{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":28,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":28,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"40da2e1ae72f","filters":{"venue":"International Journal of Computational Intelligence and Applications"}},"results":[{"id":"W2131490916","doi":"10.1142/s1469026801000251","title":"BOOK REVIEW: \"PATTERN CLASSIFICATION\", R. O. DUDA, P. E. HART and D. G. STORK, Second Edition","year":2001,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":147,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Stork; Computer science; Library science; Artificial intelligence; Ecology","authors":[{"name":"David Chiu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02008083573139918,"gpt":0.2923169523086721,"spread":0.2722361165772729,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000256562,0.0001273257,0.0001529992,0.00009374467,0.0001418138,0.00007626991,0.0002761112,0.00004609499,0.001902456],"category_scores_gemma":[0.00002997799,0.0001175117,0.00006293786,0.0001767791,0.0002211808,0.0003760727,0.00007136643,0.000175312,0.0001581379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007717824,"about_ca_system_score_gemma":0.00002930138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001356974,"about_ca_topic_score_gemma":0.000007062787,"domain_scores_codex":[0.9986183,0.00003544768,0.0005344432,0.0002223306,0.0004776416,0.0001118205],"domain_scores_gemma":[0.9989509,0.000177763,0.0003697901,0.0001241101,0.0002478554,0.0001295976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002539126,0.000274851,0.002851349,0.0000359454,0.0001103497,0.00001255442,0.0002545245,0.005345212,0.0005005653,0.002727434,0.3892542,0.5986076],"study_design_scores_gemma":[0.0001129864,0.00003691617,0.01580378,0.0001205033,0.00002998173,0.0006833656,0.00007151137,0.006379054,0.0001209281,0.008579985,0.9679161,0.0001448426],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005331901,0.02135159,0.9403704,0.02569102,0.0002629825,0.0004865844,0.00003676199,0.00003594881,0.006432769],"genre_scores_gemma":[0.8828881,0.06272142,0.01048926,0.03749378,0.001470182,0.00007955291,0.0001798262,0.00004629484,0.004631564],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9298812,"threshold_uncertainty_score":0.99901,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2016189525","doi":"10.1142/s1469026801000068","title":"LEARNING OF FUZZY AUTOMATA","year":2001,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Fuzzy logic; Generalization; Artificial intelligence; Fuzzy electronics; State (computer science); Theoretical computer science; Finite-state machine; Automaton; Neuro-fuzzy; Fuzzy control system; Algorithm; Mathematics","authors":[{"name":"Witold Pedrycz","is_ca":true},{"name":"Adam Gacek","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.024432313043925,"gpt":0.3143575538523547,"spread":0.2899252408084297,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002105596,0.00008600433,0.000135373,0.0001878275,0.00008044457,0.0000876847,0.0008697155,0.00003169179,0.00001388293],"category_scores_gemma":[0.00002622756,0.0000789141,0.00007725825,0.0003310273,0.00008290046,0.0003901894,0.000124298,0.0001572536,0.00001226091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001977069,"about_ca_system_score_gemma":0.00006828838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000566625,"about_ca_topic_score_gemma":6.62324e-7,"domain_scores_codex":[0.9987847,0.00002636162,0.0005386537,0.0001446535,0.0004114039,0.00009425726],"domain_scores_gemma":[0.9982194,0.0002851231,0.0004546425,0.000112732,0.0008513399,0.0000767667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009853564,0.0001319597,0.0007056288,0.000003342315,0.00005182671,0.000006162222,0.0001286611,0.1462301,0.0002275082,0.5217116,0.0001904448,0.3306029],"study_design_scores_gemma":[0.0003421646,0.0002393508,0.005817696,0.0000864897,0.00002287263,0.001122177,0.0002058588,0.2418758,0.001790861,0.6783983,0.06984344,0.0002549501],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01056164,0.0001926283,0.9845153,0.003202328,0.0001101632,0.0000904919,0.000002837779,0.00002455881,0.001300026],"genre_scores_gemma":[0.9623243,0.0005833686,0.03663572,0.0001611312,0.0002046593,0.0000130366,0.000005866599,0.000004916087,0.00006697616],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9517627,"threshold_uncertainty_score":0.3218024,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2005599223","doi":"10.1142/s1469026814500138","title":"SOFTWARE DEVELOPMENT EFFORT ESTIMATION USING CLASSICAL AND FUZZY ANALOGY: A CROSS-VALIDATION COMPARATIVE STUDY","year":2014,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Software Engineering Research","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Analogy; Computer science; Software; Benchmarking; Software development; Estimation; Fuzzy logic; Software sizing; Data mining; Artificial intelligence; Software engineering; Machine learning; Software construction; Systems engineering; Programming language; Linguistics","authors":[{"name":"Fatima Azzahra Amazal","is_ca":false},{"name":"Ali Idri","is_ca":false},{"name":"Alain