,0.000026474447,0.0005766202,0.000019515664,0.00009444574,8.820746e-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":[0.000005345794,0.000052172254,0.00090376445,0.000032543303,0.000061636776,0.000004901008,0.00022773995,0.6498578,0.020747079,0.0002440393,0.0000065321824,0.32785645],"study_design_scores_gemma":[0.00027097337,0.000043757147,0.007321003,0.00014581671,0.000020627964,0.00004598296,0.00006737524,0.9852406,0.0034175564,0.003314091,0.00004702091,0.00006522412],"about_ca_topic_score_codex":0.000010651319,"about_ca_topic_score_gemma":0.0000029635653,"teacher_disagreement_score":0.33538276,"about_ca_system_score_codex":0.000033128206,"about_ca_system_score_gemma":0.000010318523,"threshold_uncertainty_score":0.25234076},"labels":[],"label_agreement":null},{"id":"W2618079889","doi":"10.2316/journal.206.2017.3.206-4839","title":"PARTITIONING THE WHEAT GRAINS BY THE UNIFORMITY OF PROTEIN QUALITY BASED ON REMOTE SENSING","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Agriculture and Biological Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Quality (philosophy); Environmental science; Computer science; Remote sensing; Geology; Physics","score_opus":0.035411391170399646,"score_gpt":0.2813575114181071,"score_spread":0.24594612024770746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618079889","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":[0.9579991,0.000054118747,0.0013456179,0.040092904,0.000117829455,0.00007930892,0.000010915294,0.000004803311,0.00029537152],"genre_scores_gemma":[0.9992308,0.000030310945,0.0003071521,0.00023244412,0.00016065553,1.4218072e-7,0.000006059051,2.251823e-7,0.000032209933],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993516,0.000067939145,0.00022136758,0.000052743624,0.00024954203,0.00005677232],"domain_scores_gemma":[0.99904406,0.00016734061,0.0005045304,0.00003191143,0.00023478676,0.000017354745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047920152,0.0000538024,0.00008746305,0.00000395508,0.00039147295,0.0001113396,0.00021862422,0.00003154042,0.000005731217],"category_scores_gemma":[0.00022995028,0.000012658678,0.00006097696,0.000023129911,0.000097515825,0.00007543201,0.000039023875,0.00008854619,4.3626832e-7],"study_design_candidate":"observational","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":[0.00018055149,0.0001574825,0.013639722,0.000011480778,0.0001598888,0.000006637034,0.00022401976,0.0024316749,0.14120929,0.0055520823,0.0014506201,0.83497655],"study_design_scores_gemma":[0.00029940368,0.00037447628,0.96255076,0.00019888613,0.000023678043,0.000019008354,0.00033296537,0.019567735,0.007100111,0.006830767,0.0025880726,0.00011413418],"about_ca_topic_score_codex":0.00011563655,"about_ca_topic_score_gemma":0.000106262116,"teacher_disagreement_score":0.948911,"about_ca_system_score_codex":0.000013659955,"about_ca_system_score_gemma":0.00000367331,"threshold_uncertainty_score":0.30109328},"labels":[],"label_agreement":null},{"id":"W2618762351","doi":"10.2316/journal.206.2017.3.206-4983","title":"OPTIMIZATION ANALYSIS OF ENERGY-ABSORBING STRUCTURES IN SUBWAY TRAIN","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Social Science Fund of China; National Natural Science Foundation of China; China Railway","keywords":"Energy (signal processing); Computer science; Automotive engineering; Engineering; Physics","score_opus":0.006615125940581589,"score_gpt":0.22961207076021947,"score_spread":0.2229969448196379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618762351","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":[0.3755426,0.00022200467,0.6234001,0.000105144674,0.0005713692,0.000011798862,0.000006936041,0.00001258787,0.00012747724],"genre_scores_gemma":[0.9815579,0.0003724691,0.017996324,0.0000043156956,0.00004778679,2.1703954e-7,0.000009757684,0.000006212413,0.00000499017],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994459,0.0000066873026,0.00030265853,0.000037976934,0.0001589144,0.000047847578],"domain_scores_gemma":[0.9995365,0.000031065803,0.00020083552,0.00006564363,0.00014484997,0.00002107535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013309442,0.000056589823,0.00015499462,0.00045806647,0.0000176365,0.000060002214,0.00014198346,0.00003831759,0.0000034990198],"category_scores_gemma":[0.00007093453,0.000053749616,0.00005182865,0.000069737405,0.000017160102,0.0002257021,0.0000108048525,0.00005562373,3.2495905e-8],"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":[0.0000033159924,0.0000050166113,0.0014844429,0.000008978666,0.00032011906,0.0000045226766,0.00013983522,0.98899555,0.00043440805,0.0033476271,0.000004530026,0.00525163],"study_design_scores_gemma":[0.00019050234,0.0000090335,0.033435628,0.000047802157,0.000064359876,0.000008234559,0.00002268377,0.9652877,0.00024720744,0.00063372386,0.00000665387,0.000046509846],"about_ca_topic_score_codex":0.0000067749997,"about_ca_topic_score_gemma":0.000014646599,"teacher_disagreement_score":0.6060153,"about_ca_system_score_codex":0.000044767647,"about_ca_system_score_gemma":0.000008418929,"threshold_uncertainty_score":0.21918458},"labels":[],"label_agreement":null},{"id":"W2619010903","doi":"10.2316/journal.206.2017.3.206-4980","title":"DROPLET DISTRIBUTION AND CONTROL AGAINST CITRUS LEAFMINER WITH UAV SPRAYING","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Orchard; Horticulture; Distribution (mathematics); Tree (set theory); Environmental science; Biology; Mathematics","score_opus":0.01799177615079962,"score_gpt":0.2681205709314318,"score_spread":0.2501287947806322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619010903","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":[0.9891533,0.000059082493,0.00034139413,0.010155944,0.000114199036,0.000056163008,0.000022471966,0.0000066907655,0.000090749316],"genre_scores_gemma":[0.9992065,0.00018432047,0.00017614296,0.000076881595,0.00026433726,9.0027135e-7,0.000028856888,5.1486495e-7,0.00006156944],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992956,0.000021662763,0.00018353289,0.000082436396,0.00031773752,0.00009902766],"domain_scores_gemma":[0.9991408,0.00006333036,0.00027083236,0.000022471082,0.00042430207,0.000078284385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017462151,0.000072106835,0.00010902631,0.00000956225,0.00024849255,0.00043811154,0.00015994636,0.00003604325,0.000011035778],"category_scores_gemma":[0.00015568813,0.000023768467,0.000031154592,0.00002200366,0.00007304971,0.00043221092,0.000039280214,0.00009505297,0.0000013678144],"study_design_candidate":"observational","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":[0.00028480266,0.000120522796,0.082920685,0.000017093762,0.00022534838,0.00012330324,0.00017502398,0.0007259358,0.33702943,0.0030712222,0.00041422137,0.5748924],"study_design_scores_gemma":[0.0007415166,0.0003127449,0.98746955,0.00012772669,0.000026765598,0.00017565566,0.00017408941,0.006939869,0.0014716685,0.0002803378,0.0021532301,0.00012683465],"about_ca_topic_score_codex":0.00003600032,"about_ca_topic_score_gemma":0.000049213362,"teacher_disagreement_score":0.9045489,"about_ca_system_score_codex":0.000023398972,"about_ca_system_score_gemma":0.0000067369356,"threshold_uncertainty_score":0.42247197},"labels":[],"label_agreement":null},{"id":"W2620129414","doi":"10.2316/journal.206.2017.3.206-4972","title":"DRIVER FATIGUE DETECTION USING APPROXIMATE ENTROPIC OF STEERING WHEEL ANGLE FROM REAL DRIVING DATA","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Chongqing University of Science and Technology; State Key Laboratory of Automotive Safety and Energy; Tsinghua University; Natural Science Foundation of Chongqing; Chongqing University; National Science Foundation","keywords":"Steering wheel; Computer science; Automotive engineering; Engineering","score_opus":0.04198572413244028,"score_gpt":0.2824444551894265,"score_spread":0.24045873105698623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620129414","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":[0.7593307,0.00003678787,0.23977862,0.000035206947,0.0006946058,0.000033593216,0.0000194184,0.000018020399,0.000053053136],"genre_scores_gemma":[0.9819247,0.00023932938,0.017553544,0.000001953209,0.00024328976,2.374032e-7,0.000023009938,0.00001258639,0.0000013608499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992426,0.000013985549,0.00034038353,0.000079500125,0.0002509325,0.000072570234],"domain_scores_gemma":[0.99915594,0.00003821101,0.00042150443,0.00016129887,0.00018921739,0.000033832097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013865183,0.00007804558,0.00013484569,0.00011983782,0.00006334405,0.00015221263,0.00028169062,0.0000520681,0.000006584387],"category_scores_gemma":[0.00006202425,0.00008038861,0.000029074377,0.000019413194,0.00002248792,0.000985201,0.000086189706,0.000102088175,5.6829685e-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":[0.000024745792,0.00004990709,0.02013824,0.00007078645,0.0004805712,0.000029387194,0.00050292566,0.4804087,0.35534862,0.00017910825,0.000012943064,0.14275406],"study_design_scores_gemma":[0.00038024102,0.000013689392,0.06522102,0.00023387054,0.000044078442,0.000035601508,0.00003625349,0.92301756,0.010634997,0.0003020651,0.00001147908,0.00006911689],"about_ca_topic_score_codex":0.0000771882,"about_ca_topic_score_gemma":0.0000348607,"teacher_disagreement_score":0.4426089,"about_ca_system_score_codex":0.000068843365,"about_ca_system_score_gemma":0.000013128707,"threshold_uncertainty_score":0.32781523},"labels":[],"label_agreement":null},{"id":"W26358119","doi":"10.2316/journal.206.2009.3.206-3269","title":"DYNAMIC EVENT INTERPRETATION AND DESCRIPTION FROM VISUAL SCENE BASED ON COGNITIVE ONTOLOGY FOR RECOGNITION BY A ROBOT","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Interpretation (philosophy); Computer science; Ontology; Event (particle physics); Artificial intelligence; Cognition; Robot; Semantic interpretation; Computer vision; Human–computer interaction; Natural language processing; Programming language; Psychology; Neuroscience","score_opus":0.009048685298226538,"score_gpt":0.2623630698648263,"score_spread":0.25331438456659977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W26358119","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":[0.26886448,0.00022916208,0.7296325,0.000400162,0.00063295476,0.00013221607,0.00004509089,0.00003667439,0.00002672351],"genre_scores_gemma":[0.990805,0.00013217513,0.008592978,0.00014821615,0.00007588252,0.0000038593575,0.00022478892,0.000012547581,0.0000046034165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991346,0.0000330526,0.0004249772,0.000106738684,0.00020711707,0.00009350394],"domain_scores_gemma":[0.99926627,0.00013233777,0.00022869793,0.000028926366,0.0002923613,0.000051411367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016548188,0.00012150509,0.00017529207,0.00019925598,0.000036567413,0.00011825367,0.0000574571,0.00008466554,0.000004396823],"category_scores_gemma":[0.00006828302,0.000117787844,0.00005108138,0.000040209427,0.000015877113,0.00024329868,0.0000044269855,0.00009676769,0.0000014855349],"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":[0.00035375683,0.00021956715,0.00024086252,0.000049393006,0.00022821725,0.000010460161,0.0003820623,0.5561544,0.03362916,0.0001324721,0.0002999762,0.40829968],"study_design_scores_gemma":[0.0012122168,0.00042150627,0.007264164,0.0005297168,0.000051577805,0.000025155461,0.00006571793,0.98743963,0.0010196803,0.0018406519,0.000013004474,0.000116978044],"about_ca_topic_score_codex":0.0000041909148,"about_ca_topic_score_gemma":0.0000042720794,"teacher_disagreement_score":0.72194046,"about_ca_system_score_codex":0.000099709796,"about_ca_system_score_gemma":0.000014770895,"threshold_uncertainty_score":0.4803249},"labels":[],"label_agreement":null},{"id":"W2743047667","doi":"10.2316/journal.206.2017.4.206-4544","title":"INVESTIGATION ON VELOCITY PERFORMANCE DEVIATION OF SERIAL MANIPULATORS RESULTED FROM FABRICATION ERRORS","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Mechanical stress and fatigue analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fabrication; Serial manipulator; Computer science; Control theory (sociology); Materials science; Mathematics; Algorithm; Artificial intelligence; Parallel manipulator; Robot; Medicine","score_opus":0.037076618498628366,"score_gpt":0.2531324017581513,"score_spread":0.21605578325952296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743047667","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":[0.96927154,0.000023349283,0.029619223,0.00027114787,0.00066526025,0.000034160646,0.000010811028,0.00001248549,0.000092049275],"genre_scores_gemma":[0.9961024,0.00017827112,0.003465261,0.000012066801,0.00020016097,6.66172e-7,0.000030200563,0.00000612072,0.0000048555503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999174,0.000015852469,0.00039243168,0.00006244693,0.00030655935,0.000048710706],"domain_scores_gemma":[0.9989884,0.00003368586,0.00052782084,0.0001025408,0.00030877307,0.000038794642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015861834,0.00006886887,0.00012819855,0.000103376966,0.000064760505,0.00007369722,0.00018091785,0.000055198547,0.000010195669],"category_scores_gemma":[0.00013562564,0.00006238641,0.00004322435,0.0000324629,0.00002253142,0.00035139362,0.00001725138,0.00008081481,0.0000017049441],"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":[0.00014296727,0.000059044716,0.041302964,0.00006181651,0.0005752371,0.000004446813,0.0006500076,0.7406524,0.031677835,0.005435402,0.00021393146,0.17922398],"study_design_scores_gemma":[0.0003639304,0.000045552104,0.26743457,0.00013262434,0.000036685957,0.0000012232805,0.000015138891,0.7098677,0.020684436,0.0013358826,0.000018707484,0.00006351552],"about_ca_topic_score_codex":0.00003721964,"about_ca_topic_score_gemma":0.000007334657,"teacher_disagreement_score":0.22613159,"about_ca_system_score_codex":0.000050695704,"about_ca_system_score_gemma":0.000011470955,"threshold_uncertainty_score":0.2544044},"labels":[],"label_agreement":null},{"id":"W2743144131","doi":"10.2316/journal.206.2017.4.206-5054","title":"VERTICAL CLIMBING LOCOMOTION OF A NEW GECKO ROBOT USING DRY ADHESIVE MATERIAL","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Natural Science Foundation of China","keywords":"Gecko; Climbing; Adhesive; Robot; Materials science; Computer science; Geology; Composite material; Artificial intelligence; Structural engineering; Engineering; Paleontology","score_opus":0.03840580082748222,"score_gpt":0.31592681761560415,"score_spread":0.2775210167881219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743144131","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":[0.17430282,0.000022627784,0.8223589,0.0011647984,0.0020584725,0.000042103176,0.0000015529637,0.000012620128,0.000036108533],"genre_scores_gemma":[0.6614961,0.000013991119,0.33815524,0.000022488783,0.00029631687,1.3825014e-7,0.0000013420436,0.000004772398,0.000009638594],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987399,0.000042207055,0.0004905186,0.00011915041,0.0004932165,0.00011499188],"domain_scores_gemma":[0.9985784,0.000051765746,0.0007089731,0.00018412447,0.00039096235,0.000085746906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003812448,0.000094507246,0.0001911364,0.00016608318,0.00010994428,0.00040324553,0.0007261906,0.00006225589,0.00000411734],"category_scores_gemma":[0.0002255126,0.000087649954,0.00006591759,0.000034243756,0.00004996116,0.0009947103,0.00018743017,0.00010557837,0.0000017116055],"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":[0.00017071661,0.00040480733,0.030317886,0.0000736223,0.00058935775,0.00042776688,0.0029960722,0.6310327,0.07130547,0.036646713,0.00037391557,0.22566095],"study_design_scores_gemma":[0.0007441161,0.00012697758,0.052888073,0.00035633362,0.00002864845,0.00024606803,0.000020798154,0.93490237,0.006735668,0.0038316883,0.0000145058,0.00010476798],"about_ca_topic_score_codex":0.000043063057,"about_ca_topic_score_gemma":7.6177884e-7,"teacher_disagreement_score":0.4871933,"about_ca_system_score_codex":0.00006868734,"about_ca_system_score_gemma":0.00013349159,"threshold_uncertainty_score":0.3888506},"labels":[],"label_agreement":null},{"id":"W2743295872","doi":"10.2316/journal.206.2017.4.206-4998","title":"A MEMETIC ALGORITHM WITH VARIABLE LENGTH CHROMOSOME FOR ROBOT PATH PLANNING UNDER DYNAMIC ENVIRONMENTS","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Government of Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Memetic algorithm; Motion planning; Computer science; Path (computing); Variable (mathematics); Chromosome; Path length; Algorithm; Mathematical optimization; Artificial intelligence; Robot; Mathematics; Local search (optimization); Biology; Genetics","score_opus":0.01609915289129845,"score_gpt":0.2782613534441433,"score_spread":0.2621622005528449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743295872","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029589934,0.000093351344,0.9942889,0.0015792967,0.0009048046,0.00010680669,0.000007681609,0.00001921196,0.000040928397],"genre_scores_gemma":[0.24751179,0.000026258114,0.7521557,0.00007319836,0.0001192617,0.0000035241549,0.000006059452,0.000010874261,0.00009331168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987309,0.000025687308,0.00035037796,0.00018914188,0.00053173245,0.00017217665],"domain_scores_gemma":[0.99856955,0.00012630814,0.00081282685,0.00023752784,0.00018316528,0.00007062828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040820273,0.00013783977,0.0001946954,0.00014877776,0.00023690471,0.0005613427,0.00085682323,0.000056828892,0.0000020856826],"category_scores_gemma":[0.000092125534,0.00011376829,0.00004531361,0.0000348391,0.000053379987,0.0009972922,0.00012842746,0.0001325852,0.0000018584312],"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":[0.00002167372,0.00012762535,0.00052029407,0.00001574234,0.0003287333,0.00010451681,0.00041160538,0.9394115,0.0013212102,0.0066010156,0.00008926785,0.05104678],"study_design_scores_gemma":[0.0009795222,0.00024445102,0.013028467,0.00029139098,0.000032861506,0.0003918974,0.000027546617,0.97980875,0.00009809662,0.004790624,0.00016415957,0.00014221245],"about_ca_topic_score_codex":0.0000045392194,"about_ca_topic_score_gemma":1.6045463e-7,"teacher_disagreement_score":0.2445528,"about_ca_system_score_codex":0.000110797126,"about_ca_system_score_gemma":0.00008471643,"threshold_uncertainty_score":0.54130405},"labels":[],"label_agreement":null},{"id":"W2743871597","doi":"10.2316/journal.206.2017.4.206-4741","title":"THE TRACKING CONTROL OF UNMANNED UNDERWATER VEHICLES BASED ON MODEL PREDICTIVE CONTROL","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Underwater; Model predictive control; Tracking (education); Control (management); Computer science; Control theory (sociology); Artificial intelligence; Psychology; Geology; Oceanography","score_opus":0.01482600249872845,"score_gpt":0.25010683335833045,"score_spread":0.235280830859602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743871597","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":[0.03652504,0.00010983778,0.9605638,0.0019044803,0.00057644426,0.00010220275,0.000025014646,0.00001559813,0.00017760917],"genre_scores_gemma":[0.998775,0.0000230358,0.00094179413,0.000042490978,0.00019342646,0.0000014619261,0.0000010623801,0.000011611581,0.0000101223795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991448,0.000028057368,0.00036346514,0.000049324393,0.00033617264,0.0000781679],"domain_scores_gemma":[0.9987765,0.00021616444,0.0004194105,0.00010016516,0.00045521767,0.000032569318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003457731,0.000083314335,0.00016026874,0.00007516827,0.000098738514,0.00014138469,0.0002551692,0.0000420903,8.1513446e-7],"category_scores_gemma":[0.00013619181,0.0000574161,0.00007046048,0.000008827642,0.000047353773,0.00023123148,0.000008336828,0.0001097179,7.344895e-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":[0.00013266958,0.000016795237,0.000653813,0.000006181727,0.00017668934,0.000004192216,0.00004617806,0.99218154,0.0024587223,0.0010093083,0.000026650672,0.0032872863],"study_design_scores_gemma":[0.002064669,0.00009079574,0.011252529,0.0001343842,0.000035002646,0.000006821359,0.000022740092,0.98510766,0.00049920485,0.00070065365,0.000035127083,0.00005039961],"about_ca_topic_score_codex":0.0000016809597,"about_ca_topic_score_gemma":0.0000033389852,"teacher_disagreement_score":0.96224993,"about_ca_system_score_codex":0.000055605786,"about_ca_system_score_gemma":0.000027477903,"threshold_uncertainty_score":0.23413606},"labels":[],"label_agreement":null},{"id":"W2745285504","doi":"10.2316/journal.206.2017.4.206-4782","title":"CONSENSUS OF MULTI-AGENT SYSTEMS USING BACK-TRACKING AND HISTORY FOLLOWING ALGORITHMS","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Consensus algorithm; Network topology; Algorithm; Topology (electrical circuits); Consensus; Tracking (education); Multi-agent system; Graph; Point (geometry); Telecommunications network; Distributed computing; Artificial intelligence; Computer network; Mathematics; Theoretical computer science","score_opus":0.06303370887556577,"score_gpt":0.30783295192786125,"score_spread":0.2447992430522955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2745285504","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":[0.13757685,0.0016212673,0.8552423,0.000380026,0.0050088195,0.00010412304,0.00000592584,0.0000121783805,0.000048528862],"genre_scores_gemma":[0.95180947,0.000032216558,0.047997497,0.00001283167,0.00011334034,4.0770084e-7,0.0000010608909,0.0000057095845,0.000027455446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987296,0.00005560873,0.00055706163,0.00012438369,0.00043459403,0.00009875202],"domain_scores_gemma":[0.9978523,0.00007630421,0.0013525925,0.00017098564,0.0004803815,0.00006742388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056550157,0.000097125216,0.00022930674,0.00015348924,0.00009066358,0.0003406646,0.00048831507,0.00004943825,9.152586e-7],"category_scores_gemma":[0.0001719365,0.00009012277,0.00007748723,0.00001870199,0.00004894278,0.00056716986,0.00011986285,0.0000831599,8.831982e-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":[0.00010465737,0.0008801849,0.0982282,0.00057524367,0.0038931123,0.0014311791,0.0062698084,0.50584245,0.12436006,0.054063234,0.0011690115,0.20318283],"study_design_scores_gemma":[0.0011171026,0.000029712466,0.013987593,0.00037047587,0.000029531848,0.00026937627,0.00005330398,0.9835353,0.00015516991,0.000051077313,0.00031124344,0.00009012197],"about_ca_topic_score_codex":0.000102959566,"about_ca_topic_score_gemma":0.0000024070714,"teacher_disagreement_score":0.81423265,"about_ca_system_score_codex":0.00018583726,"about_ca_system_score_gemma":0.00008410195,"threshold_uncertainty_score":0.36751},"labels":[],"label_agreement":null},{"id":"W2747530786","doi":"","title":"荷重負荷運搬条件での人間‐メカトロニック‐油圧結合外骨格に対する制御アプローチ","year":2016,"lang":"ja","type":"article","venue":"International Journal of Robotics and Automation","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.008863658814520364,"score_gpt":0.23312283229603764,"score_spread":0.22425917348151728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747530786","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":[0.7077979,0.0104107,0.21978603,0.03646945,0.012999586,0.00024397018,0.00010708341,0.0002871488,0.01189813],"genre_scores_gemma":[0.99136776,0.003326976,0.0046123588,0.000042014995,0.00041917723,6.629656e-7,0.0000021572646,0.000015844984,0.00021308033],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998747,0.000030589104,0.00061112567,0.000108377324,0.00034559716,0.00015731817],"domain_scores_gemma":[0.999028,0.0001401234,0.0002743395,0.00010236553,0.00038537756,0.00006978691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027613612,0.00016319992,0.00022292988,0.00031860292,0.000043518758,0.00007352212,0.00030932028,0.00018271417,0.000115684685],"category_scores_gemma":[0.00012925405,0.00011796071,0.00009752276,0.00007178424,0.000099480654,0.0005753075,0.000046178273,0.00019444484,0.00003123],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018843045,0.00023748011,0.0054438603,0.00016275699,0.0020738821,0.00043334503,0.0015721292,0.05270241,0.03330444,0.6064091,0.006170737,0.29130146],"study_design_scores_gemma":[0.013229744,0.0021368184,0.15616128,0.0077236397,0.00081712235,0.0053651365,0.0026020138,0.2605073,0.013754725,0.51644254,0.018782083,0.002477641],"about_ca_topic_score_codex":0.0000042661986,"about_ca_topic_score_gemma":0.00000445154,"teacher_disagreement_score":0.2888238,"about_ca_system_score_codex":0.00010571442,"about_ca_system_score_gemma":0.000045944278,"threshold_uncertainty_score":0.48102984},"labels":[],"label_agreement":null},{"id":"W2757144173","doi":"10.2316/journal.206.2017.5.206-5027","title":"MULTIPLE 3D MARKER LOCALIZATION AND TRACKING SYSTEM IN IMAGE-GUIDED RADIOTHERAPY","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Tracking (education); Image (mathematics); Psychology","score_opus":0.012427280438252928,"score_gpt":0.30380671402785614,"score_spread":0.2913794335896032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757144173","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":[0.08626108,0.00013262629,0.912739,0.00036262593,0.00023116307,0.00007649659,0.0000038093926,0.000012554511,0.00018068375],"genre_scores_gemma":[0.911794,0.000102751204,0.08784123,0.000025623707,0.00020821684,0.0000015056042,0.0000034253985,0.000010225125,0.000013012952],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937344,0.000024001272,0.00030181368,0.000077530436,0.00015764388,0.00006556024],"domain_scores_gemma":[0.9991105,0.00003808023,0.0004985852,0.000075120646,0.00024939148,0.000028298871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021518624,0.00007660712,0.00013169395,0.000115907555,0.0000831503,0.00022411894,0.00013496238,0.000026944272,0.000010338999],"category_scores_gemma":[0.000027669546,0.000069354064,0.000028533485,0.000017458657,0.000041270836,0.0006089563,0.000018330411,0.000078106015,1.1465956e-7],"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":[0.000090171445,0.000119380034,0.6698976,0.00004726738,0.00025524347,0.000030505553,0.00073579396,0.030430147,0.012880425,0.014430018,0.0001807954,0.27090263],"study_design_scores_gemma":[0.0017660672,0.000042131836,0.10903547,0.00034922254,0.000013122081,0.000067456676,0.000111596106,0.8849874,0.0016258927,0.0012398023,0.0006224593,0.00013934111],"about_ca_topic_score_codex":0.00003848551,"about_ca_topic_score_gemma":0.000002061554,"teacher_disagreement_score":0.8545573,"about_ca_system_score_codex":0.000065410895,"about_ca_system_score_gemma":0.000016778222,"threshold_uncertainty_score":0.28281766},"labels":[],"label_agreement":null},{"id":"W2757942857","doi":"10.2316/journal.206.2017.5.206-4853","title":"BIDDING AND RULES FOR UNKNOWN ENVIRONMENT EXPLORATION","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bidding; Computer science; Business; Marketing","score_opus":0.020601590131022463,"score_gpt":0.27068898286171705,"score_spread":0.2500873927306946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757942857","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":[0.18817945,0.00026028743,0.809204,0.0014476062,0.000662722,0.00008299386,0.0000033166255,0.000017008551,0.00014261922],"genre_scores_gemma":[0.97321373,0.0005883056,0.025974173,0.000009537341,0.00016584258,0.0000023526068,0.0000033714648,0.0000067025526,0.000035964575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996463,0.0000041166536,0.00014882212,0.000038127302,0.00011431405,0.000048298596],"domain_scores_gemma":[0.99971384,0.000028509938,0.00012549355,0.00003941624,0.00006736219,0.000025399784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014575305,0.000047664966,0.000063143954,0.00006872008,0.000078031626,0.00021455645,0.00007729855,0.000021195752,0.0000024023711],"category_scores_gemma":[0.00003326752,0.00004374709,0.000018882862,0.0000037664684,0.000015313797,0.00042135583,0.000017101092,0.000033503562,3.8470782e-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":[0.00002973647,0.000045075612,0.0012456477,0.00009373549,0.00024625586,0.000016756989,0.00049105275,0.54835635,0.009080816,0.050670765,0.0007002118,0.3890236],"study_design_scores_gemma":[0.0008211557,0.000075756056,0.01002182,0.00012196027,0.000032004333,0.000035436024,0.0001562548,0.9632536,0.0017348159,0.018140806,0.0054918113,0.00011455971],"about_ca_topic_score_codex":7.1280783e-7,"about_ca_topic_score_gemma":2.3243284e-7,"teacher_disagreement_score":0.7850343,"about_ca_system_score_codex":0.000045715955,"about_ca_system_score_gemma":0.000007750698,"threshold_uncertainty_score":0.20689727},"labels":[],"label_agreement":null},{"id":"W2758097254","doi":"10.2316/journal.206.2017.5.206-5082","title":"EXPERIMENTAL STUDY ON DETECTION OF REBAR CORROSION IN CONCRETE BASED ON METAL MAGNETIC MEMORY","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Fund for Distinguished Young Scholars; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Rebar; Corrosion; Materials science; Magnetic memory; Metal; Composite material; Metallurgy","score_opus":0.017019272642656624,"score_gpt":0.28289171697644916,"score_spread":0.26587244433379253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758097254","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":[0.9911164,0.000025930625,0.0077360976,0.00003672156,0.000493376,0.00010384321,0.0000018588416,0.000027872129,0.0004579246],"genre_scores_gemma":[0.9886062,0.000003872158,0.011325079,0.0000073203673,0.000043412718,0.0000020565692,7.722357e-7,0.000010072641,0.000001198606],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992933,0.000029262621,0.00028138683,0.00006213388,0.00028473866,0.000049126073],"domain_scores_gemma":[0.99947226,0.000059508406,0.00024065525,0.000095117626,0.00011142194,0.000021026737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023640684,0.00007784028,0.00012378079,0.00022850912,0.000031953256,0.00004497008,0.0001501822,0.000031764568,0.000004402258],"category_scores_gemma":[0.00011605704,0.00007351223,0.000030891177,0.000022075403,0.000028714463,0.00015956417,0.000018538447,0.00011527943,5.820214e-7],"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":[0.0001948174,0.00019856848,0.010135547,0.00002140477,0.00003577439,0.00005585286,0.00043795764,0.040840458,0.9419627,0.0007059386,0.000010356126,0.0054005873],"study_design_scores_gemma":[0.002208916,0.0029463281,0.2833553,0.0005035743,0.000026428299,0.000044287553,0.00018927481,0.33899194,0.3698992,0.0016669611,0.0000014771506,0.00016632162],"about_ca_topic_score_codex":0.000010233318,"about_ca_topic_score_gemma":0.0000018549275,"teacher_disagreement_score":0.5720635,"about_ca_system_score_codex":0.000100553465,"about_ca_system_score_gemma":0.000009507204,"threshold_uncertainty_score":0.29977417},"labels":[],"label_agreement":null},{"id":"W2758687490","doi":"10.2316/journal.206.2017.5.206-4607","title":"PREOPERATIVE SURGICAL PLANNING FOR ROBOT-ASSISTED LIVER TUMOUR ABLATION THERAPY BASED ON COLLISION-FREE REACHABLE WORKSPACES","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"General Hospital of People’s Liberation Army; Beijing Institute of Technology; Tsinghua University; National Natural Science Foundation of China","keywords":"Robot; Workspace; Surgical robot; Medicine; Ablation; Computer science; Artificial intelligence; Internal medicine","score_opus":0.030461946461276423,"score_gpt":0.2971324671144362,"score_spread":0.26667052065315977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758687490","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":[0.19440979,0.00049004797,0.7972356,0.0049926843,0.0012753248,0.00045144785,0.000039441915,0.00009127533,0.0010143708],"genre_scores_gemma":[0.9591753,0.000174615,0.040226832,0.00003906294,0.00029426767,0.00001124259,0.000019966596,0.000017238148,0.000041477404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999212,0.000014953259,0.0002972591,0.000095148825,0.00028391354,0.00009668773],"domain_scores_gemma":[0.9989002,0.00023647655,0.0002877307,0.00014891762,0.00037127663,0.00005540663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023619618,0.00011325607,0.00015001655,0.00013145327,0.00021538955,0.00036354328,0.00030136757,0.000068363435,0.0000070523415],"category_scores_gemma":[0.00012444721,0.000097127224,0.00006811998,0.00003348185,0.000029966592,0.00029368547,0.000021511301,0.000115868745,0.00000120644],"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":[0.000048520582,0.00005479966,0.0009050892,0.0000079896845,0.00006450753,0.000009348745,0.000112856185,0.9868764,0.00047570243,0.002050709,0.00080944336,0.008584615],"study_design_scores_gemma":[0.001405663,0.0001046297,0.059967395,0.00019142091,0.000016475748,0.000022748476,0.000026479429,0.9356379,0.0010155658,0.0007286665,0.00077551644,0.00010754042],"about_ca_topic_score_codex":0.000004070518,"about_ca_topic_score_gemma":0.0000023801213,"teacher_disagreement_score":0.7647655,"about_ca_system_score_codex":0.00006493418,"about_ca_system_score_gemma":0.000030026644,"threshold_uncertainty_score":0.39607334},"labels":[],"label_agreement":null},{"id":"W2764742668","doi":"10.2316/journal.206.2016.2.206-0001","title":"REMEMBERING ACTA PRESS’S FORMER EIC PROFESSOR MOHAMED KAMEL","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Education and Islamic Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"History","score_opus":0.03495242987123405,"score_gpt":0.3499462941077755,"score_spread":0.31499386423654147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764742668","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":[0.8096089,0.00045091807,0.0153832035,0.14466037,0.006795457,0.00023414571,0.0000068303602,0.000057326495,0.022802886],"genre_scores_gemma":[0.99372584,0.0010895887,0.0018876441,0.00011646621,0.0004956971,0.0000017292053,5.0427866e-7,0.000004217195,0.0026782898],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991911,0.000042541076,0.00024846417,0.000056136392,0.00037113973,0.00009062679],"domain_scores_gemma":[0.99903107,0.000120898316,0.0002892801,0.000034582255,0.0004833933,0.00004076238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038187008,0.000048931277,0.000082499064,0.00007775107,0.00010136263,0.0000674508,0.00014618017,0.000034330198,0.00004956217],"category_scores_gemma":[0.00040523784,0.00003317071,0.00003655014,0.000036378868,0.00007095657,0.00042337924,0.000026375907,0.000047805122,0.0000038002854],"study_design_candidate":"not_applicable","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":[0.00014249055,0.00046698033,0.029695751,0.000051648694,0.00085679983,0.000017991906,0.07257417,0.00036950968,0.020968592,0.3904621,0.04406305,0.44033092],"study_design_scores_gemma":[0.006341097,0.00037092454,0.3383938,0.002324201,0.00022539307,0.00013990782,0.023425678,0.0036316523,0.004289076,0.06905469,0.55077064,0.0010329055],"about_ca_topic_score_codex":0.000026482861,"about_ca_topic_score_gemma":0.000034659464,"teacher_disagreement_score":0.5067076,"about_ca_system_score_codex":0.00009114561,"about_ca_system_score_gemma":0.00008415337,"threshold_uncertainty_score":0.13526623},"labels":[],"label_agreement":null},{"id":"W2779617886","doi":"","title":"Associate Editor of the \"INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION\"","year":2015,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robotics; Automation; Artificial intelligence; Computer science; Engineering; Robot; Mechanical engineering","score_opus":0.015819385589771667,"score_gpt":0.2487572012944189,"score_spread":0.23293781570464722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779617886","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":[0.25312132,0.0012734036,0.6493698,0.007529827,0.08759085,0.00020706197,0.00004449836,0.00006080295,0.0008024806],"genre_scores_gemma":[0.9833168,0.00022494624,0.013270581,0.00006329392,0.0030509625,3.8481718e-7,0.0000035452379,0.00001673994,0.000052753163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976776,0.000043512704,0.00091396086,0.000058475463,0.0012045663,0.00010183066],"domain_scores_gemma":[0.9964887,0.00008239805,0.00093039195,0.00009168556,0.0023207709,0.00008607085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071151124,0.000118318254,0.00022904365,0.00021976039,0.000025615893,0.000116833085,0.00065592217,0.00008336712,0.000015172964],"category_scores_gemma":[0.0003864719,0.000087954984,0.0001468984,0.00009765672,0.00004848945,0.00040959835,0.00006770301,0.00022443623,0.0000024665126],"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":[0.000020022148,0.00006725679,0.001972518,0.000013653657,0.0003738738,0.000012419193,0.00060456677,0.9760521,0.0011302336,0.0020225395,0.0097523555,0.007978452],"study_design_scores_gemma":[0.00203392,0.00025110217,0.017551832,0.0006849662,0.00018265088,0.0007250526,0.00047147306,0.95011145,0.01186769,0.008717835,0.0070724254,0.00032961046],"about_ca_topic_score_codex":0.0000056014455,"about_ca_topic_score_gemma":0.000003849845,"teacher_disagreement_score":0.73019546,"about_ca_system_score_codex":0.00019442769,"about_ca_system_score_gemma":0.00014664214,"threshold_uncertainty_score":0.35867003},"labels":[],"label_agreement":null},{"id":"W2782801664","doi":"10.2316/journal.206.2017.6.206-5139","title":"A NOVEL DESIGNED INTERACTIVE TRAINING PLATFORM FOR INDUSTRIAL ROBOT OFFLINE PROGRAMMING AND ROBOTICS EDUCATION","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robotics; Computer science; Artificial intelligence; Robot; Training (meteorology); Human–computer interaction","score_opus":0.0430235138996794,"score_gpt":0.30506304281038255,"score_spread":0.26203952891070315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782801664","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":[0.10424676,0.00019873827,0.8917186,0.00049788493,0.0029169403,0.00022473566,0.0000056035965,0.000055808134,0.00013489285],"genre_scores_gemma":[0.770337,0.00002797687,0.22905375,0.000009428415,0.00052485237,0.0000052952787,0.000008696928,0.0000185629,0.000014453052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993195,0.0000043893488,0.00032320406,0.000077339275,0.0001705387,0.00010502722],"domain_scores_gemma":[0.99928015,0.00009042695,0.00029431915,0.00006361674,0.00021081856,0.000060639417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020852282,0.00011164765,0.00015097723,0.0001493186,0.000101092664,0.00031703452,0.00016084831,0.00007092418,0.0000013953297],"category_scores_gemma":[0.00023098079,0.000113226575,0.000040687697,0.000019532416,0.000030214402,0.00064162404,0.000032871765,0.00016927121,2.3779383e-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":[0.000042850563,0.000053299165,0.00034958034,0.000028840435,0.00018050909,0.0000021710962,0.0012777644,0.6936049,0.023368994,0.0017599037,0.00003191912,0.2792993],"study_design_scores_gemma":[0.0017757904,0.00018453701,0.0034802079,0.0005600665,0.000056071618,0.00025092802,0.00075784326,0.9886755,0.0028951534,0.00031179725,0.00083328655,0.00021881632],"about_ca_topic_score_codex":0.000004206141,"about_ca_topic_score_gemma":0.0000018131774,"teacher_disagreement_score":0.6660902,"about_ca_system_score_codex":0.00010973392,"about_ca_system_score_gemma":0.00004786839,"threshold_uncertainty_score":0.46172458},"labels":[],"label_agreement":null},{"id":"W2783605161","doi":"10.2316/journal.206.2017.6.206-5110","title":"CROWBAR RESISTANCE SETTING AND ITS INFLUENCE ON DFIG LOW VOLTAGE RIDE THROUGH","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Thermal Analysis in Power Transmission","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Crowbar; Doubly fed electric machine; Voltage; Resistance (ecology); Electrical engineering; Computer science; Automotive engineering; AC power; Engineering","score_opus":0.007124713332776425,"score_gpt":0.25417241077658137,"score_spread":0.24704769744380495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783605161","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":[0.9644715,0.00051762623,0.032229636,0.001295538,0.00059116265,0.000039300226,0.000007446131,0.000028889232,0.0008188962],"genre_scores_gemma":[0.99656665,0.00040780858,0.0027683624,0.000058336318,0.00011778832,3.8496268e-7,0.0000013045465,0.000009552564,0.00006981299],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931246,0.000009837672,0.0002687181,0.00006933238,0.00026676382,0.000072865354],"domain_scores_gemma":[0.99943596,0.00004604493,0.00022488693,0.00008078584,0.00017342008,0.00003891828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016214274,0.000083288585,0.000107894804,0.00006629578,0.00010785251,0.00019332186,0.00021126342,0.000039175506,0.0000078425455],"category_scores_gemma":[0.00011533242,0.00007285818,0.00003455312,0.000017322473,0.000024596124,0.0005956739,0.000023315042,0.00013054343,0.0000029175246],"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":[0.00008515566,0.000056073113,0.0036510907,0.00017298824,0.00037826126,0.00013039936,0.0012486384,0.88691396,0.072142884,0.011090567,0.00054570055,0.023584317],"study_design_scores_gemma":[0.0019580065,0.00010475745,0.269988,0.0032109746,0.00012284615,0.00014939974,0.000094539275,0.66521275,0.04305535,0.011597611,0.003989515,0.00051620696],"about_ca_topic_score_codex":0.0000017197303,"about_ca_topic_score_gemma":0.0000026421674,"teacher_disagreement_score":0.26633692,"about_ca_system_score_codex":0.00003606863,"about_ca_system_score_gemma":0.000008832565,"threshold_uncertainty_score":0.297107},"labels":[],"label_agreement":null},{"id":"W2783626083","doi":"10.2316/journal.206.2017.6.206-5036","title":"AN OBSTACLE DETECTION SYSTEM BASED ON MONOCULAR VISION FOR APPLE ORCHARD ROBOT","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Obstacle; Computer vision; Orchard; Monocular vision; Artificial intelligence; Computer science; Monocular; Robot; Horticulture; Geography; Biology","score_opus":0.014315114378493018,"score_gpt":0.26413238671825473,"score_spread":0.2498172723397617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783626083","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":[0.95629334,0.00003142854,0.038364206,0.0036877587,0.0012710775,0.0002017883,0.000029555273,0.000034335353,0.00008653338],"genre_scores_gemma":[0.9966988,0.0000065792015,0.0024678232,0.00007123499,0.0007079198,0.0000031799527,0.00003125049,9.457141e-7,0.000012289833],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933714,0.000023117273,0.00020792468,0.000099700475,0.0002579653,0.00007415736],"domain_scores_gemma":[0.9991348,0.0000636517,0.00038019387,0.000042312942,0.00032275726,0.000056310477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024162176,0.00007403687,0.00010379946,0.000022964743,0.0002629076,0.00032221666,0.0002359371,0.00005638058,0.0000045817756],"category_scores_gemma":[0.000046042936,0.00002996034,0.00007602807,0.000021509617,0.000015606774,0.00033897796,0.000014362023,0.000056549507,0.0000017765707],"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":[0.00026416633,0.0002631074,0.003387004,0.000022209755,0.000065944856,0.000014439811,0.000074862975,0.03319884,0.53937954,0.0012876665,0.0003267834,0.4217154],"study_design_scores_gemma":[0.0009917356,0.0016590009,0.31541708,0.00024459398,0.000045112116,0.00006174512,0.00025552177,0.6540085,0.022780946,0.00048061472,0.0038428179,0.00021229582],"about_ca_topic_score_codex":0.000019248982,"about_ca_topic_score_gemma":0.000032559685,"teacher_disagreement_score":0.6208097,"about_ca_system_score_codex":0.000039976865,"about_ca_system_score_gemma":0.0000053600425,"threshold_uncertainty_score":0.31071424},"labels":[],"label_agreement":null},{"id":"W2789252337","doi":"10.2316/journal.206.2018.2.206-5131","title":"MPPT OF PHOTOVOLTAIC SYSTEM VARIABLE ACCELERATION DISTURBANCE METHOD BASED ON GENETIC ALGORITHM","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Photovoltaic system; Disturbance (geology); Acceleration; Variable (mathematics); Genetic algorithm; Control theory (sociology); Computer science; Maximum power point tracking; Algorithm; Mathematics; Engineering; Biology; Artificial intelligence; Control (management); Physics; Electrical engineering; Machine learning","score_opus":0.00879586249775545,"score_gpt":0.25577789213642826,"score_spread":0.24698202963867283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789252337","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":[0.012590434,0.00011654808,0.9824746,0.00010069757,0.0023558766,0.000057941983,0.0000095306395,0.000020840946,0.0022735246],"genre_scores_gemma":[0.80078447,0.000015958645,0.19828014,0.00006139252,0.0006649581,0.0000020398616,0.0000087903445,0.000012798443,0.00016943928],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861926,0.00009110734,0.0005887367,0.00011794999,0.0004836921,0.000099228],"domain_scores_gemma":[0.9983049,0.00009487199,0.000669131,0.000108256856,0.0007686476,0.000054208453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036945363,0.000111144895,0.00021914195,0.00022314281,0.00005458424,0.0000711144,0.00018619775,0.0000769116,0.000028303792],"category_scores_gemma":[0.00005087471,0.000089267014,0.00006477396,0.000121512916,0.00003221189,0.00015415254,0.000020485404,0.00006879851,0.0000027613805],"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":[0.00006476322,0.00011469877,0.00029576206,0.00005391034,0.00016537137,0.000015720534,0.00012343355,0.92202723,0.01456256,0.020390203,0.00028279127,0.04190355],"study_design_scores_gemma":[0.00072691595,0.00024652333,0.0031063945,0.000373802,0.000031447125,0.00008634682,0.000041464114,0.9796223,0.012270029,0.00047974146,0.0029201093,0.000094945455],"about_ca_topic_score_codex":0.0003489259,"about_ca_topic_score_gemma":0.000014683394,"teacher_disagreement_score":0.78819406,"about_ca_system_score_codex":0.00010891551,"about_ca_system_score_gemma":0.000079423065,"threshold_uncertainty_score":0.36402032},"labels":[],"label_agreement":null},{"id":"W2789324354","doi":"10.2316/journal.206.2018.2.206-5106","title":"SERVICE COMPOSITION BASED ON IMPROVED GENETIC ALGORITHM AND ANALYTICAL HIERARCHY PROCESS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Service composition; Hierarchy; Computer science; Service (business); Web service; Business process; Process (computing); Service-oriented architecture; Process management; Composition (language); Architecture; Software engineering; Genetic algorithm; Distributed computing; Database; World Wide Web; Business; Operating system; Machine learning; Work in process; Marketing","score_opus":0.006536969968850527,"score_gpt":0.2594806318508967,"score_spread":0.2529436618820462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789324354","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":[0.11404587,0.000033770408,0.8770084,0.00827543,0.00044586053,0.00006190862,0.0000032070661,0.0000256976,0.00009986838],"genre_scores_gemma":[0.8375674,0.00001249531,0.1588851,0.0032121525,0.00030814702,9.765276e-7,0.0000051994907,0.0000059400927,0.0000025853142],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990369,0.000037910377,0.00028334843,0.00015216334,0.00038893594,0.00010072277],"domain_scores_gemma":[0.9987288,0.00007501459,0.0002327466,0.00009686338,0.0007802906,0.00008629928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015422209,0.00009961358,0.000113802686,0.00021594916,0.00009974588,0.00029264792,0.00036220386,0.00004318317,0.00000619604],"category_scores_gemma":[0.0000069953194,0.0000818185,0.000028322516,0.00018040615,0.000033355944,0.00031718184,0.00006195756,0.00010966835,0.0000024128997],"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":[0.00029234673,0.0006935087,0.0023268212,0.00015740268,0.00037163208,0.000102591745,0.0046425974,0.11589905,0.0046344507,0.01086126,0.00014162001,0.8598767],"study_design_scores_gemma":[0.00059511815,0.00031215925,0.008403142,0.000102059304,0.000015244008,0.00012496777,0.00003331384,0.9865839,0.00089909154,0.0027086171,0.00013637671,0.00008602682],"about_ca_topic_score_codex":0.000015225533,"about_ca_topic_score_gemma":0.000006546136,"teacher_disagreement_score":0.87068486,"about_ca_system_score_codex":0.000023312123,"about_ca_system_score_gemma":0.000052966374,"threshold_uncertainty_score":0.33364618},"labels":[],"label_agreement":null},{"id":"W2792343921","doi":"10.2316/journal.206.2018.2.206-5099","title":"CROSS-LAYER PARAMETERS RECONFIGURATION IN INDUSTRIAL COGNITIVE WIRELESS NETWORKS USING MOABCHV ALGORITHM","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control reconfiguration; Computer science; Layer (electronics); Cognition; Fuzzy cognitive map; Fuzzy logic; Algorithm; Artificial intelligence; Computer network; Fuzzy set; Embedded system; Psychology; Fuzzy number","score_opus":0.051093790307129114,"score_gpt":0.3214210265326776,"score_spread":0.2703272362255485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792343921","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":[0.32486585,0.00003417551,0.67318237,0.0001687246,0.0016373636,0.000047601457,0.0000010932487,0.000011784019,0.000051029918],"genre_scores_gemma":[0.9641346,0.000028909204,0.03485628,0.0001311438,0.00083046715,5.5870896e-7,0.000004127439,0.0000058025225,0.000008152726],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988362,0.00009155978,0.000474149,0.00015570747,0.00030475072,0.0001376064],"domain_scores_gemma":[0.99824655,0.00022099965,0.00046639302,0.000054234348,0.0009573552,0.000054480442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005601588,0.000100882586,0.0001472458,0.00025577255,0.00007323213,0.0003899399,0.00026346403,0.00009578064,0.000004977493],"category_scores_gemma":[0.000111577225,0.000097058975,0.000047286045,0.0002028314,0.00007102865,0.00064720865,0.0000645446,0.0002280001,0.0000015057635],"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":[0.000044690132,0.000061316976,0.0046111606,0.0000014083125,0.00007025202,0.00003631566,0.0004228605,0.073803924,0.00011120878,0.00064111035,0.000033843287,0.9201619],"study_design_scores_gemma":[0.000984892,0.00012676713,0.009466455,0.00029426164,0.0000097733755,0.00013991249,0.0000314608,0.9876367,0.000505535,0.0006863234,0.000014329835,0.00010360751],"about_ca_topic_score_codex":0.000017921475,"about_ca_topic_score_gemma":0.000005246802,"teacher_disagreement_score":0.9200583,"about_ca_system_score_codex":0.000080238235,"about_ca_system_score_gemma":0.00007509263,"threshold_uncertainty_score":0.39579502},"labels":[],"label_agreement":null},{"id":"W2793541528","doi":"10.2316/journal.206.2018.2.206-5363","title":"COMPETITIVE PRICING BETWEEN HIGH-SPEED RAILWAY AND CIVIL AVIATION BASED ON THE CELLULAR AUTOMATON","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Cellular automaton; Civil aviation; Aviation; Computer science; Business; Transport engineering; Aerospace engineering; Engineering; Artificial intelligence","score_opus":0.011468003192615877,"score_gpt":0.2301031761455692,"score_spread":0.21863517295295332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793541528","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":[0.11798533,0.000023475794,0.87251306,0.00819383,0.0006333929,0.00013696578,0.0000019031847,0.000033633518,0.00047841418],"genre_scores_gemma":[0.9840661,0.000013156977,0.014937241,0.000577956,0.0003776013,0.0000011159048,0.0000050993854,0.000006197811,0.000015480731],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987449,0.000106076215,0.00034007258,0.00014253792,0.00056286616,0.00010354662],"domain_scores_gemma":[0.99868757,0.00030430348,0.00045962844,0.00013259362,0.00036645267,0.000049483977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006965444,0.00010178518,0.0001230822,0.00020260157,0.00011895948,0.00029364822,0.00037907006,0.00003314661,0.000014948198],"category_scores_gemma":[0.000059735845,0.00007453832,0.00003639496,0.00013191126,0.000056108664,0.000313883,0.00010435318,0.00010834217,0.0000065635327],"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":[0.000039507326,0.0001277562,0.004907045,0.000026953172,0.00026491654,0.00004598243,0.0009851126,0.09096199,0.0019867073,0.83625287,0.0014489554,0.062952206],"study_design_scores_gemma":[0.00057409884,0.00024523915,0.033214215,0.000175848,0.00002341193,0.0000068580675,0.000025036214,0.9586015,0.0026050603,0.0037473843,0.00068235403,0.0000989962],"about_ca_topic_score_codex":0.0000059042245,"about_ca_topic_score_gemma":0.0000034930474,"teacher_disagreement_score":0.8676395,"about_ca_system_score_codex":0.00010005177,"about_ca_system_score_gemma":0.00004015648,"threshold_uncertainty_score":0.30395845},"labels":[],"label_agreement":null},{"id":"W2794229040","doi":"10.2316/journal.206.2018.1.206-5433","title":"OPTIMAL EVALUATION INDEX SYSTEM AND BENEFIT EVALUATION MODEL FOR AGRICULTURAL INFORMATIZATION IN BEIJING","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Beijing Municipal Science and Technology Commission; Beijing Academy of Agricultural and Forestry Sciences","keywords":"Beijing; Informatization; Index (typography); Agriculture; Computer science; Business; China; Geography; Telecommunications; World Wide Web","score_opus":0.02177148361867459,"score_gpt":0.26752059617329194,"score_spread":0.24574911255461734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794229040","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":[0.92869663,0.000097485456,0.070095316,0.000242279,0.0004281452,0.00016981512,0.000006838713,0.0000070048386,0.00025647302],"genre_scores_gemma":[0.9910054,0.000031100437,0.00865066,0.000024359419,0.0002058555,3.107682e-7,0.00007287122,0.0000016799303,0.000007732181],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990042,0.000025643702,0.00035048166,0.00007112569,0.00047346612,0.00007511523],"domain_scores_gemma":[0.99863285,0.000050944123,0.0002986299,0.000027932747,0.00095326913,0.0000363679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009765596,0.000065852226,0.00009449993,0.00018368656,0.00006948245,0.00013816688,0.000058239002,0.000049028575,0.000006710469],"category_scores_gemma":[0.00009519302,0.00004931935,0.000021768976,0.000064471344,0.000020120044,0.0005605509,0.0000052946134,0.00004990677,8.9261107e-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":[0.000036311325,0.0000045861543,0.012401208,0.000010241224,0.0000159796,2.5398356e-7,0.0005919512,0.8716101,0.000023837372,0.00030973594,0.000010763003,0.11498502],"study_design_scores_gemma":[0.00067223795,0.00005990722,0.22078721,0.00010021815,0.000025785233,0.000050314735,0.00026115277,0.77750874,0.000012739738,0.0004681094,0.0000054360203,0.00004814054],"about_ca_topic_score_codex":0.000027885482,"about_ca_topic_score_gemma":0.00017747188,"teacher_disagreement_score":0.208386,"about_ca_system_score_codex":0.000035702567,"about_ca_system_score_gemma":0.000045454424,"threshold_uncertainty_score":0.20111847},"labels":[],"label_agreement":null},{"id":"W2803104877","doi":"10.2316/journal.206.2018.3.206-5004","title":"RELAY TRANSLATION POLICIES BASED ON STATE PRUNING FOR AD HOC NETWORKS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Relay; Computer science; Pruning; Translation (biology); State (computer science); Wireless ad hoc network; Computer network; Telecommunications; Algorithm; Biology; Botany; Wireless","score_opus":0.013787473912378046,"score_gpt":0.2511164517841854,"score_spread":0.23732897787180735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803104877","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":[0.07214641,0.00048508123,0.9251191,0.00069431844,0.0012144519,0.00007340122,0.0000061748046,0.0000821584,0.00017890746],"genre_scores_gemma":[0.9834995,0.00014246172,0.016130203,0.00003548149,0.0001654103,0.0000016305715,0.000004170313,0.000009731673,0.00001135924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995062,0.000006588132,0.00023433761,0.000040616702,0.00014061214,0.000071668794],"domain_scores_gemma":[0.99960214,0.00006328628,0.00011331261,0.000038731938,0.00016368619,0.000018817094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015291019,0.000062018116,0.00008279496,0.00016987507,0.000032458276,0.00006231282,0.0000862299,0.000043823013,0.0000018151887],"category_scores_gemma":[0.000025036552,0.000053785254,0.000035195608,0.00004439851,0.00002106226,0.00013659065,0.0000044696562,0.00006628747,5.7460846e-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":[0.000025002422,0.000009858428,0.00012599809,0.000011049606,0.00004799735,0.0000014702831,0.0001961264,0.9022568,0.0005342697,0.0007141619,0.00033115505,0.09574612],"study_design_scores_gemma":[0.00039662005,0.00017102939,0.0020653547,0.00013938938,0.000008153923,0.000010658157,0.000025336147,0.9922486,0.0006159322,0.0005066425,0.0037532668,0.000059036232],"about_ca_topic_score_codex":6.826704e-7,"about_ca_topic_score_gemma":0.0000042800816,"teacher_disagreement_score":0.9113532,"about_ca_system_score_codex":0.00003826114,"about_ca_system_score_gemma":0.000009537889,"threshold_uncertainty_score":0.2193299},"labels":[],"label_agreement":null},{"id":"W2803366030","doi":"10.2316/journal.206.2018.3.206-5359","title":"FAULT EVALUATION OF UNMANNED AERIAL VEHICLES POWER SYSTEM WITH AN IMPROVED FUZZY GROUP DECISION-MAKING","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Engineering Applied Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Group decision-making; Computer science; Fault (geology); Power (physics); Group (periodic table); Aeronautics; Artificial intelligence; Engineering; Psychology; Geology; Physics","score_opus":0.011145678051566422,"score_gpt":0.285662649318824,"score_spread":0.2745169712672576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803366030","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":[0.7973249,0.000060556496,0.20156741,0.000022789445,0.00067188364,0.000089825284,0.0000036316128,0.00003781121,0.00022117115],"genre_scores_gemma":[0.97225225,0.000008520531,0.027420834,0.0000028749048,0.00029129334,0.000002093042,0.0000033831966,0.000017941726,7.990147e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867505,0.00002767918,0.00035895538,0.00007402239,0.00077061023,0.0000937036],"domain_scores_gemma":[0.99857336,0.00007410777,0.00016183469,0.000080916005,0.0010637997,0.00004600674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007639271,0.00008752033,0.00013107841,0.00024138633,0.00002957231,0.000075037635,0.00016539801,0.00005533331,0.000007772421],"category_scores_gemma":[0.00007225353,0.00007232557,0.000026634112,0.000091197726,0.000034251218,0.000275028,0.000019995037,0.00010360013,0.0000014374953],"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":[0.00016748943,0.000038512626,0.00012937638,0.00004241739,0.00018073393,0.00000534446,0.0003849935,0.926403,0.027473575,0.0025554777,0.000029839997,0.04258926],"study_design_scores_gemma":[0.00084330945,0.00027897945,0.005613031,0.0003882155,0.000030764913,0.000076722295,0.00017399529,0.99045384,0.0016205851,0.00042908452,0.0000111237805,0.00008035617],"about_ca_topic_score_codex":0.0000030116103,"about_ca_topic_score_gemma":0.0000070296187,"teacher_disagreement_score":0.17492734,"about_ca_system_score_codex":0.00014505716,"about_ca_system_score_gemma":0.000035391666,"threshold_uncertainty_score":0.29493514},"labels":[],"label_agreement":null},{"id":"W2803511631","doi":"10.2316/journal.206.2018.3.206-4725","title":"ACCELERATION ANALYSIS OF MULTI-RIGID-BODY SYSTEMS AND ITS APPLICATION FOR PARALLEL STABILIZED PLATFORM","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Acceleration; Computer science; Parallel computing; Physics; Classical mechanics","score_opus":0.01644270676297806,"score_gpt":0.26471983117240866,"score_spread":0.2482771244094306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803511631","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":[0.26989084,0.00040831591,0.7291088,0.000045615197,0.0003625814,0.00013603206,0.000014133455,0.000021751752,0.000011909794],"genre_scores_gemma":[0.99643236,0.00010131195,0.0032410882,0.0000031626507,0.0001709557,0.000008891049,0.000018558307,0.0000089353425,0.000014746887],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993004,0.0000071702325,0.0003968977,0.00006127746,0.00017169573,0.00006254065],"domain_scores_gemma":[0.9991673,0.00005521035,0.00022162416,0.000045769295,0.00047523045,0.000034813893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022175166,0.00007533298,0.00020541807,0.0002262353,0.000025255444,0.000049908827,0.00007360953,0.00005138269,0.0000011874589],"category_scores_gemma":[0.00003502537,0.00006806389,0.00005170627,0.000098204306,0.0000120783425,0.00021376635,0.000007292442,0.0000399859,3.7696557e-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":[0.000026947715,0.000018492437,0.00051499205,0.000050011717,0.0007285027,2.3829595e-7,0.00026724007,0.96834105,0.0224469,0.0055295564,0.00001750027,0.0020585775],"study_design_scores_gemma":[0.00071530946,0.00005564259,0.005934668,0.00004015263,0.00016310993,0.0000068037402,0.000051335068,0.99218816,0.0006220304,0.00003495541,0.00012532772,0.000062509265],"about_ca_topic_score_codex":0.000006761773,"about_ca_topic_score_gemma":0.000006914577,"teacher_disagreement_score":0.7265415,"about_ca_system_score_codex":0.000042949687,"about_ca_system_score_gemma":0.000010155966,"threshold_uncertainty_score":0.27755648},"labels":[],"label_agreement":null},{"id":"W2803983092","doi":"10.2316/journal.206.2018.3.206-5140","title":"PRECISION CONTOUR TRACKING USING FEEDBACK-FEEDFORWARD INTEGRATED CONTROL FOR A 2-DOF MANIPULATION SYSTEM","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Feed forward; Tracking (education); Computer science; Control theory (sociology); Feedback control; Control (management); Artificial intelligence; Computer vision; Control engineering; Engineering; Psychology","score_opus":0.021962320433242033,"score_gpt":0.26031164729450706,"score_spread":0.23834932686126503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803983092","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":[0.21540381,0.00010566154,0.78167313,0.00014122855,0.002308518,0.00019653847,0.000011068272,0.00007779864,0.00008224172],"genre_scores_gemma":[0.99450713,0.000006823833,0.0045401757,0.000012867933,0.00090035726,0.000002873401,0.000005629259,0.00001476257,0.000009369535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904543,0.000027725368,0.00054153433,0.00007252246,0.00020588514,0.000106912456],"domain_scores_gemma":[0.9987037,0.00008025814,0.00030968126,0.000051966235,0.00082156016,0.000032832955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043335138,0.000103294675,0.00021144791,0.00022738295,0.00006866016,0.000100463556,0.00013562808,0.0001549464,0.0000034174182],"category_scores_gemma":[0.0001005593,0.000090652706,0.00006926651,0.00006730136,0.000026996293,0.00029530987,0.000007758889,0.000118231976,0.0000017936628],"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":[0.0007895918,0.0000688068,0.0022337066,0.00014508015,0.0013299227,0.000025472813,0.00061016454,0.706413,0.081391744,0.03149086,0.00058492,0.17491674],"study_design_scores_gemma":[0.0020456922,0.00012303899,0.0009904417,0.00039183153,0.00006867171,0.0001748266,0.0001901953,0.9933176,0.0017907352,0.00046616982,0.0003487449,0.00009204758],"about_ca_topic_score_codex":0.000007705015,"about_ca_topic_score_gemma":0.0000047970866,"teacher_disagreement_score":0.77910334,"about_ca_system_score_codex":0.00019529772,"about_ca_system_score_gemma":0.000027528267,"threshold_uncertainty_score":0.36967102},"labels":[],"label_agreement":null},{"id":"W2804371964","doi":"10.2316/journal.206.2018.3.206-4759","title":"DEVELOPMENT OF A WIRELESS COMMUNICATION NETWORK FOR MONITORING AND CONTROLLING OF AUTONOMOUS ROBOTS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Robot; Wireless; Computer network; Wireless network; Human–computer interaction; Embedded system; Telecommunications; Artificial intelligence","score_opus":0.017320804353156794,"score_gpt":0.26969563988497086,"score_spread":0.25237483553181406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804371964","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":[0.3247547,0.00021851705,0.6744092,0.00017481107,0.00037789287,0.000042906253,4.039114e-7,0.0000065311124,0.0000150105125],"genre_scores_gemma":[0.5941304,0.000052358333,0.40570536,0.0000053058548,0.00009978851,7.0085946e-7,8.5395374e-7,0.0000027517628,0.0000024818676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999063,0.000026968717,0.0005284251,0.000073744246,0.00022893527,0.00007892842],"domain_scores_gemma":[0.9981467,0.0001783083,0.0007563919,0.00008753731,0.0008004789,0.00003058515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046916836,0.000063040956,0.00016218833,0.00010422069,0.000066699424,0.000052658288,0.000311479,0.00003866228,2.9242904e-7],"category_scores_gemma":[0.00003163827,0.00005891006,0.000030663505,0.00007072894,0.00005197065,0.00021313361,0.00008490901,0.0000511403,6.65331e-8],"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":[0.00004642052,0.00006756601,0.0018871473,0.000024510944,0.00014913006,8.459876e-7,0.0018108885,0.8245656,0.006138422,0.039654884,0.000014952669,0.12563962],"study_design_scores_gemma":[0.0006393535,0.00008150008,0.0062990785,0.0003722344,0.000012128515,0.000018480798,0.000040290797,0.98281264,0.008777051,0.00080980145,0.000074302494,0.000063152416],"about_ca_topic_score_codex":0.0000024592173,"about_ca_topic_score_gemma":0.0000028648979,"teacher_disagreement_score":0.2693757,"about_ca_system_score_codex":0.000033146513,"about_ca_system_score_gemma":0.000054892786,"threshold_uncertainty_score":0.24022825},"labels":[],"label_agreement":null},{"id":"W2804436659","doi":"10.2316/journal.206.2018.3.206-5000","title":"THREE-DIMENSIONAL HYDRODYNAMICS SIMULATION AND EXPERIMENTAL ON A BIO-INSPIRED UNDERWATER HYBRID PROPELLER","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Propeller; Underwater; Computer science; Marine engineering; Aerospace engineering; Engineering; Geology; Oceanography","score_opus":0.018336652082785156,"score_gpt":0.25915114214050267,"score_spread":0.24081449005771752,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804436659","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":[0.9189716,0.00011398509,0.08011401,0.00029873534,0.00029271454,0.000065092085,0.000002990526,0.000033179556,0.00010768228],"genre_scores_gemma":[0.99631405,0.000011785433,0.0034205543,0.000047190995,0.00017002615,8.500691e-7,0.00000930313,0.000013718196,0.000012516694],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992816,0.00001568519,0.00030576138,0.00007148533,0.0002547998,0.000070679984],"domain_scores_gemma":[0.9995422,0.000037815636,0.00011610209,0.0000671238,0.00019201609,0.000044787495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011512356,0.000094955314,0.000105102285,0.00013150465,0.000058465586,0.0001020184,0.000105506784,0.00003401849,0.000012669029],"category_scores_gemma":[0.0000033362526,0.00007612865,0.000029486244,0.000030812,0.00004554757,0.00020716041,0.000036386376,0.000074649644,0.0000058750206],"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":[0.000070733426,0.00010345105,0.0013015488,0.000014957588,0.00019538356,0.000007843224,0.00064538495,0.9616886,0.026717328,0.0007539026,0.00010120173,0.008399697],"study_design_scores_gemma":[0.0004727431,0.00014287843,0.0028107984,0.00007961408,0.000008813682,0.00005413649,0.000037667705,0.98540574,0.009916839,0.0005275665,0.00045366693,0.000089542584],"about_ca_topic_score_codex":0.000004769145,"about_ca_topic_score_gemma":0.000004725716,"teacher_disagreement_score":0.07734244,"about_ca_system_score_codex":0.000060102237,"about_ca_system_score_gemma":0.000009538045,"threshold_uncertainty_score":0.31044364},"labels":[],"label_agreement":null},{"id":"W2804823065","doi":"10.2316/journal.206.2018.3.206-4949","title":"MODIFIED SENSOR ERROR MODEL FOR STATIC CALIBRATION OF A LOW-COST TRI-AXIAL MEMS ACCELEROMETER","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Microelectromechanical systems; Accelerometer; Calibration; Computer science; Electronic engineering; Materials science; Engineering; Physics; Optoelectronics","score_opus":0.03601087573772148,"score_gpt":0.2944734764925726,"score_spread":0.2584626007548511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804823065","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":[0.37522155,0.000016078648,0.6241185,0.00018566035,0.00031507906,0.00008219015,0.000017536164,0.00002777311,0.000015627598],"genre_scores_gemma":[0.93661636,0.00006478218,0.06312537,0.00002136125,0.00012681368,0.0000038993403,0.0000075764056,0.000011728768,0.00002213417],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993218,0.0000025919906,0.00036577816,0.00005528411,0.00017656502,0.000077968514],"domain_scores_gemma":[0.9993457,0.00004964556,0.00020045177,0.000049420745,0.00032973324,0.000025007892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000096890006,0.00007650837,0.00013839616,0.00018253841,0.0000219972,0.00003094606,0.00010704976,0.000057660618,0.0000033022034],"category_scores_gemma":[0.00007496925,0.000066637025,0.000047476096,0.00004893165,0.0000391844,0.00031547432,0.000014651549,0.00006307075,2.8258012e-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":[0.00005847832,0.00002864128,0.000011950113,0.0000357868,0.00007952962,0.0000012037167,0.00027021943,0.8907182,0.08916893,0.0012094846,0.00020648456,0.018211087],"study_design_scores_gemma":[0.0006351673,0.00007556893,0.00015661506,0.00006677966,0.000015093059,0.0000107984815,0.00004296509,0.9534342,0.04096825,0.0044944,0.000035025183,0.00006508678],"about_ca_topic_score_codex":0.0000010462683,"about_ca_topic_score_gemma":0.0000025139573,"teacher_disagreement_score":0.5613948,"about_ca_system_score_codex":0.00003861884,"about_ca_system_score_gemma":0.00001819606,"threshold_uncertainty_score":0.2717379},"labels":[],"label_agreement":null},{"id":"W2804898279","doi":"10.2316/journal.206.2018.3.206-5440","title":"CLASSIFICATION OF COOKED BEEF, LAMB, AND PORK USING HYPERSPECTRAL IMAGING","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hyperspectral imaging; Food science; Computer science; Artificial intelligence; Chemistry","score_opus":0.022191028672218366,"score_gpt":0.31172409895476383,"score_spread":0.2895330702825455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804898279","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":[0.98223186,0.00037072174,0.015821014,0.0005562061,0.00015770365,0.000011698272,0.0000037564712,0.000008143277,0.0008388717],"genre_scores_gemma":[0.9886236,0.00009568675,0.010868823,0.000025861162,0.00033982578,1.17990695e-7,0.000003470601,0.000005708792,0.00003685746],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993165,0.0000068768477,0.00030980544,0.00007335971,0.000229324,0.00006413571],"domain_scores_gemma":[0.99899757,0.0000414774,0.00043829327,0.00004589816,0.00044142004,0.000035332378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000114920804,0.00006382566,0.00012500252,0.00017914856,0.00003994057,0.00004939621,0.00009438293,0.000034416058,0.00006708563],"category_scores_gemma":[0.00007862806,0.000058679223,0.00003717884,0.00008926454,0.000094088886,0.00018328923,0.000020901094,0.00007182041,4.7589447e-7],"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":[0.00006138209,0.000097076736,0.051274125,0.00003322034,0.00024947818,0.000008061531,0.0004229619,0.00043955512,0.9354716,0.0060062115,0.00009900521,0.0058373003],"study_design_scores_gemma":[0.0022704245,0.00015254901,0.12083048,0.00035469673,0.00060295826,0.0009470808,0.0023273912,0.47116718,0.39410752,0.006586715,0.00028228672,0.00037071735],"about_ca_topic_score_codex":0.000012057002,"about_ca_topic_score_gemma":0.000001058663,"teacher_disagreement_score":0.5413641,"about_ca_system_score_codex":0.00005833065,"about_ca_system_score_gemma":0.000033358352,"threshold_uncertainty_score":0.23928693},"labels":[],"label_agreement":null},{"id":"W2883029769","doi":"10.2316/journal.206.2018.4.206-5075","title":"ROBUST CONTROLLER DESIGN OF SINGULARLY PERTURBATION SYSTEMS WITH ACTUATOR SATURATION VIA DELTA OPERATOR APPROACH","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Numerical methods for differential equations","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Delta operator; Perturbation (astronomy); Singular perturbation; Actuator; Operator (biology); Computer science; Mathematics; Shift operator; Physics; Mathematical analysis; Compact operator; Control (management)","score_opus":0.06669759074464349,"score_gpt":0.3071559950260061,"score_spread":0.24045840428136261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883029769","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":[0.030167904,0.000055806333,0.96878654,0.00023087,0.00044292115,0.0002531417,0.000005984638,0.000017073782,0.00003978899],"genre_scores_gemma":[0.5597735,0.00000871808,0.43993977,0.000015172019,0.00022018896,0.0000031702014,0.000006066671,0.000011780123,0.000021607535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983157,0.00019178931,0.0006689141,0.00011738542,0.0006097826,0.00009642565],"domain_scores_gemma":[0.9966357,0.00035883795,0.0009444884,0.00008701112,0.0019109903,0.00006299598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063414365,0.00013129614,0.0002921313,0.00021793284,0.00007299537,0.00014799618,0.00017094545,0.0000799898,0.000009258667],"category_scores_gemma":[0.00059189514,0.00009412806,0.000054515298,0.00012749292,0.00008452458,0.00044299854,0.00002074851,0.00011224427,0.0000010035003],"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":[0.0029390962,0.0025734368,0.0010358789,0.0004700926,0.003994105,0.000021661708,0.00830876,0.40692735,0.14242932,0.3096724,0.0006075121,0.1210204],"study_design_scores_gemma":[0.0015171231,0.0006335391,0.0007870219,0.000206622,0.0001862103,0.00014723258,0.00018562986,0.96256363,0.0015677189,0.032029003,0.000021893864,0.00015439183],"about_ca_topic_score_codex":0.000008526063,"about_ca_topic_score_gemma":0.0000010041334,"teacher_disagreement_score":0.5556363,"about_ca_system_score_codex":0.00008738932,"about_ca_system_score_gemma":0.00007534378,"threshold_uncertainty_score":0.3838431},"labels":[],"label_agreement":null},{"id":"W2883330018","doi":"10.2316/journal.206.2018.4.206-5216","title":"KINEMATICS MODELLING AND OPTIMIZATION DESIGN OF A 5-DOF HYBRID MANIPULATOR","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Computer science; Manipulator (device); Control theory (sociology); Robot; Artificial intelligence; Physics; Control (management)","score_opus":0.01835387506220915,"score_gpt":0.2266162761499433,"score_spread":0.20826240108773417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883330018","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015576521,0.000077029275,0.9837686,0.00006606662,0.0004095203,0.000047196405,0.0000020496973,0.000014425751,0.000038634873],"genre_scores_gemma":[0.4253972,0.00019894264,0.57429975,0.000008505569,0.00008198935,2.2091487e-7,0.000001939465,0.000007756321,0.0000037241243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932885,0.000010999186,0.00036011098,0.000044564553,0.00020025585,0.00005519575],"domain_scores_gemma":[0.9993834,0.00003850195,0.00018006208,0.000040642906,0.00032121156,0.000036180743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017613993,0.00006836617,0.00012314499,0.00013174358,0.000019720237,0.00004325433,0.00007263261,0.000030313857,0.000008353881],"category_scores_gemma":[0.000023866274,0.000062981555,0.000020794268,0.0000351655,0.000023822438,0.00017516801,0.00001553848,0.00004914551,4.0172162e-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":[0.000007525785,0.0000105807485,0.000013880236,0.000022702023,0.000046968256,0.0000026025136,0.000106550986,0.9931086,0.00049133523,0.004939124,0.000019126699,0.0012310551],"study_design_scores_gemma":[0.00024479144,0.000072847244,0.00003111702,0.00010596179,0.00002504935,0.00009744015,0.000021743062,0.9944016,0.0005607803,0.004378879,0.0000028177697,0.0000570214],"about_ca_topic_score_codex":0.000001106562,"about_ca_topic_score_gemma":1.4185352e-7,"teacher_disagreement_score":0.40982068,"about_ca_system_score_codex":0.000021956253,"about_ca_system_score_gemma":0.000011978153,"threshold_uncertainty_score":0.25683135},"labels":[],"label_agreement":null},{"id":"W2883344090","doi":"10.2316/journal.206.2018.4.206-5021","title":"IMPROVING DRSSI OBSERVATIONS FOR BETTER AERIAL LOCALIZATION OF RF SOURCES","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Environmental science; Remote sensing; Computer science; Geology","score_opus":0.02098836292543684,"score_gpt":0.2620730341607567,"score_spread":0.24108467123531988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883344090","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":[0.05334254,0.0000345796,0.94362134,0.0012168613,0.0016955318,0.00004790402,0.0000072137564,0.000016395217,0.000017656137],"genre_scores_gemma":[0.7422069,0.000016109174,0.25678143,0.00018578106,0.0007809739,7.93281e-7,0.000012306477,0.000004565787,0.000011148298],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991396,0.00001866202,0.00040993345,0.00008885153,0.00027038174,0.00007259334],"domain_scores_gemma":[0.998273,0.00010849932,0.0005259941,0.000085150656,0.0009753887,0.000031950436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026450487,0.000059661317,0.00010121188,0.00013276654,0.000077893994,0.00014903788,0.0003230671,0.00004444241,0.000003681965],"category_scores_gemma":[0.0001381855,0.00005200019,0.000046265883,0.00008682875,0.00004519197,0.00053234235,0.00006311462,0.00004659215,5.383993e-7],"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":[0.00020138579,0.0003782596,0.020662209,0.00010615622,0.00036241114,0.000009938124,0.0038263919,0.19757383,0.032076944,0.2162373,0.008355379,0.5202098],"study_design_scores_gemma":[0.0005585577,0.00015602505,0.0040147253,0.00008596412,0.000015780224,0.000029460625,0.000024785939,0.9823929,0.0039234273,0.006254891,0.0024676914,0.00007581122],"about_ca_topic_score_codex":0.000007817198,"about_ca_topic_score_gemma":0.0000027054768,"teacher_disagreement_score":0.78481907,"about_ca_system_score_codex":0.000017535198,"about_ca_system_score_gemma":0.000038689755,"threshold_uncertainty_score":0.21205062},"labels":[],"label_agreement":null},{"id":"W2884886191","doi":"10.2316/journal.206.2018.4.206-5337","title":"AN ONLINE PATH PLANNING METHOD BASED ON HYBRID QUANTUM ANT COLONY OPTIMIZATION FOR AUV","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Heilongjiang Province","keywords":"Ant colony optimization algorithms; Computer science; Path (computing); ANT; Motion planning; Quantum; Mathematical optimization; Artificial intelligence; Computer network; Mathematics; Physics; Robot","score_opus":0.036161121886917495,"score_gpt":0.3452874504671935,"score_spread":0.309126328580276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884886191","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009434909,0.000016587002,0.9872574,0.0016796234,0.0014397815,0.00009412391,0.000016857652,0.000044374985,0.0000162938],"genre_scores_gemma":[0.26242754,0.0000033850856,0.73675764,0.00036033615,0.0004073836,0.0000012726582,0.000029902083,0.000007863385,0.000004658293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998733,0.00008306052,0.00041709465,0.00017739079,0.00045987862,0.00012960036],"domain_scores_gemma":[0.99815243,0.0002534261,0.00052762934,0.0001359514,0.0008451715,0.000085400025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007127252,0.00011256306,0.00016023894,0.00029208892,0.00010086304,0.00023247988,0.00048166,0.00004398036,0.0000029851742],"category_scores_gemma":[0.0002105838,0.00009955669,0.000050118808,0.00009340051,0.000026881107,0.00052708964,0.000031098145,0.00010217662,8.953703e-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":[0.00003942747,0.00012849362,0.00016202604,0.0000049009727,0.00002611155,0.000023609458,0.00018169572,0.9770918,0.00022038042,0.0018472906,0.00025434772,0.020019898],"study_design_scores_gemma":[0.0007554885,0.0010055096,0.0022713044,0.00017106297,0.00001384934,0.00011659103,0.000018689454,0.99376446,0.00046431995,0.0012076409,0.000102583115,0.000108493725],"about_ca_topic_score_codex":0.0000029588336,"about_ca_topic_score_gemma":1.3306476e-7,"teacher_disagreement_score":0.25299263,"about_ca_system_score_codex":0.00007485235,"about_ca_system_score_gemma":0.000111145186,"threshold_uncertainty_score":0.4059804},"labels":[],"label_agreement":null},{"id":"W2889323670","doi":"10.2316/journal.206.2005.1.206-2771","title":"Matching Graphs with Fuzzy Attributes in Machine Vision","year":2005,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Université Laval","funders":"","keywords":"Matching (statistics); Computer science; Fuzzy logic; Artificial intelligence; Computer vision; Machine learning; Pattern recognition (psychology); Mathematics; Statistics","score_opus":0.006879808686139658,"score_gpt":0.24700504443315444,"score_spread":0.24012523574701478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889323670","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":[0.2843209,0.0001823643,0.71019626,0.0048846956,0.0002613573,0.00003223605,0.0000014259779,0.00001718494,0.000103584476],"genre_scores_gemma":[0.88393617,0.000052421063,0.115824215,0.00011646815,0.000056473913,3.0427665e-7,0.0000016668174,0.0000028623124,0.000009427704],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992418,0.000033282653,0.00026637383,0.00008185372,0.00030014053,0.00007649766],"domain_scores_gemma":[0.99946845,0.000059157413,0.00021401349,0.000058327485,0.0001622154,0.000037849466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003704421,0.00006739831,0.00009530711,0.00028797507,0.000034384237,0.00015617203,0.00030281354,0.000023423325,0.0000026686937],"category_scores_gemma":[0.0000104793535,0.00005022947,0.000031266045,0.00013309711,0.00001877995,0.0009079658,0.000048977246,0.000114064955,0.0000016776845],"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":[0.00006195036,0.00022544865,0.0045516766,0.00000918705,0.000076133816,0.00009981945,0.0014644758,0.27857113,0.0012140011,0.48183975,0.000040907264,0.23184553],"study_design_scores_gemma":[0.0019137274,0.0003244424,0.06632429,0.0003675771,0.000011991124,0.0008709699,0.00008014307,0.6573615,0.0009138298,0.27131763,0.0002917299,0.00022217295],"about_ca_topic_score_codex":0.0000043214886,"about_ca_topic_score_gemma":0.000010218514,"teacher_disagreement_score":0.5996153,"about_ca_system_score_codex":0.000027231408,"about_ca_system_score_gemma":0.000018991677,"threshold_uncertainty_score":0.20482984},"labels":[],"label_agreement":null},{"id":"W2889733044","doi":"10.2316/journal.206.2018.5.206-0059","title":"ABNORMAL USER BEHAVIOUR PERCEPTION METHOD IN SDN","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Perception; Human–computer interaction; Internet privacy; Psychology; Neuroscience","score_opus":0.012626889703749106,"score_gpt":0.29574463433442894,"score_spread":0.28311774463067985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889733044","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":[0.14489739,0.000031395437,0.85246736,0.0014878359,0.0009822674,0.000028030101,5.9666536e-7,0.000017846694,0.00008727009],"genre_scores_gemma":[0.7443865,0.000036139965,0.25504532,0.0001805315,0.00031865714,4.80641e-7,0.0000013219206,0.0000034406562,0.00002759524],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991258,0.000045771256,0.00032449779,0.00009600031,0.00031663434,0.00009130206],"domain_scores_gemma":[0.9992257,0.000060344024,0.0002246252,0.00007136847,0.00037601244,0.00004199506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047155705,0.00006586462,0.00009749341,0.00022322974,0.00003475581,0.00016348273,0.0003193903,0.000047847865,0.000017220424],"category_scores_gemma":[0.000042059146,0.000057348323,0.000039223414,0.000116459174,0.00002051675,0.00067216385,0.000074127944,0.00010798051,0.000006566871],"study_design_candidate":"design_other","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":[0.000081358274,0.00036849506,0.17668656,0.000012157555,0.00011631471,0.00014860563,0.004042739,0.056170773,0.001825583,0.080271184,0.0026706876,0.67760557],"study_design_scores_gemma":[0.00060874416,0.00016443532,0.49538913,0.000080964746,0.000008397529,0.00033791873,0.00004051548,0.49850884,0.00014012876,0.0041675163,0.0004520738,0.000101306694],"about_ca_topic_score_codex":0.000017601244,"about_ca_topic_score_gemma":0.00001120373,"teacher_disagreement_score":0.67750424,"about_ca_system_score_codex":0.000055650922,"about_ca_system_score_gemma":0.000034549463,"threshold_uncertainty_score":0.23385967},"labels":[],"label_agreement":null},{"id":"W2889782718","doi":"10.2316/journal.206.2018.5.206-5137","title":"EXPERIMENTAL VALIDATION OF A CONTROL METHOD FOR UNDERACTUATED BIPEDAL WALKING ON COMPLIANT GROUND","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Underactuation; Control theory (sociology); Bipedalism; Computer science; Planar; Point (geometry); Robot; Control (management); Control engineering; Engineering; Artificial intelligence; Mathematics; Geology","score_opus":0.019532920477984855,"score_gpt":0.30751618396998204,"score_spread":0.2879832634919972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889782718","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":[0.09658914,0.00003950923,0.9018042,0.00040616014,0.00089412153,0.00011024814,0.000006734305,0.000020292327,0.00012957439],"genre_scores_gemma":[0.9719162,0.000006099252,0.027708625,0.000078143006,0.00026135347,0.000002320502,0.000008940563,0.000010191018,0.000008144589],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992435,0.000027845517,0.00037674868,0.00005567716,0.00022765374,0.000068570655],"domain_scores_gemma":[0.99920475,0.00013894774,0.0002144167,0.000040508956,0.0003674531,0.00003389068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024458556,0.00007760748,0.00014907688,0.0001543944,0.000031661944,0.00005301951,0.00008953988,0.000037286012,0.000026861437],"category_scores_gemma":[0.000041848078,0.00006891502,0.00006116756,0.000036910944,0.000020787764,0.00015864306,0.000005986564,0.0000539262,0.0000026470889],"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":[0.00033277777,0.00024133497,0.00013790686,0.000038631577,0.00065187865,0.0000049297873,0.0011313666,0.76650035,0.15548435,0.020086596,0.00044910843,0.054940764],"study_design_scores_gemma":[0.002407958,0.00035328878,0.0016844671,0.00009815451,0.000035266712,0.000046568734,0.00012073387,0.9504306,0.04332793,0.0012824738,0.00013031371,0.000082288025],"about_ca_topic_score_codex":0.0000025786746,"about_ca_topic_score_gemma":5.235481e-7,"teacher_disagreement_score":0.87532705,"about_ca_system_score_codex":0.000067217494,"about_ca_system_score_gemma":0.0000144351325,"threshold_uncertainty_score":0.2810273},"labels":[],"label_agreement":null},{"id":"W2890055166","doi":"10.2316/journal.206.2018.5.206-0057","title":"OPPORTUNISTIC CONTENT DISSEMINATION IN INTERMITTENT MULTI-HOP DEVICE-TO-DEVICE NETWORK","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Hop (telecommunications); Computer science; Computer