{"meta":{"query_hash":"7b2a3eba743a","filters":{"venue":"International Journal of Intelligent Systems"},"cohort_total":33,"direct_labels_cover":0,"predictions_cover":33,"exported":33,"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/7b2a3eba743a","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Intelligent+Systems"},"results":[{"id":"W13093665","doi":"10.1042/bj0550204","title":"Toward better scoring metrics for pseudo-independent models: Research Articles","year":2004,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Guelph","funders":"","keywords":"Computer science; Heuristic; Dimension (graph theory); Artificial intelligence; Hypercube; Domain (mathematical analysis); Perspective (graphical); Machine learning; Theoretical computer science; Algorithm; Mathematics; Combinatorics","score_opus":0.26153605443513944,"score_gpt":0.38425387352950996,"score_spread":0.12271781909437052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W13093665","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013728003,0.0076981196,0.9728386,0.0022666256,0.00014852219,0.000069820104,0.00012000743,0.00026647752,0.0028638393],"genre_scores_gemma":[0.2790957,0.010467512,0.7014927,0.0008662728,0.0013586468,0.00035654337,0.0010096865,0.00078766,0.0045651523],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9869141,0.008579929,0.0005581887,0.001618605,0.002005938,0.00032323512],"domain_scores_gemma":[0.9202051,0.0598479,0.0037847054,0.0070012948,0.0076623945,0.0014985803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015868302,0.0026522875,0.002552324,0.00501328,0.0011639682,0.004427186,0.0035706565,0.0042308057,0.0036877512],"category_scores_gemma":[0.09515761,0.0014460022,0.0018659587,0.005834988,0.0031937335,0.01476274,0.004480783,0.0061765388,0.0013315305],"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":[0.00015691012,0.00036994822,0.0033999032,0.0006269898,0.000247347,0.00007512385,0.00040628208,0.27466622,0.0011923121,0.39463443,0.011882016,0.3123426],"study_design_scores_gemma":[0.000017336431,0.00008492269,0.00045636646,0.00009780612,0.000024009392,0.000075983786,0.000052265143,0.656727,0.00039325227,0.33730292,0.0047251,0.000042935466],"about_ca_topic_score_codex":0.0035793926,"about_ca_topic_score_gemma":0.0024110922,"teacher_disagreement_score":0.015868302,"about_ca_system_score_codex":0.0032562779,"about_ca_system_score_gemma":0.0017578773,"threshold_uncertainty_score":0.0839206},"labels":[],"label_agreement":null},{"id":"W1979980829","doi":"10.1002/int.20476","title":"Alternative approach for learning and improving the MCDA method PROAFTN","year":2011,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Machine learning; Artificial intelligence; Preprocessor; Data pre-processing; Multiple-criteria decision analysis; Data mining; Construct (python library); Measure (data warehouse); Mathematics; Mathematical optimization","score_opus":0.07620748980444986,"score_gpt":0.32182830837970583,"score_spread":0.24562081857525597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979980829","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029094247,0.000083014966,0.99608576,0.00007188671,0.000022512166,0.000039176528,0.0000228727,0.00010521212,0.00066016614],"genre_scores_gemma":[0.07352471,0.00009083677,0.92538065,0.00007335191,0.000029660972,0.00012551145,0.0000974397,0.000030560685,0.0006473614],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99610007,0.0017213204,0.00025612878,0.00061638234,0.0011921419,0.00011394699],"domain_scores_gemma":[0.99349135,0.0035517062,0.0003252156,0.0007622939,0.0017695607,0.00009986759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049860748,0.000707034,0.0011467334,0.0026581595,0.000653695,0.0013659591,0.0022999002,0.0011089367,0.0042257244],"category_scores_gemma":[0.016125381,0.00045073387,0.00093894853,0.0022339,0.00089333375,0.0020295554,0.0017793544,0.0018439298,0.0008285788],"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":[0.00021601592,0.00020076225,0.0028397576,0.00046995675,0.00014559664,0.00009394089,0.00046791608,0.2327269,0.0047979495,0.075809695,0.0028595664,0.6793719],"study_design_scores_gemma":[0.000035102545,0.000068671034,0.00042704845,0.000041719464,0.000018719875,0.000094039395,0.00006110536,0.96589714,0.0024960798,0.025045052,0.0057903654,0.0000249375],"about_ca_topic_score_codex":0.0028856944,"about_ca_topic_score_gemma":0.004390156,"teacher_disagreement_score":0.0049860748,"about_ca_system_score_codex":0.000970361,"about_ca_system_score_gemma":0.0014464526,"threshold_uncertainty_score":0.026369214},"labels":[],"label_agreement":null},{"id":"W2002910581","doi":"10.1002/int.1031","title":"Conceptual design of fuzzy object-oriented databases using extended entity-relationship model","year":2001,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Conceptual schema; Entity–relationship model; Fuzzy logic; Database schema; Database design; Data mining; Conceptual model; Relational database; Schema (genetic algorithms); Database; Fuzzy set; Imperfect; Object (grammar); Database model; Information retrieval; Artificial intelligence","score_opus":0.1350884247380204,"score_gpt":0.3359440521008348,"score_spread":0.20085562736281437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002910581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009371331,0.0006106476,0.98570466,0.00045449164,0.00006794544,0.00013560626,0.000077915654,0.0002526213,0.0033247515],"genre_scores_gemma":[0.123462856,0.000937984,0.87267846,0.00023591543,0.000052625594,0.00023176472,0.00031960921,0.000038454666,0.0020422593],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979328,0.0006064881,0.00031742523,0.00027276092,0.00076247944,0.000108165485],"domain_scores_gemma":[0.9986129,0.00031383228,0.00017460434,0.00026153063,0.0005014382,0.00013565793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036701963,0.00031792195,0.0005380751,0.0011609929,0.00071526313,0.0042442586,0.0020217656,0.0010962852,0.0016100139],"category_scores_gemma":[0.0052283676,0.00043341887,0.0009178004,0.0015007512,0.0010492571,0.004465369,0.0015047066,0.0009315703,0.00050951046],"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":[0.00007611592,0.00007811336,0.00071643636,0.00030888745,0.00007779398,0.00049766834,0.0011244955,0.028016604,0.006327982,0.86215615,0.003173053,0.097446606],"study_design_scores_gemma":[0.0001229751,0.0001645686,0.00065665646,0.00025586342,0.00019811445,0.0011442755,0.00078307604,0.37869912,0.009766212,0.4696217,0.13847902,0.00010836598],"about_ca_topic_score_codex":0.0012752624,"about_ca_topic_score_gemma":0.0011546039,"teacher_disagreement_score":0.0042442586,"about_ca_system_score_codex":0.0008097552,"about_ca_system_score_gemma":0.0012277745,"threshold_uncertainty_score":0.019410133},"labels":[],"label_agreement":null},{"id":"W2041926928","doi":"10.1002/1098-111x(200011)15:11<1015::aid-int3>3.0.co;2-9","title":"Granular worlds: Representation and communication problems","year":2000,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Space Agency; University of Alberta","funders":"","keywords":"Granular computing; Granularity; Computer science; Rough set; Possible world; Theoretical computer science; Probabilistic logic; Representation (politics); Interoperability; Artificial intelligence; Epistemology; World Wide Web","score_opus":0.027624800744125867,"score_gpt":0.28333172015030306,"score_spread":0.2557069194061772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041926928","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010186913,0.0058187386,0.92199516,0.021382695,0.0004894449,0.00020460133,0.00031749968,0.00019430675,0.03941053],"genre_scores_gemma":[0.49991786,0.01114842,0.465711,0.0031106567,0.0022794758,0.0013482812,0.0007935942,0.00020262838,0.015488016],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99165475,0.0042898348,0.00064234185,0.001275481,0.0015576232,0.0005800015],"domain_scores_gemma":[0.9799753,0.014741743,0.0013556952,0.0022123086,0.0011031725,0.0006118376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008137888,0.0010814293,0.0016674513,0.002894292,0.003670831,0.014513336,0.0032328086,0.007389547,0.007653993],"category_scores_gemma":[0.029395947,0.0010453082,0.0020761606,0.0046969387,0.012230491,0.028656533,0.0077148057,0.00637747,0.0008916448],"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":[0.000007038499,0.000004727732,0.00004804902,0.000035788,0.000007635257,0.00006759584,0.00020493029,0.0017283781,0.000032824104,0.9930577,0.00066602416,0.004139301],"study_design_scores_gemma":[0.000006003852,0.000004140108,0.000030322495,0.000030516896,0.000005715202,0.00006280972,0.00016339777,0.005554814,0.000046904424,0.98812175,0.0059648813,0.0000087549515],"about_ca_topic_score_codex":0.0027736523,"about_ca_topic_score_gemma":0.0009739445,"teacher_disagreement_score":0.014513336,"about_ca_system_score_codex":0.0038780607,"about_ca_system_score_gemma":0.0016393072,"threshold_uncertainty_score":0.043037772},"labels":[],"label_agreement":null},{"id":"W2079838695","doi":"10.1002/int.20072","title":"An