Abran","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0587535365511344,"gpt":0.3942547315765836,"spread":0.3355011950254492,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000608967,0.0001283781,0.0001798723,0.0003391191,0.0001675098,0.0003553483,0.0005393111,0.00004156901,0.00000421281],"category_scores_gemma":[0.0001894764,0.0001226092,0.00003492011,0.0002521358,0.0001048426,0.0006009383,0.0001748579,0.0001845622,0.000008391209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009697939,"about_ca_system_score_gemma":0.0001555981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004806838,"about_ca_topic_score_gemma":0.000001521246,"domain_scores_codex":[0.9983364,0.0000528108,0.0005620201,0.0002452609,0.0006779632,0.0001255258],"domain_scores_gemma":[0.9975655,0.0008770136,0.0002706147,0.0001168486,0.001053001,0.0001170183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002473893,0.0002799977,0.04142124,0.00001398763,0.000174518,0.000006083352,0.001681842,0.724195,0.00003947685,0.03428751,0.00002221699,0.1978534],"study_design_scores_gemma":[0.0005199395,0.0002523112,0.1889041,0.00007294584,0.00002198817,0.0003493568,0.0001917757,0.7455424,0.0009821599,0.06152337,0.001347106,0.0002925419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3023415,0.0000410053,0.6971757,0.0001549731,0.00008996324,0.0001562713,0.000001522335,0.00002489219,0.0000141816],"genre_scores_gemma":[0.784632,0.000004863285,0.2151657,0.00003349463,0.0001224202,0.00002028666,0.000008175662,0.000005214129,0.000007853926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4822905,"threshold_uncertainty_score":0.4999858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2791361378","doi":"10.1142/s1469026818500025","title":"Focus Group: An Optimization Algorithm Inspired by Human Behavior","year":2018,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Shahid Rajaee Teacher Training University","keywords":"Computer science; Benchmark (surveying); Evolutionary algorithm; Genetic algorithm; Focus (optics); Mathematical optimization; Algorithm; Optimization problem; Optimization algorithm; Meta-optimization; Artificial intelligence; Machine learning; Mathematics","authors":[{"name":"Edris Fattahi","is_ca":false},{"name":"Mahdi Bidar","is_ca":true},{"name":"Hamidreza Rashidy Kanan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03366772749157315,"gpt":0.3608316276317359,"spread":0.3271639001401627,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004857814,0.0001548535,0.0001762852,0.0004035019,0.0002589581,0.0004548098,0.001424485,0.00006951829,0.0001515121],"category_scores_gemma":[0.00004990066,0.0001524604,0.00006479034,0.0004400849,0.0002498437,0.001147658,0.0001765012,0.0001883819,0.00002467996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007687769,"about_ca_system_score_gemma":0.0001120696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002186066,"about_ca_topic_score_gemma":0.000002756404,"domain_scores_codex":[0.9977195,0.0000946395,0.0007449507,0.0003206885,0.0009438733,0.0001763082],"domain_scores_gemma":[0.9962696,0.0001526732,0.0004557728,0.0002266877,0.002669655,0.0002255463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001266228,0.0007725329,0.0001322849,0.000003113836,0.0001000233,0.00001411435,0.0002885039,0.07102297,0.0002403768,0.1124787,0.0007628326,0.8141719],"study_design_scores_gemma":[0.0003319527,0.0004376253,0.0003996795,0.00001905759,0.00002059821,0.0002650769,0.00007176557,0.9452462,0.001178409,0.04551296,0.006280283,0.0002363896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004029917,0.0001221007,0.9978684,0.0007442269,0.0002327199,0.000241493,0.00003228822,0.0000442284,0.0003115615],"genre_scores_gemma":[0.2451136,0.0001023113,0.7535673,0.0002846673,0.0006541529,0.00006692931,0.0001136534,0.00001711548,0.00008029005],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8742232,"threshold_uncertainty_score":0.6217154,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2322038820","doi":"10.1142/s1469026816500012","title":"A PSO-Based Approach with Fuzzy Obstacle Avoidance for Cooperative Multi-Robots in Unknown Environments","year":2016,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Obstacle avoidance; Computer science; Robot; Smoothness; Fuzzy logic; Trajectory; Task (project management); Artificial intelligence; Obstacle; Field (mathematics); Motion planning; Robotics; Key (lock); Collision avoidance; Mobile robot; Engineering; Mathematics","authors":[{"name":"Yifan Cai","is_ca":true},{"name":"Simon X. Yang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03093968061780096,"gpt":0.2919958861651228,"spread":0.2610562055473218,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000297135,0.000149929,0.0001964468,0.0002130091,0.00007359619,0.0001215083,0.0008108119,0.00004447983,0.000003148229],"category_scores_gemma":[0.00005529314,0.0001053448,0.00006467896,0.0001995293,0.000115541,0.0005293344,0.0000509549,0.00009666561,0.000009519743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000147649,"about_ca_system_score_gemma":0.0001700982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004990398,"about_ca_topic_score_gemma":0.000005212884,"domain_scores_codex":[0.9984629,0.00005401024,0.0005662693,0.0002946474,0.000456647,0.0001655665],"domain_scores_gemma":[0.9982657,0.0005404493,0.0004053251,0.0001463826,0.0005449577,0.00009716875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001294191,0.00080075,0.001594937,0.00001261749,0.000152332,0.000009992104,0.0002613658,0.7192013,0.0008397605,0.1817451,0.00005860664,0.09519388],"study_design_scores_gemma":[0.005992371,0.0004918837,0.01118443,0.0004622657,0.0000351333,0.0002781004,0.000257953,0.9277415,0.004610743,0.03433843,0.01393007,0.0006771182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001815118,0.0001447508,0.9955893,0.001758664,0.00009138188,0.000472948,0.00004916147,0.00001311151,0.00006558168],"genre_scores_gemma":[0.8586276,0.0000211072,0.1407721,0.000194577,0.00008223832,0.0001993189,0.00001557925,0.000008444219,0.00007907054],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8568125,"threshold_uncertainty_score":0.4295835,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025187426","doi":"10.1142/s1469026801000044","title":"AN