network","score_opus":0.04087477870191246,"score_gpt":0.3057394246946017,"score_spread":0.2648646459926892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890055166","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":[0.13709101,0.000067616966,0.8574538,0.0030977863,0.0020652863,0.00008802729,0.0000010604958,0.00002621025,0.00010920442],"genre_scores_gemma":[0.9044933,0.00004424873,0.094563484,0.0004189224,0.0003896424,0.0000017924418,0.000004460243,0.000008001173,0.00007616978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985164,0.00006609464,0.0006070319,0.00017568347,0.00045942608,0.00017536935],"domain_scores_gemma":[0.9982634,0.00014563884,0.00044467303,0.00012895644,0.00090327417,0.000114016824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053229404,0.0001189526,0.00017134594,0.0003005194,0.000053860607,0.00021863464,0.0005804394,0.000055150973,0.000005088725],"category_scores_gemma":[0.00016502615,0.000107912645,0.000048251328,0.00024585996,0.000038097154,0.00041306243,0.00016834642,0.0001338567,0.000007983878],"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":[0.00006124678,0.00037409307,0.007995068,0.000016530814,0.0001165143,0.00018340276,0.0018469068,0.65128493,0.0036052242,0.047136962,0.0010353224,0.28634378],"study_design_scores_gemma":[0.00045051417,0.00014557892,0.06060356,0.00048428567,0.000008506748,0.00010811075,0.000057694702,0.9371041,0.00024035208,0.00021505954,0.00045333206,0.00012892167],"about_ca_topic_score_codex":0.0000098024275,"about_ca_topic_score_gemma":0.000048298796,"teacher_disagreement_score":0.7674023,"about_ca_system_score_codex":0.0001357399,"about_ca_system_score_gemma":0.000043634976,"threshold_uncertainty_score":0.44005498},"labels":[],"label_agreement":null},{"id":"W2890126382","doi":"10.2316/journal.206.2018.5.206-0068","title":"SPECTRUM AGGREGATION SCHEME IN A WIRELESS BROADBAND DATA TRANSCEIVER SYSTEM","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wireless broadband; Broadband; Transceiver; Computer science; Spectrum (functional analysis); Wireless; Scheme (mathematics); Computer network; Telecommunications; Wireless network; Physics; Mathematics","score_opus":0.016596369011590312,"score_gpt":0.2564349967325679,"score_spread":0.2398386277209776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890126382","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":[0.291505,0.00006943651,0.70553076,0.0014740609,0.00115276,0.00004231577,0.000002211121,0.000028046356,0.00019539238],"genre_scores_gemma":[0.96417564,0.00005478601,0.03533488,0.000045446457,0.00036306496,3.0775885e-7,0.000007151257,0.0000056065,0.000013140014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987986,0.000050049817,0.00041513663,0.00017071798,0.00045207117,0.000113394686],"domain_scores_gemma":[0.9990779,0.000055246535,0.0003379677,0.00020929462,0.00027368485,0.00004588421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041739296,0.00008452654,0.00013036608,0.00026208587,0.000041237734,0.00018391783,0.00087336905,0.000052300667,0.0000025110744],"category_scores_gemma":[0.000023211762,0.00007727987,0.000026090029,0.000184353,0.000056184694,0.0008571395,0.00010544872,0.000113634735,0.0000036716951],"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":[0.00016736494,0.00051683676,0.013640635,0.00009666268,0.00036036392,0.00043588493,0.0035855328,0.36623046,0.007866716,0.44508746,0.00084084604,0.16117126],"study_design_scores_gemma":[0.0005895212,0.000057180325,0.005934749,0.00030346774,0.0000054414236,0.0002071908,0.000036041987,0.99153274,0.0008858435,0.00026032524,0.00010677755,0.00008072129],"about_ca_topic_score_codex":0.000013950022,"about_ca_topic_score_gemma":0.00004072653,"teacher_disagreement_score":0.6726706,"about_ca_system_score_codex":0.000094629286,"about_ca_system_score_gemma":0.000050399165,"threshold_uncertainty_score":0.31513813},"labels":[],"label_agreement":null},{"id":"W2890611454","doi":"10.2316/journal.206.2018.5.206-0071","title":"AN IMPROVED ANT COLONY SYSTEM ALGORITHM FOR ROBOT PATH PLANNING AND PERFORMANCE ANALYSIS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; Ant colony optimization algorithms; Path (computing); ANT; Motion planning; Ant colony; Artificial intelligence; Robot; Algorithm; Mathematical optimization; Mathematics; Computer network","score_opus":0.007094969110453101,"score_gpt":0.2433867855039077,"score_spread":0.2362918163934546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890611454","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":[0.3552028,0.000110287896,0.6437099,0.00002424261,0.00081628445,0.0000677703,0.00001244726,0.000034187517,0.000022082648],"genre_scores_gemma":[0.9573742,0.000014890794,0.042014904,0.000009305331,0.00055098266,0.0000027163276,0.000014657627,0.000012039164,0.0000062896975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925363,0.000016396632,0.00036497298,0.00007947537,0.00018684256,0.000098701246],"domain_scores_gemma":[0.99924946,0.000039508475,0.00019639556,0.00005698975,0.0003966525,0.0000610131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033656484,0.000091262635,0.00018710928,0.00029082378,0.0000632838,0.00012088449,0.00010277517,0.000050688483,0.000001290794],"category_scores_gemma":[0.000009150898,0.00008195815,0.00004650279,0.00009792349,0.000023131017,0.00031037317,0.0000100730385,0.00006292282,5.261888e-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":[0.000095072064,0.000068959635,0.020960053,0.00030569025,0.002367038,0.000024832267,0.0019741463,0.81198174,0.013870074,0.0004288358,0.00022397083,0.14769958],"study_design_scores_gemma":[0.00043493308,0.00026812477,0.018381575,0.000118745855,0.000113437534,0.000075689524,0.00014643616,0.97959244,0.0007050247,0.000009030935,0.00006685317,0.000087698216],"about_ca_topic_score_codex":0.0000048377315,"about_ca_topic_score_gemma":0.000002093352,"teacher_disagreement_score":0.6021714,"about_ca_system_score_codex":0.00009189294,"about_ca_system_score_gemma":0.000017864519,"threshold_uncertainty_score":0.3342156},"labels":[],"label_agreement":null},{"id":"W2891242934","doi":"10.2316/journal.206.2018.5.206-0066","title":"FUDP: AN SDN-BASED MECHANISM FOR CONTROLLING UDP FLOWS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Government of Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Mechanism (biology); Computer science; Computer network; Physics","score_opus":0.010276054644699838,"score_gpt":0.2504266114998949,"score_spread":0.2401505568551951,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891242934","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":[0.2804925,0.000050221413,0.71711224,0.0003805051,0.001825198,0.000054713426,0.0000060101447,0.000028372218,0.00005024439],"genre_scores_gemma":[0.9723761,0.00002720785,0.026654927,0.00010431658,0.0008188416,0.0000012647947,0.0000048539573,0.000008002255,0.000004479661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945456,0.000009443351,0.00022897497,0.000048771533,0.00018558506,0.00007269078],"domain_scores_gemma":[0.99933493,0.000055371038,0.00008387004,0.0000366533,0.00044349598,0.00004567436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017773669,0.000059910282,0.00009060132,0.000107790074,0.000046294226,0.00007153476,0.00011812612,0.000042066495,0.0000081491535],"category_scores_gemma":[0.000048462804,0.00005272407,0.000042102434,0.000028431507,0.000018449517,0.00020879362,0.000004833811,0.000058165795,0.0000016543892],"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":[0.00009265836,0.00006367882,0.000120518285,0.000035374538,0.00012852489,0.00000880658,0.0005122595,0.9239379,0.0297301,0.031550527,0.0001955892,0.013624022],"study_design_scores_gemma":[0.00072568003,0.00014556073,0.00031935572,0.00005413028,0.00001505518,0.000023395418,0.00002954669,0.9868744,0.0071268543,0.0042887647,0.00033524536,0.000061986575],"about_ca_topic_score_codex":0.0000014321514,"about_ca_topic_score_gemma":0.00000959914,"teacher_disagreement_score":0.6918836,"about_ca_system_score_codex":0.000027286043,"about_ca_system_score_gemma":0.000021580025,"threshold_uncertainty_score":0.21500252},"labels":[],"label_agreement":null},{"id":"W2892036163","doi":"10.2316/journal.206.2018.5.206-0064","title":"QoS-GUARANTEED MODEL RESEARCH FOR A SATELLITE NETWORK","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Satellite; Computer science; Quality of service; Computer network; Aerospace engineering; Engineering","score_opus":0.06142082422172565,"score_gpt":0.3481691919836529,"score_spread":0.28674836776192725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892036163","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":[0.03666583,0.00048462415,0.96024823,0.00046435875,0.0014124243,0.00008942939,0.0000040003565,0.000025170753,0.0006059014],"genre_scores_gemma":[0.9469053,0.00043418957,0.051263563,0.000055375265,0.0012630089,0.0000019512186,0.0000028586448,0.000013609968,0.000060119368],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991649,0.000015710923,0.00030566554,0.00006298935,0.00031117236,0.00013956793],"domain_scores_gemma":[0.99894774,0.00007786191,0.00007118158,0.00005539141,0.0008040465,0.0000437658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006199616,0.00006458881,0.00009990147,0.00013589197,0.00006222637,0.00009675033,0.00017476353,0.00004613165,0.000007922719],"category_scores_gemma":[0.000057296893,0.000056742894,0.00004344171,0.00007171613,0.000048087906,0.00014194967,0.000020117135,0.000112389986,0.000004818205],"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":[0.00003128564,0.000014045998,0.00013605264,0.000015058827,0.00007422379,0.0000030473873,0.0003741849,0.94028926,0.0013410345,0.019485913,0.0022180653,0.036017798],"study_design_scores_gemma":[0.00018278373,0.00008370612,0.00036303652,0.000088331144,0.000007609341,0.000037947153,0.000025010831,0.98056316,0.0010993604,0.014325861,0.0031615507,0.000061657374],"about_ca_topic_score_codex":0.000001364345,"about_ca_topic_score_gemma":0.000004063208,"teacher_disagreement_score":0.9102395,"about_ca_system_score_codex":0.000044263714,"about_ca_system_score_gemma":0.000023577893,"threshold_uncertainty_score":0.23139082},"labels":[],"label_agreement":null},{"id":"W2901112447","doi":"10.2316/journal.206.2018.6.206-5086","title":"A STRESS DETECTION METHOD FOR REINFORCED CONCRETE STRUCTURE BASED ON METAL MAGNETIC MEMORY","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reinforced concrete; Magnetic memory; Structural engineering; Materials science; Stress (linguistics); Metal; Composite material; Metallurgy; Engineering","score_opus":0.009117364533720638,"score_gpt":0.2686034929393551,"score_spread":0.25948612840563445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901112447","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":[0.11549658,0.00001909566,0.8831514,0.000094459305,0.00074939075,0.00011398006,0.00002079558,0.00009668009,0.00025762495],"genre_scores_gemma":[0.5732771,0.0000022053268,0.42647687,0.000029328183,0.00019525067,0.0000015463565,0.0000041772355,0.000010665001,0.0000028717486],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993382,0.000023459064,0.00026717695,0.00006866763,0.0002260838,0.00007640507],"domain_scores_gemma":[0.99912465,0.00015061045,0.00016530375,0.000059327427,0.0004652421,0.000034860488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019733844,0.00009655438,0.00011918285,0.00021366595,0.000035399382,0.000057999383,0.00011805295,0.00005866837,0.000014624533],"category_scores_gemma":[0.00016520178,0.00008837973,0.00004876997,0.00005295589,0.000029854318,0.00015153804,0.00001013675,0.00010478855,4.5021255e-7],"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":[0.00027389685,0.0000073500014,0.0001628457,0.00012704603,0.0002650471,0.000013778765,0.0003389533,0.329165,0.57250065,0.011518064,0.0001764759,0.085450865],"study_design_scores_gemma":[0.0004946522,0.0004141202,0.0008020874,0.000101940044,0.00003312558,0.00006272936,0.0000122036045,0.88296914,0.10789561,0.007106902,0.000019358458,0.00008814219],"about_ca_topic_score_codex":0.0000030731835,"about_ca_topic_score_gemma":0.000002203875,"teacher_disagreement_score":0.5538041,"about_ca_system_score_codex":0.0000792862,"about_ca_system_score_gemma":0.00001797187,"threshold_uncertainty_score":0.36040208},"labels":[],"label_agreement":null},{"id":"W2901302962","doi":"10.2316/journal.206.2018.6.206-5092","title":"DETECTION AND REPAIR OF COVERAGE HOLES IN MOBILE SENSOR NETWORKS USING SUB-VORONOI CELLS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Voronoi diagram; Computer science; Wireless sensor network; Computer network; Mathematics; Geometry","score_opus":0.008295951715926978,"score_gpt":0.23661105159902482,"score_spread":0.22831509988309784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901302962","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":[0.5129865,0.000113876624,0.48636875,0.000022919703,0.00046421163,0.000025514448,3.1865e-7,0.000008921696,0.000009017863],"genre_scores_gemma":[0.9712391,0.0002513458,0.028293522,0.000026091771,0.0001808615,3.088659e-7,4.3171715e-7,0.000004933696,0.0000034273642],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991319,0.000052046653,0.00037911988,0.00010965915,0.00023967383,0.0000876022],"domain_scores_gemma":[0.9990803,0.00008203924,0.00039881482,0.000075339005,0.0003287547,0.000034744073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002936397,0.0000723023,0.00012726679,0.0002096707,0.000034334927,0.00007351365,0.00014966946,0.000056552,8.792078e-7],"category_scores_gemma":[0.000018905506,0.00006864855,0.000038063346,0.00012474651,0.000069132446,0.00033560768,0.00007007585,0.00009352734,2.1223885e-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":[0.000013199398,0.000036665162,0.0010193755,0.000005132781,0.000020734593,0.000010286548,0.00015863066,0.96665066,0.0149379,0.00066118414,0.0000038748626,0.016482327],"study_design_scores_gemma":[0.00031099003,0.00012548828,0.0064935097,0.000111757225,0.000006445631,0.00008452748,0.000018342218,0.9822351,0.010391821,0.00013285312,0.000026883545,0.00006232147],"about_ca_topic_score_codex":0.000010901991,"about_ca_topic_score_gemma":0.000013698241,"teacher_disagreement_score":0.4582526,"about_ca_system_score_codex":0.00005419623,"about_ca_system_score_gemma":0.000020383102,"threshold_uncertainty_score":0.2799407},"labels":[],"label_agreement":null},{"id":"W2901752692","doi":"10.2316/journal.206.2018.6.206-5160","title":"QUICK TWO-WAY TIME MESSAGE EXCHANGE FOR TIME SYNCHRONIZATION IN ROBOT NETWORKS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Network Time Synchronization Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Southwest University; Southwest University of Science and Technology; National Natural Science Foundation of China","keywords":"Synchronization (alternating current); Computer science; Time synchronization; Robot; Real-time computing; Computer network; Artificial intelligence; Channel (broadcasting)","score_opus":0.007484217637689139,"score_gpt":0.24984583274354938,"score_spread":0.24236161510586024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901752692","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":[0.0023114695,0.00026520496,0.9939894,0.0023169983,0.0006910541,0.00015832428,0.0000019506408,0.00008624391,0.00017931774],"genre_scores_gemma":[0.84243196,0.00012973876,0.15625505,0.00017732062,0.0007042957,0.000005577241,0.00001790411,0.00001703305,0.00026109858],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987664,0.000050882358,0.0005083332,0.00017442442,0.0003271267,0.00017282735],"domain_scores_gemma":[0.99847287,0.00013516507,0.0005155726,0.0001437832,0.0006894775,0.00004315937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005716159,0.000122664,0.00018668293,0.00038839225,0.00006970162,0.00023042544,0.00062968483,0.00009005529,0.000043906737],"category_scores_gemma":[0.00013590175,0.00011638835,0.00004827229,0.0003106536,0.000069853624,0.00084163545,0.00015790288,0.00010561121,0.000020539392],"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":[0.000043577224,0.00015870976,0.0007832047,0.000023251434,0.00013504061,0.000023082994,0.00051195425,0.56527126,0.0012206062,0.026615037,0.005079339,0.40013495],"study_design_scores_gemma":[0.0008217727,0.00017566385,0.0012038513,0.00011666075,0.000008570816,0.000058621066,0.0000058161895,0.99186397,0.00033838197,0.004859662,0.00042816479,0.00011889227],"about_ca_topic_score_codex":0.0000028446407,"about_ca_topic_score_gemma":0.000004874887,"teacher_disagreement_score":0.8401205,"about_ca_system_score_codex":0.00016098678,"about_ca_system_score_gemma":0.000059436028,"threshold_uncertainty_score":0.47461793},"labels":[],"label_agreement":null},{"id":"W2901778172","doi":"10.2316/journal.206.2018.6.206-5487","title":"RING COUPLING-BASED COLLABORATIVE FAULT-TOLERANT CONTROL FOR MULTI-ROBOT ACTUATOR FAULT","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Actuator; Coupling (piping); Fault (geology); Computer science; Ring (chemistry); Fault tolerance; Control theory (sociology); Robot; Control (management); Control engineering; Engineering; Artificial intelligence; Distributed computing; Chemistry; Geology; Mechanical engineering","score_opus":0.013049677972482363,"score_gpt":0.27264959927854543,"score_spread":0.2595999213060631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901778172","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":[0.07993116,0.00015336457,0.9167875,0.00044662264,0.0023320906,0.00021057745,0.00003069965,0.000067575245,0.00004043237],"genre_scores_gemma":[0.9865982,0.000015875092,0.012669025,0.00008653735,0.0005784648,0.000009787699,0.000004805525,0.000018486431,0.000018832106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990782,0.000014166694,0.00044988637,0.000082200844,0.00026165048,0.00011390663],"domain_scores_gemma":[0.99854964,0.00009817859,0.00023799555,0.000051863313,0.0009947427,0.00006756959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000245473,0.000118737524,0.00020031727,0.00017080917,0.00007100418,0.00013553306,0.0001238467,0.00006953204,0.000008242578],"category_scores_gemma":[0.00010106403,0.00010587377,0.00007342379,0.00007135735,0.000032455126,0.00019345296,0.0000054908846,0.00009179748,0.000004881315],"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":[0.00012459593,0.00003915309,0.00010853797,0.00002538417,0.00025275705,0.000004513173,0.00026306298,0.9751354,0.018317647,0.00038739355,0.0001661319,0.0051754373],"study_design_scores_gemma":[0.0035403185,0.00015168446,0.0007626244,0.00011222869,0.000032411786,0.000021771948,0.000112792965,0.99005985,0.0034850773,0.00003937242,0.0015712583,0.000110632325],"about_ca_topic_score_codex":0.000003274543,"about_ca_topic_score_gemma":0.000015120106,"teacher_disagreement_score":0.90666705,"about_ca_system_score_codex":0.00010019632,"about_ca_system_score_gemma":0.000045919212,"threshold_uncertainty_score":0.4317407},"labels":[],"label_agreement":null},{"id":"W2909279054","doi":"10.2316/j.2019.206-5179","title":"DIFFERENTIAL FLATNESS ACTIVE DISTURBANCE REJECTION CONTROL APPROACH FOR A CLASS OF NONLINEAR UNCERTAIN SYSTEMS","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Flatness (cosmology); Nonlinear system; Disturbance (geology); Class (philosophy); Differential (mechanical device); Computer science; Mathematics; Control (management); Artificial intelligence; Engineering; Physics; Biology","score_opus":0.006115028510956585,"score_gpt":0.22475911786380393,"score_spread":0.21864408935284735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909279054","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":[0.06272285,0.00012261131,0.9352325,0.00004332523,0.0014370426,0.00030020034,0.00003236541,0.000021234726,0.0000878647],"genre_scores_gemma":[0.9885515,0.000028864371,0.011059718,0.0000037011766,0.0002721472,0.000008587939,0.000029201208,0.000014860983,0.0000314074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991608,0.000022433404,0.00043253772,0.00007320031,0.00023783049,0.000073170464],"domain_scores_gemma":[0.99893403,0.00008151926,0.00039113752,0.000054663953,0.0005130677,0.000025561681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001022709,0.00008965941,0.00023731121,0.00012484395,0.00001616977,0.00003993568,0.000097735145,0.000060694023,0.000001517405],"category_scores_gemma":[0.000037308582,0.00008046824,0.0000615946,0.00004850685,0.000012312149,0.00028164024,0.000006512485,0.0000752037,2.9735844e-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":[0.000107865766,0.000024359022,0.0002831191,0.00009686539,0.00017431268,3.6394502e-7,0.00007600543,0.98933315,0.006536282,0.0014898297,0.000010778127,0.0018670729],"study_design_scores_gemma":[0.0017403286,0.00007179864,0.0009732792,0.00011011894,0.000034268727,0.000024873869,0.00008968885,0.9962641,0.0004685872,0.00008519156,0.000064432235,0.00007336034],"about_ca_topic_score_codex":0.0000038597177,"about_ca_topic_score_gemma":4.4465125e-7,"teacher_disagreement_score":0.92582864,"about_ca_system_score_codex":0.00011116748,"about_ca_system_score_gemma":0.00001735154,"threshold_uncertainty_score":0.32814},"labels":[],"label_agreement":null},{"id":"W2909575609","doi":"10.2316/j.2019.206-0144","title":"DAMAGE IDENTIFICATION OF BRIDGE SYSTEM BASED ON A HYBRID ALGORITHM","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Fund for Distinguished Young Scholars; National Key Research and Development Program of China; Chongqing Municipal Education Commission; National Natural Science Foundation of China","keywords":"Identification (biology); Bridge (graph theory); Computer science; Algorithm","score_opus":0.009274238810376943,"score_gpt":0.26615045153822753,"score_spread":0.2568762127278506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909575609","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":[0.83901864,0.000030371108,0.15869084,0.00010921009,0.0018884932,0.00009006167,0.000015102183,0.00007227601,0.000085017346],"genre_scores_gemma":[0.9866253,0.000018383473,0.013196883,0.000008964509,0.00012870836,8.3624633e-7,0.0000065093177,0.0000093889485,0.000004984251],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991713,0.000015182543,0.0004083174,0.00004832332,0.000304488,0.00005240086],"domain_scores_gemma":[0.9993464,0.000049348037,0.00025349003,0.00007202408,0.00025175637,0.000026987955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020500964,0.000060807233,0.00011018239,0.00020285866,0.000010577395,0.000030646082,0.0001248103,0.00002725791,0.0000029268479],"category_scores_gemma":[0.000017541577,0.00005680978,0.000034526904,0.000041909556,0.000008443053,0.00013824545,0.000008455473,0.0000823753,0.0000027371154],"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":[0.000037813254,0.000039607043,0.0033089744,0.00046354186,0.00010133367,0.000020792539,0.00014983151,0.7081981,0.009949357,0.002100993,0.00031039686,0.27531928],"study_design_scores_gemma":[0.00022400833,0.000056624616,0.097900346,0.00027845014,0.000007354948,0.00003416236,0.0000106984535,0.8867994,0.014462779,0.00015294015,0.000027052738,0.00004617145],"about_ca_topic_score_codex":0.0000037337547,"about_ca_topic_score_gemma":6.9751295e-8,"teacher_disagreement_score":0.2752731,"about_ca_system_score_codex":0.0001249644,"about_ca_system_score_gemma":0.000015965748,"threshold_uncertainty_score":0.23166355},"labels":[],"label_agreement":null},{"id":"W2910246595","doi":"10.2316/j.2019.206-5582","title":"STUDY ON RUST DETECTION OF RC STRUCTURE BASED ON ELECTROMAGNETIC PULSED EDDY CURRENT","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Fund for Distinguished Young Scholars; National Key Research and Development Program of China","keywords":"Current (fluid); Eddy current; Rust (programming language); Electrical engineering; Computer science; Engineering","score_opus":0.011697572174057022,"score_gpt":0.2731956504645709,"score_spread":0.26149807829051386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910246595","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":[0.94545794,0.000019048623,0.0533744,0.000046939953,0.0007795609,0.00011067496,0.0000047013646,0.000063961066,0.00014280246],"genre_scores_gemma":[0.9752175,0.0000053336844,0.0245439,0.000009743124,0.00020688855,0.0000010623539,0.000002046669,0.000013023535,4.82617e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916637,0.000030692267,0.00030097336,0.0000713273,0.0003604282,0.000070179995],"domain_scores_gemma":[0.9992627,0.00006396338,0.00019901605,0.000072498005,0.0003736535,0.000028198376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013774584,0.000098316064,0.00011810088,0.00030316715,0.000025335376,0.00003511166,0.00012566503,0.000034701952,0.000008897745],"category_scores_gemma":[0.00009253731,0.00008808597,0.00003166397,0.00008894894,0.00002698482,0.00009094905,0.000009691626,0.00016510351,8.284027e-7],"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":[0.0004191376,0.0009316976,0.010898648,0.00010967053,0.00037496877,0.000033685963,0.00095637527,0.14497201,0.6853138,0.0042251707,0.00019477447,0.15157002],"study_design_scores_gemma":[0.0025220169,0.008548829,0.35705736,0.000745072,0.000115676805,0.00012605893,0.00008413533,0.45144543,0.15125352,0.02767039,0.000038846927,0.00039265712],"about_ca_topic_score_codex":0.0000018366451,"about_ca_topic_score_gemma":0.000002911786,"teacher_disagreement_score":0.5340603,"about_ca_system_score_codex":0.00010766359,"about_ca_system_score_gemma":0.000018297014,"threshold_uncertainty_score":0.35920417},"labels":[],"label_agreement":null},{"id":"W2910331036","doi":"10.2316/j.2019.206-5063","title":"FUZZY SLIDING MODE CONTROL OF 3-DOF SHOULDER JOINT DRIVEN BY PNEUMATIC MUSCLE ACTUATORS","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Pneumatic actuator; Actuator; Joint (building); Fuzzy logic; Sliding mode control; Computer science; Mode (computer interface); Control engineering; Control (management); Engineering; Artificial intelligence; Structural engineering; Physics; Nonlinear system","score_opus":0.010541634473686895,"score_gpt":0.24252323727965516,"score_spread":0.23198160280596827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910331036","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":[0.5232485,0.00016541198,0.47451487,0.0007345471,0.0006466657,0.000070665905,0.000010618389,0.000037509726,0.0005712072],"genre_scores_gemma":[0.9973195,0.0001773902,0.0023046343,0.000050920942,0.00012739089,9.565576e-7,0.0000031420498,0.000010553708,0.000005466712],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999172,0.000015427784,0.00039722872,0.000052319163,0.00027584875,0.00008718788],"domain_scores_gemma":[0.9993011,0.00004893255,0.0002249806,0.00004506989,0.00034149474,0.000038443246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000114722585,0.00008559656,0.00016856025,0.00020253315,0.00003613445,0.000035839344,0.00009447049,0.00003674799,0.000012609149],"category_scores_gemma":[0.000047444282,0.00007653489,0.000064759835,0.000075953474,0.000026768164,0.00022793857,0.000011794259,0.00008251401,4.7451533e-7],"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":[0.00007412537,0.00028144353,0.0056495797,0.00020580122,0.0026594524,0.000008478725,0.004785826,0.20296378,0.5124065,0.025274036,0.009040181,0.23665078],"study_design_scores_gemma":[0.001955589,0.00032149928,0.055942554,0.00037148307,0.0001075752,0.00004415538,0.0003630798,0.91518676,0.019856542,0.004999347,0.0005677977,0.00028358723],"about_ca_topic_score_codex":0.0000036760293,"about_ca_topic_score_gemma":0.0000021337396,"teacher_disagreement_score":0.712223,"about_ca_system_score_codex":0.000043540385,"about_ca_system_score_gemma":0.000014044987,"threshold_uncertainty_score":0.31210023},"labels":[],"label_agreement":null},{"id":"W2910619045","doi":"10.2316/j.2019.206-4803","title":"STABILIZING CONTROL ALGORITHM FOR NONHOLONOMIC WHEELED MOBILE ROBOTS USING ADAPTIVE INTEGRAL SLIDING MODE","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Nonholonomic system; Integral sliding mode; Mobile robot; Computer science; Control theory (sociology); Sliding mode control; Mode (computer interface); Control (management); Robot; Artificial intelligence; Physics; Human–computer interaction","score_opus":0.007604361797536175,"score_gpt":0.24305950278288863,"score_spread":0.23545514098535245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910619045","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":[0.27699584,0.00025323435,0.72122675,0.00004379606,0.0011746262,0.00022424535,0.00002362203,0.000028873796,0.000028995986],"genre_scores_gemma":[0.91257054,0.000054472745,0.08707558,0.000021133368,0.00023088761,0.0000066579487,0.000007660195,0.00002316308,0.000009880574],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907446,0.000017046978,0.00045120687,0.00010419118,0.0002035,0.00014958969],"domain_scores_gemma":[0.99914885,0.00014868977,0.00022476622,0.00006296579,0.000356094,0.00005863129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023034225,0.0001379268,0.0002643978,0.00020530404,0.000034465687,0.000102689286,0.00015805791,0.00006879732,0.000007353052],"category_scores_gemma":[0.000020986961,0.00013135237,0.00012360181,0.000038641258,0.00001214205,0.00043119988,0.000020837031,0.00014091145,0.0000020603559],"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":[0.000036453854,0.00001957348,0.00020834096,0.000011776163,0.00016781568,0.000002809537,0.00010271819,0.94245416,0.008832711,0.00061178143,0.000008093549,0.04754379],"study_design_scores_gemma":[0.0019042103,0.00013416538,0.00037611264,0.00012234884,0.000047002664,0.00006057601,0.000119509576,0.9961207,0.00022663888,0.00072255154,0.00003146503,0.00013472015],"about_ca_topic_score_codex":0.000007890291,"about_ca_topic_score_gemma":0.0000039738397,"teacher_disagreement_score":0.6355747,"about_ca_system_score_codex":0.00021758887,"about_ca_system_score_gemma":0.000039787883,"threshold_uncertainty_score":0.5356394},"labels":[],"label_agreement":null},{"id":"W2910920008","doi":"10.2316/j.2019.206-4831","title":"LEADER-FOLLOWER FORMATION CONTROL OF MULTI-ROBOTS BASED ON BEARING-ONLY OBSERVATIONS","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Bearing (navigation); Robot; Control (management); Computer science; Control theory (sociology); Artificial intelligence","score_opus":0.02332087815556719,"score_gpt":0.24497106708873143,"score_spread":0.22165018893316424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910920008","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":[0.20117672,0.00007601376,0.7971537,0.0004460313,0.0008598829,0.000102709644,0.000007820465,0.000022518125,0.00015456845],"genre_scores_gemma":[0.98751307,0.000041074905,0.012229161,0.000097072654,0.000057753874,8.994257e-7,0.000009949389,0.000011423547,0.00003960473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904495,0.00001673841,0.00045168298,0.00005944948,0.00034726245,0.00007993451],"domain_scores_gemma":[0.99922633,0.00007239623,0.0002252528,0.000078813544,0.00036045467,0.000036737107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018612912,0.00009128283,0.00015579376,0.00020427241,0.000019068144,0.00004611885,0.00014590145,0.000053795964,0.000026429376],"category_scores_gemma":[0.00004245484,0.000081965634,0.00007114375,0.00006344216,0.000014350988,0.0003293499,0.000008083765,0.00011504045,0.000008226194],"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":[0.000015692307,0.000046544952,0.0029187812,0.000029258352,0.000049813945,0.0000021978815,0.0001281702,0.98447233,0.0047622067,0.0016413748,0.000047016772,0.0058866073],"study_design_scores_gemma":[0.00076381484,0.000089339475,0.02118126,0.00016836193,0.00001647082,0.00001795345,0.000037366586,0.9752388,0.0021735877,0.00010878521,0.00012521373,0.00007905288],"about_ca_topic_score_codex":0.000003098983,"about_ca_topic_score_gemma":0.0000027923081,"teacher_disagreement_score":0.78633636,"about_ca_system_score_codex":0.00005442564,"about_ca_system_score_gemma":0.000025906409,"threshold_uncertainty_score":0.33424616},"labels":[],"label_agreement":null},{"id":"W2910983971","doi":"10.2316/j.2019.206-5477","title":"ROBUST H-INFINITY AUXILIARY DRIVING HEADING CONTROL FOR A UUV IN LOW SPEED MODE","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Heading (navigation); Control theory (sociology); Mode (computer interface); Infinity; Computer science; Control (management); Engineering; Aerospace engineering; Mathematics; Artificial intelligence; Mathematical analysis; Operating system","score_opus":0.007419834578243772,"score_gpt":0.22315380806070612,"score_spread":0.21573397348246234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910983971","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":[0.7576014,0.000061354134,0.24057297,0.00037618104,0.0010168582,0.00014854396,0.000008929616,0.000019435409,0.00019432064],"genre_scores_gemma":[0.9984506,0.000027772663,0.0012746701,0.00003623065,0.00016227222,0.0000015166875,0.0000047443136,0.0000123612435,0.000029884264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992473,0.000013737262,0.00039658937,0.000060441696,0.00018148313,0.00010045859],"domain_scores_gemma":[0.9995173,0.000100478945,0.00014036575,0.00004332476,0.00016225626,0.00003622559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025619927,0.000077579345,0.00018031031,0.00017012072,0.000014337019,0.000080149206,0.0001095516,0.00004924798,0.0000047472604],"category_scores_gemma":[0.000034346835,0.00007550439,0.000061201055,0.000038558093,0.0000056819767,0.00029628578,0.000008762135,0.0001043801,0.0000018972954],"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":[0.000017823208,0.000015985675,0.012504016,0.0000324557,0.00006442512,0.0000039511715,0.00008474065,0.97834283,0.0046388637,0.0021333152,0.0000151578615,0.0021464464],"study_design_scores_gemma":[0.0016125371,0.000029626,0.016867092,0.0002427563,0.000009150647,0.000029988405,0.00003292029,0.98048,0.000037919555,0.0005421014,0.000040520412,0.00007534453],"about_ca_topic_score_codex":0.000010766213,"about_ca_topic_score_gemma":0.000017354167,"teacher_disagreement_score":0.24084915,"about_ca_system_score_codex":0.00010514439,"about_ca_system_score_gemma":0.000017649167,"threshold_uncertainty_score":0.30789798},"labels":[],"label_agreement":null},{"id":"W2916095269","doi":"10.2316/j.2019.206-0088","title":"MULTI-OBJECTIVE TRAJECTORY PLANNING OF ROBOT MANIPULATOR IN A MOVING OBSTACLE ENVIRONMENT","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Obstacle; Trajectory; Robot; Computer science; Obstacle avoidance; Manipulator (device); Robot manipulator; Motion planning; Artificial intelligence; Mobile robot; Geography; Physics","score_opus":0.018880587133343268,"score_gpt":0.26148948268463595,"score_spread":0.2426088955512927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916095269","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":[0.31945628,0.0001646787,0.67954814,0.00014841148,0.0005757173,0.00006556124,0.0000010229766,0.000009277929,0.00003090375],"genre_scores_gemma":[0.70126885,0.000010590377,0.2986517,0.000019240502,0.000028187325,4.794391e-7,8.834301e-7,0.0000041068365,0.000015999378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887025,0.000044667202,0.00044664834,0.00012700827,0.00041028037,0.00010111518],"domain_scores_gemma":[0.9991873,0.000106494466,0.00046731462,0.0000957462,0.000103840124,0.000039334347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003425118,0.00008568497,0.0001759114,0.0002949006,0.000015222422,0.000051756546,0.00034931596,0.000044051485,0.0000038569483],"category_scores_gemma":[0.00004504261,0.000081559694,0.00004602438,0.00007319348,0.000016820224,0.00047385055,0.00008308207,0.00013732156,0.0000035116739],"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":[0.000008649503,0.000079416655,0.030040177,0.00001035642,0.0000422821,0.000041057796,0.0015324659,0.95656115,0.0062748254,0.0005393057,0.0000036072142,0.004866706],"study_design_scores_gemma":[0.00060815684,0.000073083735,0.27981713,0.00017938025,0.0000039097354,0.000084154344,0.00010278051,0.7182754,0.00061039464,0.00017589307,0.0000050353783,0.000064636886],"about_ca_topic_score_codex":0.000010885136,"about_ca_topic_score_gemma":3.5498763e-7,"teacher_disagreement_score":0.38181254,"about_ca_system_score_codex":0.00012034729,"about_ca_system_score_gemma":0.000047985624,"threshold_uncertainty_score":0.3325908},"labels":[],"label_agreement":null},{"id":"W2916283377","doi":"10.2316/j.2019.206-5441","title":"MOTION CONTINUITY AND BRANCH IDENTIFICATION OF TWO-DOF SEVEN-BAR PLANAR PARALLEL MANIPULATORS AND LINKAGES","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Engineering Applied Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bar (unit); Planar; Identification (biology); Motion (physics); Control theory (sociology); Computer science; Artificial intelligence; Physics; Computer graphics (images); Control (management)","score_opus":0.008140557573313244,"score_gpt":0.25056768848258754,"score_spread":0.24242713090927429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916283377","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":[0.90471905,0.00027166647,0.094485484,0.00012172805,0.0002604611,0.00006995454,0.0000049164796,0.00001797474,0.000048755577],"genre_scores_gemma":[0.99640054,0.00029912766,0.003202507,0.0000036564375,0.000061039085,7.23629e-7,0.0000062381982,0.000008642307,0.000017518174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928993,0.000012119268,0.00032116173,0.000064025524,0.0002491484,0.000063602005],"domain_scores_gemma":[0.9995866,0.00005226647,0.00013143686,0.00004761655,0.00014406652,0.000038027356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028598195,0.000068290334,0.0001228252,0.00016354858,0.000013308647,0.000055465265,0.00007181299,0.000044366563,0.000003959111],"category_scores_gemma":[0.000022043252,0.000066569686,0.00001935693,0.000037895727,0.000020827936,0.00018193138,0.000015221447,0.00011545825,0.0000019819793],"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":[0.000015374852,0.000038740196,0.029741796,0.00025345242,0.00020149926,0.000004803171,0.00056193775,0.8554855,0.07967208,0.0120444605,0.00005632834,0.02192403],"study_design_scores_gemma":[0.0010498428,0.00003371386,0.32058087,0.00012887002,0.00002142774,0.000089620386,0.00005265858,0.67175853,0.0036399548,0.0024956248,0.00004335133,0.00010551739],"about_ca_topic_score_codex":0.000004025341,"about_ca_topic_score_gemma":0.0000011195124,"teacher_disagreement_score":0.29083908,"about_ca_system_score_codex":0.000028995952,"about_ca_system_score_gemma":0.0000064985124,"threshold_uncertainty_score":0.27146327},"labels":[],"label_agreement":null},{"id":"W2917495073","doi":"10.2316/j.2019.206-5291","title":"RELIABILITY-BASED MULTI-ROBOT ROUTE PLANNING","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reliability (semiconductor); Computer science; Reliability engineering; Robot; Artificial intelligence; Engineering","score_opus":0.018482605562598575,"score_gpt":0.286169673298369,"score_spread":0.26768706773577045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917495073","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":[0.044553317,0.00007154979,0.9519468,0.001375514,0.001857926,0.00006401364,0.0000015942946,0.00004369283,0.00008560037],"genre_scores_gemma":[0.5119143,0.0000035233154,0.48780963,0.0001543906,0.00006788255,4.0443518e-7,0.0000026379987,0.000004460679,0.00004280077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987266,0.00005118136,0.00042401926,0.0001553979,0.00052126026,0.000121534125],"domain_scores_gemma":[0.998716,0.00014825612,0.000442428,0.00016021129,0.00046291907,0.00007017085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050166086,0.00010220108,0.00016296879,0.000232312,0.000036094523,0.0002159866,0.000589759,0.000054801123,0.0000043129135],"category_scores_gemma":[0.00010263268,0.00008923073,0.00006488876,0.0001045666,0.000019913627,0.00064757,0.00008007933,0.00016917645,0.000016862728],"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":[0.000008524952,0.000060765167,0.0110085355,0.000010114285,0.00003363532,0.000043453434,0.00027431062,0.9781547,0.0012706472,0.0017864362,0.000059314316,0.007289556],"study_design_scores_gemma":[0.0007978267,0.00008994511,0.04966385,0.0001627453,0.000006625878,0.0001113593,0.000017239241,0.9480252,0.00037386443,0.0005091332,0.00014485588,0.000097349715],"about_ca_topic_score_codex":0.000004534311,"about_ca_topic_score_gemma":9.8875255e-8,"teacher_disagreement_score":0.46736097,"about_ca_system_score_codex":0.000083983614,"about_ca_system_score_gemma":0.00010577996,"threshold_uncertainty_score":0.36387235},"labels":[],"label_agreement":null},{"id":"W2922703966","doi":"10.2316/j.2019.206-0072","title":"AN INTERACTION-AWARE PREDICTIVE MOTION PLANNER FOR UNMANNED GROUND VEHICLES IN DYNAMIC STREET SCENARIOS","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Planner; Computer science; Motion (physics); Artificial intelligence","score_opus":0.007594738576417841,"score_gpt":0.2514990632616926,"score_spread":0.24390432468527473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922703966","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":[0.93239,0.000028767783,0.066200376,0.0001636142,0.0009773086,0.00015025493,0.00002990376,0.00003550402,0.000024303608],"genre_scores_gemma":[0.9980743,0.00006306055,0.0016016177,0.000018433604,0.000112113645,0.0000034625166,0.00010563449,0.000016329535,0.0000050762333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992701,0.000021134323,0.00033931813,0.00008509108,0.00019479431,0.000089589725],"domain_scores_gemma":[0.9994293,0.00008074362,0.00015566964,0.00004426938,0.0002518947,0.000038120248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016085542,0.00009086581,0.00012396966,0.0002905911,0.000017378528,0.0000813433,0.00009388986,0.00007166438,0.0000087100625],"category_scores_gemma":[0.000017991419,0.00009154909,0.000037959508,0.000053263142,0.000008471185,0.0008882816,0.000008116592,0.00013512246,0.00000378269],"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":[0.00008645701,0.00006360986,0.005595237,0.000039757975,0.00008512874,0.0000054586467,0.00032995077,0.96696913,0.0038444127,0.000118005184,0.000020696081,0.022842126],"study_design_scores_gemma":[0.0008732321,0.00014783615,0.060105976,0.00019479606,0.000015445961,0.000047851303,0.00037043297,0.93710953,0.00032247487,0.0007049426,0.00002179871,0.000085678876],"about_ca_topic_score_codex":0.000008526616,"about_ca_topic_score_gemma":0.000050038238,"teacher_disagreement_score":0.0656843,"about_ca_system_score_codex":0.00017961214,"about_ca_system_score_gemma":0.0000137122015,"threshold_uncertainty_score":0.37332636},"labels":[],"label_agreement":null},{"id":"W2947634121","doi":"10.2316/j.2019.206-5383","title":"A REFLECTION-BASED RF SOURCE LOCALIZATION ALGORITH","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reflection (computer programming); Computer science","score_opus":0.015353859267713656,"score_gpt":0.29468892029742894,"score_spread":0.2793350610297153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947634121","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":[0.0097076325,0.00010153511,0.9853417,0.003937709,0.00056506525,0.00006583068,3.766688e-7,0.000033142962,0.00024696038],"genre_scores_gemma":[0.9415876,0.000077548604,0.057854086,0.0002497143,0.00010333535,0.000001133382,0.0000047978424,0.000006536866,0.00011519303],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988111,0.00007324702,0.00032920815,0.000101411395,0.0005947816,0.00009020659],"domain_scores_gemma":[0.99847454,0.00014649577,0.00033451957,0.0001881649,0.0008019723,0.00005433453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042441854,0.00006708721,0.00010109141,0.0002787521,0.000054260494,0.0002738912,0.0006703009,0.000045780715,0.000014602283],"category_scores_gemma":[0.000060088703,0.000061047016,0.00004405535,0.00021724618,0.000021743901,0.00055315596,0.00010488048,0.00014764938,0.000014637961],"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":[0.00001367843,0.00006629015,0.0029628817,0.000008393519,0.000041845076,0.0000035143448,0.00021439012,0.89962125,0.00054397597,0.012456331,0.00032887992,0.083738595],"study_design_scores_gemma":[0.00045766763,0.000074818425,0.0020931785,0.00007116811,0.000003011125,0.00004268272,0.00001792933,0.9931366,0.00037073676,0.0010895254,0.0025796506,0.000063034015],"about_ca_topic_score_codex":0.0000068684676,"about_ca_topic_score_gemma":0.0000018368164,"teacher_disagreement_score":0.93188,"about_ca_system_score_codex":0.000091844595,"about_ca_system_score_gemma":0.00011146686,"threshold_uncertainty_score":0.2641139},"labels":[],"label_agreement":null},{"id":"W2948132369","doi":"10.2316/j.2019.206-0108","title":"SCALABLE AND OCCLUSION-AWARE MULTI-CUES CORRELATION FILTER FOR ROBUST STEREO VISUAL TRACKING","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; RGB color model; Stereopsis; Tracking (education); Scalability; Eye tracking; Depth perception; Perception; Psychology","score_opus":0.0167074436806255,"score_gpt":0.2756338801363501,"score_spread":0.2589264364557246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948132369","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":[0.22613844,0.00013423814,0.7727054,0.00032277964,0.0005332258,0.00007912348,0.000004175525,0.00006614919,0.000016500773],"genre_scores_gemma":[0.8500129,0.00008855545,0.14977512,0.00002118059,0.000050700855,8.777288e-7,0.000007083462,0.000011627938,0.000031931155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994669,0.000005080149,0.00024164433,0.00006702023,0.000141395,0.000077969205],"domain_scores_gemma":[0.9995014,0.00010307563,0.00010576097,0.000035977493,0.00022910918,0.000024651927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000973314,0.00007629978,0.00010901273,0.0001313026,0.000027346687,0.0000916578,0.000079677266,0.00005348063,0.000006024134],"category_scores_gemma":[0.000079982936,0.000068925365,0.000027236341,0.000033563272,0.000022093374,0.000498189,0.000035174588,0.000102134974,0.0000019873503],"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":[0.000016113647,0.000025841187,0.007834806,0.00004605711,0.000057113866,0.000004115017,0.000114609975,0.9457271,0.003641879,0.0006686379,0.00009380369,0.041769933],"study_design_scores_gemma":[0.00057570625,0.00004950713,0.009748705,0.0001405608,0.000012470253,0.00005524347,0.0000873456,0.9873007,0.0009901231,0.00088203314,0.00007899282,0.00007862862],"about_ca_topic_score_codex":5.006891e-7,"about_ca_topic_score_gemma":8.3179356e-7,"teacher_disagreement_score":0.6238745,"about_ca_system_score_codex":0.0000481321,"about_ca_system_score_gemma":0.000006375605,"threshold_uncertainty_score":0.2810695},"labels":[],"label_agreement":null},{"id":"W2948332426","doi":"10.2316/j.2019.206-0193","title":"A REVIEW ON HUMAN–EXOSKELETON COORDINATION TOWARDS LOWER LIMB ROBOTIC EXOSKELETON SYSTEMS","year":2019,"lang":"en","type":"review","venue":"International Journal of Robotics and Automation","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Shenzhen Fundamental Research and Discipline Layout project; National Natural Science Foundation of China","keywords":"Exoskeleton; Computer science; Powered exoskeleton; Physical medicine and rehabilitation; Engineering; Simulation; Medicine","score_opus":0.04746011522061421,"score_gpt":0.32940873536544724,"score_spread":0.281948620144833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948332426","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016514914,0.99062663,0.004618942,0.0002816692,0.0032632966,0.00045831446,0.000009425752,0.00007318748,0.000652025],"genre_scores_gemma":[0.001504912,0.997454,0.00017348483,0.00009197193,0.0004746513,0.000017095488,0.000075218064,0.00005366457,0.00015500357],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99779123,0.000092107795,0.0011467987,0.00018302976,0.00060462096,0.00018223733],"domain_scores_gemma":[0.998238,0.00012990486,0.0008887481,0.0001644198,0.000506671,0.00007220537],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037823638,0.0003766287,0.0011944729,0.0007132893,0.00005752689,0.00016215342,0.0003244519,0.00018556332,0.000016909127],"category_scores_gemma":[0.000088301786,0.00030799728,0.00044045597,0.00025374422,0.000023982846,0.00026850216,0.000036574533,0.00043636543,0.0000108388585],"study_design_candidate":"design_other","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":[0.0000052345463,0.00007238286,0.0000012801157,0.023990402,0.001027928,0.000013330594,0.000017788827,0.013555642,0.000008433349,0.001840196,0.0119387405,0.94752866],"study_design_scores_gemma":[0.0004401627,0.00049026735,0.00007552575,0.09858942,0.00095826964,0.00023551733,0.000010993052,0.0074315662,0.0000024247909,0.000078534984,0.891149,0.00053832366],"about_ca_topic_score_codex":0.0000040109217,"about_ca_topic_score_gemma":6.723795e-7,"teacher_disagreement_score":0.9469903,"about_ca_system_score_codex":0.00032543376,"about_ca_system_score_gemma":0.00007244507,"threshold_uncertainty_score":0.99993724},"labels":[],"label_agreement":null},{"id":"W2948397083","doi":"10.2316/j.2019.206-0052","title":"DESIGN AND IMPLEMENTATION OF THE VISUAL DETECTION SYSTEM FOR AMPHIBIOUS ROBOTS","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Adaptability; Computer science; Propulsion; Robot; Artificial intelligence; Tracking (education); Real-time computing; Systems engineering; Computer vision; Human–computer interaction; Engineering; Aerospace engineering","score_opus":0.0063421223257263655,"score_gpt":0.2657393477260512,"score_spread":0.25939722540032484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948397083","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":[0.25678557,0.000050312272,0.7425393,0.00007550367,0.0003769364,0.00015455794,0.0000031210518,0.000009847633,0.0000048331394],"genre_scores_gemma":[0.97764474,0.000036551024,0.022239372,0.0000049785044,0.000059255064,0.0000037014954,0.0000016020582,0.0000062443996,0.000003573588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995838,0.000007825564,0.00021842853,0.000037420934,0.00011329832,0.000039246133],"domain_scores_gemma":[0.9995934,0.00004463506,0.00016220931,0.000027774871,0.00015789774,0.000014091133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103192404,0.00004396513,0.00006872716,0.000052662686,0.00002438329,0.000022928623,0.000051471743,0.000020906758,9.362764e-7],"category_scores_gemma":[0.000004408725,0.00003392608,0.000025014382,0.000035821406,0.00000872275,0.000124397,0.000009616782,0.00003296328,2.6466185e-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":[0.000009266632,0.000009410748,0.00035869933,0.00005741546,0.000064693784,1.6323972e-7,0.00014116925,0.8418731,0.07529816,0.0016719629,0.000010202635,0.08050577],"study_design_scores_gemma":[0.0006684664,0.000079087724,0.009023341,0.000074759104,0.000026389887,0.000054938064,0.00029564276,0.91864514,0.07037379,0.00063275034,0.00006786001,0.000057843285],"about_ca_topic_score_codex":0.0000020713176,"about_ca_topic_score_gemma":0.000001653566,"teacher_disagreement_score":0.72085917,"about_ca_system_score_codex":0.00004177973,"about_ca_system_score_gemma":0.000009217219,"threshold_uncertainty_score":0.13834654},"labels":[],"label_agreement":null},{"id":"W2948622461","doi":"10.2316/j.2019.206-0172","title":"HYBRID MOTION CONTROL OF CABLE-DRIVEN HYPER REDUNDANT ROBOT CONSIDERING KINEMATIC AND TENSION OPTIMIZATION","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Tension (geology); Control theory (sociology); Motion control; Computer science; Robot; Motion (physics); Control (management); Control engineering; Engineering; Physics; Artificial intelligence; Classical mechanics","score_opus":0.009781502227999173,"score_gpt":0.23047620071094335,"score_spread":0.22069469848294418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948622461","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":[0.04748175,0.00011088162,0.9503173,0.0011758029,0.0007525002,0.00011044428,0.00000217452,0.00001930746,0.000029789175],"genre_scores_gemma":[0.6322895,0.000038614282,0.36757237,0.000045709996,0.00003749723,3.9670897e-7,0.0000026087653,0.0000047179374,0.000008559634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875057,0.000056303594,0.0005257328,0.00013610345,0.0004366215,0.00009466373],"domain_scores_gemma":[0.99842733,0.0001511112,0.0006743973,0.00011065605,0.00058126927,0.00005523389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035484988,0.000100602054,0.00023664777,0.00024949966,0.000034537003,0.00012238616,0.00021212881,0.0000388736,0.0000053180315],"category_scores_gemma":[0.00013879265,0.00008835676,0.00004132158,0.00006360138,0.00003127943,0.0006415517,0.00006780728,0.00009906475,0.0000017639936],"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":[0.000008607118,0.000029407862,0.0021783256,0.000024886833,0.000049221908,0.000013487136,0.00015134494,0.9875532,0.0045523797,0.001077755,0.000016439782,0.0043449453],"study_design_scores_gemma":[0.0009583177,0.00011066827,0.0061475933,0.00030814752,0.000023457807,0.00066137174,0.000021717151,0.99069136,0.00043290236,0.00055521773,0.000005762311,0.00008346945],"about_ca_topic_score_codex":0.000007549059,"about_ca_topic_score_gemma":1.1088736e-7,"teacher_disagreement_score":0.58480775,"about_ca_system_score_codex":0.000042520707,"about_ca_system_score_gemma":0.000051775976,"threshold_uncertainty_score":0.3603084},"labels":[],"label_agreement":null},{"id":"W2948900487","doi":"10.2316/j.2019.206-0231","title":"VISION-BASED MOBILE ROBOT LEADER–FOLLOWER CONTROL USING MODEL PREDICTIVE CONTROL","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Model predictive control; Mobile robot; Control (management); Computer science; Robot control; Robot; Control theory (sociology); Control engineering; Artificial intelligence; Engineering","score_opus":0.010610768715944656,"score_gpt":0.27172346598702407,"score_spread":0.26111269727107944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948900487","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":[0.02190816,0.000108290486,0.97531706,0.00102577,0.0013563945,0.00018599829,0.000009713746,0.000039040577,0.000049580645],"genre_scores_gemma":[0.7860127,0.0000042928064,0.21352097,0.0003236893,0.00010269122,0.0000017638039,0.0000020704838,0.000008510848,0.000023273442],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983247,0.000068123714,0.0005068245,0.00019021115,0.00074607285,0.00016405222],"domain_scores_gemma":[0.9982336,0.00021836099,0.000585692,0.00015730796,0.0007119045,0.00009312893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048013282,0.0001426501,0.00026061974,0.00027185303,0.0000546305,0.00023528344,0.00054073014,0.00007844384,0.00000570761],"category_scores_gemma":[0.00006638039,0.00012457184,0.000106777086,0.000097418706,0.000033374672,0.0008184638,0.00004245869,0.00018651785,0.000008272971],"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":[0.000034971526,0.000073924595,0.001310648,0.0000052834366,0.00009514855,0.00002140188,0.00015067212,0.99248517,0.0032518967,0.0006888168,0.000039338345,0.0018427595],"study_design_scores_gemma":[0.002503017,0.0002757384,0.0022208379,0.0001588165,0.000031790005,0.00009371062,0.000023231996,0.9937094,0.00016451658,0.0006843393,0.000011468343,0.00012313938],"about_ca_topic_score_codex":0.0000037465209,"about_ca_topic_score_gemma":1.1713238e-7,"teacher_disagreement_score":0.76410455,"about_ca_system_score_codex":0.0001294255,"about_ca_system_score_gemma":0.00020639123,"threshold_uncertainty_score":0.5079892},"labels":[],"label_agreement":null},{"id":"W2953726176","doi":"10.2316/j.2019.206-0260","title":"AN IMPROVED SPECTRAL CLUSTERING ALGORITHM FOR LARGE-SCALE WIND FARM POWER PREDICTION","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Division of Graduate Education; Scientific Research and Technology Development Program of Guangxi; Guilin University of Electronic Technology; Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Cluster analysis; Spectral clustering; Scale (ratio); Computer science; Algorithm; Environmental science; Artificial intelligence; Geography; Cartography","score_opus":0.00552015655873361,"score_gpt":0.23795724833420417,"score_spread":0.23243709177547056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953726176","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":[0.21927783,0.00013894206,0.77241,0.0002781702,0.0067896727,0.00015254389,0.00004466087,0.000041241954,0.00086698675],"genre_scores_gemma":[0.9705183,0.000029946217,0.028103353,0.00006484282,0.0007728886,0.0000014660601,0.00003778618,0.000019287092,0.00045212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904764,0.000023927843,0.0004152149,0.00012094732,0.0002538008,0.00013845389],"domain_scores_gemma":[0.9991741,0.000025919726,0.00032926621,0.00008138568,0.0003185811,0.00007072571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028168492,0.00010048732,0.0001618017,0.0001530391,0.00004484437,0.00012182507,0.00015226543,0.00008218022,0.00003337943],"category_scores_gemma":[0.000010475969,0.00008505212,0.00008462267,0.000040444153,0.000008351526,0.00035444673,0.00002238638,0.000077292876,0.00000204496],"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":[0.00014953851,0.00035374853,0.0020182447,0.00003846028,0.0005222011,0.00001290267,0.0012935665,0.82413286,0.05679563,0.008769762,0.00013487565,0.1057782],"study_design_scores_gemma":[0.0015795961,0.00038283796,0.006088057,0.000078316756,0.000024141404,0.00013187807,0.0002771676,0.9834193,0.0009628752,0.0005636597,0.006385054,0.000107100306],"about_ca_topic_score_codex":0.000070265785,"about_ca_topic_score_gemma":0.00011455036,"teacher_disagreement_score":0.7512405,"about_ca_system_score_codex":0.000070830676,"about_ca_system_score_gemma":0.000035624937,"threshold_uncertainty_score":0.34683248},"labels":[],"label_agreement":null},{"id":"W2954066018","doi":"10.2316/j.2019.206-0233","title":"COGNITIVE RADIO RESOURCE ALLOCATION BASED ON THE IMPROVED QUANTUM GENETIC ALGORITHM","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Satellite Communication Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cognitive radio; Computer science; Genetic algorithm; Resource allocation; Quantum; Cognition; Algorithm; Computer network; Distributed computing; Psychology; Machine learning; Telecommunications; Neuroscience; Wireless; Physics","score_opus":0.013070723177536004,"score_gpt":0.23862664968255412,"score_spread":0.22555592650501813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954066018","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":[0.27086136,0.0014884619,0.7186429,0.0044074836,0.002247062,0.0005583597,0.000018096158,0.00012105738,0.0016552059],"genre_scores_gemma":[0.994938,0.00014318907,0.0045879153,0.00014932784,0.00012658503,0.0000030127992,0.000012035234,0.0000149330735,0.00002501112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917245,0.00006565895,0.0003364015,0.00005886495,0.00030112968,0.00006547093],"domain_scores_gemma":[0.9990124,0.00033106806,0.00019935248,0.000119592565,0.00030744416,0.00003010309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031673443,0.000081659186,0.00009838531,0.00013741659,0.000027801327,0.00009348351,0.00022532175,0.00004148909,0.000019776266],"category_scores_gemma":[0.00006123678,0.000062430496,0.000043900924,0.00007023363,0.000018692337,0.00010449772,0.000014871269,0.0001388851,0.0000192859],"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":[0.000057693003,0.000091970374,0.0015184915,0.000045048262,0.00033329485,0.00000714894,0.0009849734,0.7863392,0.00671671,0.0030184574,0.0003879042,0.20049909],"study_design_scores_gemma":[0.00043408445,0.000055958335,0.008974889,0.00016601688,0.00001193647,0.000032102667,0.00015782283,0.98806757,0.00062599534,0.00014831308,0.0012566331,0.00006865718],"about_ca_topic_score_codex":0.0000021535334,"about_ca_topic_score_gemma":3.3091425e-7,"teacher_disagreement_score":0.7240766,"about_ca_system_score_codex":0.00007349773,"about_ca_system_score_gemma":0.000022410999,"threshold_uncertainty_score":0.25458416},"labels":[],"label_agreement":null},{"id":"W2960274683","doi":"","title":"Indoor Robot Localisation with Active RFID","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Radio-frequency identification; Robot; Computer science; Tracking (education); Real-time computing; Mobile robot; Identification (biology); Embedded system; Artificial intelligence; Computer security","score_opus":0.007732986618363627,"score_gpt":0.21529338656566135,"score_spread":0.20756039994729772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2960274683","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":[0.24951738,0.00016393134,0.74857104,0.00036378397,0.0009524601,0.000064032,0.000003904139,0.0000407465,0.00032272603],"genre_scores_gemma":[0.9874847,0.0001081962,0.011957577,0.000054844815,0.0003500936,8.4827855e-7,0.00001745188,0.000016371525,0.000009905877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992246,0.000018676354,0.00027502168,0.00004614888,0.00032483897,0.00011071005],"domain_scores_gemma":[0.9993728,0.00003943592,0.00015524655,0.000045794506,0.0003094577,0.00007729447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013853972,0.00009489969,0.000114537346,0.00016996442,0.00002961919,0.000063970765,0.00007981935,0.000051884617,0.000014079372],"category_scores_gemma":[0.000026205582,0.00007806192,0.000029476822,0.0000808737,0.000023630691,0.0005535719,0.000009392078,0.00010510703,0.00000380403],"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":[0.000029569266,0.000040712013,0.003474565,0.000012934644,0.00012013058,0.000004476583,0.00041651164,0.97071075,0.0013358409,0.0028383492,0.00012290415,0.020893244],"study_design_scores_gemma":[0.0011984154,0.00014203525,0.068576254,0.000163206,0.00007857468,0.00028915322,0.00026515746,0.91897225,0.008746062,0.0004954681,0.0008210683,0.00025236412],"about_ca_topic_score_codex":0.0000027681251,"about_ca_topic_score_gemma":0.0000019137503,"teacher_disagreement_score":0.7379673,"about_ca_system_score_codex":0.0000928637,"about_ca_system_score_gemma":0.000017967452,"threshold_uncertainty_score":0.31832728},"labels":[],"label_agreement":null},{"id":"W2963052345","doi":"","title":"Performance Evaluation of Nanocoolants for Automotive Cooling Application","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Nanofluid Flow and Heat Transfer","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Nanofluid; Thermal conductivity; Materials science; Coolant; Heat transfer; Composite material; Heat transfer coefficient; Radiator (engine cooling); Zeta potential; Viscosity; Thermodynamics; Nanoparticle; Nanotechnology; Mechanical engineering","score_opus":0.012611555624245837,"score_gpt":0.25902642264098735,"score_spread":0.2464148670167415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963052345","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":[0.8750901,0.00013705743,0.12366575,0.000056354595,0.0006106551,0.00019620346,0.000007164797,0.000013306869,0.00022336052],"genre_scores_gemma":[0.9966288,0.00013404545,0.0031087522,0.000009469483,0.00009039745,0.0000042385873,0.000009335786,0.000008051431,0.000006906335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991853,0.000009351294,0.0002964096,0.000044772096,0.00041121885,0.000052917985],"domain_scores_gemma":[0.998463,0.00003928536,0.000084836276,0.000038009774,0.0013559981,0.00001887658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005211191,0.00005439276,0.00010545778,0.00012504442,0.000012432949,0.000015784743,0.00007836235,0.00003899275,0.000010580197],"category_scores_gemma":[0.00002567808,0.00005069407,0.00003728321,0.000039951643,0.000007641295,0.00021725557,0.0000043042714,0.00004459129,0.000002442958],"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":[0.0000449886,0.000028389093,0.0029510963,0.0000829991,0.00012031605,1.3831777e-7,0.00028488142,0.8611233,0.052566312,0.0010556699,0.00007192329,0.08166998],"study_design_scores_gemma":[0.0008608742,0.00006254004,0.020687409,0.00010529997,0.00004282793,0.000011434331,0.00002422603,0.9628496,0.014977632,0.00020530568,0.00012161695,0.000051242816],"about_ca_topic_score_codex":7.3175545e-7,"about_ca_topic_score_gemma":6.580165e-7,"teacher_disagreement_score":0.121538654,"about_ca_system_score_codex":0.00007473196,"about_ca_system_score_gemma":0.00003782198,"threshold_uncertainty_score":0.20672442},"labels":[],"label_agreement":null},{"id":"W2963594636","doi":"","title":"Design and Fabrication of Automatic Paper Recycling Machine","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Spare part; Dirt; Task (project management); Computer science; Schematic; Manufacturing engineering; Engineering; Mechanical engineering; Systems engineering; Electrical engineering","score_opus":0.00937278498597074,"score_gpt":0.22317562895138895,"score_spread":0.2138028439654182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963594636","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":[0.780936,0.00031683026,0.21781868,0.00022772686,0.00045488402,0.00008684829,0.000001982601,0.000028941538,0.00012812865],"genre_scores_gemma":[0.96309704,0.00043713735,0.03637868,0.000018452842,0.000046953315,5.4368445e-7,0.0000050846224,0.000009538195,0.0000065920112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934286,0.000022847204,0.0003440032,0.00004630376,0.00019391134,0.00005007785],"domain_scores_gemma":[0.99940574,0.000112958696,0.0001988682,0.00003747826,0.00021803807,0.000026912721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023806434,0.00006263939,0.000120626515,0.00015594295,0.000010042195,0.00003326306,0.00005942316,0.000040741255,0.000024945255],"category_scores_gemma":[0.000037591824,0.00005854702,0.000022202405,0.000047113655,0.000010232466,0.000340926,0.00001114705,0.00007672286,0.00000419026],"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":[0.000025740464,0.0000423241,0.0029141505,0.00017200486,0.00023684558,0.000004990839,0.0005540793,0.6606997,0.089364424,0.00064455305,0.00006259453,0.24527858],"study_design_scores_gemma":[0.00042314152,0.000045790457,0.014677931,0.00018635909,0.000023963135,0.00009880066,0.000024270872,0.98010874,0.0033042023,0.0010111656,0.000034972396,0.00006065523],"about_ca_topic_score_codex":0.0000017705663,"about_ca_topic_score_gemma":2.783198e-7,"teacher_disagreement_score":0.31940904,"about_ca_system_score_codex":0.00003141372,"about_ca_system_score_gemma":0.000009367481,"threshold_uncertainty_score":0.23874782},"labels":[],"label_agreement":null},{"id":"W2964039265","doi":"","title":"Design and Analysis of Automatic Motor Blower","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"IoT-based Control Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Automotive engineering; Battery (electricity); Alternator; HVAC; Ventilation (architecture); Power (physics); Air conditioning; Engineering; Computer science; Mechanical engineering","score_opus":0.008091067684625114,"score_gpt":0.23513214082290212,"score_spread":0.227041073138277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964039265","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":[0.2506562,0.000117073076,0.74808383,0.0005525335,0.00046704352,0.000073443975,0.000001170545,0.000011129567,0.000037613627],"genre_scores_gemma":[0.924585,0.000016492184,0.0752777,0.00005403134,0.000030581134,5.885582e-7,9.461106e-7,0.0000030428505,0.00003162718],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889696,0.00006735436,0.00044398304,0.000092419534,0.00043261104,0.00006664909],"domain_scores_gemma":[0.99868655,0.00019675895,0.00056979456,0.000107846216,0.00039792265,0.000041123043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000542327,0.00006877705,0.00023268437,0.0005196264,0.000015490528,0.00012506754,0.0003090423,0.000034507055,0.000008715534],"category_scores_gemma":[0.000045716697,0.000057179877,0.00007259866,0.00019618506,0.000015978902,0.000409531,0.000048167985,0.000054067827,0.000002261082],"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":[0.000083579165,0.00027884604,0.028854882,0.00010939693,0.0057148137,0.000056552533,0.0023793208,0.7228891,0.045838892,0.075082995,0.00016784233,0.11854378],"study_design_scores_gemma":[0.00043830532,0.00011115064,0.03745685,0.000058272846,0.000105684,0.00003595239,0.000010668952,0.96089137,0.00026723303,0.00055335014,0.000017796065,0.000053371434],"about_ca_topic_score_codex":0.000005816503,"about_ca_topic_score_gemma":4.5859233e-7,"teacher_disagreement_score":0.6739288,"about_ca_system_score_codex":0.000035556677,"about_ca_system_score_gemma":0.00004803753,"threshold_uncertainty_score":0.23317277},"labels":[],"label_agreement":null},{"id":"W2970037498","doi":"10.2316/j.2019.206-0330","title":"ANALYSIS OF POWER SOURCE OF MULTIROTOR UAVs","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Multirotor; Power (physics); Computer science; Aerospace engineering; Physics; Engineering","score_opus":0.0028391691723054324,"score_gpt":0.19710682014166264,"score_spread":0.19426765096935722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970037498","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":[0.81893843,0.00018104802,0.18021137,0.000040498715,0.00047309863,0.00003366962,0.000003885884,0.000011707478,0.000106287414],"genre_scores_gemma":[0.9986156,0.000024560903,0.0012694459,0.0000028372679,0.00003144779,3.02696e-7,0.0000019328888,0.000006230797,0.000047633923],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993774,0.0000071984,0.00032279338,0.000031444906,0.00021949178,0.00004164284],"domain_scores_gemma":[0.9995027,0.000041296615,0.00019389953,0.000049240018,0.00019135288,0.000021508878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012188099,0.000050969895,0.00019824946,0.00024205299,0.0000034766153,0.000011211189,0.00008570364,0.00003172012,0.000015480737],"category_scores_gemma":[0.00001840557,0.00004540831,0.00009104598,0.00009688937,0.000007449516,0.0000820413,0.00000794153,0.000048846512,0.0000010521501],"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":[0.000006452919,0.000011528431,0.009518977,0.000019212746,0.00075812626,5.482898e-7,0.00024891496,0.97406846,0.013510352,0.00026432207,0.000014337013,0.0015787845],"study_design_scores_gemma":[0.00035431248,0.000040267023,0.052307077,0.00007469011,0.00010712699,0.0000057257375,0.0000822453,0.94600725,0.00081774226,0.000011462566,0.00014506216,0.000047039757],"about_ca_topic_score_codex":0.0000065634727,"about_ca_topic_score_gemma":0.0000010015744,"teacher_disagreement_score":0.17967717,"about_ca_system_score_codex":0.000021429556,"about_ca_system_score_gemma":0.000006267437,"threshold_uncertainty_score":0.18516971},"labels":[],"label_agreement":null},{"id":"W2970529936","doi":"10.2316/j.2019.206-0302","title":"AN OVERVIEW OF ASSISTIVE DEVICES FOR BLIND AND VISUALLY IMPAIRED PEOPLE","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Urban and spatial planning","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Science and Technology Commission of Shanghai Municipality; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Visually impaired; Computer science; Human–computer interaction; Physical medicine and rehabilitation; Psychology; Medicine","score_opus":0.02776648503159789,"score_gpt":0.31580673568255785,"score_spread":0.28804025065095995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970529936","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":[0.9916461,0.00011461833,0.0077087856,0.00022007433,0.00014779973,0.00006671236,0.0000057727298,0.0000026276055,0.00008750129],"genre_scores_gemma":[0.9934307,0.00004855188,0.006404846,0.000052785657,0.000033235574,3.6178952e-7,0.0000056749436,0.0000030479425,0.00002082759],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995053,0.000013184786,0.00019425718,0.000056293058,0.0001896727,0.000041282416],"domain_scores_gemma":[0.99957097,0.00005447013,0.00025881064,0.000025741494,0.000057245798,0.000032780896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018200239,0.000042358515,0.00009397361,0.000040038787,0.000017649447,0.00003736059,0.00007731102,0.000022298942,0.000050966333],"category_scores_gemma":[0.000020958321,0.000035098947,0.00002391815,0.000027132957,0.000016698965,0.00029919192,0.0000220629,0.000028951208,0.0000015948816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020791496,0.00017015151,0.89702016,0.000060455495,0.000114777984,0.000002823295,0.0012556273,0.042830236,0.019744754,0.0017837966,0.00021645329,0.03659287],"study_design_scores_gemma":[0.00056969794,0.00025842988,0.8367405,0.000063526546,0.00001661787,0.000016923266,0.000085908025,0.1615037,0.000215638,0.00035663036,0.00012620269,0.000046242],"about_ca_topic_score_codex":0.00002844442,"about_ca_topic_score_gemma":0.000044364366,"teacher_disagreement_score":0.11867347,"about_ca_system_score_codex":0.000022188791,"about_ca_system_score_gemma":0.000009092641,"threshold_uncertainty_score":0.14312935},"labels":[],"label_agreement":null},{"id":"W2997724026","doi":"10.2316/j.2019.206-0078","title":"MOTION PLANNING FOR AN OUTDOOR MOBILE ROBOT ON A PROBABILISTIC COSTMAP","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Probabilistic logic; Mobile robot; Computer science; Motion planning; Motion (physics); Artificial intelligence; Computer vision; Human–computer interaction; Robot","score_opus":0.015730600099138837,"score_gpt":0.27584252589798136,"score_spread":0.2601119257988425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997724026","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":[0.11104092,0.000048376103,0.8873479,0.000055409997,0.0010999282,0.00019029695,0.0000081268345,0.00005144516,0.00015760267],"genre_scores_gemma":[0.9651446,0.000023495768,0.034566443,0.000025382074,0.00015931403,0.000005474367,0.000033511624,0.000014611011,0.000027179593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944437,0.00000876667,0.00023983137,0.000071773895,0.00016231586,0.00007296382],"domain_scores_gemma":[0.99950904,0.000073359435,0.00012975035,0.000052630487,0.00019811526,0.000037107857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121881065,0.000079012905,0.00010366098,0.00012285131,0.000023337256,0.00006358334,0.00008420569,0.00004260517,0.0000049195723],"category_scores_gemma":[0.000040773717,0.0000728509,0.000030323752,0.000022880344,0.0000087456565,0.0002401194,0.0000067452975,0.000079806734,0.0000025254226],"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":[0.000027584276,0.000028499779,0.00008331982,0.000026450916,0.000025611125,9.800783e-7,0.00014114816,0.9858742,0.0004695918,0.0017474509,0.000035748384,0.011539464],"study_design_scores_gemma":[0.00054943195,0.00032012735,0.0012887444,0.000091845584,0.00001405644,0.000019074929,0.00005684796,0.9933454,0.0007129528,0.0032766834,0.00023573535,0.00008911528],"about_ca_topic_score_codex":4.982805e-7,"about_ca_topic_score_gemma":3.3806631e-7,"teacher_disagreement_score":0.8541037,"about_ca_system_score_codex":0.00007236489,"about_ca_system_score_gemma":0.000008581959,"threshold_uncertainty_score":0.29707733},"labels":[],"label_agreement":null},{"id":"W3001318351","doi":"10.5555/1739839.1739841","title":"An accurate and efficient skew estimation technique for South Indian documents","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Skew; Computer science; Estimation; Cluster analysis; Boundary (topology); Optical character recognition; Character (mathematics); Pattern recognition (psychology); Artificial intelligence; k-nearest neighbors algorithm; Mathematics; Image (mathematics); Telecommunications; Engineering; Geometry","score_opus":0.011968992800398818,"score_gpt":0.3095412602110955,"score_spread":0.2975722674106967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001318351","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":[0.05725451,0.000022649047,0.94177884,0.00046591013,0.0002190871,0.00018557055,0.0000035771754,0.000042311152,0.000027537675],"genre_scores_gemma":[0.6328122,0.000011486346,0.3670492,0.00006588863,0.000046614692,0.0000033585607,0.0000044244393,0.0000036392853,0.0000031657255],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991037,0.000022703827,0.00037811254,0.000114258284,0.0002838723,0.00009730524],"domain_scores_gemma":[0.99889207,0.00007582965,0.000404147,0.00007245062,0.0004755567,0.00007996838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092248403,0.000079141195,0.000097961056,0.00034960415,0.00006246353,0.00028575878,0.00026090996,0.000055963697,0.0000016518194],"category_scores_gemma":[0.00008083899,0.00007142005,0.00003103822,0.000079727775,0.000023810033,0.0006525171,0.000041691535,0.00007677409,6.8955666e-7],"study_design_candidate":"design_other","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":[0.00007737277,0.00029919323,0.00096760545,0.000067953086,0.00012347898,0.00006063781,0.0037712445,0.012104141,0.0255068,0.06242492,0.000113196096,0.89448345],"study_design_scores_gemma":[0.0013678519,0.0006619721,0.012582654,0.0003514115,0.000028813141,0.0007639004,0.00012735366,0.8299674,0.09512147,0.058565117,0.00015073617,0.00031132085],"about_ca_topic_score_codex":0.000002358092,"about_ca_topic_score_gemma":0.0000011037738,"teacher_disagreement_score":0.89417213,"about_ca_system_score_codex":0.000051258055,"about_ca_system_score_gemma":0.0000353651,"threshold_uncertainty_score":0.29124254},"labels":[],"label_agreement":null},{"id":"W3005751031","doi":"10.2316/j.2020.206-0077","title":"STABILITY AND PERFORMANCE ANALYSIS OF A PAYLOAD-MANIPULATING ROBOT WITHOUT ADAPTIVE CONTROL","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Payload (computing); Computer science; Stability (learning theory); Robot; Control theory (sociology); Adaptive control; Control (management); Control engineering; Engineering; Artificial intelligence; Computer network","score_opus":0.013391958497711975,"score_gpt":0.22016593796307668,"score_spread":0.20677397946536472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005751031","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":[0.6737784,0.00017628634,0.32558715,0.00025198594,0.00009074552,0.000045721426,0.000009426019,0.000014261143,0.000046013443],"genre_scores_gemma":[0.9952392,0.00010550464,0.004551553,0.000035130794,0.000058064776,6.9778184e-7,0.000003411236,0.000005853281,6.052251e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923384,0.00001654832,0.0003980495,0.000065815715,0.00022389047,0.000061852],"domain_scores_gemma":[0.9993538,0.00007336581,0.00021344995,0.000035986362,0.0002643027,0.000059093418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016286566,0.000078422265,0.00025389978,0.00013033536,0.000018046638,0.000032960048,0.000079760015,0.00003102238,0.000007723015],"category_scores_gemma":[0.000049136514,0.00007006403,0.00006672795,0.000105817955,0.000022997407,0.00021499595,0.000018138908,0.00009112518,1.8952448e-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":[0.000058265883,0.000011641731,0.057827175,0.000021794423,0.0007289747,0.0000017579536,0.00030430572,0.92857313,0.002499614,0.00020372195,0.0000013794971,0.00976821],"study_design_scores_gemma":[0.0005218112,0.000084401225,0.18992585,0.000027779193,0.0002188767,0.0000051702614,0.000050787752,0.8089735,0.00010365774,0.00003503099,0.0000019778183,0.000051172752],"about_ca_topic_score_codex":0.0000042809957,"about_ca_topic_score_gemma":0.0000055072333,"teacher_disagreement_score":0.32146075,"about_ca_system_score_codex":0.00002747858,"about_ca_system_score_gemma":0.000012105669,"threshold_uncertainty_score":0.28571284},"labels":[],"label_agreement":null},{"id":"W3005999075","doi":"10.2316/j.2020.206-0151","title":"CENTRAL PATTERN GENERATOR BASED MOTION CONTROL OF HOPPING ROBOT FOR GROUND LEVEL ACCLIMATIZATION","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Central pattern generator; Robot; Generator (circuit theory); Jumping; Computer science; Motion control; Control theory (sociology); Control (management); Artificial intelligence; Acoustics; Physics; Geology; Rhythm; Power (physics)","score_opus":0.024332794879734717,"score_gpt":0.232616770011273,"score_spread":0.2082839751315383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005999075","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":[0.016271079,0.00008228086,0.98004836,0.0027471902,0.0006392821,0.0001431382,0.000028810855,0.00002832442,0.000011543326],"genre_scores_gemma":[0.98470193,0.000030761275,0.014540682,0.00033208844,0.00034776493,0.0000027757299,0.000027329286,0.000014839969,0.0000018107639],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999052,0.000023577455,0.0005020805,0.00006850456,0.0002564096,0.000097437995],"domain_scores_gemma":[0.9991498,0.00006386389,0.0002761517,0.000036829548,0.00039832375,0.00007503112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013183286,0.00009579962,0.00018441926,0.00010468871,0.000025535604,0.00006988519,0.00011573443,0.00005056181,0.000015864518],"category_scores_gemma":[0.000080795646,0.00009248247,0.0000875345,0.000054703825,0.000013121313,0.00026111983,0.000006612422,0.00006870388,7.0299916e-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":[0.00002478034,0.000025669833,0.0010651578,0.00006038468,0.000107050415,0.0000015100983,0.0001467997,0.9570141,0.012846407,0.0005836113,0.00008065364,0.028043915],"study_design_scores_gemma":[0.002140177,0.000073003685,0.010568255,0.00006477679,0.000046238787,0.000006880047,0.000030742576,0.98530734,0.0015216385,0.00010766346,0.000053271866,0.00008002531],"about_ca_topic_score_codex":0.0000015235134,"about_ca_topic_score_gemma":0.000001050246,"teacher_disagreement_score":0.9684309,"about_ca_system_score_codex":0.00005618139,"about_ca_system_score_gemma":0.000026872478,"threshold_uncertainty_score":0.37713256},"labels":[],"label_agreement":null},{"id":"W3006385983","doi":"10.2316/j.2020.206-0214","title":"NONLINEAR FLEXIBLE LINK ROBOT JOINT-FAULT ESTIMATION USING TS FUZZY OBSERVERS","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Link (geometry); Joint (building); Nonlinear system; Computer science; Fuzzy logic; Control theory (sociology); Fault (geology); Robot; Artificial intelligence; Engineering; Control (management); Structural engineering; Physics","score_opus":0.029799540310166347,"score_gpt":0.2603002472066884,"score_spread":0.23050070689652202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006385983","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":[0.27771866,0.00046619965,0.7124395,0.0055199983,0.0031334637,0.000153198,0.000011523791,0.00021950646,0.00033798852],"genre_scores_gemma":[0.9711338,0.000074165815,0.027964948,0.00014652537,0.0006445493,6.341094e-7,0.000007333683,0.000016377164,0.000011639133],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901986,0.000020126332,0.00047254298,0.000072285744,0.00032920518,0.00008600332],"domain_scores_gemma":[0.9993928,0.000022156171,0.00020698333,0.000042093703,0.0002434744,0.00009249358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000108954504,0.00010130965,0.00016604477,0.00012479728,0.00003713696,0.00013307048,0.00010939683,0.00006348394,0.000011141773],"category_scores_gemma":[0.000078971534,0.000098263634,0.00007365304,0.00009691373,0.000012384181,0.0003853579,0.000015767393,0.00014620482,0.000009726833],"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":[0.00001321937,0.000008079051,0.00008621236,0.000026949243,0.00008805026,0.000009085366,0.00017577207,0.96736866,0.016150782,0.00017119604,0.00009585719,0.01580613],"study_design_scores_gemma":[0.0006177486,0.000056014163,0.00083321915,0.000094546755,0.000025929226,0.00009331008,0.00006323725,0.99497116,0.002411075,0.00014561343,0.00059386744,0.000094263014],"about_ca_topic_score_codex":0.0000064569426,"about_ca_topic_score_gemma":0.0000011732099,"teacher_disagreement_score":0.69341516,"about_ca_system_score_codex":0.000082960425,"about_ca_system_score_gemma":0.000026511127,"threshold_uncertainty_score":0.40070745},"labels":[],"label_agreement":null},{"id":"W3006525715","doi":"10.2316/j.2020.206-0221","title":"EAGLE-VISION-INSPIRED VISUAL MEASUREMENT ALGORITHM FOR UAV’S AUTONOMOUS LANDING","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Eagle; Computer vision; Computer science; Artificial intelligence; Geology","score_opus":0.034473471863695086,"score_gpt":0.2958516896118185,"score_spread":0.2613782177481234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006525715","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00100881,0.000109289096,0.9891994,0.008225639,0.0012553631,0.00010490889,0.000004929196,0.000055613138,0.000036018344],"genre_scores_gemma":[0.29670995,0.000019802357,0.7022978,0.00043330222,0.0005125751,0.0000022988322,0.0000047825997,0.000009257115,0.000010236135],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998408,0.000036065834,0.0004920936,0.00016847983,0.0007600022,0.00013531979],"domain_scores_gemma":[0.9984889,0.00009189455,0.00046168666,0.00006570342,0.0007590201,0.00013281798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055867847,0.00011418242,0.0001870745,0.00014672415,0.00007509421,0.00029541482,0.0004840588,0.000049125607,0.0000023790515],"category_scores_gemma":[0.00020851077,0.00010236079,0.00008474945,0.00009997496,0.000018431378,0.0005608539,0.00009602799,0.00011113834,0.0000050567955],"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":[0.00002612648,0.00014499974,0.00037580312,0.000026826003,0.00027427316,0.00008761153,0.0014028348,0.10123539,0.0029918829,0.0036780895,0.0014624622,0.8882937],"study_design_scores_gemma":[0.0008842788,0.00041409928,0.0019416834,0.00009616505,0.000016968246,0.00010163071,0.000025208159,0.9946056,0.0004369205,0.0006605865,0.00070564466,0.00011120764],"about_ca_topic_score_codex":0.0000023605148,"about_ca_topic_score_gemma":1.4275055e-7,"teacher_disagreement_score":0.8933702,"about_ca_system_score_codex":0.00011464532,"about_ca_system_score_gemma":0.000121689336,"threshold_uncertainty_score":0.4174152},"labels":[],"label_agreement":null},{"id":"W3013132433","doi":"10.2316/j.2020.206-0273","title":"PATTERN MATCHING USING ALL-DIRECTION SYMMETRIC STRUCTURE WITH IMAGE VARIATIONS","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Image (mathematics); Computer science; Artificial intelligence; Pattern recognition (psychology); Image matching; Mathematics; Computer vision; Statistics","score_opus":0.018551188493183334,"score_gpt":0.28974874183568894,"score_spread":0.2711975533425056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013132433","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":[0.01655415,0.000058161957,0.98018074,0.002882743,0.00019472811,0.000046508154,0.000003237828,0.00005033482,0.000029415763],"genre_scores_gemma":[0.6079343,0.000040044008,0.3915855,0.0003150106,0.00011739648,1.4899604e-7,0.0000019573843,0.0000044812973,0.0000011754968],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919134,0.000026810672,0.0002576138,0.0001055679,0.00034796845,0.00007068524],"domain_scores_gemma":[0.9990292,0.000044318524,0.00037581866,0.00005440568,0.0004387492,0.00005749608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009491562,0.000079304664,0.0001050023,0.0001765659,0.00004893686,0.00026396412,0.0002574287,0.000029975034,0.0000036595757],"category_scores_gemma":[0.000064084954,0.00006348284,0.000028541452,0.00022788066,0.000012753285,0.0013245319,0.0000617454,0.00013295638,5.700436e-7],"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":[0.00009101494,0.00017053647,0.0028233426,0.000087812514,0.00066787243,0.00031544166,0.0045440537,0.10407287,0.14763382,0.052439958,0.00030650935,0.6868468],"study_design_scores_gemma":[0.00067114376,0.00028336456,0.006047736,0.00012919321,0.000047370962,0.00065879937,0.000050025174,0.96262956,0.012189465,0.016856046,0.00022979455,0.00020750199],"about_ca_topic_score_codex":0.0000070767073,"about_ca_topic_score_gemma":7.025238e-7,"teacher_disagreement_score":0.8585567,"about_ca_system_score_codex":0.000052771957,"about_ca_system_score_gemma":0.000037070873,"threshold_uncertainty_score":0.25887552},"labels":[],"label_agreement":null},{"id":"W3021224865","doi":"10.2316/j.2020.206-0347","title":"INVERSE KINEMATICS AND TRAJECTORY PLANNING FOR A HYPER-REDUNDANT BIONIC TRUNK-LIKE ROBOT","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inverse kinematics; Trajectory; Kinematics; Trunk; Computer science; Robot; Inverse; Control theory (sociology); Artificial intelligence; Mathematics; Physics; Classical