approach to measure the robustness of fuzzy reasoning","year":2005,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Robustness (evolution); Fuzzy logic; Computer science; Artificial intelligence; Fuzzy control system; Machine learning","score_opus":0.18220406777295975,"score_gpt":0.427996754052197,"score_spread":0.24579268627923725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079838695","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01442476,0.00082888943,0.97996646,0.0003231461,0.000093202056,0.00013889263,0.0001283915,0.0001835358,0.0039126403],"genre_scores_gemma":[0.5567278,0.00087363704,0.4395096,0.0003392581,0.0003893098,0.00044889053,0.0002463828,0.00008682667,0.001378266],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9875738,0.0043010158,0.001164577,0.0017298562,0.0048780954,0.00035264235],"domain_scores_gemma":[0.9659751,0.023405083,0.003914382,0.0033665986,0.0028784678,0.00046033156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011992477,0.0017840186,0.001322819,0.006661509,0.00081786106,0.003704107,0.0022489533,0.0027490533,0.0019585653],"category_scores_gemma":[0.043678522,0.00052766624,0.002868776,0.0031263002,0.003852795,0.0067925146,0.0031242676,0.003156709,0.00045538577],"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":[0.000557758,0.00024956267,0.0059039886,0.00089452666,0.0014013684,0.000601689,0.0012380165,0.2550244,0.041978482,0.5317086,0.0015494355,0.1588921],"study_design_scores_gemma":[0.00003776892,0.00062957476,0.0050109685,0.0001948557,0.00022275196,0.00069080904,0.00028494513,0.5636491,0.0233018,0.39957282,0.006187233,0.000217427],"about_ca_topic_score_codex":0.00053640903,"about_ca_topic_score_gemma":0.00023055881,"teacher_disagreement_score":0.011992477,"about_ca_system_score_codex":0.0018595257,"about_ca_system_score_gemma":0.0006755408,"threshold_uncertainty_score":0.06342298},"labels":[],"label_agreement":null},{"id":"W2086262313","doi":"10.1002/int.20491","title":"Evidential reasoning using extended fuzzy Dempster-Shafer theory for handling various facets of information deficiency","year":2011,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vagueness; Dempster–Shafer theory; Fuzzy logic; Data mining; Artificial intelligence; Computer science; Ambiguity; Belief structure; Ignorance; Fuzzy set operations; Fuzzy set; Machine learning; Mathematics","score_opus":0.2264374948042466,"score_gpt":0.4315268378480013,"score_spread":0.20508934304375467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086262313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075931237,0.0005108421,0.9896131,0.00026578954,0.000026972279,0.000041655498,0.000021263051,0.000023951307,0.0019033159],"genre_scores_gemma":[0.4872857,0.0012341277,0.509728,0.00015816173,0.00014028637,0.00021022197,0.00008231484,0.00001408926,0.0011470515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99530125,0.0021861175,0.00042759237,0.00038382868,0.0015596248,0.0001415168],"domain_scores_gemma":[0.99056727,0.0067250854,0.0008832163,0.00078895513,0.000888493,0.00014696411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012966541,0.0013750532,0.0018027794,0.003880482,0.0009780243,0.0028977243,0.0020061207,0.0019804274,0.001509466],"category_scores_gemma":[0.023320042,0.00058398856,0.0021810576,0.0026332901,0.0027877898,0.0061194478,0.0026518698,0.002272868,0.00021570454],"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":[0.00007815871,0.00006181353,0.00090149965,0.00042022337,0.00023392521,0.000607556,0.0006913715,0.28175107,0.0016942652,0.65156746,0.0007934699,0.06119908],"study_design_scores_gemma":[0.000031868338,0.000053585914,0.0002040703,0.00008063624,0.000059900565,0.0001637913,0.00007533145,0.5298533,0.0008964569,0.46722367,0.0013177786,0.000039647097],"about_ca_topic_score_codex":0.001375521,"about_ca_topic_score_gemma":0.0014639087,"teacher_disagreement_score":0.012966541,"about_ca_system_score_codex":0.0019008078,"about_ca_system_score_gemma":0.0012819513,"threshold_uncertainty_score":0.06857443},"labels":[],"label_agreement":null},{"id":"W2126397666","doi":"10.1002/int.20247","title":"Pyramid collaborative filtering technique for an intelligent autonomous guide agent","year":2007,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Collaborative filtering; Credibility; Pyramid (geometry); The Internet; Task (project management); Filter (signal processing); Artificial intelligence; Human–computer interaction; Domain (mathematical analysis); Intelligent agent; World Wide Web; Recommender system; Computer vision","score_opus":0.04121726241789809,"score_gpt":0.34761656320555295,"score_spread":0.30639930078765487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126397666","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050443206,0.0000772503,0.99290365,0.00011746272,0.000023715236,0.00005319289,0.000019700112,0.0005078636,0.0012528682],"genre_scores_gemma":[0.24462843,0.0001811445,0.747957,0.00016661907,0.00006067187,0.00019831028,0.00013918267,0.000053750708,0.006614822],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974566,0.0005394404,0.00012067416,0.00054015144,0.0011511466,0.00019204943],"domain_scores_gemma":[0.9975061,0.0010084122,0.00018036472,0.0004845281,0.0006630487,0.00015757066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003212112,0.00074497715,0.0013697109,0.0017549068,0.0015174341,0.0013249568,0.0023525793,0.002467903,0.0027120202],"category_scores_gemma":[0.005543126,0.00054292264,0.0013113125,0.001289168,0.0009894472,0.0027891635,0.0014635023,0.001567938,0.0011271079],"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":[0.00047083624,0.0005094003,0.0039995075,0.00027144112,0.00032719978,0.0006536265,0.0018225131,0.2314525,0.026380602,0.12182764,0.010168138,0.60211664],"study_design_scores_gemma":[0.00004654682,0.00012319602,0.0004293719,0.000010304271,0.00006057132,0.00019042617,0.00005736304,0.97239417,0.0034699263,0.01366576,0.009515014,0.000037289374],"about_ca_topic_score_codex":0.014553267,"about_ca_topic_score_gemma":0.0126329465,"teacher_disagreement_score":0.014553267,"about_ca_system_score_codex":0.0014419106,"about_ca_system_score_gemma":0.0015514118,"threshold_uncertainty_score":0.028937161},"labels":[],"label_agreement":null},{"id":"W2800627592","doi":"10.1002/int.21995","title":"Generating Z-number based on OWA weights using maximum entropy","year":2018,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Decision maker; Principle of maximum entropy; Entropy (arrow of time); Mathematics; Preference; Mathematical optimization; Computer science; Operations research; Statistics","score_opus":0.17793564038136858,"score_gpt":0.4494769802438753,"score_spread":0.2715413398625067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800627592","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008438814,0.000117478136,0.9898863,0.00005925803,0.00003346163,0.000054234766,0.000028903229,0.000108319065,0.0012733125],"genre_scores_gemma":[0.33651766,0.0003940214,0.66028416,0.00008563645,0.00008038028,0.00035332114,0.00021121191,0.00012985796,0.0019437964],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99775547,0.00077657995,0.00017786266,0.00034751263,0.0007814911,0.00016124382],"domain_scores_gemma":[0.99656653,0.002056388,0.00028630375,0.0003297225,0.0006655155,0.0000954825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027524685,0.0011667056,0.0011704235,0.0025198825,0.00091993087,0.0014984201,0.0009955695,0.00074320554,0.0036063248],"category_scores_gemma":[0.011520861,0.00041166772,0.0010947906,0.001907161,0.00095396925,0.0037206092,0.0015404578,0.0009664048,0.00072683825],"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":[0.0003883049,0.000120912206,0.002549923,0.0005209615,0.00014458041,0.00026301024,0.00041765926,0.30164337,0.020477552,0.13115077,0.002342008,0.539981],"study_design_scores_gemma":[0.000039862527,0.00010959556,0.00076561235,0.00006317946,0.000047382142,0.00015271966,0.00007013038,0.89013016,0.007934263,0.09746593,0.0031582823,0.000062879946],"about_ca_topic_score_codex":0.00079219707,"about_ca_topic_score_gemma":0.00064702384,"teacher_disagreement_score":0.0036063248,"about_ca_system_score_codex":0.00069486117,"about_ca_system_score_gemma":0.00077159976,"threshold_uncertainty_score":0.014556587},"labels":[],"label_agreement":null},{"id":"W2972580158","doi":"10.1002/int.22120","title":"Synthetic minority oversampling for function approximation problems","year":2019,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Oversampling; Categorical variable; Computer science; Artificial intelligence; Machine learning; Function approximation; Preprocessor; Benchmark (surveying); Function (biology); Data mining; Mathematics; Algorithm; Artificial neural