ENHANCED GENETIC ALGORITHM FOR SOLVING THE HIGH-LEVEL SYNTHESIS PROBLEMS OF SCHEDULING, ALLOCATION, AND BINDING","year":2001,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Crossover; Scheduling (production processes); High-level synthesis; Job shop scheduling; Mathematical optimization; Parallel computing; Theoretical computer science; Algorithm; Field-programmable gate array; Routing (electronic design automation); Mathematics","authors":[{"name":"Gary Gréwal","is_ca":true},{"name":"Thomas C. Wilson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03936328554736702,"gpt":0.3216497545698783,"spread":0.2822864690225113,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005789332,0.0001091683,0.0001607823,0.0002289527,0.000140291,0.0001701904,0.000897087,0.00004586618,0.00000365079],"category_scores_gemma":[0.00007061625,0.00008844619,0.00005328952,0.0002082866,0.0001187368,0.0004651481,0.00006492007,0.00009508737,0.000001137388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003578343,"about_ca_system_score_gemma":0.0001059755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002075484,"about_ca_topic_score_gemma":0.000003421668,"domain_scores_codex":[0.9986028,0.00004354746,0.0006534044,0.0001994296,0.0003934086,0.000107411],"domain_scores_gemma":[0.9969591,0.0007668887,0.0005945617,0.0001582631,0.001455357,0.00006575404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008731447,0.000144288,0.0001631225,0.00002090916,0.0001307892,0.000001419991,0.0007490546,0.0678735,0.004987844,0.1435743,0.00003050466,0.7823156],"study_design_scores_gemma":[0.0001764868,0.0001985046,0.001602334,0.0002344433,0.00003579549,0.0004048176,0.000345066,0.675431,0.03971076,0.2810492,0.0005934594,0.0002181142],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01169896,0.0002869113,0.9866822,0.0008479324,0.00009021596,0.0003360016,0.00001743345,0.00002156185,0.00001880442],"genre_scores_gemma":[0.5885329,0.0002064411,0.4109895,0.00005146652,0.0001178358,0.00008639454,0.000003690456,0.000005529064,0.000006305049],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7820974,"threshold_uncertainty_score":0.3606731,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2073912270","doi":"10.1142/s1469026814500084","title":"PARALLEL HYBRID METAHEURISTIC ON SHARED MEMORY SYSTEM FOR REAL-TIME UAV PATH PLANNING","year":2014,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Computer science; Parallel computing; Particle swarm optimization; Metaheuristic; Multi-core processor; Parallel algorithm; Genetic algorithm; Speedup; Path (computing); Shared memory; Mathematical optimization; Algorithm","authors":[{"name":"Vincent Roberge","is_ca":true},{"name":"Mohammed Tarbouchi","is_ca":true},{"name":"François Charles Joseph Allaire","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03187382869613357,"gpt":0.3112131873067623,"spread":0.2793393586106287,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006217584,0.0001607863,0.0002466446,0.0002706192,0.0001535495,0.0002301193,0.001036296,0.00003893457,0.000004128552],"category_scores_gemma":[0.0001264424,0.0001478451,0.0001140902,0.0001310593,0.00005574996,0.0003167157,0.00008106619,0.0001466852,0.00004564147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008570548,"about_ca_system_score_gemma":0.0001043196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004160585,"about_ca_topic_score_gemma":2.971129e-8,"domain_scores_codex":[0.9982256,0.00006479574,0.0006572719,0.0002848674,0.0005999901,0.0001674231],"domain_scores_gemma":[0.9968907,0.001324674,0.0005614402,0.0001829565,0.000906462,0.0001337983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003543439,0.00008956249,0.00003711021,0.00001796281,0.0001161709,0.00001581148,0.0001846865,0.8339019,0.00005902238,0.1262344,0.001364331,0.03794363],"study_design_scores_gemma":[0.0003005247,0.0001933796,0.0005111257,0.000197434,0.00002391177,0.0003573816,0.00005728295,0.9407647,0.0003196239,0.0548937,0.002200881,0.0001800944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007171019,0.00007123777,0.9967227,0.0009102572,0.0003616483,0.000231966,0.00003254398,0.00006201801,0.0008905342],"genre_scores_gemma":[0.5363988,0.0000162219,0.462408,0.0002852629,0.0006753391,0.0000720922,0.0000448653,0.00001416032,0.00008534599],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5356817,"threshold_uncertainty_score":0.6028947,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2182089961","doi":"10.1142/s1469026816500231","title":"A Multi-Phase Hybrid Metaheuristics Approach for the Exam Timetabling","year":2016,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Metaheuristic; Tabu search; Simulated annealing; Hill climbing; Benchmarking; Benchmark (surveying); Heuristic; Mathematical optimization; Phase (matter); Algorithm; Artificial intelligence; Mathematics","authors":[{"name":"Ali Hmer","is_ca":true},{"name":"Malek