mechanics; Geometry; Biology","score_opus":0.03690181996563711,"score_gpt":0.2818164516539834,"score_spread":0.2449146316883463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021224865","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031147981,0.00022819688,0.9609936,0.0066180932,0.00085565035,0.000096437434,0.000004202354,0.000037117647,0.000018742789],"genre_scores_gemma":[0.27065274,0.00004153016,0.728368,0.0006468463,0.0002618953,0.0000017159791,0.0000051539446,0.000009393943,0.000012719824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890965,0.00003181062,0.00043458838,0.0001508644,0.00035270292,0.000120360586],"domain_scores_gemma":[0.9989399,0.00016911382,0.0004109467,0.00006978328,0.00028089577,0.00012940165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027967396,0.00011426528,0.00019426756,0.00015535182,0.00006704139,0.0002288228,0.00035770558,0.000050722174,0.0000014895746],"category_scores_gemma":[0.00018614397,0.00010209706,0.000057857855,0.00009403565,0.00003528572,0.00047086747,0.000083063474,0.00012569435,0.000001368911],"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":[0.000048215043,0.00008135921,0.001118001,0.00009761157,0.00021386087,0.00009394697,0.0057034553,0.95138955,0.00560713,0.005248335,0.0016786674,0.028719863],"study_design_scores_gemma":[0.0008454777,0.00022666142,0.0031078095,0.00014478348,0.000025113197,0.00029703174,0.0001121085,0.99375397,0.0001777335,0.0008669335,0.00032773023,0.0001146661],"about_ca_topic_score_codex":0.0000017693131,"about_ca_topic_score_gemma":2.1172721e-7,"teacher_disagreement_score":0.23950477,"about_ca_system_score_codex":0.00003780489,"about_ca_system_score_gemma":0.00008459228,"threshold_uncertainty_score":0.41633973},"labels":[],"label_agreement":null},{"id":"W3022684642","doi":"10.2316/j.2020.206-0281","title":"CLOSED-FORM TORSIONAL COMPLIANCE OF TWO-AXIS FLEXURE HINGES","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hinge; Structural engineering; Compliance (psychology); Variable (mathematics); Engineering; Mathematics; Mathematical analysis; Psychology","score_opus":0.014679533555809617,"score_gpt":0.24512373775405424,"score_spread":0.23044420419824463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022684642","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":[0.4091357,0.0011435248,0.5841468,0.0039162305,0.0009210374,0.00007262809,0.000018646575,0.000050968498,0.0005944439],"genre_scores_gemma":[0.99445385,0.00012304257,0.0049858214,0.00013014328,0.00029018254,3.32706e-7,0.0000034167642,0.0000068695135,0.0000063506973],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993196,0.000006514026,0.00029589623,0.000043178134,0.00027378087,0.00006103081],"domain_scores_gemma":[0.999518,0.000040031457,0.00015606228,0.000026397249,0.00020501646,0.000054527598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007155063,0.000066709305,0.00013506698,0.00006095613,0.000014969166,0.0000275915,0.00013743015,0.000028150613,0.000019936499],"category_scores_gemma":[0.00003615056,0.00005855726,0.00005084711,0.000054181095,0.0000131832,0.00017575614,0.000014188537,0.00010180131,0.0000019601503],"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":[0.00009170078,0.00007051346,0.0032695027,0.00010023689,0.000499751,0.00003086191,0.0011095547,0.3515302,0.015936088,0.014341337,0.0027751408,0.6102451],"study_design_scores_gemma":[0.0006884037,0.0000872675,0.0034591376,0.000074652846,0.000019563326,0.000031902426,0.000026703854,0.9920638,0.001051186,0.0016489922,0.000774393,0.000073994066],"about_ca_topic_score_codex":0.0000017348567,"about_ca_topic_score_gemma":5.5814405e-7,"teacher_disagreement_score":0.6405336,"about_ca_system_score_codex":0.00003313915,"about_ca_system_score_gemma":0.000020500845,"threshold_uncertainty_score":0.23878957},"labels":[],"label_agreement":null},{"id":"W3022695419","doi":"10.2316/journal.206.2006.2.206-2798","title":"AN AGENT-BASED APPROACH TO INTRODUCTORY ROBOTICS USING ROBOTIC SOCCER","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Robotics; Artificial intelligence; Computer science; Robot","score_opus":0.022146395300181185,"score_gpt":0.279397791447362,"score_spread":0.2572513961471808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022695419","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0117437085,0.00007130071,0.9848418,0.0015395764,0.0015698704,0.000091670656,0.0000017388668,0.000055855948,0.000084442116],"genre_scores_gemma":[0.40766993,0.0000018198854,0.5916436,0.00018929089,0.00046325146,6.063653e-7,0.000007658433,0.0000100058905,0.000013891676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998085,0.00009379226,0.0005940465,0.00025237264,0.0007667087,0.0002080666],"domain_scores_gemma":[0.9984434,0.00006284946,0.00046495313,0.00023631101,0.0006511701,0.00014128452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052140234,0.00016826809,0.00023062,0.0004813896,0.000092150985,0.0004401195,0.00081832753,0.00007238708,0.000002439007],"category_scores_gemma":[0.00006315086,0.0001585697,0.00007345173,0.00023048681,0.000037533257,0.00073153595,0.00008147521,0.00017194467,0.000005546815],"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":[0.0000061028986,0.000194459,0.0008079913,0.0000075712755,0.00003119617,0.000025173167,0.00011836979,0.9838836,0.0020607489,0.009756674,0.0002030767,0.0029050354],"study_design_scores_gemma":[0.00043004582,0.00010214146,0.007742625,0.000059828122,0.000024761852,0.00022577557,0.000019986303,0.98954314,0.0003047969,0.001333572,0.000040562914,0.0001727929],"about_ca_topic_score_codex":0.00002565652,"about_ca_topic_score_gemma":6.3549146e-7,"teacher_disagreement_score":0.39592624,"about_ca_system_score_codex":0.0001872225,"about_ca_system_score_gemma":0.00015389117,"threshold_uncertainty_score":0.6466285},"labels":[],"label_agreement":null},{"id":"W3026156744","doi":"","title":"Editorial on Anomalies Robotics: A Future Vision","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robotics; Artificial intelligence; Task (project management); Robot; Computer science; Computer vision; Engineering; Systems engineering","score_opus":0.004513872703106301,"score_gpt":0.23145859087162127,"score_spread":0.22694471816851497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026156744","genre_codex":"editorial","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":[0.36152127,0.0008401556,0.1956319,0.003833651,0.4349704,0.00029241567,0.000017841307,0.00016936297,0.0027229758],"genre_scores_gemma":[0.9711201,0.00039912842,0.0052358042,0.000055378692,0.023088196,4.3866592e-7,0.0000055116384,0.00001566527,0.00007974834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991159,0.000012589407,0.00029033658,0.0000688747,0.00043174115,0.00008057226],"domain_scores_gemma":[0.9994942,0.000037066184,0.000113341936,0.000067249544,0.00024447666,0.000043691252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014538753,0.00009484283,0.00012721459,0.00014446533,0.000019779685,0.00010971594,0.00015505141,0.00007423116,0.000040173367],"category_scores_gemma":[0.000016119184,0.000078464946,0.000052578664,0.000041222556,0.000011296844,0.00024363396,0.000017584867,0.00015904945,0.000029278415],"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":[0.00002559119,0.000027830592,0.00031578512,0.000018512008,0.00006692959,0.000005885123,0.00014180361,0.96573824,0.0014206626,0.007175125,0.007631317,0.017432295],"study_design_scores_gemma":[0.001342249,0.0007418019,0.0073531554,0.00047283169,0.000037870086,0.00016331479,0.00022849221,0.91192377,0.0025805344,0.003927309,0.07079311,0.00043554802],"about_ca_topic_score_codex":0.0000010206084,"about_ca_topic_score_gemma":7.741718e-7,"teacher_disagreement_score":0.6095988,"about_ca_system_score_codex":0.000052152893,"about_ca_system_score_gemma":0.000014126842,"threshold_uncertainty_score":0.3199708},"labels":[],"label_agreement":null},{"id":"W3035205004","doi":"10.2316/j.2020.206-0316","title":"ORIENTATION OPTIMIZATION OF CABLE-DRIVEN PARALLEL MANIPULATOR FOR CLEANING THE DEEP SEA FISHING GROUND","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Orientation (vector space); Fishing; Marine engineering; Environmental science; Computer science; Fishery; Engineering; Mathematics; Biology; Geometry","score_opus":0.029775508157280885,"score_gpt":0.27285951448124535,"score_spread":0.24308400632396446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035205004","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036289913,0.000051276118,0.98953146,0.0060820007,0.00056183396,0.00010489855,0.0000026838138,0.000018247076,0.000018609537],"genre_scores_gemma":[0.3808114,0.000019792815,0.6187998,0.00018984324,0.00016107244,0.0000012863463,0.000008928455,0.000005167679,0.00000272835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895424,0.000040170973,0.00042570897,0.00010646675,0.00039211207,0.00008130379],"domain_scores_gemma":[0.99855405,0.00017639704,0.000638003,0.000066727844,0.0005158311,0.00004896574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002824222,0.00007374886,0.00012369856,0.000076819815,0.00007497888,0.00019759609,0.0004329153,0.000035266068,0.0000018692622],"category_scores_gemma":[0.00020622584,0.00005888115,0.000053466556,0.000109915585,0.000019874999,0.00074424775,0.00006257364,0.000085451466,4.5350572e-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":[0.000013793174,0.000013271771,0.00068202155,0.000011975022,0.000048583406,0.0000038371886,0.0014042157,0.9873338,0.000097764365,0.005486663,0.00009772584,0.0048063453],"study_design_scores_gemma":[0.0004991589,0.00010962125,0.003569191,0.00005921583,0.000019843566,0.000045851375,0.00013088765,0.9948056,0.000057744848,0.00061399327,0.000030433232,0.000058478803],"about_ca_topic_score_codex":0.0000075235453,"about_ca_topic_score_gemma":5.510121e-7,"teacher_disagreement_score":0.3771824,"about_ca_system_score_codex":0.000040762327,"about_ca_system_score_gemma":0.000048038168,"threshold_uncertainty_score":0.24011037},"labels":[],"label_agreement":null},{"id":"W3035209195","doi":"10.2316/j.2020.206-0334","title":"REGIONALIZED QUALITATIVE SPATIAL REPRESENTATION MODEL AND ITS APPLICATION TO MOBILE ROBOT NAVIGATION","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Representation (politics); Computer science; Mobile robot; Artificial intelligence; Human–computer interaction; Robot; Political science","score_opus":0.028050139473030894,"score_gpt":0.3192029292954646,"score_spread":0.29115278982243376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035209195","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":[0.21304207,0.00021401947,0.7843422,0.0017473901,0.00025125063,0.00027667315,0.000010294408,0.00006523981,0.000050823575],"genre_scores_gemma":[0.9899174,0.00012842879,0.009553224,0.00011847167,0.00019899875,0.000019364647,0.000035865032,0.000018369143,0.000009903236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884415,0.00004253034,0.00051916024,0.00012716709,0.0003818833,0.000085121515],"domain_scores_gemma":[0.9991069,0.00005926213,0.00023411347,0.0000483897,0.00042449796,0.00012686713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020888266,0.00011515294,0.00018623202,0.00012282659,0.000038559112,0.000094945,0.000117635645,0.00006017308,0.000002578559],"category_scores_gemma":[0.000059129507,0.000113806644,0.000040898107,0.00011352395,0.000013070594,0.00032809284,0.00002857472,0.00010201527,0.000006166428],"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":[0.000026484431,0.000011898914,0.000031227282,0.000033670214,0.00006135056,0.00000317091,0.0038019186,0.9547375,0.031116918,0.0014924823,0.00013841943,0.008544953],"study_design_scores_gemma":[0.0004595262,0.000085180385,0.00026540912,0.00008348793,0.000020856141,0.00003385549,0.00039127437,0.99582356,0.0018143578,0.00078729785,0.00012126293,0.00011392561],"about_ca_topic_score_codex":0.000010344851,"about_ca_topic_score_gemma":0.0000016758726,"teacher_disagreement_score":0.7768753,"about_ca_system_score_codex":0.000053013795,"about_ca_system_score_gemma":0.000019478355,"threshold_uncertainty_score":0.46409002},"labels":[],"label_agreement":null},{"id":"W3035305156","doi":"10.2316/j.2020.206-0461","title":"A FAST CONVERGENT CHANNEL SELECTION STRATEGY IN CRSN","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Selection (genetic algorithm); Channel (broadcasting); Computer science; Computer network; Artificial intelligence","score_opus":0.01789962292525086,"score_gpt":0.2623993937467957,"score_spread":0.24449977082154487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035305156","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":[0.07796173,0.00026533485,0.9182569,0.002785758,0.00023372952,0.00007546,0.0000030835333,0.00011388837,0.0003041612],"genre_scores_gemma":[0.99284345,0.00061056315,0.0063725417,0.000082449056,0.000074643576,0.0000014106754,0.0000036476488,0.000008018684,0.000003251876],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999491,0.000013249485,0.00027176514,0.000038109374,0.00013822502,0.00004768688],"domain_scores_gemma":[0.9996778,0.000017585851,0.0001023393,0.000025698744,0.00014092574,0.000035681947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006484014,0.00005402276,0.00008311482,0.00010881114,0.000010392578,0.000030307334,0.000116787,0.000030596166,0.000008825684],"category_scores_gemma":[0.00002275255,0.000055815453,0.00002047857,0.000079100784,0.0000093453245,0.00024582737,0.000016428752,0.00012478564,0.0000015094707],"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":[0.000007676219,0.000012921804,0.00027828274,0.000010289522,0.000021772077,0.0000034527818,0.00022598404,0.97972995,0.0036087437,0.0013413844,0.0001669571,0.014592613],"study_design_scores_gemma":[0.00026093744,0.000047540794,0.0034617085,0.00004815374,0.0000033124697,0.000024924393,0.00007270862,0.99023485,0.004512398,0.0010288156,0.00024513688,0.000059539],"about_ca_topic_score_codex":0.0000020424948,"about_ca_topic_score_gemma":0.0000033191639,"teacher_disagreement_score":0.91488177,"about_ca_system_score_codex":0.000060932303,"about_ca_system_score_gemma":0.000012299568,"threshold_uncertainty_score":0.22760881},"labels":[],"label_agreement":null},{"id":"W3046111609","doi":"","title":"Planning optimal paths for industrial robots using a 3D surface model","year":2003,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Computer science; Surface (topology); Artificial intelligence; Mathematics; Geometry","score_opus":0.07325877953710733,"score_gpt":0.318696359459898,"score_spread":0.24543757992279067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046111609","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052233536,0.00009567107,0.9459025,0.0003208891,0.0012966497,0.000083120955,0.0000037006635,0.000022727232,0.00004117341],"genre_scores_gemma":[0.2456832,0.000005267574,0.7541044,0.000046484653,0.00013283291,5.089834e-7,0.0000018844858,0.000007213511,0.000018230345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876684,0.000047705853,0.00044833054,0.00014486242,0.0004347023,0.00015754491],"domain_scores_gemma":[0.99874586,0.00014069251,0.0004929599,0.00009008809,0.00045165757,0.00007875818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064048154,0.00011447409,0.00017461038,0.0001587627,0.00008454296,0.000253412,0.00037093277,0.00008329914,8.720754e-7],"category_scores_gemma":[0.00024878504,0.00010814226,0.00006364032,0.000092956565,0.000019545085,0.0006704477,0.000050004794,0.00015212451,5.2843245e-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":[0.000009640317,0.000030133464,0.00041485115,0.000002681252,0.000047080022,0.000019400864,0.0003346856,0.9901643,0.0006272567,0.0056158714,0.00008596609,0.0026481769],"study_design_scores_gemma":[0.0009158606,0.0000784195,0.00013226387,0.00011981291,0.000017416694,0.00032371888,0.000024753906,0.9962456,0.00035069668,0.0016366576,0.00004147859,0.00011332538],"about_ca_topic_score_codex":0.0000019156034,"about_ca_topic_score_gemma":4.326153e-8,"teacher_disagreement_score":0.19344966,"about_ca_system_score_codex":0.00009087768,"about_ca_system_score_gemma":0.00020889172,"threshold_uncertainty_score":0.4409913},"labels":[],"label_agreement":null},{"id":"W3083206726","doi":"10.2316/j.2020.206-0050","title":"A PNEUMATIC VARIABLE SERIES ELASTIC ACTUATOR-POWERED TRANSTIBIAL PROSTHESIS","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Actuator; Series (stratigraphy); Variable (mathematics); Control theory (sociology); Computer science; Mathematics; Mathematical analysis; Artificial intelligence; Geology; Control (management)","score_opus":0.00899184718803714,"score_gpt":0.20318678239497462,"score_spread":0.19419493520693748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083206726","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":[0.41038638,0.0006260669,0.5725338,0.012719719,0.0016867337,0.00024528225,0.000019916875,0.00026834704,0.0015137623],"genre_scores_gemma":[0.9905836,0.00024876883,0.0088866735,0.000110342145,0.00015210692,0.0000013544701,0.0000029463997,0.000009723578,0.000004471487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999363,0.000011264284,0.00028105357,0.000050215353,0.00021963354,0.00007484622],"domain_scores_gemma":[0.9996235,0.000042460528,0.00009771752,0.00002484846,0.00015710095,0.0000543792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000063359825,0.00008122271,0.00013211546,0.00009296426,0.000032745287,0.00007275374,0.00009032834,0.000029546061,0.000024055948],"category_scores_gemma":[0.000075039796,0.00007331652,0.000043014672,0.00010135633,0.000017464577,0.00032651282,0.0000079145575,0.000088114706,9.75648e-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":[0.00045190146,0.00023624816,0.002163983,0.0007024791,0.0034450442,0.00007364928,0.011870919,0.4436465,0.1796828,0.029756198,0.005845086,0.3221252],"study_design_scores_gemma":[0.0052992813,0.0014375201,0.082025036,0.0009240067,0.00043496303,0.00064748945,0.0013314141,0.8553538,0.02319043,0.010815685,0.017372118,0.0011682562],"about_ca_topic_score_codex":6.929581e-7,"about_ca_topic_score_gemma":5.6387586e-7,"teacher_disagreement_score":0.5801972,"about_ca_system_score_codex":0.00002397633,"about_ca_system_score_gemma":0.00001844235,"threshold_uncertainty_score":0.2989761},"labels":[],"label_agreement":null},{"id":"W3083570310","doi":"10.2316/j.2020.206-0449","title":"ROBUST ADAPTIVE CONTROL BASED ON MACHINE LEARNING AND NTSMC FOR WORKPIECE SURFACE-GRINDING ROBOT","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Grinding; Computer science; Robot; Surface grinding; Adaptive control; Surface (topology); Control (management); Artificial intelligence; Engineering; Mechanical engineering; Mathematics; Geometry","score_opus":0.018159177756974402,"score_gpt":0.23714800926386365,"score_spread":0.21898883150688925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083570310","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":[0.0052615902,0.00027066268,0.9928916,0.0011801642,0.00021323406,0.00007554968,0.000008860356,0.00004115235,0.000057202902],"genre_scores_gemma":[0.8965273,0.00014318564,0.10305751,0.00012254018,0.00011743811,9.07117e-7,0.000010524427,0.00001535497,0.000005249383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946564,0.000011714806,0.0002208563,0.000073709336,0.00015642529,0.00007162288],"domain_scores_gemma":[0.99945503,0.0001492182,0.0001544927,0.000016104863,0.0001683453,0.00005679684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010951268,0.000088396875,0.000126574,0.00006235927,0.000049707265,0.000069716836,0.000058325677,0.000035140427,0.0000044585818],"category_scores_gemma":[0.00011597726,0.000082589206,0.000029805573,0.000047340123,0.000010684589,0.00018346931,0.000008227228,0.00014008656,3.3272428e-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":[0.00009377731,0.000007885021,0.00099123,0.000022948945,0.000042447362,0.000002365921,0.000091846865,0.99099135,0.00023453857,0.00035741975,0.0000119449005,0.007152246],"study_design_scores_gemma":[0.0011929389,0.00018096098,0.00056646694,0.000100357254,0.000023249824,0.000007723187,0.000034207358,0.9973989,0.00013636227,0.00011517157,0.00016331264,0.00008032623],"about_ca_topic_score_codex":5.304321e-7,"about_ca_topic_score_gemma":6.301474e-7,"teacher_disagreement_score":0.8912657,"about_ca_system_score_codex":0.000031255873,"about_ca_system_score_gemma":0.00001138633,"threshold_uncertainty_score":0.33678898},"labels":[],"label_agreement":null},{"id":"W3086458175","doi":"","title":"Simulation of the Inverse-Kinematics for JACO Manipulator Robot Arm","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inverse kinematics; Kinematics; Robotic arm; Computer science; Inverse; Robotics; Artificial intelligence; Process (computing); Robot; Simulation; Mathematics; Physics; Operating system","score_opus":0.03428913451826353,"score_gpt":0.28579989085636553,"score_spread":0.251510756338102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086458175","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":[0.1227297,0.00006487904,0.8756009,0.0005780931,0.00091845414,0.000054025164,0.0000037030763,0.000032830143,0.000017463179],"genre_scores_gemma":[0.9086783,0.000054827273,0.09116763,0.000009892483,0.000065283115,9.69447e-7,4.689861e-7,0.0000065765325,0.000016038139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995441,0.000009808143,0.0002571087,0.000029955174,0.00011092737,0.000048131675],"domain_scores_gemma":[0.9993469,0.0002594962,0.00014738171,0.00005566151,0.00017865206,0.00001189302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019304725,0.000052153257,0.00009333564,0.000089626665,0.000013367607,0.000007814817,0.00013883207,0.000057727197,0.0000028211791],"category_scores_gemma":[0.00044438976,0.00003119662,0.000048937225,0.000034754077,0.0000270412,0.000104014995,0.000018605828,0.000046305613,2.8854217e-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":[0.0000052317246,0.000007699746,0.00021884446,0.000025445806,0.000057262838,3.019832e-7,0.00003639956,0.9747759,0.011899213,0.0031078102,0.00007209306,0.009793778],"study_design_scores_gemma":[0.00046242427,0.00004369029,0.0054346207,0.00019786373,0.0000299749,0.000014361039,0.00001858202,0.9651048,0.01750443,0.010910229,0.00022099627,0.00005800022],"about_ca_topic_score_codex":2.1216513e-7,"about_ca_topic_score_gemma":7.6445366e-7,"teacher_disagreement_score":0.78594863,"about_ca_system_score_codex":0.000029902541,"about_ca_system_score_gemma":0.000008132606,"threshold_uncertainty_score":0.12721613},"labels":[],"label_agreement":null},{"id":"W3111728993","doi":"10.37628/ijra.v4i2.810","title":"Use of Robotic Technology in Surgery","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Minimally Invasive Surgical Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Nanorobotics; Robot; Robotics; Robotic surgery; Surgical robot; Computer science; Field (mathematics); Artificial intelligence; Open surgery; Work (physics); Human–computer interaction; Surgery; Medicine; Engineering; Mechanical engineering; Mathematics","score_opus":0.05006315006679084,"score_gpt":0.3201361366857391,"score_spread":0.27007298661894824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111728993","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":[0.97863686,0.000087471446,0.016013997,0.004812155,0.00027741518,0.00006276102,0.0000011279857,0.00001647411,0.0000917188],"genre_scores_gemma":[0.9715452,0.00019410317,0.028047683,0.000089114736,0.00009729139,4.96235e-7,0.0000018904609,0.0000052034857,0.000019024941],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914426,0.000018431094,0.00047769304,0.000056372435,0.00024149056,0.00006176802],"domain_scores_gemma":[0.9986229,0.00017079715,0.00033020074,0.000055284017,0.0007901858,0.000030609233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024072907,0.00005276015,0.00021784675,0.00069504546,0.0000072565967,0.000012857551,0.000060186223,0.00006810674,0.000025098503],"category_scores_gemma":[0.0007070918,0.000043690117,0.000053249794,0.0001507605,0.00010774684,0.00014876753,0.000027563787,0.00009902245,0.0000013733379],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006651999,0.00085657474,0.7484178,0.00013935792,0.00047440524,0.00070425746,0.00038798337,0.0021626747,0.09518254,0.039749634,0.002042511,0.10921706],"study_design_scores_gemma":[0.0019084899,0.0015582636,0.8160092,0.0035518338,0.0001422642,0.003761412,0.00014169663,0.03797746,0.110793464,0.022008449,0.0018526514,0.0002947905],"about_ca_topic_score_codex":0.0000053290487,"about_ca_topic_score_gemma":0.0000024272476,"teacher_disagreement_score":0.10892227,"about_ca_system_score_codex":0.000043631564,"about_ca_system_score_gemma":0.00006462512,"threshold_uncertainty_score":0.17816313},"labels":[],"label_agreement":null},{"id":"W3111796581","doi":"10.37628/ijra.v4i1.686","title":"Integration of Robotics and Biotechnology for Welfare of Society","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Internet of Things and AI","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robotics; Robot; Artificial intelligence; Computer science; Welfare; Engineering ethics; Engineering; Political science; Law","score_opus":0.012588279441160439,"score_gpt":0.2691620355862851,"score_spread":0.2565737561451247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111796581","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":[0.06478694,0.00006933202,0.9247743,0.009671269,0.00059821433,0.00004955107,0.0000039883544,0.000009269506,0.000037158996],"genre_scores_gemma":[0.75132334,0.000064765394,0.24846175,0.000054002594,0.000077971905,2.817487e-7,0.0000013829073,0.00000267611,0.000013811775],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927056,0.000010243252,0.00038004282,0.000079610836,0.00019910195,0.00006044079],"domain_scores_gemma":[0.99850404,0.00004488817,0.00057504274,0.000066721186,0.0007880478,0.000021249254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026045289,0.00006181444,0.0001381428,0.00012716014,0.000033811026,0.000051214538,0.00029720695,0.000071089176,0.0000018448768],"category_scores_gemma":[0.000081611295,0.000051151328,0.00006891538,0.000059390975,0.00009532318,0.00031002625,0.00008833918,0.00006560077,1.5215367e-7],"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":[0.000036141242,0.00010700265,0.00028049687,0.00006219797,0.00019340763,0.0000015659361,0.001609813,0.0034452018,0.048130833,0.827477,0.0005356102,0.118120775],"study_design_scores_gemma":[0.00075228355,0.00078411493,0.0031197243,0.00024645502,0.000027118733,0.000109993445,0.0001986118,0.91265297,0.060442798,0.020869853,0.0006943396,0.00010172115],"about_ca_topic_score_codex":0.0000067005153,"about_ca_topic_score_gemma":0.0000022326572,"teacher_disagreement_score":0.90920776,"about_ca_system_score_codex":0.000020732097,"about_ca_system_score_gemma":0.000024391627,"threshold_uncertainty_score":0.20858906},"labels":[],"label_agreement":null},{"id":"W3111890426","doi":"10.37628/ijra.v3i2.572","title":"Study on High Temperature Corrosion Cast and Wrought Steel","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Metal Alloys Wear and Properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Corrosion; Carbon steel; Metallurgy; Carbon fibers; High carbon; Oxide; Layer (electronics); Morphology (biology); Composite material","score_opus":0.027715198827677163,"score_gpt":0.29056884376406883,"score_spread":0.2628536449363917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111890426","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":[0.9969814,0.000058935006,0.00011944895,0.0012677939,0.0013722287,0.000059038404,0.000005498691,0.0000058695373,0.00012980723],"genre_scores_gemma":[0.99866253,0.000048536298,0.0008001397,0.00006662113,0.00021470092,5.601025e-7,0.0000011197407,0.000004664942,0.00020110623],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992893,0.00003738331,0.00020906005,0.000081965416,0.0003287928,0.00005350983],"domain_scores_gemma":[0.99933195,0.000028354347,0.00030303196,0.000087848624,0.00021056036,0.000038263523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003103024,0.00006787026,0.000113513706,0.000056728255,0.00017185863,0.0005073102,0.0001870302,0.000029711722,0.000020824595],"category_scores_gemma":[0.000100527606,0.000045502544,0.000019351954,0.000008661215,0.00004067001,0.0003633611,0.000067705616,0.00008040345,0.0000072882326],"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":[0.00036870543,0.00045648735,0.01764257,0.000025841682,0.00007344267,0.00019232168,0.0022687311,0.003504957,0.9558188,0.006795055,0.00065900316,0.012194093],"study_design_scores_gemma":[0.0031428887,0.001873914,0.8902457,0.0004601148,0.00008796676,0.00055476546,0.0010350115,0.0027949545,0.09684192,0.0021377823,0.00050726003,0.00031776042],"about_ca_topic_score_codex":0.000015712,"about_ca_topic_score_gemma":0.0000064743936,"teacher_disagreement_score":0.8726031,"about_ca_system_score_codex":0.000015184271,"about_ca_system_score_gemma":0.000015719452,"threshold_uncertainty_score":0.4892004},"labels":[],"label_agreement":null},{"id":"W3112093917","doi":"10.37628/ijra.v5i2.909","title":"Link position control of flexible joint robots based on Sliding Mode Technique","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Robot; Sliding mode control; Control engineering; Joint stiffness; Bandwidth (computing); Computer science; Robotics; Nonlinear system; Robustness (evolution); Engineering; Stiffness; Artificial intelligence; Control (management); Telecommunications; Physics","score_opus":0.005945836503803498,"score_gpt":0.219718025107569,"score_spread":0.21377218860376548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112093917","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":[0.0406379,0.00005862864,0.9570941,0.00067789893,0.0008875148,0.00014207621,0.0000082078595,0.000028935603,0.00046477388],"genre_scores_gemma":[0.9953993,0.000012288593,0.004382468,0.000055015014,0.00011869166,0.0000026526109,0.000004497329,0.000011225409,0.000013844118],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991333,0.000019504365,0.00040901528,0.000055229655,0.00031398426,0.000068958536],"domain_scores_gemma":[0.99940085,0.0000527727,0.00022685778,0.00005934813,0.00022304938,0.00003710526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025873876,0.00007754228,0.00018196987,0.00017854433,0.000010826033,0.000039472066,0.00009908122,0.000063497304,0.000011925515],"category_scores_gemma":[0.000017069227,0.00006890287,0.00007801905,0.000039243245,0.00000423594,0.00012278014,0.000006948565,0.00010951076,0.0000029708456],"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":[0.000028586435,0.000022692699,0.000098277786,0.000022548711,0.00006163732,0.0000034174368,0.00001685983,0.9212531,0.06143805,0.012915082,0.000010125683,0.004129666],"study_design_scores_gemma":[0.0008390113,0.00016609329,0.0011112381,0.00034370593,0.000016604901,0.00002290884,0.000008498836,0.9921157,0.0040152953,0.0012759314,0.000018844034,0.00006621302],"about_ca_topic_score_codex":0.0000036211989,"about_ca_topic_score_gemma":3.2959792e-7,"teacher_disagreement_score":0.95476145,"about_ca_system_score_codex":0.00008960992,"about_ca_system_score_gemma":0.000017626233,"threshold_uncertainty_score":0.28097776},"labels":[],"label_agreement":null},{"id":"W3112109997","doi":"10.37628/ijra.v4i1.698","title":"Medical Imaging and Application of Medical Robots in Medical Imaging: An Overview","year":2018,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Medicine; Medical imaging; Orthopedic surgery; Neurosurgery; Medical physics; Robotics; Medical robotics; Surgical robot; Surgery; General surgery; Artificial intelligence; Radiology; Computer science","score_opus":0.012176923606639793,"score_gpt":0.3158416646618814,"score_spread":0.3036647410552416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112109997","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":[0.18573178,0.0035643112,0.7918495,0.017403627,0.00094001385,0.00015008794,0.0000058556175,0.000070730275,0.00028409262],"genre_scores_gemma":[0.9937429,0.0020794007,0.0035174743,0.000217024,0.0004151293,0.000002788007,0.000010049155,0.000014049525,0.0000012304959],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979293,0.000027723492,0.00061944325,0.00010903646,0.0012071071,0.00010741604],"domain_scores_gemma":[0.9991577,0.00010181238,0.00016797107,0.00008738688,0.00027315938,0.00021194814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007989424,0.00009801242,0.00018282949,0.00021398126,0.000027061235,0.000048457106,0.0003331659,0.000093658855,0.00007989332],"category_scores_gemma":[0.00021787496,0.00009084146,0.000031380227,0.00012117123,0.000140655,0.0002420084,0.00006692557,0.00020922098,0.0000020512628],"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":[0.00001966165,0.00030878597,0.04261951,0.00011709161,0.00011369568,0.00008174332,0.0007302347,0.020279326,0.0009660579,0.06584502,0.0006592056,0.86825967],"study_design_scores_gemma":[0.0005565429,0.000015671161,0.034210876,0.00026851665,0.0000119486795,0.00037414714,0.000058537196,0.96117043,0.00010194081,0.0026494286,0.0004986951,0.000083280334],"about_ca_topic_score_codex":0.000031895608,"about_ca_topic_score_gemma":0.000048264126,"teacher_disagreement_score":0.9408911,"about_ca_system_score_codex":0.00004127516,"about_ca_system_score_gemma":0.00008987324,"threshold_uncertainty_score":0.37044072},"labels":[],"label_agreement":null},{"id":"W3121279391","doi":"10.2316/j.2021.206-0543","title":"ANALYSIS OF INFLUENCE FACTORS FOR CFST ARCH BRIDGE VOID BASED ON EDDY CURRENT THERMAL IMAGING","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Thermography and Photoacoustic Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Eddy current; Arch bridge; Structural engineering; Arch; Bridge (graph theory); Void (composites); Current (fluid); Thermal; Materials science; Engineering; Composite material; Physics; Electrical engineering; Meteorology; Medicine; Internal medicine","score_opus":0.011544369767201334,"score_gpt":0.2742345258940918,"score_spread":0.26269015612689045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121279391","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":[0.6629973,0.00011061866,0.33646235,0.00004956435,0.00022910145,0.000027865442,0.000094472576,0.000016534123,0.000012179621],"genre_scores_gemma":[0.9972931,0.000040226783,0.0025680906,0.000017399812,0.00004437073,0.0000010867377,0.000028917248,0.0000061956484,5.716978e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994034,0.000013602352,0.00026720238,0.00005125304,0.0002072249,0.00005728705],"domain_scores_gemma":[0.9993083,0.00014886745,0.00013175323,0.00004872082,0.0003359648,0.00002641382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012202342,0.00006557038,0.00013086958,0.00033001238,0.000016509746,0.00003292129,0.00009007155,0.000019494648,0.0000068914337],"category_scores_gemma":[0.000049560556,0.000059123235,0.00012828322,0.0001396164,0.000016492751,0.00009436008,0.000007717513,0.00007927723,2.837244e-8],"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":[0.000014900488,0.000042767308,0.018298035,0.000025958241,0.00027033538,0.0000031683212,0.00018545466,0.9457809,0.015785515,0.00022532912,0.000015284972,0.019352373],"study_design_scores_gemma":[0.00017712884,0.000023227245,0.25392288,0.000094994786,0.0001437087,0.0000030165015,0.000022197544,0.73467314,0.010727552,0.000118496406,0.000038851333,0.00005480423],"about_ca_topic_score_codex":0.0000044073704,"about_ca_topic_score_gemma":0.0000020539387,"teacher_disagreement_score":0.33429584,"about_ca_system_score_codex":0.000026110401,"about_ca_system_score_gemma":0.000022956527,"threshold_uncertainty_score":0.24109755},"labels":[],"label_agreement":null},{"id":"W3122155305","doi":"10.2316/j.2021.206-0610","title":"OBSTACLE AVOIDANCE FOR MULTI-UAV SYSTEM WITH OPTIMIZED ARTIFICIAL POTENTIAL FIELD ALGORITHM","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"National Natural Science Foundation of China","keywords":"Obstacle avoidance; Computer science; Potential field; Obstacle; Field (mathematics); Algorithm; Artificial intelligence; Mathematics; Mobile robot; Physics; Robot","score_opus":0.008198139425394397,"score_gpt":0.2196009070049453,"score_spread":0.2114027675795509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122155305","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":[0.012744496,0.00034718844,0.9850491,0.0002608486,0.0014660837,0.00005644424,0.000009020782,0.000049760267,0.000017031127],"genre_scores_gemma":[0.8396736,0.000022921706,0.15985928,0.000011005343,0.00036501983,0.0000036656859,0.000005888121,0.000012674682,0.00004594383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941707,0.000010070212,0.00025464763,0.000058059184,0.0001807212,0.00007940873],"domain_scores_gemma":[0.99944764,0.0000418133,0.00009693034,0.000042019932,0.00033336482,0.000038204944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010183685,0.000075258664,0.00014283168,0.000048978767,0.000028849427,0.00009686637,0.00006673397,0.000043233133,0.0000018202909],"category_scores_gemma":[0.000026351761,0.00006647955,0.000051483235,0.00003454595,0.000005676846,0.00012239594,0.0000070166498,0.000077202785,7.439044e-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":[0.00002199647,0.000014811047,0.000013853785,0.000037216963,0.00014085602,0.00003713042,0.00006682497,0.98230135,0.0029438157,0.00072884373,0.000070111346,0.013623191],"study_design_scores_gemma":[0.0009765506,0.00004371649,0.0001645233,0.00016630044,0.000025940806,0.0002766387,0.00016373886,0.9955515,0.0024321622,0.000015809966,0.0001071966,0.00007592489],"about_ca_topic_score_codex":0.0000022424938,"about_ca_topic_score_gemma":0.000002145986,"teacher_disagreement_score":0.8269291,"about_ca_system_score_codex":0.00005200723,"about_ca_system_score_gemma":0.000022799893,"threshold_uncertainty_score":0.27109575},"labels":[],"label_agreement":null},{"id":"W3124739866","doi":"10.2316/j.2021.206-0545","title":"GUEST EDITORIAL: AUTOMATIC DETECTION AND ASSESSMENT OF BRIDGE STRUCTURES","year":2021,"lang":"en","type":"editorial","venue":"International Journal of Robotics and Automation","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bridge (graph theory); Computer science; Medicine","score_opus":0.005708931977149261,"score_gpt":0.2706558423554365,"score_spread":0.2649469103782872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124739866","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0063288053,0.00040152727,0.013659107,0.000025110961,0.9794114,0.00005540137,0.000030856267,0.000029587067,0.000058174584],"genre_scores_gemma":[0.18518035,0.0010133716,0.0048559555,0.0000021458181,0.8088784,0.0000012630238,0.000037080343,0.000026149759,0.000005272916],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983102,0.000027635964,0.0006220577,0.00010395321,0.0008320418,0.000104111816],"domain_scores_gemma":[0.998164,0.00017299816,0.00050749455,0.00007814471,0.0010277629,0.000049612016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025007848,0.00018209267,0.00035048806,0.00024730363,0.00003080053,0.0001476673,0.00014809315,0.0003104734,0.0000035965202],"category_scores_gemma":[0.00023649102,0.00016835552,0.00007437044,0.000055430428,0.00003342092,0.00022645903,0.0000467984,0.0005400691,1.11855506e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026649901,0.000046078752,0.00026908627,0.0012257433,0.0015004512,0.00007573565,0.0005507825,0.09812282,0.010372448,0.0003719742,0.81817514,0.06926312],"study_design_scores_gemma":[0.0038001728,0.00056745304,0.03338251,0.0045317886,0.0008321035,0.0003798599,0.00024762112,0.28464922,0.0074599925,0.0038960371,0.6590109,0.0012423672],"about_ca_topic_score_codex":0.000011749886,"about_ca_topic_score_gemma":0.000006450526,"teacher_disagreement_score":0.1865264,"about_ca_system_score_codex":0.00016328583,"about_ca_system_score_gemma":0.00012569671,"threshold_uncertainty_score":0.68653387},"labels":[],"label_agreement":null},{"id":"W3126515410","doi":"10.2316/j.2021.206-0614","title":"DESIGN AND SYNTHESIS OF COMPLIANT MECHANISM FOR 3D MICRO-GRASPING","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mechanism (biology); Computer science; Philosophy; Epistemology","score_opus":0.023504699682123837,"score_gpt":0.25114501587090043,"score_spread":0.2276403161887766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126515410","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":[0.025126005,0.00030616412,0.9739011,0.00026416092,0.00033388953,0.000040037965,0.000002458732,0.000007214582,0.000018955961],"genre_scores_gemma":[0.6997804,0.00043466865,0.29971224,0.000019077925,0.000039769035,9.937786e-7,0.0000012352687,0.000006347329,0.0000052734285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995096,0.00001218873,0.00026227447,0.00004580191,0.00012022992,0.000049905026],"domain_scores_gemma":[0.9994356,0.00011365047,0.00010464551,0.000031321197,0.00028999092,0.000024798102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014534235,0.000053187352,0.00011611191,0.00007028796,0.000018705716,0.000040050443,0.000059379912,0.000028234714,0.0000040193277],"category_scores_gemma":[0.000070073664,0.000049702714,0.000029900155,0.000024475159,0.000011212079,0.00008603024,0.000012294453,0.00003929696,2.2912702e-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":[0.00002091727,0.000055983575,0.000086701744,0.0001376524,0.00033668758,0.000026540956,0.00032567227,0.68998605,0.19651155,0.022030508,0.00010055621,0.09038116],"study_design_scores_gemma":[0.00014943478,0.000027173803,0.00030414757,0.00018029046,0.000027199982,0.0001442417,0.000041416217,0.82038885,0.17438163,0.004270158,0.000030471017,0.00005496448],"about_ca_topic_score_codex":9.664894e-7,"about_ca_topic_score_gemma":4.7113264e-7,"teacher_disagreement_score":0.67465436,"about_ca_system_score_codex":0.00001729839,"about_ca_system_score_gemma":0.00001525825,"threshold_uncertainty_score":0.20268178},"labels":[],"label_agreement":null},{"id":"W3126750794","doi":"10.2316/j.2021.206-0521","title":"ALTERNATIVE KINEMATICS MODELLING AND ANALYSIS OF ROVERS WITH COMPLEX MOBILITY SYSTEMS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Computer science; Physics; Classical mechanics","score_opus":0.020393953442321897,"score_gpt":0.24257086219211046,"score_spread":0.22217690874978857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126750794","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":[0.4453811,0.00035453885,0.55392087,0.00004494157,0.00016330207,0.00002314976,0.000012631915,0.000014154238,0.00008532057],"genre_scores_gemma":[0.98623556,0.00022176327,0.013503645,0.0000028942661,0.000020065907,4.951756e-7,0.0000069499065,0.000004438671,0.000004180059],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993333,0.000012190134,0.00033144842,0.000051918196,0.00022572228,0.000045377725],"domain_scores_gemma":[0.9992543,0.000057624744,0.00020777318,0.000055716133,0.0004031871,0.00002141151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011936142,0.00006222586,0.00022038535,0.00020868432,0.000012243954,0.00005291535,0.00006814254,0.000030194571,0.0000023271914],"category_scores_gemma":[0.00001749346,0.00005024116,0.000036469042,0.00013784006,0.000027033935,0.00013088447,0.00001879988,0.00005934282,5.330273e-8],"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":[0.0000038083067,0.000015522939,0.0015801626,0.000047620633,0.0010534383,0.000011062309,0.00016169519,0.99208724,0.00051231665,0.0040765763,0.000008536695,0.00044200436],"study_design_scores_gemma":[0.00020043267,0.000025070438,0.003639991,0.000112809066,0.00016511587,0.000052940286,0.00026600956,0.99459845,0.0005140663,0.00034815696,0.000028091494,0.000048888443],"about_ca_topic_score_codex":0.000016115702,"about_ca_topic_score_gemma":0.000004801423,"teacher_disagreement_score":0.54085445,"about_ca_system_score_codex":0.000034221954,"about_ca_system_score_gemma":0.0000117230275,"threshold_uncertainty_score":0.20487751},"labels":[],"label_agreement":null},{"id":"W3127507992","doi":"10.2316/j.2021.206-0571","title":"GWO-BASED TUNING OF LQR–PID CONTROLLER FOR 3-DOF PARALLEL MANIPULATOR","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); PID controller; Parallel manipulator; Computer science; Controller (irrigation); Control engineering; Engineering; Control (management); Robot; Artificial intelligence; Biology","score_opus":0.01255266001339798,"score_gpt":0.2403082205339654,"score_spread":0.22775556052056742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127507992","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":[0.11664116,0.0005831822,0.8801309,0.00058641314,0.0017349914,0.00011334752,0.000019395338,0.000029414685,0.0001612248],"genre_scores_gemma":[0.97725815,0.00002015591,0.02238223,0.00003997901,0.000235845,0.0000023686305,0.000015072257,0.000015157889,0.000031068445],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999079,0.000020762482,0.0004893746,0.000057103378,0.00027174765,0.00008199304],"domain_scores_gemma":[0.99895024,0.00012454078,0.00023170788,0.000050091745,0.0006031383,0.000040287046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002177284,0.00008153948,0.000205959,0.00014429362,0.000020575235,0.000045778877,0.00009362306,0.00004914437,0.000010834393],"category_scores_gemma":[0.000087718945,0.00007833006,0.00010143864,0.00005000126,0.000013006268,0.00012985783,0.000008983447,0.00007075681,0.0000010235593],"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":[0.000037058686,0.000033287284,0.0009472251,0.000094946874,0.00021347844,0.000013145921,0.0001010271,0.9727963,0.020247053,0.0026506896,0.0004351801,0.0024305976],"study_design_scores_gemma":[0.0018881692,0.000052031093,0.0035562867,0.00021360439,0.00003373716,0.000046311474,0.00005247776,0.9877986,0.005014797,0.0004203061,0.0008382291,0.000085498876],"about_ca_topic_score_codex":0.0000017723215,"about_ca_topic_score_gemma":0.0000025907066,"teacher_disagreement_score":0.860617,"about_ca_system_score_codex":0.00006143744,"about_ca_system_score_gemma":0.00005136855,"threshold_uncertainty_score":0.3194207},"labels":[],"label_agreement":null},{"id":"W3127577397","doi":"10.2316/j.2021.206-0366","title":"ON THE APPLICATIVE WORKSPACE AND THE MECHANISM OF AN AGRICULTURE 3-DOF 4-CABLE-DRIVEN ROBOT","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Workspace; Robot; Mechanism (biology); Computer science; Human–computer interaction; Control engineering; Simulation; Artificial intelligence; Engineering; Physics","score_opus":0.003783239270321809,"score_gpt":0.19796373290663774,"score_spread":0.19418049363631593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127577397","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":[0.12662767,0.0011996606,0.8547412,0.015468345,0.00076167996,0.00027763977,0.000017107326,0.000036488473,0.0008702239],"genre_scores_gemma":[0.99293125,0.00040563438,0.0064352276,0.00009067842,0.000093190894,0.00000323031,0.0000043686623,0.0000062256195,0.000030186506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994201,0.0000390617,0.00020862251,0.000055385706,0.00022392272,0.000052908967],"domain_scores_gemma":[0.99924463,0.00023225803,0.00015290396,0.00006891881,0.00027274946,0.000028532448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018826817,0.00007231091,0.00012725263,0.000036006066,0.000038944832,0.00007018574,0.00013676223,0.00003822169,0.000006919616],"category_scores_gemma":[0.000054728767,0.00003918789,0.000045723504,0.000051849172,0.000036207937,0.000107320055,0.000028864097,0.00013929291,4.5507718e-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":[0.000020991365,0.000020525296,0.0000075782505,0.0000050498465,0.0001127445,0.0000042468023,0.0002325477,0.8134725,0.002289367,0.17910434,0.000065494445,0.004664593],"study_design_scores_gemma":[0.00080569356,0.000034767465,0.0012830774,0.00008737379,0.000035467918,0.00009305176,0.00024016546,0.97475255,0.00055889494,0.022007728,0.000045731453,0.000055473047],"about_ca_topic_score_codex":0.0000033794859,"about_ca_topic_score_gemma":0.000012360362,"teacher_disagreement_score":0.8663036,"about_ca_system_score_codex":0.000021229042,"about_ca_system_score_gemma":0.000013111904,"threshold_uncertainty_score":0.15980358},"labels":[],"label_agreement":null},{"id":"W3129223289","doi":"10.37628/ijra.v6i2.1171","title":"A Study on Multitasking Robot for Military Services","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bluetooth; Android (operating system); Robot; Human multitasking; Embedded system; Computer science; Phone; Computer security; Wireless; Human–computer interaction; Real-time computing; Operating system; Artificial intelligence","score_opus":0.01846889248213599,"score_gpt":0.2586362545008295,"score_spread":0.24016736201869351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129223289","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":[0.8699669,0.0002864468,0.12601419,0.0014053205,0.001867878,0.00028741529,0.000016239208,0.00007557527,0.000080028694],"genre_scores_gemma":[0.9944835,0.000010893478,0.004921783,0.00010919635,0.0004503778,0.0000026846549,0.000005769447,0.000013517728,0.0000022816516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992957,0.000016212078,0.00031548785,0.000061588085,0.00024728398,0.00006370756],"domain_scores_gemma":[0.9995856,0.00006862895,0.000086528766,0.00003471771,0.00017583737,0.00004868518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014791246,0.00007762456,0.00012676098,0.00009909186,0.00002459982,0.00003970321,0.00012742874,0.00002627024,0.0000020483906],"category_scores_gemma":[0.000029018709,0.00007028642,0.000047262998,0.00004047408,0.00000498261,0.00016795406,0.000012142352,0.000075432494,0.000003188933],"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":[0.00003493309,0.000052681105,0.002119213,0.00006994118,0.00018847435,0.000018300689,0.0025123858,0.98995394,0.0018407521,0.00012867848,0.00018916535,0.0028915226],"study_design_scores_gemma":[0.0012248467,0.0003912399,0.01565374,0.00014528111,0.000029790159,0.000021678852,0.0012263069,0.9803516,0.00045241124,0.00006693105,0.00033417114,0.000101975755],"about_ca_topic_score_codex":0.0000033534905,"about_ca_topic_score_gemma":0.0000045470915,"teacher_disagreement_score":0.124516584,"about_ca_system_score_codex":0.00004117764,"about_ca_system_score_gemma":0.00000889517,"threshold_uncertainty_score":0.28661972},"labels":[],"label_agreement":null},{"id":"W3133437397","doi":"10.37628/ijra.v6i2.1170","title":"Fire Fighting Robot Using IoT","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bluetooth; Robot; Arduino; Obstacle; Mobile robot; Engineering; Mobile phone; Simulation; Microcontroller; Computer science; Firefighting; Remote control; Real-time computing; Embedded system; Wireless; Electrical engineering; Artificial intelligence; Telecommunications","score_opus":0.018848440606899927,"score_gpt":0.23798027274537492,"score_spread":0.21913183213847498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133437397","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":[0.692647,0.0004017244,0.3028324,0.0016617995,0.0020835404,0.000061835475,0.000005893258,0.000083114646,0.00022270948],"genre_scores_gemma":[0.985068,0.000021648439,0.014126583,0.00008032856,0.00068222865,1.9799907e-7,0.000002676137,0.0000140018055,0.0000042999272],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924517,0.000015466216,0.00034895426,0.000050383744,0.00026547813,0.00007452273],"domain_scores_gemma":[0.999551,0.00003330037,0.00014966016,0.000029398696,0.00017205997,0.00006456616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011445514,0.000075659824,0.00012258814,0.00007223424,0.000027477523,0.00008122117,0.000114797986,0.000038951293,0.0000135080045],"category_scores_gemma":[0.000054102045,0.000071887065,0.000046583806,0.00006564016,0.000009458923,0.00016285402,0.00001728635,0.00011293317,0.0000047433323],"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":[0.000005412437,0.0000056616927,0.00063332805,0.000031021704,0.0000721072,0.000022983439,0.0003303285,0.9826447,0.00934275,0.00018020385,0.00024800978,0.006483531],"study_design_scores_gemma":[0.0002818196,0.000026875843,0.0014087318,0.0001178364,0.000013892899,0.000098861565,0.000056460816,0.99613726,0.0012247349,0.000055394008,0.0005024326,0.0000757195],"about_ca_topic_score_codex":0.00000267887,"about_ca_topic_score_gemma":5.779079e-7,"teacher_disagreement_score":0.29242107,"about_ca_system_score_codex":0.00006395101,"about_ca_system_score_gemma":0.000020004918,"threshold_uncertainty_score":0.29314694},"labels":[],"label_agreement":null},{"id":"W3140732062","doi":"10.5555/1164085.1164089","title":"Design and testing of an ultra-high-speed cable robot","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Computer science; Simulation; Artificial intelligence","score_opus":0.008342954060709588,"score_gpt":0.21050870385922063,"score_spread":0.20216574979851104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3140732062","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":[0.42894825,0.00026478953,0.57007957,0.00013296129,0.00032348055,0.000057656733,0.0000031420718,0.0000282322,0.00016190269],"genre_scores_gemma":[0.91828585,0.000042913012,0.08152751,0.000006612266,0.000113886636,3.318261e-7,0.0000042166284,0.000008590365,0.000010073636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993616,0.000015148631,0.00031951416,0.000050472685,0.00018503323,0.00006825057],"domain_scores_gemma":[0.9994169,0.00011240443,0.00015256593,0.000036458932,0.0002471362,0.00003454202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019371329,0.00007147465,0.00012935494,0.00012505145,0.000020637211,0.00005739406,0.000080954036,0.000035884397,0.0000030639303],"category_scores_gemma":[0.000034551696,0.00006677666,0.000019347388,0.000043692886,0.000018134713,0.00027615402,0.0000063658013,0.00006617788,2.6513823e-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":[0.00000942334,0.000022983275,0.00040590085,0.000010960454,0.000030264579,0.000007597699,0.000025728412,0.9410284,0.044943396,0.0006725804,0.000015832484,0.012826919],"study_design_scores_gemma":[0.0005594803,0.000080462916,0.014998116,0.000065797394,0.000020317513,0.00012219048,0.000010677129,0.97811717,0.0032613778,0.0026877846,0.000008966407,0.000067641486],"about_ca_topic_score_codex":0.00004784418,"about_ca_topic_score_gemma":0.0000055873293,"teacher_disagreement_score":0.4893376,"about_ca_system_score_codex":0.000026145306,"about_ca_system_score_gemma":0.000015122917,"threshold_uncertainty_score":0.2723073},"labels":[],"label_agreement":null},{"id":"W3140840285","doi":"10.5555/1164085.1164086","title":"PD Control of robot with velocity estimation and uncertainties compensation","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Compensation (psychology); Control theory (sociology); Robot; Zero (linguistics); Control (management); State (computer science); Computer science; Joint (building); Control engineering; Industrial robot; Engineering; Artificial intelligence; Algorithm; Structural engineering; Psychology","score_opus":0.0041118990870187755,"score_gpt":0.2040026099256772,"score_spread":0.19989071083865842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3140840285","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":[0.34981102,0.00017587274,0.64940995,0.00026989167,0.00017069044,0.000054623106,0.0000028603292,0.00001645292,0.00008861495],"genre_scores_gemma":[0.9888854,0.000011747762,0.010975326,0.000008941807,0.00009307381,8.386843e-7,0.000007145379,0.00000706369,0.000010484136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933,0.00002790004,0.00031839777,0.000042247473,0.0002322093,0.000049288104],"domain_scores_gemma":[0.9992589,0.00007536037,0.00025563576,0.000027407239,0.00036624394,0.000016451204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017448688,0.000069799105,0.00014606141,0.00013088474,0.000022603865,0.000065692235,0.000046707242,0.000030158546,0.0000021493538],"category_scores_gemma":[0.000025820613,0.00005789368,0.000018601635,0.00003775208,0.00003316913,0.00024655645,0.00000459582,0.00006824562,3.4944233e-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":[0.000025640325,0.000011643437,0.004940146,0.00002586917,0.000073617644,0.0000024439087,0.00016137723,0.9819816,0.0034806838,0.0037790737,0.000022393957,0.0054955096],"study_design_scores_gemma":[0.0008893847,0.00007603125,0.084872,0.00012630584,0.000023074846,0.00006149877,0.00003187775,0.91279054,0.00041788354,0.0006220547,0.00003478345,0.000054546486],"about_ca_topic_score_codex":0.000019634463,"about_ca_topic_score_gemma":0.000007802838,"teacher_disagreement_score":0.6390744,"about_ca_system_score_codex":0.00004489009,"about_ca_system_score_gemma":0.000012694128,"threshold_uncertainty_score":0.23608358},"labels":[],"label_agreement":null},{"id":"W3142550489","doi":"10.5555/1739829.1739832","title":"Neuro-adaptive compliant force/motion control of uncertain constrained wheeled mobile manipulators","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Computer science; Motion (physics); Motion control; Control (management); Robot; Artificial intelligence","score_opus":0.012998525658142537,"score_gpt":0.2523066204547549,"score_spread":0.23930809479661236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3142550489","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":[0.15181883,0.00009255694,0.84717757,0.00014836114,0.00041365606,0.000120916986,0.000011514657,0.000026982427,0.00018961568],"genre_scores_gemma":[0.9906574,0.000038999722,0.009133106,0.000033240907,0.00010952156,0.0000016769441,0.000008052707,0.000011587957,0.0000064210435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990712,0.000010360062,0.00050897937,0.00006169155,0.00025289066,0.000094875475],"domain_scores_gemma":[0.99910593,0.00014993294,0.00026058313,0.000055112512,0.00037063163,0.00005779978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024872858,0.000090338624,0.00016061272,0.00017418676,0.000026945847,0.000029355175,0.00011863635,0.000047925085,0.0000098096225],"category_scores_gemma":[0.000030998104,0.00008578324,0.000063118,0.00007868391,0.000040585128,0.00012448976,0.000010309592,0.00010141767,0.0000013571632],"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":[0.000025504056,0.0000505142,0.001335617,0.000015081611,0.00013421688,0.000010384124,0.00013467988,0.95436114,0.013850572,0.01910333,0.00005763833,0.010921309],"study_design_scores_gemma":[0.0011100556,0.00011666818,0.019202769,0.00007709503,0.000046419314,0.00011642371,0.0001702101,0.9737279,0.0025857077,0.0026201871,0.000115025156,0.00011156486],"about_ca_topic_score_codex":0.0000037922225,"about_ca_topic_score_gemma":0.000002890685,"teacher_disagreement_score":0.8388386,"about_ca_system_score_codex":0.00005778794,"about_ca_system_score_gemma":0.000016947382,"threshold_uncertainty_score":0.3498139},"labels":[],"label_agreement":null},{"id":"W3143498588","doi":"","title":"Feature point correspondence between consecutive frames based on genetic algorithm","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Computer science; Algorithm; Point (geometry); Artificial intelligence; Pattern recognition (psychology); Genetic algorithm; Machine learning; Mathematics; Linguistics","score_opus":0.005883528618012175,"score_gpt":0.24461931679570054,"score_spread":0.23873578817768837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143498588","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":[0.011343081,0.000135311,0.9861335,0.0018449767,0.0001673094,0.000047511083,0.000017201994,0.00006458352,0.0002465007],"genre_scores_gemma":[0.75076663,0.000023140665,0.24889348,0.000071148694,0.00019052088,0.0000017896093,0.000011288864,0.000008965032,0.00003303566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947625,0.000009754139,0.00017876018,0.000055056098,0.00021808989,0.00006209549],"domain_scores_gemma":[0.9995243,0.00006929544,0.00011717696,0.000045872832,0.00021828832,0.00002504965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000082077175,0.00007415867,0.000087203734,0.00013872306,0.000031347456,0.00009078123,0.00011724444,0.0000498479,0.0000059276917],"category_scores_gemma":[0.00001658749,0.00006733071,0.00003327425,0.00005858288,0.00002597993,0.00009707863,0.000009087064,0.00013372525,0.000002219661],"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":[0.000019367537,0.00009171875,0.0026085714,0.00003335394,0.000081977465,0.000052276475,0.000105016494,0.7478342,0.0026514304,0.0026081759,0.013228699,0.23068522],"study_design_scores_gemma":[0.00026093767,0.000051122912,0.024117406,0.00014148113,0.000019960737,0.000048434555,0.000010744252,0.964424,0.003672237,0.005835427,0.0013200404,0.00009821226],"about_ca_topic_score_codex":0.0000025691904,"about_ca_topic_score_gemma":2.5390347e-7,"teacher_disagreement_score":0.7394236,"about_ca_system_score_codex":0.000049788257,"about_ca_system_score_gemma":0.00002249362,"threshold_uncertainty_score":0.27456665},"labels":[],"label_agreement":null},{"id":"W3144562320","doi":"10.5555/1165139.1165141","title":"A multi-agent architecture for robotic systems in real-time environments","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Architecture; Distributed computing; Multi-agent system; Agent architecture; Computer architecture; Embedded system; Real-time computing; Artificial intelligence","score_opus":0.015702238508529694,"score_gpt":0.2646063850324099,"score_spread":0.2489041465238802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3144562320","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":[0.004292348,0.00008137134,0.99367124,0.0013719826,0.00037503534,0.00015202888,0.0000016115318,0.000011903963,0.00004250733],"genre_scores_gemma":[0.5731827,0.00012835531,0.42608273,0.000056499535,0.0001384041,0.0000066944503,0.000012265175,0.000009055425,0.0003833196],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990711,0.00004285673,0.00038174074,0.00009931762,0.0003056624,0.000099289755],"domain_scores_gemma":[0.9994629,0.00007698246,0.00025397632,0.00006396801,0.0001102149,0.000031937405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030029783,0.00006902075,0.00011528921,0.0002359551,0.000029064788,0.00018131502,0.00027251852,0.000035715882,0.000002171248],"category_scores_gemma":[0.00003496151,0.00006006759,0.000039760034,0.00006501365,0.000014826447,0.00027711442,0.000044481483,0.00006556291,0.0000028912007],"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":[0.000005127961,0.00008752377,0.00027130792,0.0000075204607,0.000015345991,0.000008154633,0.00010792398,0.9868622,0.0031200822,0.0073776892,0.00011305999,0.0020240685],"study_design_scores_gemma":[0.0006843642,0.000055333938,0.006649815,0.00007626006,0.0000035959658,0.000050980765,0.000007657775,0.9907373,0.00005607511,0.0013193411,0.0002977622,0.00006150892],"about_ca_topic_score_codex":0.000023296376,"about_ca_topic_score_gemma":0.000004054719,"teacher_disagreement_score":0.56889033,"about_ca_system_score_codex":0.000080933925,"about_ca_system_score_gemma":0.000030532847,"threshold_uncertainty_score":0.2449485},"labels":[],"label_agreement":null},{"id":"W3147166570","doi":"10.5555/1750496.1750503","title":"Kinematics-based characterization of the collision course","year":2008,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Collision; Course (navigation); Object (grammar); Motion (physics); Characterization (materials science); Kinematics equations; Computer science; Mobile robot; Robot kinematics; Artificial intelligence; Computer vision; Physics; Robot; Classical mechanics; Astronomy; Computer security; Optics","score_opus":0.014691747760442532,"score_gpt":0.2525867213101402,"score_spread":0.23789497354969769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3147166570","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":[0.24893883,0.000016929933,0.7475527,0.0024603356,0.0009477702,0.000048214493,0.000002588159,0.000010134768,0.000022538075],"genre_scores_gemma":[0.8701021,0.000022286304,0.12965979,0.00011028251,0.00007537424,4.3353046e-7,0.000003076583,0.0000035923,0.000023063925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988628,0.00004685845,0.00040204133,0.000065521956,0.0005639603,0.000058826074],"domain_scores_gemma":[0.99846876,0.00007309331,0.0007219492,0.000120471304,0.0005843607,0.000031390045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002439338,0.0000632844,0.00011732644,0.00010464668,0.000059253933,0.00004426938,0.0004912771,0.00003448581,0.0000015077982],"category_scores_gemma":[0.00009497236,0.000044527907,0.00005386558,0.00013788107,0.00004629502,0.0003187117,0.000057300287,0.000078018726,9.43891e-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":[0.000027441898,0.00045776286,0.017834453,0.000047551104,0.00015403067,0.000085613625,0.0018562985,0.90396214,0.046241533,0.014342502,0.00037863862,0.014612031],"study_design_scores_gemma":[0.0003771908,0.000050921735,0.1463249,0.00015874748,0.000010053505,0.00022236245,0.0000052711835,0.84721214,0.0052335477,0.0003221613,0.0000343219,0.000048368518],"about_ca_topic_score_codex":0.0000015593204,"about_ca_topic_score_gemma":7.8088554e-8,"teacher_disagreement_score":0.62116325,"about_ca_system_score_codex":0.000029331044,"about_ca_system_score_gemma":0.0001323263,"threshold_uncertainty_score":0.18157953},"labels":[],"label_agreement":null},{"id":"W3147282787","doi":"10.5555/1164085.1164091","title":"Exact linearization and sliding mode observer for a quadrotor unmanned aerial vehicle","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Linearization; Feedback linearization; Observer (physics); Mode (computer interface); Computer science; Physics; Artificial intelligence; Nonlinear system; Control (management)","score_opus":0.011865598899562037,"score_gpt":0.2474265275974805,"score_spread":0.23556092869791845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3147282787","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":[0.49327677,0.00019808926,0.50514483,0.0003117032,0.00085207395,0.00013236233,0.000014626084,0.000031915206,0.0000376443],"genre_scores_gemma":[0.9854775,0.000026604019,0.013467478,0.000012235659,0.000958861,0.0000027529304,0.000016102087,0.000014634577,0.000023819845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993655,0.0000128438005,0.00032863492,0.000055580185,0.00016739682,0.00007002067],"domain_scores_gemma":[0.99945235,0.00006907767,0.00015407524,0.000028693956,0.00026706595,0.000028735583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014188614,0.00007472589,0.0001231244,0.000099253106,0.000029123285,0.0000976155,0.00006135566,0.000046415964,0.00000177182],"category_scores_gemma":[0.000049218124,0.00007105598,0.00003778246,0.000028884744,0.000007501844,0.00028920182,0.000010308464,0.0000506353,5.9430255e-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":[0.000082905,0.000034377816,0.0015567726,0.000047155292,0.00012815636,0.0000064728147,0.00012282566,0.94140005,0.0447523,0.006712878,0.0002856217,0.004870478],"study_design_scores_gemma":[0.0010648429,0.000052016545,0.007486136,0.000068370646,0.000019549007,0.00002636597,0.000016316722,0.98894733,0.00095609896,0.00071998086,0.0005691576,0.000073817624],"about_ca_topic_score_codex":0.000010966739,"about_ca_topic_score_gemma":0.000010102294,"teacher_disagreement_score":0.49220073,"about_ca_system_score_codex":0.000055164764,"about_ca_system_score_gemma":0.000013320598,"threshold_uncertainty_score":0.2897579},"labels":[],"label_agreement":null},{"id":"W3147578001","doi":"10.5555/1739829.1739837","title":"Integral sliding mode control of a bipedal leap","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Mode (computer interface); Control (management); Dynamics (music); Computer science; Humanoid robot; Sliding mode control; Physics; Nonlinear system; Artificial intelligence; Acoustics; Operating system; Robot","score_opus":0.00667414474484851,"score_gpt":0.24613987276132968,"score_spread":0.23946572801648117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3147578001","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":[0.10315223,0.00015452347,0.89494956,0.00035840628,0.0008679177,0.000040551153,0.0000028608194,0.000023442182,0.00045050835],"genre_scores_gemma":[0.99284154,0.000052848034,0.0068366323,0.000042656193,0.00019973493,2.821301e-7,0.0000017480708,0.000008372833,0.000016204873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991221,0.0000113811775,0.00047016828,0.000040417937,0.00026988517,0.00008609342],"domain_scores_gemma":[0.99936473,0.00007636329,0.00018286925,0.000037985512,0.00028706877,0.000050950584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031837693,0.000072784074,0.00015054274,0.00021741957,0.000014482809,0.000032884618,0.000116622046,0.000044470577,0.000012887288],"category_scores_gemma":[0.00005268848,0.000063689324,0.00006876175,0.000050311017,0.000015905693,0.00018565916,0.000008175,0.000110748435,0.000001498513],"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":[0.000063703104,0.000055650642,0.0019619802,0.000023422093,0.00027604913,0.000023568731,0.00041527877,0.8906939,0.022893643,0.024038834,0.00013067899,0.05942328],"study_design_scores_gemma":[0.0015006779,0.00006585531,0.0066271196,0.000100806,0.000033108605,0.000121580146,0.0001251888,0.98720956,0.002768947,0.0011717315,0.00019199241,0.00008343853],"about_ca_topic_score_codex":0.000003925981,"about_ca_topic_score_gemma":0.0000036280362,"teacher_disagreement_score":0.88968927,"about_ca_system_score_codex":0.000051970914,"about_ca_system_score_gemma":0.000015678088,"threshold_uncertainty_score":0.25971752},"labels":[],"label_agreement":null},{"id":"W3148022066","doi":"10.5555/1164085.1164088","title":"A constructive methodology of Lyapunov function of composite systems with nonlinear interconnection term","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Lyapunov function; Interconnection; Term (time); Nonlinear system; Constructive; Composite number; Computer science; Control theory (sociology); Mathematics; Control (management); Algorithm; Artificial intelligence; Telecommunications; Physics; Process (computing)","score_opus":0.013641004420319134,"score_gpt":0.25634121068136795,"score_spread":0.24270020626104882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148022066","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":[0.21163535,0.000064003005,0.78730226,0.00011186191,0.0007279638,0.00005534623,0.0000035559037,0.000008153092,0.00009149724],"genre_scores_gemma":[0.84738934,0.0000069441703,0.1524426,0.000007544307,0.00013641902,6.597801e-7,0.0000030823223,0.00000284168,0.000010594124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990572,0.00011232959,0.00045566968,0.00007962959,0.00024340955,0.000051796284],"domain_scores_gemma":[0.9982177,0.0001692321,0.00084070524,0.00006401414,0.000689455,0.000018920424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042262016,0.000067739966,0.0001878594,0.00023730496,0.00002126729,0.000042226016,0.00018606512,0.000038298,0.0000020856141],"category_scores_gemma":[0.000020965364,0.000052629908,0.00004351965,0.00009742965,0.00006522358,0.0003726758,0.000036015066,0.00007282382,2.5508268e-7],"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":[0.0004425022,0.0003694596,0.00928624,0.0001508262,0.000580611,0.000026432086,0.0008018431,0.22349167,0.050846446,0.6565178,0.000036292662,0.057449903],"study_design_scores_gemma":[0.002709653,0.0014146382,0.042926766,0.0007985408,0.00011557709,0.0016778044,0.0002898602,0.8975479,0.02189246,0.030264251,0.0001300282,0.00023252283],"about_ca_topic_score_codex":0.000018825995,"about_ca_topic_score_gemma":0.0000016264944,"teacher_disagreement_score":0.67405623,"about_ca_system_score_codex":0.00002464006,"about_ca_system_score_gemma":0.000034991386,"threshold_uncertainty_score":0.21461853},"labels":[],"label_agreement":null},{"id":"W3148646278","doi":"10.5555/1739829.1739835","title":"View-invariant human activity recognition based on shape and motion features","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Invariant (physics); Computer vision; Computer science; Focus (optics); Activity recognition; Human motion; Pattern recognition (psychology); Motion (physics); Mathematics","score_opus":0.022934384190924924,"score_gpt":0.2847754715261749,"score_spread":0.26184108733524997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148646278","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":[0.3444562,0.000027005937,0.65131116,0.0023795352,0.0006786224,0.000079614845,0.0000034221396,0.000039763112,0.0010246648],"genre_scores_gemma":[0.9907923,0.000034625093,0.008533582,0.00038879242,0.00021966195,5.8466804e-7,0.000009042493,0.000004565825,0.00001688608],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991299,0.00004276446,0.00025592666,0.00012200439,0.00036606632,0.00008337112],"domain_scores_gemma":[0.999136,0.00009450344,0.00034252426,0.000059212252,0.00030496067,0.00006284074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056043296,0.0000851753,0.000097368786,0.00033671845,0.000101304024,0.00022209373,0.00013087406,0.000056422054,0.000016288264],"category_scores_gemma":[0.000050850722,0.00007629364,0.00004200268,0.00007388829,0.000020425377,0.00057199656,0.000025471401,0.00014428316,0.0000033864858],"study_design_candidate":"design_other","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":[0.00004516423,0.0001896934,0.00025822732,0.000014429532,0.000039360228,0.000040403713,0.00014925387,0.0012276989,0.013385405,0.0070263552,0.00012804718,0.97749597],"study_design_scores_gemma":[0.0023953672,0.0007488746,0.43564472,0.00051212095,0.000048685033,0.00054653996,0.00004323381,0.5101168,0.02870715,0.020278307,0.0005853969,0.00037277286],"about_ca_topic_score_codex":0.0000049978935,"about_ca_topic_score_gemma":0.000007817957,"teacher_disagreement_score":0.9771232,"about_ca_system_score_codex":0.000051749128,"about_ca_system_score_gemma":0.000018369617,"threshold_uncertainty_score":0.31111643},"labels":[],"label_agreement":null},{"id":"W3150349000","doi":"10.5555/1739807.1739809","title":"Development of multi-directional compliant joint module for human-care robot","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Joint (building); Robot; Computer science; Development (topology); Engineering; Simulation; Artificial intelligence; Structural engineering; Mathematics","score_opus":0.052309296395449914,"score_gpt":0.3241966720793265,"score_spread":0.2718873756838766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150349000","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":[0.06889487,0.0000739557,0.9300711,0.0003575939,0.00048980035,0.00004894701,0.0000018383206,0.000024004701,0.00003786004],"genre_scores_gemma":[0.54758954,0.0000020916762,0.45234817,0.000012670751,0.000032913515,5.4913363e-7,0.0000026636608,0.0000021693827,0.000009244873],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9990779,0.000007981261,0.00047675456,0.00009156454,0.0002597307,0.00008605611],"domain_scores_gemma":[0.9986164,0.000042842155,0.000439152,0.00005633351,0.0008132879,0.000031979354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037464715,0.00006667541,0.00012598594,0.00025220713,0.00007497257,0.000039655475,0.0002621894,0.000042162657,0.0000013783579],"category_scores_gemma":[0.00004034825,0.00005979443,0.000054143464,0.00005866001,0.00003002725,0.00014820306,0.000057243444,0.00007283574,6.4084315e-7],"study_design_candidate":"design_other","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":[0.00004426099,0.0006235709,0.0050344793,0.00009950807,0.00039697337,0.000027122896,0.0026836526,0.039962705,0.14610136,0.18568175,0.00015185983,0.6191928],"study_design_scores_gemma":[0.0031465092,0.00034673366,0.60523504,0.0004565279,0.00003101308,0.00029956468,0.00045391047,0.23429753,0.14587101,0.007834202,0.0016825349,0.00034539803],"about_ca_topic_score_codex":0.0000020389502,"about_ca_topic_score_gemma":0.000009740359,"teacher_disagreement_score":0.61884737,"about_ca_system_score_codex":0.00007862438,"about_ca_system_score_gemma":0.000052864812,"threshold_uncertainty_score":0.24383461},"labels":[],"label_agreement":null},{"id":"W3150475574","doi":"10.5555/1739829.1739831","title":"Application and comparison of passivity-based and integrator backstepping control methods for trajectory tracking of rigid-link robot manipulators incorporating motor dynamics","year":2007,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Backstepping; Control theory (sociology); Passivity; Integrator; Trajectory; Computer science; Tracking (education); Link (geometry); Control engineering; Dynamics (music); Robot manipulator; Control (management); Engineering; Adaptive control; Artificial intelligence; Physics; Psychology","score_opus":0.013180749449397393,"score_gpt":0.30524861095576905,"score_spread":0.29206786150637165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150475574","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":[0.12527592,0.00028095648,0.8738891,0.00010512381,0.0002561141,0.00016301351,0.000009399664,0.000012561603,0.00000779932],"genre_scores_gemma":[0.89669245,0.00001300327,0.10318347,0.000008871016,0.000079551544,0.0000025167542,0.000006983003,0.00001243861,7.139471e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988226,0.00003728614,0.0007953245,0.000080978265,0.00018251421,0.000081289676],"domain_scores_gemma":[0.99841374,0.00044103476,0.00067808543,0.0000432096,0.00036759555,0.00005634872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010404651,0.000105182386,0.00033594522,0.00018564975,0.000029230287,0.00004032084,0.000086181695,0.00008556369,2.9065325e-7],"category_scores_gemma":[0.00010253049,0.00009759931,0.0000635948,0.000052315034,0.000028952732,0.0001349833,0.00000965007,0.00012339061,1.9717243e-8],"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":[0.00012991489,0.000063505395,0.012095763,0.0003155363,0.00026564367,0.0000010541979,0.00015124242,0.47476327,0.12911795,0.020140486,0.0000012335734,0.3629544],"study_design_scores_gemma":[0.0010642519,0.0001466793,0.0081847785,0.00018320557,0.000056696616,0.000008649736,0.00012228405,0.98678106,0.0021580483,0.0011989041,0.0000134152415,0.0000820394],"about_ca_topic_score_codex":0.000008406207,"about_ca_topic_score_gemma":0.000021501135,"teacher_disagreement_score":0.77141654,"about_ca_system_score_codex":0.00008447115,"about_ca_system_score_gemma":0.000019290905,"threshold_uncertainty_score":0.39799845},"labels":[],"label_agreement":null},{"id":"W3152973102","doi":"10.2316/j.2021.206-0467","title":"MODELLING OF ROBOTIC MANTA RAY PROPELLED BY SERVO-ACTUATED PECTORAL FINS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Pectoral muscle; Servo; Marine engineering; Anatomy; Artificial intelligence; Biology; Engineering","score_opus":0.02068454027639473,"score_gpt":0.23144368855253597,"score_spread":0.21075914827614123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152973102","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":[0.19330268,0.000658444,0.8049933,0.00026710777,0.00060221343,0.000036164674,0.0000053867843,0.000018199484,0.00011652288],"genre_scores_gemma":[0.9829779,0.00068878074,0.016101055,0.000018098988,0.00007562821,4.1222708e-7,0.000018295561,0.0000139472995,0.00010584198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905604,0.000019630415,0.00045698514,0.00007324889,0.00030604575,0.0000880228],"domain_scores_gemma":[0.99922633,0.00003037062,0.00016643829,0.00006560544,0.0004641411,0.000047135458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011749252,0.00009425548,0.00018284706,0.00009261069,0.000020485773,0.0000624334,0.00013703194,0.000048325233,0.00005947664],"category_scores_gemma":[0.00002482378,0.00008525093,0.00006056676,0.000077614284,0.000017480761,0.00019483418,0.000023362749,0.000119582335,0.0000024756248],"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":[0.000007491429,0.00003637498,0.00013414411,0.00003132944,0.00011006194,0.000023058412,0.00015918678,0.98653185,0.009805827,0.000367225,0.00034243078,0.00245102],"study_design_scores_gemma":[0.00024525542,0.000030399451,0.00019457331,0.00013351261,0.000025103562,0.00008470855,0.000036043846,0.98181105,0.0168476,0.00037249865,0.00013217215,0.00008708889],"about_ca_topic_score_codex":0.0000074250297,"about_ca_topic_score_gemma":0.0000023385887,"teacher_disagreement_score":0.7896753,"about_ca_system_score_codex":0.000042460273,"about_ca_system_score_gemma":0.000034303037,"threshold_uncertainty_score":0.3476432},"labels":[],"label_agreement":null},{"id":"W3153110208","doi":"10.2316/j.2021.206-0625","title":"VEHICLE TYPE DETECTION BASED ON RETINANET WITH ADAPTIVE LEARNING RATE ATTENUATION","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Attenuation; Computer science; Type (biology); Artificial intelligence; Control theory (sociology); Algorithm; Physics; Geology; Optics","score_opus":0.018109055354126945,"score_gpt":0.27160647209840155,"score_spread":0.2534974167442746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153110208","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":[0.09228428,0.00003298765,0.9054448,0.0015962493,0.00046305332,0.000021195467,2.724487e-7,0.000019720817,0.00013742069],"genre_scores_gemma":[0.9365314,0.000020815321,0.06318545,0.00014954418,0.0000841133,3.2851366e-7,0.0000025486784,0.0000040080026,0.000021797021],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992177,0.00016189396,0.00017393172,0.000098204895,0.00029001734,0.000058285645],"domain_scores_gemma":[0.9986739,0.00016703912,0.00026056715,0.00006113072,0.0008103711,0.000026946516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051397027,0.00005660054,0.0000807473,0.00010291979,0.000054210686,0.00014270323,0.000109426976,0.000027672286,0.0000028527131],"category_scores_gemma":[0.0001875505,0.000047153088,0.000023094524,0.00015368445,0.000011255331,0.0002931562,0.000017870116,0.00013197512,0.0000024447154],"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":[0.00012841617,0.00006011872,0.004619355,0.0000058203486,0.0000638803,0.00011170478,0.00018040091,0.8075946,0.007689829,0.003476805,0.000016046864,0.176053],"study_design_scores_gemma":[0.0004934381,0.00039799057,0.06829145,0.00010068474,0.00000834242,0.00008909865,0.000018797435,0.92140126,0.008109552,0.00085477607,0.00016812797,0.00006645395],"about_ca_topic_score_codex":0.0000022287795,"about_ca_topic_score_gemma":0.0000041876897,"teacher_disagreement_score":0.8442471,"about_ca_system_score_codex":0.000040853763,"about_ca_system_score_gemma":0.00007573163,"threshold_uncertainty_score":0.19228472},"labels":[],"label_agreement":null},{"id":"W3154784987","doi":"10.2316/j.2021.206-0613","title":"FEATURE EXTRACTION OF MOTOR IMAGERY EEG SIGNALS BASED ON MULTI-SCALE RECURRENCE PLOT AND SDA","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Administration of Surveying, Mapping and Geoinformation of China; Wuhan University of Technology; Wuhan University","keywords":"Motor imagery; Electroencephalography; Artificial intelligence; Pattern recognition (psychology); Computer science; Plot (graphics); Feature extraction; Scale (ratio); Recurrence plot; Class (philosophy); Psychology; Mathematics; Geography; Cartography; Statistics; Brain–computer interface; Neuroscience; Physics","score_opus":0.018315555287318198,"score_gpt":0.2911296863332035,"score_spread":0.2728141310458853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154784987","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":[0.055020586,0.00023923976,0.9349316,0.009207346,0.00048035124,0.000056533427,0.000008026036,0.000013304669,0.000043013566],"genre_scores_gemma":[0.8542738,0.00016456208,0.14522745,0.00019018569,0.00008048733,0.0000012975177,0.000004182553,0.000003511074,0.00005451065],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992902,0.000035295838,0.00022193044,0.00011416394,0.00028068924,0.000057710455],"domain_scores_gemma":[0.998924,0.00014889197,0.0003309501,0.00008424048,0.00046532354,0.000046585457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015356968,0.00006529308,0.00010433097,0.000095636125,0.00004132739,0.00012494379,0.0001638848,0.00003595997,0.00000352134],"category_scores_gemma":[0.00004627209,0.000057058165,0.000044190238,0.00010315143,0.000022988525,0.00033865936,0.00003784304,0.000119897886,6.4290793e-7],"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":[0.000092533766,0.0010631214,0.0040502506,0.00008477454,0.0001386377,0.0001282121,0.00039577484,0.2813644,0.37895206,0.017359346,0.0029578202,0.31341308],"study_design_scores_gemma":[0.00038260288,0.000080293816,0.033701032,0.00017848556,0.000009897014,0.00011608849,0.000013485513,0.956099,0.008161762,0.0008024629,0.00038530005,0.0000696217],"about_ca_topic_score_codex":0.0000013925264,"about_ca_topic_score_gemma":0.0000015002574,"teacher_disagreement_score":0.7992532,"about_ca_system_score_codex":0.000019298846,"about_ca_system_score_gemma":0.000048349175,"threshold_uncertainty_score":0.23267643},"labels":[],"label_agreement":null},{"id":"W3155007818","doi":"10.2316/j.2021.206-0615","title":"AN IMPROVED BOOSTING-BIPLS MODELS BASED ON WEIGHT ADJUSTMENT FOR SOIL HEAVY METAL CONTENT PREDICTION","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Agriculture, Soil, Plant Science","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Boosting (machine learning); Content (measure theory); Heavy metals; Environmental science; Soil science; Computer science; Artificial intelligence; Mathematics; Environmental chemistry; Chemistry; Mathematical analysis","score_opus":0.03139711497446079,"score_gpt":0.23839397615468508,"score_spread":0.20699686118022428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155007818","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":[0.958163,0.00023229288,0.03356197,0.005842065,0.001618726,0.00022817665,0.00020307655,0.000040057323,0.0001105979],"genre_scores_gemma":[0.99509084,0.00005944577,0.003714365,0.00039226643,0.0005277669,0.0000045843385,0.00016470869,9.388118e-7,0.000045054603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989338,0.00004298805,0.00033459326,0.00015701276,0.00041931504,0.00011228573],"domain_scores_gemma":[0.99872607,0.00014303313,0.00031229304,0.000028206032,0.00070197444,0.000088395704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028749052,0.00009656871,0.00012937721,0.000025183585,0.0001007823,0.00012229354,0.00016657209,0.000056942696,0.0000053256135],"category_scores_gemma":[0.00007651869,0.00004006798,0.00008786877,0.00007462631,0.000020854122,0.00042508254,0.000018190709,0.000079358055,6.411879e-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":[0.00040781143,0.0011480855,0.0025263403,0.000020096279,0.00019236273,0.000031077998,0.00021967432,0.61262536,0.26135293,0.0063039847,0.0008265865,0.11434574],"study_design_scores_gemma":[0.00047465335,0.0006274796,0.037747398,0.00007507654,0.000037521302,0.00007571598,0.00012860558,0.94815105,0.011043531,0.0013533783,0.00018912426,0.00009646463],"about_ca_topic_score_codex":0.000011876827,"about_ca_topic_score_gemma":0.000034607594,"teacher_disagreement_score":0.33552572,"about_ca_system_score_codex":0.000056497105,"about_ca_system_score_gemma":0.000028861434,"threshold_uncertainty_score":0.16339247},"labels":[],"label_agreement":null},{"id":"W3155356553","doi":"10.2316/j.2021.206-0619","title":"CLUSTERING ROUTING PROTOCOL BASED ON GAME THEORY IN WIRELESS SENSOR NETWORKS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wireless Routing Protocol; Computer science; Cluster analysis; Computer network; Routing protocol; Zone Routing Protocol; Wireless sensor network; Dynamic Source Routing; Protocol (science); Routing (electronic design automation); Artificial