network","score_opus":0.030057870587504226,"score_gpt":0.27872686520023826,"score_spread":0.24866899461273403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972580158","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06908451,0.0008444212,0.92698437,0.00046001832,0.00013869282,0.000116607225,0.0001836355,0.0006393245,0.0015484238],"genre_scores_gemma":[0.73755485,0.00043589182,0.25781143,0.0003595122,0.00025335173,0.0002793472,0.0012935041,0.00010299284,0.0019090954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987458,0.0005539221,0.00006242889,0.00019527951,0.0003593559,0.00008323864],"domain_scores_gemma":[0.9967079,0.0018677785,0.0002938365,0.0005021155,0.0005024556,0.00012585048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003668664,0.00085124874,0.0010475138,0.0009068561,0.00059774827,0.00078921136,0.0010053014,0.00083640346,0.00078939385],"category_scores_gemma":[0.009986219,0.00025317713,0.00074164296,0.00066921586,0.00069577264,0.0010013111,0.001225247,0.0013075791,0.00030976415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007117057,0.00036057894,0.009532412,0.0002765791,0.00014331422,0.00023412514,0.0002869357,0.6424452,0.0109719215,0.024359586,0.0087603815,0.30191728],"study_design_scores_gemma":[0.0000107164415,0.00004883836,0.00044504384,0.000009664009,0.0000061438836,0.00003582074,0.000018349807,0.9906578,0.0020588024,0.005640545,0.0010643069,0.000004047064],"about_ca_topic_score_codex":0.0016207674,"about_ca_topic_score_gemma":0.0018062693,"teacher_disagreement_score":0.003668664,"about_ca_system_score_codex":0.000683266,"about_ca_system_score_gemma":0.0006312961,"threshold_uncertainty_score":0.019401968},"labels":[],"label_agreement":null},{"id":"W2998229105","doi":"10.1002/int.22213","title":"A normal wiggly hesitant fuzzy linguistic projection‐based multiattributive border approximation area comparison method","year":2020,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Measure (data warehouse); Projection (relational algebra); Representation (politics); Set (abstract data type); Computer science; Rule-based machine translation; Term (time); Fuzzy logic; Artificial intelligence; Score; Fuzzy set; Scale (ratio); Function (biology); Mathematics; Algorithm; Data mining; Machine learning","score_opus":0.25908008157913953,"score_gpt":0.4883926337511811,"score_spread":0.22931255217204155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998229105","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009601794,0.00015976685,0.9875371,0.000081406906,0.000029237226,0.00007553662,0.00003883667,0.0001529333,0.0023234512],"genre_scores_gemma":[0.4040533,0.0002949094,0.591506,0.000092735,0.000052550404,0.00032707938,0.0002135122,0.00006686494,0.003393134],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961572,0.0011899481,0.00022717565,0.00069578225,0.0015624525,0.00016751922],"domain_scores_gemma":[0.9982072,0.00054300285,0.00015098833,0.00015578656,0.0008608193,0.00008216682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028699997,0.0007802994,0.0010191037,0.0023216764,0.0007572875,0.00221122,0.0018512664,0.0008788653,0.00308259],"category_scores_gemma":[0.0067622107,0.00032462954,0.0011690385,0.0023654397,0.0010560885,0.0038067573,0.0018517306,0.0012919515,0.00046529688],"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":[0.00031048068,0.00016710152,0.003898308,0.0003687556,0.00024160965,0.00038061064,0.0011811499,0.21623802,0.012437991,0.14218423,0.0033499473,0.6192418],"study_design_scores_gemma":[0.00002487124,0.000111731664,0.0010367975,0.00004061449,0.00004820032,0.00022825932,0.0001982013,0.9474627,0.0060345433,0.040836867,0.003910768,0.00006643042],"about_ca_topic_score_codex":0.0025083213,"about_ca_topic_score_gemma":0.0012859502,"teacher_disagreement_score":0.00308259,"about_ca_system_score_codex":0.0010637429,"about_ca_system_score_gemma":0.0017072009,"threshold_uncertainty_score":0.015178144},"labels":[],"label_agreement":null},{"id":"W3167071550","doi":"10.1002/int.22531","title":"Intelligent optimization for charging scheduling of electric vehicle using exponential Harris Hawks technique","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheduling (production processes); Schedule; Exponential function; Renewable energy; Electric vehicle; Mathematical optimization; Automotive engineering; Electrical engineering; Engineering; Mathematics","score_opus":0.0159643605403183,"score_gpt":0.25662334842883283,"score_spread":0.24065898788851453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167071550","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038806904,0.00030654258,0.9556619,0.00013947014,0.00005552339,0.000051508425,0.000032125034,0.00012208793,0.004823917],"genre_scores_gemma":[0.9199991,0.00029360474,0.074997604,0.00007515052,0.000032555246,0.00010404681,0.000066794244,0.000041952568,0.00438908],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999782,0.000059267317,0.000010010635,0.00004568159,0.000062621104,0.000040453437],"domain_scores_gemma":[0.99979323,0.000099624565,0.000028720622,0.000008486358,0.00005687453,0.00001312265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004844019,0.00054329407,0.0005896408,0.00040258653,0.00032194718,0.00051195355,0.00056649843,0.00042270045,0.0016538878],"category_scores_gemma":[0.00083821587,0.0003211382,0.00055416767,0.00044349124,0.00041907904,0.00051595276,0.0004706893,0.00042049083,0.00014252316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019714871,0.0000141145565,0.00039219443,0.000021587086,0.000015104157,0.000025427702,0.000018937666,0.98442286,0.0007909972,0.0030256435,0.00030793104,0.010945407],"study_design_scores_gemma":[0.0000024280394,0.000009042683,0.00005625028,9.985315e-7,0.0000021568178,0.0000030940218,0.000004431483,0.9991424,0.0000945023,0.00058657106,0.0000965917,0.0000015590008],"about_ca_topic_score_codex":0.0071901996,"about_ca_topic_score_gemma":0.0048848237,"teacher_disagreement_score":0.0071901996,"about_ca_system_score_codex":0.0006941103,"about_ca_system_score_gemma":0.0009794006,"threshold_uncertainty_score":0.0142967105},"labels":[],"label_agreement":null},{"id":"W3170466384","doi":"10.1002/int.22473","title":"A novel method based on probabilistic linguistic term sets and its application in ranking products through online ratings","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ranking (information retrieval); Probabilistic logic; Term (time); Computer science; Decision maker; Selection (genetic algorithm); Prospect theory; Artificial intelligence; Machine learning; Data mining; Mathematics; Operations research","score_opus":0.190004953955526,"score_gpt":0.471015128163082,"score_spread":0.28101017420755603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170466384","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053395717,0.00016611435,0.99256814,0.00009537207,0.00005319485,0.000102518155,0.00006142598,0.0001733238,0.0014403487],"genre_scores_gemma":[0.23041087,0.00044125307,0.76557446,0.00011941126,0.00013585428,0.00055233727,0.00028400094,0.000063743304,0.0024180692],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946397,0.0017576887,0.00045221386,0.0007940177,0.0021666691,0.0001897283],"domain_scores_gemma":[0.99667466,0.0016667972,0.00030298263,0.00019518666,0.0010435556,0.00011681255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036512685,0.0012332652,0.001364095,0.0045502717,0.0009300378,0.002014489,0.00191816,0.0011212854,0.0029316144],"category_scores_gemma":[0.0107927,0.00046283292,0.0016568983,0.0036349092,0.0008585713,0.0029537277,0.0014649894,0.0014251411,0.0005579064],"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":[0.00027167014,0.0002705105,0.0037624761,0.0007768697,0.00029289201,0.00023718893,0.0006567155,0.15832125,0.010229885,0.07873991,0.004487466,0.7419532],"study_design_scores_gemma":[0.000032562046,0.00013407037,0.0009400116,0.00004268147,0.00006546074,0.00013018088,0.00010377895,0.97508246,0.0020892215,0.018739987,0.0025628123,0.000076789285],"about_ca_topic_score_codex":0.0049211397,"about_ca_topic_score_gemma":0.0040229424,"teacher_disagreement_score":0.0049211397,"about_ca_system_score_codex":0.0011553196,"about_ca_system_score_gemma":0.0018301569,"threshold_uncertainty_score":0.019309938},"labels":[],"label_agreement":null},{"id":"W3171436672","doi":"10.1002/int.22493","title":"Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Automation; Cloud computing; Computer science; Process (computing); Fault (geology); Software deployment; Manufacturing engineering; Machining; Systems engineering; Engineering; Software engineering; Mechanical