{"meta":{"query_hash":"7052225d0efb","filters":{"venue":"Cognitive intelligence and robotics"},"cohort_total":5,"direct_labels_cover":0,"predictions_cover":5,"exported":5,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/7052225d0efb","api":"https://metacan.xera.ac/api/v1/cohort?venue=Cognitive+intelligence+and+robotics"},"results":[{"id":"W3214202479","doi":"10.1007/978-981-16-7069-5","title":"Cognitively Inspired Video Text Processing","year":2021,"lang":"en","type":"book","venue":"Cognitive intelligence and robotics","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Psychology","score_opus":0.03984596163690346,"score_gpt":0.28424097996649167,"score_spread":0.2443950183295882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214202479","genre_codex":"methods","genre_gemma":"other","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":[0.0000044930066,0.005238547,0.8412099,0.0002716942,0.0003106234,0.0005833299,0.000053070682,0.00049124117,0.15183713],"genre_scores_gemma":[0.027742153,0.01897492,0.22547235,0.009375843,0.0027232503,0.00042670366,0.0010525597,0.00048456085,0.7137477],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964766,0.00014228161,0.0007802108,0.0013846844,0.00060742686,0.00060881674],"domain_scores_gemma":[0.9953114,0.00068655924,0.00048441335,0.00041266944,0.0028065138,0.0002984463],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003574205,0.000730804,0.0008188152,0.00044801834,0.00037880705,0.00078974344,0.00084183394,0.0006934774,0.00010627984],"category_scores_gemma":[0.0005332809,0.00074378663,0.00021770694,0.0004758841,0.0005963867,0.0007447419,0.000903087,0.0010406931,0.0003056619],"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":[0.0000098097835,0.00010539721,0.000011929423,0.0003123847,0.00010283214,0.0003390139,0.0006449688,0.000005785669,0.000020388105,0.008038675,0.003301254,0.9871076],"study_design_scores_gemma":[0.001769137,0.002929068,0.00038211074,0.05865854,0.0019755806,0.0022188956,0.0028855738,0.03896637,0.111500144,0.6461846,0.119528614,0.0130013665],"about_ca_topic_score_codex":0.0000044056073,"about_ca_topic_score_gemma":0.000008982653,"teacher_disagreement_score":0.9741062,"about_ca_system_score_codex":0.00013499918,"about_ca_system_score_gemma":0.001313459,"threshold_uncertainty_score":0.9995013},"labels":[],"label_agreement":null},{"id":"W4231251686","doi":"10.1007/978-981-32-9945-0_3","title":"Face Recognition","year":2019,"lang":"en","type":"book-chapter","venue":"Cognitive intelligence and robotics","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biometrics; Computer security; Authentication (law); Identification (biology); Computer science; Phone; Facial recognition system; Access control; Face (sociological concept); Field (mathematics); Internet privacy; Artificial intelligence; Pattern recognition (psychology)","score_opus":0.05963458351129151,"score_gpt":0.2661674054037441,"score_spread":0.20653282189245262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231251686","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011411586,0.0011037529,0.7135173,0.00028104344,0.0006754981,0.0004248651,0.00005489624,0.00012670155,0.28380457],"genre_scores_gemma":[0.022511484,0.024746541,0.032508057,0.0038879185,0.0006509657,0.00003838367,0.00071476423,0.00019437188,0.91474754],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998169,0.000027581216,0.00039285686,0.00076956034,0.0003341896,0.0003068096],"domain_scores_gemma":[0.9984552,0.00035855357,0.0002501018,0.0003364617,0.00044784762,0.0001518069],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014912852,0.00042417593,0.00039704697,0.0002271581,0.0001455081,0.00020164895,0.00041240072,0.00047251894,0.00023978451],"category_scores_gemma":[0.000071402384,0.0003970734,0.0001382191,0.00006502025,0.00015547735,0.00042871243,0.0003715256,0.000559324,0.0050263694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021337086,0.000039952116,0.000008205851,0.00014261607,0.00009863697,0.000058913978,0.00042432392,0.00020339618,0.000024515726,0.07274173,0.0014200585,0.9248163],"study_design_scores_gemma":[0.000824584,0.0015987833,0.00006792909,0.01217086,0.0005909972,0.00037345506,0.00093701517,0.045172226,0.0116272075,0.8613046,0.060291916,0.00504046],"about_ca_topic_score_codex":0.0000029020155,"about_ca_topic_score_gemma":0.0000033583901,"teacher_disagreement_score":0.91977584,"about_ca_system_score_codex":0.000029990126,"about_ca_system_score_gemma":0.0001202794,"threshold_uncertainty_score":0.9998481},"labels":[],"label_agreement":null},{"id":"W4232427071","doi":"10.1007/978-981-32-9945-0_5","title":"Fingerprint Classification","year":2019,"lang":"en","type":"book-chapter","venue":"Cognitive intelligence and robotics","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biometrics; Fingerprint (computing); Consistency (knowledge bases); Impression; Reliability (semiconductor); Artificial intelligence; Computer science; Pattern recognition (psychology); Mathematics; World Wide