intelligence; Medicine","score_opus":0.010335839036091431,"score_gpt":0.261276493578177,"score_spread":0.2509406545420856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155356553","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":[0.008893989,0.000007591954,0.9886042,0.0009418553,0.00059683766,0.00067577284,2.889483e-7,0.00002400439,0.00025547342],"genre_scores_gemma":[0.952019,0.0000055674204,0.04735834,0.00032703724,0.00019324796,0.000063041865,0.0000018533668,0.000008747212,0.000023156943],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867624,0.00016050614,0.00044729214,0.00015411136,0.0004231835,0.00013864481],"domain_scores_gemma":[0.9988765,0.00027498466,0.00036600165,0.00012277035,0.00031100525,0.00004871651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005616183,0.000100549965,0.00014460356,0.00019138065,0.000033569915,0.00024545557,0.00031543823,0.000061395316,0.0000037162808],"category_scores_gemma":[0.000081727085,0.000092694165,0.00005484583,0.00018196303,0.000018505752,0.00024684274,0.00009458996,0.00021685747,6.97878e-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":[0.000025805468,0.00007585133,0.0006209809,0.0000054763163,0.000012900343,0.0001593628,0.000078853285,0.9561488,0.00016454376,0.013145709,0.00000644872,0.029555261],"study_design_scores_gemma":[0.00080673303,0.000048013226,0.0037482504,0.00040353942,0.000002734033,0.00010779257,0.000019640896,0.994064,0.00040004821,0.00027171793,0.00003708136,0.00009049963],"about_ca_topic_score_codex":0.0000013971606,"about_ca_topic_score_gemma":0.000004293792,"teacher_disagreement_score":0.943125,"about_ca_system_score_codex":0.000095961215,"about_ca_system_score_gemma":0.00006864061,"threshold_uncertainty_score":0.37799582},"labels":[],"label_agreement":null},{"id":"W3157700977","doi":"10.2316/j.2021.206-0598","title":"CAPABILITY ITERATION NETWORK FOR ROBOT PATH PLANNING","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Computer science; Convergence (economics); Path (computing); Robot; Artificial intelligence; Kernel (algebra); Mathematical optimization; Machine learning; Mathematics","score_opus":0.010741086931893509,"score_gpt":0.2474021370204753,"score_spread":0.2366610500885818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157700977","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":[0.02601036,0.0004649525,0.97056603,0.001024725,0.0016833189,0.00006184421,0.0000043430236,0.000031643114,0.00015280346],"genre_scores_gemma":[0.94806796,0.000057479356,0.051140487,0.000106746156,0.00056329044,0.0000023766613,0.000023250552,0.000009003307,0.000029428746],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934167,0.000019609397,0.00032994358,0.00005783717,0.00017086556,0.00008008955],"domain_scores_gemma":[0.99930817,0.00007674102,0.00010738903,0.00004449783,0.000422893,0.000040330207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020173397,0.00006650663,0.00011709995,0.000045954013,0.000036291643,0.000112947186,0.00006487549,0.000040846877,0.000013133288],"category_scores_gemma":[0.00006989062,0.000064009444,0.00006053971,0.000043250777,0.000008598628,0.00020292695,0.0000091302045,0.00007359202,8.784875e-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":[0.000008471891,0.00001694184,0.00081933825,0.000015093019,0.000074576776,0.000008863693,0.00013210534,0.9822987,0.0012121188,0.0031080272,0.000805281,0.01150049],"study_design_scores_gemma":[0.0007259999,0.00003314111,0.010808057,0.00010583495,0.000025308382,0.00010497158,0.000047859583,0.9824566,0.00042915787,0.00396259,0.0012200769,0.00008035701],"about_ca_topic_score_codex":4.3152303e-7,"about_ca_topic_score_gemma":9.669579e-7,"teacher_disagreement_score":0.92205757,"about_ca_system_score_codex":0.000052660092,"about_ca_system_score_gemma":0.00002866873,"threshold_uncertainty_score":0.26102293},"labels":[],"label_agreement":null},{"id":"W3164381974","doi":"10.2316/j.2021.206-0564","title":"ASSEMBLY AUTOMATION – AN EFFICIENT APPROACH TO FIND OPTIMAL PARAMETERS FOR PART FEEDERS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Automation; Computer science; Engineering; Mechanical engineering","score_opus":0.014408983694235543,"score_gpt":0.252612085026232,"score_spread":0.23820310133199646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164381974","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":[0.13580686,0.000069346075,0.8625486,0.00029667467,0.0009275876,0.00014608499,0.0000091931,0.000048920258,0.00014673738],"genre_scores_gemma":[0.6930869,0.00001405194,0.30661142,0.00004686532,0.00014997282,0.000009274791,0.000044288154,0.000016744658,0.000020443707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990252,0.000026733238,0.00042822832,0.00011047463,0.00029650255,0.00011284422],"domain_scores_gemma":[0.9990409,0.00006379895,0.00017311114,0.00007313798,0.00056364905,0.00008540752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022797346,0.00010349446,0.00015908416,0.0001604433,0.000041724466,0.00016496038,0.00011043821,0.000055837045,0.0000014618875],"category_scores_gemma":[0.00012426425,0.00010619037,0.000057319285,0.000090299094,0.000008489684,0.00031724168,0.0000137693705,0.00006577354,0.0000011579596],"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":[0.00001534043,0.000044924323,0.000017461258,0.000018850438,0.000078195364,0.0000022115153,0.0002277848,0.9881769,0.0030393286,0.0014791206,0.00014811425,0.006751794],"study_design_scores_gemma":[0.0006317316,0.000059828642,0.0008292777,0.00006314612,0.000026480418,0.00008045714,0.00019909407,0.99669594,0.0009794047,0.00013395099,0.00019079215,0.00010987965],"about_ca_topic_score_codex":9.703592e-7,"about_ca_topic_score_gemma":8.3951795e-7,"teacher_disagreement_score":0.5572801,"about_ca_system_score_codex":0.00014395238,"about_ca_system_score_gemma":0.000034544628,"threshold_uncertainty_score":0.43303174},"labels":[],"label_agreement":null},{"id":"W3165252354","doi":"","title":"Biped Robot Driven By Single Actuator","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Actuator; Robot; Humanoid robot; Computer science; Control theory (sociology); Joint (building); Control engineering; Control (management); Engineering; Artificial intelligence","score_opus":0.010228602930316846,"score_gpt":0.22269499421198535,"score_spread":0.2124663912816685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165252354","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":[0.14073399,0.00024075463,0.85623145,0.0014155939,0.0010881118,0.000035546465,0.00000872979,0.000041600084,0.00020423],"genre_scores_gemma":[0.99070764,0.00036836445,0.00863208,0.000036869485,0.00015578259,4.994164e-7,0.0000023303926,0.000011442712,0.00008499027],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933946,0.000009990505,0.00027938673,0.0000542122,0.00023759488,0.00007935822],"domain_scores_gemma":[0.99956536,0.00004826711,0.0001073851,0.000047385958,0.00017680589,0.000054804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008491321,0.00007510456,0.00009808214,0.0000939164,0.000017032804,0.00005860417,0.00014431393,0.000039797178,0.00005030526],"category_scores_gemma":[0.000043175543,0.000051499886,0.000039000282,0.000031207706,0.000020205003,0.00025684896,0.000015470769,0.00005182578,0.000009930814],"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":[0.000017318065,0.00008452403,0.0009121331,0.000015369951,0.00024009343,0.000024331026,0.000236917,0.11244706,0.5392138,0.002048815,0.004973826,0.3397858],"study_design_scores_gemma":[0.0031351214,0.0006394036,0.01307729,0.0011639358,0.0001227546,0.00077437604,0.00013537492,0.61596507,0.33019304,0.007303059,0.026437877,0.0010526729],"about_ca_topic_score_codex":0.0000011054674,"about_ca_topic_score_gemma":0.0000010238182,"teacher_disagreement_score":0.8499737,"about_ca_system_score_codex":0.00006543128,"about_ca_system_score_gemma":0.000009563686,"threshold_uncertainty_score":0.21001044},"labels":[],"label_agreement":null},{"id":"W3165609087","doi":"10.2316/j.2021.206-0486","title":"A GLOBAL PATH PLANNING ALGORITHM FOR MANNED SUBMERSIBLE BASED ON IMPROVED ANT COLONY ALGORITHMS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Computer science; Algorithm; Ant colony optimization algorithms; Motion planning; Artificial intelligence; Computer network; Robot","score_opus":0.010477962241403158,"score_gpt":0.2590737295580777,"score_spread":0.24859576731667457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165609087","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018150588,0.00012277893,0.9965075,0.00023784689,0.0010661765,0.000058706246,0.00004568438,0.000037834372,0.00010840092],"genre_scores_gemma":[0.49294615,0.00006307682,0.5065676,0.00008837822,0.00022517644,0.000002959489,0.000072203446,0.00001263145,0.000021847403],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939585,0.000009756451,0.00024261435,0.000079063255,0.00017520087,0.000097526376],"domain_scores_gemma":[0.9993919,0.00006944393,0.00012499832,0.00004544141,0.0003223167,0.000045900284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103222046,0.00008798509,0.00011626771,0.0000752772,0.00003966604,0.00007632202,0.0000720751,0.000049089173,0.0000032686544],"category_scores_gemma":[0.000066833025,0.00008656688,0.000049088037,0.000053197582,0.000011224365,0.00011546341,0.000010380982,0.00006536205,3.1826676e-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":[0.000016311302,0.000029577523,0.000045930083,0.000013139535,0.000047290705,0.00002553372,0.000023606834,0.9590478,0.000111130634,0.00028847368,0.0001616471,0.040189546],"study_design_scores_gemma":[0.00087298796,0.00009991775,0.0008779677,0.00008663938,0.000021567052,0.000042696425,0.000036539757,0.99521375,0.0011279554,0.0011917711,0.0003392478,0.000088955254],"about_ca_topic_score_codex":9.604987e-7,"about_ca_topic_score_gemma":4.779866e-7,"teacher_disagreement_score":0.49113107,"about_ca_system_score_codex":0.00012432778,"about_ca_system_score_gemma":0.00003823061,"threshold_uncertainty_score":0.35300946},"labels":[],"label_agreement":null},{"id":"W3167166853","doi":"10.37628/ijra.v6i2.1172","title":"A Survey on Flood Alert System Using IoT","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flood myth; Mobile phone; GSM; Computer science; Cloud computing; Computer security; Node (physics); Phone; Computer network; Telecommunications; Engineering; Geography","score_opus":0.06260992569749331,"score_gpt":0.2889121934895253,"score_spread":0.226302267792032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167166853","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":[0.9811926,0.000012238046,0.016270231,0.0019560775,0.00044199024,0.000032705324,0.00000518333,0.000035860958,0.0000531511],"genre_scores_gemma":[0.9899821,0.0000050527765,0.009823279,0.000071250564,0.0001075543,1.5291616e-7,0.0000015032318,0.0000047763747,0.0000043043406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992185,0.00004417873,0.00023925981,0.00007405693,0.00036587415,0.00005809754],"domain_scores_gemma":[0.9996196,0.00004523326,0.00021011182,0.00004218063,0.00004280783,0.00004006452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025969988,0.00005702311,0.00008792047,0.000040254206,0.00002922977,0.00005733645,0.00020102762,0.000034560744,0.000009088784],"category_scores_gemma":[0.00014292372,0.000047844962,0.00002495735,0.000060476326,0.000030587024,0.00010277097,0.00008668166,0.00008490028,0.000015125917],"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":[0.00009800813,0.00010705106,0.21743807,0.000026601123,0.00014385498,0.0000862349,0.00084842986,0.74330497,0.01909401,0.0011441662,0.0011948175,0.016513823],"study_design_scores_gemma":[0.00058372354,0.00024713608,0.5320652,0.00017712075,0.00002093475,0.00007937083,0.00017318418,0.4577636,0.0082470635,0.00027749,0.00020646506,0.00015869502],"about_ca_topic_score_codex":0.00006081919,"about_ca_topic_score_gemma":0.0000022922866,"teacher_disagreement_score":0.31462714,"about_ca_system_score_codex":0.00012984377,"about_ca_system_score_gemma":0.000006774259,"threshold_uncertainty_score":0.1951061},"labels":[],"label_agreement":null},{"id":"W3172471931","doi":"10.2316/j.2021.206-0616","title":"A PROPRIETARILY DEVELOPED BIONIC OLFACTORY SYSTEM USED FOR RAPID DETECTION OF DETERIORATED REFRIGERATED-STORED APPLES","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Horticulture; Biology","score_opus":0.02807072326213364,"score_gpt":0.2753467540966839,"score_spread":0.24727603083455027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172471931","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":[0.89483863,0.0006971561,0.10369255,0.0001605654,0.00043075258,0.000053597607,0.000025091,0.00002944888,0.00007221265],"genre_scores_gemma":[0.99265426,0.000092008726,0.006972243,0.000010403035,0.00014809784,0.000003206865,0.00003678253,0.000011169934,0.0000718002],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99890405,0.000019257057,0.00057068403,0.000113076596,0.00030464094,0.000088271954],"domain_scores_gemma":[0.99777263,0.00008272566,0.00070445205,0.00006962747,0.0013272953,0.000043239914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017098372,0.00010218949,0.00024413632,0.00019568861,0.000053734886,0.00007326796,0.00011799419,0.00009813216,0.000035088222],"category_scores_gemma":[0.00015680808,0.00009070713,0.00009863663,0.00019509721,0.000028979004,0.00016227584,0.000020994006,0.0000962981,6.478981e-7],"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":[0.00007586361,0.00006708709,0.0008102274,0.00016503055,0.00042485513,0.000011326699,0.00013556377,0.0008663635,0.99354875,0.0002618035,0.000018050116,0.0036150822],"study_design_scores_gemma":[0.0009696573,0.00006508215,0.001533276,0.00015709171,0.00017579786,0.0001607786,0.0005256128,0.016363088,0.9795532,0.000093715884,0.00029269254,0.000109994005],"about_ca_topic_score_codex":0.0000067622705,"about_ca_topic_score_gemma":0.000007513877,"teacher_disagreement_score":0.09781566,"about_ca_system_score_codex":0.00018029237,"about_ca_system_score_gemma":0.0002068822,"threshold_uncertainty_score":0.36989295},"labels":[],"label_agreement":null},{"id":"W3172744965","doi":"10.2316/j.2021.206-0618","title":"BACK-PROPAGATION NEURAL NETWORK–BASED MODELLING FOR SOIL HEAVY METAL","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Environmental science; Heavy metals; Backpropagation; Computer science; Artificial intelligence; Environmental chemistry; Chemistry","score_opus":0.02812564992378832,"score_gpt":0.269617798033951,"score_spread":0.24149214811016265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172744965","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":[0.011415602,0.00020927787,0.9791657,0.008317845,0.00075898936,0.000066624554,0.0000025190805,0.000013473773,0.00004998797],"genre_scores_gemma":[0.71865594,0.00005811322,0.2802719,0.000451745,0.0004798238,0.0000032877026,0.000016774102,0.000006294723,0.000056136796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991351,0.000029300758,0.0003501224,0.0001248664,0.0002545674,0.000106076855],"domain_scores_gemma":[0.99875325,0.00011077371,0.00030122802,0.00009088679,0.0006918958,0.000051977393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020041203,0.00007536038,0.00011552532,0.00005862165,0.00008382408,0.00024832154,0.0002479675,0.00003347781,0.0000056184776],"category_scores_gemma":[0.000016926995,0.00006808918,0.000089809175,0.00012169474,0.000014073622,0.00046049058,0.00004655375,0.000081745406,0.0000017726207],"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":[0.0000075066987,0.000032538555,0.000031818523,0.00000503983,0.000024907187,0.0000040826517,0.000018314287,0.9532891,0.00046038462,0.032311805,0.00031748347,0.013497014],"study_design_scores_gemma":[0.00038310283,0.00004280594,0.00012147721,0.000037937025,0.00001374402,0.00007690374,0.000004299781,0.98874384,0.0014189975,0.008297119,0.00079006416,0.000069725946],"about_ca_topic_score_codex":0.0000014326648,"about_ca_topic_score_gemma":0.0000021609276,"teacher_disagreement_score":0.70724034,"about_ca_system_score_codex":0.000027400149,"about_ca_system_score_gemma":0.00007130696,"threshold_uncertainty_score":0.27765962},"labels":[],"label_agreement":null},{"id":"W3179494462","doi":"10.2316/j.2021.206-0705","title":"VIBRATION-BASED DAMAGE IDENTIFICATION OF REINFORCED CONCRETE ARCH BRIDGES USING KALMAN–ARMA–GARCH MODEL","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Arch; Structural engineering; Identification (biology); Kalman filter; Autoregressive conditional heteroskedasticity; Extended Kalman filter; Ambient vibration; Reinforced concrete; Computer science; Engineering; Mathematics; Econometrics; Artificial intelligence; Finite element method","score_opus":0.027821129570054087,"score_gpt":0.3168492571923609,"score_spread":0.2890281276223068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179494462","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":[0.6514746,0.00006314028,0.3477954,0.00020620732,0.00036157024,0.00004036858,0.000007931677,0.000032318527,0.000018443849],"genre_scores_gemma":[0.94090647,0.00008157166,0.058833983,0.000022179489,0.00011806305,8.506142e-7,0.000014297703,0.000011557162,0.000011006403],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889416,0.000023877577,0.00058727065,0.00006358187,0.0003557192,0.000075425065],"domain_scores_gemma":[0.9987842,0.00007338073,0.00028899626,0.00006929321,0.00074422336,0.00003991194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021133314,0.000075820935,0.00012999735,0.00018959059,0.0000314467,0.00005584827,0.00012525407,0.00005177809,0.0000035244884],"category_scores_gemma":[0.00008446681,0.0000797275,0.0000444898,0.00007936096,0.000025283845,0.00027867034,0.000019639405,0.00011464856,2.2698586e-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":[0.000008181615,0.0000012244773,0.00019633975,0.000057376037,0.000024722032,0.0000042861757,0.000113182105,0.8576262,0.1390445,0.0012217902,0.000024482732,0.0016777444],"study_design_scores_gemma":[0.00020146486,0.0000138018895,0.005720166,0.00012729487,0.000013555847,0.000030478299,0.00002427768,0.8422104,0.15127641,0.00032083725,0.0000054823468,0.0000558307],"about_ca_topic_score_codex":0.0000089936375,"about_ca_topic_score_gemma":6.7075723e-7,"teacher_disagreement_score":0.28943187,"about_ca_system_score_codex":0.00011411663,"about_ca_system_score_gemma":0.0001023141,"threshold_uncertainty_score":0.32511932},"labels":[],"label_agreement":null},{"id":"W3180179525","doi":"10.2316/j.2021.206-0622","title":"BEND ANGLE AND CONTACT FORCE ON SOFT PNEUMATIC GRIPPER FOR GRASPING CYLINDRICAL-SHAPED DIFFERENT-SIZED OBJECTS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Analysis and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Contact force; Mechanical engineering; Materials science; Computer science; Structural engineering; Engineering; Physics; Classical mechanics","score_opus":0.009645416893345552,"score_gpt":0.234638502918711,"score_spread":0.22499308602536544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3180179525","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":[0.6744251,0.00032335345,0.32380533,0.00068708305,0.0005891559,0.00007341294,0.0000059068716,0.000023667873,0.000066927576],"genre_scores_gemma":[0.99420756,0.00021920862,0.0053073876,0.000070120615,0.00012800407,0.0000015382847,0.000028687753,0.000010219796,0.000027258015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993401,0.000013129075,0.00030701936,0.00007419459,0.00019091558,0.00007462505],"domain_scores_gemma":[0.9994149,0.0001235705,0.00013606003,0.000036495414,0.0002445825,0.000044390734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060736496,0.00009126244,0.0001763017,0.000106103136,0.000043527256,0.0001236729,0.000053736287,0.000041644278,0.000014014655],"category_scores_gemma":[0.00009972443,0.00007295347,0.00006942184,0.000047987203,0.000007568265,0.00016267273,0.000013198428,0.000069143956,3.565561e-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":[0.000082094615,0.000075200325,0.00200659,0.00015915,0.0008254287,0.00002553951,0.000638403,0.868069,0.07492839,0.008786231,0.00013063107,0.044273328],"study_design_scores_gemma":[0.0008566334,0.00006384114,0.02717352,0.0001420587,0.00006273933,0.000058092948,0.000069073314,0.96676594,0.0016283112,0.0030772232,0.000013214669,0.000089339854],"about_ca_topic_score_codex":7.240634e-7,"about_ca_topic_score_gemma":0.000004467479,"teacher_disagreement_score":0.3197824,"about_ca_system_score_codex":0.000044740926,"about_ca_system_score_gemma":0.000010628789,"threshold_uncertainty_score":0.29749563},"labels":[],"label_agreement":null},{"id":"W3180882405","doi":"10.2316/j.2021.206-0404","title":"AN IMPROVED SIMULTANEOUS LOCALIZATION AND MAPPING FOR DYNAMIC ENVIRONMENTS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Algebraic and Geometric Analysis","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.013132709109161159,"score_gpt":0.2901359837617153,"score_spread":0.27700327465255414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3180882405","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":[0.093354106,0.00015761208,0.9057421,0.0005469939,0.00013247156,0.000046540306,0.000005552263,0.000005996579,0.00000860843],"genre_scores_gemma":[0.9316045,0.00022082635,0.06786173,0.000077396864,0.00006936723,8.1974684e-7,0.00002096907,0.000008160167,0.00013622746],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992855,0.000023715897,0.00033103392,0.00009061553,0.00020589781,0.00006319178],"domain_scores_gemma":[0.99902856,0.00029825993,0.00032594995,0.000052709427,0.00025479228,0.0000397198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021235239,0.00006720257,0.00013518886,0.00015028908,0.000052814346,0.00007753245,0.00006833373,0.000046061326,0.000011549499],"category_scores_gemma":[0.0005776154,0.00006155726,0.000043819382,0.00007943398,0.000020683552,0.00018914041,0.000020916568,0.000047429367,3.0190614e-7],"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":[0.0002128002,0.0014071345,0.0077658333,0.00035063844,0.0030248112,0.0002138972,0.00476787,0.27375436,0.02969863,0.06961773,0.0004355519,0.6087507],"study_design_scores_gemma":[0.00045665848,0.000066767345,0.00067233853,0.00004421245,0.000082203245,0.00010097454,0.00034112233,0.95801663,0.00016883963,0.03965118,0.0003266353,0.00007243636],"about_ca_topic_score_codex":9.769113e-7,"about_ca_topic_score_gemma":0.0000026677376,"teacher_disagreement_score":0.8382504,"about_ca_system_score_codex":0.000049048544,"about_ca_system_score_gemma":0.000024453511,"threshold_uncertainty_score":0.25102323},"labels":[],"label_agreement":null},{"id":"W3209614597","doi":"","title":"Design and Optimization of Automatic Glass Window Cleaning Robot","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Window (computing); Climb; sort; Computer science; Robot; Window of opportunity; Space (punctuation); Task (project management); Simulation; Artificial intelligence; Engineering; Real-time computing; Operating system; Aerospace engineering","score_opus":0.01861546944148647,"score_gpt":0.2585475255005015,"score_spread":0.239932056059015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209614597","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056314743,0.00024424685,0.99212325,0.0013194615,0.00058293383,0.000045309313,6.329128e-7,0.000023922068,0.000028786195],"genre_scores_gemma":[0.22893402,0.00009116218,0.7708546,0.00005153154,0.000050042676,3.9247584e-7,0.0000021685041,0.00000501331,0.000011089735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987691,0.00010015903,0.00047893374,0.0001233387,0.0004396034,0.00008884236],"domain_scores_gemma":[0.9984067,0.00021423811,0.00055477524,0.00009810544,0.00066852913,0.00005762336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004782915,0.00008808773,0.00018261961,0.00018405828,0.000043537213,0.00018264899,0.00026208448,0.00004814664,0.00000373007],"category_scores_gemma":[0.00021072637,0.000083788414,0.00003500427,0.00014590594,0.000030451116,0.00061346136,0.00010221743,0.000096253396,5.9981244e-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":[0.000003182342,0.000034390774,0.00026776295,0.000014294261,0.00006147876,0.000053172065,0.00040192244,0.9672517,0.0014029455,0.002372028,0.000020555653,0.028116537],"study_design_scores_gemma":[0.00047054313,0.00007647779,0.004537234,0.00022769305,0.000019169025,0.0007001549,0.00004445594,0.99095637,0.0017933385,0.0010943101,0.0000046502873,0.00007560333],"about_ca_topic_score_codex":0.0000016476055,"about_ca_topic_score_gemma":9.2789556e-8,"teacher_disagreement_score":0.22330254,"about_ca_system_score_codex":0.000038193,"about_ca_system_score_gemma":0.00011802721,"threshold_uncertainty_score":0.34167922},"labels":[],"label_agreement":null},{"id":"W3210739019","doi":"10.5555/1739829.1739836","title":"An analysis for a mini robot gripper using SMA springs","year":2007,"lang":"de","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"SMA*; Robot; Computer science; Artificial intelligence; Algorithm","score_opus":0.015267171923826112,"score_gpt":0.28135416796979984,"score_spread":0.26608699604597374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210739019","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":[0.1033258,0.00046088727,0.89264923,0.00024748268,0.0031540263,0.000106279615,0.000018446575,0.000020972731,0.000016848926],"genre_scores_gemma":[0.522894,0.0001642338,0.47588262,0.000049723778,0.00094366114,3.8667662e-7,0.000025879868,0.000024763287,0.00001467676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809486,0.000021835927,0.0009606763,0.00016785867,0.00050757936,0.0002472082],"domain_scores_gemma":[0.998216,0.00012878474,0.0005958893,0.0001292178,0.00074354996,0.00018655953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010083487,0.00020777142,0.00038088844,0.0007966142,0.00007990235,0.00028806453,0.00028043476,0.0001661245,0.000021861013],"category_scores_gemma":[0.000080214304,0.00020801101,0.0002700869,0.00022592116,0.000027488051,0.00044918232,0.00003200177,0.0001760204,0.0000020070022],"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":[0.00005379084,0.00008888497,0.0020070188,0.0000365171,0.0015883244,0.00003022007,0.00033367192,0.9751827,0.00354014,0.009782792,0.000009906646,0.007346023],"study_design_scores_gemma":[0.00069993973,0.00015740289,0.011111786,0.00012220553,0.0011893753,0.000061019342,0.00017399534,0.98436636,0.00028748674,0.0015059737,0.000111789755,0.00021269092],"about_ca_topic_score_codex":0.000024412546,"about_ca_topic_score_gemma":0.000020745898,"teacher_disagreement_score":0.41956824,"about_ca_system_score_codex":0.00023078792,"about_ca_system_score_gemma":0.000055505076,"threshold_uncertainty_score":0.8482443},"labels":[],"label_agreement":null},{"id":"W3212714014","doi":"10.5555/1165139.1165145","title":"Agent-based support for balancing teleoperation and autonomy in urban search and rescue","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Teleoperation; Autonomy; Search and rescue; Computer science; Urban search and rescue; Business; Computer security; Artificial intelligence; Mobile robot; Robot; Political science","score_opus":0.00955495869260023,"score_gpt":0.24060048997042796,"score_spread":0.23104553127782773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212714014","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":[0.8406167,0.00020525433,0.15785347,0.000652462,0.00037555452,0.00013601368,0.0000061719625,0.000022351569,0.0001320128],"genre_scores_gemma":[0.9919446,0.000023777773,0.007762497,0.000033042732,0.00017102035,0.0000027438093,0.000015231511,0.0000074807967,0.00003958235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994192,0.000012926151,0.00031107827,0.000057080186,0.00013427337,0.000065410895],"domain_scores_gemma":[0.9997453,0.000037558875,0.000033760465,0.000024067134,0.00013067233,0.000028657909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025939557,0.000059949718,0.00009786557,0.000179309,0.000026029378,0.00013003794,0.00003540873,0.00003637095,0.0000042849274],"category_scores_gemma":[0.000016992502,0.00005684671,0.000015633923,0.000030157147,0.000012666968,0.00018842984,0.0000059799313,0.00005453758,3.6991864e-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":[0.000020478768,0.000030619914,0.02085796,0.00007949363,0.000035018602,0.000010356411,0.00058939494,0.9520997,0.0074973777,0.0062460266,0.00031766327,0.012215928],"study_design_scores_gemma":[0.0008527516,0.00004450673,0.06394346,0.000061771825,0.0000062623435,0.000046193065,0.000056268917,0.93351704,0.0007396603,0.00005939373,0.00061010325,0.00006259409],"about_ca_topic_score_codex":0.00002699144,"about_ca_topic_score_gemma":0.00006344628,"teacher_disagreement_score":0.15132791,"about_ca_system_score_codex":0.00006720613,"about_ca_system_score_gemma":0.000038582675,"threshold_uncertainty_score":0.23181416},"labels":[],"label_agreement":null},{"id":"W3216444206","doi":"10.2316/j.2021.206-0431","title":"A NOVEL METHOD FOR EXTRACTING TEXT FROM A GEOMETRIC REGION","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Natural language processing","score_opus":0.04663467977667322,"score_gpt":0.35686314654962104,"score_spread":0.3102284667729478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216444206","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":[0.009072833,0.0002859059,0.9820429,0.00618618,0.0012287545,0.00006982234,0.000007235814,0.000011957619,0.0010944046],"genre_scores_gemma":[0.72698134,0.00024309025,0.27178672,0.00017009964,0.0006075141,0.0000027660153,0.000008157314,0.0000046634937,0.00019565481],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99898416,0.000040714338,0.0003985706,0.000062254694,0.00043163667,0.00008265109],"domain_scores_gemma":[0.9971409,0.0005646111,0.00059119373,0.000034504414,0.0016294887,0.00003934454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076325366,0.000050098246,0.00012043697,0.00026257944,0.00017631425,0.00017932919,0.00010690672,0.000048949154,0.000010635383],"category_scores_gemma":[0.0011438801,0.00004786922,0.00007877207,0.00021897604,0.000024468065,0.00044084212,0.000024791807,0.00006566174,0.0000011107278],"study_design_candidate":"design_other","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":[0.00013094362,0.00043599555,0.023039736,0.00008542685,0.0018611456,0.000070870585,0.06459551,0.02066436,0.0065272436,0.2697207,0.004801748,0.6080663],"study_design_scores_gemma":[0.011607333,0.000365553,0.2545909,0.0019067903,0.0006298716,0.0018973,0.14110294,0.19155243,0.0027186063,0.082126446,0.31014907,0.001352744],"about_ca_topic_score_codex":0.0001763473,"about_ca_topic_score_gemma":0.00007153827,"teacher_disagreement_score":0.7179085,"about_ca_system_score_codex":0.00006275138,"about_ca_system_score_gemma":0.00009916112,"threshold_uncertainty_score":0.19520502},"labels":[],"label_agreement":null},{"id":"W3216914197","doi":"10.2316/j.2021.206-0407","title":"MULTI-STEP OPTIMAL PREDICTIVE CONTROL FOR PATH CORRECTION OF THE AGV DRIVEN BY HUB MOTORS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Model predictive control; Computer science; Control (management); Control theory (sociology); Control engineering; Engineering; Artificial intelligence; Computer network","score_opus":0.0056889531951066705,"score_gpt":0.2383615974612151,"score_spread":0.23267264426610842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216914197","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":[0.035734903,0.00011930923,0.96275187,0.0002464146,0.00094699906,0.00009313777,0.0000780571,0.000011786832,0.000017503353],"genre_scores_gemma":[0.95205814,0.00008960276,0.04764303,0.000018827846,0.00011142621,0.0000060701054,0.000013008427,0.000008150443,0.000051773586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951607,0.00000909882,0.00023790095,0.000046919697,0.00014229862,0.00004768821],"domain_scores_gemma":[0.9993027,0.00006157869,0.0001677017,0.000039980932,0.00040587637,0.000022171349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052875333,0.00005302497,0.00008891578,0.00002963734,0.000033210046,0.000021443248,0.00007897644,0.000030827785,0.0000024077542],"category_scores_gemma":[0.000049672515,0.000042571115,0.00006048091,0.0000427401,0.000018103932,0.00011692404,0.000010665817,0.0000708483,1.6162299e-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":[0.0000071734185,0.00003823941,0.00036355312,0.000006777504,0.000092792754,5.1642536e-7,0.00008358199,0.9765009,0.013302423,0.00018511759,0.00044204635,0.008976858],"study_design_scores_gemma":[0.00066949945,0.000029697057,0.0056095966,0.000053927244,0.000027855393,0.000021300833,0.00009975556,0.9884255,0.004353896,0.00008667479,0.000582191,0.00004011794],"about_ca_topic_score_codex":0.0000012478746,"about_ca_topic_score_gemma":0.0000013307018,"teacher_disagreement_score":0.9163232,"about_ca_system_score_codex":0.000044657554,"about_ca_system_score_gemma":0.000020220474,"threshold_uncertainty_score":0.17359997},"labels":[],"label_agreement":null},{"id":"W3217028903","doi":"","title":"PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate Nonlinear Control and MATLAB Courses","year":2012,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":120,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"MATLAB; Computer science; Control theory (sociology); Nonlinear system; Control engineering; Torque; Control (management); Engineering; Artificial intelligence; Physics; Programming language","score_opus":0.02980525537656286,"score_gpt":0.30847914639422036,"score_spread":0.2786738910176575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3217028903","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":[0.279585,0.001472399,0.717303,0.00045947908,0.00095672655,0.00015793741,0.000016813996,0.000041848267,0.0000067826063],"genre_scores_gemma":[0.8945094,0.000101185935,0.10449477,0.000088785884,0.0007564464,0.0000018758619,0.000016479706,0.000028295888,0.0000028057734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867886,0.00013777181,0.0006380257,0.00011331434,0.0002628798,0.00016915123],"domain_scores_gemma":[0.99858135,0.00025178012,0.00038955643,0.000070354676,0.00056874997,0.00013823465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000716437,0.00022269014,0.0003823654,0.00024822765,0.0000750265,0.00020037452,0.00010491342,0.00011104752,0.0000026037155],"category_scores_gemma":[0.00008675476,0.00018511125,0.00006454567,0.00006168653,0.00004939159,0.000778369,0.000025626625,0.00021741772,0.0000010881793],"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":[0.00028817245,0.0001875403,0.0056735394,0.00016824013,0.0016307576,0.00002245894,0.0024101224,0.686293,0.20176668,0.0030652962,0.0000842842,0.09840991],"study_design_scores_gemma":[0.0018071138,0.000077578414,0.012651801,0.00022398909,0.000104969884,0.00040351402,0.00018031267,0.9829432,0.0009859235,0.00034698102,0.00010038619,0.00017425577],"about_ca_topic_score_codex":0.000024060788,"about_ca_topic_score_gemma":0.000005824715,"teacher_disagreement_score":0.6149243,"about_ca_system_score_codex":0.00015047635,"about_ca_system_score_gemma":0.00002374595,"threshold_uncertainty_score":0.7548617},"labels":[],"label_agreement":null},{"id":"W3217467022","doi":"","title":"Voice Assistant: Magical Speech Recognition Tool","year":2019,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Voice command device; Action (physics); Human–computer interaction; Multimedia; Artificial intelligence; Speech recognition","score_opus":0.02625708508483195,"score_gpt":0.2824554977110513,"score_spread":0.25619841262621934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3217467022","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":[0.9869409,0.000023840874,0.008027817,0.0021957096,0.0016395769,0.000062019695,0.000008230064,0.00001936208,0.0010825346],"genre_scores_gemma":[0.99207807,0.00005538235,0.006951504,0.0004920063,0.00024218926,3.1527543e-7,0.0000029591702,0.000006373594,0.00017122545],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99896556,0.000050442584,0.00034256425,0.000119021504,0.00043827124,0.000084141306],"domain_scores_gemma":[0.99919057,0.00018306359,0.0003053632,0.0000518628,0.00023230466,0.000036864727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021803756,0.000076342054,0.00011110606,0.00013803113,0.000028514949,0.00019463495,0.0002016465,0.00004211232,0.00008607398],"category_scores_gemma":[0.0001727565,0.00006241652,0.000055416094,0.00006184009,0.000025451523,0.0004987789,0.00004423686,0.00014020498,0.00008353385],"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":[0.00020065522,0.0003128501,0.0028740203,0.000046172074,0.00007854826,0.00019560326,0.0005024876,0.0055209934,0.6326792,0.00531392,0.0014046411,0.3508709],"study_design_scores_gemma":[0.003921546,0.0009882319,0.040245328,0.0009445587,0.00006873246,0.0049416693,0.00019033627,0.27090058,0.6394805,0.02544577,0.012161742,0.00071105856],"about_ca_topic_score_codex":0.0000014135684,"about_ca_topic_score_gemma":4.959479e-7,"teacher_disagreement_score":0.35015985,"about_ca_system_score_codex":0.000039802235,"about_ca_system_score_gemma":0.000024684437,"threshold_uncertainty_score":0.25452718},"labels":[],"label_agreement":null},{"id":"W329024442","doi":"10.2316/journal.206.2009.3.206-3261","title":"SERVICE ROBOT SYSTEM BASED ON NETWORKED ROBOTS FOR USING PERSONAL ATTRIBUTE AND TO GET PREFERENCE ATTRIBUTE","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Preference; Computer science; Robot; Service robot; Service (business); Human–computer interaction; Artificial intelligence; Business; Mathematics; Statistics; Marketing","score_opus":0.036398715261622416,"score_gpt":0.2860545637432399,"score_spread":0.24965584848161748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W329024442","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":[0.041985597,0.00013748287,0.95637333,0.0009748979,0.00025821576,0.00012526536,0.00004193882,0.000094913856,0.000008356367],"genre_scores_gemma":[0.7716556,0.000022105296,0.22792737,0.00020281138,0.00015116199,0.0000018505481,0.0000270278,0.000010707208,0.0000013389647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992043,0.000012950623,0.00030539924,0.00010440166,0.00025192628,0.000121034944],"domain_scores_gemma":[0.99921733,0.00006856737,0.00015790321,0.0000573544,0.00042263806,0.00007621533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020809175,0.00012135449,0.00016503102,0.00016472045,0.000055851993,0.0001205844,0.00014505895,0.000056431058,7.935341e-7],"category_scores_gemma":[0.000038989434,0.0001160788,0.000027808284,0.00009168821,0.000007688122,0.0003134645,0.000017863935,0.00010017893,3.7394716e-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":[0.000038133236,0.0000138891955,0.0000917454,0.000047780806,0.00002309541,0.0000040732198,0.000052933443,0.9842095,0.0016685578,0.00037331445,0.0001257149,0.013351261],"study_design_scores_gemma":[0.000424987,0.00013221204,0.0020223302,0.00069993385,0.000020835716,0.0000674469,0.000026006392,0.9952418,0.00088127475,0.00023861983,0.00012555318,0.000118991775],"about_ca_topic_score_codex":0.0000014154975,"about_ca_topic_score_gemma":0.0000014931591,"teacher_disagreement_score":0.72967005,"about_ca_system_score_codex":0.00015872729,"about_ca_system_score_gemma":0.000026357662,"threshold_uncertainty_score":0.47335562},"labels":[],"label_agreement":null},{"id":"W4229764814","doi":"10.2316/j.2021.206-0577","title":"A TRAJECTORY TRACKING METHOD OF PARALLEL MANIPULATOR BASED ON KINEMATIC CONTROL ALGORITHM","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Trajectory; Tracking (education); Computer science; Parallel manipulator; Manipulator (device); Control theory (sociology); Control (management); Algorithm; Artificial intelligence; Robot; Physics","score_opus":0.0140648841087347,"score_gpt":0.2557894064281394,"score_spread":0.24172452231940472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229764814","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":[0.008022241,0.0001785702,0.99024653,0.00048398462,0.0008302132,0.000057186808,0.000007270725,0.000028590559,0.00014537956],"genre_scores_gemma":[0.9441357,0.000013116077,0.05562468,0.000046394947,0.00015907583,0.0000014739257,0.0000030342635,0.000008342757,0.0000081817725],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991689,0.000049984345,0.0004273127,0.000050953116,0.00023857634,0.00006430495],"domain_scores_gemma":[0.9993079,0.00013999711,0.00020867847,0.000054919423,0.00026428295,0.000024250703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002920294,0.00007407797,0.00020961439,0.00015338356,0.000015849033,0.00002577714,0.000092543436,0.00009317827,0.000013407782],"category_scores_gemma":[0.00008573028,0.00006771318,0.000075747885,0.000056098306,0.000011381295,0.00008409341,0.0000041758426,0.00014993182,7.9162663e-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":[0.000020279851,0.000041363368,0.00013393593,0.000026386626,0.00020013026,0.000043704265,0.0000389899,0.9456067,0.005190958,0.0022116336,0.000043037064,0.046442878],"study_design_scores_gemma":[0.001591827,0.000058255642,0.0021203214,0.00021373715,0.000044765933,0.00012226973,0.000042758365,0.9928689,0.0022177552,0.00058989396,0.000067989604,0.0000615537],"about_ca_topic_score_codex":0.0000018112279,"about_ca_topic_score_gemma":0.0000010847698,"teacher_disagreement_score":0.9361135,"about_ca_system_score_codex":0.000042048694,"about_ca_system_score_gemma":0.00003431445,"threshold_uncertainty_score":0.27612635},"labels":[],"label_agreement":null},{"id":"W4235934394","doi":"10.2316/journal.206","title":"International Journal of Robotics and Automation","year":2006,"lang":"en","type":"paratext","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robotics; Automation; Artificial intelligence; Computer science; Engineering; Robot; Mechanical engineering","score_opus":0.009571355789837133,"score_gpt":0.24861479758499264,"score_spread":0.2390434417951555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235934394","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":[0.03721913,0.017340496,0.8148478,0.004993028,0.10727215,0.00074137194,0.0004477182,0.00024772182,0.01689055],"genre_scores_gemma":[0.9156213,0.016420092,0.05381687,0.0001468949,0.009886147,0.000004671759,0.0005030885,0.0002476895,0.0033532775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99615157,0.00007918185,0.00203872,0.00017366205,0.0013285937,0.00022825698],"domain_scores_gemma":[0.9954871,0.00014360758,0.002052395,0.00013674016,0.002034688,0.00014549578],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00062364346,0.00040424019,0.00073180615,0.0011127337,0.000059015412,0.00064553035,0.0006537106,0.0004051376,0.000074546944],"category_scores_gemma":[0.00009513011,0.00037376728,0.00023332277,0.00013887411,0.00007838035,0.00066159153,0.0000959672,0.000617422,0.00003239289],"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":[0.000023054046,0.00007644159,0.000107428976,0.00015904321,0.00093840936,0.0000931669,0.00021716807,0.92228806,0.0009722314,0.0005494894,0.061616074,0.0129594095],"study_design_scores_gemma":[0.0026079125,0.0002736308,0.0025756583,0.0027537784,0.00034700093,0.0030946303,0.00014455871,0.9368517,0.00063394994,0.00082163094,0.04914512,0.0007504612],"about_ca_topic_score_codex":0.000013367975,"about_ca_topic_score_gemma":0.0000035335052,"teacher_disagreement_score":0.8784021,"about_ca_system_score_codex":0.00032550786,"about_ca_system_score_gemma":0.0001584932,"threshold_uncertainty_score":0.99987143},"labels":[],"label_agreement":null},{"id":"W4236083144","doi":"10.2316/j.2021.206-0563","title":"SELF-COMPETITION LEADER–FOLLOWER MULTI-AUV FORMATION CONTROL BASED ON IMPROVED PSO ALGORITHM WITH ENERGY CONSUMPTION ALLOCATION","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Energy consumption; Competition (biology); Consumption (sociology); Control (management); Energy (signal processing); Mathematical optimization; Algorithm; Artificial intelligence; Engineering; Mathematics; Sociology; Statistics","score_opus":0.0066828117107695555,"score_gpt":0.2240183132167868,"score_spread":0.21733550150601724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236083144","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":[0.0031288418,0.00013472085,0.99531764,0.00080291583,0.00036258507,0.00008385206,0.00002064876,0.000084124564,0.000064671345],"genre_scores_gemma":[0.79987127,0.00028484614,0.19933277,0.00018323158,0.0001658612,0.000011821834,0.00011216428,0.00001911099,0.000018909317],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990778,0.000025766134,0.00037986226,0.00010700255,0.00030505852,0.00010451725],"domain_scores_gemma":[0.998949,0.00006309455,0.00023248285,0.00008549597,0.0006097955,0.000060133432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010465177,0.00013250484,0.0001464803,0.000160657,0.000064262436,0.00010308803,0.00008336901,0.00006483845,0.000012758656],"category_scores_gemma":[0.000015515976,0.000121141326,0.000052689105,0.00009063514,0.00002014822,0.00046368755,0.0000065447916,0.00012207039,0.0000034001848],"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":[0.000029276669,0.00022844449,0.00007514113,0.000040693936,0.00015388906,0.000017866078,0.00010842689,0.90223074,0.0069735055,0.0031233104,0.000049793238,0.086968936],"study_design_scores_gemma":[0.0019786058,0.000078505276,0.001262135,0.00011302588,0.000045425397,0.00010148515,0.000048108443,0.9902954,0.0048151654,0.0001740097,0.00095462054,0.00013353175],"about_ca_topic_score_codex":0.0000016294375,"about_ca_topic_score_gemma":0.000007680047,"teacher_disagreement_score":0.79674244,"about_ca_system_score_codex":0.00014542104,"about_ca_system_score_gemma":0.00004236992,"threshold_uncertainty_score":0.494},"labels":[],"label_agreement":null},{"id":"W4240081352","doi":"10.2316/j.2021.206-0654","title":"REPETITIVE CONTROL OF ROBOTIC MANIPULATORS IN OPERATIONAL SPACE: A NEURAL NETWORK-BASED APPROACH","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Automation and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial neural network; Robot manipulator; Control (management); Control engineering; Artificial intelligence; Engineering","score_opus":0.011183664948867857,"score_gpt":0.2194520658394788,"score_spread":0.20826840089061094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240081352","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":[0.22982453,0.0008239981,0.76322967,0.0021167337,0.002759685,0.00024666984,0.00001371012,0.000051614315,0.00093337765],"genre_scores_gemma":[0.99604195,0.000015660478,0.0035436267,0.00007248943,0.00028109728,0.0000024541262,0.000017099908,0.000009630269,0.000015961974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988319,0.000070935384,0.00059277524,0.00007210298,0.00033825726,0.00009402971],"domain_scores_gemma":[0.99916685,0.000079892416,0.00021894346,0.000051446954,0.00044404584,0.000038808892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028495432,0.00009051648,0.00023439428,0.0001514259,0.000018479634,0.00006312556,0.000088662644,0.00007059217,0.000016670014],"category_scores_gemma":[0.00007549681,0.000086887034,0.00006927805,0.00012870716,0.000017945918,0.00018610047,0.000008813369,0.00013978466,7.210903e-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":[0.000020052898,0.00003780127,0.003638305,0.000017259606,0.00007790199,0.000020856829,0.000064141175,0.98597944,0.0007562505,0.008178956,0.00006511541,0.001143909],"study_design_scores_gemma":[0.0017108762,0.000028432143,0.01636381,0.00012425733,0.000020228148,0.000087217784,0.000059859925,0.98102593,0.0002732081,0.00017613814,0.000055048804,0.00007497931],"about_ca_topic_score_codex":0.0000067181354,"about_ca_topic_score_gemma":0.000006198733,"teacher_disagreement_score":0.76621747,"about_ca_system_score_codex":0.00008155987,"about_ca_system_score_gemma":0.000080586135,"threshold_uncertainty_score":0.35431504},"labels":[],"label_agreement":null},{"id":"W4244818555","doi":"10.2316/j.2021.206-0605","title":"RAPID SELECTING UAVs FOR COMBAT BASED ON THREE-WAY MULTIPLE ATTRIBUTE DECISION","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Beijing Union University; National Natural Science Foundation of China","keywords":"Computer science; Computer security","score_opus":0.01624061201175018,"score_gpt":0.263636828889015,"score_spread":0.24739621687726485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244818555","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":[0.032833707,0.00016687457,0.96572995,0.00057454186,0.0005443215,0.00006308216,0.000020720789,0.00002961129,0.000037161884],"genre_scores_gemma":[0.84723985,0.000078823796,0.15237388,0.00006015748,0.00019658936,0.0000037009224,0.000028906636,0.000011943431,0.0000061454953],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937147,0.0000057420843,0.00027257288,0.00007039054,0.00020278839,0.00007705226],"domain_scores_gemma":[0.99903005,0.00032552076,0.00011074055,0.000053734504,0.0004398482,0.000040117608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010238676,0.00007331364,0.00010515565,0.00008622984,0.00005872989,0.00006594324,0.00008035654,0.000035973088,0.0000074279815],"category_scores_gemma":[0.00013978493,0.000068979985,0.000059902635,0.00007476196,0.000007845835,0.00012678494,0.0000106840325,0.00009133424,0.0000013347043],"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":[0.000013212871,0.000034484132,0.00027578737,0.000008254689,0.000033740904,0.0000040134273,0.000015544541,0.80911285,0.001748917,0.00091237744,0.00018438237,0.18765643],"study_design_scores_gemma":[0.0007882896,0.000054724012,0.004696931,0.000101666876,0.000012210237,0.000029286526,0.00001693596,0.9864591,0.003547296,0.0023953465,0.0018248109,0.00007340256],"about_ca_topic_score_codex":4.5982068e-7,"about_ca_topic_score_gemma":0.000005062776,"teacher_disagreement_score":0.81440616,"about_ca_system_score_codex":0.00006080282,"about_ca_system_score_gemma":0.00002136409,"threshold_uncertainty_score":0.2812922},"labels":[],"label_agreement":null},{"id":"W4245163155","doi":"10.2316/j.2021.206-0457","title":"BEARING CHARACTERISTICS OF HEAVY LOAD SUPPORT PLATFORMS WITH REDUNDANT MULTIBRANCH CHAINS","year":2021,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vibration and Dynamic Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Load bearing; Bearing (navigation); Computer science; Structural engineering; Engineering; Artificial intelligence","score_opus":0.006710616039415058,"score_gpt":0.21811480520736087,"score_spread":0.21140418916794582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245163155","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":[0.48214865,0.000061238716,0.51688176,0.0002499651,0.00032885926,0.00002186164,0.00001077056,0.000017457895,0.0002794196],"genre_scores_gemma":[0.98871434,0.00016714317,0.010903116,0.000026294438,0.00008125578,2.8033256e-7,0.000025188167,0.000008654173,0.00007375498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991869,0.0000044929025,0.00037497777,0.0000494364,0.00032458693,0.000059653416],"domain_scores_gemma":[0.99921477,0.00001984713,0.00018910035,0.00004937864,0.0004858879,0.00004101075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001087851,0.0000673009,0.00015620224,0.00010136351,0.000019032459,0.00005027456,0.00006682373,0.00003301568,0.000029784596],"category_scores_gemma":[0.000030500996,0.000056093806,0.000046599853,0.00007443438,0.000018527158,0.0002265008,0.000014533231,0.00008362423,0.0000011188948],"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":[0.00006394953,0.0001329387,0.011934095,0.00010594426,0.00074133696,0.00013466364,0.001114283,0.9352723,0.00832272,0.003802006,0.000094446295,0.03828133],"study_design_scores_gemma":[0.0005971797,0.000049771803,0.024854092,0.00012983751,0.00004342255,0.00023222741,0.000113710186,0.97000647,0.003643932,0.00013601447,0.000111215246,0.00008214315],"about_ca_topic_score_codex":0.000002042333,"about_ca_topic_score_gemma":0.00000927383,"teacher_disagreement_score":0.5065657,"about_ca_system_score_codex":0.000056679793,"about_ca_system_score_gemma":0.00007447724,"threshold_uncertainty_score":0.22874391},"labels":[],"label_agreement":null},{"id":"W4285113825","doi":"10.2316/j.2022.206-0622","title":"BEND ANGLE AND CONTACT FORCE ON SOFT PNEUMATIC GRIPPER FOR GRASPING CYLINDRICAL-SHAPED DIFFERENT-SIZED OBJECTS, 391-399.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Contact force; Mechanical engineering; Physics; Engineering; Classical mechanics","score_opus":0.01541785354421486,"score_gpt":0.24749799048438612,"score_spread":0.23208013694017127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285113825","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":[0.53577006,0.00028533104,0.46102422,0.0010906284,0.001350106,0.00022077694,0.0000048116754,0.00007239893,0.0001816465],"genre_scores_gemma":[0.9980911,0.000043490145,0.0015206927,0.000112411675,0.00012739049,0.0000071077125,0.000023178689,0.000019189805,0.000055454126],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991163,0.000032604305,0.0003603666,0.00008405681,0.0003043674,0.00010232871],"domain_scores_gemma":[0.9994188,0.00019263302,0.00019682146,0.000042867236,0.00009629812,0.00005259028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017345115,0.000106276595,0.00017369022,0.00020550835,0.0001259262,0.00010668716,0.00010056645,0.000030861538,0.000038478185],"category_scores_gemma":[0.00008350791,0.00009875859,0.0000643278,0.000047462338,0.000008594704,0.00016553604,0.000031270603,0.00018338264,7.822897e-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":[0.000058382597,0.000044649372,0.0009994829,0.0000453738,0.00014041425,0.000006754066,0.0005876671,0.9774848,0.007785766,0.004152566,0.00011230535,0.00858179],"study_design_scores_gemma":[0.0011995408,0.00018207854,0.028681485,0.00007511442,0.000027661754,0.00007445346,0.00019863836,0.967793,0.00008147845,0.0014398264,0.0001374713,0.00010926022],"about_ca_topic_score_codex":0.0000014427028,"about_ca_topic_score_gemma":0.000001831485,"teacher_disagreement_score":0.462321,"about_ca_system_score_codex":0.00009966308,"about_ca_system_score_gemma":0.000012385566,"threshold_uncertainty_score":0.40272585},"labels":[],"label_agreement":null},{"id":"W4285147914","doi":"10.2316/j.2022.206-0571","title":"GWO-BASED TUNING OF LQR–PID CONTROLLER FOR 3-DOF PARALLEL MANIPULATOR, 248-256.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); PID controller; Parallel manipulator; Computer science; Controller (irrigation); Control engineering; Engineering; Control (management); Robot; Artificial intelligence; Biology","score_opus":0.013478857520818304,"score_gpt":0.23869777579305443,"score_spread":0.2252189182722361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285147914","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":[0.01433431,0.00051497156,0.98361826,0.00033717774,0.00090446265,0.00016481079,0.000019063555,0.000028786428,0.0000781464],"genre_scores_gemma":[0.97901386,0.000011951383,0.020719199,0.000049943003,0.00013812169,0.000012342599,0.000008406528,0.000017636175,0.000028515075],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897516,0.000029930814,0.0005007809,0.000059612954,0.00034610037,0.00008840715],"domain_scores_gemma":[0.999166,0.00015042319,0.00034469197,0.000048933554,0.0002550143,0.000034914767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029044802,0.00008517027,0.00020929336,0.0001816309,0.000045227927,0.000026510474,0.00015849162,0.000025675954,0.000013627128],"category_scores_gemma":[0.000050788916,0.000085808075,0.00009079856,0.00004631676,0.000011601464,0.0001437993,0.000016533011,0.00010218132,3.8205977e-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":[0.000077565484,0.00002134906,0.00017774856,0.000024719142,0.00013794794,0.0000047412364,0.00007596495,0.9823321,0.009649806,0.003490116,0.00018292617,0.0038249823],"study_design_scores_gemma":[0.002352335,0.00012132669,0.0008590866,0.0000489775,0.00002892926,0.00003914478,0.00005574584,0.99317867,0.0003020488,0.0017558553,0.001176558,0.00008130078],"about_ca_topic_score_codex":0.0000021316723,"about_ca_topic_score_gemma":6.904982e-7,"teacher_disagreement_score":0.9646796,"about_ca_system_score_codex":0.00012301636,"about_ca_system_score_gemma":0.000027186426,"threshold_uncertainty_score":0.34991518},"labels":[],"label_agreement":null},{"id":"W4285156248","doi":"10.2316/j.2022.206-0765","title":"DYNAMICS ANALYSIS OF 2D CHAOTIC CAT MAP OVER FINITE-STATE SPACE, 163-172.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Quantum chaos and dynamical systems","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Chaotic; State space; Dynamics (music); Space (punctuation); Statistical physics; State (computer science); Computer science; Mathematics; Physics; Algorithm; Artificial intelligence; Acoustics; Statistics","score_opus":0.006017253168288432,"score_gpt":0.24378057642534984,"score_spread":0.2377633232570614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285156248","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":[0.8429092,0.000047989957,0.15468359,0.0010808723,0.0007705612,0.00006296954,0.00021490017,0.000006533167,0.00022337261],"genre_scores_gemma":[0.99877423,0.000007642776,0.00075286377,0.000025782965,0.000111134905,0.0000017829666,0.0001173409,0.000008246169,0.00020097438],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873716,0.000052698826,0.0005228734,0.000094754425,0.00049546617,0.00009702326],"domain_scores_gemma":[0.9987884,0.00011210809,0.00072873157,0.00007664677,0.00023896238,0.000055159977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026092492,0.000093683404,0.0002645462,0.00037900338,0.000065550565,0.000057550722,0.00018679851,0.000016485747,0.00023522874],"category_scores_gemma":[0.000010480874,0.00008518425,0.00019183202,0.00023835582,0.000026070242,0.00013219425,0.00008450038,0.00011659549,0.0000012659007],"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":[0.00003101693,0.00016425336,0.061258372,0.000011024984,0.001340882,0.000011333537,0.00037342816,0.87201595,0.00017360307,0.061484456,0.00008514526,0.0030505436],"study_design_scores_gemma":[0.0003974017,0.000071388415,0.02131213,0.000022293603,0.00022549483,0.0000058656665,0.00026069305,0.9713998,0.000017578108,0.006020289,0.00017947148,0.00008758634],"about_ca_topic_score_codex":0.00014603416,"about_ca_topic_score_gemma":0.000012500093,"teacher_disagreement_score":0.15586503,"about_ca_system_score_codex":0.00009526815,"about_ca_system_score_gemma":0.0000437567,"threshold_uncertainty_score":0.34737128},"labels":[],"label_agreement":null},{"id":"W4285183605","doi":"10.2316/j.2022.206-0654","title":"REPETITIVE CONTROL OF ROBOTIC MANIPULATORS IN OPERATIONAL SPACE: A NEURAL NETWORK-BASED APPROACH, 302-309.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Computer science; Robot manipulator; Control (management); Artificial intelligence; Control engineering; Control theory (sociology); Engineering","score_opus":0.009168060181035293,"score_gpt":0.20891527120246117,"score_spread":0.19974721102142587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285183605","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":[0.49902463,0.0010156208,0.4920318,0.0027183052,0.0040400526,0.00048120282,0.000030750685,0.000088193396,0.00056943117],"genre_scores_gemma":[0.99845886,0.000007295357,0.0012565063,0.000049929244,0.00018884882,0.000008235002,0.0000111868885,0.000009136522,0.0000100034895],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989706,0.000071426446,0.0004796541,0.00006777051,0.00031348845,0.00009705891],"domain_scores_gemma":[0.9994928,0.0000668028,0.00023190034,0.000049764727,0.00013562999,0.000023053182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040838183,0.00008213319,0.0002042878,0.00022994031,0.00004345917,0.000022913748,0.0001547106,0.000060860573,0.000018332496],"category_scores_gemma":[0.000038682443,0.00008224571,0.000057040572,0.00012024769,0.000025555615,0.000118939446,0.00001973468,0.00027504005,2.6474657e-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":[0.000051265208,0.000037975162,0.004920637,0.0000073772367,0.000080457765,0.000016385424,0.00005108551,0.9803963,0.000306991,0.013190529,0.000072542796,0.00086846895],"study_design_scores_gemma":[0.0016268267,0.000093077506,0.0057846713,0.00003672214,0.000019625224,0.000095782496,0.000085189575,0.991603,0.00006288847,0.00044017422,0.00008073859,0.000071271745],"about_ca_topic_score_codex":0.000009761127,"about_ca_topic_score_gemma":0.0000028745835,"teacher_disagreement_score":0.49943423,"about_ca_system_score_codex":0.00012134316,"about_ca_system_score_gemma":0.00004423583,"threshold_uncertainty_score":0.33538827},"labels":[],"label_agreement":null},{"id":"W4285203768","doi":"10.2316/j.2022.206-0158","title":"SLUNG-LOAD TRAJECTORY CONTROL USING AN INPUT-SHAPING METHOD WITH MODEL-FOLLOWING CONTROL, 60-75.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Control theory (sociology); Control (management); Computer science; Artificial intelligence; Physics","score_opus":0.020898577396312436,"score_gpt":0.2669769481544284,"score_spread":0.24607837075811598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285203768","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":[0.27701274,0.00040224657,0.7215827,0.000110857676,0.000690309,0.00007054354,0.000009840567,0.00007781722,0.000042954096],"genre_scores_gemma":[0.9554868,0.0000104144165,0.0443396,0.00004845615,0.000085639316,0.0000045604475,0.000002013924,0.000018197812,0.000004338071],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988985,0.000047497546,0.00035775214,0.0000872001,0.0004931616,0.00011591066],"domain_scores_gemma":[0.9994589,0.00006263915,0.00020895508,0.00007053797,0.0001576315,0.000041356016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005296242,0.00011085199,0.00021574566,0.00022373085,0.00009300279,0.000091280104,0.00019946546,0.000040405237,0.000005176919],"category_scores_gemma":[0.000028956454,0.00009931737,0.00006724227,0.00007261811,0.000012503414,0.0004184108,0.000022429715,0.0002202784,1.7551102e-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":[0.000021736638,0.00002143155,0.00037935347,0.000008040739,0.00025547764,0.00004894552,0.00021900622,0.9837209,0.0114877885,0.0005920633,0.000012789676,0.003232444],"study_design_scores_gemma":[0.001311159,0.0001001052,0.00075383723,0.00006193284,0.00006025464,0.00028950462,0.00015017677,0.99649274,0.00020140514,0.0003600307,0.00010341778,0.000115423194],"about_ca_topic_score_codex":0.000013336945,"about_ca_topic_score_gemma":0.0000036862407,"teacher_disagreement_score":0.678474,"about_ca_system_score_codex":0.0002617805,"about_ca_system_score_gemma":0.00006096786,"threshold_uncertainty_score":0.40500447},"labels":[],"label_agreement":null},{"id":"W4285204562","doi":"10.2316/j.2022.206-0453","title":"DESIGN AND EXPERIMENT OF A NOVEL 4-DOF VIBRATION ISOLATING SYSTEM, 182-191.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Vibration; Computer science; Acoustics; Physics","score_opus":0.017503128380126885,"score_gpt":0.23145059193032194,"score_spread":0.21394746355019506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285204562","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":[0.15137744,0.00033577852,0.8469867,0.00022723204,0.0008531593,0.00010515561,0.0000037478808,0.000035060453,0.000075689524],"genre_scores_gemma":[0.9880356,0.000011377309,0.011844751,0.00000731874,0.00008407551,0.000004819347,0.0000019723152,0.000006030971,0.0000040209598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932104,0.000029611583,0.0003575188,0.000041820906,0.00020188343,0.000048128513],"domain_scores_gemma":[0.99955523,0.0000487257,0.00023618226,0.000031742034,0.00011215097,0.000015941065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032203866,0.00005349388,0.00011812336,0.00014267294,0.000051531788,0.00002458888,0.000080660575,0.00003843511,0.0000039798547],"category_scores_gemma":[0.000020583135,0.000052981406,0.000019347333,0.000050013292,0.000012013862,0.00012232157,0.00002604206,0.00011011275,1.1176147e-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":[0.00003305272,0.0000274936,0.00008498108,0.000021425116,0.00012203589,0.0000047878048,0.00043717297,0.88047785,0.10416647,0.010227598,0.0000440945,0.0043530217],"study_design_scores_gemma":[0.0008561985,0.00011495986,0.00015883734,0.000075660624,0.000016300632,0.00021089701,0.00051756104,0.99271667,0.005126704,0.00009934073,0.000055264212,0.000051617568],"about_ca_topic_score_codex":0.000004146849,"about_ca_topic_score_gemma":1.8237803e-7,"teacher_disagreement_score":0.8366582,"about_ca_system_score_codex":0.000082134575,"about_ca_system_score_gemma":0.000018919747,"threshold_uncertainty_score":0.2160519},"labels":[],"label_agreement":null},{"id":"W4285206761","doi":"10.2316/j.2022.206-0693","title":"DETERMINATION OF CLOSED-FORM MATHEMATICAL EXPRESSION OF VOLUME OF CONSTANT ORIENTATION WORKSPACE FOR GOUGH–STEWART PLATFORM","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Workspace; Constant (computer programming); Orientation (vector space); Volume (thermodynamics); Computer science; Expression (computer science); Computer graphics (images); Mathematics; Geometry; Physics; Artificial intelligence; Programming language; Thermodynamics; Robot","score_opus":0.01054646872394602,"score_gpt":0.2461087799211329,"score_spread":0.23556231119718687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285206761","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":[0.114266306,0.00004229675,0.88491136,0.000066245644,0.00046374407,0.00012016672,0.000031906562,0.000007854752,0.000090097295],"genre_scores_gemma":[0.7367317,0.00003128992,0.2631575,0.0000036126535,0.00002712757,0.0000033965641,0.000017914785,0.000009002795,0.000018503744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987768,0.000011690557,0.0006711933,0.000051770534,0.00042425244,0.00006431043],"domain_scores_gemma":[0.9988404,0.00011628817,0.0006013258,0.000057394114,0.00035702554,0.000027564756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033663688,0.00007213583,0.00020341677,0.00018704747,0.000027699096,0.00001170907,0.000120454104,0.000039442995,0.000028453165],"category_scores_gemma":[0.000066858884,0.000068223,0.00007535606,0.00006953434,0.000025546973,0.00020275389,0.0000336972,0.000075283446,1.2130216e-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":[0.0001059139,0.00012917272,0.00020732093,0.0002573784,0.00006114831,0.0000023921893,0.0012145501,0.87772614,0.02539568,0.077630244,0.00007606104,0.017193975],"study_design_scores_gemma":[0.0007232585,0.00023618131,0.00031126998,0.00018318954,0.000036978316,0.000046629986,0.0005510071,0.96398807,0.008489531,0.025347598,0.000020156922,0.00006610532],"about_ca_topic_score_codex":9.691304e-7,"about_ca_topic_score_gemma":5.507019e-7,"teacher_disagreement_score":0.6224654,"about_ca_system_score_codex":0.000070673916,"about_ca_system_score_gemma":0.000032002892,"threshold_uncertainty_score":0.27820534},"labels":[],"label_agreement":null},{"id":"W4285210263","doi":"10.2316/j.2022.206-0544","title":"A NOVEL CENTRAL PATTERN GENERATOR FOR CYCLIC MOTIONS INCLUDING IMPACT, 280-287.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Generator (circuit theory); Computer science; Physics","score_opus":0.018822988336397572,"score_gpt":0.26551972603836366,"score_spread":0.2466967377019661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285210263","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":[0.097237796,0.00006686745,0.9005749,0.00040184933,0.0015271067,0.00007436767,0.00006984227,0.000026193049,0.000021062466],"genre_scores_gemma":[0.93001205,0.00003433437,0.06950337,0.0000669246,0.00030698418,0.000006022635,0.000036506575,0.000018622068,0.000015169363],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991858,0.000010407339,0.0003277373,0.000063077205,0.00027451725,0.00013845286],"domain_scores_gemma":[0.99955994,0.00003519118,0.00015090936,0.00004597428,0.00013575649,0.00007223567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001811102,0.00008756427,0.00011976336,0.00016460379,0.00010529538,0.00008301452,0.00014767905,0.00002568731,0.000032799522],"category_scores_gemma":[0.000027731014,0.00008447457,0.000094012095,0.000055737022,0.0000070097844,0.00016348794,0.000048452577,0.00012303729,4.0913486e-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":[0.000004566775,0.000039997285,0.00023182573,0.0000085158135,0.000105329615,0.000004105281,0.00015716057,0.9789307,0.008489471,0.0033756234,0.00016615802,0.008486537],"study_design_scores_gemma":[0.000585869,0.000081496604,0.0039957236,0.000018853576,0.000024449191,0.00021772296,0.00006206542,0.9933348,0.00009321051,0.0013435292,0.00015340575,0.00008890793],"about_ca_topic_score_codex":0.0000058990113,"about_ca_topic_score_gemma":0.0000030043645,"teacher_disagreement_score":0.8327743,"about_ca_system_score_codex":0.00023480052,"about_ca_system_score_gemma":0.000036470607,"threshold_uncertainty_score":0.34447727},"labels":[],"label_agreement":null},{"id":"W4285215122","doi":"10.2316/j.2022.206-0578","title":"NOVEL TOPOLOGICAL RELATIONSHIP SOLUTIONS TO THE ALV MULTI-INDEGREE–MULTI-OUTDEGREE TASK SEQUENCE PLANNING PROBLEM, 257-265.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Differential Equations and Boundary Problems","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Task (project management); Computer science; Sequence (biology); Biology; Engineering; Biochemistry; Systems engineering","score_opus":0.22747873193961338,"score_gpt":0.37276174285110586,"score_spread":0.14528301091149248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285215122","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":[0.074796095,0.00009791729,0.9148994,0.008805596,0.0008846348,0.000301673,0.000061063765,0.000040714214,0.000112885784],"genre_scores_gemma":[0.82850033,0.000006969616,0.17078237,0.00020942392,0.0001381036,0.00002174941,0.00002117769,0.000013284555,0.00030662358],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99810606,0.0001251005,0.0006967312,0.00016291556,0.0007201832,0.00018901698],"domain_scores_gemma":[0.99838334,0.0003740916,0.0005771123,0.00013668448,0.00044326167,0.00008551081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001092818,0.00014196157,0.00018307727,0.00025193847,0.0007034692,0.00024429537,0.00047428452,0.00005434974,0.00006093831],"category_scores_gemma":[0.00047177204,0.0001057234,0.00010589452,0.0002032402,0.00006838823,0.0002891294,0.00026172353,0.00043005813,0.000005545599],"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":[0.00008248842,0.0013881281,0.007643421,0.00003871643,0.00040599098,0.000059262442,0.0068006422,0.5399994,0.0056536705,0.42144218,0.0021198923,0.014366199],"study_design_scores_gemma":[0.0041432222,0.0007438959,0.04630585,0.00036963934,0.00028723388,0.002360906,0.0041096285,0.8219893,0.000069186215,0.11123893,0.007676292,0.00070591114],"about_ca_topic_score_codex":0.00004057614,"about_ca_topic_score_gemma":0.000041364186,"teacher_disagreement_score":0.7537042,"about_ca_system_score_codex":0.0001980576,"about_ca_system_score_gemma":0.00013689863,"threshold_uncertainty_score":0.5410587},"labels":[],"label_agreement":null},{"id":"W4285267709","doi":"10.2316/j.2022.206-0510","title":"MLC-SLAM: MASK LOOP CLOSING FOR MONOCULAR SLAM, 107-114.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Closing (real estate); Monocular; Loop (graph theory); Simultaneous localization and mapping; Artificial intelligence; Computer vision; Computer science; Political science; Mathematics; Robot; Law; Mobile robot","score_opus":0.017480433809966174,"score_gpt":0.27211997951356576,"score_spread":0.2546395457035996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285267709","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013542428,0.00023714724,0.9788613,0.004807269,0.0023248582,0.000101245525,0.000007840511,0.000036357924,0.00008160164],"genre_scores_gemma":[0.35779497,0.000029560533,0.64133227,0.0003180998,0.00032611057,0.0000072312364,0.0000126991345,0.000013044767,0.00016600263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985277,0.00006235336,0.0004507058,0.00015690153,0.00065781473,0.00014450109],"domain_scores_gemma":[0.99878395,0.00013716564,0.0005138504,0.0001217424,0.00038279445,0.000060475628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066917884,0.00010254288,0.0001580171,0.0002740928,0.00017951644,0.0002492306,0.0006919971,0.000031325966,0.0000070821143],"category_scores_gemma":[0.00010636165,0.00010244473,0.00009422318,0.0001296824,0.000019200785,0.0005199341,0.00020827669,0.00017323765,0.000001857776],"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":[0.000027372334,0.00012293791,0.0007762633,0.000015991767,0.00018226368,0.00012438915,0.0010775917,0.8739207,0.0015800865,0.030491188,0.0013018602,0.09037938],"study_design_scores_gemma":[0.0006798069,0.00017696411,0.0015604225,0.000043387157,0.000018715838,0.00055151683,0.0000700627,0.98684084,0.00029177548,0.008266495,0.0013815402,0.00011846584],"about_ca_topic_score_codex":0.0000044258627,"about_ca_topic_score_gemma":1.7683291e-7,"teacher_disagreement_score":0.34425253,"about_ca_system_score_codex":0.00013938468,"about_ca_system_score_gemma":0.00009854614,"threshold_uncertainty_score":0.41775748},"labels":[],"label_agreement":null},{"id":"W4285286563","doi":"10.2316/j.2022.206-0589","title":"DEEP HASHING MULTI-LABEL IMAGE RETRIEVAL WITH ATTENTION MECHANISM, 372-381.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Mechanism (biology); Hash function; Image retrieval; Image (mathematics); Artificial intelligence; Computer security; Physics","score_opus":0.01236806761516669,"score_gpt":0.2587122412035198,"score_spread":0.24634417358835314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285286563","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":[0.05540644,0.00010164348,0.9433745,0.00065650657,0.00023716003,0.00006201163,0.0000052380833,0.00009135376,0.00006510462],"genre_scores_gemma":[0.68354577,0.000050968792,0.3162384,0.000039081166,0.000065338594,0.0000037238422,0.000013393889,0.000015284628,0.000027995939],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926555,0.000014047077,0.00025015825,0.00006653369,0.00032750424,0.000076188255],"domain_scores_gemma":[0.99949205,0.000017201339,0.00017338434,0.00004935331,0.00023671883,0.00003129786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021222093,0.000075480624,0.000086528875,0.00014630881,0.000117682095,0.00013149854,0.00016546792,0.000021425101,0.000018011056],"category_scores_gemma":[0.00001391021,0.00007121971,0.000027374248,0.00009635609,0.000015899821,0.00032251692,0.000044557877,0.0001847233,0.0000011504675],"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":[0.00018403736,0.0006547861,0.0005799311,0.00015507129,0.0005750564,0.00017292768,0.0015844232,0.4051528,0.45171437,0.031512544,0.0009359819,0.10677809],"study_design_scores_gemma":[0.0005788903,0.00007178954,0.00048203653,0.000041720155,0.000027095468,0.0003156667,0.00011828363,0.9927899,0.003290892,0.0020227472,0.00016335696,0.00009757278],"about_ca_topic_score_codex":0.0000017015811,"about_ca_topic_score_gemma":8.696979e-7,"teacher_disagreement_score":0.6281394,"about_ca_system_score_codex":0.000107524145,"about_ca_system_score_gemma":0.000018457733,"threshold_uncertainty_score":0.29042554},"labels":[],"label_agreement":null},{"id":"W4285299332","doi":"10.2316/j.2022.206-0471","title":"BRAIN-INSPIRED COGNITIVE MAP BUILDING FOR MOBILE ROBOT, 88-96.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mobile robot; Cognitive map; Computer science; Robot; Cognition; Artificial intelligence; Mechanism (biology); Mobile robot navigation; Computer vision; Human–computer interaction; Psychology; Neuroscience; Robot control","score_opus":0.010514439023549729,"score_gpt":0.25798622200085963,"score_spread":0.2474717829773099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285299332","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":[0.22017543,0.0011720409,0.7707928,0.0017619121,0.0052226367,0.0004407468,0.00010581892,0.0001623481,0.00016628322],"genre_scores_gemma":[0.9894723,0.0000378511,0.009920658,0.00010254522,0.0003069516,0.000025312453,0.000031163538,0.000027423992,0.000075774544],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989037,0.000029792347,0.00047117,0.000089647736,0.00037597597,0.0001297514],"domain_scores_gemma":[0.99918514,0.00017703217,0.00024507937,0.000046678382,0.00029159462,0.00005448111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035439344,0.000112014684,0.00018182791,0.00023283057,0.000118491305,0.000116001116,0.0001843082,0.00003614581,0.000024472094],"category_scores_gemma":[0.00004692573,0.00011494096,0.00009445045,0.00007519665,0.000015608692,0.00019389551,0.000047190268,0.00014647921,0.0000016370335],"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":[0.000017803719,0.000034859113,0.00012076539,0.00003464635,0.00018372572,0.000015539996,0.0002758878,0.9811926,0.006284878,0.0013645053,0.001687068,0.008787713],"study_design_scores_gemma":[0.0011267212,0.00019991503,0.0005560689,0.00012214994,0.000038856997,0.00020520341,0.00040116775,0.98916745,0.0013911693,0.00091417617,0.0057132975,0.00016382743],"about_ca_topic_score_codex":0.0000023936814,"about_ca_topic_score_gemma":5.7746837e-7,"teacher_disagreement_score":0.7692969,"about_ca_system_score_codex":0.00012700594,"about_ca_system_score_gemma":0.000029290255,"threshold_uncertainty_score":0.4687156},"labels":[],"label_agreement":null},{"id":"W4285300723","doi":"10.2316/j.2022.206-0743","title":"AUTOMATIC SELECTION OF XRF SPECTRAL FEATURE VARIABLES FOR SOIL HEAVY METAL BASED ON FiPLS AND BiPLS, 52-59.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Feature selection; Heavy metals; Metal; Selection (genetic algorithm); Range (aeronautics); Analytical Chemistry (journal); Noise (video); Feature (linguistics); Environmental chemistry; Environmental science; Chemistry; Materials science; Computer science; Artificial intelligence; Metallurgy","score_opus":0.010086178599053931,"score_gpt":0.23430843254487851,"score_spread":0.2242222539458246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285300723","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":[0.2245665,0.00018884896,0.75180155,0.021362806,0.0012792266,0.00021965957,0.000025121142,0.000052976284,0.00050329615],"genre_scores_gemma":[0.9410159,0.000009777579,0.058636576,0.00012427151,0.00008338568,0.0000037022494,0.000008383356,0.000002151929,0.00011583958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915665,0.00004630827,0.00026115985,0.000112143,0.00033974575,0.00008399974],"domain_scores_gemma":[0.99909997,0.00015960964,0.00038763112,0.000059359423,0.00025993274,0.000033515946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046300754,0.0000770658,0.00013748552,0.00016252186,0.00010918414,0.00007411223,0.00022864409,0.000032454886,0.00002383887],"category_scores_gemma":[0.00012327735,0.00006962949,0.00005755771,0.0001330085,0.000018385257,0.00018682878,0.00006148691,0.00012449003,1.5987384e-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":[0.00009863949,0.00028884382,0.0014965889,0.00012187996,0.00019213642,0.000014784152,0.00036666566,0.91619384,0.009959648,0.045291893,0.001713953,0.024261141],"study_design_scores_gemma":[0.00056027604,0.00029326894,0.0033280896,0.00004747405,0.00001897616,0.00017442994,0.000030615825,0.9810744,0.004551627,0.00900947,0.00084234943,0.00006900775],"about_ca_topic_score_codex":0.000002527987,"about_ca_topic_score_gemma":6.889004e-7,"teacher_disagreement_score":0.71644944,"about_ca_system_score_codex":0.000047794638,"about_ca_system_score_gemma":0.00007665191,"threshold_uncertainty_score":0.28394082},"labels":[],"label_agreement":null},{"id":"W4285305064","doi":"10.2316/j.2022.206-0730","title":"CULTIVATED LAND SEGMENTATION OF REMOTE SENSING IMAGE BASED ON PSPNET OF ATTENTION MECHANISM, 11-19.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Segmentation; Mechanism (biology); Remote sensing; Food security; Cultivated land; Image segmentation; Geography; Computer vision; Agriculture","score_opus":0.012057245204086109,"score_gpt":0.24257861392565405,"score_spread":0.23052136872156795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285305064","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":[0.92874414,0.000018382352,0.070011035,0.00051933574,0.0004873075,0.000050458188,0.000035764966,0.000006586304,0.00012697146],"genre_scores_gemma":[0.9659517,0.000020801313,0.033810828,0.000058009256,0.00004417709,5.169685e-9,0.000099478326,0.0000023527364,0.000012643818],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989775,0.00008928732,0.00033764882,0.00006577303,0.0004749162,0.000054873046],"domain_scores_gemma":[0.9991122,0.00007836192,0.00053021876,0.000042357944,0.00020475111,0.00003211563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037711085,0.000058022433,0.00011552751,0.00020952307,0.000058839043,0.00002605444,0.00006986781,0.000020283522,0.00005828681],"category_scores_gemma":[0.00004062402,0.000048567756,0.000050197716,0.00008724986,0.000018372193,0.000104235536,0.000007087712,0.000077278695,5.838019e-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":[0.0003175982,0.000060216833,0.020219356,0.00003768281,0.00008493459,0.00004072832,0.00036045982,0.78265357,0.012761439,0.000103470506,0.00012377945,0.1832368],"study_design_scores_gemma":[0.00073367934,0.00022858632,0.053991843,0.000071923074,0.000022704837,0.00009273047,0.00014408905,0.9417738,0.0020784049,0.0007724904,0.000037895225,0.000051875406],"about_ca_topic_score_codex":0.00033115078,"about_ca_topic_score_gemma":0.00003722555,"teacher_disagreement_score":0.18318492,"about_ca_system_score_codex":0.000013220456,"about_ca_system_score_gemma":0.00003534758,"threshold_uncertainty_score":0.19805355},"labels":[],"label_agreement":null},{"id":"W4285310183","doi":"10.2316/j.2022.206-0582","title":"APPLICATION OF NEURAL NETWORKS FOR ROBOT 3D MAPPING AND ANNOTATION USING DEPTH IMAGE CAMERA, 529-536.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Annotation; Artificial neural network; Image (mathematics)","score_opus":0.012201405623053838,"score_gpt":0.2452622407077393,"score_spread":0.23306083508468547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285310183","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":[0.12988956,0.00022661255,0.86916536,0.00013693466,0.0004217657,0.00012316064,0.000008691416,0.000016005277,0.000011904681],"genre_scores_gemma":[0.9319103,0.00006428551,0.067783736,0.000034652363,0.00013525959,0.0000040152677,0.000048537808,0.0000165466,0.0000027156782],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991231,0.000021879941,0.0004450926,0.00008009864,0.00024392265,0.00008593415],"domain_scores_gemma":[0.99921936,0.000068031346,0.00031810958,0.000047490492,0.00031223483,0.000034794924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022701113,0.00008783364,0.00014417527,0.00021514551,0.00008559984,0.000052359603,0.00008685079,0.000033038443,0.0000031495777],"category_scores_gemma":[0.000025882187,0.0000956181,0.000042880223,0.00010502496,0.000022623984,0.00021557005,0.000026432484,0.00010152211,5.4886772e-8],"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":[0.00001678098,0.000018121395,0.0008217946,0.000030264357,0.00004893992,0.0000015080216,0.00016049636,0.965825,0.008048128,0.00081704825,0.00002376536,0.024188139],"study_design_scores_gemma":[0.00048350505,0.000058759742,0.0033051723,0.000024606574,0.0000318202,0.00006183972,0.00012094371,0.9951141,0.0002458805,0.00039240703,0.00007468278,0.00008626886],"about_ca_topic_score_codex":0.000009627332,"about_ca_topic_score_gemma":0.0000018726815,"teacher_disagreement_score":0.80202067,"about_ca_system_score_codex":0.00008429397,"about_ca_system_score_gemma":0.000014425978,"threshold_uncertainty_score":0.3899193},"labels":[],"label_agreement":null},{"id":"W4287855185","doi":"10.2316/j.2022.206-0739","title":"OPTIMAL COVERAGE PATH PLANNING FOR TRACTORS IN HILLY AREAS BASED ON ENERGY CONSUMPTION MODEL","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Technology and Security Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Headland; Energy consumption; Motion planning; Consumption (sociology); Path (computing); Energy (signal processing); Computer science; Energy planning; Mathematical optimization; Operations research; Agricultural engineering; Engineering; Mathematics; Statistics; Artificial intelligence; Geology; Renewable energy; Computer network","score_opus":0.018301045265877447,"score_gpt":0.26234651402245407,"score_spread":0.24404546875657662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287855185","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":[0.15714975,0.000041097865,0.841053,0.001238291,0.00042827064,0.000038898466,0.000009296282,0.000017431512,0.000023952525],"genre_scores_gemma":[0.98271215,0.00000777698,0.017021423,0.00020594681,0.000028963936,0.000005403686,0.000007866666,0.000003253622,0.0000072456833],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924845,0.00003610084,0.00026628323,0.00009006516,0.00029083408,0.00006828743],"domain_scores_gemma":[0.99944484,0.00012030845,0.00026869585,0.000055155655,0.0000896338,0.000021393013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031689784,0.000056409583,0.00009363099,0.0003056616,0.00006447183,0.00005894345,0.00027948202,0.000036648133,0.0000023357743],"category_scores_gemma":[0.000039229843,0.000055752032,0.000039261828,0.00005097551,0.000010009471,0.00022241741,0.000039937477,0.00012315123,1.2012944e-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":[0.00003693977,0.00006906081,0.00134238,0.0000033682993,0.000010713021,0.000020851767,0.0002633857,0.94960535,0.00010590094,0.04445977,0.000085352134,0.003996932],"study_design_scores_gemma":[0.0006921715,0.0001576984,0.0025537924,0.00004155362,0.000002612612,0.00006363216,0.000020117312,0.9928162,0.0000751095,0.003323428,0.0001984705,0.000055200224],"about_ca_topic_score_codex":0.000003010732,"about_ca_topic_score_gemma":8.778157e-7,"teacher_disagreement_score":0.82556236,"about_ca_system_score_codex":0.00007906127,"about_ca_system_score_gemma":0.000056936045,"threshold_uncertainty_score":0.22735019},"labels":[],"label_agreement":null},{"id":"W4287888933","doi":"10.2316/j.2022.206-0797","title":"A SLIDING MODE FAULT RECONSTRUCTION METHOD USING IMPROVED REDUCED ORDER MODEL","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Degree (music); Fault (geology); Mode (computer interface); Actuator; Scheme (mathematics); Computer science; Order (exchange); Mathematics; Physics; Artificial intelligence; Geology; Control (management); Mathematical analysis; Seismology","score_opus":0.015077404940828208,"score_gpt":0.28100912720868504,"score_spread":0.26593172226785683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287888933","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":[0.22496593,0.00007630441,0.7726615,0.00019364261,0.0018919327,0.00005531005,0.0000065890986,0.000043393782,0.00010538561],"genre_scores_gemma":[0.9297352,0.00001848551,0.0700265,0.000026880474,0.00014617022,0.0000030325432,0.0000022764982,0.000013082442,0.000028357801],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919224,0.000041753803,0.00036962726,0.00006564762,0.00025634753,0.00007441245],"domain_scores_gemma":[0.9994877,0.000023180415,0.00020039441,0.000041180425,0.00021170932,0.00003586052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002699663,0.00007496394,0.0001240919,0.000222055,0.000087994755,0.00007110086,0.000095572126,0.0000308571,0.000014861317],"category_scores_gemma":[0.000029883638,0.000077377175,0.00005206368,0.00009281355,0.000004851841,0.00024610138,0.000022842054,0.00016972779,2.5674106e-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":[0.0000145096365,0.0000070932,0.0000075211947,0.000005047167,0.00007106074,0.0000018692716,0.00016279025,0.84925705,0.13130435,0.00032540102,0.000018975948,0.018824345],"study_design_scores_gemma":[0.00049742276,0.000025044394,0.00001611677,0.000022631348,0.000021178548,0.0007894324,0.00024289804,0.99622905,0.0013214515,0.0006628827,0.000093584065,0.000078309946],"about_ca_topic_score_codex":0.000014676382,"about_ca_topic_score_gemma":0.0000018944106,"teacher_disagreement_score":0.70476925,"about_ca_system_score_codex":0.0002124084,"about_ca_system_score_gemma":0.000036055673,"threshold_uncertainty_score":0.31553495},"labels":[],"label_agreement":null},{"id":"W4293705096","doi":"10.2316/j.2022.206-0580","title":"ANALYSIS OF THE DAMAGE COUPLING MODEL OF REINFORCED CONCRETE BEAMS BASED ON COMSOL","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Engineering and Vibration Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reinforced concrete; Structural engineering; Coupling (piping); Materials science; Engineering; Composite material","score_opus":0.00887688614494491,"score_gpt":0.22177209578058601,"score_spread":0.2128952096356411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293705096","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":[0.51216215,0.000016351709,0.48730606,0.00017654688,0.00021664743,0.000024956997,0.00002773481,0.000010886202,0.00005866922],"genre_scores_gemma":[0.9979277,0.000008507022,0.0019853506,0.00003493184,0.000012049969,5.4878524e-7,0.0000131193665,0.000004989984,0.00001278105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920434,0.000009347466,0.00034398754,0.000033769706,0.0003716343,0.000036928173],"domain_scores_gemma":[0.9994703,0.000055903834,0.00023799592,0.0000683795,0.0001501067,0.000017349972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014636942,0.00005265771,0.00015041148,0.00031759776,0.00002993411,0.000012658474,0.00015058703,0.000015972706,0.000024400999],"category_scores_gemma":[0.000026698095,0.000042149597,0.00013000629,0.00024507582,0.00001748,0.000057175697,0.00001952812,0.0000967409,4.176101e-8],"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":[0.000008227565,0.0000012038475,0.00018050298,0.000006806683,0.0003576014,3.2205594e-7,0.00008378166,0.99197525,0.006030269,0.0011430387,0.000013163348,0.00019984892],"study_design_scores_gemma":[0.00021262257,0.00002285431,0.0015289806,0.00001799363,0.00019297497,0.0000010277814,0.000052167856,0.99510103,0.002799529,0.000028609278,0.0000037815992,0.000038425722],"about_ca_topic_score_codex":0.0000035302248,"about_ca_topic_score_gemma":3.075298e-7,"teacher_disagreement_score":0.48576558,"about_ca_system_score_codex":0.000048777994,"about_ca_system_score_gemma":0.000017368542,"threshold_uncertainty_score":0.17188106},"labels":[],"label_agreement":null},{"id":"W4297098349","doi":"10.2316/j.2022.206-0811","title":"DISTURBANCE REJECTION DIFFERENTIAL TRACKING VARIABLE STRUCTURE CONTROLLER, 1-8.