engineering","score_opus":0.02158188550714101,"score_gpt":0.28915211068924546,"score_spread":0.26757022518210444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171436672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14024328,0.0005418485,0.85318226,0.00027400686,0.00010996745,0.000057845577,0.00015629035,0.0030488614,0.0023856289],"genre_scores_gemma":[0.95581555,0.00009442006,0.042041425,0.00008303452,0.000021217553,0.000026516936,0.00015535987,0.000026734648,0.0017358436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998104,0.000020001105,0.000009955357,0.000053466345,0.00006573037,0.00004045273],"domain_scores_gemma":[0.9997638,0.000066468536,0.00003711649,0.00003034133,0.00008435047,0.000018004213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002911676,0.0006289293,0.00037815544,0.0005994307,0.00021323556,0.000439788,0.0008119959,0.0007422072,0.0015285122],"category_scores_gemma":[0.00091749744,0.000159947,0.0003169505,0.00037462363,0.00029550318,0.0008531953,0.0006189363,0.0006731328,0.00032738945],"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":[0.0004649058,0.00037575295,0.0075589223,0.00015010014,0.00008706662,0.0003316881,0.00011876785,0.28973916,0.030847639,0.0018240148,0.0032547982,0.66524714],"study_design_scores_gemma":[0.000004986025,0.00004678711,0.00085423107,0.0000036552883,0.0000073428337,0.000044042637,0.000010388726,0.9920413,0.005747517,0.0009317062,0.00030177436,0.0000062633244],"about_ca_topic_score_codex":0.0033142716,"about_ca_topic_score_gemma":0.0034615067,"teacher_disagreement_score":0.0033142716,"about_ca_system_score_codex":0.0005240081,"about_ca_system_score_gemma":0.0005010859,"threshold_uncertainty_score":0.006589949},"labels":[],"label_agreement":null},{"id":"W3182719754","doi":"10.1002/int.22548","title":"Trusted audit with untrusted auditors: A decentralized data integrity Crowdauditing approach based on blockchain","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National University of Defense Technology; National Natural Science Foundation of China","keywords":"Computer science; Audit; Cloud computing; Computer security; Enhanced Data Rates for GSM Evolution; Blockchain; Incentive; Credibility; Crowdsourcing; External auditor; Accounting; Internal audit; Business; Operating system","score_opus":0.034155547205424186,"score_gpt":0.2848747199434247,"score_spread":0.25071917273800054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3182719754","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058385797,0.00033124557,0.93219805,0.00093270704,0.00007773933,0.00031523127,0.000082546576,0.00046459623,0.007212063],"genre_scores_gemma":[0.94923705,0.00017372274,0.046118148,0.00008831834,0.00004244157,0.0001218492,0.000062191946,0.000028941447,0.0041274535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959907,0.0015435297,0.00019419965,0.00074493553,0.00091992255,0.0006067081],"domain_scores_gemma":[0.99398214,0.0024289563,0.00079409237,0.0012380974,0.0009296435,0.00062697695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035326013,0.0005793836,0.0012549608,0.0008543545,0.0018583401,0.0024392516,0.0023730563,0.0015591965,0.0026432024],"category_scores_gemma":[0.007846194,0.00046032981,0.0006967487,0.0012911237,0.002083995,0.0033845457,0.0041178414,0.001394674,0.00044127504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009957082,0.0002829572,0.0040474017,0.00026469305,0.00012344943,0.0014606882,0.0016952507,0.6689503,0.010404342,0.17821966,0.003349426,0.13020615],"study_design_scores_gemma":[0.000038692648,0.000057067384,0.0001766971,0.000017894874,0.000017197995,0.00009331222,0.000096656695,0.9579575,0.0014435648,0.03757689,0.0025009874,0.000023489749],"about_ca_topic_score_codex":0.00564803,"about_ca_topic_score_gemma":0.0046386546,"teacher_disagreement_score":0.00564803,"about_ca_system_score_codex":0.0016657852,"about_ca_system_score_gemma":0.0039673415,"threshold_uncertainty_score":0.01868242},"labels":[],"label_agreement":null},{"id":"W3185287204","doi":"10.1002/int.22562","title":"A new method for deriving priority from dual hesitant fuzzy preference relations","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Consistency (knowledge bases); Preference; Dual (grammatical number); Preference relation; Computer science; Group decision-making; Fuzzy logic; Probabilistic logic; Property (philosophy); Basis (linear algebra); Data mining; Mathematical optimization; Artificial intelligence; Mathematics; Statistics","score_opus":0.2587212012644264,"score_gpt":0.4737449613594993,"score_spread":0.2150237600950729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185287204","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009332993,0.000056025387,0.998018,0.000035679655,0.000025344083,0.000034956727,0.000020858353,0.00004747242,0.0008283028],"genre_scores_gemma":[0.0752599,0.0002577652,0.92163575,0.00007665676,0.00008849954,0.00022110279,0.00013838345,0.0000617847,0.002259999],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99615085,0.0012856409,0.00042721035,0.0006887836,0.0012612145,0.00018623292],"domain_scores_gemma":[0.9969913,0.0013708948,0.00021480181,0.00024201447,0.0010694031,0.00011161937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040043117,0.0011859784,0.0012640619,0.0034904028,0.0009988268,0.002455984,0.0014750081,0.000923229,0.004329228],"category_scores_gemma":[0.009217139,0.00072317745,0.002152019,0.0030106422,0.0011255951,0.004258279,0.0017357004,0.0024143471,0.00091813895],"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":[0.00021405602,0.00012256758,0.001354359,0.0007721019,0.00025371733,0.00035504313,0.0012171419,0.09370637,0.013358161,0.39928162,0.0046702577,0.4846947],"study_design_scores_gemma":[0.00008076298,0.00020998647,0.0005545808,0.00010789166,0.00012572859,0.00057735684,0.00027090407,0.77416176,0.008808322,0.19657913,0.018371182,0.00015234575],"about_ca_topic_score_codex":0.0019335146,"about_ca_topic_score_gemma":0.0016059376,"teacher_disagreement_score":0.004329228,"about_ca_system_score_codex":0.0013369534,"about_ca_system_score_gemma":0.0019557273,"threshold_uncertainty_score":0.021177113},"labels":[],"label_agreement":null},{"id":"W3201288682","doi":"10.1002/int.22676","title":"EviChain: A scalable blockchain for accountable intelligent surveillance systems","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Scalability; Computer security; Byzantine fault tolerance; Context (archaeology); Overhead (engineering); Cryptography; Block (permutation group theory); Blockchain; Authentication (law); Distributed computing; Tamper resistance; Process (computing); Exploit; Vulnerability (computing); Embedded system; Fault tolerance; Database; Operating system","score_opus":0.021129659900494775,"score_gpt":0.280248707412957,"score_spread":0.25911904751246223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201288682","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1367957,0.001161381,0.8368678,0.0012034443,0.00030168134,0.00080707937,0.0007399378,0.005110442,0.017012488],"genre_scores_gemma":[0.9211209,0.0003786765,0.07134135,0.00012066865,0.000039937833,0.0003431775,0.000483559,0.000086614666,0.006085119],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991961,0.00025183102,0.00004513304,0.00010553894,0.00023817705,0.00016319337],"domain_scores_gemma":[0.99854976,0.00047486273,0.00012610576,0.00041208856,0.00020925475,0.00022797551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012867085,0.00050759496,0.0006871222,0.00044254994,0.0009092413,0.0009821665,0.0014186146,0.0008431841,0.00742275],"category_scores_gemma":[0.003065048,0.00023716311,0.0002856538,0.00071171275,0.0007426685,0.0020237563,0.0023855565,0.0008803051,0.0008640568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011691514,0.0003596992,0.0023312445,0.00042928843,0.00009233313,0.0007747819,0.0003789409,0.7009827,0.015073488,0.07732003,0.01139714,0.18969122],"study_design_scores_gemma":[0.00018672878,0.00019192634,0.00022260955,0.000029894445,0.000015583388,0.00010534523,0.000052158273,0.9546776,0.003768649,0.031157276,0.009573314,0.000018906587],"about_ca_topic_score_codex":0.003944324,"about_ca_topic_score_gemma":0.0052949465,"teacher_disagreement_score":0.00742275,"about_ca_system_score_codex":0.0008183717,"about_ca_system_score_gemma":0.0021818203,"threshold_uncertainty_score":0.024831533},"labels":[],"label_agreement":null},{"id":"W4200120261","doi":"10.1002/int.22477","title":"Issue Information","year":2021,"lang":"en","type":"paratext","venue":"International Journal of Intelligent Systems","topic":"Corporate Taxation and Avoidance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence","score_opus":0.020679507946288245,"score_gpt":0.26071741615497185,"score_spread":0.2400379082086836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200120261","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000110190034,0.0004170604,0.00030094085,0.0013248617,0.0046830075,0.00019658863,0.016303929,0.0012357245,0.97542757],"genre_scores_gemma":[0.00048791154,0.00038239794,0.000190381,0.00055278506,0.00069516426,0.000045801382,0.0073141735,0.00037111453,0.9899603],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990871,0.0000551279,0.00006285497,0.0001445013,0.0005227094,0.0001276726],"domain_scores_gemma":[0.99606174,0.00034974568,0.0001722508,0.00041789238,0.0020753106,0.00092295406],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007688902,0.0015949825,0.0013788805,0.0036096897,0.0021556027,0.008973564,0.001721227,0.0023778803,0.92281765],"category_scores_gemma":[0.0050613596,0.00068924524,0.0007552782,0.005129612,0.0005832866,0.004209871,0.0018461278,0.0021794941,0.90755934],"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":[0.000009093146,0.000010080584,0.00003077703,0.00006774859,6.672572e-7,0.000009978489,0.0000056674094,0.000018295057,0.00005347994,0.0005954097,0.9801466,0.019052243],"study_design_scores_gemma":[0.000005266102,0.0000049191476,0.00016744107,0.000046033787,6.23448e-7,0.000011286035,0.00001259602,0.000019570816,0.000030277028,0.00022959849,0.9994696,0.0000027216447],"about_ca_topic_score_codex":0.011579012,"about_ca_topic_score_gemma":0.021876145,"teacher_disagreement_score":0.07718235,"about_ca_system_score_codex":0.0019090207,"about_ca_system_score_gemma":0.003415164,"threshold_uncertainty_score":0.11009127},"labels":[],"label_agreement":null},{"id":"W4229799740","doi":"10.1002/int.20018","title":"Belief, plausibility, and