Web; Physics","score_opus":0.08498569158122893,"score_gpt":0.28745897260911957,"score_spread":0.20247328102789064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232427071","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003032175,0.0010193405,0.8072372,0.00041998373,0.00058204203,0.00024592035,0.000013615768,0.00006849436,0.19041036],"genre_scores_gemma":[0.1268626,0.010592842,0.019485915,0.0013317709,0.0002737754,0.000012442117,0.00015498603,0.00006585329,0.84121984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985775,0.000018578128,0.0003410287,0.00060060865,0.0002860072,0.00017627429],"domain_scores_gemma":[0.99853027,0.00026359537,0.000235282,0.00041545942,0.00045698634,0.00009841844],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00020656399,0.00023853735,0.00024819712,0.00036315605,0.000107654145,0.00022825914,0.0004963547,0.00030690865,0.00008811008],"category_scores_gemma":[0.000094892326,0.00023112941,0.000089095534,0.00014355149,0.00017065382,0.00016913524,0.0002808593,0.00037439453,0.0013887062],"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":[0.0000018892791,0.000015866322,0.000016485707,0.00003374015,0.000025509236,0.000004445508,0.00015043635,0.000010174434,0.000005122777,0.7710426,0.00019543362,0.22849832],"study_design_scores_gemma":[0.0004125758,0.0005565548,0.0035884145,0.0020203271,0.00035753995,0.0001436119,0.0004547468,0.18480752,0.0016964658,0.48936164,0.31293517,0.003665398],"about_ca_topic_score_codex":0.0000027220058,"about_ca_topic_score_gemma":0.0000027522985,"teacher_disagreement_score":0.7877513,"about_ca_system_score_codex":0.00004378878,"about_ca_system_score_gemma":0.0001428875,"threshold_uncertainty_score":0.9993888},"labels":[],"label_agreement":null},{"id":"W4241463658","doi":"10.1007/978-981-32-9945-0_7","title":"Conclusion","year":2019,"lang":"en","type":"book-chapter","venue":"Cognitive intelligence and robotics","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biometrics; Computer science; Artificial intelligence; Pattern recognition (psychology)","score_opus":0.04339881004719913,"score_gpt":0.26788542113882735,"score_spread":0.2244866110916282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241463658","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000017631023,0.0018346782,0.6027528,0.00018967857,0.0008095601,0.00035324477,0.000018206645,0.000078588804,0.3939615],"genre_scores_gemma":[0.046673145,0.0069465847,0.007419523,0.0018080188,0.0006902178,0.000011967133,0.00008748979,0.00010098433,0.9362621],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998276,0.000031079544,0.0004061577,0.0006686682,0.00036094687,0.00025717163],"domain_scores_gemma":[0.99823594,0.00048101583,0.00024727016,0.00034729159,0.00053784775,0.00015063773],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00020423598,0.00038006902,0.00046429515,0.0001894155,0.0001332426,0.00017019875,0.00045121825,0.00042038236,0.00007941965],"category_scores_gemma":[0.000059351994,0.00033345743,0.0001242302,0.000058012403,0.0001619054,0.00020422741,0.0005502515,0.00045232003,0.0025498075],"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":[0.000007998856,0.000019685149,0.000024435896,0.00014059039,0.000108101034,0.000098587545,0.00051840703,0.00007408569,0.000008059087,0.6285693,0.0004969281,0.36993384],"study_design_scores_gemma":[0.0011487585,0.0021007154,0.00013963807,0.016776964,0.0006756323,0.0014454542,0.0006919022,0.030644666,0.0033100415,0.49718803,0.43936616,0.0065120375],"about_ca_topic_score_codex":0.0000021567398,"about_ca_topic_score_gemma":0.0000046528967,"teacher_disagreement_score":0.5953333,"about_ca_system_score_codex":0.000032847023,"about_ca_system_score_gemma":0.00016811505,"threshold_uncertainty_score":0.9999117},"labels":[],"label_agreement":null},{"id":"W4251447660","doi":"10.1007/978-981-32-9945-0_4","title":"Expression Recognition","year":2019,"lang":"en","type":"book-chapter","venue":"Cognitive intelligence and robotics","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Biology; Artificial intelligence","score_opus":0.10086055483611034,"score_gpt":0.3291133787910924,"score_spread":0.2282528239549821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251447660","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009410486,0.0017937135,0.038728405,0.00009697316,0.0021630104,0.00069485727,0.00017787474,0.000107857224,0.9561432],"genre_scores_gemma":[0.027363531,0.0042131306,0.00070662267,0.0010281424,0.0006732576,0.000024001074,0.0010817981,0.0001419524,0.9647676],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983254,0.000051693332,0.00044195808,0.00067218434,0.00021875648,0.00029001565],"domain_scores_gemma":[0.99858856,0.0003305757,0.0002941862,0.00022056962,0.00042182876,0.0001442706],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00015308379,0.00041955445,0.00040225303,0.00025394658,0.00011926596,0.00004731053,0.0001108701,0.0007725372,0.008134307],"category_scores_gemma":[0.000059131467,0.00039846372,0.00015885271,0.00003562064,0.00023288536,0.00009517677,0.000090031346,0.0006733028,0.012979883],"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":[0.00020453635,0.00014690997,0.000043166012,0.00018176243,0.00025563274,0.000098904966,0.0011032801,0.000011296548,0.000056104655,0.06185824,0.004044872,0.9319953],"study_design_scores_gemma":[0.0038235763,0.0053008813,0.0011535456,0.030673763,0.0039184284,0.0013416031,0.01116899,0.00041596324,0.011787264,0.7392533,0.18162315,0.009539593],"about_ca_topic_score_codex":0.0000038753756,"about_ca_topic_score_gemma":0.0000060485972,"teacher_disagreement_score":0.9224557,"about_ca_system_score_codex":0.000028605988,"about_ca_system_score_gemma":0.00005310066,"threshold_uncertainty_score":0.9998467},"labels":[],"label_agreement":null}]}