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Disturbance (geology); Nonlinear system; Tracking (education); Differential (mechanical device); Controller (irrigation); Active disturbance rejection control; Process (computing); Computer science; Derivative (finance); Mathematics; Control (management); Artificial intelligence; Engineering; Physics; State observer; Psychology; Biology","score_opus":0.006072493052172092,"score_gpt":0.20220289695381316,"score_spread":0.19613040390164108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297098349","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":[0.68234766,0.0008414619,0.30384445,0.0009136345,0.011276646,0.00018655845,0.0000528342,0.00015812748,0.00037861543],"genre_scores_gemma":[0.99912095,0.00001790431,0.00040637772,0.000017507955,0.0003865711,0.0000021826572,0.0000065727945,0.000007149668,0.000034777047],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993584,0.000027798085,0.00027214712,0.000047502814,0.00022782866,0.00006628503],"domain_scores_gemma":[0.9996617,0.00002807667,0.00016047132,0.000031123407,0.000101680336,0.000016968457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012162932,0.00006155776,0.000121579236,0.00011924995,0.00008717608,0.000051020306,0.00012715445,0.00005098658,0.000041592168],"category_scores_gemma":[0.000027550652,0.000058235488,0.00003371604,0.0000602101,0.000010535879,0.0001374187,0.000020027588,0.00025327486,2.6783343e-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":[0.00008559391,0.000029367398,0.00075634755,0.000009437992,0.00028986414,0.000013166495,0.00014214903,0.9243755,0.028214872,0.016976736,0.000602373,0.028504608],"study_design_scores_gemma":[0.003411371,0.00017870075,0.0056767943,0.00006442072,0.0000755428,0.00067337125,0.00023552017,0.9721864,0.0011610239,0.010031328,0.0060983417,0.00020722504],"about_ca_topic_score_codex":0.0000035892874,"about_ca_topic_score_gemma":6.870843e-7,"teacher_disagreement_score":0.31677327,"about_ca_system_score_codex":0.000101162645,"about_ca_system_score_gemma":0.000013096953,"threshold_uncertainty_score":0.23747744},"labels":[],"label_agreement":null},{"id":"W4315698448","doi":"10.37628/ijra.v8i2.1474","title":"Bibliometric Analysis of Robotic Process Automation","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Process Automation Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Automation; Process (computing); Globe; Computer science; Publish or perish; Domain (mathematical analysis); Bibliometrics; Publication; Process automation system; Engineering management; Data science; Software engineering; Engineering; World Wide Web; Publishing; Business; Political science; Mathematics","score_opus":0.012235399369153532,"score_gpt":0.27729529119872226,"score_spread":0.26505989182956874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315698448","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":[0.3925809,0.00052287267,0.6048836,0.0005963847,0.0007551543,0.00014125822,0.000027530514,0.0001286602,0.00036361325],"genre_scores_gemma":[0.99198556,0.000110516776,0.0077477666,0.000029824972,0.00004202652,0.000012299087,0.000044671255,0.000014894653,0.000012429532],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981447,0.000033666285,0.0007807846,0.00009450356,0.00084673933,0.000099604134],"domain_scores_gemma":[0.9985041,0.00010577417,0.00059243554,0.000106238775,0.00063527614,0.000056151075],"candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.00042353972,0.00010624068,0.0002784837,0.032678936,0.00007232981,0.000067267945,0.00035132156,0.000034867586,0.0001109372],"category_scores_gemma":[0.00009380632,0.00011199795,0.00011280713,0.027967915,0.0000276626,0.00037982353,0.000049171726,0.00015048083,0.0000016589456],"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":[0.0000045754173,0.000064755695,0.002169127,0.000031474356,0.00068846456,0.000002233088,0.00029857125,0.97952884,0.00067385065,0.0019850829,0.00010680212,0.014446205],"study_design_scores_gemma":[0.00027142174,0.000039500166,0.0934016,0.000015737593,0.00032719987,0.000045077246,0.0001448018,0.9042974,0.00030861126,0.0009803979,0.00007419436,0.00009407413],"about_ca_topic_score_codex":0.0000030025215,"about_ca_topic_score_gemma":0.0000010606198,"teacher_disagreement_score":0.59940463,"about_ca_system_score_codex":0.00014548433,"about_ca_system_score_gemma":0.000055892466,"threshold_uncertainty_score":0.9926931},"labels":[],"label_agreement":null},{"id":"W4317791174","doi":"10.2316/j.2023.206-0868","title":"A NOVEL MINING BELT CONVEYOR INSPECTION ROBOT USED IN EXTREMELY COLD CONDITIONS, 155-169.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Belt Conveyor Systems Engineering","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Coal mining; Conveyor belt; Belt conveyor; Mining engineering; Robot; Coal; Automotive engineering; Computer science; Environmental science; Engineering; Artificial intelligence; Mechanical engineering; Waste management","score_opus":0.02058478127792479,"score_gpt":0.24959296289427219,"score_spread":0.2290081816163474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791174","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":[0.8584753,0.00018579178,0.13703796,0.0005524158,0.0031424267,0.00013251496,0.000017118118,0.00032090524,0.00013551294],"genre_scores_gemma":[0.99600714,0.00008317272,0.0035904136,0.000015906393,0.00022012378,0.0000054837246,0.000020821184,0.000025887379,0.000031037413],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988824,0.00001528893,0.00054663303,0.00008666108,0.00033239325,0.00013662715],"domain_scores_gemma":[0.9994483,0.00010106194,0.0001570017,0.00005995292,0.00017802346,0.000055667057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032631322,0.0001181682,0.00018551889,0.0006663238,0.000030626143,0.00009333743,0.00013261044,0.00007492838,0.000006361038],"category_scores_gemma":[0.00007065921,0.00012979507,0.000048094676,0.00028414442,0.000017159628,0.0003931137,0.00002215201,0.00015832568,0.000007897889],"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":[0.000005392457,0.000022858403,0.00358494,0.000041983858,0.00010031449,0.00004712988,0.00048694696,0.8844346,0.10777089,0.0021471954,0.00040205082,0.00095571106],"study_design_scores_gemma":[0.0010463634,0.00002956088,0.070201755,0.0003480728,0.000014680217,0.0002163976,0.00022407067,0.92515606,0.0023222854,0.00008226134,0.00020909897,0.00014939015],"about_ca_topic_score_codex":0.000012824246,"about_ca_topic_score_gemma":0.000031736225,"teacher_disagreement_score":0.1375318,"about_ca_system_score_codex":0.00017692443,"about_ca_system_score_gemma":0.00002737828,"threshold_uncertainty_score":0.52928895},"labels":[],"label_agreement":null},{"id":"W4317791201","doi":"10.2316/j.2023.206-0790","title":"HUMAN BACK ACUPUNCTURE POINTS LOCATION USING RGB-D IMAGE FOR TCM MASSAGE ROBOTS, 67-75.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Massage; Acupuncture; Artificial intelligence; Robot; Computer science; Medicine; Computer vision; Image (mathematics); Traditional medicine; RGB color model; Physical medicine and rehabilitation; Alternative medicine; Pathology","score_opus":0.01760887826807956,"score_gpt":0.27802268277108966,"score_spread":0.2604138045030101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791201","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":[0.055448763,0.000107785374,0.9398451,0.002183867,0.0018070285,0.00023802908,0.000013460467,0.00012290191,0.00023308059],"genre_scores_gemma":[0.97086537,0.00006277486,0.028184202,0.00010777894,0.00051596924,0.0000033690972,0.00004901238,0.00003303805,0.00017847604],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990103,0.000021184622,0.00044282817,0.00008913173,0.00029969297,0.00013682927],"domain_scores_gemma":[0.99915695,0.000051614225,0.00019540971,0.00007377067,0.00045869808,0.000063527565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028890322,0.00014036146,0.0001830338,0.00027013247,0.000065808534,0.00016016804,0.00016497592,0.000076155746,0.000039177263],"category_scores_gemma":[0.000060777154,0.000116248426,0.00009537699,0.00013122462,0.000020618132,0.00038456885,0.000022729211,0.00011517736,0.000022314829],"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":[0.000009089445,0.000022547745,0.00017990862,0.000060288592,0.0001473276,0.000009702268,0.00015403597,0.97382474,0.0152987,0.0019388081,0.0025769842,0.0057778507],"study_design_scores_gemma":[0.0010793282,0.00003947655,0.0067907083,0.00014254254,0.000047985533,0.00006718525,0.00007231595,0.9882736,0.00061090995,0.002384516,0.00036026625,0.000131128],"about_ca_topic_score_codex":0.0000020869375,"about_ca_topic_score_gemma":0.0000017569386,"teacher_disagreement_score":0.9154166,"about_ca_system_score_codex":0.0001116671,"about_ca_system_score_gemma":0.000022212549,"threshold_uncertainty_score":0.4740473},"labels":[],"label_agreement":null},{"id":"W4317791203","doi":"10.2316/j.2023.206-0321","title":"INDOOR LOCALIZATION SYSTEM OF ROS MOBILE ROBOT BASED ON VISIBLE LIGHT COMMUNICATION, 1-12.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visible light communication; Robot; Mobile robot; Computer science; Artificial intelligence; Computer vision; Light-emitting diode; Engineering; Electrical engineering","score_opus":0.009473166191224982,"score_gpt":0.24199620607791855,"score_spread":0.23252303988669357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791203","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":[0.097487174,0.0013369167,0.8890019,0.005471111,0.0013868677,0.0005537315,0.000030991425,0.0013504836,0.003380843],"genre_scores_gemma":[0.9904295,0.00074027583,0.00872132,0.000018409639,0.000028557386,0.000007920463,0.000025835117,0.000016291915,0.000011899132],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892604,0.000048754864,0.000512633,0.000055809334,0.0003733385,0.000083402425],"domain_scores_gemma":[0.9988154,0.00019102752,0.0002565163,0.00022442143,0.00047745547,0.000035190133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035822255,0.000084978405,0.00015952077,0.00048688674,0.00005559141,0.000067368725,0.00041330405,0.00008941525,0.00000584093],"category_scores_gemma":[0.0001430942,0.00008247921,0.000046543235,0.00023154421,0.00004645356,0.00019922273,0.000053666074,0.00014389168,0.000007693491],"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":[0.0000088716815,0.000036028534,0.00054693606,0.000048414528,0.000043160664,0.0000021113199,0.00015272386,0.97504884,0.00087075465,0.013234186,0.00031539286,0.009692566],"study_design_scores_gemma":[0.00040287737,0.00006790692,0.002197979,0.00043362245,0.000011487057,0.0000062045297,0.00030038934,0.9885043,0.0068011447,0.00040707545,0.0007888242,0.00007822531],"about_ca_topic_score_codex":0.0000032613532,"about_ca_topic_score_gemma":0.0000026713672,"teacher_disagreement_score":0.8929423,"about_ca_system_score_codex":0.00012715391,"about_ca_system_score_gemma":0.00003205339,"threshold_uncertainty_score":0.33634043},"labels":[],"label_agreement":null},{"id":"W4317791204","doi":"10.2316/j.2023.206-0580","title":"ANALYSIS OF THE DAMAGE COUPLING MODEL OF REINFORCED CONCRETE BEAMS BASED ON COMSOL, 13-19.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Behavior of Reinforced Concrete","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reinforced concrete; Coupling (piping); Materials science; Structural engineering; Composite material; Engineering","score_opus":0.01618572573305894,"score_gpt":0.2537064916689888,"score_spread":0.23752076593592986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791204","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":[0.94101286,0.00000979283,0.058308605,0.00015586287,0.00031272488,0.000051928128,0.000029897337,0.000028048964,0.00009026267],"genre_scores_gemma":[0.9978546,0.000030219819,0.0020111913,0.000028672412,0.000022392152,5.576103e-7,0.000020113044,0.000009145618,0.000023102903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889344,0.000007742852,0.00048789484,0.000049682418,0.0004875638,0.00007365167],"domain_scores_gemma":[0.9990815,0.00012564428,0.00035989063,0.00010851001,0.00028820694,0.00003625965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018939418,0.000085904154,0.00021314023,0.00043995815,0.000023833796,0.000024981133,0.00023752461,0.000049073922,0.00000943607],"category_scores_gemma":[0.000083057384,0.00006638007,0.0001606146,0.00033393447,0.000040735566,0.00012295018,0.000027574279,0.000114521696,4.328161e-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":[0.000013285683,1.4473184e-7,0.000671227,0.000013175705,0.0002309138,0.0000015358495,0.00009169828,0.9751162,0.022771789,0.0008014913,0.00002073668,0.00026782672],"study_design_scores_gemma":[0.00035681768,0.000027819247,0.0076317806,0.00008522004,0.0002136246,0.0000021236563,0.000031772997,0.9797813,0.011769337,0.000037947328,0.0000029125906,0.000059307702],"about_ca_topic_score_codex":0.000006827692,"about_ca_topic_score_gemma":3.5001847e-7,"teacher_disagreement_score":0.05684173,"about_ca_system_score_codex":0.00005143307,"about_ca_system_score_gemma":0.000033047167,"threshold_uncertainty_score":0.27069005},"labels":[],"label_agreement":null},{"id":"W4317791215","doi":"10.2316/j.2023.206-0739","title":"OPTIMAL COVERAGE PATH PLANNING FOR TRACTORS IN HILLY AREAS BASED ON ENERGY CONSUMPTION MODEL, 20-31.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Systems and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Headland; Energy consumption; Computer science; Path (computing); Motion planning; Consumption (sociology); Energy (signal processing); Mathematical optimization; Energy planning; Agricultural engineering; Operations research; Engineering; Mathematics; Artificial intelligence; Statistics; Geology; Computer network; Renewable energy; Electrical engineering","score_opus":0.020113731314844622,"score_gpt":0.257746804912169,"score_spread":0.23763307359732438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791215","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":[0.48002326,0.00007333856,0.51872545,0.00025758924,0.0006228883,0.000047111407,0.000025678535,0.00010024363,0.00012443839],"genre_scores_gemma":[0.9966468,0.00007695847,0.0031565577,0.000020027543,0.000050597286,0.000003912596,0.000022490598,0.000009634854,0.000013021463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942297,0.000005603763,0.00026035152,0.000054037217,0.00017646188,0.00008055563],"domain_scores_gemma":[0.99967515,0.00009537357,0.00010363816,0.000035173587,0.00007001713,0.000020625375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014736006,0.00007067485,0.000104838036,0.00035278447,0.000016961301,0.000048608963,0.00008429346,0.00006044862,0.0000014214411],"category_scores_gemma":[0.00004447779,0.00006526525,0.0000366896,0.000053309075,0.000008221165,0.00014387253,0.000007954493,0.000073679264,6.941672e-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":[0.000017318174,0.000012680165,0.0009933152,0.000014989329,0.000020982992,0.000016675876,0.000056381443,0.9929513,0.00052225235,0.0013834308,0.0005694452,0.0034412718],"study_design_scores_gemma":[0.00051444845,0.000050615818,0.0049466537,0.00020238898,0.0000045753654,0.000011212984,0.000020021165,0.99292946,0.00033799632,0.0006232164,0.00029466828,0.00006475221],"about_ca_topic_score_codex":0.0000017679594,"about_ca_topic_score_gemma":0.0000013875631,"teacher_disagreement_score":0.51662356,"about_ca_system_score_codex":0.00006151512,"about_ca_system_score_gemma":0.000017796656,"threshold_uncertainty_score":0.26614398},"labels":[],"label_agreement":null},{"id":"W4317791217","doi":"10.2316/j.2023.206-0751","title":"CONSENSUS CONTROL OF MULTIPLE AUTONOMOUS UNDERWATER VEHICLES UNDER DELAYS AIMING FOR DYNAMIC TARGET HUNTING TASKS, 42-49.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Underwater; Control (management); Computer science; Real-time computing; Artificial intelligence; Geography","score_opus":0.015993498423347827,"score_gpt":0.2510306148805057,"score_spread":0.23503711645715789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791217","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":[0.43673405,0.00021549728,0.5613004,0.0011813119,0.00032582215,0.000116175055,0.00003157526,0.00006909387,0.00002608197],"genre_scores_gemma":[0.9867425,0.00006037381,0.013018101,0.000033020853,0.000069696376,0.0000041874437,0.000026505188,0.000021360242,0.000024247005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896735,0.000029657696,0.00059758936,0.00006911391,0.0002119116,0.00012436234],"domain_scores_gemma":[0.9989898,0.0002680052,0.00028501762,0.000077428806,0.00034061234,0.000039131413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034895886,0.000098577904,0.00019475381,0.00022529284,0.000055030785,0.000074103344,0.00018491711,0.00006002914,0.0000026928853],"category_scores_gemma":[0.000018534914,0.000091431146,0.00008334091,0.00007139498,0.000029088678,0.00012501293,0.000029335773,0.000090587586,0.0000032578203],"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":[0.000026250891,0.000023982628,0.0022670869,0.0000762324,0.00030337155,0.0000035872015,0.00043595867,0.91918635,0.071311615,0.0004945011,0.000065350694,0.005805677],"study_design_scores_gemma":[0.0011545027,0.00003787108,0.0055696215,0.00011640714,0.000027331756,0.000043367,0.0003706423,0.9847405,0.005165112,0.0020933116,0.0005829872,0.00009832212],"about_ca_topic_score_codex":0.000011649956,"about_ca_topic_score_gemma":0.000010959073,"teacher_disagreement_score":0.5500085,"about_ca_system_score_codex":0.000073398,"about_ca_system_score_gemma":0.000026179358,"threshold_uncertainty_score":0.3728454},"labels":[],"label_agreement":null},{"id":"W4317791222","doi":"10.2316/j.2023.206-0754","title":"TIME-OPTIMAL TRAJECTORY GENERATION FOR INDUSTRIAL ROBOTS BASED ON ELITE MUTATION SPARROW SEARCH ALGORITHM, 126-135.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Sparrow; Elite; Computer science; Robot; Mutation; Algorithm; Trajectory optimization; Mathematical optimization; Mathematics; Artificial intelligence; Biology; Physics; Genetics; Political science","score_opus":0.04996422944326542,"score_gpt":0.3004088546636162,"score_spread":0.2504446252203508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791222","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021718303,0.000021222962,0.9728611,0.0029804253,0.0020825258,0.00019783953,0.000017970655,0.00009109426,0.000029500243],"genre_scores_gemma":[0.16509287,0.0000305669,0.83190477,0.00032745468,0.0021622127,0.00001458681,0.00022970534,0.000031309522,0.00020650293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980477,0.00010884273,0.0005240425,0.00023323033,0.0008843231,0.00020188131],"domain_scores_gemma":[0.998372,0.0003378529,0.00038177878,0.00013398891,0.00067503116,0.0000993101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011132809,0.00014758513,0.0001912275,0.00065833476,0.000118953336,0.00032197323,0.00043304535,0.00011476103,0.0000052228083],"category_scores_gemma":[0.00023474815,0.0001411888,0.000098562145,0.0002856833,0.0000334488,0.000583139,0.000044905304,0.00019786312,0.00002236628],"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":[0.000020039903,0.000046995854,0.000032853706,0.0000044089247,0.000042999873,0.000040971758,0.00022592767,0.896845,0.001574941,0.00035556595,0.0012008835,0.09960945],"study_design_scores_gemma":[0.0013633147,0.00032955073,0.0013816187,0.00010438216,0.000015797155,0.00006496212,0.000019851166,0.99524444,0.0010727204,0.00018148065,0.00008579502,0.00013606598],"about_ca_topic_score_codex":0.000002973519,"about_ca_topic_score_gemma":2.1791612e-7,"teacher_disagreement_score":0.14337458,"about_ca_system_score_codex":0.00013854407,"about_ca_system_score_gemma":0.00021317137,"threshold_uncertainty_score":0.5757512},"labels":[],"label_agreement":null},{"id":"W4317791239","doi":"10.2316/j.2023.206-0782","title":"MOBILE ROBOT DOCKING WITH OBSTACLE AVOIDANCE AND VISUAL SERVOING AVOIDANCE AND VISUAL SERVOING, 97-108.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visual servoing; Obstacle avoidance; Computer vision; Computer science; Artificial intelligence; Mobile robot; Collision avoidance; Robot; Computer security","score_opus":0.010095309885706286,"score_gpt":0.29351200225230395,"score_spread":0.28341669236659767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317791239","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":[0.37407625,0.00044862228,0.6241904,0.00079132133,0.000336307,0.000065288325,0.000001015862,0.00006182099,0.0000289819],"genre_scores_gemma":[0.9303034,0.00044466564,0.06882435,0.00020185475,0.00012568106,0.0000021270707,0.000002537799,0.000012220374,0.000083185296],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987055,0.00004201089,0.00037012587,0.0002257202,0.00047841534,0.00017822172],"domain_scores_gemma":[0.9989842,0.00013394158,0.0003921712,0.00006407987,0.0003226233,0.0001029426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035689806,0.00014179955,0.00018148507,0.00025807228,0.00017257355,0.00048365328,0.00021630063,0.00003551583,0.0000023984958],"category_scores_gemma":[0.00005973645,0.00012098825,0.000029330757,0.00023202275,0.00005436322,0.0015347046,0.00021284915,0.00019084544,0.0000037165503],"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":[0.000067193105,0.00011896962,0.013642279,0.00010068246,0.00014097009,0.00023317306,0.00333836,0.23872961,0.014016878,0.0031965892,0.000113154,0.72630215],"study_design_scores_gemma":[0.000724947,0.00022493569,0.019202223,0.00041501332,0.000009317398,0.0004208415,0.00025919217,0.97575194,0.0014472567,0.0010736182,0.0003070569,0.00016365408],"about_ca_topic_score_codex":0.0000050868666,"about_ca_topic_score_gemma":0.000003814951,"teacher_disagreement_score":0.73702234,"about_ca_system_score_codex":0.000044654236,"about_ca_system_score_gemma":0.000046218778,"threshold_uncertainty_score":0.49337575},"labels":[],"label_agreement":null},{"id":"W4317815191","doi":"10.2316/j.2023.206-0701","title":"TRAJECTORY OPTIMIZATION OF A SPOT-WELDING ROBOT IN THE JOINT AND CARTESIAN SPACES, 109-125.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Spot welding; Cartesian coordinate system; Joint (building); Computer science; Welding; Trajectory; Mathematics; Engineering; Mechanical engineering; Structural engineering; Geometry; Physics","score_opus":0.023415373023894837,"score_gpt":0.26397854018844263,"score_spread":0.2405631671645478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317815191","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":[0.06175294,0.00013620513,0.9332665,0.00415385,0.0005310581,0.00007213179,0.0000013052414,0.000022462442,0.000063499465],"genre_scores_gemma":[0.8163646,0.00012965877,0.18335548,0.000054344135,0.000076751945,9.822869e-7,0.000003330609,0.0000045030465,0.000010373582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988972,0.00008996355,0.00038789332,0.000098616685,0.0004317844,0.00009452039],"domain_scores_gemma":[0.9992269,0.00014834029,0.0003510942,0.00008272783,0.00015928724,0.000031606294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009782754,0.000074053496,0.00013740789,0.00038501646,0.000037401693,0.00014878465,0.00030878262,0.000038045066,0.0000010206448],"category_scores_gemma":[0.000114436814,0.00005697389,0.00003365366,0.00025427184,0.00003187165,0.0003942457,0.000058632657,0.000116001844,5.7487904e-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":[0.0000023887287,0.000021967982,0.0011875533,0.000010143543,0.00001982211,0.00004657209,0.0019298511,0.98639596,0.00035528955,0.0025511174,0.000051160194,0.0074281925],"study_design_scores_gemma":[0.00034030768,0.00006220116,0.054594707,0.00014555309,0.0000073261685,0.00020689891,0.00021404168,0.9434964,0.00013381329,0.00073081994,0.000012212691,0.000055705485],"about_ca_topic_score_codex":0.000011857595,"about_ca_topic_score_gemma":0.000001469953,"teacher_disagreement_score":0.7546116,"about_ca_system_score_codex":0.00003317913,"about_ca_system_score_gemma":0.000047593032,"threshold_uncertainty_score":0.2323328},"labels":[],"label_agreement":null},{"id":"W4319988162","doi":"10.2316/j.2023.206-0792","title":"KINEMATIC ANALYSIS OF THE VARIABLE HEIGHT ROTATING MECHANISM FOR END-TRACTION UPPER LIMB REHABILITATION ROBOT, 85-96.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Mechanism (biology); Traction (geology); Robot; Planar; Variable (mathematics); Computer science; Control theory (sociology); Physical medicine and rehabilitation; Physics; Mathematics; Engineering; Artificial intelligence; Medicine; Mechanical engineering; Classical mechanics; Mathematical analysis","score_opus":0.009251013570495849,"score_gpt":0.25564801979914226,"score_spread":0.2463970062286464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319988162","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":[0.22818445,0.000038651495,0.7675479,0.0026967498,0.0010674191,0.0002654512,0.000033908476,0.00006991561,0.00009558653],"genre_scores_gemma":[0.9314326,0.000052686326,0.068289965,0.00002642733,0.000104973224,0.0000105358085,0.00003493129,0.000014886691,0.000032968463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893504,0.000022604425,0.00055326545,0.00007884441,0.00031908156,0.00009117514],"domain_scores_gemma":[0.99851334,0.00046520444,0.0003507477,0.00010017375,0.0005406238,0.000029902954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003905376,0.000086771455,0.00018673395,0.00042905874,0.000069097754,0.000059810536,0.00016147157,0.00005284529,0.000012658287],"category_scores_gemma":[0.00028803953,0.000070164206,0.00016611823,0.00056579843,0.000022229784,0.00018733671,0.000021866239,0.000087547945,0.0000013569768],"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":[0.0000052524674,0.000025113739,0.00055314536,0.00004229883,0.00046723985,1.9978972e-7,0.00022743244,0.9362193,0.013031622,0.04805527,0.00011553032,0.0012576258],"study_design_scores_gemma":[0.00021919048,0.00003769651,0.023027118,0.00007838035,0.00034562786,0.0000061411197,0.00012230707,0.95734924,0.0011594566,0.017532377,0.00005509862,0.00006736984],"about_ca_topic_score_codex":0.0000050600906,"about_ca_topic_score_gemma":0.0000049153377,"teacher_disagreement_score":0.7032482,"about_ca_system_score_codex":0.0000538425,"about_ca_system_score_gemma":0.000023218792,"threshold_uncertainty_score":0.2861213},"labels":[],"label_agreement":null},{"id":"W4319988174","doi":"10.2316/j.2023.206-0876","title":"OPTIMISATION OF A SIX-DEGREE-OF-FREEDOM ROBOT TRAJECTORY BASED ON IMPROVED MULTI-OBJECTIVE PSO ALGORITHM, 218-230.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Degree (music); Computer science; Particle swarm optimization; Mathematical optimization; Algorithm; Mathematics; Physics","score_opus":0.017811422604680723,"score_gpt":0.27390275079262477,"score_spread":0.25609132818794406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319988174","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":[0.021304898,0.000049713988,0.97792745,0.0001538703,0.00031170875,0.00008872322,0.000017838816,0.00009466847,0.000051113868],"genre_scores_gemma":[0.6701508,0.00008351063,0.32965264,0.000009449173,0.000062472194,0.0000023724638,0.000015239105,0.00001432959,0.000009166919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998893,0.000027575343,0.00053517875,0.00008740981,0.00036888706,0.000087948116],"domain_scores_gemma":[0.9988942,0.00014846706,0.00038428965,0.00007999524,0.00045109948,0.00004196096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021858147,0.000115022434,0.00023961902,0.0004940962,0.000018267432,0.00001730677,0.00016184432,0.000063822554,0.0000073986844],"category_scores_gemma":[0.00011980538,0.00010527493,0.000104654966,0.00023989698,0.00004186239,0.00019297807,0.000018776194,0.00013717094,0.0000011535068],"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":[0.000022265871,0.00007201998,0.00010994098,0.000020583393,0.00011500834,0.000004113518,0.00009324773,0.9082615,0.025500504,0.0000866039,0.000025425694,0.06568879],"study_design_scores_gemma":[0.000673312,0.00017760544,0.0058916593,0.00012328028,0.00003626687,0.0000053415106,0.00005541589,0.97821605,0.014422262,0.0002964061,0.000012896416,0.00008948753],"about_ca_topic_score_codex":0.000009627684,"about_ca_topic_score_gemma":0.000002740946,"teacher_disagreement_score":0.6488459,"about_ca_system_score_codex":0.00010621485,"about_ca_system_score_gemma":0.000026768554,"threshold_uncertainty_score":0.4292987},"labels":[],"label_agreement":null},{"id":"W4319988238","doi":"10.2316/j.2023.206-0770","title":"KINEMATIC ANALYSIS AND DESIGN OF A HAPTIC DEVICE FOR NEUROSURGERY SIMULATION, 60-66","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Haptic technology; Computer science; Simulation; Physics","score_opus":0.03036428261075333,"score_gpt":0.28995133792507766,"score_spread":0.25958705531432436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319988238","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":[0.11620501,0.00006684699,0.8831104,0.00031674295,0.0001623058,0.00009337349,0.000007887733,0.0000312067,0.0000062352096],"genre_scores_gemma":[0.97344446,0.00013231797,0.02631365,0.000017780307,0.00005607148,0.0000041437393,0.0000122576575,0.000010156899,0.000009133777],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992751,0.000012519851,0.00041347858,0.000057150417,0.00017765407,0.000064103224],"domain_scores_gemma":[0.99884874,0.0005462795,0.00019326329,0.000051031686,0.0003249602,0.000035735648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027040503,0.00006672686,0.0001664852,0.00043699596,0.000027687274,0.00005052773,0.00007499612,0.000030402525,0.0000030538251],"category_scores_gemma":[0.00014422584,0.00006356288,0.00006211508,0.00031568858,0.000016707014,0.0001158399,0.000012897226,0.000039716433,8.161076e-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":[0.000004443339,0.000010960155,0.0008491141,0.000037726048,0.00026782247,0.0000014707517,0.000090875066,0.9936811,0.0023231348,0.0005816148,0.00007082703,0.002080917],"study_design_scores_gemma":[0.000196019,0.000020254534,0.022474451,0.000036614565,0.00019052177,0.0000062977506,0.00002137373,0.97479004,0.0001626801,0.002011559,0.000036042904,0.000054130414],"about_ca_topic_score_codex":0.0000011830715,"about_ca_topic_score_gemma":7.781992e-7,"teacher_disagreement_score":0.8572395,"about_ca_system_score_codex":0.000014175271,"about_ca_system_score_gemma":0.000012567862,"threshold_uncertainty_score":0.2592019},"labels":[],"label_agreement":null},{"id":"W4319988293","doi":"10.2316/j.2023.206-0769","title":"INVERSE KINEMATIC SOLUTION OF A 7-DOF ROBOT WITH A TELESCOPIC FOREARM BASED ON JOINT LIMIT AND INERTIA MATRIX FLUCTUATION, 50-59.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inertia; Inverse kinematics; Kinematics; Limit (mathematics); Inverse; Joint (building); Matrix (chemical analysis); Mathematics; Mathematical analysis; Computer science; Control theory (sociology); Physics; Classical mechanics; Artificial intelligence; Engineering; Geometry; Structural engineering; Materials science; Control (management)","score_opus":0.011726542260543186,"score_gpt":0.22585360365583937,"score_spread":0.2141270613952962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319988293","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":[0.17804421,0.0000382167,0.8206265,0.000748584,0.0003098635,0.00011825715,0.000005962764,0.000052340012,0.00005606193],"genre_scores_gemma":[0.8676039,0.000085891326,0.13216071,0.000032957174,0.000059141563,0.000002243624,0.000019931309,0.000016657661,0.000018549705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990123,0.00001708889,0.00042625758,0.000075831136,0.00037428585,0.00009422132],"domain_scores_gemma":[0.9993419,0.00006473562,0.00023165296,0.00006905799,0.00023812929,0.000054523298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002331872,0.00010889926,0.00018650282,0.0003989673,0.000028227645,0.000049552957,0.0000756711,0.000050917348,0.000008725801],"category_scores_gemma":[0.00006716352,0.00008882677,0.000037551657,0.00014275465,0.00002588884,0.00016258264,0.00001737478,0.00009576773,0.0000023629414],"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":[0.000020740483,0.000024233681,0.0003069395,0.000100051235,0.000060490293,0.0000087540475,0.0001286246,0.99020654,0.0041866945,0.0026906976,0.00009527128,0.0021709423],"study_design_scores_gemma":[0.0007757995,0.0001956241,0.013525604,0.00041141815,0.00004038566,0.000043546566,0.000052232564,0.982917,0.00034892999,0.0015988208,0.0000060174593,0.00008461111],"about_ca_topic_score_codex":0.000006440931,"about_ca_topic_score_gemma":0.000010385273,"teacher_disagreement_score":0.6895597,"about_ca_system_score_codex":0.00005356134,"about_ca_system_score_gemma":0.00003440905,"threshold_uncertainty_score":0.36222506},"labels":[],"label_agreement":null},{"id":"W4321325517","doi":"10.2316/j.2023.206-0741","title":"APF–BUG-BASED INTELLIGENT PATH PLANNING FOR AUTONOMOUS VEHICLE WITH HIGH PRECISION IN COMPLEX ENVIRONMENT, 277-283.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Computer science; Motion planning; Real-time computing; Artificial intelligence; Embedded system; Programming language; Robot","score_opus":0.023713020828247822,"score_gpt":0.25137905012504513,"score_spread":0.2276660292967973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321325517","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":[0.777576,0.000045158704,0.22147487,0.00036361034,0.00028883276,0.00014262747,0.000018575996,0.00006187958,0.00002842136],"genre_scores_gemma":[0.9864991,0.000081782346,0.013158698,0.000029217192,0.00010689651,0.0000062796516,0.000091962,0.000019908073,0.0000061904275],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999165,0.000016189688,0.0003598595,0.00008485897,0.00025698342,0.000117124095],"domain_scores_gemma":[0.99952286,0.00013857076,0.00014567308,0.00004463617,0.00010529484,0.00004297074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023497756,0.00009648778,0.00013660343,0.00030184156,0.000026950176,0.00006243044,0.000094130985,0.00004851282,0.000011530852],"category_scores_gemma":[0.000027537855,0.0000884053,0.000033630397,0.00008645204,0.000014046476,0.00018973237,0.000014444801,0.00010470679,0.000008128921],"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":[0.00005076429,0.000029061168,0.0014562418,0.00002611429,0.00004287089,0.000022752942,0.00015620318,0.96901274,0.00257214,0.00008581336,0.00016351836,0.026381787],"study_design_scores_gemma":[0.0009254956,0.000113585294,0.045469902,0.00021274267,0.00001470844,0.000023644958,0.000053779662,0.95013535,0.0017986883,0.0006119302,0.0005411179,0.000099050565],"about_ca_topic_score_codex":0.0000032574494,"about_ca_topic_score_gemma":0.00000169982,"teacher_disagreement_score":0.20892306,"about_ca_system_score_codex":0.00013927072,"about_ca_system_score_gemma":0.000017243969,"threshold_uncertainty_score":0.36050636},"labels":[],"label_agreement":null},{"id":"W4321325529","doi":"10.2316/j.2023.206-0595","title":"METHOD BASED ON WORK–TIME NUMBERS FOR ATTRACTIVE SEGMENTS, 148-154.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Work (physics); Physics; Thermodynamics","score_opus":0.026246799411897778,"score_gpt":0.35304699953079016,"score_spread":0.3268002001188924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321325529","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00094379275,0.0000045637394,0.99336153,0.0048845205,0.0005016398,0.00006171358,0.000013560942,0.000042066076,0.00018660123],"genre_scores_gemma":[0.23820113,0.00006185085,0.75811785,0.0019643533,0.0004115858,0.0000055758405,0.00015392248,0.000025001655,0.0010587337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990466,0.000043023145,0.00028698923,0.00011185995,0.0004227849,0.000088709065],"domain_scores_gemma":[0.9988563,0.00029546482,0.00032243688,0.00008073053,0.00039045862,0.000054621178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005442163,0.00007415616,0.00010985227,0.00030149726,0.000059555747,0.00023237868,0.00033400505,0.000033845732,0.000010602116],"category_scores_gemma":[0.0001312238,0.00006599191,0.00006728302,0.00024135098,0.000011178206,0.00041844053,0.0000440702,0.00006277936,0.000020741812],"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":[0.00006700132,0.00021264631,0.00078101014,0.000019134239,0.00021874152,0.000033018572,0.00045526144,0.80382127,0.00048140445,0.056798406,0.017660229,0.119451895],"study_design_scores_gemma":[0.00053517375,0.000073823045,0.0022756835,0.00007398618,0.000012566451,0.000010005152,0.000018739509,0.9921478,0.00028905098,0.0021402477,0.002351288,0.000071657174],"about_ca_topic_score_codex":9.470308e-7,"about_ca_topic_score_gemma":2.1057176e-7,"teacher_disagreement_score":0.23725733,"about_ca_system_score_codex":0.000053204036,"about_ca_system_score_gemma":0.00005512862,"threshold_uncertainty_score":0.2691072},"labels":[],"label_agreement":null},{"id":"W4321325551","doi":"10.2316/j.2023.206-0846","title":"STANDARDS OF MEASUREMENT AND DEVELOPMENTAL CHALLENGES IN PATH PLANNING FOR MANIPULATOR, 208-217.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Computer science; Motion planning; Manipulator (device); Artificial intelligence; Computer network; Robot","score_opus":0.09859575490531718,"score_gpt":0.3203520093752216,"score_spread":0.22175625446990443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321325551","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":[0.084946886,0.0011356982,0.9108507,0.0020303011,0.0008114275,0.000116257244,0.000008826703,0.00002804202,0.00007183917],"genre_scores_gemma":[0.80399466,0.00027612736,0.195657,0.000013994115,0.00004639445,0.0000017501723,0.0000019161932,0.000004493593,0.0000036411125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987967,0.000021372087,0.00035159284,0.00009530581,0.0006483734,0.00008667954],"domain_scores_gemma":[0.9991535,0.000085650514,0.00024271985,0.000037849946,0.0004464807,0.00003381893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011848969,0.00006444991,0.00013073612,0.00028025528,0.000024688601,0.00005216187,0.000188932,0.000030312098,3.512464e-7],"category_scores_gemma":[0.00017660629,0.00005919388,0.000021943195,0.00007752683,0.000013729692,0.00025299165,0.00006369124,0.000055476037,2.4589804e-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":[0.000110433975,0.0002133983,0.026439449,0.00031647683,0.00043689212,0.00027252873,0.017255241,0.49526933,0.0040815044,0.038656354,0.0012170455,0.41573134],"study_design_scores_gemma":[0.0010853689,0.00015299488,0.14179234,0.00067897787,0.0000074696704,0.00015059886,0.00045319286,0.8504996,0.00041509606,0.0044331546,0.00022340252,0.00010783201],"about_ca_topic_score_codex":0.0000018339554,"about_ca_topic_score_gemma":6.9909663e-7,"teacher_disagreement_score":0.7190478,"about_ca_system_score_codex":0.000106035804,"about_ca_system_score_gemma":0.000103048915,"threshold_uncertainty_score":0.24138564},"labels":[],"label_agreement":null},{"id":"W4360584419","doi":"10.2316/j.2023.206-0841","title":"ROBUST TRAJECTORY TRACKING WITH OPTIMAL VISUAL SERVOING ON A DEFORMABLE OBJECT, 180-193.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visual servoing; Computer vision; Artificial intelligence; Trajectory; Object (grammar); Computer science; Tracking (education); Video tracking; Image (mathematics); Psychology; Physics","score_opus":0.02277398329257791,"score_gpt":0.28686944367231765,"score_spread":0.26409546037973974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584419","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":[0.118331246,0.000026583184,0.87976086,0.0011380984,0.00047759616,0.000037087873,6.800378e-7,0.000068774,0.00015905964],"genre_scores_gemma":[0.85862684,0.000048435486,0.14093488,0.00019844426,0.0001284892,6.9171017e-7,0.0000025896838,0.000008465777,0.000051135186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895614,0.000022778222,0.00027492916,0.00012017205,0.0004944678,0.00013147929],"domain_scores_gemma":[0.9992382,0.00007802915,0.00026713326,0.000064074244,0.00029363163,0.00005893472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029472884,0.00009018038,0.00011210372,0.00034265773,0.00009101547,0.00028328475,0.00027723957,0.000022877659,0.000003413765],"category_scores_gemma":[0.00004395593,0.000070520306,0.00004151752,0.00021624222,0.00001817556,0.0011678614,0.00006015436,0.0001470065,0.000007906956],"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":[0.00002489101,0.000035433026,0.00030671817,0.000006426104,0.00003478019,0.0000788662,0.00047412227,0.9126092,0.0008255709,0.0023023905,0.00008668128,0.08321489],"study_design_scores_gemma":[0.00055559014,0.00018897458,0.0075031985,0.00022002943,0.0000053032577,0.00026295966,0.00012774953,0.98959285,0.0009864004,0.0002960387,0.00016909394,0.00009180113],"about_ca_topic_score_codex":0.0000017271773,"about_ca_topic_score_gemma":0.0000011898121,"teacher_disagreement_score":0.74029565,"about_ca_system_score_codex":0.00006141051,"about_ca_system_score_gemma":0.00006179231,"threshold_uncertainty_score":0.2875735},"labels":[],"label_agreement":null},{"id":"W4360584516","doi":"10.2316/j.2023.206-0889","title":"LOW-COMPLEXITY CHANNEL ESTIMATION AND MULTI-USER DETECTION IN MIMO-ENABLED UAV-ASSISTED MASSIVE IoT ACCESS, 231-240.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Internet of Things; Computer science; Channel (broadcasting); MIMO; Computer network; Real-time computing; Embedded system","score_opus":0.055361461127967415,"score_gpt":0.3451197145959313,"score_spread":0.2897582534679639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584516","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":[0.28992093,0.00003161421,0.7070966,0.002030858,0.000781571,0.00007414871,0.000001865321,0.000049007234,0.000013415176],"genre_scores_gemma":[0.92183274,0.000099751676,0.07787457,0.000073122916,0.00007917088,0.000002824331,0.000005677793,0.000006847995,0.000025283913],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987859,0.00011768759,0.000439228,0.00016952139,0.00035447054,0.00013315526],"domain_scores_gemma":[0.9989172,0.000161192,0.0004191805,0.00009066606,0.00035672108,0.000055037104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083386456,0.000106945234,0.0001734942,0.000514904,0.00007685118,0.0003953163,0.0003254188,0.00006522867,0.0000018688327],"category_scores_gemma":[0.0002569681,0.00009853699,0.000041910727,0.00037304923,0.000034517187,0.0009212287,0.0001357283,0.00015237588,0.0000033167098],"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":[0.000075074684,0.00023731738,0.009839231,0.00010616869,0.00011905072,0.00016746786,0.0014268714,0.35469028,0.0060809655,0.005823475,0.00011014167,0.62132394],"study_design_scores_gemma":[0.0006466982,0.00003217572,0.3230202,0.000097035154,0.0000044151884,0.000059877046,0.0000215692,0.6687955,0.0011977374,0.00603548,0.00001555257,0.00007377355],"about_ca_topic_score_codex":0.0000319698,"about_ca_topic_score_gemma":0.000066707944,"teacher_disagreement_score":0.6319118,"about_ca_system_score_codex":0.000077403725,"about_ca_system_score_gemma":0.00004371258,"threshold_uncertainty_score":0.40182218},"labels":[],"label_agreement":null},{"id":"W4360584586","doi":"10.2316/j.2023.206-0715","title":"ROBUST ADAPTIVE FAULT-TOLERANT CONTROL BASED ON GBF-CMAC NEURAL NETWORK FOR LOW-ALTITUDE UAV, 267-276.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cerebellar model articulation controller; Control theory (sociology); Artificial neural network; Computer science; Fault tolerance; Fault (geology); Controller (irrigation); Control engineering; Control (management); Engineering; Artificial intelligence; Distributed computing; Biology","score_opus":0.016556738001643926,"score_gpt":0.25236737376585056,"score_spread":0.23581063576420663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584586","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":[0.0146397315,0.00007765792,0.98241276,0.0014874653,0.00096798915,0.00018923331,0.000058960293,0.000099184545,0.000067011686],"genre_scores_gemma":[0.96864474,0.000054674903,0.030349633,0.00017693304,0.0006748916,0.000016744323,0.00003740867,0.00002204205,0.00002291884],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991812,0.000010570115,0.00033164595,0.0000869365,0.0002480122,0.0001415961],"domain_scores_gemma":[0.99928945,0.00018308769,0.00015181542,0.000058705322,0.00025767303,0.000059243786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014036654,0.00010953595,0.00015119843,0.00012855855,0.00006935708,0.00006245135,0.00013117323,0.000044148816,0.000005214318],"category_scores_gemma":[0.000030262905,0.00009925499,0.000080181744,0.000109034896,0.000017707409,0.0001497859,0.0000091574875,0.00012142313,0.0000049552996],"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":[0.000034659133,0.000021658367,0.00005046701,0.000009021461,0.000057660654,0.0000062439804,0.000027616246,0.985031,0.00014421644,0.0018998623,0.0007864702,0.011931105],"study_design_scores_gemma":[0.0010410236,0.00008134397,0.0037764804,0.00009599746,0.000021061656,0.000010195975,0.000024774017,0.9929137,0.000067524474,0.0012706807,0.0005983409,0.00009884242],"about_ca_topic_score_codex":0.0000012432552,"about_ca_topic_score_gemma":0.000002055604,"teacher_disagreement_score":0.954005,"about_ca_system_score_codex":0.000060342853,"about_ca_system_score_gemma":0.000018238468,"threshold_uncertainty_score":0.4047501},"labels":[],"label_agreement":null},{"id":"W4360584676","doi":"10.2316/j.2023.206-0712","title":"DISTURBANCE OBSERVER-BASED EXTENDED STATE CONVERGENCE ARCHITECTURE FOR MULTILATERAL TELEOPERATION SYSTEMS, 1-10.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Teleoperation; Control theory (sociology); Convergence (economics); Disturbance (geology); Computer science; Observer (physics); State (computer science); State observer; Control (management); Artificial intelligence; Geology; Nonlinear system; Economics; Physics; Algorithm","score_opus":0.016605672299307195,"score_gpt":0.25391081905529483,"score_spread":0.23730514675598763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584676","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":[0.51284534,0.00026608142,0.48052037,0.00071854965,0.005054499,0.00030216933,0.000066596054,0.00018966522,0.00003673325],"genre_scores_gemma":[0.9960322,0.000053764554,0.0032730447,0.00003103163,0.00027189413,0.00001062814,0.000060038983,0.000015321748,0.00025210372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991212,0.000015987138,0.00042414598,0.000077031335,0.0002617237,0.00009995131],"domain_scores_gemma":[0.9991648,0.00007342433,0.00013592956,0.000054118038,0.0005230148,0.000048668564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021541807,0.000097631135,0.00014086744,0.00016337668,0.000044068674,0.00016342288,0.00011369026,0.000040638854,0.000010641039],"category_scores_gemma":[0.00007372105,0.000085156,0.000049683495,0.00007979387,0.000014052864,0.00019223621,0.000007714037,0.000065806744,0.000008662448],"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":[0.00002297365,0.000011292529,0.00032466298,0.000065301116,0.000057332818,0.000006016998,0.0002083354,0.9897275,0.0030932685,0.0005538846,0.0015367515,0.004392679],"study_design_scores_gemma":[0.00067793624,0.000053134052,0.011125557,0.00011187584,0.000010085677,0.000022364411,0.000039732215,0.98412955,0.0007341924,0.000111929934,0.0028862325,0.000097398864],"about_ca_topic_score_codex":0.000004322278,"about_ca_topic_score_gemma":0.000005721851,"teacher_disagreement_score":0.48318684,"about_ca_system_score_codex":0.000056192166,"about_ca_system_score_gemma":0.00002890164,"threshold_uncertainty_score":0.3472561},"labels":[],"label_agreement":null},{"id":"W4360584697","doi":"10.2316/j.2023.206-0698","title":"OUTPUT PREDICTIVE CONTROL FOR ENDOVASCULAR MRI-GUIDED NANOROBOTS WITH CONTROL DELAY, 259-266.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Model predictive control; Control (management); Nanorobotics; Computer science; Medicine; Artificial intelligence","score_opus":0.0074749565526324524,"score_gpt":0.2975155565932155,"score_spread":0.290040600040583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584697","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":[0.037523963,0.00018150588,0.96002036,0.0017695804,0.00011176106,0.0002879025,0.000057371937,0.000023897033,0.000023645956],"genre_scores_gemma":[0.9752518,0.0004268387,0.023495832,0.00029108525,0.00026202868,0.00003787171,0.000096608455,0.00001862293,0.0001193236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924785,0.000019096155,0.00027987393,0.00013861101,0.00018341218,0.00013116686],"domain_scores_gemma":[0.99895334,0.00003261888,0.00028006508,0.00008698236,0.0005979311,0.00004904506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020483218,0.000103594546,0.0001404376,0.00009193327,0.00006476838,0.000040757644,0.00015211926,0.00006688924,0.0000014028298],"category_scores_gemma":[0.00004595121,0.00008567853,0.00008520198,0.000059523416,0.000041000778,0.000017684848,0.00001907611,0.00006470038,9.241161e-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":[0.00072383886,0.00013687408,0.0015245018,0.000025676427,0.001139757,0.000017627486,0.00007746324,0.5015295,0.4727607,0.0043236716,0.009135113,0.008605273],"study_design_scores_gemma":[0.027173668,0.006143173,0.013029846,0.00040484263,0.000802474,0.0018429036,0.00024047907,0.57261753,0.2600543,0.013063849,0.10341894,0.0012079842],"about_ca_topic_score_codex":0.0000018168407,"about_ca_topic_score_gemma":0.0000021433834,"teacher_disagreement_score":0.9377278,"about_ca_system_score_codex":0.000028008868,"about_ca_system_score_gemma":0.000063658896,"threshold_uncertainty_score":0.3493869},"labels":[],"label_agreement":null},{"id":"W4360584738","doi":"10.2316/j.2023.206-0764","title":"A DYNAMIC SECOND-ORDER ESTIMATION STRATEGY FOR FAULTY SYSTEMS, 1-14.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Estimation; Order (exchange); Computer science; Economics; Finance","score_opus":0.08936748120290379,"score_gpt":0.4415989860009116,"score_spread":0.3522315047980078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360584738","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":[0.08478656,0.00006827331,0.91087353,0.0028165744,0.00078257965,0.00026022014,0.000057494955,0.000070681126,0.00028407542],"genre_scores_gemma":[0.97909886,0.000035292775,0.019687066,0.00004873738,0.00008463362,0.000012711358,0.000055378052,0.000008792335,0.00096850964],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981756,0.00003766309,0.00079255307,0.00013697644,0.0007651301,0.000092081806],"domain_scores_gemma":[0.9967119,0.0005176917,0.0006738841,0.00011243143,0.0019310184,0.000053054464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012956265,0.00008037499,0.00015931543,0.0004773416,0.00009076726,0.00042994056,0.00031252345,0.00006291247,0.000049537262],"category_scores_gemma":[0.0007211301,0.00006370736,0.00007121929,0.0003650582,0.000025995629,0.00044218882,0.00003563435,0.00007174778,0.000023629073],"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":[0.000017854243,0.000031225616,0.00022062917,0.0000090140165,0.000040918778,0.0000024524998,0.0001238361,0.87961656,0.0003965768,0.027216736,0.006227893,0.086096294],"study_design_scores_gemma":[0.00035647032,0.000054527645,0.0065688067,0.000028844046,0.000010144777,0.000035503304,0.00017925745,0.9438601,0.000041990425,0.044095945,0.004702961,0.00006545945],"about_ca_topic_score_codex":0.0000028481477,"about_ca_topic_score_gemma":0.000003390207,"teacher_disagreement_score":0.8943123,"about_ca_system_score_codex":0.000051646268,"about_ca_system_score_gemma":0.00006256536,"threshold_uncertainty_score":0.41459268},"labels":[],"label_agreement":null},{"id":"W4362714323","doi":"10.2316/j.2023.206-0845","title":"A NOVEL TIME-VARYING FORMATION OBSTACLE AVOIDANCE ALGORITHM FOR MULTIPLE AUVs, 194-207.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Obstacle avoidance; Underwater; Computer science; Collision avoidance; Obstacle; Algorithm; Real-time computing; Artificial intelligence; Geology; Oceanography; Mobile robot; Computer security; Geography","score_opus":0.021087419269363708,"score_gpt":0.24773143329391828,"score_spread":0.22664401402455459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714323","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":[0.02857324,0.00012690783,0.97012234,0.0005197012,0.00036743627,0.000107179316,0.000026992035,0.00010331839,0.000052866384],"genre_scores_gemma":[0.906607,0.00015714482,0.09280582,0.000035328954,0.00021148869,0.000008400938,0.00006346604,0.00001826192,0.000093133436],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992217,0.000011498456,0.00039690195,0.000050989827,0.00022285529,0.00009610135],"domain_scores_gemma":[0.99932814,0.00011443167,0.000173133,0.000063698666,0.00028313388,0.00003747004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025732064,0.0000758341,0.00011281265,0.00017457426,0.00006169877,0.0001199502,0.00017708028,0.000041508596,0.0000029754572],"category_scores_gemma":[0.000015268173,0.000072913004,0.000055137436,0.00009307566,0.000010224834,0.0004526984,0.000028679115,0.00007319911,0.000013095709],"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":[0.000014613889,0.000048727634,0.0001207282,0.00007276653,0.00018782089,0.0000036042302,0.0012882228,0.47207934,0.106404,0.00030018148,0.0009974142,0.41848257],"study_design_scores_gemma":[0.00071973057,0.000023893246,0.00076281355,0.00010049588,0.000009436209,0.00007369726,0.00007885143,0.98947203,0.0047289887,0.0003811627,0.0035695254,0.000079344245],"about_ca_topic_score_codex":0.000003229124,"about_ca_topic_score_gemma":0.0000016620178,"teacher_disagreement_score":0.8780337,"about_ca_system_score_codex":0.00007039465,"about_ca_system_score_gemma":0.000011984899,"threshold_uncertainty_score":0.2973306},"labels":[],"label_agreement":null},{"id":"W4362714526","doi":"10.2316/j.2023.206-0899","title":"ON SOLVING THE KINEMATICS AND CONTROLLING OF ORIGAMI BOX-SHAPED ROBOT, 405-415. SI","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Robot; Computer science; Artificial intelligence; Physics; Classical mechanics","score_opus":0.01792043234815103,"score_gpt":0.27459861700553434,"score_spread":0.2566781846573833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714526","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":[0.053659078,0.00011130756,0.94029325,0.0047400105,0.0010078218,0.0000777435,0.0000023176478,0.00003792402,0.00007057341],"genre_scores_gemma":[0.87544197,0.000107150576,0.12410302,0.00015704792,0.00014580613,9.771484e-7,0.000002232628,0.0000073066467,0.000034466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986499,0.00005545228,0.00049951696,0.000106851425,0.00057294476,0.00011531633],"domain_scores_gemma":[0.9981995,0.00068556424,0.0005917002,0.00011523522,0.00036087335,0.00004708126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007836467,0.000096297605,0.00019156294,0.00024245743,0.00007900337,0.00019489747,0.00044376534,0.00004147725,0.000001441794],"category_scores_gemma":[0.00039400056,0.000067835994,0.00005169482,0.00017423494,0.000044085387,0.0002985239,0.00010744119,0.00014769474,0.0000030963806],"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":[0.000016940969,0.000049730654,0.00056638004,0.000030412853,0.00016569113,0.00006282917,0.0014910983,0.9251237,0.0036569657,0.049853567,0.00025114906,0.018731525],"study_design_scores_gemma":[0.00051864685,0.0001001169,0.007892303,0.00024183064,0.000016720523,0.00011125922,0.00006229347,0.982414,0.00019695274,0.008362306,0.00001704018,0.000066511624],"about_ca_topic_score_codex":0.000004113582,"about_ca_topic_score_gemma":3.552968e-7,"teacher_disagreement_score":0.8217829,"about_ca_system_score_codex":0.000027212312,"about_ca_system_score_gemma":0.000046175057,"threshold_uncertainty_score":0.27662715},"labels":[],"label_agreement":null},{"id":"W4362714531","doi":"10.2316/j.2023.206-0891","title":"DETECTION OF PINE WILT DISEASE IN AUTUMN BASED ON REMOTE SENSING IMAGES AND ENF MODULE, 241-246.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wilt disease; Remote sensing; Geography; Biology; Botany","score_opus":0.006670440433124589,"score_gpt":0.2309717190948961,"score_spread":0.22430127866177152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714531","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":[0.9628279,0.000020732306,0.034204055,0.0024254352,0.0003201329,0.00006273047,0.0000032914613,0.000015980308,0.000119698816],"genre_scores_gemma":[0.9920498,0.00005924111,0.0077377474,0.000058419613,0.00004651405,1.8489045e-8,0.0000043950245,0.0000053751232,0.000038485792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915457,0.0000397468,0.00025804358,0.00009521307,0.00038341578,0.000068991234],"domain_scores_gemma":[0.9995587,0.000062643485,0.00023377776,0.00004928038,0.000052652926,0.000042954955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023905108,0.000070238275,0.00009459856,0.00015422257,0.0000279936,0.00003693184,0.000059302554,0.000032417807,0.000005128759],"category_scores_gemma":[0.000147372,0.000056669094,0.000030344374,0.00015218827,0.00004727938,0.00015833859,0.000034650853,0.00009431378,0.0000033366637],"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":[0.000055041713,0.000025375442,0.0026319656,0.000011697534,0.000011543925,0.000055838387,0.00010257615,0.78445375,0.058068905,0.00001235801,0.000088688095,0.15448229],"study_design_scores_gemma":[0.00024828385,0.000034651715,0.3407963,0.00011848032,0.000006953101,0.000018776711,0.000011170067,0.65594995,0.0021176708,0.000618882,0.00003779544,0.00004109886],"about_ca_topic_score_codex":0.00005564852,"about_ca_topic_score_gemma":0.000015117819,"teacher_disagreement_score":0.33816433,"about_ca_system_score_codex":0.00008928351,"about_ca_system_score_gemma":0.000008299192,"threshold_uncertainty_score":0.23108986},"labels":[],"label_agreement":null},{"id":"W4362714706","doi":"10.2316/j.2023.206-0878","title":"KINEMATICS AND STIFFNESS ANALYSIS OF A NOVEL 4-DOF OVER-CONSTRAINED PARALLEL MECHANISM WITH THREE LEGS, 450-460.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kinematics; Mechanism (biology); Stiffness; Computer science; Control theory (sociology); Structural engineering; Physics; Engineering; Artificial intelligence; Classical mechanics; Control (management)","score_opus":0.011935770577766675,"score_gpt":0.23754917293482034,"score_spread":0.22561340235705366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714706","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":[0.35145208,0.00003696092,0.6477719,0.0003986176,0.00018187678,0.00005951071,0.000011964401,0.000035069424,0.000052006722],"genre_scores_gemma":[0.9866465,0.00008743713,0.013160239,0.000022246406,0.000046128847,0.0000015404464,0.0000123057725,0.000010463449,0.00001315235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990615,0.000009136072,0.00041828642,0.00006820937,0.0003576732,0.000085169384],"domain_scores_gemma":[0.9993382,0.000067927496,0.00023016009,0.00006240258,0.00024761318,0.000053666026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018662367,0.00010149426,0.0002651935,0.0004957436,0.000022506849,0.00006341301,0.00010511228,0.0000445558,0.000012886115],"category_scores_gemma":[0.000025475989,0.000082661136,0.00006583371,0.00029105204,0.000032291387,0.00016602653,0.000019527213,0.000080406615,5.3537275e-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":[0.000017898476,0.000037131507,0.00053982675,0.000034699788,0.0012899305,0.000011374809,0.00022511603,0.9636941,0.0031511753,0.026978051,0.000015294954,0.00400541],"study_design_scores_gemma":[0.0013087968,0.000041489653,0.046538692,0.00010415177,0.00032701163,0.00004025867,0.000106835985,0.94978523,0.00006632902,0.0015929892,0.00000513914,0.00008306178],"about_ca_topic_score_codex":0.0000069197017,"about_ca_topic_score_gemma":0.000021936512,"teacher_disagreement_score":0.6351944,"about_ca_system_score_codex":0.000024688437,"about_ca_system_score_gemma":0.000021377626,"threshold_uncertainty_score":0.33708233},"labels":[],"label_agreement":null},{"id":"W4362714713","doi":"10.2316/j.2023.206-0910","title":"AUTOMATIC SEPARATION OF TEMPERATURE EFFECTS FROM BRIDGE CABLE FORCE DATA BASED ON THE VMD-PE-KLD ALGORITHM, 247-258.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bridge (graph theory); Separation (statistics); Algorithm; Computer science; Structural engineering; Engineering; Machine learning; Biology","score_opus":0.023621297985554204,"score_gpt":0.31612850436356366,"score_spread":0.2925072063780095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714713","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":[0.95716536,0.00013655439,0.037964027,0.0016479486,0.002418901,0.00024617196,0.00012040606,0.00025604703,0.000044559354],"genre_scores_gemma":[0.9814568,0.00008683613,0.017908072,0.000065467204,0.00033435668,0.0000033218332,0.00011773814,0.00001678387,0.000010609149],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989207,0.000044612672,0.0003877772,0.00009161126,0.00045560126,0.00009973391],"domain_scores_gemma":[0.99889475,0.00047111808,0.00021606083,0.00019950564,0.00018054631,0.000038025966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003400087,0.00010838653,0.00015851205,0.00018374734,0.000048388792,0.00007685112,0.0003712885,0.0000718878,0.00000893199],"category_scores_gemma":[0.00015251363,0.00008066998,0.00003558631,0.00015011715,0.00001898655,0.00026759584,0.000044937373,0.0001868602,0.0000030539147],"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":[0.000034901175,0.000048255028,0.00112926,0.00031776234,0.00031073004,0.00004879406,0.0005998744,0.77357876,0.012892525,0.00090328866,0.019813268,0.19032258],"study_design_scores_gemma":[0.00023854084,0.00005872444,0.056911405,0.0004183856,0.000020723555,0.000010153802,0.0000122376805,0.9350844,0.0058805514,0.0012252074,0.00007131817,0.00006835374],"about_ca_topic_score_codex":0.00003005686,"about_ca_topic_score_gemma":0.0000022253912,"teacher_disagreement_score":0.19025423,"about_ca_system_score_codex":0.00008350988,"about_ca_system_score_gemma":0.00003652045,"threshold_uncertainty_score":0.32896265},"labels":[],"label_agreement":null},{"id":"W4362714855","doi":"10.2316/j.2023.206-0826","title":"MULTI-CONSTRAINT SLAM OPTIMISATION ALGORITHM FOR INDOOR SCENES, 375-382.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Constraint (computer-aided design); Artificial intelligence; Computer vision; Engineering","score_opus":0.019098214499226364,"score_gpt":0.2623319913678224,"score_spread":0.24323377686859607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714855","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":[0.021347255,0.00007455811,0.9762712,0.0005437487,0.0014782379,0.00013009537,0.000025448797,0.00009731388,0.00003212902],"genre_scores_gemma":[0.71305454,0.00044920613,0.28572553,0.000063340165,0.00044928357,0.0000055476075,0.00015312081,0.000034399174,0.00006503458],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990911,0.000014249443,0.00042686734,0.00008047337,0.0002692729,0.00011806983],"domain_scores_gemma":[0.99919873,0.00007817295,0.00015868145,0.000050373896,0.00045701215,0.00005703961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026643273,0.000104548344,0.00013686047,0.0003071848,0.00004747947,0.00011605952,0.00011172865,0.00007349725,0.000006228632],"category_scores_gemma":[0.00007117074,0.000101806654,0.00006785057,0.00012155255,0.000023275059,0.0002191431,0.000013574228,0.00008310141,0.00000509346],"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":[0.000004725607,0.000021063619,0.0001107366,0.000018923402,0.000080844606,0.000007550479,0.00013132811,0.8766714,0.0022196332,0.00084127893,0.0004068436,0.11948572],"study_design_scores_gemma":[0.00090762606,0.000044559485,0.0024152722,0.000073904645,0.00002310393,0.00004186891,0.000078330864,0.9940993,0.0011550342,0.0005079706,0.000546896,0.00010614052],"about_ca_topic_score_codex":0.000002037312,"about_ca_topic_score_gemma":0.0000015366003,"teacher_disagreement_score":0.69170725,"about_ca_system_score_codex":0.00007753694,"about_ca_system_score_gemma":0.000031044576,"threshold_uncertainty_score":0.41515547},"labels":[],"label_agreement":null},{"id":"W4362714877","doi":"10.2316/j.2023.206-0817","title":"CHAINED-CENTER-TRACKER: AN EFFICIENT END-TO-END NEURAL NETWORK FOR AUTOMATED MULTI-OBJECT TRACKING, 306-316.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Tracking (education); Computer science; Computer vision; End-to-end principle; Object (grammar); Artificial intelligence; Artificial neural network; Center (category theory); Video tracking; Psychology","score_opus":0.028756320506081585,"score_gpt":0.3163884747570456,"score_spread":0.28763215425096406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714877","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":[0.264607,0.000052128114,0.7261318,0.0065621003,0.0019462975,0.00030721424,0.000025464351,0.00035479784,0.000013210695],"genre_scores_gemma":[0.9154438,0.00003129042,0.083445385,0.00038919903,0.0005824013,0.000011994392,0.000045016903,0.000015271087,0.00003565823],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984859,0.000048357117,0.0005355174,0.00023425661,0.00043842342,0.0002575497],"domain_scores_gemma":[0.9986207,0.00015929271,0.00039354648,0.00016132212,0.00051206636,0.00015310055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005233134,0.00014585604,0.00018297147,0.00024879674,0.00016993037,0.00042007928,0.0006453776,0.000054154647,0.0000035625994],"category_scores_gemma":[0.000055315442,0.00012913135,0.000098018216,0.00037378859,0.000025536747,0.00042961122,0.000115322786,0.00013005163,0.000008438941],"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":[0.0000142616245,0.00012809313,0.00035074586,0.0000061893015,0.00004021241,0.000015588106,0.0002503386,0.9380803,0.00063201983,0.0071993517,0.0017282476,0.051554635],"study_design_scores_gemma":[0.0006751084,0.0001562057,0.023851313,0.000062578394,0.000011059978,0.000106338244,0.00002071745,0.9734792,0.00010362054,0.0005337537,0.00086985796,0.00013023734],"about_ca_topic_score_codex":0.0000052161,"about_ca_topic_score_gemma":0.000009884022,"teacher_disagreement_score":0.65083677,"about_ca_system_score_codex":0.000050210514,"about_ca_system_score_gemma":0.00004216495,"threshold_uncertainty_score":0.52658236},"labels":[],"label_agreement":null},{"id":"W4362714963","doi":"10.2316/j.2023.206-0812","title":"FORMATION TRACKING FOR A MULTI-AUV SYSTEM BASED ON AN ADAPTIVE SLIDING-MODE METHOD IN THE WATER FLOW ENVIRONMENT, 352-366.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fluid Dynamics Simulations and Interactions","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mode (computer interface); Tracking (education); Computer science; Flow (mathematics); Environmental science; Control theory (sociology); Mechanics; Artificial intelligence; Physics; Operating system; Control (management)","score_opus":0.03364041556820842,"score_gpt":0.306164485160218,"score_spread":0.2725240695920096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362714963","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":[0.0337699,0.000005756451,0.96517485,0.0003429738,0.00045240653,0.00014943237,0.000030522562,0.000039554696,0.00003461392],"genre_scores_gemma":[0.9354141,0.000013999247,0.064324,0.000029572759,0.00009913635,0.000012453652,0.000084728636,0.000013204037,0.000008837559],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992193,0.000050249888,0.000350059,0.00006464165,0.0002198947,0.00009588189],"domain_scores_gemma":[0.99957556,0.00014880756,0.00008665874,0.00006158336,0.00010430282,0.000023066279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004893085,0.00008397497,0.00009587442,0.00035038983,0.00006603404,0.00011079272,0.00011871436,0.000041899326,0.0000031723948],"category_scores_gemma":[0.00002279446,0.00005454178,0.000057216977,0.00006092925,0.0000052940627,0.0005034748,0.0000071543163,0.00011009343,0.000004358594],"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":[0.000020436008,0.000032074156,0.000020345084,0.000015625896,0.000022070974,0.0000033267245,0.0008807969,0.99131185,0.0018173206,0.0015279329,0.000038547656,0.0043096635],"study_design_scores_gemma":[0.0005632693,0.00009419765,0.0009636016,0.00010206036,0.00001588472,0.000024337387,0.00048486984,0.996825,0.0005116819,0.00018840012,0.00015902419,0.00006770749],"about_ca_topic_score_codex":0.0000036802137,"about_ca_topic_score_gemma":0.000006672422,"teacher_disagreement_score":0.9016442,"about_ca_system_score_codex":0.00016337856,"about_ca_system_score_gemma":0.000006619409,"threshold_uncertainty_score":0.22241493},"labels":[],"label_agreement":null},{"id":"W4362715094","doi":"10.2316/j.2023.206-0747","title":"TOWARDS AUTOMATED ROBOT MANIPULATION: A UNIFIED ACTIVE VISION FRAMEWORK, 284-295.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Robot; Artificial intelligence; Robot vision; Computer vision; Human–computer interaction; Mobile robot","score_opus":0.027324967717165347,"score_gpt":0.32259689123839064,"score_spread":0.2952719235212253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362715094","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":[0.013805636,0.000042363372,0.9755083,0.007343287,0.0025251436,0.0000891792,0.000004006139,0.000448895,0.00023322209],"genre_scores_gemma":[0.6410391,0.0000673722,0.3584012,0.00013698608,0.00026269886,0.0000016832395,0.00001736194,0.000012089638,0.00006154984],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981104,0.00008535289,0.0005469043,0.00020405535,0.00086888805,0.00018440471],"domain_scores_gemma":[0.99829024,0.00020770844,0.00055883056,0.00017628934,0.0006610244,0.00010593595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055094855,0.00014875024,0.00021067288,0.00055604574,0.00009401473,0.00037149878,0.0006894217,0.00011885702,0.000006830059],"category_scores_gemma":[0.00027761233,0.00013454905,0.000080228834,0.0004973212,0.000033844557,0.0010130747,0.00019884246,0.00024154308,0.000035755016],"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":[0.000030506168,0.0000922008,0.00043866353,0.000016445183,0.00018996805,0.00030628554,0.0015879186,0.83527714,0.00081434194,0.0428516,0.0013609522,0.117034],"study_design_scores_gemma":[0.00040802042,0.00011271762,0.0913011,0.00020757059,0.000012885692,0.00023885153,0.000050857827,0.8952532,0.0002136923,0.011957438,0.00011654992,0.00012711446],"about_ca_topic_score_codex":0.000007854481,"about_ca_topic_score_gemma":3.8069027e-7,"teacher_disagreement_score":0.62723345,"about_ca_system_score_codex":0.00011794727,"about_ca_system_score_gemma":0.00011651112,"threshold_uncertainty_score":0.5486751},"labels":[],"label_agreement":null},{"id":"W4376456767","doi":"10.2316/j.2023.206-0879","title":"AN ADAPTIVE FORMULATION OF THE SMOOTH VARIABLE STRUCTURE FILTER BASED ON STATIC MULTIPLE MODELS, 1-10.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Variable (mathematics); Computer science; Filter (signal processing); Control theory (sociology); Mathematics; Artificial intelligence; Mathematical analysis; Computer vision","score_opus":0.022567919545609855,"score_gpt":0.27513856460127245,"score_spread":0.2525706450556626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376456767","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":[0.84490234,0.000012564111,0.15340137,0.00024288832,0.0010844785,0.00013620555,0.000055964563,0.00010508255,0.00005910183],"genre_scores_gemma":[0.9711052,0.000008597097,0.028738342,0.000022892795,0.00009466349,0.0000010115356,0.000013564568,0.000010882108,0.0000048304732],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992847,0.000022288841,0.00026545892,0.000047026864,0.00031200613,0.0000685381],"domain_scores_gemma":[0.9994015,0.000095635296,0.0001631249,0.00007585378,0.0002367149,0.00002718331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011519445,0.00006841343,0.00008696423,0.00015201578,0.00002960989,0.00002563363,0.00014537462,0.000044458408,0.000008697983],"category_scores_gemma":[0.00003835969,0.000049691258,0.000026343665,0.00010703774,0.000009955247,0.00024621878,0.000011690983,0.000098698656,2.8521387e-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":[0.00002527578,0.0000053904046,0.00033245506,0.00001931767,0.000014848649,6.455048e-7,0.00010754267,0.9912552,0.0011515386,0.0013560805,0.00013683875,0.005594825],"study_design_scores_gemma":[0.00023076349,0.00008703117,0.034323342,0.00013040988,0.00000768934,0.000003290313,0.000019861225,0.95124364,0.0018784849,0.012010215,0.000020987376,0.000044281558],"about_ca_topic_score_codex":0.000008459708,"about_ca_topic_score_gemma":0.0000015544373,"teacher_disagreement_score":0.12620287,"about_ca_system_score_codex":0.00008119809,"about_ca_system_score_gemma":0.000025493944,"threshold_uncertainty_score":0.20263508},"labels":[],"label_agreement":null},{"id":"W4376456804","doi":"10.2316/j.2023.206-0821","title":"OPTIMAL DESIGN OF INTELLIGENT CONTROL AND RECOGNITION OF TRAFFIC LIGHTS AT ROAD INTERSECTIONS, 317-322.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Transport Systems and Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Control (management); Transport engineering; Automotive engineering; Engineering; Artificial intelligence","score_opus":0.01600324220696225,"score_gpt":0.22463341646973017,"score_spread":0.20863017426276792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376456804","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":[0.8601814,0.0002405854,0.13881885,0.00012248073,0.0005015407,0.000068901216,0.00001402726,0.00004087777,0.000011324844],"genre_scores_gemma":[0.9966793,0.0005457117,0.0027006103,0.0000027150484,0.000043842174,0.0000015548619,0.000008622393,0.000007930555,0.000009704154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927807,0.000015040401,0.00045076275,0.00004985326,0.00014910937,0.000057145236],"domain_scores_gemma":[0.9995059,0.000050322673,0.00020043935,0.000033086122,0.00018558277,0.000024687357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018176602,0.000065121196,0.00016055387,0.00033133317,0.000015087109,0.000010232343,0.000062584164,0.00006196731,0.000007231938],"category_scores_gemma":[0.000017561659,0.000059223144,0.000041507592,0.000077442,0.0000306365,0.00010352354,0.000008434474,0.000068541085,0.0000018053134],"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":[0.00005466875,0.000030387679,0.00035089976,0.000069405774,0.0002654434,0.000013952675,0.00059049664,0.94712436,0.014996374,0.0001875305,0.00012430547,0.036192153],"study_design_scores_gemma":[0.0009873057,0.0002535495,0.011186214,0.00037708192,0.000067950314,0.00025509327,0.0002246539,0.9756908,0.010362225,0.00037557518,0.000112385394,0.000107163476],"about_ca_topic_score_codex":0.0000044497638,"about_ca_topic_score_gemma":0.000005421917,"teacher_disagreement_score":0.1364979,"about_ca_system_score_codex":0.000034297507,"about_ca_system_score_gemma":0.000008948241,"threshold_uncertainty_score":0.24150498},"labels":[],"label_agreement":null},{"id":"W4376456855","doi":"10.2316/j.2023.206-0866","title":"AN ADAPTIVE LOCALISATION METHOD BASED ON DBSCAN ALGORITHM IN MOBILE ROBOT, 323-333.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; DBSCAN; Mobile robot; Artificial intelligence; Computer vision; Algorithm; Robot; Cluster analysis","score_opus":0.012250025095155543,"score_gpt":0.2785871994894558,"score_spread":0.26633717439430027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376456855","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":[0.026504373,0.000034783938,0.9721756,0.000254153,0.00073794177,0.000108902976,0.000011815096,0.00008630382,0.00008610098],"genre_scores_gemma":[0.92139536,0.00010744575,0.07809568,0.00008739577,0.00019521802,0.000004746564,0.000078481564,0.000026720052,0.000008964675],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987929,0.00007601015,0.00044958378,0.00011391319,0.0004395078,0.00012810704],"domain_scores_gemma":[0.9993119,0.00012174567,0.00014728245,0.000084504485,0.0002619022,0.00007261202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047318244,0.00012627784,0.00016880636,0.0006407224,0.000030849107,0.00009485489,0.0001395579,0.00008259946,0.000011768622],"category_scores_gemma":[0.00003466436,0.00012347901,0.00004986372,0.0002828797,0.000016994165,0.00028769727,0.000009078375,0.00015371903,0.000006234272],"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":[0.00001859545,0.000045332923,0.00016781823,0.000007372764,0.000023420564,0.000029356375,0.00014826948,0.9199021,0.00062874804,0.0006340503,0.00008006457,0.07831491],"study_design_scores_gemma":[0.0006155662,0.00024125977,0.0048693246,0.00010391252,0.000012251491,0.000016747412,0.00013918513,0.99218065,0.0007944734,0.0008052764,0.000099047524,0.00012229869],"about_ca_topic_score_codex":0.000011302862,"about_ca_topic_score_gemma":0.000008971214,"teacher_disagreement_score":0.89489096,"about_ca_system_score_codex":0.00015574395,"about_ca_system_score_gemma":0.000035563597,"threshold_uncertainty_score":0.50353277},"labels":[],"label_agreement":null},{"id":"W4376456990","doi":"10.2316/j.2023.206-0909","title":"A STUDY OF ELECTRONIC SIGNATURE HANDWRITING UNDER FORCE FEEDBACK PERCEPTION, 471-480.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Handwriting; Signature (topology); Computer science; Perception; Mathematics; Artificial intelligence; Psychology; Neuroscience; Geometry","score_opus":0.017356386049392276,"score_gpt":0.28269214249029684,"score_spread":0.26533575644090457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376456990","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":[0.6761686,0.00007678789,0.32098436,0.0018463727,0.00063430105,0.00012443136,0.0000016182815,0.0000460045,0.00011746503],"genre_scores_gemma":[0.9976098,0.000058539437,0.0019850014,0.000059501384,0.00018294816,0.0000017219612,0.000003847293,0.000005890343,0.000092767346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986665,0.000071780676,0.00046105633,0.000113487804,0.00057001633,0.00011715973],"domain_scores_gemma":[0.9986149,0.000106507294,0.0004395591,0.00008025397,0.0007178587,0.00004089683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005506998,0.000080409634,0.00015366882,0.00032999014,0.000053228297,0.00014485042,0.00032492017,0.000050000308,0.0000048514494],"category_scores_gemma":[0.000054331525,0.00006869586,0.000054333363,0.00027788265,0.000013094903,0.0004456442,0.00007081852,0.00014842229,0.000007646306],"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":[0.00013088822,0.0016634831,0.016484838,0.00018786779,0.0019306917,0.00024667117,0.03516547,0.5589286,0.0405616,0.083713144,0.003656003,0.25733075],"study_design_scores_gemma":[0.0064612627,0.0018355446,0.2601858,0.00091503566,0.00011138203,0.0013874947,0.013490319,0.67942536,0.0010708735,0.034011126,0.00053131074,0.0005745045],"about_ca_topic_score_codex":0.000004133635,"about_ca_topic_score_gemma":0.000008343418,"teacher_disagreement_score":0.32144114,"about_ca_system_score_codex":0.000059162325,"about_ca_system_score_gemma":0.00006544554,"threshold_uncertainty_score":0.28013358},"labels":[],"label_agreement":null},{"id":"W4376457040","doi":"10.2316/j.2023.206-0874","title":"DESIGN OF REVERSE THRUST ADSORPTION WALL-CLIMBING ROBOT BASED ON TRIZ AND INPD FUSION, 441-449.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Extenics and Innovation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"TRIZ; Thrust; Robot; Climbing; Computer science; Engineering; Mechanical engineering; Artificial intelligence; Structural engineering","score_opus":0.03080068892437869,"score_gpt":0.285152176874478,"score_spread":0.2543514879500993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376457040","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":[0.12417429,0.00008265756,0.8730157,0.0014479575,0.00092887913,0.000104528706,0.000005060482,0.0000597689,0.00018115646],"genre_scores_gemma":[0.94776946,0.0005731952,0.051405545,0.00010807622,0.00009117313,0.0000012469676,0.000012533201,0.000014507959,0.000024242208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902105,0.00004612549,0.00045632818,0.00006986353,0.0003300937,0.000076557735],"domain_scores_gemma":[0.9991598,0.00017360403,0.00023613784,0.000056583624,0.00033844667,0.000035396653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008004852,0.00008632066,0.0001424355,0.00043923382,0.000028714323,0.000048691963,0.00008857656,0.00006138747,0.000020359292],"category_scores_gemma":[0.00012994446,0.00007982438,0.000035019926,0.00020927866,0.000018902789,0.00020040605,0.000016421509,0.00012662761,0.0000022694287],"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":[0.00003201481,0.000021089383,0.00022896926,0.000027968295,0.000039741346,0.000004800263,0.00011055539,0.9393753,0.037622645,0.0016280854,0.00045633415,0.02045253],"study_design_scores_gemma":[0.0006280511,0.0001130508,0.008961341,0.00019914588,0.000016305059,0.000014970807,0.000035607867,0.9857673,0.0027265965,0.001306888,0.00015234613,0.000078388424],"about_ca_topic_score_codex":0.0000016529818,"about_ca_topic_score_gemma":2.585397e-7,"teacher_disagreement_score":0.82359517,"about_ca_system_score_codex":0.000042922864,"about_ca_system_score_gemma":0.000023452698,"threshold_uncertainty_score":0.32551438},"labels":[],"label_agreement":null},{"id":"W4385414852","doi":"10.2316/j.2023.206-0893","title":"DESIGN AND ANALYSIS OF HIGH-PERFORMANCE PARALLEL DEXTEROUS HAND BASED ON CONTROLLABLE FIVE-BAR LINKAGE, 383-395.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Technology and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bar (unit); Linkage (software); Computer science; Four-bar linkage; Artificial intelligence; Physics; Chemistry","score_opus":0.012228420109592688,"score_gpt":0.22503348867648218,"score_spread":0.2128050685668895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414852","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":[0.7420247,0.000110381894,0.25692096,0.00038221097,0.00039774991,0.00008047449,0.0000067622036,0.000042693682,0.000034070606],"genre_scores_gemma":[0.9975143,0.00013276633,0.002225511,0.000021372953,0.000060001214,0.0000024533026,0.000008669718,0.0000065040017,0.000028390268],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992895,0.000029349196,0.00034168415,0.000058720514,0.00020096161,0.00007977259],"domain_scores_gemma":[0.99942726,0.0001471361,0.00018099797,0.000053529413,0.00016612837,0.00002493082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035259855,0.00007601541,0.00023587306,0.000507766,0.000038166927,0.00004638198,0.000097618766,0.00009619187,0.00000505015],"category_scores_gemma":[0.000041998697,0.000065909924,0.00003904062,0.00020231941,0.000029137942,0.00010508622,0.000008541981,0.00011029863,0.000002068122],"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":[0.000066619126,0.000011642502,0.0010961738,0.0000103105685,0.000502141,0.000008995503,0.000044082324,0.9889446,0.0010780658,0.00042678506,0.00006665374,0.0077439398],"study_design_scores_gemma":[0.0012668429,0.00013329397,0.014049109,0.000083645326,0.00015291684,0.0000065175664,0.000012438563,0.9830082,0.00093096175,0.00027367126,0.000024958676,0.00005742097],"about_ca_topic_score_codex":0.0000061833985,"about_ca_topic_score_gemma":0.0000012817244,"teacher_disagreement_score":0.25548962,"about_ca_system_score_codex":0.000029138795,"about_ca_system_score_gemma":0.000016995698,"threshold_uncertainty_score":0.26877287},"labels":[],"label_agreement":null},{"id":"W4385414858","doi":"10.2316/j.2023.206-0897","title":"LOCALISATION FOR AUTONOMOUS MOBILE ROBOTS BASED ON CONTOUR RECOGNITION TECHNOLOGY, 396-404.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reliability (semiconductor); Mobile robot; Robot; Computer science; Artificial intelligence; Computer vision; Laser; Embedded system","score_opus":0.015284345462547318,"score_gpt":0.2510295746736534,"score_spread":0.23574522921110608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414858","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":[0.08425211,0.00006640745,0.91148204,0.0016997864,0.0017138681,0.0003076153,0.000038514274,0.00028572048,0.00015395996],"genre_scores_gemma":[0.98742,0.00010585256,0.011891358,0.00010154947,0.0002402991,0.000017353032,0.00017376001,0.000028369848,0.000021406058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904233,0.000017229155,0.0004342754,0.00010215822,0.00027628182,0.00012774351],"domain_scores_gemma":[0.9990595,0.00012540584,0.00018954213,0.000071928735,0.0005048742,0.00004876881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027537506,0.000120127246,0.000156301,0.0006675565,0.000055713557,0.00009170611,0.00011735025,0.00011994398,0.000010426535],"category_scores_gemma":[0.00011519857,0.00011871101,0.00006843848,0.00021745134,0.000027148371,0.00017574697,0.000009313552,0.00010871686,0.0000126097075],"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":[0.000023311542,0.000029228682,0.000114975475,0.000025149711,0.0000423788,0.0000065813297,0.000042203803,0.94655126,0.0012264282,0.0008455945,0.0007086437,0.05038424],"study_design_scores_gemma":[0.0008916765,0.00020950456,0.00071767933,0.00013876332,0.000026384505,0.000016237374,0.000068331276,0.9914496,0.0025905196,0.0030168241,0.00074965396,0.00012481895],"about_ca_topic_score_codex":0.0000015788465,"about_ca_topic_score_gemma":0.0000020005064,"teacher_disagreement_score":0.90316796,"about_ca_system_score_codex":0.00012571173,"about_ca_system_score_gemma":0.00003495008,"threshold_uncertainty_score":0.48408943},"labels":[],"label_agreement":null},{"id":"W4385414868","doi":"10.2316/j.2023.206-0822","title":"RESEARCH ON OPTIMAL CONTROL ALGORITHM OF DOUBLE CONTRAFLOW LEFT-TURN LANES AT URBAN ROAD INTERSECTIONS, 367-374.