Mouhoub","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2233509282656287,"gpt":0.4622628122840309,"spread":0.2389118840184023,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002448712,0.000119598,0.0002043732,0.0003341204,0.0002807713,0.0002762821,0.001093205,0.00003251413,0.00005870169],"category_scores_gemma":[0.002351035,0.00006236925,0.0002035277,0.0002997335,0.0002327893,0.000299443,0.00007932619,0.0001199659,0.0000361618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003497227,"about_ca_system_score_gemma":0.0001582206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003286308,"about_ca_topic_score_gemma":5.832017e-7,"domain_scores_codex":[0.9976112,0.00006680163,0.0009516991,0.0002486609,0.0009686971,0.0001529043],"domain_scores_gemma":[0.9894255,0.006594406,0.0006446794,0.0002001032,0.003025019,0.0001103409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001240583,0.0006878806,0.0002784719,0.000002915611,0.000447408,0.000002799584,0.0001540811,0.148661,0.0004379925,0.08432412,0.001789388,0.7630898],"study_design_scores_gemma":[0.001426218,0.0001394616,0.001364856,0.00003724005,0.0001875392,0.0005590196,0.000555074,0.5415437,0.001359015,0.3565277,0.09604318,0.0002569683],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001437598,0.000642059,0.9934596,0.003699779,0.0003021772,0.0002443625,0.000123572,0.0000125492,0.00007826622],"genre_scores_gemma":[0.7184071,0.000136233,0.2802956,0.0002194608,0.0005111721,0.00005883926,0.000008868072,0.000008791813,0.0003540034],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7628329,"threshold_uncertainty_score":0.2814578,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1977565676","doi":"10.1142/s1469026813500065","title":"COMPARISON OF PARALLEL PARTICLE SWARM OPTIMIZERS FOR GRAPHICAL PROCESSING UNITS AND MULTICORE PROCESSORS","year":2013,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"CUDA; Computer science; Parallel computing; Speedup; Multi-core processor; Particle swarm optimization; Central processing unit; General-purpose computing on graphics processing units; Algorithm; Graphics; Computer hardware; Operating system","authors":[{"name":"Vincent Roberge","is_ca":true},{"name":"Mohammed Tarbouchi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02901098590058832,"gpt":0.3121473107673336,"spread":0.2831363248667453,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008040945,0.00008144335,0.0001493368,0.00009621655,0.00004798743,0.00006403195,0.0001374575,0.00003651229,0.000008747744],"category_scores_gemma":[0.00003038597,0.00007438414,0.00003156552,0.0001335392,0.00008478768,0.0002391595,0.00001427465,0.00007994544,0.00000111494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001289432,"about_ca_system_score_gemma":0.00003181432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003306365,"about_ca_topic_score_gemma":8.700023e-7,"domain_scores_codex":[0.9991997,0.000007256198,0.0004633773,0.00007988913,0.0001692321,0.00008056614],"domain_scores_gemma":[0.9984418,0.0001591714,0.0001753888,0.00003092447,0.001127657,0.00006505933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002574252,0.00005840382,0.001137366,0.00003643334,0.00005946705,1.420639e-7,0.0003548474,0.8793135,0.0002547754,0.003227244,0.00006502749,0.115467],"study_design_scores_gemma":[0.00027483,0.00004614942,0.001613331,0.00004403933,0.00002341341,0.000017584,0.0003808971,0.983878,0.001517187,0.01170724,0.0004165298,0.00008084701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0895147,0.001395562,0.9083807,0.00036741,0.0000439801,0.0002505609,0.000008814527,0.00001533279,0.00002287315],"genre_scores_gemma":[0.954367,0.0002796676,0.04515257,0.0000389235,0.00006992644,0.00006394186,0.00001533912,0.000008440694,0.000004170968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8648523,"threshold_uncertainty_score":0.3033297,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2512972094","doi":"10.1142/s1469026816500176","title":"A New Parallel GA-Based Method for Constraint Satisfaction Problems","year":2016,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Constraint satisfaction problem; Crossover; Computer science; Heuristic; Mathematical optimization; Solver; Constraint satisfaction; Computation; Constraint (computer-aided design); Constraint programming; Local consistency; Genetic algorithm; Algorithm; Artificial intelligence; Mathematics; Machine learning","authors":[{"name":"Reza Abbasian","is_ca":true},{"name":"Malek Mouhoub","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.030263103537537,"gpt":0.3294731553865745,"spread":0.2992100518490375,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000332057,0.0001234228,0.0001479168,0.0002780497,0.00009065928,0.0001523938,0.0004148277,0.00005349357,0.00007144955],"category_scores_gemma":[0.00007808574,0.00009533222,0.0001144532,0.0001637113,0.00006405139,0.0005306354,0.00003696722,0.00007785618,0.00001104852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008406737,"about_ca_system_score_gemma":0.000391166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001167029,"about_ca_topic_score_gemma":0.000009942204,"domain_scores_codex":[0.9986451,0.00003797964,0.000581146,0.0002233389,0.0003904409,0.0001219849],"domain_scores_gemma":[0.997413,0.0007929339,0.0004581387,0.0001113371,0.001083195,0.000141332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001751207,0.00002476703,0.0003049037,0.000003532115,0.00004569429,7.197432e-7,0.00004852088,0.09940838,0.0001916965,0.2588877,0.0002749805,0.6407916],"study_design_scores_gemma":[0.001454707,0.0002274914,0.005298041,0.0001583128,0.00003397352,0.0004181638,0.00006720078,0.3028052,0.001551864,0.6596522,0.02798785,0.0003449992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00006228543,0.00006152311,0.9878145,0.01131688,0.0002648709,0.0003066265,0.00001980777,0.00003666638,0.0001168397],"genre_scores_gemma":[0.2513592,0.00006230406,0.747825,0.00043627,0.0002000668,0.00004325791,0.000006082777,0.000006677875,0.00006111532],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6404466,"threshold_uncertainty_score":0.3887535,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025201938","doi":"10.1142/s1469026805001441","title":"USING