probability measures on interval-valued type 2 fuzzy sets","year":2004,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematics; Interval (graph theory); Axiom; Type (biology); Measure (data warehouse); Fuzzy set; Fuzzy logic; Discrete mathematics; Probability measure; Set (abstract data type); Fuzzy measure theory; Representation (politics); Analogy; Fuzzy number; Combinatorics; Artificial intelligence; Computer science; Data mining","score_opus":0.2532592522639635,"score_gpt":0.4500281764192226,"score_spread":0.1967689241552591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229799740","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034970313,0.0040193633,0.9349224,0.0011083154,0.00028127932,0.00009180369,0.00033615835,0.00015987792,0.024110518],"genre_scores_gemma":[0.6353077,0.0035153914,0.35265422,0.00040563458,0.00066770706,0.00049706973,0.0003856205,0.000040307732,0.006526258],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960395,0.0014272736,0.0003540338,0.0005483436,0.0014425816,0.00018819791],"domain_scores_gemma":[0.9941876,0.0031195579,0.0009976499,0.00046144344,0.0009917154,0.00024199372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004107118,0.0009995522,0.000727184,0.0033044384,0.000747698,0.004447052,0.0011833074,0.0015734994,0.0023121652],"category_scores_gemma":[0.013886836,0.00042474346,0.001189378,0.0029192027,0.0034539339,0.0064540743,0.0013452036,0.0019453437,0.00052707305],"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":[0.000075505486,0.000026393931,0.00048803427,0.00017566605,0.0000708208,0.0003239138,0.000489209,0.020974962,0.0016004082,0.9432276,0.0010127979,0.03153466],"study_design_scores_gemma":[0.000018877454,0.00005972931,0.000620341,0.00010039102,0.00003122623,0.00025969438,0.00014358616,0.05824106,0.00090317806,0.93287116,0.006706056,0.00004469493],"about_ca_topic_score_codex":0.0011052149,"about_ca_topic_score_gemma":0.0009075505,"teacher_disagreement_score":0.004447052,"about_ca_system_score_codex":0.0018945002,"about_ca_system_score_gemma":0.0007594722,"threshold_uncertainty_score":0.021720767},"labels":[],"label_agreement":null},{"id":"W4251464076","doi":"10.1002/int.22002","title":"Issue Information","year":2018,"lang":"en","type":"paratext","venue":"International Journal of Intelligent Systems","topic":"Human auditory perception and evaluation","field":"Engineering","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; University of Alberta; University of Calgary","funders":"","keywords":"Computer science; Data science","score_opus":0.024531415310985006,"score_gpt":0.30293360298314215,"score_spread":0.27840218767215713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251464076","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000349862,0.0005673705,0.001509575,0.0021429216,0.0063748243,0.00029823798,0.012856614,0.003386217,0.97251445],"genre_scores_gemma":[0.0006627974,0.0003041595,0.00042043414,0.00047556838,0.00056641357,0.00006067534,0.0045307074,0.0005234481,0.9924557],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991522,0.00008810323,0.00005705089,0.0001439877,0.0004634955,0.0000951784],"domain_scores_gemma":[0.99656004,0.00049992924,0.00015273131,0.00049109216,0.0013070275,0.0009891388],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001124894,0.0012872173,0.0012828313,0.0044328603,0.0013203444,0.007181331,0.0016218455,0.001986889,0.94513214],"category_scores_gemma":[0.006462659,0.00052833057,0.00074430445,0.0035555726,0.0004954703,0.0034658783,0.0024061839,0.0016930246,0.9168124],"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":[0.000022177863,0.000040866904,0.000070730166,0.00014658638,0.0000024007156,0.00002158027,0.000013154492,0.00004392955,0.00018026322,0.001517635,0.9348564,0.063084245],"study_design_scores_gemma":[0.000012878448,0.00001690309,0.00021857614,0.00006989212,0.0000023377986,0.000027864071,0.000024797571,0.00009347472,0.00012082565,0.001328134,0.9980794,0.0000050176786],"about_ca_topic_score_codex":0.0011554924,"about_ca_topic_score_gemma":0.002613474,"teacher_disagreement_score":0.054867864,"about_ca_system_score_codex":0.00084499177,"about_ca_system_score_gemma":0.0020565523,"threshold_uncertainty_score":0.07826227},"labels":[],"label_agreement":null},{"id":"W4251659863","doi":"10.1002/int.20016","title":"Associations and rules in data mining: A link analysis","year":2004,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Data mining; Computer science; Consistency (knowledge bases); Set (abstract data type); Cluster analysis; Relevance (law); Quality (philosophy); Rough set; Association rule learning; Fuzzy rule; Fuzzy logic; Rule-based system; Block (permutation group theory); Fuzzy set; Artificial intelligence; Mathematics","score_opus":0.06573665888699667,"score_gpt":0.32312337699832433,"score_spread":0.25738671811132763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251659863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010301376,0.011200165,0.971739,0.002364488,0.00018906164,0.0001936485,0.00024925717,0.000286464,0.003476562],"genre_scores_gemma":[0.10959169,0.008895983,0.8760922,0.0005317475,0.0008321148,0.0006757053,0.0007044211,0.00012265678,0.0025534874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99001837,0.004915261,0.0009096513,0.0014406053,0.002498996,0.00021707999],"domain_scores_gemma":[0.97011405,0.024513239,0.0018502,0.0020811062,0.0010125694,0.00042878176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011854115,0.0011596594,0.0017802556,0.010755772,0.0019213193,0.009625353,0.002768113,0.0029962542,0.0038702677],"category_scores_gemma":[0.040038798,0.00075656624,0.0020708484,0.013746308,0.005509277,0.013041791,0.003936933,0.0031924478,0.0014007931],"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":[0.00011130678,0.0001728111,0.0046825744,0.001335037,0.00036910427,0.0007175552,0.0016626541,0.0373063,0.0009887168,0.6951592,0.0039975876,0.25349715],"study_design_scores_gemma":[0.000012197029,0.00005091701,0.0004901442,0.00025907948,0.00009742927,0.00038012696,0.00032002316,0.0858459,0.00058911886,0.89242923,0.019494113,0.000031660864],"about_ca_topic_score_codex":0.00089577097,"about_ca_topic_score_gemma":0.000614392,"teacher_disagreement_score":0.011854115,"about_ca_system_score_codex":0.0010846457,"about_ca_system_score_gemma":0.0011088056,"threshold_uncertainty_score":0.06269127},"labels":[],"label_agreement":null},{"id":"W4283710515","doi":"10.1002/int.22947","title":"A data variability index: Quantifying complexity of models and analyzing adversarial data","year":2022,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Data mining; Transformation (genetics); Algorithm; Lipschitz continuity; Piecewise; Mathematical optimization; Mathematics","score_opus":0.24637303769046864,"score_gpt":0.3822583595158197,"score_spread":0.13588532182535107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283710515","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034282584,0.0004967412,0.9626166,0.00063071586,0.000055999983,0.00008565485,0.00020450508,0.00017406479,0.0014531768],"genre_scores_gemma":[0.7744575,0.0008867413,0.22181976,0.00033016596,0.000251137,0.00032136418,0.0007125184,0.0001870067,0.0010337242],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99520147,0.0015444681,0.00044103645,0.0009396457,0.0016167298,0.00025646892],"domain_scores_gemma":[0.9379745,0.049551565,0.004290401,0.0058819796,0.0016412091,0.00066033984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0092747975,0.001562115,0.0014080052,0.002487949,0.0008001717,0.0029198397,0.0018860991,0.0025318915,0.001110241],"category_scores_gemma":[0.051085755,0.0006679237,0.0016277746,0.0013905235,0.0040260046,0.006010779,0.0040427404,0.0045360606,0.00017714687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020392048,0.0000978006,0.0085276775,0.00026772651,0.0002213348,0.00036553468,0.0003078106,0.8555317,0.0065815165,0.091249555,0.0007477716,0.035897642],"study_design_scores_gemma":[0.0000056853046,0.00016505939,0.0017288626,0.000062787585,0.000025827561,0.00021543761,0.00006791942,0.9208914,0.0028427786,0.073125206,0.0008168352,0.000052100764],"about_ca_topic_score_codex":0.0009651143,"about_ca_topic_score_gemma":0.0006105138,"teacher_disagreement_score":0.0092747975,"about_ca_system_score_codex":0.0017830839,"about_ca_system_score_gemma":0.0010110857,"threshold_uncertainty_score":0.04905039},"labels":[],"label_agreement":null},{"id":"W4322488172","doi":"10.1155/2023/2467539","title":"CNFRD: A Few‐Shot Rumor Detection Framework via Capsule Network for COVID‐19","year":2023,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Sichuan Province Science and Technology Support Program; Xihua University; National Natural Science Foundation of China","keywords":"Rumor; Computer science; Artificial intelligence; Class (philosophy); Metric (unit); Data mining","score_opus":0.09118930593706516,"score_gpt":0.40680201849015324,"score_spread":0.3156127125530881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322488172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07106684,0.002979707,0.91667825,0.0011534076,0.00019312563,0.00030105427,0.0010624959,0.003099812,0.0034653037],"genre_scores_gemma":[0.78494483,0.001388274,0.20035774,0.0006782685,0.00031845804,0.00027584555,0.0030435233,0.0001343195,0.0088587925],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990125,0.0002649795,0.00007010386,0.00031250637,0.00021134653,0.00012845652],"domain_scores_gemma":[0.99863356,0.00055211736,0.00023415941,0.00014834198,0.00032602463,0.00010567163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014385935,0.0013945485,0.0012476988,0.0022873234,0.0006913995,0.0012285267,0.0024700274,0.0016119735,0.0012888236],"category_scores_gemma":[0.004821034,0.00046731508,0.0010654584,0.0010078499,0.0005426764,0.002289066,0.0015368579,0.0018596842,0.0006768271],"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":[0.0007358906,0.00064741576,0.02565801,0.00047938956,0.00046402944,0.0007327871,0.0007136776,0.18731622,0.008491818,0.008811158,0.012267383,0.75368214],"study_design_scores_gemma":[0.000007491576,0.000060828905,0.0015014615,0.00001880279,0.00003229647,0.00009683782,0.00006712905,0.99258024,0.0011933798,0.0030145713,0.0014078814,0.00001911901],"about_ca_topic_score_codex":0.017125988,"about_ca_topic_score_gemma":0.01598005,"teacher_disagreement_score":0.017125988,"about_ca_system_score_codex":0.0012453644,"about_ca_system_score_gemma":0.00090781087,"threshold_uncertainty_score":0.03405261},"labels":[],"label_agreement":null},{"id":"W4362575694","doi":"10.1155/2023/8616939","title":"Hybrid Techniques for Diagnosing Endoscopy Images for Early Detection of Gastrointestinal Disease Based on Fusion Features","year":2023,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Gastrointestinal Bleeding Diagnosis and Treatment","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Ministry of Education – Kingdom of Saudi Arabi","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Principal component analysis; Artificial neural network; Support vector machine; Histogram; Dimensionality reduction; Discrete wavelet transform; Wavelet transform; Wavelet; Image (mathematics)","score_opus":0.02506109929127648,"score_gpt":0.3188664433560617,"score_spread":0.2938053440647852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362575694","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18923333,0.0031027964,0.79651964,0.0004552858,0.00028412414,0.00024502142,0.00063331006,0.004647652,0.0048788106],"genre_scores_gemma":[0.7454691,0.0011544006,0.24905315,0.00022626361,0.00011622176,0.00009853149,0.00077720324,0.00008776502,0.0030173275],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951315,0.00004665109,0.000047510763,0.00013240625,0.00019172365,0.000068484565],"domain_scores_gemma":[0.9994337,0.00012118822,0.000080414495,0.00006546299,0.0002671808,0.000031918873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006494338,0.0008821464,0.0007703122,0.002246034,0.0002678927,0.00071209273,0.00062573154,0.0008615083,0.001467852],"category_scores_gemma":[0.0013012697,0.00034213116,0.0008521277,0.0009847329,0.00022279097,0.0010531027,0.00070847134,0.0005525861,0.0007927661],"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":[0.00076675904,0.00025300746,0.013292376,0.0003692675,0.00024118162,0.0005255174,0.00017493538,0.020862134,0.116373375,0.0011046381,0.0038981952,0.84213877],"study_design_scores_gemma":[0.000056173023,0.0006111613,0.03265132,0.000104063016,0.00035083207,0.0017676706,0.00018446059,0.8706924,0.084778026,0.0026270135,0.0060940017,0.00008301091],"about_ca_topic_score_codex":0.0020479078,"about_ca_topic_score_gemma":0.0027091033,"teacher_disagreement_score":0.002246034,"about_ca_system_score_codex":0.00039500202,"about_ca_system_score_gemma":0.00036365684,"threshold_uncertainty_score":0.004910469},"labels":[],"label_agreement":null},{"id":"W4378904793","doi":"10.1155/2023/2662719","title":"Analysis of Histopathological Images for Early Diagnosis of Oral Squamous Cell Carcinoma by Hybrid Systems Based on CNN Fusion Features","year":2023,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"AI in cancer detection","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Najran University","keywords":"Basal cell; Stage (stratigraphy); Computer science; Cancer; Medicine; Segmentation; Artificial intelligence; Pathology; Internal medicine","score_opus":0.022708683803372168,"score_gpt":0.2799947814244216,"score_spread":0.2572860976210494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378904793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6287916,0.0036339809,0.35115084,0.00047017366,0.00041875217,0.00032797878,0.0030155191,0.005938501,0.006252634],"genre_scores_gemma":[0.9263223,0.00069821475,0.06807443,0.00012786464,0.00004616249,0.00008583304,0.0018008604,0.000078421996,0.0027659999],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970144,0.000025703312,0.000022819177,0.00009908947,0.00008377603,0.000067213485],"domain_scores_gemma":[0.99974376,0.00004834573,0.00003373364,0.000031363303,0.00012843439,0.000014354677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054757163,0.0010607066,0.0006100981,0.0015953355,0.00021513559,0.00061492977,0.00069609034,0.0006460687,0.0011006319],"category_scores_gemma":[0.0009829955,0.0003675785,0.0011240228,0.0006617857,0.00017204351,0.0006411053,0.000528723,0.00041688158,0.00041689092],"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":[0.0009600251,0.00032120617,0.030476408,0.00039257054,0.0006376669,0.00088534324,0.00019492974,0.20131694,0.098962195,0.0012854743,0.0065352283,0.65803206],"study_design_scores_gemma":[0.000010380367,0.00013015656,0.009756024,0.000025105843,0.00013927097,0.00018088864,0.000049303588,0.9683659,0.019565882,0.00054171274,0.0012108053,0.000024648398],"about_ca_topic_score_codex":0.012407941,"about_ca_topic_score_gemma":0.012494082,"teacher_disagreement_score":0.012407941,"about_ca_system_score_codex":0.00084706355,"about_ca_system_score_gemma":0.00056510034,"threshold_uncertainty_score":0.024671435},"labels":[],"label_agreement":null},{"id":"W4385693906","doi":"10.1155/2023/6442756","title":"Towards Diagnostic Aided Systems in Coronary Artery Disease Detection: A Comprehensive Multiview Survey of the State of the Art","year":2023,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"CAD; Support vector machine; Computer science; Machine learning; Artificial intelligence; Field (mathematics); Random forest; Artificial neural network; Coronary artery disease; Feature extraction; Data mining; Data extraction; Pattern recognition (psychology); Medicine; MEDLINE; Mathematics; Internal medicine; Engineering drawing","score_opus":0.17777504142200737,"score_gpt":0.44229123227928785,"score_spread":0.2645161908572805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385693906","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036570835,0.9912116,0.0012136048,0.001718367,0.0001370844,0.000049583803,0.00030743642,0.000034035802,0.0016710655],"genre_scores_gemma":[0.021117399,0.97263473,0.0042283074,0.0009930527,0.00016585134,0.000061255545,0.0004922045,0.000018116725,0.0002891277],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9945575,0.0016468652,0.0014720587,0.0005100571,0.0016560914,0.00015753547],"domain_scores_gemma":[0.95906746,0.029076071,0.00325572,0.0007038357,0.0073544057,0.0005425758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0155754,0.0005705457,0.0013153928,0.020255685,0.0004365214,0.0037156013,0.0012269234,0.0015550992,0.0030406003],"category_scores_gemma":[0.025539828,0.0005062068,0.0017515061,0.0120907845,0.0010718916,0.0046201427,0.0016558416,0.0011175446,0.0007128549],"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":[0.00017709563,0.00009549684,0.010084848,0.09268752,0.0008269889,0.00017842861,0.001489972,0.0005297544,0.0011508901,0.004997075,0.011047908,0.87673396],"study_design_scores_gemma":[0.00007264106,0.00093464187,0.07125077,0.3542295,0.005347726,0.002956418,0.005486596,0.0025507864,0.002022025,0.008233073,0.54671013,0.00020568985],"about_ca_topic_score_codex":0.0040911613,"about_ca_topic_score_gemma":0.0049381824,"teacher_disagreement_score":0.020255685,"about_ca_system_score_codex":0.0021863917,"about_ca_system_score_gemma":0.004583557,"threshold_uncertainty_score":0.08237153},"labels":[],"label_agreement":null},{"id":"W4388405697","doi":"10.1155/2023/3044155","title":"A