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Turn (biochemistry); Matching (statistics); Control (management); SIGNAL (programming language); Order (exchange); Computer science; Mode (computer interface); Algorithm; Mathematics; Control theory (sociology); Artificial intelligence; Statistics; Physics; Business; Finance","score_opus":0.03430239703023318,"score_gpt":0.33279133591579124,"score_spread":0.29848893888555805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414868","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":[0.81130856,0.000184393,0.1844221,0.0017144149,0.0013458631,0.00020208303,0.0000469174,0.00015042181,0.00062523235],"genre_scores_gemma":[0.9975555,0.00014572399,0.0018444539,0.000024314488,0.0002238441,0.0000034965353,0.000026862142,0.000014008599,0.00016177249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998953,0.000027794791,0.0003906317,0.00007809586,0.0004387815,0.00011173322],"domain_scores_gemma":[0.9990356,0.00015143497,0.00011852401,0.00007551577,0.0005630227,0.0000559034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044661615,0.000077640594,0.00013591771,0.00048585862,0.00006571471,0.00005230529,0.00013991498,0.000060243558,0.000024881001],"category_scores_gemma":[0.000029845463,0.000072699746,0.000059228183,0.00013369994,0.00003464509,0.00012247372,0.000021194985,0.00017410312,0.000023286511],"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":[0.00004391889,0.000029270212,0.00023066366,0.000008757945,0.0001100844,0.0000048604074,0.00031597688,0.9866235,0.0018060831,0.0012652521,0.0019784442,0.007583157],"study_design_scores_gemma":[0.001267321,0.000065688175,0.004308354,0.000074490876,0.000014467328,0.000038292026,0.00015915935,0.9913779,0.0013008522,0.00019796369,0.0011308236,0.0000646795],"about_ca_topic_score_codex":0.000012801657,"about_ca_topic_score_gemma":0.000006178359,"teacher_disagreement_score":0.18624695,"about_ca_system_score_codex":0.00010552012,"about_ca_system_score_gemma":0.000022367323,"threshold_uncertainty_score":0.29646096},"labels":[],"label_agreement":null},{"id":"W4385414897","doi":"10.2316/j.2023.206-0810","title":"VISUAL SERVOING IN VIRTUALISED ENVIRONMENTS BASED ON OPTICAL FLOW LEARNING AND CONSTRAINED OPTIMISATION, 1-10.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visual servoing; Computer science; Optical flow; Flow (mathematics); Artificial intelligence; Computer vision; Image (mathematics); Mathematics; Geometry","score_opus":0.010238754273739633,"score_gpt":0.28973838134941376,"score_spread":0.2794996270756741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414897","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":[0.037102412,0.000011539441,0.9595015,0.0029938463,0.00020641132,0.000037767826,5.250591e-7,0.00002493187,0.00012107408],"genre_scores_gemma":[0.8835729,0.000044017404,0.11611485,0.00017248973,0.000037794445,5.9274936e-7,0.0000055309906,0.0000045405823,0.000047307418],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991571,0.000039733543,0.00027159764,0.000106994565,0.00034154722,0.000083053164],"domain_scores_gemma":[0.9995267,0.00017172552,0.0001547693,0.000033278262,0.00006281496,0.00005076025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034067576,0.0000665389,0.000090427144,0.0002996924,0.00004539269,0.00013865453,0.00011949258,0.000025242738,0.000009337681],"category_scores_gemma":[0.00017871258,0.00006226774,0.000021286694,0.000111762914,0.000027419672,0.00041671153,0.000054693508,0.00011724698,0.000005284755],"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":[0.000019169971,0.00003997389,0.0010172909,0.0000037297061,0.000010390604,0.00004198243,0.0002171814,0.83769643,0.0023829665,0.0018594343,0.000020362648,0.15669107],"study_design_scores_gemma":[0.00082231493,0.00009179101,0.008854348,0.000100581194,0.0000020732784,0.000023106262,0.00005985562,0.98895127,0.00039947472,0.00046032542,0.00017458892,0.00006029775],"about_ca_topic_score_codex":3.6109253e-7,"about_ca_topic_score_gemma":1.514965e-7,"teacher_disagreement_score":0.8464705,"about_ca_system_score_codex":0.000042147472,"about_ca_system_score_gemma":0.000026118876,"threshold_uncertainty_score":0.25392047},"labels":[],"label_agreement":null},{"id":"W4385414902","doi":"10.2316/j.2023.206-0779","title":"A NEW REAL-TIME 3D DENSE SEMANTIC MAPPING SYSTEM FOR LARGE-SCALE ENVIRONMENTS","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Scale (ratio); Semantic mapping; Semantic computing; Artificial intelligence; Semantic Web; Cartography; Geography","score_opus":0.008927920328263925,"score_gpt":0.22042187266403018,"score_spread":0.21149395233576626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414902","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":[0.11532456,0.00003793425,0.8834369,0.00018119896,0.0007399883,0.00009896886,0.000013474559,0.00008217613,0.00008479782],"genre_scores_gemma":[0.96278197,0.0002591262,0.03623458,0.000013290141,0.0003723294,0.000001956585,0.00006547489,0.000032057007,0.0002392482],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991731,0.000013129555,0.00035988234,0.000070642614,0.00026355128,0.000119669094],"domain_scores_gemma":[0.99960065,0.000066185414,0.00013801413,0.00005310746,0.00008677276,0.00005526001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020760429,0.000090893,0.00014128869,0.00023416741,0.000041216572,0.00007828319,0.00009255346,0.000052758056,0.000008577994],"category_scores_gemma":[0.000023572467,0.00008629006,0.00006922083,0.000090349145,0.0000050618382,0.00013928741,0.000016458685,0.000049615555,0.000020226404],"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":[0.000009069655,0.00001010602,0.00034219638,0.000045184246,0.00010942228,0.000012812497,0.00020998661,0.98688006,0.008286794,0.00072445936,0.0011827413,0.0021871703],"study_design_scores_gemma":[0.0005168302,0.000032356857,0.0026344962,0.00018846296,0.00002734993,0.00004670459,0.00011335942,0.9953888,0.0003861773,0.0001954612,0.0003854843,0.00008451407],"about_ca_topic_score_codex":0.0000035316382,"about_ca_topic_score_gemma":0.000001203276,"teacher_disagreement_score":0.84745735,"about_ca_system_score_codex":0.0001588222,"about_ca_system_score_gemma":0.000019178115,"threshold_uncertainty_score":0.35188067},"labels":[],"label_agreement":null},{"id":"W4385414908","doi":"10.2316/j.2023.206-0931","title":"QUADROTOR TRAJECTORY PLANNING WITH MODIFIED SELF-REGULATING PARTICLE SWARM OPTIMISATION FOR AUTONOMOUS FLIGHT, 481-488.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Particle swarm optimization; Swarm behaviour; Computer science; Control theory (sociology); Aeronautics; Engineering; Artificial intelligence; Control (management); Physics; Algorithm","score_opus":0.013716889601161564,"score_gpt":0.2497511231613671,"score_spread":0.23603423356020553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414908","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":[0.28613153,0.00007060459,0.71256566,0.00026420123,0.00047597435,0.00020577379,0.0000045122006,0.0002242707,0.00005748242],"genre_scores_gemma":[0.9460003,0.000019675515,0.053630114,0.0000138687465,0.0002482521,0.000017960956,0.000018127781,0.000026524582,0.000025195777],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909914,0.000016366801,0.00041402775,0.000085857915,0.0002558945,0.00012870935],"domain_scores_gemma":[0.99926275,0.000115117,0.00024548147,0.00005346592,0.00027310423,0.000050097664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023549517,0.00010628605,0.00015111979,0.00016793772,0.00005969909,0.000091626476,0.00009319016,0.00004922251,0.0000012965013],"category_scores_gemma":[0.00004292281,0.00009709335,0.00004086139,0.000106801475,0.000010270142,0.00042905673,0.000008989047,0.000070876406,0.0000013840171],"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":[0.000034368375,0.000011323827,0.00024976578,0.00002933433,0.00012435377,0.0000047715516,0.00061306846,0.99170434,0.0030603136,0.0008225069,0.000045725985,0.0033001194],"study_design_scores_gemma":[0.0011348322,0.00007611911,0.002080516,0.000106638414,0.00003251887,0.000040051338,0.00010849361,0.99422914,0.0016274848,0.00035847173,0.00009579818,0.00010990825],"about_ca_topic_score_codex":0.0000012157936,"about_ca_topic_score_gemma":0.0000010806784,"teacher_disagreement_score":0.6598687,"about_ca_system_score_codex":0.00013475602,"about_ca_system_score_gemma":0.000028320901,"threshold_uncertainty_score":0.39593518},"labels":[],"label_agreement":null},{"id":"W4385414941","doi":"10.2316/j.2023.206-0757","title":"DESIGN AND EXPERIMENT OF A CONTINUOUSLY VARIABLE-STIFFNESS WRIST FOR RELIABLE ROBOT ASSEMBLY UNDER MISALIGNMENT, 334-343.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wrist; Stiffness; Computer science; Simulation; Engineering; Structural engineering; Medicine; Anatomy","score_opus":0.018247028180552235,"score_gpt":0.25959058527618606,"score_spread":0.24134355709563382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385414941","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017880345,0.00013247786,0.9807413,0.00026215415,0.00075455627,0.0001360512,0.0000059227923,0.00003587716,0.00005127075],"genre_scores_gemma":[0.4821083,0.00037712918,0.5171801,0.000037495684,0.000120868135,0.000009214266,0.000018572426,0.000030395064,0.00011796235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991349,0.000013515323,0.00041727835,0.00007945325,0.00024469264,0.00011014838],"domain_scores_gemma":[0.9993062,0.00014646263,0.00019521188,0.000054941014,0.00024429552,0.000052884883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036483663,0.0000988802,0.00018976176,0.00015338279,0.000032426557,0.00007551417,0.00010375325,0.00005711611,0.000005404035],"category_scores_gemma":[0.000035424604,0.00009223267,0.000035969253,0.0000751014,0.000016433476,0.0001514623,0.000025391635,0.000055162724,7.178126e-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":[0.00002534938,0.000023726372,0.0000143631105,0.000042797168,0.00011674917,0.0000036426495,0.00014499962,0.94538265,0.02976685,0.022820378,0.00039424465,0.0012642359],"study_design_scores_gemma":[0.000818457,0.00009437433,0.00041881856,0.00014713372,0.00003380739,0.000038638227,0.00012984185,0.9861907,0.0026176902,0.009340206,0.00007444621,0.00009588506],"about_ca_topic_score_codex":0.0000037251416,"about_ca_topic_score_gemma":3.2586536e-7,"teacher_disagreement_score":0.46422794,"about_ca_system_score_codex":0.000050789284,"about_ca_system_score_gemma":0.000028947776,"threshold_uncertainty_score":0.37611392},"labels":[],"label_agreement":null},{"id":"W4388036820","doi":"10.2316/j.2023.206-0927","title":"USING YUMI ROBOT AND RGB-D CAMERA WITH YOLOV5 FOR PICK-AND-PLACE APPLICATION, 1-10.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Royal Golden Jubilee (RGJ) Ph.D. Programme; Thailand Research Fund","keywords":"Computer science; RGB color model; Artificial intelligence; Robot; Computer vision; Computer graphics (images)","score_opus":0.026741235112367305,"score_gpt":0.30304265449781104,"score_spread":0.2763014193854437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388036820","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0407494,0.000100979734,0.95553523,0.003196654,0.00025212544,0.00010483151,0.0000035148053,0.0000410117,0.000016223832],"genre_scores_gemma":[0.37865257,0.00007371374,0.62085754,0.00012080525,0.00017390047,0.000004350002,0.000008679385,0.000011035273,0.00009737172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912286,0.00002223364,0.0002820877,0.0001563214,0.0003029426,0.000113541406],"domain_scores_gemma":[0.9989345,0.00016677346,0.00033106515,0.00008303045,0.0004155255,0.00006910869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038409146,0.0000943609,0.00014016221,0.00021738112,0.0000928815,0.00021581288,0.00022568462,0.00004082406,7.1017234e-7],"category_scores_gemma":[0.000069406444,0.0000792166,0.000021253096,0.00014452578,0.000041852916,0.0004357186,0.0000768068,0.000075580545,0.0000016368031],"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":[0.00004477643,0.000046159807,0.003400214,0.000045088196,0.00018603833,0.000037561735,0.0012274558,0.9218494,0.0022269497,0.013823538,0.0005737713,0.056539036],"study_design_scores_gemma":[0.0005810506,0.00010391904,0.00954194,0.00008339414,0.00001961801,0.00043355292,0.000048312413,0.98729426,0.000105065286,0.0014502701,0.0002443032,0.000094341405],"about_ca_topic_score_codex":0.000007856698,"about_ca_topic_score_gemma":9.3546856e-7,"teacher_disagreement_score":0.33790317,"about_ca_system_score_codex":0.000038210645,"about_ca_system_score_gemma":0.000062755724,"threshold_uncertainty_score":0.32303593},"labels":[],"label_agreement":null},{"id":"W4388072373","doi":"10.2316/j.2023.206-0886","title":"PROBABILISTIC MODEL CHECKING METHOD FOR ROBOT PERFORMANCE OPTIMISATION, 461-470.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Probabilistic logic; Model checking; Robot; Statistical model; Artificial intelligence; Programming language","score_opus":0.04118871263207958,"score_gpt":0.32994843460602785,"score_spread":0.2887597219739483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388072373","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007178605,0.000019364732,0.9894882,0.0021758706,0.0003808401,0.000085547974,0.0000014609653,0.00063963124,0.000030468567],"genre_scores_gemma":[0.32641518,0.000027006614,0.6733507,0.00007923957,0.00007905978,0.0000050876447,0.0000037664415,0.0000056094655,0.000034359142],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910444,0.000020667656,0.00033932072,0.0001180587,0.00031349028,0.00010399875],"domain_scores_gemma":[0.9986335,0.00025809396,0.00031677744,0.00009517287,0.00065731676,0.00003911105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086660066,0.00007742762,0.00011333149,0.0002499694,0.00007816266,0.00018371883,0.0003909918,0.000038920418,4.973339e-7],"category_scores_gemma":[0.0004916634,0.000069298105,0.00004935237,0.00015342438,0.000014278658,0.000464743,0.00007840056,0.00007468182,0.0000012475593],"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":[0.0000054205643,0.000017223201,0.00028143855,0.000021280252,0.000021394706,0.0000017280468,0.0003075855,0.9111461,0.00020019797,0.009547905,0.0010929983,0.07735674],"study_design_scores_gemma":[0.0001992364,0.00006179327,0.0017437801,0.000104584935,0.000008449554,0.00006863492,0.0000028998509,0.9285526,0.00031368068,0.06882981,0.00004300426,0.00007149949],"about_ca_topic_score_codex":0.0000019783924,"about_ca_topic_score_gemma":2.2233868e-7,"teacher_disagreement_score":0.31923658,"about_ca_system_score_codex":0.000054711723,"about_ca_system_score_gemma":0.0000773356,"threshold_uncertainty_score":0.28258947},"labels":[],"label_agreement":null},{"id":"W4388073039","doi":"10.2316/j.2023.206-0850","title":"RELATION EXTRACTION METHOD OF CHINESE MEDICAL TEXT BASED ON RSIG-LSTM, 1-12.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Natural language processing; Relation (database); Artificial intelligence; Relationship extraction; Extraction (chemistry); Information extraction; Data mining; Chemistry; Chromatography","score_opus":0.01673016046962649,"score_gpt":0.3650042939308681,"score_spread":0.3482741334612416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388073039","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":[0.0038181513,0.00001169015,0.983876,0.011408137,0.00040361038,0.00006900492,0.0000019936012,0.00007028318,0.0003411674],"genre_scores_gemma":[0.6497503,0.000057083977,0.3498633,0.00015775283,0.00011891698,0.0000029645428,0.000011357006,0.0000053109206,0.00003302473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843836,0.00006396711,0.00044159387,0.00011617701,0.0008648539,0.0000750491],"domain_scores_gemma":[0.9983868,0.00048603496,0.00047491258,0.000103868275,0.0004810493,0.00006735119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007189096,0.000076125674,0.00011912349,0.000426354,0.00006210457,0.000060004008,0.0003633634,0.00006855504,0.000010244693],"category_scores_gemma":[0.0003295587,0.000066803696,0.00006617366,0.00028858418,0.000032751825,0.00042894616,0.000048654772,0.00014346496,0.000004036034],"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":[0.000020545154,0.00012131885,0.0008884011,0.000010069586,0.000031652246,0.000018134971,0.00017649459,0.55955976,0.0008180769,0.26694688,0.00030105415,0.17110758],"study_design_scores_gemma":[0.00030458596,0.000075875374,0.022025371,0.00008231817,0.0000042530146,0.000051798623,0.00000839704,0.9255909,0.00030493792,0.050812446,0.00067946827,0.000059653623],"about_ca_topic_score_codex":0.000004720994,"about_ca_topic_score_gemma":0.0000019716776,"teacher_disagreement_score":0.64593214,"about_ca_system_score_codex":0.00005817041,"about_ca_system_score_gemma":0.000121734214,"threshold_uncertainty_score":0.27241758},"labels":[],"label_agreement":null},{"id":"W4388080880","doi":"10.2316/j.2023.206-0837","title":"MOBILE ROBOT PATH PLANNING WITH TWO STAGES BASED ON HYBRID INTELLIGENT OPTIMISATION ALGORITHM, 416-429.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Mobile robot; Computer science; Path (computing); Artificial intelligence; Robot; Computer network","score_opus":0.020092507972515977,"score_gpt":0.29208274928490635,"score_spread":0.27199024131239036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388080880","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011994159,0.00005550292,0.98582864,0.00080474844,0.0009897033,0.0001201502,0.000007573579,0.00012626492,0.00007324782],"genre_scores_gemma":[0.4693934,0.000039933537,0.5300941,0.00016626947,0.00020286826,0.0000061446517,0.000029828725,0.000015061942,0.00005243475],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808156,0.000072408,0.00046860144,0.00022636564,0.00095640495,0.00019467517],"domain_scores_gemma":[0.99851966,0.00022153395,0.0005214402,0.00017315522,0.0004572036,0.000107034495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063928805,0.00017061876,0.00019920326,0.0005614364,0.00009584032,0.00034344796,0.00053841906,0.00003721765,0.000004086202],"category_scores_gemma":[0.000068941925,0.000140258,0.000060028746,0.0002645681,0.000034979195,0.0005358242,0.00007964006,0.0002102367,0.000013337753],"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":[0.000014703646,0.000055683122,0.0005919643,0.0000059143304,0.000047822534,0.00025721232,0.0003788103,0.89931685,0.00010223061,0.00034531104,0.00025519604,0.09862833],"study_design_scores_gemma":[0.00074093795,0.00055590726,0.0035615298,0.00033224566,0.000013759388,0.00018821839,0.00007333698,0.9925277,0.001146708,0.00056217605,0.00013935012,0.00015809319],"about_ca_topic_score_codex":0.000005369482,"about_ca_topic_score_gemma":9.316145e-8,"teacher_disagreement_score":0.45739925,"about_ca_system_score_codex":0.00012225445,"about_ca_system_score_gemma":0.00011919806,"threshold_uncertainty_score":0.5719555},"labels":[],"label_agreement":null},{"id":"W4388085911","doi":"10.2316/j.2023.206-0840","title":"FEED FORWARD NEURAL NETWORK BCI-BASED TRAJECTORY-CONTROLLED LOWER-LIMB EXOSKELETON: A BIOMECHATRONICS APPROACH, 430-440.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Exoskeleton; Trajectory; Brain–computer interface; Computer science; Physical medicine and rehabilitation; Artificial neural network; Artificial intelligence; Simulation; Medicine; Psychology; Physics; Neuroscience; Electroencephalography","score_opus":0.013511881349329612,"score_gpt":0.27432899383509446,"score_spread":0.26081711248576483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388085911","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":[0.9238728,0.000533121,0.063282765,0.0072209956,0.0041110716,0.0004998354,0.000010654715,0.000120650315,0.0003480599],"genre_scores_gemma":[0.98424333,0.00015786318,0.014026858,0.00036561122,0.00089546514,0.000007162979,0.0000496004,0.000021184684,0.00023290176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983151,0.0000651457,0.0006352308,0.00014368033,0.0006472236,0.00019360971],"domain_scores_gemma":[0.9985594,0.00029373856,0.0004506682,0.000095325515,0.00047196145,0.0001288862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005382476,0.00014891497,0.00040665144,0.000511309,0.00006322278,0.00008418852,0.0001254423,0.00010408674,0.000027091168],"category_scores_gemma":[0.00024158825,0.00011565071,0.00037079645,0.000271943,0.000050258033,0.00017323485,0.000023493692,0.00020303667,0.000009078665],"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":[0.0053842207,0.00071998854,0.012294782,0.00023431436,0.0014444814,0.00018911195,0.00034700122,0.91726613,0.004504763,0.0023125208,0.0066574533,0.04864524],"study_design_scores_gemma":[0.009676417,0.000943193,0.038030274,0.00018604357,0.00016725517,0.00018726276,0.0001466624,0.94889,0.00006552818,0.00043348732,0.0011315988,0.00014228497],"about_ca_topic_score_codex":0.0000027556696,"about_ca_topic_score_gemma":0.0000011629811,"teacher_disagreement_score":0.06037051,"about_ca_system_score_codex":0.00013498809,"about_ca_system_score_gemma":0.00016785812,"threshold_uncertainty_score":0.47160992},"labels":[],"label_agreement":null},{"id":"W4388087356","doi":"10.2316/j.2023.206-0938","title":"TWO-STAGE FRAME MATCHING IN VSLAM BASED ON FEATURE EXTRACTION WITH ADAPTIVE THRESHOLD FOR INDOOR TEXTURE-LESS AND STRUCTURE-LESS, 1-7. SI","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Urban and spatial planning","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Artificial intelligence; Texture (cosmology); Frame (networking); Stage (stratigraphy); Extraction (chemistry); Computer vision; Computer science; Feature matching; Feature extraction; Feature (linguistics); Pattern recognition (psychology); Image (mathematics); Mathematics; Geology; Chemistry; Chromatography; Statistics","score_opus":0.01562835580459855,"score_gpt":0.2636439724569264,"score_spread":0.24801561665232785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388087356","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":[0.95959276,0.000014840362,0.03863437,0.0011767948,0.00022014632,0.00013574515,0.00002290903,0.000014350276,0.00018806716],"genre_scores_gemma":[0.9915141,0.000009079962,0.008125456,0.00016985743,0.00008434962,0.0000017859583,0.000020419611,0.0000094408915,0.000065536726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992386,0.00001751644,0.00017771071,0.00011896629,0.00035017246,0.000097033306],"domain_scores_gemma":[0.9995538,0.00010587984,0.00022611363,0.00003873208,0.0000348284,0.00004063982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018602735,0.00009501442,0.000113078146,0.00014259898,0.000056344415,0.000098129414,0.000088830755,0.00005710542,0.0000125807155],"category_scores_gemma":[0.000021969021,0.0000726987,0.000022768063,0.00009434695,0.000033740995,0.00030136094,0.000023243621,0.00019943308,9.954057e-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":[0.00030040412,0.00003806916,0.042428654,0.00001071798,0.000026439124,0.000046329867,0.0005265467,0.94175965,0.0040004905,0.0013664786,0.00019045974,0.009305775],"study_design_scores_gemma":[0.0012062882,0.00017855308,0.2321149,0.00017416288,0.00001226884,0.000029986693,0.00044776074,0.7634705,0.00030272573,0.001868937,0.00008324299,0.00011069352],"about_ca_topic_score_codex":0.000046951372,"about_ca_topic_score_gemma":0.00021125241,"teacher_disagreement_score":0.18968625,"about_ca_system_score_codex":0.00009321625,"about_ca_system_score_gemma":0.00001431799,"threshold_uncertainty_score":0.29645666},"labels":[],"label_agreement":null},{"id":"W4391054243","doi":"10.2316/j.2024.206-1055","title":"BEHAVIOUR-DEFINED NAVIGATION FRAMEWORK FOR DYNAMICAL OBSTACLE AVOIDANCE IN MULTI-ROBOT SYSTEMS CONSISTING OF HOLONOMIC ROBOTS, 379-390.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Holonomic; Obstacle avoidance; Robot; Obstacle; Computer science; Collision avoidance; Mobile robot; Artificial intelligence; Control engineering; Computer vision; Control theory (sociology); Engineering; Geography; Computer security; Control (management); Collision","score_opus":0.03261786131653167,"score_gpt":0.32186430714436737,"score_spread":0.2892464458278357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054243","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":[0.06836615,0.0008164243,0.9272832,0.0008812542,0.0024577493,0.00013737919,0.000015728974,0.000038238242,0.000003848308],"genre_scores_gemma":[0.5645891,0.000015675212,0.43528205,0.000012728756,0.000073067065,0.0000032913724,0.000009651376,0.0000071441314,0.0000072921325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984856,0.000059375394,0.0007774714,0.0001951148,0.00034149684,0.00014090369],"domain_scores_gemma":[0.9983881,0.00058750605,0.0004937379,0.00011217663,0.0003660912,0.00005240121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006744493,0.000119410906,0.00024512954,0.0003110741,0.000038058148,0.0002796446,0.0003963828,0.00010211539,5.063418e-7],"category_scores_gemma":[0.00032465038,0.000115524,0.00007826998,0.00016730701,0.000041040446,0.00052179745,0.00006450228,0.00023684751,0.0000015073208],"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":[0.000013814625,0.00009296457,0.004607868,0.000109294044,0.00007240188,0.000074675634,0.0007140099,0.9163314,0.0014738647,0.06555129,0.00002521601,0.010933194],"study_design_scores_gemma":[0.00042644067,0.00007800813,0.021530949,0.0015212774,0.000018030352,0.00025292483,0.00005370984,0.97258055,0.00014287795,0.0032821351,0.000007597511,0.000105499596],"about_ca_topic_score_codex":0.000024897196,"about_ca_topic_score_gemma":0.0000011645244,"teacher_disagreement_score":0.49622297,"about_ca_system_score_codex":0.00017237065,"about_ca_system_score_gemma":0.00011654895,"threshold_uncertainty_score":0.4710932},"labels":[],"label_agreement":null},{"id":"W4391054254","doi":"10.2316/j.2024.206-0857","title":"RESEARCH ON THE YAW ANGLE CONTROL STRATEGY OF HEXAPOD ROBO WITH TACTILE SENSOR FEEDBACK, 46-55.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hexapod; Yaw; Control theory (sociology); Control (management); Computer science; Artificial intelligence; Engineering; Automotive engineering; Robot","score_opus":0.023217093829787833,"score_gpt":0.2886570571873192,"score_spread":0.2654399633575314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054254","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":[0.6373665,0.0013414386,0.33274043,0.017330732,0.002541082,0.0005743834,0.000049019123,0.00017465481,0.007881772],"genre_scores_gemma":[0.99899113,0.00007974887,0.00054115726,0.00004484028,0.00021537652,0.0000023301998,0.0000023434739,0.000014472576,0.00010861577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989199,0.00006254211,0.00030145186,0.000068702386,0.00054127607,0.00010610674],"domain_scores_gemma":[0.99908364,0.00031162368,0.00007849638,0.000072439114,0.000409917,0.000043899243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004352091,0.000084835476,0.00013185934,0.00022662699,0.000037677095,0.00017466751,0.00015097624,0.000043089134,0.00006237862],"category_scores_gemma":[0.000030129462,0.000052718944,0.00005270255,0.0001281826,0.00004792917,0.00017367656,0.000008890867,0.0002771287,0.0000128976135],"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":[0.00004351904,0.000041789935,0.000044932072,0.000028210898,0.00028323868,0.00004211191,0.00015673798,0.9608653,0.0022728276,0.023939777,0.0009332925,0.011348224],"study_design_scores_gemma":[0.0009195935,0.0002318233,0.004087006,0.00042915155,0.0000378152,0.00020676442,0.00048800473,0.9904618,0.00093309744,0.0015799404,0.0005320289,0.000092971066],"about_ca_topic_score_codex":0.0000047631866,"about_ca_topic_score_gemma":0.0000027904014,"teacher_disagreement_score":0.36162463,"about_ca_system_score_codex":0.000064526685,"about_ca_system_score_gemma":0.00005052713,"threshold_uncertainty_score":0.21498162},"labels":[],"label_agreement":null},{"id":"W4391054297","doi":"10.2316/j.2024.206-0835","title":"RESEARCH ON MOTOR LEARNING AND CONTROL OF MULTI-DOF BIONIC MANIPULATOR, 87-93.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Manipulator (device); Control (management); Motor learning; Computer science; Motor control; Control engineering; Control theory (sociology); Artificial intelligence; Engineering; Psychology; Robot; Neuroscience","score_opus":0.028764967387751673,"score_gpt":0.32209526637904434,"score_spread":0.29333029899129265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054297","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":[0.87486297,0.0059870332,0.11544999,0.0017248532,0.0012138013,0.00014615772,0.000008157843,0.00009322025,0.00051379256],"genre_scores_gemma":[0.9981042,0.001060208,0.00069132954,0.000011006786,0.000095042014,0.0000010376114,0.0000012572685,0.000008258053,0.000027668792],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935603,0.000027047816,0.00021936593,0.00005351167,0.00027290924,0.00007114815],"domain_scores_gemma":[0.99952924,0.00014656883,0.000049027134,0.000021465561,0.00022641647,0.000027286624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029134046,0.00005535402,0.00009439113,0.00043613647,0.000035566474,0.00006817943,0.000050499086,0.00003119578,0.000006863112],"category_scores_gemma":[0.00004498712,0.000047632384,0.000036011203,0.000102874554,0.000029027115,0.0001260017,0.000010598862,0.00019804727,6.2827297e-7],"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":[0.00018136301,0.00022932372,0.009725168,0.00060655945,0.002584477,0.00007349963,0.0021122661,0.36655876,0.15143517,0.06152937,0.001090939,0.4038731],"study_design_scores_gemma":[0.0007727443,0.0002872404,0.06632556,0.00045863664,0.000025882004,0.00004719458,0.0002642934,0.92673093,0.0023593514,0.000713929,0.0019146639,0.00009956229],"about_ca_topic_score_codex":0.0000027174947,"about_ca_topic_score_gemma":9.906581e-7,"teacher_disagreement_score":0.5601722,"about_ca_system_score_codex":0.000038006452,"about_ca_system_score_gemma":0.000011967381,"threshold_uncertainty_score":0.19423923},"labels":[],"label_agreement":null},{"id":"W4391054325","doi":"10.2316/j.2024.206-0947","title":"MOTION CHARACTERISTICS OF A REVERSE THRUST ADSORPTION WALL-CLIMBING ROBOT WITH MULTI-DEGREE-OF-FREEDOM PROPELLER, 137-149.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Rocket and propulsion systems research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Propeller; Thrust; Climbing; Motion (physics); Robot; Marine engineering; Aerospace engineering; Computer science; Engineering; Artificial intelligence; Structural engineering","score_opus":0.03626775959575965,"score_gpt":0.279702975552054,"score_spread":0.24343521595629433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054325","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":[0.60877645,0.00095075,0.38750005,0.00044109585,0.0017110863,0.00025025284,0.000024918256,0.00006508116,0.00028033467],"genre_scores_gemma":[0.9880249,0.0005924894,0.011077876,0.0000029403232,0.00016511632,0.0000016238648,0.000014384985,0.000018910514,0.00010177253],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870306,0.00003485882,0.0005831066,0.000080971266,0.00050938677,0.00008864139],"domain_scores_gemma":[0.9990266,0.0000537535,0.00023501797,0.00006939695,0.00056844833,0.00004676644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003759862,0.00010181527,0.000203638,0.0003405575,0.000018618963,0.00007505228,0.000138873,0.00006569616,0.000026467513],"category_scores_gemma":[0.000046625584,0.000078134,0.000062003295,0.00013026614,0.00003271211,0.00034996055,0.000025268215,0.0001791426,0.0000037450625],"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":[0.00023405156,0.00020991151,0.005309044,0.0016654052,0.0008915285,0.000097611,0.002209513,0.2966758,0.12255003,0.0005389535,0.0007085865,0.5689095],"study_design_scores_gemma":[0.0007357112,0.00019679195,0.01576243,0.0019355731,0.000053207354,0.0001989014,0.000119291,0.97490925,0.0055916957,0.00007301187,0.0002925957,0.00013155154],"about_ca_topic_score_codex":0.000014460395,"about_ca_topic_score_gemma":0.0000035247622,"teacher_disagreement_score":0.67823344,"about_ca_system_score_codex":0.00006792641,"about_ca_system_score_gemma":0.000040139224,"threshold_uncertainty_score":0.3186212},"labels":[],"label_agreement":null},{"id":"W4391054380","doi":"10.2316/j.2024.206-0952","title":"WDCNN-BASED FAULT DIAGNOSIS METHOD FOR AGV ON CLOUD PLATFORM, 150-160.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cloud computing; Fault (geology); Computer science; Real-time computing; Artificial intelligence; Embedded system; Geology; Operating system; Seismology","score_opus":0.020213200089436317,"score_gpt":0.3203714535582359,"score_spread":0.30015825346879954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054380","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":[0.021519024,0.00021000988,0.96823275,0.005782304,0.004025966,0.000111458634,0.00000788599,0.00006120613,0.00004941295],"genre_scores_gemma":[0.7848572,0.00007149521,0.21407622,0.00036906026,0.0005686912,0.000011125901,0.0000056833983,0.000008158536,0.00003236481],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890363,0.000027800059,0.00040365208,0.00014549376,0.00042119218,0.00009822233],"domain_scores_gemma":[0.9986859,0.00059818587,0.00019157799,0.000102281396,0.00036988978,0.000052153864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074774673,0.00009433774,0.00013912431,0.00023281215,0.000056374673,0.0003285673,0.0003507574,0.00006202261,0.0000055319674],"category_scores_gemma":[0.00014077935,0.00006929183,0.00012534687,0.000110940004,0.000014968514,0.00049317686,0.000032602566,0.00011511155,0.000006797791],"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":[0.000075609365,0.00021532322,0.0024506205,0.00026295244,0.00029983727,0.000047909918,0.0009558297,0.31835696,0.0002209152,0.086715825,0.007190144,0.5832081],"study_design_scores_gemma":[0.00041874728,0.0002445543,0.001677851,0.0003863992,0.000017215316,0.000060320122,0.00001411109,0.98055834,0.0014539423,0.007500572,0.007573869,0.00009411024],"about_ca_topic_score_codex":0.000004851158,"about_ca_topic_score_gemma":0.0000011625606,"teacher_disagreement_score":0.76333815,"about_ca_system_score_codex":0.00011193711,"about_ca_system_score_gemma":0.00011449111,"threshold_uncertainty_score":0.3168382},"labels":[],"label_agreement":null},{"id":"W4391054425","doi":"10.2316/j.2024.206-0919","title":"AN ADVERSARIAL AND DEEP HASHING-BASED HIERARCHICAL SUPERVISED CROSS-MODAL IMAGE AND TEXT RETRIEVAL ALGORITHM, 77-86.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Hash function; Modal; Artificial intelligence; Adversarial system; Pattern recognition (psychology); Image (mathematics); Deep learning; Algorithm","score_opus":0.009896935907330585,"score_gpt":0.296268869777066,"score_spread":0.2863719338697354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054425","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":[0.028696027,0.0003893056,0.96631104,0.0038210782,0.00058506796,0.00006656111,0.000008771366,0.00008934896,0.000032825123],"genre_scores_gemma":[0.7816065,0.0001505743,0.2177862,0.00013621274,0.00028406014,6.9457866e-7,0.000009630231,0.000008884322,0.000017268367],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872893,0.000062334795,0.00038037516,0.00021380972,0.0005035882,0.0001109326],"domain_scores_gemma":[0.9990254,0.00014678255,0.00014168107,0.000097968375,0.00046823244,0.00011996031],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00054702844,0.00011672388,0.00013909419,0.00026270744,0.00009290224,0.0015563148,0.00032501933,0.0000809213,0.000008349418],"category_scores_gemma":[0.000107126965,0.000098917786,0.000045820132,0.0001466968,0.00013274564,0.0014880416,0.000076627395,0.00022189051,0.0000014761317],"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":[0.00013307705,0.00016972315,0.0006049383,0.000070859554,0.00012074411,0.000199905,0.0009269613,0.0005395364,0.025705904,0.04490123,0.0000779499,0.9265492],"study_design_scores_gemma":[0.00056472403,0.00021197878,0.007932849,0.00007967544,0.000015080855,0.00023038188,0.000015905423,0.9794997,0.0040255636,0.0069616307,0.00034621623,0.000116286945],"about_ca_topic_score_codex":0.000004850192,"about_ca_topic_score_gemma":5.8508226e-7,"teacher_disagreement_score":0.97896016,"about_ca_system_score_codex":0.000053140604,"about_ca_system_score_gemma":0.0001297441,"threshold_uncertainty_score":0.9994802},"labels":[],"label_agreement":null},{"id":"W4392839490","doi":"10.2316/j.2024.206-0940","title":"FAULT-TOLERANT CONTROL OF A QUADROTOR DESPITE THE COMPLETE ROTOR FAILURE, 258-269.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Nonlinear system; Artificial neural network; Rotor (electric); Computer science; Lyapunov function; Position (finance); Control (management); Fault tolerance; Control engineering; Fault (geology); Attitude control; Scheme (mathematics); Engineering; Artificial intelligence; Mathematics; Distributed computing","score_opus":0.010582175506492469,"score_gpt":0.2377208202951102,"score_spread":0.22713864478861776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392839490","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":[0.07407751,0.0025242344,0.9182761,0.0024789195,0.0021183912,0.00029308425,0.000068314795,0.0000654202,0.00009804672],"genre_scores_gemma":[0.9965554,0.000043566757,0.002817592,0.000037200913,0.0005038467,0.0000041948038,0.0000031028108,0.000016416241,0.000018673854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989561,0.000036094356,0.0005047668,0.000058829577,0.0003640553,0.000080147154],"domain_scores_gemma":[0.9992084,0.00019334885,0.0001652491,0.00006106362,0.00033469548,0.000037257825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003069188,0.00009787215,0.00019050461,0.00015009171,0.000021547723,0.00011613577,0.00018975273,0.000040287843,0.00001084311],"category_scores_gemma":[0.000048508453,0.00006719257,0.000101280515,0.00006036322,0.000029453942,0.00021241127,0.000013759329,0.0001486364,0.000006474854],"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":[0.000070110545,0.000041230254,0.00043387464,0.00015635695,0.0012959599,0.00008166821,0.00074454513,0.92906755,0.03572882,0.013323256,0.0010202419,0.018036397],"study_design_scores_gemma":[0.00057624554,0.00006222802,0.002278288,0.000313719,0.00004528148,0.00015041165,0.00005279163,0.9875902,0.0001742239,0.00026353367,0.008423447,0.00006961913],"about_ca_topic_score_codex":0.000005783667,"about_ca_topic_score_gemma":0.0000070215106,"teacher_disagreement_score":0.9224779,"about_ca_system_score_codex":0.000060326896,"about_ca_system_score_gemma":0.000031022446,"threshold_uncertainty_score":0.27400336},"labels":[],"label_agreement":null},{"id":"W4392839494","doi":"10.2316/j.2024.206-1063","title":"DDETR-SLAM: A TRANSFORMER-BASED APPROACH TO POSE OPTIMISATION IN DYNAMIC ENVIRONMENTS, 407-421.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Transformer; Computer science; Artificial intelligence; Computer vision; Engineering; Electrical engineering; Voltage","score_opus":0.00634937286587795,"score_gpt":0.2236352834717118,"score_spread":0.21728591060583385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392839494","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":[0.032604627,0.00018746644,0.9653208,0.00069424295,0.0008037434,0.00009921545,0.00000809592,0.000032013122,0.000249784],"genre_scores_gemma":[0.8571152,0.00015573301,0.14252868,0.00004722486,0.00007722868,0.0000033824567,0.000029065128,0.000013211569,0.000030279272],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991519,0.000011762735,0.000359312,0.00008843427,0.00029289554,0.00009570983],"domain_scores_gemma":[0.99979615,0.000034968063,0.000042417156,0.00003943993,0.000030238158,0.000056776284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019376335,0.00010058441,0.00011640796,0.0002920731,0.000013507427,0.00011370678,0.00010954573,0.00005723095,0.000010858665],"category_scores_gemma":[0.000010844608,0.00008658251,0.00005035529,0.00010091712,0.0000074158984,0.00022369942,0.0000065393165,0.00013046806,0.0000041831013],"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":[0.0000086101845,0.00003839352,0.0000170835,0.000030351426,0.000037254973,0.000013207975,0.00019398116,0.95632935,0.006492147,0.0035487013,0.000027378781,0.03326353],"study_design_scores_gemma":[0.0002716284,0.000050072802,0.0012161806,0.00014969935,0.000016281969,0.000048539958,0.00004239234,0.9965293,0.00019260375,0.0011866027,0.00020130191,0.00009540155],"about_ca_topic_score_codex":0.0000027909339,"about_ca_topic_score_gemma":0.0000041448284,"teacher_disagreement_score":0.8245106,"about_ca_system_score_codex":0.00018827149,"about_ca_system_score_gemma":0.000021707996,"threshold_uncertainty_score":0.35307324},"labels":[],"label_agreement":null},{"id":"W4392839526","doi":"10.2316/j.2024.206-1036","title":"APPROACH TO MAGNETIC ACTUATION OF A SOFT INSPECTION ROBOT FOR HVDC TRANSMISSION LINES, 270-283. SI","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Power Line Inspection Robots","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Transmission (telecommunications); Electric power transmission; Electrical engineering; Engineering; Computer science; Artificial intelligence","score_opus":0.01054894256233451,"score_gpt":0.2517829196700534,"score_spread":0.24123397710771888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392839526","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":[0.016641313,0.00073512126,0.9794385,0.0009107137,0.0016792734,0.00017567426,0.000009717166,0.0001324254,0.00027727117],"genre_scores_gemma":[0.92785025,0.00018300375,0.071372844,0.000027159782,0.0004596799,0.000007034854,0.000020384725,0.00002608499,0.00005357584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989261,0.000011450973,0.000533362,0.00010752835,0.0003296104,0.00009195382],"domain_scores_gemma":[0.99931884,0.00007607987,0.00010525951,0.00005427341,0.00037829528,0.000067240646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022533658,0.00011634667,0.00016097483,0.0004922942,0.000028816035,0.00010119688,0.00012129198,0.00007222172,0.000008348538],"category_scores_gemma":[0.000057386467,0.00010823248,0.00009327386,0.00018018813,0.000015214843,0.00033566935,0.000011130831,0.00012098131,0.0000025475695],"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":[0.000030669376,0.000057359775,0.000023302213,0.0001348744,0.000086042324,0.0000019637844,0.00053111225,0.8983435,0.027144562,0.00164471,0.00084343733,0.071158476],"study_design_scores_gemma":[0.0003992314,0.00016129986,0.0017818186,0.00026445976,0.000050391467,0.00010639283,0.000045467154,0.98930925,0.0036550737,0.0012114717,0.0029058403,0.00010932308],"about_ca_topic_score_codex":0.000003948779,"about_ca_topic_score_gemma":0.000001431727,"teacher_disagreement_score":0.9112089,"about_ca_system_score_codex":0.00011873848,"about_ca_system_score_gemma":0.000042733667,"threshold_uncertainty_score":0.44135925},"labels":[],"label_agreement":null},{"id":"W4393274989","doi":"10.2316/j.2024.206-0964","title":"ROBOT GRASPING AND MANIPULATION COMBINING VISION AND TOUCH, 181-194.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Robot; Robot vision; Human–computer interaction; Mobile robot","score_opus":0.012059062726794322,"score_gpt":0.2648641141795628,"score_spread":0.2528050514527685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393274989","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":[0.39092878,0.0021843307,0.60327065,0.001384082,0.0016832857,0.00007327679,4.6071105e-7,0.00013579884,0.00033933093],"genre_scores_gemma":[0.9947001,0.0005168073,0.0045346045,0.0000294881,0.00017266712,4.4622539e-7,0.0000067344085,0.000015187213,0.000023995191],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993178,0.000017153072,0.00030441853,0.00008200966,0.00020856582,0.0000700547],"domain_scores_gemma":[0.9996869,0.00007191863,0.00007496372,0.000029027235,0.00008772001,0.00004949245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017090574,0.000090676025,0.000109786575,0.00026156378,0.000049462462,0.00034716656,0.000046013894,0.000048554793,0.000009762485],"category_scores_gemma":[0.000030221037,0.00008375552,0.00002584504,0.000063713596,0.000018659633,0.00053738337,0.000024629508,0.00015232578,0.0000019051009],"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":[0.00000599818,0.000006729429,0.0017154817,0.0000727145,0.000080189195,0.00002184867,0.00058509136,0.9230554,0.00498566,0.008160864,0.000118142605,0.061191883],"study_design_scores_gemma":[0.00023011562,0.00004001679,0.04603354,0.00035906775,0.00002133474,0.00022095961,0.00006911834,0.9513193,0.000112432754,0.0011760829,0.00033243233,0.00008560856],"about_ca_topic_score_codex":0.0000029416674,"about_ca_topic_score_gemma":0.0000016919623,"teacher_disagreement_score":0.60377127,"about_ca_system_score_codex":0.000039088598,"about_ca_system_score_gemma":0.000008544977,"threshold_uncertainty_score":0.34154508},"labels":[],"label_agreement":null},{"id":"W4393275085","doi":"10.2316/j.2024.206-1099","title":"ADAPTIVE CONSTRAINT CONTROL OF ROBOTIC MANIPULATORS BASED ON BARRIER LYAPUNOV FUNCTION","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Lyapunov function; Control theory (sociology); Constraint (computer-aided design); Lyapunov redesign; Computer science; Robot manipulator; Adaptive control; Function (biology); Control (management); Control engineering; Mathematics; Artificial intelligence; Engineering; Physics; Nonlinear system","score_opus":0.014302368082974545,"score_gpt":0.2503783437830337,"score_spread":0.23607597570005914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393275085","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":[0.001716111,0.000168701,0.9939683,0.0012924061,0.0025716862,0.00006988677,0.0000053903254,0.00004233851,0.00016518506],"genre_scores_gemma":[0.91587263,0.000006904996,0.08380634,0.0001491194,0.0001393965,8.8363157e-7,0.0000023035707,0.0000071193776,0.000015324282],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860656,0.000061452476,0.0004754478,0.00014849036,0.0006070542,0.00010098785],"domain_scores_gemma":[0.9988485,0.00027541828,0.00030780552,0.00010291908,0.00039608422,0.00006928176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045932207,0.00011412283,0.00018443189,0.00042547673,0.000031412677,0.0001646955,0.0002888651,0.000058091107,0.0000086818845],"category_scores_gemma":[0.00008902974,0.00009568325,0.00009592255,0.00013952925,0.00004870353,0.00040077628,0.00002562968,0.00016825013,0.0000051118955],"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":[0.000028695003,0.000044025863,0.00032019403,0.000014495924,0.00013895854,0.000077358265,0.00012057898,0.92096144,0.00042584084,0.0518462,0.00008193291,0.025940282],"study_design_scores_gemma":[0.00051772187,0.00035714888,0.0060910536,0.00039384118,0.000037650152,0.00012777721,0.00002199861,0.98911524,0.00018938452,0.0030245762,0.0000383745,0.00008523438],"about_ca_topic_score_codex":0.000002989612,"about_ca_topic_score_gemma":1.4561054e-7,"teacher_disagreement_score":0.9141565,"about_ca_system_score_codex":0.00008583294,"about_ca_system_score_gemma":0.00015273616,"threshold_uncertainty_score":0.39018497},"labels":[],"label_agreement":null},{"id":"W4393275150","doi":"10.2316/j.2024.206-0935","title":"PATENT SEARCH CLASSIFICATION MODEL FOR SERVICE ROBOTS FIELD USING DEEP LEARNING APPROACH","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Field (mathematics); Computer science; Artificial intelligence; Service (business); Robot; Deep learning; Machine learning; Business; Mathematics","score_opus":0.0992669932511405,"score_gpt":0.30617750257725,"score_spread":0.20691050932610952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393275150","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":[0.077895924,0.0002283226,0.9204196,0.00018267575,0.0010250981,0.00008743669,0.000001839187,0.000051431314,0.0001077029],"genre_scores_gemma":[0.9841283,0.00006090363,0.015356333,0.000017316223,0.00038772082,0.000002426668,0.000007830645,0.000014884964,0.000024316156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928284,0.000018152421,0.00031279275,0.00007210732,0.00023919475,0.000074927535],"domain_scores_gemma":[0.99947226,0.0000659143,0.00006761336,0.000031629992,0.00032898324,0.000033601358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003336224,0.00006977031,0.0000959734,0.00021045582,0.000046883302,0.00019674249,0.000067810615,0.00008329141,0.0000019837444],"category_scores_gemma":[0.000029045714,0.00006238154,0.000055510256,0.00009258274,0.0000038420117,0.00026287397,0.000010951096,0.00017212851,0.0000012603476],"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":[0.000012715383,0.0000068866852,0.000021943126,0.00006674819,0.00005716535,0.0000012315293,0.0003329562,0.95163035,0.007105024,0.0009142188,0.00003419855,0.039816562],"study_design_scores_gemma":[0.00021019354,0.000036310947,0.00011683467,0.0001353619,0.000022072532,0.00007431135,0.00012230303,0.9982923,0.0005478581,0.00027620647,0.00010296586,0.00006326746],"about_ca_topic_score_codex":0.0000057424736,"about_ca_topic_score_gemma":9.693688e-7,"teacher_disagreement_score":0.90623236,"about_ca_system_score_codex":0.00009933836,"about_ca_system_score_gemma":0.000025564992,"threshold_uncertainty_score":0.25438455},"labels":[],"label_agreement":null},{"id":"W4393284069","doi":"10.2316/j.2024.206-0915","title":"CIOT-BASED EARLY DIAGNOSIS OF HEART FAILURE FROM MULTIMODAL DATA USING CHI-SQUARE-BASED DEEP NEURAL CLASSIFIER, 464-472.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Classifier (UML); Pattern recognition (psychology); Artificial intelligence; Artificial neural network; Computer science; Speech recognition; Medicine","score_opus":0.14994753560571433,"score_gpt":0.4560037271018872,"score_spread":0.30605619149617286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393284069","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":[0.8658973,0.00073701754,0.11181284,0.017120779,0.0037111132,0.00029858892,0.00036040533,0.00005202163,0.000009915383],"genre_scores_gemma":[0.9621604,0.000027066677,0.036314294,0.00040244957,0.0009158483,0.000005477802,0.00014260304,0.000027059457,0.000004821994],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973955,0.0002968827,0.0011778517,0.00023602965,0.00068087643,0.00021283096],"domain_scores_gemma":[0.99704164,0.0011006731,0.00061809714,0.00024150017,0.0008699538,0.00012814596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006126809,0.00015510798,0.00029156,0.00035982602,0.00018235954,0.00008987824,0.00044112792,0.00019123165,0.0001827212],"category_scores_gemma":[0.00048623778,0.00013701904,0.00010209667,0.0001678124,0.00007807734,0.0005534912,0.00010483363,0.0006026381,0.000013741135],"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":[0.00029682255,0.00029206398,0.70228016,0.00053146144,0.00030625763,0.000094282084,0.0025754182,0.24282098,0.0035049636,0.0016722175,0.001959463,0.04366591],"study_design_scores_gemma":[0.0003062929,0.00010329725,0.030463977,0.001401352,0.000061045816,0.0000055229093,0.00043753514,0.9651168,0.0006370844,0.00055870187,0.0007953897,0.00011297524],"about_ca_topic_score_codex":0.0018701596,"about_ca_topic_score_gemma":0.00055760366,"teacher_disagreement_score":0.7222958,"about_ca_system_score_codex":0.00020303373,"about_ca_system_score_gemma":0.0004965564,"threshold_uncertainty_score":0.5587474},"labels":[],"label_agreement":null},{"id":"W4393284193","doi":"10.2316/j.2024.206-1058","title":"CONSISTENCY ANALYSIS AND SUGGESTIONS OF COLLISION MEASUREMENT IN HUMAN–ROBOT COLLABORATION SAFETY EVALUATION, 1-13.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Science and Technology Commission of Shanghai Municipality","keywords":"Consistency (knowledge bases); Collision; Computer science; Robot; Collision avoidance; Risk analysis (engineering); Human–computer interaction; Computer security; Business; Artificial intelligence","score_opus":0.07686404113111628,"score_gpt":0.47547154799606356,"score_spread":0.3986075068649473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393284193","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":[0.89688104,0.0051131486,0.07678522,0.01627469,0.0020477527,0.0013189563,0.00013003757,0.00003096931,0.0014181839],"genre_scores_gemma":[0.9969358,0.0006316899,0.002130886,0.00004972291,0.00013559057,0.000015416108,0.00006319701,0.000006976324,0.00003070971],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99676347,0.00045687388,0.0012028767,0.00014153663,0.0013034898,0.00013176735],"domain_scores_gemma":[0.9947765,0.0006066643,0.00043721826,0.00007646567,0.0040129293,0.000090225505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004511893,0.0000887806,0.00025927517,0.0010629959,0.00019348568,0.00004211813,0.00009461067,0.00010149458,0.000107103224],"category_scores_gemma":[0.0009581752,0.00007741348,0.00005851196,0.0007460033,0.00005621561,0.00032039295,0.000039417555,0.00027533152,0.0000023912862],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008258619,0.0005577785,0.52685684,0.0012859259,0.0019462929,0.000049499762,0.007830472,0.25053227,0.0068163243,0.1143016,0.0011072395,0.0878899],"study_design_scores_gemma":[0.0010062031,0.00011369423,0.78439695,0.00079760543,0.0002153345,0.000008648761,0.00051555975,0.20914082,0.000053834632,0.003448192,0.00022936755,0.00007380056],"about_ca_topic_score_codex":0.00014960187,"about_ca_topic_score_gemma":0.00059500034,"teacher_disagreement_score":0.25754008,"about_ca_system_score_codex":0.0004738403,"about_ca_system_score_gemma":0.0010151828,"threshold_uncertainty_score":0.31568304},"labels":[],"label_agreement":null},{"id":"W4395671342","doi":"10.2316/j.2024.206-1087","title":"A NOVEL ROBOT PATH PLANNING ALGORITHM BASED ON THE IMPROVED WILD HORSE OPTIMISER WITH HYBRID STRATEGIES, 515-533.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Horse; Path (computing); Computer science; Robot; Algorithm; Artificial intelligence; Biology; Operating system; Paleontology","score_opus":0.015584726676932682,"score_gpt":0.25811946381208173,"score_spread":0.24253473713514906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395671342","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013604871,0.00015848853,0.99138093,0.0056174165,0.0011366004,0.00010595718,0.000010294312,0.000080989696,0.00014881461],"genre_scores_gemma":[0.34466872,0.000012633908,0.65460366,0.0003708691,0.00027918283,0.000003915293,0.000008440028,0.000016340438,0.000036225687],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984235,0.000047494665,0.0003969336,0.0002282977,0.00072573306,0.00017805338],"domain_scores_gemma":[0.99878806,0.00030845052,0.00029806636,0.00018066796,0.00033921067,0.00008554578],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00059305225,0.00018323006,0.00016939729,0.00026967446,0.000099566314,0.0011812986,0.0006577603,0.00004488451,0.00000414353],"category_scores_gemma":[0.000052995572,0.000115607036,0.00007063282,0.00018532677,0.000048285743,0.00080076855,0.000066122644,0.00034950094,0.000003313437],"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":[0.000017389577,0.000072369505,0.000026899961,0.000011290178,0.000121487494,0.0003107442,0.00031092574,0.9656746,0.00059437164,0.005500741,0.0004163653,0.026942808],"study_design_scores_gemma":[0.0004660293,0.00029375518,0.00092775805,0.00065674534,0.000023690052,0.00071002287,0.000074669835,0.9956828,0.00018906426,0.0006416066,0.00018737513,0.00014651376],"about_ca_topic_score_codex":0.0000093847875,"about_ca_topic_score_gemma":1.8506712e-7,"teacher_disagreement_score":0.34330824,"about_ca_system_score_codex":0.00009347565,"about_ca_system_score_gemma":0.00032153138,"threshold_uncertainty_score":0.9998556},"labels":[],"label_agreement":null},{"id":"W4395672024","doi":"10.2316/j.2024.206-1122","title":"DEVELOPMENT OF INTELLIGENT SEWING EQUIPMENT BASED ON THE COLLABORATION OF MACHINE VISION AND ROBOT ARM","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Sewing machine; Robot; Computer science; Machine vision; Artificial intelligence; Robotic arm; Human–computer interaction; Engineering; Manufacturing engineering; Control engineering; Mechanical engineering","score_opus":0.018773634384871448,"score_gpt":0.2928204682050801,"score_spread":0.27404683382020867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395672024","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":[0.17613022,0.0003283909,0.82181203,0.0011469312,0.0003396142,0.000083460356,0.0000053414856,0.000019589668,0.00013443491],"genre_scores_gemma":[0.9799742,0.00008166574,0.01987096,0.00002431856,0.000028240303,0.000001555198,0.000008264911,0.0000063159887,0.0000044554163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992936,0.000010240428,0.00037479066,0.000044961216,0.00024314484,0.000033210632],"domain_scores_gemma":[0.99953896,0.0001076148,0.00009923768,0.000038732775,0.00019586708,0.000019605703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026933092,0.000055902503,0.00007587834,0.00016460888,0.000023466968,0.00004651176,0.000057330184,0.000022820985,0.000009408833],"category_scores_gemma":[0.000022651353,0.000039988736,0.000021844466,0.00007941292,0.000013422871,0.00007612778,0.000011408216,0.000058674046,5.7845426e-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":[0.000007203465,0.000028039261,0.000031488165,0.000034413588,0.000047593636,4.8529887e-7,0.000829866,0.95176774,0.008321794,0.004681982,0.00003133551,0.034218054],"study_design_scores_gemma":[0.00011949243,0.00003108901,0.0006692231,0.00027244893,0.000012866495,0.0000037566358,0.00010522751,0.9871344,0.010848844,0.0003710664,0.0003961879,0.00003541096],"about_ca_topic_score_codex":7.855397e-7,"about_ca_topic_score_gemma":0.0000013115023,"teacher_disagreement_score":0.803844,"about_ca_system_score_codex":0.000051138428,"about_ca_system_score_gemma":0.00003911779,"threshold_uncertainty_score":0.16306934},"labels":[],"label_agreement":null},{"id":"W4395673182","doi":"10.2316/j.2024.206-0890","title":"STABILITY ANALYSIS AND OPTIMISATION OF GRASSHOPPER HOPPING ROBOT WITH DAMPING SYSTEM","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Grasshopper; Stability (learning theory); Control theory (sociology); Robot; Computer science; Ecology; Artificial intelligence; Biology; Control (management); Machine learning","score_opus":0.007219140683466757,"score_gpt":0.216144369592141,"score_spread":0.20892522890867424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395673182","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":[0.17797495,0.00037790192,0.82083905,0.00031841217,0.00028810647,0.00004606969,0.0000030204428,0.000042876803,0.000109607754],"genre_scores_gemma":[0.9898955,0.00009380142,0.00992459,0.0000061052824,0.00006302629,8.890058e-7,0.000004695495,0.0000075315143,0.0000038372127],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992469,0.00002104319,0.00035479013,0.00006987126,0.00025144892,0.000055923156],"domain_scores_gemma":[0.99953264,0.00006318445,0.00010539452,0.000046261284,0.00021435074,0.00003819527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002569526,0.00007474237,0.00017132437,0.00030843483,0.000018593426,0.000116380645,0.000058493704,0.000032734075,0.000007182477],"category_scores_gemma":[0.000014243591,0.000059454007,0.000055944518,0.00016755883,0.00002279639,0.00027694172,0.000010030219,0.00007960758,3.3117672e-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":[0.0000101261,0.000010984807,0.0025705185,0.00014319851,0.00092382333,0.000008949551,0.00034364112,0.9772828,0.003100522,0.0030459582,0.000006326644,0.012553151],"study_design_scores_gemma":[0.00024969818,0.000033719145,0.012898976,0.00027842802,0.00025758287,0.00007077561,0.00023217344,0.9852084,0.00062975724,0.0000656241,0.000012103102,0.000062768886],"about_ca_topic_score_codex":0.000005333797,"about_ca_topic_score_gemma":0.00000519528,"teacher_disagreement_score":0.8119206,"about_ca_system_score_codex":0.000077321914,"about_ca_system_score_gemma":0.00001966936,"threshold_uncertainty_score":0.2424464},"labels":[],"label_agreement":null},{"id":"W4395685550","doi":"10.2316/j.2024.206-1100","title":"CHINESE VOCATIONAL SKILLS EDUCATION QUALITY ASSESSMENT USING ATTENTIVE DUAL RESIDUAL GENERATIVE ADVERSARIAL NETWORK OPTIMISED WITH GAZELLE OPTIMISATION ALGORITHM, 1-10.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Vocational education; Residual; Adversarial system; Generative grammar; Dual (grammatical number); Quality (philosophy); Artificial intelligence; Generative adversarial network; Computer science; Machine learning; Algorithm; Psychology; Deep learning; Pedagogy; Epistemology; Philosophy","score_opus":0.010560402556746219,"score_gpt":0.30714456369833043,"score_spread":0.2965841611415842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395685550","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":[0.09335362,0.00054864265,0.9016566,0.00045504447,0.0031587484,0.0001852515,0.00002939618,0.000068694346,0.0005439999],"genre_scores_gemma":[0.83205795,0.000075777985,0.16514547,0.00003488113,0.0024112829,0.0000049427285,0.000110892644,0.000024402518,0.00013442204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985912,0.000074342395,0.0005310501,0.00013767203,0.00054489425,0.00012082893],"domain_scores_gemma":[0.99891424,0.00012838401,0.0002224473,0.00006416585,0.000606092,0.00006463942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033868154,0.00016142483,0.00020238661,0.00016578792,0.000077684694,0.00022091356,0.00008535593,0.00006449094,0.000031907617],"category_scores_gemma":[0.000027812333,0.00013298236,0.0000626657,0.0001324876,0.000030528907,0.00061804696,0.000015901218,0.00016660665,0.0000021569876],"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":[0.000032231314,0.00004952517,0.0002319776,0.000020807349,0.00033207546,0.000010425193,0.0003462532,0.9785412,0.0016047815,0.0015648529,0.00029335517,0.016972505],"study_design_scores_gemma":[0.00078895345,0.00007251219,0.011626436,0.00023783368,0.00006799453,0.00016064805,0.00014426201,0.9851198,0.00007809729,0.0012992129,0.00022804203,0.00017616479],"about_ca_topic_score_codex":0.000009107442,"about_ca_topic_score_gemma":0.000003832943,"teacher_disagreement_score":0.7387043,"about_ca_system_score_codex":0.0003029255,"about_ca_system_score_gemma":0.00022485455,"threshold_uncertainty_score":0.54228634},"labels":[],"label_agreement":null},{"id":"W4400971924","doi":"10.2316/j.2024.206-1045","title":"SIMULTANEOUS LOCALISATION AND MAPPING (SLAM) TECHNIQUE IN REAL TIME: AN INTRODUCTION OF DIK-SLAM, 490-503.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Simultaneous localization and mapping; Computer science; Artificial intelligence; Robot; Mobile robot","score_opus":0.006572418939268274,"score_gpt":0.2335330161741303,"score_spread":0.22696059723486203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971924","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":[0.39799652,0.00020174403,0.6000398,0.0008139759,0.0006477648,0.00013134025,0.000006424569,0.00007443185,0.000088014946],"genre_scores_gemma":[0.987954,0.00045741283,0.011199616,0.000007009655,0.00031078086,0.00000123233,0.000037345628,0.000017260645,0.000015310166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902713,0.00003314447,0.00052323577,0.000099900004,0.00024098283,0.0000755929],"domain_scores_gemma":[0.99948066,0.00007296774,0.000119044365,0.00005372558,0.00023768973,0.000035886336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033050164,0.00009601051,0.0001470706,0.00044251664,0.00001726838,0.00009563145,0.0000680554,0.00008030449,0.000008568717],"category_scores_gemma":[0.000072138486,0.00009385173,0.000027221342,0.00015118692,0.000030352086,0.00036392212,0.000012426605,0.00012698134,8.0513905e-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":[0.000011763666,0.000026804177,0.00016175162,0.000077411736,0.000039435625,0.000023167366,0.00041081264,0.93101966,0.045035537,0.0042031873,0.000056847166,0.0189336],"study_design_scores_gemma":[0.00018648824,0.00008873594,0.0009117937,0.0001851149,0.000016418713,0.00012209354,0.0000668188,0.9930309,0.0035835765,0.0014895808,0.00022973522,0.000088747845],"about_ca_topic_score_codex":0.000013977614,"about_ca_topic_score_gemma":0.0000065125955,"teacher_disagreement_score":0.58995754,"about_ca_system_score_codex":0.00010161347,"about_ca_system_score_gemma":0.00002267561,"threshold_uncertainty_score":0.38271624},"labels":[],"label_agreement":null},{"id":"W4400971925","doi":"10.2316/j.2024.206-1111","title":"AN IMPROVED ILLUMINATION ADAPTIVE ORB-SLAM3 ALGORITHM","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Orb (optics); Computer science; Computer vision; Artificial intelligence; Algorithm; Image (mathematics)","score_opus":0.00883932470383306,"score_gpt":0.28026935213368065,"score_spread":0.27143002742984756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971925","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":[0.0020732465,0.0001867395,0.9946825,0.0015040432,0.0012401699,0.00005693233,0.0000022376187,0.00011660969,0.0001375582],"genre_scores_gemma":[0.57481074,0.00007201223,0.42480174,0.00006389471,0.00020071706,0.0000013801184,0.0000034214895,0.0000050604463,0.000041049054],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991155,0.00003271458,0.00028963637,0.00012429786,0.00036236498,0.000075462805],"domain_scores_gemma":[0.999172,0.00004205033,0.00016964354,0.0000830079,0.00049364276,0.000039704817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036882024,0.00007704399,0.00008178312,0.00029063094,0.000031917214,0.0004900858,0.0003896214,0.00003719401,0.0000059102554],"category_scores_gemma":[0.000024814115,0.00006745849,0.00003995168,0.00011559341,0.000023106679,0.00198026,0.000054330252,0.000110505855,0.0000034512068],"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":[0.0000037305413,0.000051025054,0.000007819785,0.000006194357,0.00005702488,0.000050259485,0.00055997196,0.0007131656,0.009308499,0.041106984,0.0002474877,0.94788784],"study_design_scores_gemma":[0.0001265788,0.00022480772,0.0004756511,0.00009493574,0.0000085970305,0.00014203833,0.000026939468,0.9809992,0.007630814,0.009773622,0.00042045055,0.00007639905],"about_ca_topic_score_codex":0.0000043348605,"about_ca_topic_score_gemma":8.6004167e-7,"teacher_disagreement_score":0.980286,"about_ca_system_score_codex":0.00009227756,"about_ca_system_score_gemma":0.000065275606,"threshold_uncertainty_score":0.47259083},"labels":[],"label_agreement":null},{"id":"W4400971931","doi":"10.2316/j.2024.206-1118","title":"DESIGN AND OPTIMISATION OF THE DAMPING SYSTEM FOR OPTICAL SCANNING EQUIPMENT","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Engineering","score_opus":0.025499362591098442,"score_gpt":0.2763522921215313,"score_spread":0.25085292953043287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971931","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":[0.04029734,0.0005615351,0.9581523,0.00024271688,0.0005913779,0.000079980295,7.1007895e-7,0.000029811275,0.000044215525],"genre_scores_gemma":[0.87592214,0.00006618655,0.12393716,0.000004813015,0.000058643647,0.0000021402907,5.8161004e-7,0.000004823273,0.0000035021835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996133,0.000007339369,0.00018775817,0.000031581465,0.00012272807,0.000037301375],"domain_scores_gemma":[0.9997388,0.000066158216,0.000057061974,0.000019423684,0.00010602169,0.000012521608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030088754,0.000038444017,0.000062785315,0.00007899232,0.000016599688,0.000030326806,0.00004814388,0.000024332396,3.4917443e-7],"category_scores_gemma":[0.000025380776,0.000027934087,0.000023029237,0.000024809375,0.000014646497,0.00011926012,0.000009886424,0.000045848126,3.6369308e-8],"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":[0.000018290788,0.000006892554,0.00012436298,0.00019008081,0.00015049029,0.0000020669652,0.00026089096,0.8422635,0.09790623,0.017815249,0.00008177251,0.041180126],"study_design_scores_gemma":[0.00018980983,0.000051049883,0.00049901183,0.0006111655,0.000042595402,0.000058224945,0.000053616768,0.94413066,0.052914537,0.0012848057,0.00012429069,0.000040222454],"about_ca_topic_score_codex":1.345735e-7,"about_ca_topic_score_gemma":5.5807366e-8,"teacher_disagreement_score":0.8356248,"about_ca_system_score_codex":0.000057379155,"about_ca_system_score_gemma":0.000012333858,"threshold_uncertainty_score":0.113911904},"labels":[],"label_agreement":null},{"id":"W4400971935","doi":"10.2316/j.2024.206-1081","title":"A ROBUST MONOCULAR VISUAL SLAM SYSTEM WITH POINT AND LINE FEATURES","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Monocular; Artificial intelligence; Computer vision; Computer science; Line (geometry); Point (geometry); Monocular vision; Mathematics; Geometry","score_opus":0.010255541306047212,"score_gpt":0.27201711848499266,"score_spread":0.26176157717894544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971935","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":[0.0048359223,0.00094213855,0.99035007,0.0031839486,0.00047461246,0.000030523457,6.336784e-7,0.000044232143,0.00013793941],"genre_scores_gemma":[0.8233769,0.000095641255,0.17626996,0.00007820891,0.00012499194,3.761222e-7,9.079744e-7,0.000004807421,0.00004821625],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993629,0.000015396054,0.00018779385,0.00010062493,0.00027567925,0.00005763955],"domain_scores_gemma":[0.9995717,0.000039502665,0.00010695035,0.000041563184,0.00019486833,0.00004542176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015957523,0.000066169756,0.000085541295,0.00017337098,0.000034326666,0.00044545648,0.00013418923,0.000018438592,0.0000010333016],"category_scores_gemma":[0.000016495003,0.000045979617,0.000023980807,0.0000618588,0.00001731705,0.000644678,0.000057308476,0.000099968485,9.192058e-7],"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":[0.000037177866,0.000061018363,0.0002562888,0.00012498283,0.00023920156,0.00064413913,0.0011749534,0.14857654,0.0027439569,0.18757695,0.00029361877,0.6582712],"study_design_scores_gemma":[0.00023241481,0.000105418396,0.0015532187,0.0004987972,0.000009123863,0.001611879,0.000060922415,0.9946228,0.00031213352,0.00059856934,0.00033534528,0.000059329854],"about_ca_topic_score_codex":0.000002332576,"about_ca_topic_score_gemma":7.6233613e-7,"teacher_disagreement_score":0.8460463,"about_ca_system_score_codex":0.000037191647,"about_ca_system_score_gemma":0.000031381074,"threshold_uncertainty_score":0.4295547},"labels":[],"label_agreement":null},{"id":"W4400971937","doi":"10.2316/j.2024.206-1148","title":"MARGIN-CONSTRAINED PID CONTROLLER TUNING METHOD FOR SYSTEMS WITH PARAMETER UNCERTAINTY","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Mathematical Control Systems and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"PID controller; Control theory (sociology); Margin (machine learning); Controller (irrigation); Computer science; Phase margin; Control engineering; Engineering; Control (management); Artificial intelligence; Machine learning; Temperature control; Telecommunications","score_opus":0.01362953299435855,"score_gpt":0.28522178560343214,"score_spread":0.2715922526090736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971937","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":[0.0005984013,0.00044084887,0.99524474,0.0029665641,0.0004819374,0.00012212073,0.000004470624,0.000029090806,0.00011180108],"genre_scores_gemma":[0.7905701,0.0000106006255,0.20901887,0.00007029691,0.0001958539,0.0000067529736,0.0000015970796,0.0000058615633,0.00012006896],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892277,0.00005565734,0.00044609784,0.00012720106,0.00035031475,0.000097935874],"domain_scores_gemma":[0.9985197,0.00064515165,0.00025158026,0.000065315086,0.00045988688,0.000058348818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084829103,0.00009326611,0.000249461,0.00020454495,0.00003914928,0.0007293692,0.00024653008,0.000035285975,0.0000029593273],"category_scores_gemma":[0.00010836338,0.000058957274,0.00011081345,0.00009719382,0.000016349692,0.0003642683,0.000023865628,0.000079048514,0.0000011236082],"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":[0.000051590083,0.000050131777,0.000045098535,0.00019211242,0.001308253,0.00006158451,0.000559012,0.22584681,0.0015862042,0.68927443,0.0003777403,0.08064704],"study_design_scores_gemma":[0.0005886458,0.00010045704,0.000032387885,0.00033809262,0.000060762297,0.00023257897,0.000039352817,0.98969746,0.000014690577,0.0076660328,0.0011557235,0.00007380504],"about_ca_topic_score_codex":0.000010304872,"about_ca_topic_score_gemma":0.0000018991022,"teacher_disagreement_score":0.7899717,"about_ca_system_score_codex":0.000042585834,"about_ca_system_score_gemma":0.000056196666,"threshold_uncertainty_score":0.70333236},"labels":[],"label_agreement":null},{"id":"W4400971938","doi":"10.2316/j.2024.206-0941","title":"VISUAL-INERTIAL ODOMETRY SYSTEMS WITH ONLINE TEMPORAL OFFSET OPTIMISATION","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Odometry; Offset (computer science); Computer vision; Inertial frame of reference; Computer science; Artificial intelligence; Inertial measurement unit; Visual odometry; Physics; Robot","score_opus":0.012075560605873928,"score_gpt":0.30746374272670884,"score_spread":0.2953881821208349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971938","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":[0.020936966,0.0004921972,0.9740165,0.0029017967,0.0015128964,0.000040147163,0.0000028011927,0.00005204734,0.000044649885],"genre_scores_gemma":[0.86048806,0.00008015874,0.13899003,0.00008377069,0.00028455944,4.001303e-7,0.000010479872,0.0000060714415,0.00005647481],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990232,0.00002441719,0.00032014778,0.00010953839,0.000452908,0.00006979284],"domain_scores_gemma":[0.99930775,0.00005969655,0.00019118398,0.000054910975,0.0003352964,0.000051168277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020060231,0.000076949866,0.000102427766,0.000330908,0.000033003187,0.0005015773,0.00021093585,0.00002474609,0.0000032239745],"category_scores_gemma":[0.000033123702,0.00005577345,0.000033150434,0.00016905465,0.000018764284,0.0011378435,0.00004759472,0.00011539385,0.0000028844343],"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":[0.000056661316,0.00022619513,0.0013478525,0.000081945946,0.00025447446,0.00031507475,0.00059167907,0.37764528,0.0046100463,0.04014627,0.001062444,0.57366204],"study_design_scores_gemma":[0.00027976866,0.000115665716,0.0013940954,0.00030166743,0.0000084797775,0.00048849016,0.000049224804,0.99532527,0.00012808538,0.00038159275,0.0014566255,0.00007103529],"about_ca_topic_score_codex":0.000004732018,"about_ca_topic_score_gemma":6.204383e-7,"teacher_disagreement_score":0.8395511,"about_ca_system_score_codex":0.000058487087,"about_ca_system_score_gemma":0.000068307556,"threshold_uncertainty_score":0.48367214},"labels":[],"label_agreement":null},{"id":"W4400971942","doi":"10.2316/j.2024.206-1052","title":"MULTI-OBJECT GRASPING DETECTION BASED ON THE IMPROVED SHUFFLENET NETWORK","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Object (grammar); Object detection; Artificial intelligence; Computer vision; Pattern recognition (psychology)","score_opus":0.01762200947271747,"score_gpt":0.26329679833485026,"score_spread":0.2456747888621328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971942","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":[0.003940657,0.00019853517,0.98797077,0.004619096,0.0030704585,0.00007587607,7.957464e-7,0.000047820355,0.000075993405],"genre_scores_gemma":[0.98079425,0.000028211129,0.018296203,0.00032328247,0.00052667694,0.0000027130977,0.0000011431905,0.0000056347417,0.000021873693],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991168,0.00007921468,0.00029146572,0.00010559712,0.00032506627,0.00008189447],"domain_scores_gemma":[0.9992027,0.00025461643,0.00017859387,0.00007826724,0.00025183588,0.000033959277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067539624,0.00007603329,0.00008202993,0.00016265399,0.00007046145,0.00053098606,0.00026166873,0.000039104638,0.000003389773],"category_scores_gemma":[0.00007817928,0.000049246162,0.000069083246,0.0001581173,0.000013037243,0.0003043427,0.000029362196,0.00015463747,0.0000072837074],"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":[0.00003273338,0.00010535702,0.0002843933,0.000054109645,0.00030299305,0.000079941696,0.0007190037,0.50137335,0.013457255,0.015679695,0.0007679441,0.4671432],"study_design_scores_gemma":[0.00018650935,0.000079356876,0.0026618487,0.00028044995,0.000008293912,0.000101336474,0.000011598357,0.99423814,0.00072501035,0.0009768375,0.0006737303,0.00005689046],"about_ca_topic_score_codex":0.0000035449525,"about_ca_topic_score_gemma":0.0000050147855,"teacher_disagreement_score":0.9768536,"about_ca_system_score_codex":0.00005671788,"about_ca_system_score_gemma":0.000057083453,"threshold_uncertainty_score":0.5120311},"labels":[],"label_agreement":null},{"id":"W4400971943","doi":"10.2316/j.2024.206-1074","title":"MULTIMODE HUAUV AERIAL TRAJECTORY TRACKING WITH ANTISATURATION CONTROL","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Multi-mode optical fiber; Tracking (education); Computer science; Geology; Control (management); Control theory (sociology); Geodesy; Computer vision; Artificial intelligence; Physics; Telecommunications; Psychology; Optical fiber","score_opus":0.006004399549394465,"score_gpt":0.22813806493752314,"score_spread":0.22213366538812868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971943","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":[0.6015462,0.00046669957,0.39483413,0.00040188417,0.00242801,0.00006897932,0.000008061533,0.00009645415,0.0001495548],"genre_scores_gemma":[0.9963292,0.00008701965,0.0028851537,0.000017526132,0.000650828,6.196587e-7,0.0000101228225,0.000012670181,0.0000068737304],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940795,0.000013140609,0.00023662235,0.000050560946,0.00023132062,0.000060403796],"domain_scores_gemma":[0.99968433,0.00004307748,0.00005586666,0.000023233404,0.00016635143,0.00002714172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106711275,0.000071369795,0.000087529406,0.00013411164,0.000021644833,0.00016663852,0.000051028666,0.000041373707,0.000008188688],"category_scores_gemma":[0.000013705925,0.000056777706,0.000034297565,0.000051378127,0.00001371492,0.00044507644,0.0000023318307,0.00011282872,0.0000021509952],"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":[0.00006262136,0.000015168141,0.00020608449,0.00003751062,0.00018608167,0.000054535576,0.00049358164,0.8697353,0.07831563,0.0016438564,0.00014050792,0.049109116],"study_design_scores_gemma":[0.0006664112,0.0000674944,0.0068172147,0.00022250706,0.00004440459,0.00021477244,0.000027199789,0.9849865,0.006324452,0.0001994897,0.0003375121,0.00009203178],"about_ca_topic_score_codex":0.0000042546085,"about_ca_topic_score_gemma":0.0000044020535,"teacher_disagreement_score":0.39478296,"about_ca_system_score_codex":0.000057294343,"about_ca_system_score_gemma":0.000017683904,"threshold_uncertainty_score":0.23153277},"labels":[],"label_agreement":null},{"id":"W4400971947","doi":"10.2316/j.2024.206-1162","title":"A SPATIAL POSITIONING METHOD OF LIGHT ABSORBING MATERIAL OBJECT FOR VOLUTE DEPALLETISING SYSTEM BASED ON RGB-D CAMERA","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optical Systems and Laser Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Volute; Computer vision; RGB color model; Artificial intelligence; Computer science; Object (grammar); Computer graphics (images); Engineering; Mechanical engineering","score_opus":0.005263392841855246,"score_gpt":0.2434720687790136,"score_spread":0.23820867593715833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971947","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":[0.047987916,0.00013206693,0.948879,0.00049461366,0.0021336635,0.000086467175,0.000023557088,0.00008448101,0.00017821859],"genre_scores_gemma":[0.94650954,0.0000066042353,0.053132966,0.000009591007,0.00031224216,0.0000027222359,0.000007292649,0.000015085037,0.0000039761485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992374,0.000018741188,0.0003988596,0.000068683206,0.00019818242,0.000078085664],"domain_scores_gemma":[0.9995712,0.00011007189,0.00010679859,0.00003884348,0.00014690048,0.00002617748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025951336,0.000079109566,0.00016263982,0.00024437092,0.00002531123,0.00010872523,0.00008098883,0.00007027491,0.0000064465657],"category_scores_gemma":[0.00002840351,0.00006921669,0.000071138486,0.000048654576,0.0000086592645,0.000096058844,0.000009339843,0.00008479067,9.82935e-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":[0.000090456044,0.000034964032,0.000056045003,0.0008691803,0.0003779549,0.000071466224,0.0002823242,0.85888743,0.05862577,0.03292075,0.00023111577,0.04755256],"study_design_scores_gemma":[0.00028451567,0.00011927792,0.00016658515,0.0011897855,0.000038684706,0.00013358568,0.00004581359,0.98405045,0.013437552,0.00019365425,0.00027326558,0.00006679821],"about_ca_topic_score_codex":0.000015219812,"about_ca_topic_score_gemma":0.0000023376892,"teacher_disagreement_score":0.8985216,"about_ca_system_score_codex":0.00010491546,"about_ca_system_score_gemma":0.000020754025,"threshold_uncertainty_score":0.28225744},"labels":[],"label_agreement":null},{"id":"W4400971954","doi":"10.2316/j.2024.206-1164","title":"GLOBAL PATH PLANNING OF CLIMBING ROBOT FOR WELD QUALITY INSPECTION IN LARGE SCALE STORAGE TANKS","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Scale (ratio); Storage tank; Path (computing); Robot; Quality (philosophy); Climbing; Welding; Computer science; Marine engineering; Engineering; Artificial intelligence; Mechanical engineering; Structural engineering; Geography; Computer network","score_opus":0.023030506741832414,"score_gpt":0.34008021347227924,"score_spread":0.3170497067304468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971954","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":[0.071226835,0.00038042935,0.92509836,0.0007782502,0.0023251928,0.00006927974,0.000015881473,0.00004402872,0.00006172936],"genre_scores_gemma":[0.7902973,0.000017413726,0.20950358,0.000029240719,0.00013417285,0.0000012441968,0.0000050616345,0.00000417723,0.000007801043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986603,0.00005286734,0.000599992,0.00014943133,0.00041297392,0.00012443062],"domain_scores_gemma":[0.99910975,0.00016072903,0.00034761967,0.00007770011,0.00026256935,0.000041637828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010578602,0.000087261455,0.00018042972,0.00024800576,0.000038983024,0.00017116865,0.00029479712,0.00006181657,7.9060425e-7],"category_scores_gemma":[0.00012462889,0.00008231495,0.00007311123,0.00020738685,0.000017930317,0.0006378259,0.00006708938,0.00012421876,5.6065204e-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":[0.00003229546,0.00014550351,0.022758089,0.00011101065,0.000093426235,0.00008437062,0.0022085574,0.92254657,0.0006661913,0.031118747,0.00026052623,0.019974736],"study_design_scores_gemma":[0.00046420572,0.00009824953,0.09238156,0.0005193784,0.000008469244,0.00010960413,0.000106518324,0.9021424,0.00007737526,0.003964973,0.000049900398,0.000077331766],"about_ca_topic_score_codex":0.000012799104,"about_ca_topic_score_gemma":0.0000030114334,"teacher_disagreement_score":0.7190705,"about_ca_system_score_codex":0.00017419498,"about_ca_system_score_gemma":0.00008929506,"threshold_uncertainty_score":0.33567065},"labels":[],"label_agreement":null},{"id":"W4400971964","doi":"10.2316/j.2024.206-0842","title":"RESEARCH ON PATH PLANNING OF LOGISTICS INTELLIGENT UNMANNED AERIAL VEHICLE, 450-463.