COMPETITIVE CO-EVOLUTION TO EVOLVE BETTER PATTERN RECOGNISERS","year":2005,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Task (project management); Software; Binary number; Artificial intelligence; Reliability (semiconductor); Base (topology); Pattern recognition (psychology); Arithmetic","authors":[{"name":"Taras Kowaliw","is_ca":true},{"name":"Nawwaf Kharma","is_ca":true},{"name":"Christopher Jensen","is_ca":true},{"name":"Hussein Moghnieh","is_ca":true},{"name":"Jie Yao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03700165440096965,"gpt":0.3397540574526187,"spread":0.3027524030516491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000266517,0.0001518155,0.0001653298,0.0003788958,0.0001847657,0.0001757003,0.0009162451,0.00005157736,0.00004208509],"category_scores_gemma":[0.00002207783,0.0001532097,0.0001011143,0.0003435769,0.0000904089,0.0007750137,0.0001372073,0.0001868126,0.0001154705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002220133,"about_ca_system_score_gemma":0.0001689687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001420053,"about_ca_topic_score_gemma":0.000004192669,"domain_scores_codex":[0.9982958,0.00003913846,0.0006294781,0.0002827703,0.0005808673,0.0001719608],"domain_scores_gemma":[0.9978098,0.0002207147,0.0003491388,0.0001643221,0.001268451,0.0001875954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001385187,0.0003169611,0.0009020627,0.00000464168,0.0001314045,0.00000585731,0.0005132271,0.2097179,0.0004085762,0.2809992,0.0007552872,0.5062311],"study_design_scores_gemma":[0.0006282615,0.0002308624,0.01120435,0.0001682362,0.00005232821,0.00114101,0.0006599033,0.6292372,0.002199264,0.2046584,0.1490898,0.000730452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005558957,0.000145186,0.9845346,0.008626061,0.0001526563,0.0001766774,0.00003479241,0.00003092266,0.0007400977],"genre_scores_gemma":[0.6940048,0.00003448487,0.3038094,0.001360244,0.0006947556,0.00003343711,0.00001638988,0.000008699159,0.00003781725],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6884458,"threshold_uncertainty_score":0.624771,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980383049","doi":"10.1142/s1469026804001410","title":"ROTATIONAL MATCHING PROBLEMS","year":2004,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Geomagnetism and Paleomagnetism Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Rotation (mathematics); Computer science; Algorithm; Fourier transform; Orientation (vector space); Function (biology); Matching (statistics); Fourier series; Mathematics; Mathematical analysis; Artificial intelligence; Geometry; Statistics","authors":[{"name":"Gregory S. Chirikjian","is_ca":false},{"name":"Peter T. Kim","is_ca":true},{"name":"Ja‐Yong Koo","is_ca":false},{"name":"Christine H. Lee","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01418413911060131,"gpt":0.2834823705571947,"spread":0.2692982314465934,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001249604,0.00009052869,0.00008568016,0.00008954291,0.00008198086,0.00004902755,0.0002387084,0.00003875695,0.0000176261],"category_scores_gemma":[0.0000221656,0.00008572717,0.00006148027,0.00006608183,0.00009768489,0.00001790268,0.00006058172,0.00007758713,0.00001261179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001243394,"about_ca_system_score_gemma":0.00009687593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009538862,"about_ca_topic_score_gemma":0.000009197084,"domain_scores_codex":[0.9991546,0.00001252483,0.000336703,0.0001327002,0.0002780937,0.00008532286],"domain_scores_gemma":[0.9990941,0.00003324518,0.000192003,0.00005788721,0.0005640762,0.00005864573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000662531,0.0002568733,0.001619027,0.00001579733,0.0002508791,0.000009220951,0.0005211859,0.839322,0.00662711,0.08761951,0.0003050861,0.06338706],"study_design_scores_gemma":[0.001142689,0.0007109151,0.02730546,0.0001228297,0.00005077546,0.001340648,0.0007929876,0.0003034118,0.007229912,0.9090199,0.05152998,0.0004504765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1270257,0.001575597,0.8682972,0.001908525,0.0001864751,0.0001496741,0.00002372989,0.00000627742,0.0008267773],"genre_scores_gemma":[0.9816647,0.0005443473,0.01683919,0.0003094018,0.0004854165,0.00002358528,0.00005477972,0.000007374068,0.00007122826],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.854639,"threshold_uncertainty_score":0.3495852,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2808950187","doi":"10.1142/s1469026818500104","title":"A Strength Pareto Evolutionary Algorithm for Optimizing System-On-Chip Test Schedules","year":2018,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Pareto principle; Evolutionary algorithm; System on a chip; Chip; Pareto optimal; Scheduling (production processes); Embedded system; Parallel computing; Multi-objective optimization; Mathematical optimization; Artificial intelligence; Machine learning","authors":[{"name":"Wissam Marrouche","is_ca":false},{"name":"Rana Farah","is_ca":true},{"name":"Haidar