New Multinetwork Mean Distillation Loss Function for Open‐World Domain Incremental Object Detection","year":2023,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Science and Technology Program of Guizhou Province; Petroleum Technology Research Centre; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Pascal (unit); Computer science; Distillation; Object detection; Artificial intelligence; Benchmark (surveying); Detector; Pattern recognition (psychology); Computer vision; Chromatography","score_opus":0.03736207295549617,"score_gpt":0.32318409551757526,"score_spread":0.2858220225620791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388405697","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030498352,0.0014318718,0.9605358,0.0005951227,0.00021638491,0.000110945664,0.00033274558,0.0042749424,0.0020038795],"genre_scores_gemma":[0.52593005,0.000863441,0.45240918,0.0012859954,0.00027917427,0.00043612413,0.0030179678,0.0008402505,0.014937815],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991148,0.00016361626,0.000051410494,0.00024905018,0.00030620614,0.00011484209],"domain_scores_gemma":[0.9990741,0.00032456423,0.00007897268,0.00013025335,0.00032586965,0.00006624656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022008084,0.0017996115,0.0013220683,0.00093371095,0.00052945194,0.0011024368,0.0035829267,0.0020042066,0.0025107206],"category_scores_gemma":[0.004021611,0.0005691349,0.0011110499,0.00087050465,0.00095980545,0.0031035228,0.002122348,0.003050673,0.0010455034],"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":[0.00048756646,0.00037365232,0.001847794,0.00019111668,0.0002048104,0.00023920191,0.00007961672,0.41739845,0.016757222,0.009043452,0.015448862,0.53792834],"study_design_scores_gemma":[0.000010581322,0.00004708251,0.00020240794,0.0000076061565,0.000014820582,0.00004370975,0.000004235127,0.9934999,0.0031679946,0.0019522902,0.0010350692,0.000014289547],"about_ca_topic_score_codex":0.0064994646,"about_ca_topic_score_gemma":0.007648356,"teacher_disagreement_score":0.0064994646,"about_ca_system_score_codex":0.0017964058,"about_ca_system_score_gemma":0.0019433044,"threshold_uncertainty_score":0.0130339265},"labels":[],"label_agreement":null},{"id":"W4388445625","doi":"10.1155/2023/3578867","title":"Hybrid Time‐Series Prediction Method Based on Entropy Fusion Feature","year":2023,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Major Science and Technology Projects in Yunnan Province","keywords":"Hilbert–Huang transform; Computer science; Subsequence; Pattern recognition (psychology); Artificial intelligence; Entropy (arrow of time); Feature (linguistics); Time series; Series (stratigraphy); Algorithm; Data mining; Machine learning; Mathematics","score_opus":0.009320707029338618,"score_gpt":0.29155278498199394,"score_spread":0.2822320779526553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388445625","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052955274,0.0008734504,0.94191885,0.00021738956,0.00015735645,0.00004608872,0.00020106263,0.001825098,0.001805444],"genre_scores_gemma":[0.8818123,0.0006349819,0.113102086,0.0001221081,0.000116313095,0.00009054258,0.0004941567,0.000098031414,0.0035295114],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997104,0.000027440403,0.00002521851,0.000100975856,0.00010244918,0.000033435546],"domain_scores_gemma":[0.9997118,0.00007982035,0.000037957656,0.00002742914,0.00012449553,0.000018305198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005926365,0.000912459,0.0007701375,0.0009949167,0.00029821336,0.0006004545,0.0007949588,0.00051423727,0.0013777576],"category_scores_gemma":[0.0010499735,0.00028234348,0.0008485128,0.00074504997,0.00022025075,0.0015247,0.00060682365,0.0007980954,0.00044906494],"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":[0.00031816933,0.00019895712,0.0056391004,0.00015205146,0.00025012784,0.00030152165,0.00016653258,0.32689,0.02646988,0.004305917,0.0036490893,0.6316587],"study_design_scores_gemma":[0.0000042530733,0.000030304069,0.0006225776,0.0000053970034,0.000018916206,0.000035006866,0.0000071361615,0.99561006,0.0024456885,0.0008559834,0.00035663307,0.000008134967],"about_ca_topic_score_codex":0.00527485,"about_ca_topic_score_gemma":0.004272184,"teacher_disagreement_score":0.00527485,"about_ca_system_score_codex":0.00042664143,"about_ca_system_score_gemma":0.00057666644,"threshold_uncertainty_score":0.010488331},"labels":[],"label_agreement":null},{"id":"W4391162811","doi":"10.1155/2024/5780186","title":"Constructing Perturbation Matrices of Prototypes for Enhancing the Performance of Fuzzy Decoding Mechanism","year":2024,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Decoding methods; Perturbation (astronomy); Fuzzy logic; Mechanism (biology); Computer science; Algebra over a field; Algorithm; Theoretical computer science; Mathematics; Artificial intelligence; Pure mathematics; Physics","score_opus":0.022396438670897793,"score_gpt":0.28117350499639704,"score_spread":0.25877706632549924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391162811","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02207248,0.00016392427,0.9763624,0.000053493906,0.00003203871,0.00003823227,0.00001192086,0.00023752192,0.001028009],"genre_scores_gemma":[0.46653897,0.00027490815,0.53146756,0.00006955342,0.000032394455,0.00010144805,0.000076835895,0.000064413136,0.0013739975],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931633,0.00013797126,0.000058114194,0.00012897183,0.00029944011,0.000059144426],"domain_scores_gemma":[0.99892443,0.00043465177,0.00011817927,0.0001561041,0.00032606607,0.00004064781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010449731,0.0008222688,0.0007581836,0.00072067045,0.00045638462,0.00092429837,0.0010957876,0.0010131327,0.0012685879],"category_scores_gemma":[0.0047317995,0.00037404284,0.0004910577,0.00082850334,0.00052093517,0.0016158043,0.00080615154,0.00074601086,0.0004171905],"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":[0.00035186717,0.00011520694,0.0009897661,0.00025369722,0.00007271126,0.00019710543,0.00030197995,0.3563933,0.077356905,0.025036685,0.0016562167,0.5372746],"study_design_scores_gemma":[0.000013402339,0.000053221698,0.00016751992,0.0000072676617,0.00001532481,0.00008662371,0.00002057876,0.98088384,0.015182592,0.002841611,0.0007131335,0.00001488153],"about_ca_topic_score_codex":0.0019822726,"about_ca_topic_score_gemma":0.0012028217,"teacher_disagreement_score":0.0019822726,"about_ca_system_score_codex":0.0004070817,"about_ca_system_score_gemma":0.00095315883,"threshold_uncertainty_score":0.0055264235},"labels":[],"label_agreement":null},{"id":"W4398268938","doi":"10.1155/2024/8014111","title":"An Intelligent COVID-19-Related Arabic Text Detection Framework Based on Transfer Learning Using Context Representation","year":2024,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"King Saud University","keywords":"Coronavirus disease 2019 (COVID-19); Transfer of learning; Context (archaeology); Arabic; Computer science; Representation (politics); Artificial intelligence; Natural language processing; Linguistics; Medicine; Geography","score_opus":0.06537820810809168,"score_gpt":0.3997826155834569,"score_spread":0.3344044074753652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398268938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1919327,0.0050369957,0.7773365,0.0012981058,0.000766353,0.00042354938,0.0014730677,0.013137063,0.008595631],"genre_scores_gemma":[0.76053286,0.0013588115,0.21772249,0.0010113645,0.0004281819,0.00028446896,0.0038005807,0.00017774146,0.014683572],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996853,0.000046597226,0.00001890501,0.00012734823,0.000067246765,0.000054604796],"domain_scores_gemma":[0.9997348,0.00006286472,0.000032083764,0.000028954431,0.00010960195,0.000031629304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043802138,0.0012527525,0.00078267575,0.0012896046,0.00045376775,0.0006495614,0.0011524298,0.0009696508,0.0017938449],"category_scores_gemma":[0.0010232097,0.00019297897,0.0008200192,0.0006924081,0.00027831845,0.0013324751,0.0008662851,0.0011035994,0.0012139116],"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":[0.00035544432,0.0005939468,0.0040725693,0.00013737609,0.00013180949,0.0003731247,0.0001631106,0.0456226,0.02436066,0.0017396904,0.014810733,0.9076388],"study_design_scores_gemma":[0.000019865867,0.00017624312,0.0013570176,0.000016480255,0.000053893502,0.00015133932,0.00006423664,0.9848328,0.00771793,0.0026944801,0.0028940334,0.000021648513],"about_ca_topic_score_codex":0.0061792587,"about_ca_topic_score_gemma":0.00678861,"teacher_disagreement_score":0.0061792587,"about_ca_system_score_codex":0.00054481375,"about_ca_system_score_gemma":0.0008533298,"threshold_uncertainty_score":0.012286603},"labels":[],"label_agreement":null},{"id":"W4400462316","doi":"10.1155/2024/2960447","title":"Deep