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Path (computing); Computer science; Aeronautics; Systems engineering; Aerospace engineering; Artificial intelligence; Engineering; Robot; Computer network","score_opus":0.08256451143108832,"score_gpt":0.38917426256140825,"score_spread":0.3066097511303199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971964","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":[0.23554851,0.00057288504,0.760387,0.0007024862,0.0017732205,0.00008365352,0.000015225067,0.000073134506,0.0008438613],"genre_scores_gemma":[0.99605376,0.00019436068,0.003389523,0.00001514889,0.00030308103,0.0000012631236,0.000009798611,0.000011460362,0.000021636184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911606,0.000019896112,0.00035008794,0.000061066734,0.00038056143,0.00007229569],"domain_scores_gemma":[0.9992842,0.000198207,0.000058002875,0.000052921132,0.00036853753,0.000038111313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036815475,0.000058400958,0.00008692576,0.00034256448,0.000026888065,0.00008393283,0.000111941496,0.000047284208,0.000010410834],"category_scores_gemma":[0.00005787519,0.000052949013,0.00003722505,0.00011304638,0.000027444947,0.00008364917,0.000017042032,0.00018605073,0.000006716836],"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":[0.000013755553,0.000020707666,0.000040108036,0.000023849345,0.00005566381,0.000007210905,0.0002687255,0.96599746,0.0017669939,0.021703018,0.00065650675,0.009446033],"study_design_scores_gemma":[0.00014522953,0.00006088088,0.0006156963,0.00029317438,0.000010667771,0.000013910061,0.00010318989,0.9923202,0.001460296,0.003536376,0.0013925415,0.00004785963],"about_ca_topic_score_codex":0.000002441455,"about_ca_topic_score_gemma":2.7430687e-7,"teacher_disagreement_score":0.7605052,"about_ca_system_score_codex":0.00007175921,"about_ca_system_score_gemma":0.000032851167,"threshold_uncertainty_score":0.21591981},"labels":[],"label_agreement":null},{"id":"W4400971967","doi":"10.2316/j.2024.206-1048","title":"IMAGE STYLE MIGRATION BASED ON CYCLEGAN WITH SAME MAPPING LOSS","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Style (visual arts); Image (mathematics); Computer science; Artificial intelligence; Computer vision; Art; Visual arts","score_opus":0.008594740710790716,"score_gpt":0.2349604466331488,"score_spread":0.22636570592235808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971967","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":[0.009560812,0.000068308844,0.97811306,0.011379056,0.00064390997,0.00003816525,0.0000019363806,0.00002861003,0.00016616749],"genre_scores_gemma":[0.8180741,0.000027244887,0.18142508,0.0002035807,0.0002365267,6.433894e-7,0.0000027531316,0.0000050688145,0.000024980396],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991946,0.00003884416,0.00021570873,0.000115371346,0.00036350772,0.000071955204],"domain_scores_gemma":[0.99938345,0.000100856094,0.00013589175,0.000069507354,0.0002709464,0.000039323542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023696125,0.00008019223,0.000087838336,0.00022211211,0.0000439711,0.00060890726,0.00020471508,0.000024269055,0.000006971277],"category_scores_gemma":[0.000030847255,0.000058741276,0.000044357683,0.00012655836,0.000023572598,0.0007840716,0.000022753966,0.00009493641,0.000004594026],"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":[0.00005507465,0.00013639478,0.0005502185,0.000041686457,0.00023961514,0.00038097176,0.0012944974,0.8086085,0.009367802,0.023408402,0.0015705501,0.15434633],"study_design_scores_gemma":[0.00020741353,0.00011629428,0.002423754,0.00024023252,0.000008661794,0.00006535229,0.000023396477,0.9943098,0.0009030783,0.0007728706,0.00085804326,0.000071103335],"about_ca_topic_score_codex":0.0000056246968,"about_ca_topic_score_gemma":0.0000038985113,"teacher_disagreement_score":0.8085133,"about_ca_system_score_codex":0.000048705097,"about_ca_system_score_gemma":0.00006124597,"threshold_uncertainty_score":0.58717066},"labels":[],"label_agreement":null},{"id":"W4400971970","doi":"10.2316/j.2024.206-1098","title":"A NOVEL PATH PLANNING FOR AUV BASED ON DUNG BEETLE OPTIMISATION ALGORITHM WITH DEEP Q-NETWORK","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Path (computing); Computer science; Dung beetle; Artificial intelligence; Algorithm; Ecology; Computer network; Robot; Biology","score_opus":0.016568595776252967,"score_gpt":0.2732823468562783,"score_spread":0.2567137510800253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400971970","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004499623,0.00016055736,0.99594873,0.0017843427,0.0014129919,0.00010611145,0.0000059658096,0.00006602243,0.00006533966],"genre_scores_gemma":[0.10676809,0.000006577665,0.8925202,0.00017964085,0.00047212714,0.0000047255367,0.000014053898,0.000012300381,0.000022321172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988161,0.000021781116,0.0003267452,0.00017687114,0.00051636354,0.00014215741],"domain_scores_gemma":[0.9989345,0.0003321894,0.00024434878,0.00008981298,0.00033575128,0.00006341823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049785804,0.000120259305,0.00013804107,0.00023795772,0.00007440777,0.0004417036,0.0003042439,0.000052132487,0.0000013458487],"category_scores_gemma":[0.000055583074,0.00009626418,0.00005683333,0.00014962238,0.000018335319,0.00047460798,0.000029202503,0.0001430124,0.0000014325336],"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":[0.000016152499,0.000035761517,0.000059040976,0.00001397586,0.00006458496,0.000057268626,0.00025992235,0.9356388,0.00008405368,0.004192902,0.0002188258,0.059358705],"study_design_scores_gemma":[0.0005781142,0.0003354684,0.0013994685,0.0007011662,0.000021856456,0.00024286465,0.000015809053,0.99513495,0.000065507615,0.001123554,0.00026797646,0.00011326538],"about_ca_topic_score_codex":0.0000017525705,"about_ca_topic_score_gemma":1.2977618e-7,"teacher_disagreement_score":0.10631812,"about_ca_system_score_codex":0.00009466651,"about_ca_system_score_gemma":0.00012164733,"threshold_uncertainty_score":0.4259358},"labels":[],"label_agreement":null},{"id":"W4400972116","doi":"10.2316/j.2024.206-1114","title":"OVERCOMING VALUE OVERESTIMATION FOR DISTRIBUTIONAL REINFORCEMENT LEARNING-BASED PATH PLANNING WITH CONSERVATIVE CONSTRAINTS","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reinforcement learning; Reinforcement; Path (computing); Value (mathematics); Computer science; Mathematical optimization; Operations research; Artificial intelligence; Psychology; Mathematics; Machine learning; Social psychology","score_opus":0.018973155249037844,"score_gpt":0.29280428513766765,"score_spread":0.2738311298886298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400972116","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":[0.004313749,0.00009496692,0.99269956,0.0020444887,0.0006258136,0.00010707351,0.0000099880135,0.00005435135,0.000050024704],"genre_scores_gemma":[0.7165943,0.0000033509373,0.2831658,0.000079816,0.000093203154,0.0000032885812,0.00004048735,0.0000055240507,0.000014263991],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988307,0.000036871235,0.00036791232,0.00014301403,0.0005040467,0.000117451586],"domain_scores_gemma":[0.99860895,0.00047454904,0.0003218427,0.00005440537,0.00048422161,0.00005605715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047543697,0.000109890236,0.00013166436,0.00018486952,0.00008998268,0.00039429884,0.00021751896,0.000041729192,0.000002895329],"category_scores_gemma":[0.00019743996,0.000090758615,0.000051041443,0.00010168942,0.000057597637,0.00061778666,0.00003157845,0.00015793527,0.0000011295383],"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":[0.000025009445,0.00001646685,0.00076964725,0.000027437776,0.00010070879,0.0000562667,0.000264661,0.93560773,0.00012997212,0.058750685,0.00016486637,0.0040865634],"study_design_scores_gemma":[0.0006717693,0.00025993,0.003430339,0.00086151715,0.000022441282,0.00022192989,0.000031271637,0.991825,0.00024226331,0.0020709129,0.00025775225,0.00010491812],"about_ca_topic_score_codex":0.0000022753547,"about_ca_topic_score_gemma":4.6611387e-8,"teacher_disagreement_score":0.7122805,"about_ca_system_score_codex":0.00014712849,"about_ca_system_score_gemma":0.000273727,"threshold_uncertainty_score":0.38022327},"labels":[],"label_agreement":null},{"id":"W4400972566","doi":"10.2316/j.2024.206-0880","title":"LIGHTWEIGHT AND FAST MATCHING METHOD FOR LIDAR-INERTIAL ODOMETRY AND MAPPING, 338-348.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Odometry; Lidar; Matching (statistics); Artificial intelligence; Inertial frame of reference; Inertial measurement unit; Computer vision; Computer science; Remote sensing; Geology; Mathematics; Physics; Statistics; Robot; Mobile robot","score_opus":0.009859912057109227,"score_gpt":0.2823089137777131,"score_spread":0.2724490017206039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400972566","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":[0.25117368,0.0003331665,0.7419903,0.005595875,0.0004043603,0.000076294324,0.0000062447207,0.000019963774,0.00040008358],"genre_scores_gemma":[0.7841938,0.00015602652,0.21512836,0.000088088775,0.00023474247,5.3297765e-7,0.000004120191,0.000008717231,0.0001856252],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993649,0.000018992481,0.00023282407,0.000117063304,0.00019789547,0.00006829981],"domain_scores_gemma":[0.9996354,0.00013293652,0.000107246335,0.000036084773,0.00003404347,0.00005429967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032316492,0.0000705846,0.00009240061,0.000114493836,0.00007025573,0.00022656994,0.00006649737,0.000038067294,0.000015561982],"category_scores_gemma":[0.000029303397,0.000057485617,0.000033432007,0.000068172456,0.000039104223,0.00021879729,0.00005044731,0.000085855085,0.0000030649576],"study_design_candidate":"design_other","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":[0.00002572519,0.000055871205,0.0017029515,0.00007254501,0.00019322455,0.000020709087,0.002855124,0.009127886,0.073371075,0.011583597,0.0018135014,0.8991778],"study_design_scores_gemma":[0.0007512735,0.00013612349,0.042119354,0.000360898,0.000098038385,0.0012004913,0.00035073436,0.8827237,0.0027436765,0.025313916,0.04393226,0.000269528],"about_ca_topic_score_codex":0.000025424313,"about_ca_topic_score_gemma":0.0000048547163,"teacher_disagreement_score":0.89890826,"about_ca_system_score_codex":0.000040781866,"about_ca_system_score_gemma":0.000009133224,"threshold_uncertainty_score":0.23441954},"labels":[],"label_agreement":null},{"id":"W4400972574","doi":"10.2316/j.2024.206-0903","title":"KINEMATIC ANALYSIS OF TWO DEGREES-OF-FREEDOM PLANAR SEVEN-BAR MECHANISMS WITH PRISMATIC PAIRS, 349-361.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bar (unit); Kinematics; Planar; Structural engineering; Geometry; Mathematics; Materials science; Physics; Computer science; Classical mechanics; Engineering; Computer graphics (images)","score_opus":0.008860247958671399,"score_gpt":0.23503840178998758,"score_spread":0.22617815383131618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400972574","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":[0.02581951,0.00023605571,0.9729987,0.00017041057,0.0005516855,0.000069610374,0.000018998991,0.00003579496,0.000099236364],"genre_scores_gemma":[0.5961048,0.00007065415,0.40372205,0.0000048269258,0.000045300232,9.642e-7,0.000017406934,0.000015469433,0.00001851652],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861073,0.000023513045,0.00067163823,0.0000840054,0.00051744183,0.00009266808],"domain_scores_gemma":[0.9991975,0.00012890325,0.00027761658,0.00010013098,0.00024211693,0.000053722666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034568532,0.00012950995,0.00035792895,0.0006313214,0.000015248452,0.000064374784,0.00018442392,0.000049842376,0.000034014756],"category_scores_gemma":[0.000025885338,0.000100302896,0.00013136663,0.00029392465,0.000024505669,0.00019492878,0.000016283855,0.00011713734,0.0000013285177],"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":[0.000008103387,0.000025691459,0.000073373376,0.0001661404,0.001664885,0.000027815699,0.00028902016,0.91383916,0.00092483097,0.08159439,0.000035800673,0.0013507706],"study_design_scores_gemma":[0.00031208684,0.000113530594,0.0010203755,0.00051506015,0.00080028694,0.00008566236,0.00008604095,0.9907362,0.000108519635,0.006118433,0.000005152177,0.00009868884],"about_ca_topic_score_codex":0.000009855008,"about_ca_topic_score_gemma":0.00001985183,"teacher_disagreement_score":0.5702853,"about_ca_system_score_codex":0.000052645737,"about_ca_system_score_gemma":0.000038845737,"threshold_uncertainty_score":0.40902334},"labels":[],"label_agreement":null},{"id":"W4400972576","doi":"10.2316/j.2024.206-1029","title":"AN ANN-BASED INTEGRATED MODEL FOR AUTONOMOUS UAV FLIGHT CONTROL CONSIDERING EXTERNAL FORCES, 362-378.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control (management); Computer science; Control engineering; Aerospace engineering; Control theory (sociology); Artificial intelligence; Engineering","score_opus":0.00873697462402518,"score_gpt":0.24946726851784784,"score_spread":0.24073029389382267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400972576","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":[0.058729596,0.00049783755,0.9387414,0.00091354764,0.00078368094,0.00008930039,0.00003425457,0.00019109013,0.000019284922],"genre_scores_gemma":[0.9616455,0.000052680833,0.037975576,0.00008554666,0.0001645667,0.0000056371105,0.000017519313,0.000021813788,0.00003115547],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992431,0.000009311243,0.0003733304,0.000091577465,0.00017265965,0.00011005809],"domain_scores_gemma":[0.9994621,0.00007245344,0.000104145896,0.000057304384,0.000251617,0.000052324107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017045421,0.00011370803,0.0001529329,0.00026380175,0.000034418837,0.00019183998,0.00014313786,0.000089956324,0.000009822898],"category_scores_gemma":[0.000030869203,0.0001023664,0.00007058917,0.000055585246,0.000025548707,0.00038397004,0.0000063177517,0.00014813898,0.0000018330036],"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":[0.000016123558,0.000016458473,0.00012762826,0.000029748679,0.000089008536,0.0000141205255,0.0001146485,0.96721494,0.012582206,0.005690454,0.000245788,0.013858887],"study_design_scores_gemma":[0.00063401175,0.00007979427,0.00014557745,0.00015937068,0.000035972524,0.00006182768,0.000029961468,0.99205184,0.0032660088,0.002987481,0.00044374698,0.000104410814],"about_ca_topic_score_codex":0.0000020937507,"about_ca_topic_score_gemma":0.000005231402,"teacher_disagreement_score":0.9029159,"about_ca_system_score_codex":0.000105050516,"about_ca_system_score_gemma":0.00007668627,"threshold_uncertainty_score":0.41743806},"labels":[],"label_agreement":null},{"id":"W4400972583","doi":"10.2316/j.2024.206-1123","title":"MULTI-SCALE CROSS-FUSION FINE-GRAINED NETWORK FOR IDENTIFYING INVASIVE PLANTS, 431-440.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Scale (ratio); Fusion; Computer science; Geography; Cartography","score_opus":0.038252414133159246,"score_gpt":0.35127732947158036,"score_spread":0.31302491533842114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400972583","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":[0.86077505,0.002797648,0.12934415,0.0030978124,0.003120297,0.00016731194,0.00014002332,0.00009786208,0.0004598558],"genre_scores_gemma":[0.974915,0.0003716847,0.021746857,0.000040417577,0.0015855668,0.0000042584115,0.00009335653,0.000020847976,0.0012220044],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988662,0.000012469751,0.0004207647,0.00013369131,0.00041296057,0.00015390175],"domain_scores_gemma":[0.99906343,0.00027485652,0.00018541886,0.000057087374,0.00034924413,0.00006994176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003449162,0.00010182013,0.00013897949,0.00012407912,0.00009841192,0.000488283,0.00021466582,0.00008136368,0.00007439669],"category_scores_gemma":[0.00013879186,0.000083977124,0.00011887018,0.0000562026,0.000034150577,0.0002979584,0.000070788854,0.00019376313,0.0000060880516],"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":[0.00048008168,0.0004242537,0.011540891,0.0016308237,0.0013913263,0.0005221088,0.0027111354,0.09939024,0.77261263,0.0050451686,0.018170381,0.08608096],"study_design_scores_gemma":[0.0039407257,0.00016910744,0.009907043,0.0046918807,0.000108380234,0.0007609781,0.0004207706,0.89292926,0.06780748,0.009604394,0.009175923,0.00048404004],"about_ca_topic_score_codex":0.000006303192,"about_ca_topic_score_gemma":0.000019284922,"teacher_disagreement_score":0.79353905,"about_ca_system_score_codex":0.00006322421,"about_ca_system_score_gemma":0.000092022194,"threshold_uncertainty_score":0.47085243},"labels":[],"label_agreement":null},{"id":"W4400972601","doi":"10.2316/j.2024.206-1059","title":"VISION-BASED ROBOT INDOOR-POSITIONING AND NAVIGATION METHOD RESEARCH, 1-9.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Mobile robot navigation; Robot; Human–computer interaction; Mobile robot; Robot control","score_opus":0.028240259328945232,"score_gpt":0.3889500768446982,"score_spread":0.36070981751575293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400972601","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048412057,0.0005706542,0.98554707,0.0077816043,0.0010593431,0.000057483416,0.0000020031755,0.000054784567,0.00008584607],"genre_scores_gemma":[0.43769,0.000029416136,0.5620058,0.00007682196,0.0001677537,0.0000011809175,0.0000053891413,0.0000061750266,0.000017456538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829406,0.00016944594,0.00037202687,0.00018292134,0.00085501035,0.00012655075],"domain_scores_gemma":[0.99840415,0.00058575923,0.00015634007,0.00009039104,0.0006807671,0.000082584265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001957561,0.00008767062,0.00011941716,0.0005426412,0.0001121139,0.00094546954,0.00032280514,0.00006654502,0.0000021983806],"category_scores_gemma":[0.00014593569,0.00007693285,0.00004079529,0.00026381257,0.000047263136,0.0009153864,0.000096742704,0.00032799516,0.0000046161113],"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":[0.000019108882,0.000087957844,0.00060344354,0.00009199971,0.00017186666,0.00050814735,0.0017363448,0.48137394,0.0074943216,0.08609348,0.0008744088,0.420945],"study_design_scores_gemma":[0.00023875767,0.00013525327,0.0039115255,0.0007234745,0.000009834503,0.00051759405,0.000025392867,0.9821503,0.0008304122,0.011180219,0.00019968567,0.00007751],"about_ca_topic_score_codex":0.000010205455,"about_ca_topic_score_gemma":2.1496935e-7,"teacher_disagreement_score":0.5007764,"about_ca_system_score_codex":0.00009572979,"about_ca_system_score_gemma":0.00014013858,"threshold_uncertainty_score":0.9117184},"labels":[],"label_agreement":null},{"id":"W4404510353","doi":"10.2316/j.2024.206-0922","title":"A NOVEL INTELLIGENT FAULT OBSERVER TO DIAGNOSE ACTUATOR FAULT AND SENSOR NOISE BASED ON PROBABILITY DISTRIBUTIONS, 1-12.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Observer (physics); Actuator; Fault (geology); Noise (video); Computer science; Control theory (sociology); Artificial intelligence; Physics; Control (management); Geology","score_opus":0.015190048086705718,"score_gpt":0.2541019303311755,"score_spread":0.2389118822444698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404510353","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":[0.4279532,0.00028359084,0.5642997,0.004483738,0.0023730947,0.00027955353,0.00009348526,0.00013433209,0.00009931493],"genre_scores_gemma":[0.9955907,0.00007463415,0.0039712815,0.000082482686,0.0002202689,0.00000806785,0.000009330671,0.000011841232,0.000031397474],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991106,0.0000242298,0.0003533083,0.000104073166,0.00031542926,0.0000923951],"domain_scores_gemma":[0.9994166,0.00014939114,0.000055733544,0.00006229396,0.00020254363,0.00011342417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027214226,0.00010631823,0.00012741495,0.00018325947,0.00003916009,0.00026563447,0.000079802645,0.00005798649,0.000012976796],"category_scores_gemma":[0.00022490055,0.000092484894,0.00006100975,0.00007522955,0.000016664115,0.00016848728,0.00001307223,0.0001409056,0.000006456444],"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":[0.00008871294,0.00016416634,0.00056681945,0.00016166618,0.00023976616,0.000045624754,0.0005904025,0.9012527,0.01299523,0.0042190426,0.00096137804,0.07871452],"study_design_scores_gemma":[0.00039486884,0.00009343365,0.0044768904,0.00037855146,0.000024612189,0.00006104685,0.000054228432,0.9832703,0.001049986,0.00019136287,0.009889278,0.00011545927],"about_ca_topic_score_codex":0.000014745422,"about_ca_topic_score_gemma":0.000019143159,"teacher_disagreement_score":0.5676375,"about_ca_system_score_codex":0.00020836311,"about_ca_system_score_gemma":0.000036458627,"threshold_uncertainty_score":0.37714246},"labels":[],"label_agreement":null},{"id":"W4405602834","doi":"10.2316/j.2025.206-1048","title":"IMAGE STYLE MIGRATION BASED ON CYCLEGAN WITH SAME MAPPING LOSS, 23-32.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Style (visual arts); Image (mathematics); Computer science; Artificial intelligence; Computer vision; Art; Visual arts","score_opus":0.009722148558883544,"score_gpt":0.2729533958971858,"score_spread":0.2632312473383023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405602834","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":[0.005273823,0.000052115167,0.9837395,0.010203706,0.00042133132,0.00006250039,0.0000023643352,0.00009664763,0.00014799643],"genre_scores_gemma":[0.5034742,0.00004218559,0.49570602,0.0005794462,0.00013874624,0.0000018295123,0.000009404375,0.000007126336,0.0000410614],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880123,0.00004124498,0.00031125662,0.00012834163,0.0006414646,0.00007647403],"domain_scores_gemma":[0.9992357,0.00011605867,0.00019004426,0.000085159794,0.0003119739,0.000061090286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034289787,0.00008577648,0.00009262792,0.00035381093,0.000034976947,0.0005973639,0.0002768966,0.00003194505,0.000014067666],"category_scores_gemma":[0.00006279289,0.00006541505,0.000039876686,0.00015565725,0.0000378303,0.0009687729,0.000028717232,0.00014054748,0.000008327121],"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":[0.00012373192,0.0005739363,0.0015277613,0.00030200067,0.0004676381,0.0017521544,0.004511811,0.037943404,0.060864065,0.05993902,0.012670717,0.8193238],"study_design_scores_gemma":[0.00030855322,0.00018535223,0.0020037415,0.0005119224,0.000009234137,0.00014335079,0.00003122266,0.988905,0.005796866,0.0015600391,0.00045266107,0.000092022536],"about_ca_topic_score_codex":0.0000046608984,"about_ca_topic_score_gemma":0.0000018916293,"teacher_disagreement_score":0.95096165,"about_ca_system_score_codex":0.00008211983,"about_ca_system_score_gemma":0.000088570676,"threshold_uncertainty_score":0.57603943},"labels":[],"label_agreement":null},{"id":"W4405602838","doi":"10.2316/j.2025.206-1098","title":"A NOVEL PATH PLANNING FOR AUV BASED ON DUNG BEETLE OPTIMISATION ALGORITHM WITH DEEP Q-NETWORK, 65-73.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Computer science; Motion planning; Algorithm; Artificial intelligence; Computer network","score_opus":0.01194561930477063,"score_gpt":0.24014702189901266,"score_spread":0.22820140259424204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405602838","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":[0.021401366,0.00016665448,0.97692466,0.00034322948,0.0008148304,0.000103009595,0.000017703931,0.000079807585,0.00014874233],"genre_scores_gemma":[0.743628,0.00003358477,0.25566018,0.000049011043,0.0005311485,0.0000056460844,0.00005631755,0.000026830696,0.000009249088],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927056,0.000008301538,0.0002608123,0.00008287708,0.00027544744,0.00010197828],"domain_scores_gemma":[0.9994548,0.00016514515,0.00009325655,0.000033478183,0.0002114195,0.000041907762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020816023,0.000101186444,0.000106508036,0.0001890496,0.000032804754,0.00017042356,0.000063449625,0.000056000234,0.0000059272197],"category_scores_gemma":[0.00001946208,0.00008853617,0.00004458906,0.00007786025,0.00000949115,0.00027648458,0.00000548969,0.0001301729,0.000001971722],"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":[0.000026729702,0.000018423876,0.000028915008,0.0000404358,0.00010087372,0.000018685265,0.000108693035,0.9329727,0.0008170039,0.0002920078,0.0001405788,0.06543492],"study_design_scores_gemma":[0.0005934887,0.0001407781,0.000889397,0.000720141,0.00004415265,0.00014302362,0.000024443394,0.9962642,0.00034922067,0.00034070882,0.0003884149,0.000102029364],"about_ca_topic_score_codex":9.1868606e-7,"about_ca_topic_score_gemma":7.274533e-7,"teacher_disagreement_score":0.7222267,"about_ca_system_score_codex":0.0001030529,"about_ca_system_score_gemma":0.000028408827,"threshold_uncertainty_score":0.36104003},"labels":[],"label_agreement":null},{"id":"W4405603038","doi":"10.2316/j.2025.206-1164","title":"GLOBAL PATH PLANNING OF CLIMBING ROBOT FOR WELD QUALITY INSPECTION IN LARGE SCALE STORAGE TANKS, 242-253.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Scale (ratio); Storage tank; Robot; Computer science; Path (computing); Marine engineering; Environmental science; Artificial intelligence; Engineering; Mechanical engineering; Geography","score_opus":0.022946404129995015,"score_gpt":0.33887407109252166,"score_spread":0.31592766696252667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603038","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":[0.07588348,0.00045392945,0.92002857,0.00087772706,0.0025432906,0.00007919689,0.000020748952,0.00005039221,0.000062642],"genre_scores_gemma":[0.8074419,0.000022711441,0.19231732,0.00003406923,0.00016101389,0.0000014959487,0.0000071498657,0.000005142104,0.0000091960555],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850184,0.00006130366,0.00066189136,0.00016953083,0.00046378316,0.00014167627],"domain_scores_gemma":[0.9990944,0.0001743864,0.00030475468,0.00008858826,0.00028942336,0.000048441314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011355904,0.000100163226,0.00020260153,0.00027412394,0.00004563988,0.00019498676,0.00032921595,0.00006675792,9.714614e-7],"category_scores_gemma":[0.00014019349,0.00009487508,0.000081380196,0.00023712368,0.000020508705,0.00070905534,0.000076651784,0.00013739483,7.262091e-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":[0.000038192302,0.00017156047,0.02485991,0.00012871304,0.0001085161,0.00009806057,0.0022593564,0.92445487,0.0008427004,0.029390402,0.00036501372,0.017282683],"study_design_scores_gemma":[0.00053254154,0.000107364554,0.0922217,0.000577779,0.00001018766,0.00012286972,0.00011569394,0.902571,0.00009702253,0.0034854752,0.00006799294,0.00009037485],"about_ca_topic_score_codex":0.000016968917,"about_ca_topic_score_gemma":0.0000042671486,"teacher_disagreement_score":0.73155844,"about_ca_system_score_codex":0.00020390128,"about_ca_system_score_gemma":0.000105754116,"threshold_uncertainty_score":0.38688937},"labels":[],"label_agreement":null},{"id":"W4405603084","doi":"10.2316/j.2025.206-0890","title":"STABILITY ANALYSIS AND OPTIMISATION OF GRASSHOPPER HOPPING ROBOT WITH DAMPING SYSTEM, 1-14.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Grasshopper; Robot; Stability (learning theory); Control theory (sociology); Computer science; Artificial intelligence; Ecology; Biology; Machine learning","score_opus":0.007418838095601268,"score_gpt":0.2186183761345116,"score_spread":0.21119953803891034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603084","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":[0.16258913,0.00042607804,0.8360455,0.0003627709,0.00034398393,0.000052684085,0.0000036965066,0.000046229816,0.00012991657],"genre_scores_gemma":[0.98988074,0.000105408464,0.009917816,0.0000071481445,0.0000687513,0.0000010288386,0.000005669736,0.000008318066,0.000005089517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991785,0.000023404442,0.00038347478,0.000076274046,0.00027698465,0.00006133563],"domain_scores_gemma":[0.9994711,0.00006873383,0.000115612434,0.000050728126,0.00025209022,0.00004173158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028368237,0.00008158275,0.00018514505,0.0003309918,0.000020740521,0.00012634044,0.00006380008,0.00003664372,0.00000879736],"category_scores_gemma":[0.000018554814,0.000065189626,0.00006070353,0.00017976857,0.000025481579,0.00029924265,0.000011068076,0.00008887108,3.931358e-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":[0.000011377028,0.0000128032425,0.0025623494,0.00015451557,0.0009760841,0.000009558618,0.00035122686,0.97863144,0.0030716686,0.0027940795,0.0000092791,0.011415631],"study_design_scores_gemma":[0.000287821,0.000037332386,0.012498099,0.00030299803,0.0002839572,0.000074817886,0.00020502329,0.9855129,0.00063338736,0.000077394936,0.000015812946,0.00007043386],"about_ca_topic_score_codex":0.0000059999893,"about_ca_topic_score_gemma":0.0000063985126,"teacher_disagreement_score":0.82729167,"about_ca_system_score_codex":0.00008066603,"about_ca_system_score_gemma":0.0000217382,"threshold_uncertainty_score":0.26583558},"labels":[],"label_agreement":null},{"id":"W4405603119","doi":"10.2316/j.2025.206-1114","title":"OVERCOMING VALUE OVERESTIMATION FOR DISTRIBUTIONAL REINFORCEMENT LEARNING-BASED PATH PLANNING WITH CONSERVATIVE CONSTRAINTS, 124-132.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reinforcement learning; Reinforcement; Path (computing); Computer science; Mathematical optimization; Motion planning; Value (mathematics); Artificial intelligence; Mathematics; Machine learning; Engineering; Structural engineering","score_opus":0.018899572378057224,"score_gpt":0.29031087367882,"score_spread":0.2714113013007628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603119","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":[0.0039789705,0.00012304807,0.9927024,0.002260144,0.0006844731,0.00012143,0.000013341917,0.00006247007,0.000053689368],"genre_scores_gemma":[0.7125174,0.0000046197924,0.28718805,0.00009408245,0.00011300747,0.0000039862707,0.00005453003,0.0000066987022,0.000017618673],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986862,0.000042970216,0.00041705288,0.00016296808,0.0005567305,0.00013409673],"domain_scores_gemma":[0.9984584,0.0005203752,0.00036671566,0.000063208485,0.00052753027,0.00006376888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005310319,0.00012632748,0.00015011034,0.00020446963,0.000104327955,0.00044787035,0.00024484695,0.000048369802,0.0000035996395],"category_scores_gemma":[0.00021765576,0.00010505177,0.00005112528,0.00011462159,0.000065753935,0.0006793597,0.000036710062,0.0001842528,0.0000013123253],"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":[0.000028122608,0.000018887953,0.0007496745,0.000031989493,0.00011438467,0.00006119389,0.00028813985,0.92758876,0.00016220835,0.066498786,0.00020781464,0.0042500123],"study_design_scores_gemma":[0.0007210589,0.0003180893,0.0032160373,0.0009464952,0.000026848838,0.00024461237,0.000036718957,0.99163973,0.00024190343,0.002121355,0.00036536972,0.00012180216],"about_ca_topic_score_codex":0.0000029649007,"about_ca_topic_score_gemma":6.2594815e-8,"teacher_disagreement_score":0.7085384,"about_ca_system_score_codex":0.00016969001,"about_ca_system_score_gemma":0.00030463256,"threshold_uncertainty_score":0.4318824},"labels":[],"label_agreement":null},{"id":"W4405603145","doi":"10.2316/j.2025.206-1162","title":"A SPATIAL POSITIONING METHOD OF LIGHT ABSORBING MATERIAL OBJECT FOR VOLUTE DEPALLETISING SYSTEM BASED ON RGB-D CAMERA, 230-241.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optical Systems and Laser Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Volute; Computer vision; RGB color model; Artificial intelligence; Object (grammar); Computer science; Computer graphics (images); Engineering; Mechanical engineering","score_opus":0.005246455162048062,"score_gpt":0.2430559909997558,"score_spread":0.23780953583770775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603145","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":[0.054487027,0.0001532573,0.94210386,0.0005246947,0.0023011335,0.00010002973,0.00002679751,0.000093783965,0.00020940613],"genre_scores_gemma":[0.9491637,0.000007549975,0.05043552,0.000011013693,0.00034660584,0.0000032271544,0.000009169028,0.0000174735,0.0000057547413],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991438,0.000022071552,0.0004438365,0.0000788344,0.0002219204,0.00008956741],"domain_scores_gemma":[0.99951833,0.0001217907,0.00012239999,0.0000446613,0.00016256758,0.00003026723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028770103,0.00009038054,0.00018350073,0.00026879445,0.000029867851,0.00012173583,0.00009211964,0.000080063255,0.000007949079],"category_scores_gemma":[0.00003229749,0.000079624464,0.000080550904,0.00005447254,0.000010068395,0.000107726315,0.000011038997,0.00009623298,0.0000013536662],"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":[0.00010682604,0.000042243217,0.00006903337,0.0009631388,0.0004393638,0.00008462524,0.00031983948,0.8553712,0.062364865,0.032507632,0.0003127769,0.047418505],"study_design_scores_gemma":[0.00032497055,0.00013339616,0.00019479527,0.0012878844,0.000044760065,0.00014312888,0.000051735333,0.9834166,0.013791486,0.00020809403,0.00032548484,0.0000776359],"about_ca_topic_score_codex":0.000019690415,"about_ca_topic_score_gemma":0.0000032957794,"teacher_disagreement_score":0.8946767,"about_ca_system_score_codex":0.00012082643,"about_ca_system_score_gemma":0.000023563773,"threshold_uncertainty_score":0.32469913},"labels":[],"label_agreement":null},{"id":"W4405603205","doi":"10.2316/j.2025.206-1148","title":"MARGIN-CONSTRAINED PID CONTROLLER TUNING METHOD FOR SYSTEMS WITH PARAMETER UNCERTAINTY, 153-162.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Mathematical Control Systems and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"PID controller; Control theory (sociology); Margin (machine learning); Controller (irrigation); Computer science; Mathematics; Control engineering; Mathematical optimization; Engineering; Control (management); Artificial intelligence; Temperature control; Biology","score_opus":0.013816403928668041,"score_gpt":0.2864334027428782,"score_spread":0.27261699881421014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603205","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":[0.00065176503,0.00049254624,0.994568,0.0034229932,0.00054475793,0.00014247159,0.000005431287,0.000033395387,0.00013863288],"genre_scores_gemma":[0.8041069,0.000013015976,0.1953856,0.000083959494,0.00023310281,0.000008212087,0.0000021054022,0.0000074258696,0.00015968886],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998754,0.00006466495,0.00051214645,0.00014686909,0.00040737016,0.00011494286],"domain_scores_gemma":[0.9983423,0.00070220925,0.00029544922,0.000076085256,0.0005158761,0.00006811396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093336764,0.000109509696,0.0002871114,0.00024168637,0.000045550423,0.0008594104,0.00028968934,0.00004125782,0.000004017294],"category_scores_gemma":[0.0001204336,0.00007037343,0.0001280966,0.00011309994,0.000019369281,0.00041382815,0.000030977673,0.00009227372,0.0000015828605],"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":[0.000059179398,0.00006220941,0.000059129456,0.00023080387,0.0015224374,0.000078689634,0.0006716961,0.21068199,0.0017641388,0.7015475,0.0004795249,0.082842685],"study_design_scores_gemma":[0.0006690317,0.00011959779,0.000035854897,0.00040788917,0.00007160353,0.00027691427,0.00004525208,0.988114,0.000016677635,0.00885303,0.0013026586,0.0000875088],"about_ca_topic_score_codex":0.000012781237,"about_ca_topic_score_gemma":0.0000025269333,"teacher_disagreement_score":0.8034551,"about_ca_system_score_codex":0.000049391994,"about_ca_system_score_gemma":0.000065055596,"threshold_uncertainty_score":0.8287314},"labels":[],"label_agreement":null},{"id":"W4405603221","doi":"10.2316/j.2025.206-1134","title":"HAPTIC SENSITIVITY STUDY FOR WEARABLE HELMET-TYPE DEVICES, 144-152.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Haptic technology; Wearable computer; Sensitivity (control systems); Computer science; Wearable technology; Human–computer interaction; Simulation; Engineering; Embedded system","score_opus":0.01994268839260709,"score_gpt":0.3373885486117711,"score_spread":0.317445860219164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603221","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":[0.9417952,0.0014892009,0.047803007,0.0021790273,0.005199332,0.00025603094,0.000012311863,0.000034340475,0.0012315826],"genre_scores_gemma":[0.99742573,0.000072818206,0.0017537894,0.00009983087,0.00023793767,0.0000027358649,0.0000065319587,0.000013507008,0.00038709198],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992629,0.000046623405,0.00030685455,0.00012078128,0.00016771593,0.00009508524],"domain_scores_gemma":[0.9993157,0.00016171487,0.00013862636,0.000057237066,0.00028478718,0.000041972373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005215094,0.00008335359,0.00013003314,0.00018611058,0.00003882753,0.00015675882,0.00008369043,0.000043141477,0.00003616017],"category_scores_gemma":[0.000052729993,0.00007320999,0.000079532416,0.00006895857,0.00001815211,0.0001896487,0.000022260732,0.00010425172,0.000017315442],"study_design_candidate":"design_other","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":[0.0010560858,0.0031375075,0.02250511,0.0004082586,0.0077145854,0.00069110125,0.009708285,0.05170733,0.009569918,0.2900653,0.01257718,0.59085935],"study_design_scores_gemma":[0.004730904,0.0029824488,0.4803696,0.0007775603,0.00064024754,0.0007998823,0.0043533063,0.45707524,0.000085591564,0.016347235,0.031134747,0.00070324703],"about_ca_topic_score_codex":0.00003762693,"about_ca_topic_score_gemma":0.00004711322,"teacher_disagreement_score":0.59015614,"about_ca_system_score_codex":0.000042778076,"about_ca_system_score_gemma":0.000046248413,"threshold_uncertainty_score":0.29854167},"labels":[],"label_agreement":null},{"id":"W4405603229","doi":"10.2316/j.2025.206-1074","title":"MULTIMODE HUAUV AERIAL TRAJECTORY TRACKING WITH ANTISATURATION CONTROL, 93-103.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Multi-mode optical fiber; Trajectory; Tracking (education); Computer science; Control (management); Control theory (sociology); Optics; Physics; Artificial intelligence; Psychology; Optical fiber","score_opus":0.006197763075984429,"score_gpt":0.2288977527158716,"score_spread":0.22269998963988716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603229","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":[0.62708235,0.0005687543,0.36873636,0.0004491967,0.0027593996,0.00007974728,0.000010330198,0.00011199228,0.00020189643],"genre_scores_gemma":[0.9958553,0.00010774617,0.003231955,0.00002072602,0.0007453053,7.3148954e-7,0.000013967447,0.0000151864915,0.000009108118],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999309,0.000015900261,0.00027508943,0.000060618084,0.00026760934,0.00007177459],"domain_scores_gemma":[0.9996261,0.00004902953,0.000068365276,0.000027908447,0.00019652615,0.00003208298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012399859,0.00008460055,0.00010341361,0.00015230472,0.000026764234,0.00019438883,0.00006036194,0.00004958236,0.000010160356],"category_scores_gemma":[0.000017145241,0.00006806751,0.000040149982,0.00006232025,0.000016447766,0.0005228422,0.0000030879182,0.00013293956,0.0000027136832],"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":[0.00007611546,0.000018961306,0.0002271972,0.000043689324,0.0002118353,0.00006242836,0.0005231062,0.87680167,0.068920396,0.0019383243,0.00018725355,0.05098903],"study_design_scores_gemma":[0.0007450127,0.00007763037,0.0074374056,0.00025291508,0.000050954157,0.00022619321,0.000029730305,0.98484933,0.0055737915,0.0002242012,0.00042538604,0.00010746371],"about_ca_topic_score_codex":0.0000058656146,"about_ca_topic_score_gemma":0.000006235699,"teacher_disagreement_score":0.36877292,"about_ca_system_score_codex":0.000068715504,"about_ca_system_score_gemma":0.000021471691,"threshold_uncertainty_score":0.27757126},"labels":[],"label_agreement":null},{"id":"W4405603230","doi":"10.2316/j.2025.206-1052","title":"MULTI-OBJECT GRASPING DETECTION BASED ON THE IMPROVED SHUFFLENET NETWORK, 33-42.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Object detection; Computer vision; Artificial intelligence; Object (grammar); Remote sensing; Pattern recognition (psychology); Geography","score_opus":0.018769216977374176,"score_gpt":0.2639024319139,"score_spread":0.24513321493652582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603230","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":[0.004446227,0.00020673683,0.98747396,0.0044354815,0.0031975785,0.00008804157,0.0000014685362,0.00005348301,0.000097028555],"genre_scores_gemma":[0.9823284,0.000032640608,0.016691687,0.00034274952,0.0005608777,0.0000032832265,0.0000016321766,0.000006770504,0.000031961372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899185,0.000090937996,0.00033185523,0.00012215678,0.00036795577,0.00009522635],"domain_scores_gemma":[0.9991003,0.00027181001,0.00020672042,0.00008868102,0.0002925564,0.000039892373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007383739,0.000088549656,0.00009479453,0.00018914131,0.000074465606,0.0005966204,0.00029018364,0.000045467415,0.000003890933],"category_scores_gemma":[0.00008562201,0.000058262252,0.00007905759,0.00016976394,0.000015070559,0.00035643528,0.000034533026,0.00017911586,0.0000089082205],"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":[0.000040837433,0.00012870466,0.00031134667,0.00006628369,0.00035055826,0.00009493064,0.00083563896,0.49506363,0.016322171,0.015191291,0.0009287626,0.47066584],"study_design_scores_gemma":[0.00023024196,0.00008903518,0.0026358273,0.00030964008,0.0000100410525,0.000118574964,0.000013563994,0.99405086,0.0006306806,0.0009607357,0.000883779,0.00006702309],"about_ca_topic_score_codex":0.000004756426,"about_ca_topic_score_gemma":0.00000703567,"teacher_disagreement_score":0.97788215,"about_ca_system_score_codex":0.00006674748,"about_ca_system_score_gemma":0.00006603516,"threshold_uncertainty_score":0.5753224},"labels":[],"label_agreement":null},{"id":"W4405603271","doi":"10.2316/j.2025.206-0941","title":"VISUAL-INERTIAL ODOMETRY SYSTEMS WITH ONLINE TEMPORAL OFFSET OPTIMISATION, 82-92.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Odometry; Offset (computer science); Inertial frame of reference; Computer vision; Artificial intelligence; Visual odometry; Computer science; Inertial measurement unit; Robot; Physics; Mobile robot","score_opus":0.011415250914081273,"score_gpt":0.3049930718813991,"score_spread":0.2935778209673178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603271","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":[0.015826276,0.0005634406,0.9779619,0.0038279165,0.00166009,0.00004569925,0.0000040477075,0.00005908588,0.000051565567],"genre_scores_gemma":[0.85558933,0.0000877996,0.14375316,0.000117715485,0.0003421643,5.1619423e-7,0.000012976417,0.000007589089,0.000088722605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886465,0.000028051223,0.00038159612,0.00012819782,0.00051463355,0.00008285128],"domain_scores_gemma":[0.9991248,0.000070238806,0.00022123937,0.000067270696,0.00045297408,0.00006342756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002272797,0.00009088809,0.00012103915,0.00036335477,0.000041972617,0.000575158,0.00026068374,0.000028039036,0.0000048297643],"category_scores_gemma":[0.000042858755,0.00006630853,0.00003884088,0.00020223837,0.000024089935,0.0011893784,0.000058096073,0.00013271622,0.000003924164],"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":[0.000071461705,0.0003275638,0.002379497,0.000111570786,0.0003914259,0.00044257523,0.0009860261,0.4698006,0.003435039,0.061502427,0.0026242887,0.45792753],"study_design_scores_gemma":[0.0003236194,0.000118930024,0.0013373947,0.00032864814,0.000010112224,0.0005598305,0.000055540142,0.9942447,0.00011391331,0.00054760044,0.002274219,0.00008549895],"about_ca_topic_score_codex":0.0000055039623,"about_ca_topic_score_gemma":7.836466e-7,"teacher_disagreement_score":0.8397631,"about_ca_system_score_codex":0.0000638407,"about_ca_system_score_gemma":0.00008907833,"threshold_uncertainty_score":0.55462617},"labels":[],"label_agreement":null},{"id":"W4405603276","doi":"10.2316/j.2025.206-1106","title":"DEEP REINFORCEMENT LEARNING FOR AUTONOMOUS CONTROL OF MANUFACTURING SYSTEMS IN VOCATIONAL EDUCATION: A COMPARATIVE ANALYSIS, 163-174.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Vocational education; Reinforcement learning; Control (management); Autonomous learning; Reinforcement; Artificial intelligence; Mathematics education; Manufacturing engineering; Computer science; Engineering; Psychology; Pedagogy; Structural engineering","score_opus":0.0138803162539617,"score_gpt":0.2722643675956464,"score_spread":0.2583840513416847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603276","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":[0.01874183,0.00095692807,0.9758558,0.00020431058,0.0012648328,0.00017862771,0.000006654456,0.000033845317,0.002757124],"genre_scores_gemma":[0.99845576,0.000051505252,0.0012257405,0.000008384202,0.00012929324,0.000012549502,0.000044585835,0.00000627674,0.00006592909],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896485,0.000013987089,0.0006409915,0.000058893722,0.00025088078,0.000070418064],"domain_scores_gemma":[0.99937314,0.00014205476,0.00016171946,0.00003322379,0.00025729358,0.0000325862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021788859,0.000083602405,0.00018921687,0.0006445935,0.000019482979,0.00017989865,0.00009665893,0.00004667054,0.000010340211],"category_scores_gemma":[0.000015575934,0.0000816523,0.000079363876,0.00015510942,0.000016323498,0.00048545867,0.0000054159073,0.0001285003,0.000001049389],"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":[0.000009848056,0.000018248002,0.00012221852,0.000106207066,0.0005146541,0.0000010352788,0.00051058555,0.9811464,0.00005653666,0.0091892695,0.00005484193,0.008270185],"study_design_scores_gemma":[0.00033641607,0.000036301186,0.0023036608,0.00024950763,0.00009242382,0.000026236896,0.00044109733,0.994435,0.0005765681,0.0003215174,0.0011078697,0.000073410854],"about_ca_topic_score_codex":0.0000052996265,"about_ca_topic_score_gemma":0.0000025906745,"teacher_disagreement_score":0.9797139,"about_ca_system_score_codex":0.00016313362,"about_ca_system_score_gemma":0.000079249396,"threshold_uncertainty_score":0.3329684},"labels":[],"label_agreement":null},{"id":"W4405603278","doi":"10.2316/j.2025.206-1107","title":"STUDY ON CONTROL STRATEGY OF BILATERAL PERMANENT MAGNET LINEAR MOTOR, 254-262.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Magnet; Linear motor; Control theory (sociology); Control (management); Motor control; Computer science; Psychology; Engineering; Mechanical engineering; Artificial intelligence; Neuroscience","score_opus":0.011525649721310259,"score_gpt":0.25823734955439837,"score_spread":0.2467116998330881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603278","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":[0.9904748,0.0004932788,0.007178295,0.0002987066,0.0011617721,0.0001368464,0.00001263717,0.000047263507,0.00019639418],"genre_scores_gemma":[0.99925435,0.00006296636,0.00032655968,0.000018531402,0.00028528617,0.0000013472269,0.000002579447,0.000014813628,0.00003358005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903053,0.000024186982,0.00042804552,0.00006906795,0.00036795798,0.00008023423],"domain_scores_gemma":[0.99954015,0.00009651563,0.000096169075,0.00005047947,0.00017738513,0.000039279323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017153875,0.000098872486,0.000167104,0.00031727846,0.000010862048,0.000075503114,0.00011599915,0.00003706556,0.00001635191],"category_scores_gemma":[0.000022681523,0.00008220697,0.00006387854,0.00006158006,0.00001158007,0.00015596718,0.000006682261,0.00014784519,0.0000041564263],"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":[0.00007794594,0.00015941983,0.0012388602,0.000044170098,0.00066744315,0.00028246111,0.00047950732,0.96117175,0.011811225,0.0020047089,0.0002401963,0.02182234],"study_design_scores_gemma":[0.0012137038,0.00067247584,0.043854356,0.00013927338,0.00007005686,0.00013407502,0.000082704675,0.9528722,0.00046962686,0.00028670984,0.000105064435,0.0000997324],"about_ca_topic_score_codex":0.0000033866233,"about_ca_topic_score_gemma":0.000001176393,"teacher_disagreement_score":0.042615496,"about_ca_system_score_codex":0.000064460095,"about_ca_system_score_gemma":0.000022759472,"threshold_uncertainty_score":0.3352303},"labels":[],"label_agreement":null},{"id":"W4405603297","doi":"10.2316/j.2025.206-1111","title":"AN IMPROVED ILLUMINATION ADAPTIVE ORB-SLAM3 ALGORITHM, 115-123.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Orb (optics); Computer science; Algorithm; Artificial intelligence; Image (mathematics)","score_opus":0.008906515755286358,"score_gpt":0.2801432405546302,"score_spread":0.27123672479934385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603297","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":[0.0025030293,0.00020073821,0.9938552,0.001668472,0.0013796284,0.00006899061,0.0000029389041,0.00013242586,0.00018857756],"genre_scores_gemma":[0.5983834,0.00008490565,0.4011352,0.00007845136,0.00024227436,0.0000018708317,0.000004795315,0.0000065558074,0.00006248663],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896413,0.000039354927,0.0003371275,0.0001469183,0.0004217932,0.00009068111],"domain_scores_gemma":[0.9990352,0.000049861294,0.00020323768,0.000097744116,0.00056677166,0.000047198042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041982037,0.00009226899,0.000097036485,0.00032845334,0.00003920641,0.0005496061,0.00045036816,0.000044573833,0.000007723371],"category_scores_gemma":[0.000030993964,0.000081474005,0.000047726022,0.0001366439,0.000027821045,0.002130192,0.00006520295,0.000131846,0.000005480556],"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":[0.0000059701815,0.00007635456,0.00001279633,0.000009503548,0.00008090303,0.00006878913,0.0007462636,0.001030016,0.012012591,0.03967018,0.000486964,0.94579965],"study_design_scores_gemma":[0.00015780375,0.0002565365,0.00060216704,0.00011496126,0.0000109069515,0.00015069959,0.000032233023,0.9800126,0.00855379,0.009366991,0.0006482315,0.00009308959],"about_ca_topic_score_codex":0.000005607448,"about_ca_topic_score_gemma":0.0000012939867,"teacher_disagreement_score":0.97898257,"about_ca_system_score_codex":0.0001114691,"about_ca_system_score_gemma":0.000077736404,"threshold_uncertainty_score":0.52998644},"labels":[],"label_agreement":null},{"id":"W4405603354","doi":"10.2316/j.2025.206-1150","title":"A KEY FRAME SELECTION AND LOCAL BA OPTIMISATION METHOD FOR VSLAM, 289-300.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Key (lock); Frame (networking); Computer science; Key frame; Artificial intelligence; Computer vision; Computer security; Computer network","score_opus":0.010488990303643248,"score_gpt":0.29682048787614135,"score_spread":0.2863314975724981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603354","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":[0.019461926,0.000566447,0.9784832,0.0006546725,0.0006112673,0.00007545549,0.00000449245,0.00007879177,0.000063717736],"genre_scores_gemma":[0.79192966,0.00026488618,0.20746867,0.000010907092,0.0002705556,0.0000047300105,0.000006520013,0.000018829951,0.000025245188],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993807,0.000010571567,0.00022661591,0.000071930226,0.00022680582,0.00008334859],"domain_scores_gemma":[0.99956733,0.00015716298,0.000035445242,0.000024421144,0.00017132433,0.00004433261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003523462,0.00007511302,0.00009106318,0.00025099533,0.00002341906,0.00017348485,0.000061418374,0.0000638233,0.0000064739334],"category_scores_gemma":[0.000044733424,0.00007058288,0.000034341567,0.00007580176,0.000011488772,0.00020906235,0.000012346866,0.00016619357,0.0000014402893],"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":[0.000008478954,0.0000061089677,0.000011309247,0.00009446912,0.00011210696,0.0000033105512,0.00018197024,0.8744944,0.008398557,0.00783025,0.00029147606,0.10856762],"study_design_scores_gemma":[0.00020975393,0.00004932587,0.0003937036,0.00011661874,0.00002065995,0.00015848881,0.000026800426,0.99246323,0.002367988,0.0022974405,0.0018265822,0.00006943437],"about_ca_topic_score_codex":0.000002545309,"about_ca_topic_score_gemma":0.0000014798594,"teacher_disagreement_score":0.77246773,"about_ca_system_score_codex":0.00010363208,"about_ca_system_score_gemma":0.000022260716,"threshold_uncertainty_score":0.28782862},"labels":[],"label_agreement":null},{"id":"W4405603386","doi":"10.2316/j.2025.206-1122","title":"DEVELOPMENT OF INTELLIGENT SEWING EQUIPMENT BASED ON THE COLLABORATION OF MACHINE VISION AND ROBOT ARM, 133-143.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Sewing machine; Machine vision; Robot; Computer science; Robotic arm; Engineering; Human–computer interaction; Artificial intelligence; Manufacturing engineering; Engineering drawing; Computer vision; Mechanical engineering","score_opus":0.018632901541539064,"score_gpt":0.2922299982731046,"score_spread":0.2735970967315655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603386","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":[0.17565088,0.00037264905,0.82183915,0.0013209472,0.0005319958,0.00010153411,0.0000069097146,0.000023849927,0.0001520605],"genre_scores_gemma":[0.9815132,0.00009190706,0.018306734,0.000028324332,0.00003257643,0.0000018742069,0.000010365264,0.0000073833144,0.000007649344],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992119,0.000012307266,0.0004148848,0.000051761086,0.0002707876,0.0000383756],"domain_scores_gemma":[0.9994827,0.00011791387,0.000112636364,0.000044228622,0.00021983813,0.000022691132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029479212,0.00006392412,0.00008577543,0.00018006378,0.000027288022,0.000053428783,0.00006507256,0.000026315827,0.0000114490695],"category_scores_gemma":[0.000026151962,0.000046212845,0.000024934314,0.00009021079,0.000015115919,0.00008733259,0.000013292403,0.00006713255,7.3368295e-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":[0.000008413402,0.00003111939,0.000037778784,0.00003859483,0.00005421502,5.8910086e-7,0.00085895014,0.95822096,0.008964008,0.004578231,0.000050791048,0.02715635],"study_design_scores_gemma":[0.00013687668,0.000033820415,0.0007448546,0.00030001564,0.000014950263,0.0000043490068,0.00011123066,0.9869183,0.0107947355,0.0003759129,0.0005238339,0.00004112493],"about_ca_topic_score_codex":9.76354e-7,"about_ca_topic_score_gemma":0.0000016125115,"teacher_disagreement_score":0.8058623,"about_ca_system_score_codex":0.00005816536,"about_ca_system_score_gemma":0.000044653305,"threshold_uncertainty_score":0.18845052},"labels":[],"label_agreement":null},{"id":"W4405603425","doi":"10.2316/j.2025.206-1099","title":"ADAPTIVE CONSTRAINT CONTROL OF ROBOTIC MANIPULATORS BASED ON BARRIER LYAPUNOV FUNCTION, 74-81. SI","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Lyapunov function; Control theory (sociology); Constraint (computer-aided design); Adaptive control; Lyapunov redesign; Robot manipulator; Computer science; Control (management); Function (biology); Control engineering; Engineering; Artificial intelligence; Physics; Nonlinear system; Mechanical engineering; Biology","score_opus":0.010881407162859288,"score_gpt":0.2275154617855228,"score_spread":0.2166340546226635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603425","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":[0.010812235,0.000700289,0.9848236,0.00046622398,0.002662498,0.00011473675,0.000022435175,0.00006198972,0.00033598786],"genre_scores_gemma":[0.9961116,0.000019210733,0.0034080718,0.0000616925,0.00035179438,0.0000015970853,0.0000053411723,0.000022619186,0.000018088203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987929,0.000037391506,0.00055099145,0.00009144465,0.0004332442,0.00009405406],"domain_scores_gemma":[0.9990865,0.00021592616,0.00017302576,0.00006423629,0.00039475143,0.000065578824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002839012,0.00013487147,0.00023541373,0.00034414855,0.000019051744,0.00006963083,0.00011120951,0.00006797384,0.00003203064],"category_scores_gemma":[0.000062360545,0.00011689522,0.000117225965,0.00007169035,0.000038820643,0.00020738516,0.000007647632,0.00017283828,0.000007283516],"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":[0.0000594482,0.000023102493,0.00029176148,0.000035506033,0.00036944542,0.00003453266,0.000057450583,0.9833331,0.00162578,0.0085845115,0.00015199745,0.0054333266],"study_design_scores_gemma":[0.0007702684,0.00021128259,0.0036059238,0.0004322795,0.00008163648,0.000057202302,0.000056211684,0.99376714,0.00016860373,0.0004172227,0.00033316066,0.00009903639],"about_ca_topic_score_codex":0.0000024931041,"about_ca_topic_score_gemma":0.0000019780161,"teacher_disagreement_score":0.98529935,"about_ca_system_score_codex":0.000123728,"about_ca_system_score_gemma":0.00006782268,"threshold_uncertainty_score":0.4766849},"labels":[],"label_agreement":null},{"id":"W4405603434","doi":"10.2316/j.2025.206-1112","title":"A SLIDING MODE-BASED MODEL-FREE CONTROL FOR WHEELED MOBILE ROBOTS, 263-269.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mobile robot; Sliding mode control; Robot; Mode (computer interface); Control theory (sociology); Computer science; Control (management); Control engineering; Engineering; Artificial intelligence; Human–computer interaction; Physics; Nonlinear system","score_opus":0.006070463065151852,"score_gpt":0.2424220423818574,"score_spread":0.23635157931670556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603434","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":[0.010370471,0.001497682,0.9854471,0.0009833243,0.0012516865,0.00019357719,0.000061332634,0.00011415032,0.00008065396],"genre_scores_gemma":[0.97431356,0.00014284621,0.025076944,0.000060287854,0.00030651217,0.000023163018,0.000015586362,0.000028876486,0.000032212898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903315,0.000010475202,0.0004288134,0.000101368474,0.0002913673,0.00013485199],"domain_scores_gemma":[0.99927706,0.00018550402,0.00009224223,0.000085047635,0.0002926884,0.0000674797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023642383,0.00013363553,0.00020101528,0.00026667718,0.000035169505,0.00023313268,0.00022267939,0.00007049849,0.0000051161983],"category_scores_gemma":[0.000055161672,0.00012207995,0.00015007796,0.000054081283,0.000011680986,0.0003276814,0.000017419281,0.00013503314,0.0000014694688],"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":[0.00003717056,0.000020909101,0.000013941938,0.000062612904,0.00017204539,0.000011853337,0.000055102024,0.97148865,0.003032734,0.008366529,0.0004404592,0.01629797],"study_design_scores_gemma":[0.0015626168,0.00007618221,0.00004451636,0.00020533436,0.00007160988,0.000037072732,0.000009063825,0.9894297,0.00012978059,0.008050146,0.0002609662,0.00012299289],"about_ca_topic_score_codex":0.0000018395598,"about_ca_topic_score_gemma":0.000006425105,"teacher_disagreement_score":0.9639431,"about_ca_system_score_codex":0.0001230249,"about_ca_system_score_gemma":0.000065511835,"threshold_uncertainty_score":0.49782756},"labels":[],"label_agreement":null},{"id":"W4405603465","doi":"10.2316/j.2025.206-0935","title":"PATENT SEARCH CLASSIFICATION MODEL FOR SERVICE ROBOTS FIELD USING DEEP LEARNING APPROACH, 15-22. SI","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Field (mathematics); Artificial intelligence; Robot; Deep learning; Service (business); Computer science; Machine learning; Engineering; Business; Mathematics","score_opus":0.08773949370482367,"score_gpt":0.30116899895661925,"score_spread":0.21342950525179558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603465","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":[0.08998782,0.00025403392,0.9081484,0.000189623,0.001120659,0.00010246914,0.0000024343249,0.000059018967,0.0001355371],"genre_scores_gemma":[0.9855993,0.00006607864,0.013797735,0.000023420804,0.0004494423,0.0000029321868,0.0000101167525,0.000017915128,0.000033076347],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916404,0.000022419174,0.0003616736,0.000085522275,0.00027782013,0.00008850159],"domain_scores_gemma":[0.99938476,0.00007959558,0.000085144464,0.000038023347,0.0003713666,0.000041110845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035774586,0.00008326187,0.000112482376,0.00023634576,0.000055634675,0.00022867131,0.00007886881,0.00009793902,0.000003540776],"category_scores_gemma":[0.000037948896,0.0000750225,0.000066182656,0.00010534352,0.000004713351,0.00030762237,0.0000136532735,0.00020173972,0.0000017911751],"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":[0.000015716361,0.000008769,0.000026687067,0.000076143486,0.00006692349,0.0000017122966,0.00033941353,0.9522486,0.008200195,0.00089890993,0.00005183905,0.03806514],"study_design_scores_gemma":[0.00024859677,0.000043696426,0.00012769521,0.00016813693,0.00002660626,0.000080603575,0.00013740148,0.9980419,0.0005995846,0.00030865186,0.0001410881,0.00007602699],"about_ca_topic_score_codex":0.000007121677,"about_ca_topic_score_gemma":0.000001305941,"teacher_disagreement_score":0.89561146,"about_ca_system_score_codex":0.00011419176,"about_ca_system_score_gemma":0.000030364126,"threshold_uncertainty_score":0.30593288},"labels":[],"label_agreement":null},{"id":"W4405603561","doi":"10.2316/j.2025.206-1081","title":"A ROBUST MONOCULAR VISUAL SLAM SYSTEM WITH POINT AND LINE FEATURES, 43-55.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Monocular; Artificial intelligence; Line (geometry); Computer vision; Computer science; Point (geometry); Mathematics; Geometry","score_opus":0.008674778666835754,"score_gpt":0.2313545065438045,"score_spread":0.22267972787696874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603561","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":[0.25229266,0.0026111845,0.74161667,0.0013170539,0.0013750792,0.00011917531,0.000011968927,0.00019597421,0.00046026197],"genre_scores_gemma":[0.9941851,0.00020746457,0.005261568,0.000022941244,0.0002702582,0.0000012158855,0.00001722094,0.000013386322,0.000020828636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942046,0.000011898562,0.0002159019,0.000061526516,0.00023627123,0.000053951037],"domain_scores_gemma":[0.9996494,0.00003126507,0.000058319994,0.000022450376,0.00019411539,0.000044456385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013114135,0.00007895069,0.00009300469,0.00017009763,0.000022703718,0.00019398754,0.000041111234,0.000042087235,0.000006022966],"category_scores_gemma":[0.000011829038,0.000062527244,0.000026281537,0.0000548659,0.000013756016,0.00027160504,0.0000097216,0.00012403911,0.0000029828686],"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":[0.00009819909,0.000049319744,0.00031316475,0.00047623506,0.0006820946,0.00037526255,0.0009428199,0.84047437,0.0057368255,0.015004194,0.00090354565,0.13494398],"study_design_scores_gemma":[0.00038766247,0.000087387045,0.0021164345,0.0007107409,0.000045045857,0.00085942674,0.00009937283,0.9941566,0.0010366831,0.00017463644,0.00023929737,0.00008668448],"about_ca_topic_score_codex":0.000006591399,"about_ca_topic_score_gemma":0.0000058778637,"teacher_disagreement_score":0.74189246,"about_ca_system_score_codex":0.00006248763,"about_ca_system_score_gemma":0.00001661191,"threshold_uncertainty_score":0.25497872},"labels":[],"label_agreement":null},{"id":"W4405603623","doi":"10.2316/j.2025.206-1170","title":"ADAPTIVE CONTROL OF A CABLE-DRIVEN SERPENTINE MANIPULATOR BASED ON NEURAL NETWORK OBSERVER, 311-320.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Manipulator (device); Artificial neural network; Observer (physics); Control theory (sociology); Computer science; Control engineering; Robot manipulator; Control (management); Adaptive control; Engineering; Artificial intelligence; Robot; Physics","score_opus":0.015044419453350198,"score_gpt":0.23202594249498526,"score_spread":0.21698152304163507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603623","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":[0.16918993,0.0014219932,0.8196905,0.0015287038,0.0071522007,0.00025079932,0.000042471434,0.00014974781,0.0005736249],"genre_scores_gemma":[0.99653846,0.000021529937,0.002928807,0.00006232194,0.000398064,0.0000013592754,0.000006844973,0.000012936183,0.000029697605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916005,0.000024587931,0.00039070507,0.000059739214,0.00029186465,0.000073045376],"domain_scores_gemma":[0.9995313,0.00008596976,0.0001018985,0.000044786095,0.00019555696,0.00004048646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015803301,0.000084587424,0.000151087,0.00012618498,0.000017243574,0.00008726243,0.00009097149,0.0000397005,0.000034662095],"category_scores_gemma":[0.000017796327,0.000072583156,0.000068379035,0.00006671129,0.000011566177,0.00016515721,0.000006430454,0.00009995573,0.0000035790122],"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":[0.00002541135,0.0000146280545,0.00067623303,0.000033460485,0.00011030964,0.000020076688,0.00005808626,0.99255764,0.00041804198,0.0035841176,0.00048532593,0.0020166584],"study_design_scores_gemma":[0.0005394217,0.00009554842,0.0069125276,0.00029799325,0.000030122153,0.000040095463,0.000018610715,0.9914917,0.000064364576,0.00007874702,0.00036826587,0.000062602056],"about_ca_topic_score_codex":0.000006882488,"about_ca_topic_score_gemma":0.0000047938647,"teacher_disagreement_score":0.82734853,"about_ca_system_score_codex":0.000053180986,"about_ca_system_score_gemma":0.000028926446,"threshold_uncertainty_score":0.29598552},"labels":[],"label_agreement":null},{"id":"W4405603630","doi":"10.2316/j.2025.206-1121","title":"AN ASSIST-AS-NEEDED CONTROL WITH FAULT-TOLERANT REGION FOR SAFE AND EFFECTIVE TRAINING ON END-EFFECTOR UPPER LIMB REHABILITATION ROBOT, 194-202.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Rehabilitation; Robot end effector; Training (meteorology); Physical medicine and rehabilitation; Robot; Control (management); Fault tolerance; Computer science; Medicine; Artificial intelligence; Physical therapy; Distributed computing; Geography","score_opus":0.005648446505454687,"score_gpt":0.24921514160030342,"score_spread":0.24356669509484874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603630","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":[0.47142503,0.00040838632,0.5212237,0.004890262,0.0012522027,0.000587155,0.000028020842,0.0000974143,0.00008780629],"genre_scores_gemma":[0.98199654,0.000058278918,0.017527847,0.000102539314,0.00022494858,0.000024307497,0.000018990811,0.000032937583,0.000013601835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894917,0.000059756683,0.00038661587,0.00016198678,0.00031601085,0.00012648592],"domain_scores_gemma":[0.998378,0.0009812644,0.00012288358,0.000072981326,0.0003536784,0.0000912271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004003443,0.0001665549,0.00023123827,0.00032824854,0.000066457884,0.00024360756,0.00008721981,0.00011100043,0.0000033380727],"category_scores_gemma":[0.00015734357,0.00012895206,0.0000871336,0.00007953079,0.00006411341,0.00034712823,0.0000063118077,0.00021636205,0.0000015840546],"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":[0.00032651002,0.00008260143,0.0002830314,0.00021020231,0.00032132427,0.000021192684,0.0030263865,0.8900421,0.0049640997,0.016306864,0.000102436185,0.08431325],"study_design_scores_gemma":[0.0016998823,0.002524177,0.0146122025,0.00079115,0.00009996103,0.00020385777,0.000508694,0.97558856,0.0003858248,0.002754627,0.00062673754,0.00020430262],"about_ca_topic_score_codex":0.000003059967,"about_ca_topic_score_gemma":0.0000026365715,"teacher_disagreement_score":0.51057154,"about_ca_system_score_codex":0.000123474,"about_ca_system_score_gemma":0.00004331398,"threshold_uncertainty_score":0.52585125},"labels":[],"label_agreement":null},{"id":"W4405603635","doi":"10.2316/j.2025.206-1118","title":"DESIGN AND OPTIMISATION OF THE DAMPING SYSTEM FOR OPTICAL SCANNING EQUIPMENT, 175-183.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Engineering; Mechanical engineering; Automotive engineering","score_opus":0.026616722511358246,"score_gpt":0.2789761601301119,"score_spread":0.2523594376187536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405603635","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":[0.032805566,0.00063428615,0.965504,0.00023711103,0.00063185615,0.00008739724,0.0000010320247,0.000036763748,0.00006199907],"genre_scores_gemma":[0.8713264,0.00008750141,0.12849328,0.0000060116963,0.000072120034,0.0000023685286,8.729833e-7,0.000006109932,0.0000053443337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995693,0.000008935163,0.00020849466,0.000037242226,0.0001316656,0.000044354423],"domain_scores_gemma":[0.9996949,0.00007719824,0.00006932951,0.0000229654,0.00012093978,0.000014653865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032221302,0.000045108194,0.00007275804,0.00009228396,0.000020015168,0.000036780097,0.00005744964,0.0000295415,4.5816313e-7],"category_scores_gemma":[0.00003366806,0.000033430402,0.000026629556,0.000031445375,0.000017361597,0.00015284905,0.0000115083085,0.000055513025,5.2642893e-8],"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":[0.000025709864,0.0000096184485,0.00023942921,0.00025460657,0.00021425913,0.0000030306744,0.00032012918,0.79910916,0.13480148,0.018730508,0.00014385748,0.04614819],"study_design_scores_gemma":[0.00023729415,0.000056667104,0.00069636723,0.0006861343,0.00005390295,0.00007025683,0.00006030384,0.945061,0.05140172,0.0014346634,0.00019058157,0.00005106636],"about_ca_topic_score_codex":1.6156876e-7,"about_ca_topic_score_gemma":8.031015e-8,"teacher_disagreement_score":0.8385208,"about_ca_system_score_codex":0.000059158436,"about_ca_system_score_gemma":0.000014293963,"threshold_uncertainty_score":0.13632523},"labels":[],"label_agreement":null},{"id":"W4406809705","doi":"10.2316/j.2025.206-1119","title":"ROPE-RRT: EFFICIENT FRONT-END PATH PLANNING METHODS IN CLUTTERED MAZE ENVIRONMENTS, 270-278.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Rope; Front (military); Path (computing); Computer science; Motion planning; Front and back ends; Simulation; Aeronautics; Artificial intelligence; Operations research; Engineering; Mechanical engineering; Operating system; Robot; Algorithm","score_opus":0.01569463970983768,"score_gpt":0.32569486095278893,"score_spread":0.31000022124295123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406809705","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017041584,0.00044686222,0.9787197,0.0018802194,0.0015959549,0.000070388276,0.000001919684,0.000018955838,0.00022441204],"genre_scores_gemma":[0.32536638,0.00003459653,0.67420995,0.00021475583,0.00007013104,0.0000014894408,0.0000034090308,0.0000053799545,0.000093897994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984331,0.00015095397,0.000608025,0.00019104182,0.00045464913,0.00016222331],"domain_scores_gemma":[0.99910146,0.00020129315,0.00040821623,0.00014329543,0.000087979206,0.000057748137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009314412,0.00012766007,0.00021056384,0.00046901766,0.000042862706,0.00020442072,0.00061313855,0.00006690814,0.000004434731],"category_scores_gemma":[0.00013732402,0.00011644791,0.000056309673,0.00013554354,0.000031701544,0.00030867825,0.00018858978,0.0002267014,0.0000041551666],"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":[0.000014083562,0.00011912558,0.0053626862,0.000009974613,0.00008825164,0.00013809261,0.001100748,0.91395515,0.0015938601,0.0036679083,0.00026816933,0.07368194],"study_design_scores_gemma":[0.00069382024,0.000044015753,0.10402468,0.00032691454,0.000011700331,0.000082483886,0.000049731323,0.8922727,0.0004394356,0.0013999902,0.0005538229,0.00010069931],"about_ca_topic_score_codex":0.000010245863,"about_ca_topic_score_gemma":2.958059e-7,"teacher_disagreement_score":0.3083248,"about_ca_system_score_codex":0.00018405398,"about_ca_system_score_gemma":0.00007342378,"threshold_uncertainty_score":0.4748608},"labels":[],"label_agreement":null},{"id":"W4406809808","doi":"10.2316/j.2025.206-1136","title":"A NOVEL PATH PLANNING SCHEME BASED ON IMPROVED INFORMED RRT*-CONNECT FOR INDUSTRIAL ROBOTS, 279-288.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Scheme (mathematics); Robot; Motion planning; Path (computing); Computer science; Artificial intelligence; Computer network; Mathematics","score_opus":0.03446222297544785,"score_gpt":0.30905436580535667,"score_spread":0.27459214282990885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406809808","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035434624,0.000035326688,0.9897004,0.0039417353,0.0023817765,0.00017593417,0.000008998413,0.00004537914,0.00016699111],"genre_scores_gemma":[0.23043272,0.000005299247,0.76823306,0.00088851317,0.0003500101,0.000008189099,0.000018056897,0.000009411719,0.000054737004],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861765,0.000025302725,0.0005845306,0.00017614375,0.00042139806,0.00017495353],"domain_scores_gemma":[0.9981561,0.00055459025,0.000566308,0.00014221607,0.00051014294,0.00007067595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056224904,0.0001496295,0.00022024801,0.00049836084,0.00009268408,0.00033086922,0.0006014643,0.000113897484,0.0000011837906],"category_scores_gemma":[0.00081930455,0.0001334144,0.00009773458,0.0001687783,0.000024024714,0.00049291627,0.00007813448,0.00022648576,8.2244696e-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":[0.0001721593,0.00020127834,0.001166077,0.0000340167,0.00021398955,0.000021896487,0.00027430404,0.9156942,0.0027587381,0.026105037,0.0019268944,0.051431425],"study_design_scores_gemma":[0.0028954109,0.00025391745,0.002688009,0.0005618439,0.00001725665,0.000035860194,0.000021550028,0.9914801,0.00050822494,0.00092648313,0.0004814067,0.00012993233],"about_ca_topic_score_codex":0.0000051678758,"about_ca_topic_score_gemma":2.31025e-7,"teacher_disagreement_score":0.22688927,"about_ca_system_score_codex":0.0001478217,"about_ca_system_score_gemma":0.00042758568,"threshold_uncertainty_score":0.5440482},"labels":[],"label_agreement":null},{"id":"W4411569939","doi":"10.2316/j.2025.206-1203","title":"CONVEYOR BELT DAMAGE DETECTION UNDER MULTI-SOURCE ENVIRONMENTAL INTERFERENCES BASED ON ENHANCED FEATURE EXTRACTION NETWORK, 361-373.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Belt Conveyor Systems Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Feature extraction; Conveyor belt; Computer science; Feature (linguistics); Pattern recognition (psychology); Belt conveyor; Environmental science; Artificial intelligence; Chemistry; Engineering; Chromatography; Mechanical engineering","score_opus":0.006447886539617744,"score_gpt":0.22775421375077373,"score_spread":0.22130632721115598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411569939","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":[0.18513447,0.00014218499,0.81165934,0.00021416161,0.0025675718,0.00007655992,0.0000031216132,0.000064179294,0.00013838462],"genre_scores_gemma":[0.9954339,0.00005491561,0.004067885,0.000063026455,0.00021789971,0.0000032313485,0.000011094506,0.000016072392,0.00013196349],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991889,0.000031847863,0.00032762822,0.00009840243,0.00024354232,0.000109683104],"domain_scores_gemma":[0.9995677,0.00009508201,0.00015713865,0.00007077362,0.00006853309,0.000040781084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017894589,0.00013899225,0.00014892741,0.00025314046,0.000043418884,0.00009861702,0.00013023258,0.000102397185,0.000010553374],"category_scores_gemma":[0.00002434562,0.00013630942,0.000051200263,0.00008269208,0.00001894568,0.00024062778,0.000016177992,0.00026421098,0.0000030400504],"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":[0.000021122085,0.000024573166,0.00017840482,0.000021814905,0.00009671006,0.000003068103,0.000046564375,0.9309603,0.047343083,0.00008858805,0.000075990174,0.021139808],"study_design_scores_gemma":[0.0006442485,0.00005781332,0.01956371,0.00031399057,0.000026756046,0.000020804406,0.000075170516,0.9641491,0.014664662,0.000050952294,0.00032088713,0.0001118886],"about_ca_topic_score_codex":0.000003537337,"about_ca_topic_score_gemma":0.00001321795,"teacher_disagreement_score":0.81029946,"about_ca_system_score_codex":0.00021611588,"about_ca_system_score_gemma":0.000015003734,"threshold_uncertainty_score":0.55585366},"labels":[],"label_agreement":null},{"id":"W4411569951","doi":"10.2316/j.2025.206-1258","title":"TIME-OPTIMAL TRAJECTORY PLANNING FOR TOOL-CHANGING ROBOTS BASED ON THE HYBRID SEARCH ALGORITHM OF SPARROW-OSPREY, 415-424.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Sparrow; Trajectory; Robot; Computer science; Algorithm; Mathematical optimization; Artificial intelligence; Mathematics; Biology; Ecology; Physics","score_opus":0.017827548967886638,"score_gpt":0.28184239682058787,"score_spread":0.26401484785270124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411569951","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016449206,0.00008218023,0.9795947,0.002726319,0.000864162,0.00014391598,0.000009991185,0.000026381913,0.00010311403],"genre_scores_gemma":[0.36913934,0.0000065273102,0.63020134,0.0003295477,0.00017554154,0.000004686321,0.00000875922,0.000009965695,0.00012431276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985263,0.0000770119,0.00047301955,0.00015928352,0.0005836201,0.00018077523],"domain_scores_gemma":[0.99813306,0.0007791483,0.00036025254,0.00015536476,0.00053328247,0.00003887639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011323523,0.00012441906,0.00020031781,0.0005093594,0.00011281996,0.00016560096,0.00064599176,0.000043386688,0.0000036806214],"category_scores_gemma":[0.00016576778,0.00009748055,0.00010775482,0.00018444154,0.00005106983,0.00027495844,0.00008812655,0.00017759229,0.0000014994653],"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":[0.000021940512,0.000045988738,0.00011592823,0.000014947446,0.0000865165,0.000019485838,0.00030625568,0.9649589,0.00049793324,0.0027531667,0.0003712752,0.03080763],"study_design_scores_gemma":[0.0005702579,0.00015782674,0.0016064257,0.00043363587,0.000019013056,0.00004090117,0.000048676837,0.99369055,0.002746685,0.00054971816,0.000049411603,0.00008690999],"about_ca_topic_score_codex":0.0000019463696,"about_ca_topic_score_gemma":3.299741e-8,"teacher_disagreement_score":0.35269013,"about_ca_system_score_codex":0.00008072014,"about_ca_system_score_gemma":0.00017606778,"threshold_uncertainty_score":0.39751413},"labels":[],"label_agreement":null},{"id":"W4411569957","doi":"10.2316/j.2025.206-1208","title":"JERK-CONTINUOUS ONLINE TRAJECTORY PLANNING AND FEEDFORWARD CONTROL FOR FLEXIBLE JOINT ROBOTS, 1-8.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Feed forward; Jerk; Trajectory; Robot; Joint (building); Computer science; Control theory (sociology); Control (management); Control engineering; Engineering; Artificial intelligence; Physics; Structural engineering","score_opus":0.01107979786662072,"score_gpt":0.25317398256363277,"score_spread":0.24209418469701205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411569957","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":[0.023195341,0.0008012498,0.9739206,0.0006739253,0.0011313456,0.00010135273,0.00001638386,0.000045777237,0.000114068236],"genre_scores_gemma":[0.7899453,0.00022136097,0.20919983,0.00018716748,0.00025462787,0.000003149158,0.00001848859,0.000017727027,0.00015233122],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992928,0.000008659394,0.0003851307,0.00007049806,0.0001465464,0.000096350916],"domain_scores_gemma":[0.999507,0.00008148083,0.00012720432,0.00004121056,0.00019891126,0.000044194996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001936449,0.00009718337,0.00020068344,0.00021495346,0.000037551043,0.00009276937,0.00008323793,0.000061005554,0.0000026980345],"category_scores_gemma":[0.000055328164,0.000089419824,0.000056628807,0.000032589498,0.00001534378,0.00014709834,0.000014064641,0.000104682484,2.0533834e-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":[0.000024541634,0.000022886046,0.0002552799,0.000045940116,0.00017140442,0.000005106143,0.00010473601,0.9686738,0.0018035885,0.0128546525,0.0002803521,0.015757663],"study_design_scores_gemma":[0.0013021915,0.00007188883,0.005106002,0.00023165476,0.000060495917,0.000049972914,0.0001117633,0.98610824,0.00020089725,0.0064624553,0.00020374512,0.00009066954],"about_ca_topic_score_codex":0.0000018280576,"about_ca_topic_score_gemma":0.0000016903116,"teacher_disagreement_score":0.76675,"about_ca_system_score_codex":0.000050638748,"about_ca_system_score_gemma":0.000026860274,"threshold_uncertainty_score":0.36464345},"labels":[],"label_agreement":null},{"id":"W4411570043","doi":"10.2316/j.2025.206-1227","title":"IMPROVED DEEP LEARNING-GUIDED SPARSE ICP FOR POINT CLOUDS REGISTRATION IN RAIL WEAR CALCULATION, 486-502.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Welding Techniques and Residual Stresses","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Point cloud; Artificial intelligence; Point (geometry); Computer science; Geology; Mathematics; Geometry","score_opus":0.011277911106257282,"score_gpt":0.2730104529884471,"score_spread":0.26173254188218986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411570043","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":[0.2031899,0.0003679438,0.79276633,0.002144385,0.00084211,0.00018943739,0.0000033210813,0.00009027231,0.0004062951],"genre_scores_gemma":[0.9805229,0.00032130774,0.018865189,0.000030275403,0.00012675003,0.000004376784,0.000015076891,0.000009115906,0.00010504647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925196,0.000016944621,0.0004413858,0.00006809314,0.00014051654,0.00008110691],"domain_scores_gemma":[0.9994474,0.00006901305,0.00016231845,0.00004286131,0.000254225,0.000024194816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027103562,0.00008109472,0.00012255422,0.00021205151,0.000033404605,0.000089338144,0.000094851035,0.000073645046,0.000004039229],"category_scores_gemma":[0.00016574707,0.00007567905,0.000051141753,0.00008179045,0.0000150107035,0.00017609552,0.000015649486,0.00012568384,2.546826e-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":[0.000035321034,0.000034251647,0.0018406209,0.00006779886,0.00008667633,0.00000551778,0.00017366403,0.97320604,0.0061116666,0.005265519,0.001392821,0.011780123],"study_design_scores_gemma":[0.000868387,0.00007323647,0.013847438,0.00027584116,0.000024075134,0.000026885506,0.00004739357,0.9695987,0.0076199663,0.005662297,0.0018460487,0.000109749184],"about_ca_topic_score_codex":0.000016491294,"about_ca_topic_score_gemma":0.00002351766,"teacher_disagreement_score":0.77733296,"about_ca_system_score_codex":0.00009913852,"about_ca_system_score_gemma":0.00002675357,"threshold_uncertainty_score":0.3086102},"labels":[],"label_agreement":null},{"id":"W4411570066","doi":"10.2316/j.2025.206-1139","title":"MULTI-AGV PATH PLANNING FOR AUTOMATED WAREHOUSE SYSTEM BASED ON IMPROVED ANT COLONY OPTIMISATION AND NODE VECTOR TIME WINDOW, 334-349.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Ant colony optimization algorithms; Node (physics); Window (computing); Path (computing); Computer science; Ant colony; Warehouse; Automated guided vehicle; Real-time computing; Data mining; Engineering; Artificial intelligence; Computer network; Operating system; Business","score_opus":0.008520410956728128,"score_gpt":0.25102939073121167,"score_spread":0.24250897977448355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411570066","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":[0.019269485,0.00007858748,0.97923934,0.00021950521,0.00068486965,0.00018198462,0.0000288083,0.00025241394,0.00004497738],"genre_scores_gemma":[0.8368559,0.000020442798,0.16293083,0.000042823096,0.00006588346,0.000005670399,0.000039910843,0.000015778138,0.000022778753],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992955,0.00001722368,0.00034886313,0.000100081554,0.00014112209,0.00009720846],"domain_scores_gemma":[0.99930084,0.00016974629,0.00019263534,0.000057045723,0.00023960994,0.000040132083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016848255,0.00012212347,0.0001633529,0.00023441057,0.00006769061,0.00010115917,0.000080946236,0.000074021315,0.0000010792178],"category_scores_gemma":[0.00012450754,0.00011487723,0.00003534184,0.000047691537,0.00001709504,0.0001472726,0.000012571328,0.00009375936,5.069676e-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":[0.00006172394,0.000026787802,0.00008777989,0.00009492887,0.00006442177,0.000004496142,0.000075867436,0.995667,0.0026708934,0.00020292289,0.0001424963,0.0009006847],"study_design_scores_gemma":[0.0013913359,0.00008102989,0.0040437104,0.0004185739,0.000035580077,0.000010970156,0.000032634005,0.9924454,0.0013356865,0.000040094357,0.00006374337,0.00010122999],"about_ca_topic_score_codex":0.0000019754339,"about_ca_topic_score_gemma":2.706821e-7,"teacher_disagreement_score":0.8175864,"about_ca_system_score_codex":0.00017316536,"about_ca_system_score_gemma":0.000030807936,"threshold_uncertainty_score":0.46845576},"labels":[],"label_agreement":null},{"id":"W4411570083","doi":"10.2316/j.2025.206-1151","title":"QUICK-PICK CNN: A NOVEL ALGORITHM FOR QUICKER DUAL-ARM GRASP LOCALISATION IN A CLUTTERED ENVIRONMENT, 1-9.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"GRASP; Computer science; Dual (grammatical number); Artificial intelligence; Computer vision; Algorithm; Art","score_opus":0.014114521199996427,"score_gpt":0.2545403835725694,"score_spread":0.240425862372573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411570083","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":[0.017291956,0.00013252422,0.98053384,0.001028465,0.0007464058,0.00011207485,0.0000021276892,0.000024136021,0.00012845041],"genre_scores_gemma":[0.95138544,0.00011029822,0.04808174,0.00013748147,0.0001553124,0.000005364104,0.00002530697,0.000012349531,0.00008669778],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991717,0.000015405236,0.0004489657,0.000078828416,0.000191615,0.00009350045],"domain_scores_gemma":[0.9996116,0.00006996295,0.0001465265,0.00004534755,0.00009677899,0.000029785817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023340891,0.00009109413,0.00013322607,0.00033859446,0.000029187067,0.00007532584,0.00007964179,0.00006163185,0.000017265093],"category_scores_gemma":[0.000040321556,0.000093040784,0.000051092655,0.00007503675,0.000015947977,0.00024199122,0.00001682248,0.000121618315,0.0000023243228],"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":[0.000011300677,0.00005182547,0.00087198947,0.000020451354,0.00007034844,0.0000030679598,0.0002461353,0.94722617,0.0011197566,0.002513248,0.0002072733,0.04765844],"study_design_scores_gemma":[0.0012291753,0.000032616164,0.020676179,0.000117149146,0.000016529839,0.000018592322,0.00008423163,0.97501487,0.00019322493,0.0010173178,0.0015185757,0.0000815325],"about_ca_topic_score_codex":0.0000068863924,"about_ca_topic_score_gemma":0.0000047618832,"teacher_disagreement_score":0.9340935,"about_ca_system_score_codex":0.00014457558,"about_ca_system_score_gemma":0.00002151503,"threshold_uncertainty_score":0.37940928},"labels":[],"label_agreement":null},{"id":"W4412512946","doi":"10.2316/j.2025.206-1221","title":"MODEL OF A HUMAN WRIST FOR ESTIMATING FORCE FEEDBACK IN HUMAN–ROBOT INTERACTIONS, 1-17.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wrist; Robot; Human–robot interaction; Computer science; Human–computer interaction; Psychology; Physical medicine and rehabilitation; Control theory (sociology); Artificial intelligence; Medicine; Control (management); Anatomy","score_opus":0.029532621395074208,"score_gpt":0.32135341982670795,"score_spread":0.2918207984316337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412512946","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":[0.102095425,0.000048632548,0.8963133,0.0002722672,0.00040242975,0.00007647081,0.0000011826579,0.000020664904,0.0007696382],"genre_scores_gemma":[0.9434396,0.000007621593,0.056177408,0.00002552636,0.000068222675,0.0000025037248,0.000011674916,0.000008592273,0.00025885395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991808,0.000011348568,0.0005486292,0.000056564535,0.00013482457,0.00006783364],"domain_scores_gemma":[0.99942833,0.000068987596,0.00022136261,0.000042200743,0.00022003606,0.00001907469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019801686,0.00007387935,0.00014890813,0.0003724074,0.000043944503,0.000054555967,0.00010919875,0.000036087964,0.000008489413],"category_scores_gemma":[0.00006151457,0.00007785943,0.000056921588,0.000072639494,0.000014043818,0.00024422692,0.000017620452,0.00012809402,2.703567e-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":[0.0000072731345,0.000022689048,0.0007290949,0.000050799077,0.000046779875,5.7510096e-7,0.0001814712,0.97302693,0.017826483,0.0056871525,0.00027990216,0.002140842],"study_design_scores_gemma":[0.000598074,0.000022069296,0.003647125,0.00036182528,0.000015700129,0.0000058473443,0.00007066154,0.99070454,0.00060712174,0.0038852228,0.000023215729,0.000058620277],"about_ca_topic_score_codex":0.0000044470216,"about_ca_topic_score_gemma":0.000014528009,"teacher_disagreement_score":0.8413442,"about_ca_system_score_codex":0.00008599277,"about_ca_system_score_gemma":0.000017697803,"threshold_uncertainty_score":0.31750154},"labels":[],"label_agreement":null},{"id":"W4412513184","doi":"10.2316/j.2025.206-1233","title":"MULTIMODAL INFORMATION PROCESSING AND BEHAVIOUR GENERATION OF HUMANOID ROBOTS BASED ON PALM 2 MODEL AND MULTIMODAL TRANSFORMER ARCHITECTURE, 648-664. SI","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanoid robot; Transformer; Architecture; Computer science; Robot; Human–computer interaction; Multimodal therapy; Artificial intelligence; Computer architecture; Engineering; Psychology; Electrical engineering; Art; Visual arts","score_opus":0.009941634760405917,"score_gpt":0.2438105774906332,"score_spread":0.2338689427302273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412513184","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":[0.4250384,0.00015192799,0.5739414,0.00027820826,0.0002710101,0.00012270047,0.000013960346,0.000028687877,0.00015366919],"genre_scores_gemma":[0.97957486,0.000076571654,0.020190075,0.000057307007,0.00005249051,0.0000027179374,0.000028155422,0.000009881907,0.000007920797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998934,0.000018374712,0.000581122,0.000079472666,0.00029313576,0.00009393044],"domain_scores_gemma":[0.9993697,0.00003278211,0.00021789655,0.000049922975,0.0002842906,0.000045419194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019679891,0.00013925447,0.00019601411,0.00042534032,0.00006164874,0.00014762889,0.00007999272,0.00009113737,0.0000012765626],"category_scores_gemma":[0.000024613415,0.00012467346,0.000041337742,0.000071444,0.000033155527,0.00042629702,0.000009596738,0.00014230591,1.9165196e-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":[0.000018263489,0.000028763174,0.00068876817,0.0001170727,0.000038381917,0.000001173564,0.00036157438,0.9547419,0.008059428,0.00043786032,0.000022925524,0.03548389],"study_design_scores_gemma":[0.0009803146,0.000057034995,0.011165214,0.00032519328,0.000038225193,0.00001782066,0.000038279984,0.9847064,0.0023354313,0.00022049573,0.0000113978185,0.00010421587],"about_ca_topic_score_codex":0.0000070734222,"about_ca_topic_score_gemma":0.0000042966158,"teacher_disagreement_score":0.55453646,"about_ca_system_score_codex":0.000045850946,"about_ca_system_score_gemma":0.00004909934,"threshold_uncertainty_score":0.5084036},"labels":[],"label_agreement":null},{"id":"W4412513569","doi":"10.2316/j.2025.206-1185","title":"A NOVEL OBJECT DETECTION FRAMEWORK BASED ON INCREMENTAL LEARNING IN AN INDUSTRIAL SAFETY INSPECTION SYSTEM, 619-631.