Harmanani","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03092966379209095,"gpt":0.3078852919468777,"spread":0.2769556281547867,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002993454,0.0001388113,0.0001614075,0.0002820945,0.000272326,0.0002122312,0.0008732826,0.00004670701,0.000005345986],"category_scores_gemma":[0.0001311139,0.0001291333,0.000103424,0.0002351445,0.0001347532,0.0004118784,0.00008625209,0.0001371377,0.00002383802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009438257,"about_ca_system_score_gemma":0.000177988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003727293,"about_ca_topic_score_gemma":8.508183e-7,"domain_scores_codex":[0.9985194,0.00002436462,0.000562862,0.000255697,0.0004741634,0.0001635768],"domain_scores_gemma":[0.9965138,0.001092583,0.0004098054,0.0001336919,0.00173337,0.0001167876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002593694,0.0001777116,0.0002464786,0.00001001658,0.00008179376,0.000006142691,0.0001413273,0.01361929,0.00004843869,0.3702066,0.0001866624,0.6152729],"study_design_scores_gemma":[0.0002616851,0.0003679535,0.0009736349,0.0002299011,0.00001885574,0.0004397432,0.0003811954,0.9033441,0.0007817165,0.08981027,0.003182219,0.0002087543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001179322,0.0001840262,0.996749,0.0008242757,0.0003140038,0.0001725015,0.00004655191,0.0000498741,0.0004803917],"genre_scores_gemma":[0.7209122,0.00002230563,0.2777213,0.0002403261,0.001030935,0.00003707328,0.00001367208,0.000007901956,0.00001438078],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8897248,"threshold_uncertainty_score":0.5265902,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3043139694","doi":"10.1142/s1469026820500108","title":"A Novel Nature-Inspired Technique Based on Mushroom Reproduction for Constraint Solving and Optimization","year":2020,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Constraint (computer-aided design); Mathematical optimization; Reproduction; Optimization problem; Set (abstract data type); Computation; Process (computing); Mushroom; Algorithm; Mathematics; Ecology; Biology","authors":[{"name":"Mahdi Bidar","is_ca":true},{"name":"Malek Mouhoub","is_ca":true},{"name":"Samira Sadaoui","is_ca":true},{"name":"Hamidreza Rashidy Kanan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02621352050204756,"gpt":0.2998587408069799,"spread":0.2736452203049323,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002869258,0.000121587,0.0001412612,0.0002251303,0.0001280067,0.0001943059,0.0003118188,0.00008101869,0.00001196868],"category_scores_gemma":[0.0002280339,0.0001217707,0.00006593945,0.000226196,0.00009245372,0.0003991787,0.00004467658,0.000202921,0.000001132867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004590785,"about_ca_system_score_gemma":0.0001518552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000145845,"about_ca_topic_score_gemma":4.454818e-7,"domain_scores_codex":[0.9987608,0.00002237975,0.0004830745,0.0003086303,0.0003360868,0.00008901817],"domain_scores_gemma":[0.9980929,0.0003217052,0.0003921044,0.00009877568,0.0009817642,0.0001127822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003490761,0.00005941984,0.00004696829,0.00001028126,0.00002688898,9.795048e-7,0.0001025154,0.8311257,0.0003455035,0.08379485,0.00004676351,0.08440518],"study_design_scores_gemma":[0.000324569,0.0001489403,0.0002273874,0.00004848078,0.00001168593,0.0001309156,0.00006359536,0.9860693,0.001635986,0.009266056,0.001945242,0.000127899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008643018,0.00007428039,0.984416,0.0146532,0.0001636201,0.000429548,0.00002086106,0.00004416869,0.000111909],"genre_scores_gemma":[0.4945905,0.00004442293,0.5036904,0.001410295,0.0001891907,0.00004826007,0.00001839887,0.000006203023,0.000002363488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4945041,"threshold_uncertainty_score":0.4965665,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2017351056","doi":"10.1142/s1469026815500029","title":"Collaborative Parallel Hybrid Metaheuristics on Graphics Processing Unit","year":2015,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Computer science; Parallel computing; Metaheuristic; Speedup; Graphics processing unit; CUDA; Parallel metaheuristic; Asynchronous communication; Simulated annealing; Instruction set; Multi-core processor; Algorithm","authors":[{"name":"Vincent Roberge","is_ca":true},{"name":"Mohammed Tarbouchi","is_ca":true},{"name":"Francis A. Okou","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06856806425648525,"gpt":0.3758262417399429,"spread":0.3072581774834576,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000677082,0.0001421643,0.0001898825,0.0004839206,0.0001143121,0.0004311708,0.00110615,0.00003614532,0.00001166768],"category_scores_gemma":[0.0003584518,0.0001275848,0.0000561303,0.0006270946,0.0001519021,0.0005800615,0.000139659,0.0002582513,0.00003416535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005967381,"about_ca_system_score_gemma":0.00061885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002885463,"about_ca_topic_score_gemma":4.905759e-7,"domain_scores_codex":[0.9976573,0.0001013226,0.0006297067,0.0002316632,0.001236568,0.0001434252],"domain_scores_gemma":[0.9928662,0.0004470194,0.0004759187,0.0001562706,0.005802148,0.0002525046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003502887,0.000208121,0.00007687879,0.000004897926,0.00008631688,0.00002894507,0.0002687686,0.4040616,0.000002017166,0.4944473,0.0008258965,0.09995418],"study_design_scores_gemma":[0.0003358593,0.0001862814,0.0002291297,0.00003907557,0.00001568142,0.0002722693,0.0001918929,0.6318662,0.0002117362,0.3411351,0.02533987,0.0001769278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002323764,0.0003827498,0.9948708,0.002957948,0.0002081164,0.0001819162,0.00001919379,0.00002648491,0.001120453],"genre_scores_gemma":[0.5268899,0.000343732,0.471307,0.0008750308,0.0003647537,0.00003949127,0.0000283402,0.00001466279,0.0001370645],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5266575,"threshold_uncertainty_score":0.5202757,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2904101610","doi":"10.1142/s1469026818500220","title":"Multidirectional