Reinforcement Learning‐Based Multireconfigurable Intelligent Surface for MEC Offloading","year":2024,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Science Foundation of Zhejiang Province; Fundamental Research Funds for the Central Universities; Sichuan Province Science and Technology Support Program; Natural Science Foundation of Ningbo; King Saud University; National Natural Science Foundation of China","keywords":"Reinforcement learning; Computer science; Server; Leverage (statistics); Optimization problem; Computation offloading; Mobile edge computing; Distributed computing; Wireless; Edge computing; Enhanced Data Rates for GSM Evolution; Mathematical optimization; Artificial intelligence; Computer network; Algorithm; Telecommunications","score_opus":0.026691265297336345,"score_gpt":0.2905613476179283,"score_spread":0.26387008232059195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400462316","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054724168,0.00035871175,0.9383481,0.00023684447,0.00006113066,0.000032910284,0.00003498774,0.0005065808,0.005696489],"genre_scores_gemma":[0.95035285,0.00012608558,0.046227783,0.0001352305,0.000016134105,0.0000739923,0.00006695889,0.000045206132,0.0029557429],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998047,0.000042714782,0.0000073968245,0.0000440992,0.00004961584,0.00005158552],"domain_scores_gemma":[0.9996884,0.00015315379,0.000043264892,0.000026970261,0.00006236755,0.000025892365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038601557,0.00074805046,0.00066606654,0.00020668932,0.00022547222,0.00060089794,0.00070607616,0.00067427533,0.0018215957],"category_scores_gemma":[0.000940726,0.0002969084,0.00041201478,0.00019608614,0.00060222065,0.0005758445,0.0008213229,0.0008983304,0.00027432153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043938817,0.00004208728,0.00039517265,0.000030109934,0.000014229655,0.00005007143,0.000025057081,0.97036034,0.0035317114,0.0023454137,0.0006635719,0.02249838],"study_design_scores_gemma":[0.0000023501862,0.000013701476,0.000024642932,0.0000012108167,0.0000014736881,0.0000029144874,0.0000023020011,0.9991837,0.0002571862,0.00039986367,0.00010931079,0.0000013184102],"about_ca_topic_score_codex":0.0029865822,"about_ca_topic_score_gemma":0.0032816664,"teacher_disagreement_score":0.0029865822,"about_ca_system_score_codex":0.00050445856,"about_ca_system_score_gemma":0.00071609823,"threshold_uncertainty_score":0.0060938597},"labels":[],"label_agreement":null},{"id":"W4407667139","doi":"10.1155/int/7026120","title":"Neuron Segmentation via a Frequency and Spatial Domain–Integrated Encoder–Decoder Network","year":2025,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; British Columbia Innovation Council","keywords":"Computer science; Encoder; Segmentation; Domain (mathematical analysis); Frequency domain; Artificial intelligence; Computer vision; Pattern recognition (psychology); Speech recognition; Mathematics","score_opus":0.005818709018001526,"score_gpt":0.27443097600447747,"score_spread":0.26861226698647594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407667139","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06687595,0.0008852908,0.9240695,0.00032578246,0.000101609636,0.00007735407,0.0002808142,0.003569774,0.0038139736],"genre_scores_gemma":[0.5752837,0.0004081411,0.41393542,0.00042756175,0.000059695903,0.0001433636,0.0008482601,0.00018382915,0.008710107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998023,0.0000227733,0.000009926475,0.00007969468,0.000050128812,0.000035145793],"domain_scores_gemma":[0.9997906,0.000068341025,0.00002198549,0.000027720898,0.00006869631,0.000022763372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003674755,0.0009447037,0.00068728597,0.000566796,0.00035926382,0.00057518046,0.0012541583,0.0012824337,0.0017022014],"category_scores_gemma":[0.00082000945,0.00047183575,0.00056329503,0.0004974334,0.00054868317,0.0009604462,0.0009804346,0.0007434524,0.0005774224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028119213,0.00013106431,0.0017552909,0.00011890963,0.00011658212,0.0002996268,0.00016153333,0.5232067,0.060160816,0.006270165,0.00481256,0.40268558],"study_design_scores_gemma":[0.0000057089023,0.000032921365,0.00016420797,0.000004750912,0.000012713336,0.000046540274,0.000008364345,0.9912246,0.0062847626,0.0014617299,0.0007464533,0.0000071916306],"about_ca_topic_score_codex":0.00849223,"about_ca_topic_score_gemma":0.013775754,"teacher_disagreement_score":0.00849223,"about_ca_system_score_codex":0.0009741403,"about_ca_system_score_gemma":0.0009289799,"threshold_uncertainty_score":0.016885579},"labels":[],"label_agreement":null},{"id":"W7092208968","doi":"10.1155/int/4962106","title":"Neural Incremental Dynamic Inversion Control of a Multirotor Robotic Airship","year":2025,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Aerospace Engineering and Energy Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Control theory (sociology); Multirotor; Inversion (geology); Artificial neural network; Robustness (evolution); Nonlinear system; Inverse","score_opus":0.007307084416572383,"score_gpt":0.22976384559399113,"score_spread":0.22245676117741875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7092208968","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11855822,0.00032444947,0.8739293,0.0001089227,0.00008202777,0.000038980525,0.000019193118,0.00046276284,0.006476143],"genre_scores_gemma":[0.96963555,0.00007592095,0.028433241,0.00003197332,0.000014445574,0.000027999844,0.000019711628,0.000009127172,0.0017519558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990845,0.000014389035,0.0000043572395,0.000020865482,0.00003689939,0.0000149555235],"domain_scores_gemma":[0.9998834,0.000031827734,0.000028232063,0.0000138542755,0.00003385012,0.000008735799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002781646,0.00035581732,0.00024190095,0.00013279048,0.00017463023,0.00029216005,0.0004957717,0.00023177898,0.0006375867],"category_scores_gemma":[0.00042422148,0.00014868018,0.00018242678,0.00009049233,0.00026038324,0.00028720163,0.0004085195,0.00040518906,0.00010539057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002949141,0.000089945264,0.0013132568,0.00022061581,0.00006003623,0.00020969579,0.0001804024,0.6873422,0.090141565,0.007825394,0.0008720222,0.21144989],"study_design_scores_gemma":[0.000009440599,0.00012323125,0.0003245315,0.0000030832514,0.0000073477972,0.000028600674,0.0000054365332,0.994351,0.004212053,0.00031117874,0.00061857083,0.000005404416],"about_ca_topic_score_codex":0.0020654162,"about_ca_topic_score_gemma":0.002024497,"teacher_disagreement_score":0.0020654162,"about_ca_system_score_codex":0.00018165282,"about_ca_system_score_gemma":0.00028145118,"threshold_uncertainty_score":0.0041068196},"labels":[],"label_agreement":null},{"id":"W79425221","doi":"","title":"A fuzzy-based multimodel system for reasoning about the number of software defects: Research Articles","year":2005,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Fuzzy logic; Software; Artificial intelligence; Function (biology); Machine learning; Data mining; Software engineering","score_opus":0.0621005207150327,"score_gpt":0.3703374831358635,"score_spread":0.3082369624208308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W79425221","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011987918,0.0004194348,0.9839107,0.00035387604,0.000038473132,0.0001036559,0.0002597297,0.0012017628,0.0017244412],"genre_scores_gemma":[0.25632828,0.0006363201,0.73995185,0.0001689314,0.000075149386,0.00027145707,0.00060926843,0.00007855485,0.0018801293],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901617,0.00023949267,0.00013213675,0.00023488668,0.0003256159,0.000051649844],"domain_scores_gemma":[0.9980386,0.0010983349,0.00015821568,0.00024580007,0.0003872124,0.00007179975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002192059,0.0008134181,0.0010079454,0.0027347903,0.00086525193,0.0030730462,0.0018454952,0.0020599235,0.004983946],"category_scores_gemma":[0.007960217,0.00042311064,0.0013710617,0.0016230451,0.0006374752,0.003234681,0.0010363187,0.001037643,0.0010912752],"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":[0.00037555405,0.00038718528,0.005473255,0.0005830527,0.00035932058,0.0007213097,0.00092903554,0.25307813,0.011945288,0.06437793,0.0051386007,0.65663135],"study_design_scores_gemma":[0.000023616314,0.00005433019,0.00049539463,0.00007505192,0.00007968264,0.00017558149,0.00006950461,0.9531047,0.002130882,0.039144758,0.004613455,0.000033085496],"about_ca_topic_score_codex":0.00661231,"about_ca_topic_score_gemma":0.0068255737,"teacher_disagreement_score":0.00661231,"about_ca_system_score_codex":0.0013049627,"about_ca_system_score_gemma":0.0012967952,"threshold_uncertainty_score":0.01667291},"labels":[],"label_agreement":null}]}