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Systems engineering; Risk analysis (engineering); Engineering; Business","score_opus":0.012817754996998196,"score_gpt":0.2759819218993399,"score_spread":0.2631641669023417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412513569","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":[0.13189183,0.000009549387,0.8650764,0.0011248615,0.0014892215,0.000057482575,6.7219855e-7,0.000091565715,0.00025838107],"genre_scores_gemma":[0.98444635,0.000004295147,0.015215814,0.00010711627,0.00020834901,0.0000012388427,0.0000034123696,0.000004199018,0.000009241168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988539,0.00013115608,0.00040567623,0.0001394456,0.00038207578,0.000087737826],"domain_scores_gemma":[0.9992354,0.00014112459,0.00032751253,0.00007761061,0.00018205607,0.000036280984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073674624,0.00008877403,0.0001276176,0.0006063889,0.00011509231,0.00024352335,0.00024926357,0.00009606233,0.0000012635686],"category_scores_gemma":[0.0002590718,0.000083802835,0.000042580727,0.0002659253,0.000012840858,0.00042382075,0.00004386684,0.00040392022,0.0000011237412],"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":[0.0001421472,0.00017285773,0.010006599,0.000013717356,0.00003389642,0.000011199189,0.00028258318,0.8512761,0.0015224288,0.017745337,0.00001230932,0.118780814],"study_design_scores_gemma":[0.0011025249,0.00025848974,0.041545965,0.00046489306,0.0000069735797,0.00003308001,0.00008314222,0.95578283,0.00034340724,0.00022604816,0.00008799879,0.000064643646],"about_ca_topic_score_codex":0.000062254905,"about_ca_topic_score_gemma":0.000022800883,"teacher_disagreement_score":0.8525545,"about_ca_system_score_codex":0.0003124749,"about_ca_system_score_gemma":0.00009149418,"threshold_uncertainty_score":0.34173805},"labels":[],"label_agreement":null},{"id":"W4413472919","doi":"10.2316/j.2025.206-1237","title":"HUMAN FOLLOWING TASK BASED ON MULTI-SENSOR FUSION PLANNING ALGORITHM","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Task (project management); Computer science; Sensor fusion; Fusion; Artificial intelligence; Algorithm; Real-time computing; Engineering; Systems engineering","score_opus":0.013126693652630595,"score_gpt":0.28114410078775937,"score_spread":0.2680174071351288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413472919","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":[0.09646104,0.00024340914,0.89848256,0.0004632139,0.0034020182,0.000094010815,0.000006328506,0.00011776764,0.0007296582],"genre_scores_gemma":[0.9699992,0.000011648788,0.029684613,0.00008529381,0.00012599077,0.0000010514783,0.000009966532,0.000013761457,0.000068458634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905986,0.000022430111,0.00043450866,0.000078949284,0.00030444493,0.00009980574],"domain_scores_gemma":[0.9995647,0.000049857495,0.00013934575,0.00006514031,0.00014079383,0.000040159648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022085184,0.00011385119,0.00016797708,0.00038449583,0.00007187209,0.00013647512,0.00014130474,0.000068469075,0.0000034489613],"category_scores_gemma":[0.00002888172,0.00010387779,0.00008979463,0.00009019535,0.000009827364,0.0001249509,0.000016177946,0.00014551252,0.0000022441911],"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":[0.0000026897724,0.00003642154,0.0005900253,0.000019364588,0.00010649152,0.00004844184,0.0000690767,0.98224586,0.0067693465,0.00032590685,0.00029114343,0.009495252],"study_design_scores_gemma":[0.0008182992,0.00003816993,0.0073805964,0.00067689054,0.000024636385,0.000012627384,0.000049987844,0.9898619,0.0006294174,0.000112478796,0.000301984,0.000093007635],"about_ca_topic_score_codex":0.0000026957607,"about_ca_topic_score_gemma":3.896742e-7,"teacher_disagreement_score":0.8735382,"about_ca_system_score_codex":0.00008681324,"about_ca_system_score_gemma":0.000019707133,"threshold_uncertainty_score":0.42360133},"labels":[],"label_agreement":null},{"id":"W4413472929","doi":"10.2316/j.2025.206-1224","title":"ANGLE ERROR OBSERVER BASED-ADAPTIVE TRACKING CONTROL OF WHEELED MOBILE ROBOT WITH UNCERTAINTIES","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Observer (physics); Tracking (education); Mobile robot; Computer science; Control theory (sociology); Tracking error; Artificial intelligence; Computer vision; Robot; Control (management); Control engineering; Engineering; Psychology; Physics","score_opus":0.007144598402626992,"score_gpt":0.22635161369511758,"score_spread":0.2192070152924906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413472929","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":[0.14481348,0.0007764347,0.85316247,0.00037570685,0.00050958176,0.00012844404,0.00001228372,0.000030841333,0.00019073646],"genre_scores_gemma":[0.99219066,0.000042320375,0.0076311436,0.00004289621,0.000049402297,0.000004411179,0.0000041243043,0.000008997318,0.00002601887],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999226,0.00001806922,0.00036370655,0.00006416927,0.00024400098,0.00008408715],"domain_scores_gemma":[0.999068,0.000118849246,0.00018881784,0.000057520116,0.00053691777,0.000029901765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015182265,0.000101300524,0.00021374153,0.00021105871,0.00002331512,0.000050093353,0.00013596671,0.000045725432,0.000008363487],"category_scores_gemma":[0.000026250476,0.000083616775,0.000069126996,0.00007990618,0.0000339328,0.0002308785,0.000010965072,0.000104917075,3.1461033e-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":[0.00010061474,0.000041381754,0.0017632907,0.000029742816,0.00024143502,0.000007739662,0.000065738335,0.9797481,0.0016331543,0.0017272948,0.00002988713,0.014611654],"study_design_scores_gemma":[0.0017389482,0.00015027913,0.016075363,0.00031003272,0.00006792557,0.00001202738,0.00010462165,0.9803877,0.0004708989,0.000532893,0.0000679467,0.00008136663],"about_ca_topic_score_codex":0.000008964699,"about_ca_topic_score_gemma":0.00002245365,"teacher_disagreement_score":0.8473772,"about_ca_system_score_codex":0.00007087231,"about_ca_system_score_gemma":0.00005721615,"threshold_uncertainty_score":0.3409793},"labels":[],"label_agreement":null},{"id":"W4413472943","doi":"10.2316/j.2025.206-1217","title":"FIXED-TIME BIPARTITE CONSENSUS UNDER DYNAMIC EVENT-TRIGGERED MECHANISM FOR MULTI-AGENT SYSTEMS, 584-592.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bipartite graph; Mechanism (biology); Computer science; Multi-agent system; Distributed computing; Event (particle physics); Consensus; Theoretical computer science; Artificial intelligence; Physics","score_opus":0.017352924249189557,"score_gpt":0.3019631493749063,"score_spread":0.28461022512571676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413472943","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":[0.0076693753,0.00039851802,0.98579925,0.003245294,0.0025984845,0.00018478015,0.0000369452,0.00003083901,0.000036532623],"genre_scores_gemma":[0.95691925,0.000051367602,0.04197282,0.00020317276,0.00007116465,0.000007174823,0.000014295851,0.000006252171,0.00075448205],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872833,0.000052409672,0.00062498875,0.0001484987,0.00031905583,0.0001267277],"domain_scores_gemma":[0.99825937,0.00010215289,0.000509113,0.00011717755,0.0009559872,0.000056196153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040159037,0.00011063272,0.00021098535,0.0002146631,0.00008071157,0.0003423982,0.00038682562,0.00006531641,0.0000015195544],"category_scores_gemma":[0.00007813384,0.00009686362,0.000092904025,0.00011902476,0.000018090459,0.00022110448,0.000059596838,0.0000791399,0.000005370302],"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":[0.00004149161,0.00023842482,0.000093066206,0.000103997125,0.00055467145,0.0000345076,0.00019785583,0.2126467,0.0070583564,0.7656687,0.0029300821,0.010432145],"study_design_scores_gemma":[0.0010857173,0.000047348836,0.0006241868,0.000300764,0.00002314565,0.0000697973,0.00004108715,0.9913577,0.00020727474,0.005422256,0.00072755973,0.00009319382],"about_ca_topic_score_codex":0.000008098647,"about_ca_topic_score_gemma":0.0000029881485,"teacher_disagreement_score":0.9492499,"about_ca_system_score_codex":0.00013063774,"about_ca_system_score_gemma":0.00011724922,"threshold_uncertainty_score":0.39499837},"labels":[],"label_agreement":null},{"id":"W4413472946","doi":"10.2316/j.2025.206-1262","title":"RLH-MAPPING: REAL-TIME DENSE MAPPING FOR ROBOTS USING LOW-LIGHT FIELD AND HYBRID REPRESENTATIONS","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Field (mathematics); Computer science; Light field; Artificial intelligence; Real-time computing; Computer vision; Mathematics","score_opus":0.012039049802191943,"score_gpt":0.2627601264439154,"score_spread":0.25072107664172344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413472946","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":[0.15184502,0.0001365547,0.8454104,0.0014197546,0.0006971727,0.000116763695,0.0000050958843,0.000035232675,0.00033401724],"genre_scores_gemma":[0.93235165,0.0004322698,0.06667279,0.00013435536,0.00022098632,0.00000246668,0.000023984523,0.00001895928,0.00014254263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916863,0.000018421317,0.00044718126,0.00009630365,0.00016974156,0.00009970783],"domain_scores_gemma":[0.9991942,0.0001767156,0.00015575992,0.00006525396,0.00036279374,0.000045263623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017121926,0.000100985846,0.00015839977,0.00034531762,0.00007875598,0.00014787381,0.000087871245,0.000053118827,0.000005525087],"category_scores_gemma":[0.0001350497,0.00010338726,0.000054799504,0.00009821666,0.000015568894,0.00021786816,0.000022875241,0.00007798389,5.639952e-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":[0.000012464492,0.00001878889,0.0006055437,0.000067171604,0.00014313178,0.000009233828,0.0001644381,0.9684172,0.02194321,0.0036926812,0.0009692342,0.0039568725],"study_design_scores_gemma":[0.00052078976,0.000019518604,0.0015776138,0.00030760656,0.000037583548,0.00005600123,0.00006928698,0.99169785,0.0032702251,0.0020030108,0.00034242685,0.00009809912],"about_ca_topic_score_codex":0.000007473956,"about_ca_topic_score_gemma":0.0000013035396,"teacher_disagreement_score":0.7805066,"about_ca_system_score_codex":0.000070083996,"about_ca_system_score_gemma":0.000034497196,"threshold_uncertainty_score":0.42160103},"labels":[],"label_agreement":null},{"id":"W4416371747","doi":"10.2316/j.2026.206-1175","title":"OPTIMISATION AND IMPLEMENTATION OF A CONTROLLER PID TUNING USING CORONA VIRUS SEARCH OPTIMISER ALGORITHM. 29-40","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Extremum Seeking Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); PID controller; Controller (irrigation); Control system; Process control","score_opus":0.013455552586427845,"score_gpt":0.2939110600464108,"score_spread":0.280455507459983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371747","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":[0.26100656,0.00055887277,0.7374461,0.00019222905,0.0005465123,0.00012503983,0.000009317505,0.000019626883,0.00009567226],"genre_scores_gemma":[0.96939844,0.00017421781,0.030276028,0.000021581875,0.000100515004,0.0000012042411,0.000005669434,0.00000989913,0.000012465069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900466,0.000037652742,0.0005176636,0.00006957372,0.00028432388,0.0000861474],"domain_scores_gemma":[0.99924046,0.000088704175,0.0002139507,0.000039912065,0.0003840796,0.000032876178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036712462,0.00008980567,0.00018971032,0.000312595,0.00003603203,0.000088057815,0.000086780936,0.00004770657,0.000008056832],"category_scores_gemma":[0.000022887063,0.000089259476,0.000040414794,0.00007459288,0.000022199123,0.00029147574,0.000024176528,0.000095723226,2.3264091e-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":[0.000038578608,0.000022149274,0.0020402938,0.00006780522,0.0004248042,0.0000051666602,0.0006494781,0.69881016,0.1854822,0.0010265983,0.000047502628,0.11138524],"study_design_scores_gemma":[0.0014656362,0.00003351133,0.0072709396,0.00019141477,0.00005145073,0.0000393601,0.00027327676,0.98860383,0.0017379517,0.00021766087,0.00004829166,0.00006665428],"about_ca_topic_score_codex":0.000059458805,"about_ca_topic_score_gemma":0.0000072110706,"teacher_disagreement_score":0.70839185,"about_ca_system_score_codex":0.00012198883,"about_ca_system_score_gemma":0.000041541585,"threshold_uncertainty_score":0.36398956},"labels":[],"label_agreement":null},{"id":"W4416371749","doi":"10.2316/j.2026.206-1167","title":"THE PREDICTION OF THE WIND AND PHOTOVOLTAIC OUTPUT COEFFICIENTS OF ORDOS ZERO-CARBON INDUSTRIAL PARK BASED ON NEURAL NETWORKS. 11-18","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Surface Treatment and Coatings","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Photovoltaic system; Industrial park; Artificial neural network; Wind speed; Wind power","score_opus":0.013803718563945194,"score_gpt":0.22306517235000992,"score_spread":0.20926145378606473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371749","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":[0.99047434,0.00009850946,0.007799033,0.00019779486,0.0012359576,0.00008925551,0.0000050997664,0.000008433068,0.000091585054],"genre_scores_gemma":[0.99979705,0.000036023677,0.00007842045,0.0000145121485,0.000049336824,6.161565e-7,0.0000020105208,0.000004278716,0.000017774406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935377,0.000027445754,0.000291847,0.00004094682,0.00023405218,0.0000519504],"domain_scores_gemma":[0.99943864,0.00016669463,0.000194956,0.000050579194,0.00013517601,0.000013925758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015497088,0.00006429095,0.00009109408,0.00007271361,0.00003853587,0.000032965017,0.00009535618,0.00004267152,0.0000011624398],"category_scores_gemma":[0.00006403084,0.00004039391,0.000037986832,0.00008979193,0.000037141104,0.000046833167,0.00001654532,0.00009320381,2.2166095e-8],"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":[0.00004307931,0.00002301553,0.07483448,0.000006123342,0.00006516514,4.190477e-7,0.000045113415,0.9165061,0.00064157177,0.000073118914,0.000094786934,0.0076670083],"study_design_scores_gemma":[0.00076647766,0.000056002835,0.067951486,0.00018577225,0.00003578351,0.000002179692,0.000027391117,0.92934185,0.0014899563,0.00008973264,0.000029458302,0.000023888286],"about_ca_topic_score_codex":0.0000076331535,"about_ca_topic_score_gemma":0.0000021478902,"teacher_disagreement_score":0.012835755,"about_ca_system_score_codex":0.000034661694,"about_ca_system_score_gemma":0.00001903771,"threshold_uncertainty_score":0.16472158},"labels":[],"label_agreement":null},{"id":"W4416371751","doi":"10.2316/j.2026.206-1171","title":"IMPROVEMENT OF PATH OPTIMISATION METHOD BASED ON D*LITE ALGORITHM. 19-28","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Cybersecurity and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Stability (learning theory); Control theory (sociology); Trajectory; Minification","score_opus":0.009123758992059142,"score_gpt":0.28287198446387135,"score_spread":0.2737482254718122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371751","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":[0.0014779039,0.000030454401,0.9936204,0.0030598901,0.00091973343,0.00007450094,0.0000050362305,0.000013240764,0.00079883385],"genre_scores_gemma":[0.5522317,0.000038125712,0.44678158,0.0007993889,0.00007443311,0.0000019488616,0.00000837251,0.0000026379544,0.00006182456],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987877,0.000040765237,0.000574127,0.00007541166,0.00046382836,0.0000581398],"domain_scores_gemma":[0.99857956,0.00012440825,0.00058993604,0.00010133875,0.000568655,0.000036098896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007239119,0.00006848773,0.00012895126,0.0003636881,0.000036850688,0.00013245553,0.00030212567,0.000039985138,0.0000050990675],"category_scores_gemma":[0.0000747883,0.00005972334,0.00006585429,0.00014119409,0.000013425567,0.00054983934,0.00004528037,0.00007902995,0.0000012333813],"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":[0.000025672352,0.00015001447,0.00013092233,0.00005245473,0.00010851007,0.0000045180172,0.001062845,0.27174246,0.0010521834,0.1320747,0.00086782937,0.5927279],"study_design_scores_gemma":[0.00065384875,0.00012772801,0.0009700209,0.00017178897,0.000008111311,0.000010663755,0.00007202356,0.9915534,0.0023460821,0.0025942775,0.001441039,0.000050984487],"about_ca_topic_score_codex":0.000011328111,"about_ca_topic_score_gemma":4.0604985e-7,"teacher_disagreement_score":0.71981096,"about_ca_system_score_codex":0.00008170559,"about_ca_system_score_gemma":0.000111755995,"threshold_uncertainty_score":0.24354471},"labels":[],"label_agreement":null},{"id":"W4416371754","doi":"10.2316/j.2026.206-1239","title":"CROSS-DOMAIN VISUAL LOOP CLOSURE DETECTION BASED ON IMAGE TRANSLATION MODEL. 64-72","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Translation (biology); Image (mathematics); Closure (psychology); Visualization; Visual control; Object detection; Noise (video)","score_opus":0.00758436131314896,"score_gpt":0.26874177948007305,"score_spread":0.2611574181669241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371754","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":[0.14724669,0.00005911099,0.850801,0.0004770953,0.0007865314,0.00007458527,0.0000059442627,0.000052310555,0.00049674715],"genre_scores_gemma":[0.9832988,0.000054465778,0.01632978,0.000121871475,0.000118714124,0.0000014898415,0.00002366934,0.000017383933,0.000033857814],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891216,0.000030137287,0.00047291463,0.00010057701,0.00037176593,0.000112444155],"domain_scores_gemma":[0.9992868,0.00007049104,0.00014121244,0.000064221706,0.000393325,0.000043955515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002654217,0.00013093014,0.00014416622,0.0004150551,0.000069860645,0.00019364127,0.000104888655,0.00010407666,0.000009442369],"category_scores_gemma":[0.000041208892,0.00012902192,0.000084579864,0.00014520282,0.000029188986,0.0002968244,0.0000074122595,0.00016466163,0.0000023338291],"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":[0.000058187285,0.000045779318,0.0002999432,0.00003003695,0.0000505647,0.0000054447505,0.0000449149,0.96952,0.010418404,0.001077977,0.000049026698,0.018399755],"study_design_scores_gemma":[0.0009729282,0.000074034244,0.0026193878,0.00012704964,0.000026280637,0.0000082791175,0.000014071762,0.9877396,0.006497328,0.0017279651,0.0000865611,0.00010650418],"about_ca_topic_score_codex":0.0000018353696,"about_ca_topic_score_gemma":0.0000040551918,"teacher_disagreement_score":0.83605206,"about_ca_system_score_codex":0.00012562523,"about_ca_system_score_gemma":0.00004195577,"threshold_uncertainty_score":0.5261361},"labels":[],"label_agreement":null},{"id":"W4416371773","doi":"10.2316/j.2026.206-1313","title":"DYNAMIC MODELLING AND EXPERIMENTAL VERIFICATION OF LONGITUDINAL MOTION OF BIOMIMETIC ROBOTIC FISH. 420-431","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Biomimetic flight and propulsion mechanisms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion (physics); Fish <Actinopterygii>; Robot; Motion control; Robotics","score_opus":0.011665811170854348,"score_gpt":0.25134815664562654,"score_spread":0.23968234547477218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371773","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":[0.45869184,0.00065471936,0.5397966,0.00020902556,0.00054379064,0.000049073024,0.0000032379992,0.000009337643,0.00004238292],"genre_scores_gemma":[0.9751062,0.00028853852,0.024555968,0.000006614211,0.000015962805,7.4212e-7,0.000007645429,0.000006181171,0.000012192257],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922043,0.000016374375,0.0004475119,0.000066838336,0.00019464939,0.000054174623],"domain_scores_gemma":[0.9994922,0.000033997163,0.00020160801,0.00005277656,0.00019479753,0.000024572342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016038308,0.00007883126,0.0001613191,0.0002966788,0.00001926798,0.000025292407,0.00009041667,0.000057834033,0.000008265547],"category_scores_gemma":[0.000012564463,0.00007435124,0.00004230957,0.00008879966,0.00003458343,0.00015241372,0.000019911602,0.000063823,2.8309148e-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":[0.000044399443,0.000080496284,0.00035471504,0.00013241902,0.00016496857,0.0000019975432,0.0002430574,0.82160825,0.16033393,0.005288145,0.000032726864,0.011714913],"study_design_scores_gemma":[0.00042335974,0.00006186797,0.0029021893,0.000194606,0.000041925465,0.000018650404,0.000056054825,0.8901678,0.10406107,0.0020099713,0.000007470725,0.000055044708],"about_ca_topic_score_codex":0.0000056487306,"about_ca_topic_score_gemma":7.515596e-7,"teacher_disagreement_score":0.51641434,"about_ca_system_score_codex":0.000042071533,"about_ca_system_score_gemma":0.000013691257,"threshold_uncertainty_score":0.30319557},"labels":[],"label_agreement":null},{"id":"W4416371776","doi":"10.2316/j.2026.206-1312","title":"GRAPH COLLABORATIVE GUIDED SESSION-BASED RECOMMENDATION. 368-382","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Graph; Matching (statistics); Recommender system; Context (archaeology)","score_opus":0.009506109429260369,"score_gpt":0.2881235341783957,"score_spread":0.2786174247491353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371776","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":[0.00587201,0.000078223966,0.9778248,0.013769836,0.0017075795,0.00005554086,0.0000044204257,0.000027350801,0.00066023803],"genre_scores_gemma":[0.8565621,0.000060890936,0.14216828,0.0010307068,0.00008075192,0.0000020131442,0.000009812831,0.0000036247113,0.0000818437],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910307,0.00008580521,0.00038805493,0.0001074706,0.00024108651,0.0000745363],"domain_scores_gemma":[0.99843746,0.00017073585,0.00035307836,0.00008228852,0.000914664,0.00004177075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004469038,0.00008219883,0.00011825825,0.00042955234,0.000092716684,0.00023928672,0.000397157,0.00004006097,0.000013403612],"category_scores_gemma":[0.00011499005,0.000069523114,0.000057400415,0.00036312622,0.000032056843,0.0005527205,0.00005896717,0.000099696845,0.0000017609908],"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":[0.00006829216,0.00030531932,0.0017991465,0.000025144685,0.00033277966,0.00003736582,0.00061843323,0.08831534,0.0016200339,0.64898384,0.006770872,0.25112343],"study_design_scores_gemma":[0.001793283,0.00012859632,0.008676617,0.00032856825,0.000029252387,0.00005123084,0.00013578968,0.77663326,0.0041717156,0.20391497,0.0039461423,0.00019057105],"about_ca_topic_score_codex":0.0000014046634,"about_ca_topic_score_gemma":6.36728e-7,"teacher_disagreement_score":0.85069007,"about_ca_system_score_codex":0.00004221159,"about_ca_system_score_gemma":0.00015503266,"threshold_uncertainty_score":0.28350705},"labels":[],"label_agreement":null},{"id":"W4416371779","doi":"10.2316/j.2026.206-1294","title":"BASKETBALL ROBOT TARGET DETECTION COMBINING ROS AND IMPROVED YOLOv5 ALGORITHM. 265-279","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Basketball; Noise (video); Feature (linguistics); Mobile robot","score_opus":0.004164945910901284,"score_gpt":0.21435564920605843,"score_spread":0.21019070329515716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371779","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":[0.046045292,0.0005278199,0.947792,0.00083049637,0.0041241962,0.000101629834,0.0000057878456,0.000098118566,0.00047467806],"genre_scores_gemma":[0.9892771,0.00015986648,0.010224251,0.00006641208,0.0001468999,0.0000020116931,0.000003977306,0.000010384996,0.00010909642],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992342,0.000024413186,0.0004066821,0.0000782398,0.00017095734,0.000085480766],"domain_scores_gemma":[0.9995056,0.000042256383,0.00013927458,0.00004651701,0.0002210802,0.000045312507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002360812,0.00009995362,0.00015232936,0.00025995437,0.000055216864,0.000112810376,0.00008602682,0.00007593526,0.0000061661053],"category_scores_gemma":[0.00004281839,0.00009738667,0.00004598248,0.00008885477,0.000019099249,0.00024576782,0.00002271493,0.00015817855,0.0000013835042],"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":[0.000067879635,0.00007397108,0.001098285,0.00014565185,0.00069959677,0.000024125658,0.0006918431,0.31368217,0.07908983,0.0015134133,0.0005054215,0.6024078],"study_design_scores_gemma":[0.00071245135,0.000056945384,0.008453214,0.000113247595,0.000020519696,0.00012505402,0.00009222826,0.98403627,0.00426216,0.0006767707,0.0013586102,0.00009252736],"about_ca_topic_score_codex":0.000010235143,"about_ca_topic_score_gemma":0.00000629628,"teacher_disagreement_score":0.9432318,"about_ca_system_score_codex":0.00008408888,"about_ca_system_score_gemma":0.00001727214,"threshold_uncertainty_score":0.3971313},"labels":[],"label_agreement":null},{"id":"W4416371780","doi":"10.2316/j.2026.206-1090","title":"RESEARCH ON PATH PLANNING EFFICIENCY OF Q-LEARNING ALGORITHM. 1-10","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Path (computing); Motion planning; Stability (learning theory); Context (archaeology); Work (physics)","score_opus":0.029655543611449734,"score_gpt":0.39884289352708807,"score_spread":0.36918734991563834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371780","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":[0.056463294,0.00018901634,0.9350415,0.0058214352,0.0007372329,0.000039061546,7.364079e-7,0.000018521303,0.0016892384],"genre_scores_gemma":[0.9394399,0.000036384907,0.060229976,0.000036090998,0.0000463141,8.719654e-7,0.0000013173321,0.0000015838983,0.00020756696],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990686,0.00006285842,0.00027048314,0.000084774656,0.00043890986,0.00007437319],"domain_scores_gemma":[0.9987354,0.00027949616,0.00020895222,0.00006691141,0.0006898923,0.000019330353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008122591,0.00004459547,0.00008223884,0.000551458,0.00007527447,0.00006400515,0.000431202,0.000042651325,0.000004792337],"category_scores_gemma":[0.00013338713,0.0000387032,0.000027538505,0.000244156,0.000043353797,0.00017209271,0.00009250243,0.0002415094,0.000001698216],"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":[0.00001474126,0.00031119597,0.002799643,0.000016672513,0.000100988,0.00002085576,0.0004730957,0.07131281,0.0008381203,0.77271974,0.0015274902,0.14986466],"study_design_scores_gemma":[0.0008160625,0.000651337,0.039174296,0.0010321683,0.000012003316,0.00006491951,0.0009029005,0.88158387,0.00584033,0.066594936,0.0031973466,0.00012984822],"about_ca_topic_score_codex":0.0000013529339,"about_ca_topic_score_gemma":4.590781e-8,"teacher_disagreement_score":0.8829766,"about_ca_system_score_codex":0.000053389325,"about_ca_system_score_gemma":0.0001449741,"threshold_uncertainty_score":0.15782706},"labels":[],"label_agreement":null},{"id":"W4416371806","doi":"10.2316/j.2026.206-1310","title":"GRU-ENHANCED MADDPG WITH DECOUPLED VALUE NETWORK FOR FAILURE-RESILIENT MULTI-ROBOT ENCIRCLEMENT. 357-367","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Control theory (sociology); Unit (ring theory); Action (physics); Network topology","score_opus":0.007931146439607543,"score_gpt":0.2538984374827885,"score_spread":0.24596729104318096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371806","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":[0.03797706,0.0002907895,0.9598215,0.00058961427,0.0010451161,0.00017107134,0.000005571765,0.00003433766,0.00006494968],"genre_scores_gemma":[0.8573369,0.00017332585,0.1421131,0.000090998576,0.00016786112,0.000007800113,0.000012035696,0.000013736007,0.000084260195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903154,0.000013468592,0.00044234682,0.000105271145,0.00025578745,0.00015159062],"domain_scores_gemma":[0.999237,0.00007688644,0.00016277772,0.00007740512,0.00039604754,0.00004989188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022774702,0.00012569205,0.00018259152,0.00014470963,0.000058599584,0.00011041153,0.00019554922,0.000045535206,0.000017217835],"category_scores_gemma":[0.000038789865,0.00010725053,0.00006395447,0.00009249537,0.000021899792,0.0001788736,0.000022057195,0.000109826426,0.0000019679394],"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":[0.000032191674,0.000039759052,0.00023908555,0.000036590238,0.00021811608,0.0000057165034,0.00008648369,0.97906065,0.0024637308,0.00480656,0.00055034476,0.012460753],"study_design_scores_gemma":[0.001180385,0.00010070573,0.004671068,0.00039178945,0.000060981347,0.000033156484,0.00006514912,0.9844016,0.006463125,0.0015786488,0.00090247235,0.00015095105],"about_ca_topic_score_codex":0.000004574712,"about_ca_topic_score_gemma":0.000030391548,"teacher_disagreement_score":0.81935984,"about_ca_system_score_codex":0.000093603696,"about_ca_system_score_gemma":0.00004128218,"threshold_uncertainty_score":0.43735498},"labels":[],"label_agreement":null},{"id":"W4416371824","doi":"10.2316/j.2026.206-1289","title":"STYLE TRANSFER AND PERSONALISED DESIGN OF VISUAL ELEMENTS BASED ON CLIP CONTRASTIVE LANGUAGE IMAGE MODEL. 254-264","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Style (visual arts); Visual language; Bridge (graph theory); Contrastive analysis; Image (mathematics); Visualization","score_opus":0.009868304675649349,"score_gpt":0.2735447946368721,"score_spread":0.2636764899612227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371824","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":[0.0186021,0.000060314465,0.97989285,0.001102082,0.00017338603,0.000075107906,0.00000647541,0.00000614791,0.00008150977],"genre_scores_gemma":[0.88414574,0.000028353415,0.11554218,0.00022205517,0.00003562444,8.9270947e-7,0.0000019346467,0.0000028039076,0.000020423953],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918944,0.00007417376,0.00029219664,0.00010132237,0.00027282172,0.000070064976],"domain_scores_gemma":[0.99929696,0.00015755904,0.00013756426,0.00004537942,0.0003306379,0.000031903546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032439383,0.000079996375,0.00013874954,0.0001721042,0.000037605507,0.00010617004,0.00016783706,0.000029217716,0.0000050898047],"category_scores_gemma":[0.00006469968,0.000067385896,0.000043751013,0.000069439215,0.0000351522,0.0003019497,0.00002361679,0.00006834397,2.2185229e-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":[0.00015915022,0.0002220328,0.0002645531,0.00001845092,0.00019697196,0.000016222444,0.0009370975,0.9153781,0.036107104,0.0077942433,0.0002150636,0.038691],"study_design_scores_gemma":[0.0009969962,0.00013400338,0.0014685746,0.00010782467,0.000022169363,0.000002920888,0.000067349436,0.9898367,0.0068038492,0.00049963576,0.0000057060984,0.000054252803],"about_ca_topic_score_codex":0.0000035125065,"about_ca_topic_score_gemma":7.341921e-7,"teacher_disagreement_score":0.8655436,"about_ca_system_score_codex":0.000028904326,"about_ca_system_score_gemma":0.00006931795,"threshold_uncertainty_score":0.27479172},"labels":[],"label_agreement":null},{"id":"W4416371825","doi":"10.2316/j.2026.206-1286","title":"GRIPPING RELIABILITY ANALYSIS OF STEEL ARCH SPLICING ROBOT IN VIBRATION ENVIRONMENT BASED ON FUZZY RANDOM VARIABLES. 243-253","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Contact Mechanics and Variational Inequalities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Reliability (semiconductor); Fuzzy logic; Robot; Vibration; Noise (video)","score_opus":0.012581287247843187,"score_gpt":0.2611124017893015,"score_spread":0.24853111454145832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371825","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":[0.026777696,0.000031645443,0.9698814,0.0026600563,0.00036571454,0.00008267045,0.000005607605,0.0000068461004,0.0001883341],"genre_scores_gemma":[0.9599805,0.0000408216,0.039712965,0.00019983033,0.000029002194,0.000002302168,0.000012897475,0.000002402195,0.000019285682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844736,0.00011650357,0.0007176584,0.00014833747,0.00048902765,0.00008113407],"domain_scores_gemma":[0.9985639,0.0005260289,0.0004794281,0.00014100954,0.00026267985,0.000026994754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012491877,0.000088035595,0.00025319683,0.0009484322,0.00003615698,0.000105240826,0.00029036103,0.000047279067,0.000007977348],"category_scores_gemma":[0.00017906885,0.00008097322,0.00010417931,0.00036610226,0.000007867768,0.00032965763,0.00006676437,0.00011263436,2.5413385e-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":[0.000041769996,0.00009566872,0.0017642499,0.000011540467,0.00013398993,0.0000018236682,0.00015521311,0.73551583,0.0016750017,0.25754267,0.0000034711131,0.0030587742],"study_design_scores_gemma":[0.00096015865,0.000056449997,0.054381955,0.00014159328,0.00006754409,0.00000101762,0.0000246816,0.93415004,0.00048295045,0.009645906,0.00002731417,0.00006036226],"about_ca_topic_score_codex":0.00006755205,"about_ca_topic_score_gemma":0.000011992228,"teacher_disagreement_score":0.9332028,"about_ca_system_score_codex":0.00017685715,"about_ca_system_score_gemma":0.000112139096,"threshold_uncertainty_score":0.3301992},"labels":[],"label_agreement":null},{"id":"W4416371828","doi":"10.2316/j.2026.206-1301","title":"A NOVEL SEA ICE DETECTION ALGORITHM BASED ON YOLOV10. 348-356","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Sea ice; Noise (video); Feature (linguistics)","score_opus":0.005799179698373807,"score_gpt":0.23657861392416496,"score_spread":0.23077943422579114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371828","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":[0.004911799,0.000044784527,0.99035347,0.0010935322,0.0013471959,0.000049510327,0.000011398653,0.0000509962,0.0021373436],"genre_scores_gemma":[0.970538,0.00004356888,0.02888334,0.00027921682,0.00015014614,0.0000013735217,0.000013463519,0.000008293557,0.00008254787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993242,0.000012961876,0.0002905102,0.000057493988,0.00025236775,0.00006244966],"domain_scores_gemma":[0.9994918,0.00007648841,0.000091742804,0.000046123725,0.00025973082,0.000034104614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001776608,0.000076256045,0.000094730785,0.00026011665,0.000034503897,0.000070909635,0.00009204777,0.000058454738,0.00002272194],"category_scores_gemma":[0.000048877075,0.000073929696,0.000050339655,0.00010457252,0.000012246831,0.00014088144,0.000009754267,0.00014686951,0.0000035717592],"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":[0.00002305922,0.00005763086,0.00015228003,0.000023515642,0.00008408722,0.0000057655216,0.00003654038,0.7065829,0.0040110685,0.0012915216,0.00029131974,0.2874403],"study_design_scores_gemma":[0.000704554,0.00003452664,0.0073025906,0.00013378076,0.000016368049,0.000029785002,0.000011613747,0.98748064,0.0020695876,0.0003969373,0.0017567017,0.00006292112],"about_ca_topic_score_codex":0.0000047860435,"about_ca_topic_score_gemma":0.0000027959427,"teacher_disagreement_score":0.96562624,"about_ca_system_score_codex":0.000103574544,"about_ca_system_score_gemma":0.000027172078,"threshold_uncertainty_score":0.30147654},"labels":[],"label_agreement":null},{"id":"W4416371830","doi":"10.2316/j.2026.206-1290","title":"OPTIMISATION OF SPORTS REHABILITATION TRAINING SYSTEM BASED ON COMPUTER VISION TECHNOLOGY AND ROBOT COLLABORATION MECHANISM. 335-347","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Computing and Algorithms","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mechanism (biology); Training (meteorology); Robot; Training system; Rehabilitation; Machine vision","score_opus":0.006897886096457237,"score_gpt":0.3017190223122433,"score_spread":0.29482113621578604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371830","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":[0.21359818,0.000054679247,0.77735984,0.007317266,0.0011411667,0.00014440589,0.0000023453088,0.000043015934,0.00033909082],"genre_scores_gemma":[0.8612399,0.000016352475,0.13857858,0.000044726698,0.000098254684,9.704502e-7,0.0000032161238,0.0000033510719,0.000014641775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989458,0.00007888471,0.0004008765,0.000105197716,0.00039869925,0.00007056687],"domain_scores_gemma":[0.99848044,0.00022423641,0.00047716036,0.00004786765,0.00074187055,0.000028411712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000688892,0.00006784003,0.00014821667,0.0005905272,0.00012918907,0.00006942115,0.00009196385,0.00008069599,0.0000020778798],"category_scores_gemma":[0.00018656836,0.00006572362,0.00002893853,0.00029646562,0.00007647595,0.00018006249,0.000017459522,0.000079899684,1.3898838e-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":[0.000056824298,0.000055584336,0.00038338907,0.000038750313,0.000028686629,0.000005867613,0.0019576508,0.40626207,0.00077350787,0.36031938,0.00002791625,0.2300904],"study_design_scores_gemma":[0.0007739543,0.000369744,0.003948043,0.0012417668,0.000027535967,0.000010549747,0.004472404,0.96554023,0.00038999427,0.023007402,0.00012939893,0.00008896334],"about_ca_topic_score_codex":0.0000047308913,"about_ca_topic_score_gemma":0.0000020914986,"teacher_disagreement_score":0.6476417,"about_ca_system_score_codex":0.00012676051,"about_ca_system_score_gemma":0.00012941055,"threshold_uncertainty_score":0.26801318},"labels":[],"label_agreement":null},{"id":"W4416371835","doi":"10.2316/j.2026.206-1283","title":"A NEW MULTIMODAL PERCEPTION-BASED SENSOR FUSION COST MAP. 321-334","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Sensor fusion; Fusion; Field (mathematics); Key (lock); Image fusion; Feature (linguistics)","score_opus":0.006205274678054952,"score_gpt":0.23862828359326077,"score_spread":0.23242300891520581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371835","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":[0.054996233,0.0001313427,0.93641806,0.0031863959,0.0044048526,0.00012043545,0.00000726397,0.00009240739,0.000643031],"genre_scores_gemma":[0.98595965,0.000050795225,0.013258726,0.0001164541,0.00025755426,0.0000010765576,0.000008555741,0.000008581183,0.00033859623],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992793,0.000018822839,0.0003448228,0.000058029942,0.00023147311,0.000067559326],"domain_scores_gemma":[0.9995348,0.00004961657,0.000096356875,0.000048152546,0.00021932693,0.000051753734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012697092,0.000081917264,0.00011365159,0.00025766616,0.000036534937,0.00008345956,0.00009212852,0.000061632236,0.00006045078],"category_scores_gemma":[0.000030900206,0.00007665792,0.00006403189,0.000073341405,0.000009549581,0.00013063029,0.000010111741,0.00011317057,0.000012645803],"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":[0.000049018843,0.000030008821,0.0010498685,0.000053550728,0.00012090668,0.000013335433,0.00023473924,0.8659883,0.0144398585,0.0004926117,0.0054401103,0.11208766],"study_design_scores_gemma":[0.0008991928,0.000025580928,0.016827997,0.00020453306,0.000014828545,0.000036391335,0.000088990346,0.9743247,0.0005342749,0.00012542077,0.0068395087,0.00007859024],"about_ca_topic_score_codex":0.00001506144,"about_ca_topic_score_gemma":0.0000061276937,"teacher_disagreement_score":0.93096346,"about_ca_system_score_codex":0.00012373751,"about_ca_system_score_gemma":0.000046458597,"threshold_uncertainty_score":0.3126019},"labels":[],"label_agreement":null},{"id":"W4416371839","doi":"10.2316/j.2026.206-1278","title":"DATA-DRIVEN FAULT DIAGNOSIS FOR MULTI-MODE LARGE-SCALE AVIONICS SYSTEMS. 307-320","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Avionics; Fault (geology); Troubleshooting; Reliability (semiconductor); Identification (biology)","score_opus":0.020607448939079277,"score_gpt":0.3028237935020142,"score_spread":0.28221634456293493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371839","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":[0.026107298,0.0011176728,0.9666079,0.0006668372,0.004871351,0.00021616546,0.00023701912,0.00007645638,0.000099278215],"genre_scores_gemma":[0.9911496,0.00029838306,0.008043473,0.000053528987,0.00024151562,0.000016893799,0.000054138167,0.000012602216,0.00012989086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913085,0.000020484196,0.00045725945,0.00009050875,0.00020471061,0.000096180585],"domain_scores_gemma":[0.99930024,0.00007700611,0.0001557904,0.00010968781,0.00031709272,0.000040164687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022901138,0.00009015938,0.00017308263,0.00018045904,0.00005107651,0.0001605935,0.0002597356,0.00006904086,0.0000028371437],"category_scores_gemma":[0.00007467508,0.00008357343,0.000056210865,0.000061303326,0.000009013484,0.00028278388,0.000035774527,0.0000983455,0.000002473259],"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":[0.000019086774,0.000067597415,0.0010334138,0.00011740246,0.0002876019,0.0000039008996,0.00014011799,0.9845469,0.0005040589,0.0021058875,0.0039101825,0.007263865],"study_design_scores_gemma":[0.001121625,0.000021233329,0.0009768548,0.00019325853,0.00004798457,0.000023840192,0.00015053818,0.97993195,0.00009167012,0.0000651815,0.017301839,0.000074044896],"about_ca_topic_score_codex":0.000008599946,"about_ca_topic_score_gemma":0.00004609566,"teacher_disagreement_score":0.9650423,"about_ca_system_score_codex":0.000091095375,"about_ca_system_score_gemma":0.000027300437,"threshold_uncertainty_score":0.34080258},"labels":[],"label_agreement":null},{"id":"W4416371844","doi":"10.2316/j.2026.206-1269","title":"PATROL ROBOT USING SOBEL AND HOUGH ALGORITHMS FOR COAL MINE FIRE PREVENTION. 230-242","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Belt Conveyor Systems Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Coal mining; Sobel operator; Robot; Hough transform; Edge detection; Robotics","score_opus":0.016877078388994677,"score_gpt":0.27555105861947254,"score_spread":0.2586739802304779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371844","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":[0.14976868,0.0010941586,0.84709764,0.0002702725,0.0015748944,0.00011538968,0.000008488168,0.000037855156,0.000032640542],"genre_scores_gemma":[0.947222,0.00012051944,0.052273847,0.000017187984,0.00026170415,0.0000033459153,0.000006640544,0.000015107024,0.00007967806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929047,0.000010194452,0.00038091085,0.00006994058,0.0001575846,0.00009087773],"domain_scores_gemma":[0.99953574,0.00005937561,0.00011726069,0.000044202072,0.0002071943,0.000036217567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018325425,0.000099303514,0.00015832546,0.00016875692,0.000035376568,0.00009206549,0.00009046201,0.000059115002,0.0000022082477],"category_scores_gemma":[0.000037131063,0.00010055146,0.00005341989,0.00005472062,0.000012695154,0.00024475058,0.00002123559,0.00008503786,2.46626e-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":[0.000011302308,0.00001994742,0.0004898168,0.00014130543,0.00028846003,0.000005450214,0.000107068496,0.9457317,0.003627326,0.0007895584,0.0002313242,0.04855673],"study_design_scores_gemma":[0.0007653338,0.00003284468,0.0036383644,0.0003582161,0.000051539053,0.00009633339,0.00003523779,0.9932065,0.0007732176,0.0004986749,0.0004549998,0.00008873477],"about_ca_topic_score_codex":0.0000049601163,"about_ca_topic_score_gemma":0.0000026417865,"teacher_disagreement_score":0.7974533,"about_ca_system_score_codex":0.00008040089,"about_ca_system_score_gemma":0.00002637337,"threshold_uncertainty_score":0.41003695},"labels":[],"label_agreement":null},{"id":"W4416371847","doi":"10.2316/j.2026.206-1252","title":"DISTRIBUTED DRIVE ELECTRIC MONORAIL CRANES COOPERATIVE STEERING CONTROL VIA CONTINUOUS FAST TERMINAL SLIDING MODE CONTROL. 139-149","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Monorail; Terminal (telecommunication); Mode (computer interface); Control (management); Control theory (sociology); Terminal sliding mode","score_opus":0.002846536251284157,"score_gpt":0.21325550886931718,"score_spread":0.21040897261803304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371847","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":[0.09168675,0.00040299157,0.9059242,0.0005470415,0.0010622753,0.00015500897,0.00003815425,0.000049397557,0.00013418173],"genre_scores_gemma":[0.99911505,0.00009397992,0.00045080736,0.00007685811,0.00019023205,0.000006453557,0.000012051488,0.000013763114,0.000040800896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987241,0.00004590668,0.0006429056,0.00011103408,0.00030415057,0.00017191091],"domain_scores_gemma":[0.9989152,0.00015522588,0.0002460331,0.00006314773,0.00054920773,0.000071213886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024379908,0.0001696673,0.00037826237,0.00021851357,0.0000630915,0.0002098549,0.00021456416,0.00008731121,0.0000036113881],"category_scores_gemma":[0.000064198626,0.00015326381,0.000102335456,0.00011509635,0.000012534301,0.00026333277,0.000013954822,0.00020807692,0.0000015137299],"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":[0.00010063005,0.000047260273,0.0004888003,0.000029141545,0.0006740445,0.000053365657,0.00007780008,0.9332175,0.034720317,0.008056666,0.000105844476,0.022428624],"study_design_scores_gemma":[0.0025247158,0.00009177276,0.0017603972,0.00019617552,0.0000937325,0.000091145135,0.000042422373,0.99346536,0.00037630752,0.0010686556,0.00015318763,0.00013611259],"about_ca_topic_score_codex":0.000013516489,"about_ca_topic_score_gemma":0.00000882265,"teacher_disagreement_score":0.9074283,"about_ca_system_score_codex":0.0001834573,"about_ca_system_score_gemma":0.00003661971,"threshold_uncertainty_score":0.6249917},"labels":[],"label_agreement":null},{"id":"W4416371850","doi":"10.2316/j.2026.206-1232","title":"PATH PLANNING FOR MOBILE ROBOTS–BASED ON DOUBLE DUELING DEEP Q-NETWORK AND ARTIFICIAL POTENTIAL FIELD. 194-202","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion planning; Path (computing); Field (mathematics); Mobile robot","score_opus":0.008870512990890304,"score_gpt":0.26047210380282654,"score_spread":0.2516015908119362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371850","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":[0.06750835,0.00057542033,0.92821616,0.00043565498,0.0028137462,0.00016767408,0.0000040113546,0.000054587046,0.00022440197],"genre_scores_gemma":[0.9867072,0.00004828234,0.012672671,0.0000954884,0.00042881657,0.000006416632,0.0000111306035,0.000012405779,0.000017552517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991562,0.000012311626,0.00042490984,0.00008867147,0.00019573377,0.00012219057],"domain_scores_gemma":[0.9994695,0.0001224286,0.00014186904,0.000051502928,0.00017542613,0.000039257277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023649921,0.000107131156,0.00016939898,0.00017871545,0.00007999701,0.00018820619,0.00009787552,0.0000788405,0.0000037008933],"category_scores_gemma":[0.000023107435,0.00010048918,0.000060271926,0.0000659727,0.000010797613,0.0001080505,0.000015742713,0.000117541305,5.4352006e-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":[0.000056251203,0.000019622856,0.0002043891,0.000054433985,0.00008198336,0.000010225369,0.00005823394,0.9879267,0.00070189004,0.0019236886,0.00052937405,0.008433187],"study_design_scores_gemma":[0.00069704454,0.00009329632,0.0005291614,0.00043583658,0.000033692395,0.00001548315,0.000051322,0.99591863,0.00061642285,0.0012927548,0.00022506295,0.00009126931],"about_ca_topic_score_codex":0.0000020202986,"about_ca_topic_score_gemma":9.082908e-7,"teacher_disagreement_score":0.9191989,"about_ca_system_score_codex":0.000040626423,"about_ca_system_score_gemma":0.000023270512,"threshold_uncertainty_score":0.409783},"labels":[],"label_agreement":null},{"id":"W4416371852","doi":"10.2316/j.2026.206-1247","title":"GRASPING TASK PLANNING ALGORITHM FOR DEXTEROUS HAND BASED ON SCENE UNDERSTANDING AND SEMANTIC INFORMATION. 295-306","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Task (project management); Feature (linguistics); Key (lock); Complete information; Semantics (computer science)","score_opus":0.019458827815113863,"score_gpt":0.27649595280646144,"score_spread":0.25703712499134757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371852","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":[0.0009415577,0.000055331915,0.9955355,0.0024516713,0.0007782615,0.00009074248,0.0000045307097,0.0000174247,0.00012496601],"genre_scores_gemma":[0.7473397,0.00002999079,0.2519385,0.0005713074,0.00007629785,0.0000020072207,0.000019642815,0.0000033198132,0.000019238554],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992402,0.000014510236,0.00030662693,0.00008846148,0.00026043967,0.0000897476],"domain_scores_gemma":[0.99935204,0.000119090815,0.00025317818,0.000067488196,0.00017648334,0.00003172705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033329625,0.00008049809,0.00010494944,0.00046365752,0.00013849193,0.0008887886,0.0002525137,0.00002751108,4.9691226e-7],"category_scores_gemma":[0.000054493106,0.00007287036,0.00003170534,0.000105990446,0.000024318211,0.0012919606,0.000075929594,0.00006648318,4.403103e-7],"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":[0.000035835816,0.00008549171,0.0013064746,0.00011475203,0.00023213516,0.000021004458,0.00055169285,0.13093711,0.00012576739,0.1200098,0.0010733982,0.7455065],"study_design_scores_gemma":[0.0008961462,0.000081507096,0.0020627966,0.0003574636,0.000017493052,0.000013088775,0.00008564375,0.9868715,0.00008165848,0.009166758,0.00029541703,0.00007053446],"about_ca_topic_score_codex":0.0000020627372,"about_ca_topic_score_gemma":4.2268732e-7,"teacher_disagreement_score":0.8559344,"about_ca_system_score_codex":0.000072635085,"about_ca_system_score_gemma":0.000036632067,"threshold_uncertainty_score":0.8570609},"labels":[],"label_agreement":null},{"id":"W4416371853","doi":"10.2316/j.2026.206-1234","title":"EFFICIENT COLLISION AVOIDANCE AND MOTION PLANNING FOR INDUSTRIAL ROBOTS BASED ON NSGA-II AND GJK. 124-138","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Collision avoidance; Motion planning; Motion (physics); Industrial robot; Collision; Context (archaeology)","score_opus":0.018498770433627198,"score_gpt":0.2684457899500992,"score_spread":0.24994701951647202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371853","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":[0.3363783,0.0002360842,0.66169363,0.00062871556,0.0008458062,0.00012848643,0.0000060617713,0.000016430542,0.000066489956],"genre_scores_gemma":[0.99285847,0.00005954469,0.0068504065,0.000063645486,0.00012728505,0.0000031426841,0.000005811928,0.0000073503015,0.000024351828],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932504,0.000015781761,0.00029475012,0.00009240318,0.00019347663,0.00007858092],"domain_scores_gemma":[0.99951756,0.00012832897,0.00011057748,0.00004154939,0.0001626693,0.0000393337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027560108,0.000092576265,0.00012695137,0.000221169,0.00008638311,0.000095732525,0.000069535505,0.00007015638,0.000001705202],"category_scores_gemma":[0.00010904108,0.000082957085,0.000024364968,0.000057994137,0.000020353878,0.00007268376,0.000020918165,0.00011894386,1.5722993e-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":[0.000044297132,0.000023421691,0.0004131246,0.000022605573,0.000029367377,0.000002634905,0.00009709011,0.96469176,0.0006843123,0.0018738556,0.00014346157,0.031974085],"study_design_scores_gemma":[0.0007194104,0.000121345314,0.003906399,0.00042720264,0.000019160221,0.0000119182,0.000025126523,0.99246496,0.001485486,0.00046364503,0.00028207735,0.00007324043],"about_ca_topic_score_codex":0.000001581554,"about_ca_topic_score_gemma":6.3761405e-7,"teacher_disagreement_score":0.65648013,"about_ca_system_score_codex":0.000057569894,"about_ca_system_score_gemma":0.000019844476,"threshold_uncertainty_score":0.3382892},"labels":[],"label_agreement":null},{"id":"W4416371854","doi":"10.2316/j.2026.206-1262","title":"RLH-MAPPING: REAL-TIME DENSE MAPPING FOR ROBOTS USING LOW-LIGHT FIELD AND HYBRID REPRESENTATIONS. 162-170","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Field (mathematics); Robot; Mobile robot; Noise (video); Tracking (education)","score_opus":0.01864981537205624,"score_gpt":0.29735832350108704,"score_spread":0.2787085081290308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371854","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034061756,0.00012031325,0.9582598,0.0061486135,0.0010403792,0.00012452452,0.000002518203,0.000035321777,0.00020675173],"genre_scores_gemma":[0.16965978,0.000107455955,0.8293784,0.00033890182,0.00022501689,0.000003153691,0.000006694955,0.000008892535,0.0002716849],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987719,0.000047714115,0.00053434307,0.00019705977,0.0003101645,0.00013880285],"domain_scores_gemma":[0.99841183,0.00040272964,0.0004455717,0.00013453401,0.000542669,0.00006263859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045680528,0.000116331525,0.0001971191,0.00044926978,0.00013057911,0.0003473316,0.000356536,0.000052675437,0.0000019659235],"category_scores_gemma":[0.00034468295,0.00011365358,0.0000647435,0.00015530326,0.000023455512,0.0005798909,0.00013229257,0.000109737506,0.0000010659687],"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":[0.0000745128,0.0002366401,0.0077484264,0.00021164688,0.0008358446,0.00028680664,0.0028705269,0.79281175,0.03955959,0.043780386,0.0074185664,0.10416531],"study_design_scores_gemma":[0.00062566245,0.0000387625,0.0052566836,0.00044923832,0.000022051587,0.0002995438,0.000043044987,0.9860361,0.0014059923,0.0055272607,0.00018285526,0.00011279616],"about_ca_topic_score_codex":0.000013713774,"about_ca_topic_score_gemma":2.8717736e-7,"teacher_disagreement_score":0.19322436,"about_ca_system_score_codex":0.00007879674,"about_ca_system_score_gemma":0.00012274389,"threshold_uncertainty_score":0.46346587},"labels":[],"label_agreement":null},{"id":"W4416371855","doi":"10.2316/j.2026.206-1254","title":"A NOVEL BIONIC THREE-TOED ADHESION MODULE WITH HIGH ADAPTABILITY TO COMPLEX SURFACES. 218-229","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Adaptability; Adhesion; Flexibility (engineering); Cell adhesion","score_opus":0.011219855281319786,"score_gpt":0.2553471692125258,"score_spread":0.24412731393120604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371855","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":[0.67343646,0.00001986473,0.32349706,0.0027567747,0.000113498645,0.000045942048,0.0000095771275,0.0000066033963,0.00011419481],"genre_scores_gemma":[0.9733879,0.0000033094234,0.026337268,0.000069541966,0.000099696634,0.0000016101585,0.000015850143,0.000005228038,0.00007962188],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992253,0.000016187008,0.00029335334,0.00011850083,0.00025105488,0.00009557349],"domain_scores_gemma":[0.9992704,0.00004145416,0.00019075019,0.000084243344,0.00036282875,0.0000503307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015789922,0.00009466851,0.00016089143,0.00016427772,0.00005837214,0.00010298071,0.00016101268,0.000019819037,0.000053849813],"category_scores_gemma":[0.000009958798,0.000075686316,0.000050709554,0.00014921495,0.00002432204,0.000086772554,0.000041208987,0.00008251482,0.0000017628784],"study_design_candidate":"observational","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":[0.00036393342,0.0012627322,0.18291716,0.00004522532,0.0017178435,0.000007275546,0.0002674883,0.42600605,0.15833347,0.03367394,0.00090319564,0.19450168],"study_design_scores_gemma":[0.0019778858,0.0004153026,0.7586705,0.0002583021,0.00013770869,0.000015334743,0.000094710434,0.22943728,0.0028437092,0.005751008,0.000182876,0.00021540142],"about_ca_topic_score_codex":0.0001278053,"about_ca_topic_score_gemma":0.000021621532,"teacher_disagreement_score":0.57575333,"about_ca_system_score_codex":0.000040189847,"about_ca_system_score_gemma":0.00006510908,"threshold_uncertainty_score":0.30863985},"labels":[],"label_agreement":null},{"id":"W4416371859","doi":"10.2316/j.2026.206-1253","title":"TRAFFIC MITIGATION AND VEHICLE DETECTION BASED ON HOMOMORPHIC ENCRYPTION ALGORITHM AND FUZZY COMPREHENSIVE EVALUATION. 150-161","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Homomorphic encryption; Encryption; Fuzzy control system; Key (lock); Homomorphic filtering","score_opus":0.009642631767008181,"score_gpt":0.24250908667095186,"score_spread":0.23286645490394367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371859","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":[0.8725468,0.00036131774,0.12550646,0.00063216285,0.00064803276,0.00015861489,0.000006642167,0.00006434157,0.00007562374],"genre_scores_gemma":[0.9933293,0.00026867058,0.0061780284,0.00008571666,0.0001000706,0.0000048587394,0.000018225099,0.000012234254,0.0000028805605],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907464,0.00005934937,0.00032991447,0.00010684776,0.00035093413,0.000078301106],"domain_scores_gemma":[0.9990961,0.00013939406,0.00014561627,0.000044238604,0.00052933465,0.00004532039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002648686,0.000112071626,0.00013089522,0.000405846,0.00008108469,0.00016135769,0.000045550627,0.00008495006,0.0000046480495],"category_scores_gemma":[0.00004995888,0.000116550305,0.000030150864,0.00011518683,0.000041817326,0.00031604827,0.000010346476,0.00015170632,0.0000016301233],"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":[0.000023458111,0.00002765304,0.0001271386,0.000037556023,0.00007262395,0.000003704121,0.000096137504,0.4730115,0.007313834,0.00023186032,0.000019897456,0.5190347],"study_design_scores_gemma":[0.0012054082,0.00008527385,0.032217853,0.00023194656,0.00007396058,0.000059411825,0.00007126436,0.9621711,0.0022929085,0.0014610626,0.000037148355,0.000092657865],"about_ca_topic_score_codex":0.0000025596835,"about_ca_topic_score_gemma":0.000003610567,"teacher_disagreement_score":0.518942,"about_ca_system_score_codex":0.00012403521,"about_ca_system_score_gemma":0.000031918156,"threshold_uncertainty_score":0.47527838},"labels":[],"label_agreement":null},{"id":"W4416371860","doi":"10.2316/j.2026.206-1268","title":"DYNAMIC UAV POSITION ESTIMATION FOR ENHANCED SAFETY SURVEILLANCE. 171-180","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Position (finance); Kalman filter; Estimation; Trajectory; Key (lock); Extended Kalman filter","score_opus":0.002773656596109195,"score_gpt":0.24436240376597665,"score_spread":0.24158874716986745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371860","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":[0.019445213,0.00014112431,0.9780379,0.0010907257,0.0006983194,0.0001362293,0.000017881503,0.000044650522,0.00038795278],"genre_scores_gemma":[0.91592884,0.00034013225,0.08347864,0.000041854535,0.000045921577,0.0000072084704,0.000102373924,0.0000085709,0.000046438323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935377,0.000009713066,0.0003730398,0.00006446836,0.00013350598,0.000065481494],"domain_scores_gemma":[0.9992947,0.00007225958,0.00014223986,0.00005269469,0.0004163104,0.00002180567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016781493,0.000075165946,0.00010882233,0.00020037444,0.0000517041,0.000077811936,0.00009331103,0.000052526528,0.0000059230133],"category_scores_gemma":[0.00004380017,0.00007573722,0.000043128697,0.00010070265,0.000013021182,0.00022697984,0.000009731249,0.00005666907,0.0000012430771],"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":[0.000024387273,0.000018798346,0.00004890634,0.000027502934,0.000068819245,2.6803048e-7,0.00004756285,0.9319681,0.0039499495,0.007915981,0.00020535728,0.05572437],"study_design_scores_gemma":[0.0005469465,0.000024314715,0.006929942,0.00007845803,0.000020032889,0.000009188782,0.000016968686,0.98607934,0.0012251943,0.004639833,0.00036175933,0.00006805112],"about_ca_topic_score_codex":0.0000011040423,"about_ca_topic_score_gemma":0.0000047970525,"teacher_disagreement_score":0.89648366,"about_ca_system_score_codex":0.0001366087,"about_ca_system_score_gemma":0.00002596294,"threshold_uncertainty_score":0.30884743},"labels":[],"label_agreement":null},{"id":"W4416371861","doi":"10.2316/j.2026.206-1259","title":"EXTENDED DEEP DOWNSAMPLING NETWORK WITH MULTI-INTERACTIVE REFINEMENT FOR UNDERWATER SALIENT OBJECT DETECTION. 280-294","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Upsampling; Object detection; Object (grammar); Salient; Pattern recognition (psychology); Underwater; Artificial neural network","score_opus":0.011779852206467259,"score_gpt":0.2585860917002281,"score_spread":0.24680623949376085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371861","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":[0.018842813,0.0002517416,0.9796239,0.00050094456,0.000495882,0.00013892133,0.0000024019841,0.00003859811,0.000104810286],"genre_scores_gemma":[0.93935096,0.000101465404,0.060264975,0.000080148944,0.00011882367,0.00001228672,0.000007537278,0.0000113022015,0.00005248135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992319,0.00002290734,0.0003968135,0.000076890006,0.00016866886,0.000102835875],"domain_scores_gemma":[0.9992507,0.00008391563,0.00017144144,0.00007815349,0.0003850952,0.000030656483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019697797,0.00009996294,0.0001392951,0.00014736188,0.00007401354,0.00014029635,0.00014991392,0.000039565173,0.000003830668],"category_scores_gemma":[0.0000057640277,0.000079181256,0.000054185777,0.000070087044,0.000014423586,0.00017447547,0.000028591476,0.00010375955,8.649417e-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":[0.000113906244,0.00006606623,0.00033295955,0.000046982157,0.0006208416,0.0000025065187,0.00047270893,0.94189656,0.0062384116,0.00076888356,0.00007846488,0.049361706],"study_design_scores_gemma":[0.0018665212,0.00013678706,0.004509233,0.0004427739,0.000073946045,0.00005324377,0.00043776893,0.97476035,0.011043561,0.0023522987,0.004160803,0.00016270867],"about_ca_topic_score_codex":0.000006650429,"about_ca_topic_score_gemma":0.000045822973,"teacher_disagreement_score":0.92050815,"about_ca_system_score_codex":0.00015889233,"about_ca_system_score_gemma":0.000020379932,"threshold_uncertainty_score":0.3228918},"labels":[],"label_agreement":null},{"id":"W4416371865","doi":"10.2316/j.2026.206-1237","title":"HUMAN FOLLOWING TASK BASED ON MULTI-SENSOR FUSION PLANNING ALGORITHM. 203-217","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Task (project management); Sensor fusion; Fusion; Key (lock); Automation","score_opus":0.011821549426975818,"score_gpt":0.27384215266997614,"score_spread":0.2620206032430003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371865","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":[0.102222316,0.00016828185,0.8912199,0.00067985454,0.004623315,0.00009159257,0.000006124399,0.00010617261,0.0008824455],"genre_scores_gemma":[0.9883753,0.000008521209,0.011229924,0.000101914695,0.0001384566,0.000001064182,0.000006666856,0.00000979947,0.00012833733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992192,0.000022539985,0.0003575209,0.000065589295,0.00026155735,0.00007362029],"domain_scores_gemma":[0.9996438,0.000043983084,0.0001094796,0.000050875336,0.00011823931,0.000033629665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019824354,0.000089085166,0.00012837492,0.00033765068,0.00007014066,0.00008435578,0.00009838746,0.000058578018,0.0000055281716],"category_scores_gemma":[0.000032389293,0.00008359053,0.00008376243,0.00007606988,0.0000075138405,0.00011838026,0.000010696637,0.0001388198,0.0000027826675],"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":[0.000009146454,0.00003813593,0.0007288,0.00002278112,0.000120271565,0.000041356485,0.00013940154,0.96407926,0.008342731,0.00018928893,0.00047723827,0.025811583],"study_design_scores_gemma":[0.00085458625,0.000040175993,0.012431772,0.00043086437,0.000016202262,0.000015748981,0.000063699415,0.98431736,0.00061184977,0.0000518905,0.0010896142,0.00007621322],"about_ca_topic_score_codex":0.0000040779073,"about_ca_topic_score_gemma":0.0000011335663,"teacher_disagreement_score":0.886153,"about_ca_system_score_codex":0.00009395341,"about_ca_system_score_gemma":0.000014511614,"threshold_uncertainty_score":0.3408723},"labels":[],"label_agreement":null},{"id":"W4416371875","doi":"10.2316/j.2026.206-1225","title":"ACTIVE FLEXIBILITY AND STABILITY CONTROL FOR HYDRAULIC QUADRUPED ROBOTS. 98-110","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Stability (learning theory); Flexibility (engineering); Control (management); Robot; Model predictive control","score_opus":0.01105843355622099,"score_gpt":0.26178834718566946,"score_spread":0.25072991362944846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371875","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":[0.10899377,0.00029212507,0.8856832,0.0033167112,0.000993753,0.00025733377,0.000015231349,0.00004744136,0.0004004368],"genre_scores_gemma":[0.9957441,0.000069615926,0.0038604776,0.00019546645,0.00009109813,0.000005985454,0.000004578504,0.000006598601,0.000022064998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922097,0.00003153077,0.0004005968,0.00009282861,0.00016268998,0.00009139958],"domain_scores_gemma":[0.99918824,0.00020062835,0.00012246781,0.00006581809,0.00037152102,0.000051317853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030945268,0.000098406774,0.00020488416,0.00013027035,0.00004146967,0.00008306406,0.00010263236,0.00005917762,0.000013031233],"category_scores_gemma":[0.0001453908,0.00008919351,0.00006904963,0.000049533304,0.00003758226,0.00023587747,0.000013930539,0.00010693218,6.0242985e-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":[0.00034130627,0.0001785394,0.0036558907,0.0001633328,0.0008968329,0.0000047439935,0.00053824304,0.81955,0.0055972836,0.020602558,0.0006874564,0.1477838],"study_design_scores_gemma":[0.0027080516,0.00006246348,0.03277346,0.00007285613,0.000073458315,0.000014927872,0.000100067635,0.9534139,0.0010776782,0.009120187,0.0004819616,0.0001009547],"about_ca_topic_score_codex":0.000005030612,"about_ca_topic_score_gemma":0.0000061136716,"teacher_disagreement_score":0.88675034,"about_ca_system_score_codex":0.00010217492,"about_ca_system_score_gemma":0.00003873606,"threshold_uncertainty_score":0.3637206},"labels":[],"label_agreement":null},{"id":"W4416371877","doi":"10.2316/j.2026.206-1214","title":"FUZZY LOGIC-BASED ERROR DETECTION AND CORRECTION IN ENGLISH WRITING FOR LANGUAGE LEARNING. 85-97","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Error detection and correction; Natural language; Fuzzy control system; Error analysis","score_opus":0.009513769704676007,"score_gpt":0.2914994519304855,"score_spread":0.2819856822258095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371877","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":[0.034348033,0.0006957388,0.96294904,0.00091605034,0.00085623795,0.00007484588,4.4531689e-7,0.00007885987,0.00008073337],"genre_scores_gemma":[0.85563433,0.000016035838,0.14412545,0.000113086746,0.000071821254,0.0000024777673,0.0000016697675,0.0000025813283,0.000032544165],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994243,0.000031785916,0.00024398741,0.00009514618,0.00014094479,0.00006386881],"domain_scores_gemma":[0.9991873,0.00013239245,0.00022813785,0.000035351397,0.0004002242,0.000016578577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039763574,0.000058514022,0.00008654449,0.00034597752,0.000047792913,0.00019316077,0.00015087097,0.000051260668,3.7427375e-7],"category_scores_gemma":[0.00051926426,0.00005385796,0.000026025298,0.00012546334,0.0000166221,0.00038756445,0.00003791654,0.00015284646,8.501301e-8],"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":[0.000070899005,0.00007398767,0.0032670554,0.00006886981,0.000035520156,0.000020801965,0.0014791129,0.029188246,0.010726532,0.018088488,0.00006976152,0.93691075],"study_design_scores_gemma":[0.0007109263,0.00013087013,0.003612254,0.00038000196,0.000009963287,0.000034259927,0.00021420083,0.9688017,0.011056672,0.014866063,0.00009172803,0.00009140267],"about_ca_topic_score_codex":0.000009533989,"about_ca_topic_score_gemma":0.000012243252,"teacher_disagreement_score":0.9396134,"about_ca_system_score_codex":0.00007023362,"about_ca_system_score_gemma":0.00003514413,"threshold_uncertainty_score":0.21962638},"labels":[],"label_agreement":null},{"id":"W4416371879","doi":"10.2316/j.2026.206-1229","title":"METHOD FOR GENERATING INSPECTION INSTRUCTIONS FOR POWER INTELLIGENT DISPATCHING ROBOTS BASED ON DIRECTED GRAPH MODEL. 111-123","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Cybersecurity and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Robot; Directed graph; Graph; Power (physics); Automation","score_opus":0.015042909321950751,"score_gpt":0.3050811006443613,"score_spread":0.29003819132241054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371879","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029101803,0.000024243342,0.9920366,0.0025409663,0.0020264192,0.00021939033,0.000010955751,0.00006798992,0.00016327781],"genre_scores_gemma":[0.41086757,0.000011469364,0.5885996,0.0003771901,0.00008819137,0.000013462488,0.000012045465,0.0000043402406,0.00002612048],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988831,0.000038716047,0.00057889073,0.00012230994,0.0002840145,0.00009294351],"domain_scores_gemma":[0.99835503,0.00023001626,0.00045497535,0.000089386995,0.0008311868,0.000039376002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060045376,0.00009796322,0.00014784955,0.0005309068,0.00020201354,0.00032347534,0.0002536853,0.000058020272,7.6653356e-7],"category_scores_gemma":[0.00015364787,0.000089518544,0.00012566418,0.0001769327,0.000012411818,0.0007388398,0.00003262458,0.00010201739,3.8626084e-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":[0.00002836935,0.00004204144,0.000039735136,0.000017381646,0.000052853888,2.403366e-7,0.00048538463,0.87292135,0.00036898445,0.098341845,0.00044670692,0.027255105],"study_design_scores_gemma":[0.0006211647,0.00009966702,0.00021408388,0.00016013223,0.000013529758,0.000014307707,0.00007693435,0.988822,0.0008742921,0.0084381895,0.0005848721,0.000080825834],"about_ca_topic_score_codex":0.0000056351905,"about_ca_topic_score_gemma":0.000007016861,"teacher_disagreement_score":0.4079574,"about_ca_system_score_codex":0.00011932338,"about_ca_system_score_gemma":0.000099991514,"threshold_uncertainty_score":0.36504602},"labels":[],"label_agreement":null},{"id":"W4416371885","doi":"10.2316/j.2026.206-1224","title":"ANGLE ERROR OBSERVER BASED-ADAPTIVE TRACKING CONTROL OF WHEELED MOBILE ROBOT WITH UNCERTAINTIES. 181-193","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mobile robot; Trajectory; Observer (physics); Control theory (sociology); Robot; Tracking (education); Tracking error","score_opus":0.006980356936023633,"score_gpt":0.22605517767412184,"score_spread":0.2190748207380982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416371885","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":[0.12171037,0.00080377195,0.8760037,0.00041704983,0.00060937036,0.00016074924,0.000016030734,0.000036442092,0.00024251237],"genre_scores_gemma":[0.9921298,0.000047143832,0.00765304,0.000057481873,0.00006012525,0.0000053300237,0.0000058129262,0.000011370749,0.000029893457],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908656,0.0000211761,0.00042453615,0.0000788751,0.0002868754,0.00010197557],"domain_scores_gemma":[0.9989423,0.00013141303,0.00022397215,0.00007045257,0.00059302436,0.000038812992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017964849,0.00011944357,0.00024749307,0.00023629071,0.00002740938,0.000057455138,0.00016211138,0.000055818622,0.000011550848],"category_scores_gemma":[0.00003155766,0.00010058108,0.000082557315,0.00009871313,0.00003740623,0.00025541836,0.000013601356,0.00012987632,4.5494676e-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":[0.00011318527,0.00005193474,0.0017005467,0.00003280026,0.00027217425,0.000010220022,0.00006620508,0.97804993,0.001635073,0.0015138029,0.000044169272,0.01650993],"study_design_scores_gemma":[0.002108257,0.00016148252,0.0150323715,0.00033711857,0.00007866402,0.0000146386155,0.00008970007,0.98108196,0.00042551884,0.00047467145,0.00009846011,0.00009715946],"about_ca_topic_score_codex":0.000012136944,"about_ca_topic_score_gemma":0.000026863818,"teacher_disagreement_score":0.87041944,"about_ca_system_score_codex":0.000095697185,"about_ca_system_score_gemma":0.00007428633,"threshold_uncertainty_score":0.4101577},"labels":[],"label_agreement":null},{"id":"W4416372073","doi":"10.2316/j.2026.206-1197","title":"A*-TEB: AN IMPROVED A* ALGORITHM BASED ON THE TEB STRATEGY FOR MULTI-ROBOT MOTION PLANNING. 41-53","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion (physics); Stability (learning theory); Noise (video); Feature (linguistics); Sequence (biology)","score_opus":0.03724951964160129,"score_gpt":0.30994532209041054,"score_spread":0.27269580244880925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416372073","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":[0.0066126683,0.00010001652,0.9913664,0.0007237819,0.00092592306,0.00014462374,0.000012011775,0.000034330165,0.00008024657],"genre_scores_gemma":[0.94393325,0.00003233561,0.05556528,0.00021139979,0.00016582059,0.000006379755,0.000019994019,0.00001337901,0.000052169322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992524,0.000024045094,0.00034184178,0.00008970487,0.00019187851,0.00010016565],"domain_scores_gemma":[0.99934334,0.00009778225,0.0001285957,0.00008421498,0.0003080915,0.000037998245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030344317,0.00011043527,0.000117189295,0.0001753218,0.00006865619,0.00015567496,0.00020450658,0.00006166459,0.000009689247],"category_scores_gemma":[0.000056247252,0.00008162371,0.00006192038,0.00006213179,0.000020286801,0.00018194642,0.000010391778,0.00014273443,8.7777147e-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":[0.000013837067,0.000051506166,0.000060524337,0.0000134649235,0.000058263948,0.000002628447,0.00006088142,0.8896411,0.0011993713,0.0018909437,0.00014737013,0.106860116],"study_design_scores_gemma":[0.00040704836,0.0001133431,0.0026359453,0.00011683138,0.000019673304,0.000007901427,0.00006569956,0.99290335,0.0026778178,0.00080272346,0.00017040389,0.00007926726],"about_ca_topic_score_codex":0.000004674339,"about_ca_topic_score_gemma":0.0000025177903,"teacher_disagreement_score":0.9373206,"about_ca_system_score_codex":0.00006488047,"about_ca_system_score_gemma":0.000032643908,"threshold_uncertainty_score":0.33285183},"labels":[],"label_agreement":null},{"id":"W4416372079","doi":"10.2316/j.2026.206-1201","title":"RESEARCH ON COOPERATIVE CONTROL METHOD OF MULTI-AGENT FORMATION FOR ENGINEERING VEHICLES. 54-63","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Control (management); Control system; Process (computing); Process control; Stability (learning theory); Component (thermodynamics)","score_opus":0.022000747116762174,"score_gpt":0.3318996526522823,"score_spread":0.3098989055355201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416372079","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":[0.027164241,0.00017736093,0.97135633,0.00043639995,0.00058435125,0.0001774555,0.000017911512,0.000014100055,0.00007187042],"genre_scores_gemma":[0.985794,0.000053731867,0.014003631,0.000023111315,0.00007603867,0.000008848203,0.000004790555,0.000007945853,0.000027909024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991518,0.000038510145,0.0004221985,0.00005245431,0.0002471973,0.000087830434],"domain_scores_gemma":[0.9987348,0.0002754616,0.00011408388,0.00004561177,0.0008033583,0.000026736067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007796927,0.00006920753,0.00016315625,0.0003528565,0.000030867683,0.000058260193,0.00011790959,0.00005008428,0.0000010767451],"category_scores_gemma":[0.00008908064,0.000062417515,0.000056492943,0.00009032221,0.000010018708,0.00014813174,0.000010489058,0.00012501018,4.5984717e-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":[0.000035514946,0.000028302311,0.000041528874,0.00005991836,0.00016420493,0.0000011740678,0.0001355612,0.9499862,0.014008002,0.017098187,0.000095511066,0.018345894],"study_design_scores_gemma":[0.0014860352,0.00008302353,0.0014119558,0.00023601827,0.000016957767,0.000008557605,0.00008019557,0.99379396,0.0022771792,0.00018860081,0.00037034863,0.000047181184],"about_ca_topic_score_codex":0.0000035314533,"about_ca_topic_score_gemma":0.0000023710613,"teacher_disagreement_score":0.9586297,"about_ca_system_score_codex":0.00011992067,"about_ca_system_score_gemma":0.00002512499,"threshold_uncertainty_score":0.25453123},"labels":[],"label_agreement":null},{"id":"W4416372086","doi":"10.2316/j.2026.206-1246","title":"MULTI-DIMENSIONAL FEATURE FUSION AND LAYER-INTERACTIVE ATTENTION REINFORCED FOR INSULATOR DETECTION IN REMOTE SENSING NETWORK. 73-84","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Sensor fusion; Insulator (electricity); Fusion; Remote sensing application","score_opus":0.009431016867172648,"score_gpt":0.2661095848053006,"score_spread":0.256678567938128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416372086","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":[0.06227383,0.000100892845,0.9341692,0.0015647864,0.0017247336,0.00012505498,0.0000024103952,0.000022828355,0.000016267251],"genre_scores_gemma":[0.8023133,0.000060228416,0.19717185,0.00017969076,0.00015830627,3.4562447e-7,0.00000750379,0.0000047617204,0.00010399899],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910384,0.00004557977,0.0003647369,0.00015621983,0.00021636712,0.00011327061],"domain_scores_gemma":[0.9988627,0.00013491177,0.00034964934,0.0000673269,0.0005435253,0.00004191458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034642892,0.00010180728,0.00014902955,0.00027995277,0.00010044052,0.0002096055,0.000116450115,0.000091909686,5.2614644e-7],"category_scores_gemma":[0.00009158898,0.0000942274,0.000060734907,0.00019820801,0.000017731832,0.00047369182,0.00007686364,0.00017697402,3.2050468e-7],"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":[0.0002315256,0.00003386583,0.0001170139,0.000021197378,0.00012954924,0.0000261895,0.00013885123,0.3750697,0.015370212,0.0026825648,0.0002817543,0.60589755],"study_design_scores_gemma":[0.0012600725,0.00007228908,0.01010921,0.00026447367,0.000012548432,0.00015694012,0.000027093407,0.9850993,0.00068881223,0.0018756118,0.0003521169,0.00008154112],"about_ca_topic_score_codex":0.000013997779,"about_ca_topic_score_gemma":0.000020977051,"teacher_disagreement_score":0.74003947,"about_ca_system_score_codex":0.00010713014,"about_ca_system_score_gemma":0.000034075307,"threshold_uncertainty_score":0.38424817},"labels":[],"label_agreement":null},{"id":"W4417062269","doi":"10.2316/j.2026.206-1295","title":"RESEARCH ON OPTIMISATION OF COUNTY-LEVEL URBAN EXPRESS DELIVERY USING A MULTI-STRATEGY IMPROVED GENETIC ALGORITHM","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Genetic algorithm; Path (computing); Distribution (mathematics); Distribution center; Stability (learning theory)","score_opus":0.07587368645534594,"score_gpt":0.3677128739842457,"score_spread":0.29183918752889976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417062269","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":[0.16636582,0.00017659989,0.83277863,0.00005399161,0.0004597285,0.00007438024,0.000013305853,0.000017916007,0.000059654372],"genre_scores_gemma":[0.53687114,0.000105735286,0.4629121,0.000010284505,0.000065359396,8.5518155e-7,0.0000035469325,0.000009085839,0.000021868816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988428,0.000095696676,0.0004961625,0.00008487266,0.0003759592,0.00010453038],"domain_scores_gemma":[0.9984794,0.000176871,0.00018621689,0.000075412354,0.001046907,0.00003519645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006484841,0.00008747467,0.00014304498,0.0005238105,0.00004650712,0.000082000784,0.00016870741,0.00007834305,0.000004633265],"category_scores_gemma":[0.00009387653,0.00008880822,0.000041827847,0.00018094857,0.000038574122,0.00017718774,0.000030081786,0.0001943462,3.3097098e-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":[0.0000132041205,0.000039804512,0.00020473551,0.000026515672,0.0000824868,0.000002726181,0.00010618864,0.94751805,0.016972246,0.00024910705,0.000037486996,0.03474745],"study_design_scores_gemma":[0.00062455196,0.000046729914,0.0062434003,0.0002354129,0.000019042336,0.000015060903,0.000118472264,0.9860005,0.0064640534,0.00014669026,0.00002150925,0.0000645734],"about_ca_topic_score_codex":0.000014445203,"about_ca_topic_score_gemma":7.1146053e-7,"teacher_disagreement_score":0.37050533,"about_ca_system_score_codex":0.00016482703,"about_ca_system_score_gemma":0.00008446621,"threshold_uncertainty_score":0.36214942},"labels":[],"label_agreement":null},{"id":"W7088357224","doi":"10.2316/j.2025.206-1272","title":"NEURAL NETWORK CONTROL OF A 2-DOF HELICOPTER SYSTEM WITH TIME-VARYING STATE CONSTRAINTS AND UNKNOWN INPUT HYSTERESIS, 593-605.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Science and Science Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"State (computer science); Artificial neural network; Control theory (sociology); Control (management); Control system; Stability (learning theory)","score_opus":0.010638400707996726,"score_gpt":0.28577777171044205,"score_spread":0.27513937100244534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7088357224","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":[0.94115156,0.00022828142,0.050540753,0.0053613367,0.0010705376,0.00016090533,0.000004093103,0.000014879048,0.0014676405],"genre_scores_gemma":[0.9979578,0.00004199099,0.001624137,0.00014174923,0.00012581373,9.435943e-7,8.8611273e-7,0.0000020355783,0.00010464216],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890834,0.000092023736,0.00033527345,0.00009338149,0.00045030747,0.000120674165],"domain_scores_gemma":[0.9987978,0.00016824012,0.00039511258,0.00004126602,0.0005374747,0.000060149505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009110256,0.00006274057,0.00014630712,0.00016140976,0.00015164989,0.00018652213,0.00017872873,0.000030895535,0.000008194261],"category_scores_gemma":[0.00009484574,0.000048746773,0.000026427704,0.00018168792,0.00029278605,0.00046255483,0.00001867663,0.00006680762,7.852157e-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":[0.00045848763,0.00028681275,0.18922536,0.00019874604,0.00061638927,0.000054831573,0.022192914,0.32618618,0.0057481737,0.17777914,0.0012011586,0.27605182],"study_design_scores_gemma":[0.0050227335,0.00057283376,0.18242402,0.0038051954,0.0002202509,0.00019019215,0.008926194,0.79048336,0.00071070687,0.0057643773,0.0013481796,0.0005319356],"about_ca_topic_score_codex":0.000055866298,"about_ca_topic_score_gemma":0.000038265993,"teacher_disagreement_score":0.4642972,"about_ca_system_score_codex":0.00006825663,"about_ca_system_score_gemma":0.0002549844,"threshold_uncertainty_score":0.19878356},"labels":[],"label_agreement":null},{"id":"W7093317959","doi":"10.2316/j.2025.206-1308","title":"DYNAMIC COMMUNITY DETECTION-DRIVEN FRAMEWORK FOR COLLABORATIVE PLANNING AND ADAPTIVE CONTROL OF UAV SWARMS","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Adaptive control; Control (management); Context (archaeology); Field (mathematics); Control system","score_opus":0.015211575960383136,"score_gpt":0.2932815697155661,"score_spread":0.278069993755183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7093317959","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":[0.057228446,0.00029137306,0.9404014,0.0014523467,0.00049016403,0.00008011266,0.0000037982522,0.000029316803,0.000023095254],"genre_scores_gemma":[0.723587,0.00001189879,0.27634707,0.000039106413,0.000008865543,0.0000011597981,3.328786e-7,0.0000016563524,0.0000029183927],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940467,0.000059910853,0.00027184052,0.000062688414,0.00014748545,0.00005339132],"domain_scores_gemma":[0.9981933,0.0006185312,0.00042587603,0.000080784084,0.0006654372,0.000016036136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030759283,0.00006132233,0.00014513756,0.00025835118,0.0001109547,0.000061020837,0.000358554,0.000057734516,1.4765577e-7],"category_scores_gemma":[0.0003572208,0.000057771616,0.000029685265,0.00011810262,0.00007530846,0.00021438667,0.000082785235,0.00018125695,6.732396e-8],"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":[0.00018949335,0.00015819441,0.0020141616,0.00006318237,0.0006136505,0.000007746584,0.005141398,0.33449316,0.00366307,0.5076462,0.00010966252,0.14590012],"study_design_scores_gemma":[0.00054632087,0.00023443319,0.007283032,0.0002829933,0.000016224287,0.000014588197,0.00034255235,0.88849694,0.000700742,0.10195957,0.000070727045,0.000051904586],"about_ca_topic_score_codex":0.000003119723,"about_ca_topic_score_gemma":0.0000031229365,"teacher_disagreement_score":0.66635853,"about_ca_system_score_codex":0.000072976865,"about_ca_system_score_gemma":0.00006594004,"threshold_uncertainty_score":0.23558582},"labels":[],"label_agreement":null},{"id":"W80327629","doi":"10.2316/journal.206.2009.3.206-3270","title":"INTERNAL REPRESENTATION OF THE ENVIRONMENT IN COGNITIVE ROBOTICS","year":2009,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Representation (politics); Artificial intelligence; Cognitive robotics; Computer science; Cognition; Robotics; Psychology; Robot; Neuroscience; Political science","score_opus":0.017317283841722236,"score_gpt":0.2809598773564247,"score_spread":0.26364259351470243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W80327629","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":[0.036775395,0.00004361922,0.9584441,0.0038527723,0.00051157945,0.0000737883,5.0095196e-7,0.000005853638,0.00029238776],"genre_scores_gemma":[0.9723266,0.00009857409,0.027345382,0.00013228122,0.000045108525,2.7728498e-7,0.0000011238121,0.0000025675574,0.000048125374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998693,0.000059653124,0.00052163086,0.00008939115,0.000557685,0.00007865436],"domain_scores_gemma":[0.9988947,0.000106190324,0.00066458434,0.00010113343,0.00020562524,0.000027803679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025881192,0.00007278437,0.00012499119,0.00017397755,0.000023589912,0.00008161936,0.0004948959,0.000035179055,0.000004116046],"category_scores_gemma":[0.00015790193,0.00005584634,0.00006315555,0.00012044933,0.00003738467,0.00043623926,0.00010014858,0.00015272776,0.0000011304658],"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":[0.000009840488,0.000048639562,0.007451946,0.0000022216884,0.000027912747,0.000007862943,0.00045265598,0.9599904,0.00068770925,0.011505368,0.000019692969,0.019795788],"study_design_scores_gemma":[0.00076134066,0.00016684091,0.1910892,0.00024535254,0.0000147047995,0.00007272929,0.0000707152,0.7996474,0.0022811028,0.005554956,0.0000205879,0.00007506172],"about_ca_topic_score_codex":0.000004627642,"about_ca_topic_score_gemma":6.4238304e-7,"teacher_disagreement_score":0.93555117,"about_ca_system_score_codex":0.00007145691,"about_ca_system_score_gemma":0.000036533642,"threshold_uncertainty_score":0.22773476},"labels":[],"label_agreement":null}]}