Grey Wolf Optimizer Algorithm for Solving Global Optimization Problems","year":2018,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Thompson Rivers University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Mathematical optimization; Minimax; Heuristics; Algorithm; Integer programming; Integer (computer science); Local search (optimization); Convergence (economics); Search algorithm; Mathematics","authors":[{"name":"Mohamed A. Tawhid","is_ca":true},{"name":"Ahmed F. Ali","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03535944098536298,"gpt":0.348958549445557,"spread":0.313599108460194,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006516859,0.000173146,0.0002094386,0.0003128351,0.0002709873,0.0004543366,0.001081296,0.00007596822,0.00008126048],"category_scores_gemma":[0.0002195007,0.0001678021,0.0001206548,0.0005230321,0.0002198555,0.0008732214,0.0001848693,0.0001431045,0.00002082251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001492486,"about_ca_system_score_gemma":0.0003217158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008366419,"about_ca_topic_score_gemma":0.000001649915,"domain_scores_codex":[0.9977069,0.00004720294,0.0008085579,0.0003525028,0.0008636136,0.0002211965],"domain_scores_gemma":[0.9927086,0.000463635,0.0005189104,0.0001682304,0.005961633,0.0001789495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001388158,0.0001386669,0.00005066604,0.000005084422,0.0001115462,0.000001807131,0.00009440492,0.6371521,0.000006641457,0.04286236,0.0003564477,0.3192064],"study_design_scores_gemma":[0.0003427544,0.0001350696,0.0001242627,0.00003257491,0.0000137382,0.0002329184,0.00003793375,0.94282,0.0001997354,0.05062442,0.005282395,0.0001541663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003241841,0.0001867655,0.9966131,0.001581864,0.0006571093,0.0004332892,0.00005537642,0.00004754267,0.0003925452],"genre_scores_gemma":[0.0232558,0.0001664039,0.975031,0.0003030753,0.0009824737,0.00010022,0.00004176293,0.00001293713,0.0001063275],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3190522,"threshold_uncertainty_score":0.6842772,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2000038675","doi":"10.1142/s1469026808002193","title":"SYSTEMATIC VERSUS LOCAL SEARCH AND GA TECHNIQUES FOR INCREMENTAL SAT","year":2008,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Satisfiability; Computer science; Completeness (order theory); Propositional calculus; Boolean satisfiability problem; Mathematical optimization; Range (aeronautics); Approximation algorithm; Conjunctive normal form; Local search (optimization); Set (abstract data type); Mathematics; Theoretical computer science; Algorithm","authors":[{"name":"Malek Mouhoub","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07812007125231435,"gpt":0.3857766504357405,"spread":0.3076565791834261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005784839,0.0001007571,0.0001678659,0.0002310599,0.000157163,0.00009745694,0.0006206235,0.00004326491,0.000003024948],"category_scores_gemma":[0.00009031058,0.00009208632,0.00006172388,0.0001510448,0.0001989915,0.0005313532,0.000116943,0.0001164082,0.000005340468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008179002,"about_ca_system_score_gemma":0.0001057909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005760157,"about_ca_topic_score_gemma":8.11282e-7,"domain_scores_codex":[0.9986306,0.00005525962,0.0005657523,0.000173208,0.0004704832,0.0001047302],"domain_scores_gemma":[0.9980317,0.0005709378,0.000248763,0.0001142322,0.0009503658,0.00008402335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001501227,0.0001964438,0.0001474806,0.000361693,0.0002438497,0.000009045664,0.001014768,0.01777983,0.0002591395,0.873885,0.0001283013,0.1058243],"study_design_scores_gemma":[0.001041199,0.0009223342,0.002096423,0.0009003542,0.00007223891,0.003050942,0.001067354,0.8307506,0.01838541,0.1389852,0.002187459,0.0005405312],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004602219,0.0003250357,0.9939065,0.0004643671,0.0001774046,0.0003841242,0.000008773223,0.00002592525,0.0001056441],"genre_scores_gemma":[0.5950691,0.0001480472,0.4044839,0.00009638286,0.0001161313,0.00006404561,0.000006524039,0.000004681652,0.00001118002],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8129708,"threshold_uncertainty_score":0.3755171,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3208450211","doi":"10.1142/s1469026821500218","title":"FUSIONET: A Hybrid Model Towards Image Classification","year":2021,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Artificial intelligence; Classifier (UML); Contextual image classification; Pattern recognition (psychology); Image (mathematics); Pixel; Feature (linguistics); Representation (politics); Object (grammar); Computer vision","authors":[{"name":"Molokwu C. Reginald","is_ca":false},{"name":"Molokwu C. Bonaventure","is_ca":true},{"name":"Victor C. Molokwu","is_ca":false},{"name":"Okeke C. Ogochukwu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04350850150595689,"gpt":0.3573988894882072,"spread":0.3138903879822504,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002197129,0.0001131465,0.0001463441,0.0001825689,0.00009573982,0.0002393928,0.0007447438,0.00003381003,0.00001988926],"category_scores_gemma":[0.00009776904,0.0001087084,0.0000975081,0.0002641109,0.0000839912,0.0009397023,0.0001907114,0.0001766366,0.00001547186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006255897,"about_ca_system_score_gemma":0.0003329002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001454359,"about_ca_topic_score_gemma":3.561103e-7,"domain_scores_codex":[0.9985429,0.00003113697,0.0005376572,0.0002333692,0.0005437821,0.0001111457],"domain_scores_gemma":[0.9967996,0.0001415048,0.000340054,0.0001801432,0.002439554,0.00009914555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001238684,0.0001845005,0.00002691528,0.000006439125,0.00005429591,0.00004097878,0.0001315518,0.01701351,0.002904698,0.362651,0.0005656499,0.6164081],"study_design_scores_gemma":[0.0001144304,0.00003789762,0.0004240433,0.00003484096,0.00001019719,0.0007041946,0.00006852962,0.3058842,0.0377153,0.6464106,0.008452693,0.0001430957],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007095236,0.0004677352,0.9935848,0.003883,0.0001077087,0.00008961467,0.00001459133,0.00004281388,0.001100282],"genre_scores_gemma":[0.5318788,0.0008565689,0.4662978,0.0006637017,0.0001605445,0.00001711981,0.00001939614,0.00000704992,0.00009897484],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6162649,"threshold_uncertainty_score":0.4432999,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2076906193","doi":"10.1142/s1469026805001611","title":"A GENETIC ALGORITHM FOR THE DESIGN OF MINIMUM-COST TWO-CONNECTED NETWORKS WITH BOUNDED RINGS","year":2005,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tabu search; Computer science; Bounded function; Genetic algorithm; Algorithm; Mathematical optimization; Network planning and design; Constraint (computer-aided design); Ring (chemistry); Enhanced Data Rates for GSM Evolution; Mathematics; Artificial intelligence; Machine learning; Computer network","authors":[{"name":"Mario Ventresca","is_ca":true},{"name":"Beatrice M. Ombuki","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01981469221337038,"gpt":0.2802936908947584,"spread":0.260478998681388,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000170486,0.00009888713,0.0001229006,0.0001150664,0.00005963759,0.00005406043,0.0003095524,0.00003204492,0.00001261985],"category_scores_gemma":[0.00001012414,0.00007290301,0.00005193884,0.00012268,0.00009158826,0.0001203545,0.00001324911,0.0001091954,0.000001332733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003715397,"about_ca_system_score_gemma":0.00004346935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003338163,"about_ca_topic_score_gemma":0.000001974669,"domain_scores_codex":[0.9991878,0.00001251732,0.0004069629,0.00008117067,0.000219059,0.00009249213],"domain_scores_gemma":[0.9984161,0.0006395021,0.0001736191,0.00006579153,0.0006623922,0.00004255888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001571102,0.00002586468,0.00001874286,0.000002493209,0.0001090668,5.458919e-7,0.00006048413,0.69899,0.00007270164,0.00228106,0.0001335992,0.2982897],"study_design_scores_gemma":[0.0002083489,0.0000749222,0.0002466523,0.00003558572,0.00003703747,0.0001394643,0.0000522987,0.9822572,0.002106699,0.01195979,0.002794813,0.0000871274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007845811,0.0007221306,0.9977245,0.0002305401,0.00005333253,0.000401868,0.0000157124,0.00002706298,0.0000402311],"genre_scores_gemma":[0.6695532,0.0002854459,0.3296326,0.000076863,0.0003192764,0.0001067303,0.000005762072,0.00001220689,0.000007842713],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6687686,"threshold_uncertainty_score":0.2972898,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980452543","doi":"10.1142/s1469026804001409","title":"FINDING CONSERVED WELL-ORDERED RNA STRUCTURES IN GENOMIC SEQUENCES","year":2004,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; U.S. Department of Health and Human Services","keywords":"Computational biology; RNA; Genome; Nucleic acid structure; Base pair; Gene; Ribozyme; Biology; Genetics; Nucleic acid secondary structure; Conserved sequence; Caenorhabditis elegans; Computer science; Base sequence","authors":[{"name":"Shu‐Yun Le","is_ca":false},{"name":"Jacob V. Maizel","is_ca":false},{"name":"Kaizhong Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02260537293304751,"gpt":0.3050428772907436,"spread":0.2824375043576961,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001711946,0.00008806127,0.00009925674,0.0001291764,0.00004959483,0.00005027944,0.000298598,0.00005611697,0.00003014172],"category_scores_gemma":[0.00003494195,0.00008307584,0.00005508947,0.00007054877,0.00007549248,0.00001514385,0.00004296912,0.00008013404,0.000006744583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003059931,"about_ca_system_score_gemma":0.000148247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002078095,"about_ca_topic_score_gemma":0.00001546326,"domain_scores_codex":[0.9991868,0.00002447609,0.0003678331,0.0001393437,0.0001949436,0.00008656175],"domain_scores_gemma":[0.9993743,0.00004665752,0.0002163259,0.00006144308,0.0002523258,0.00004895479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001930361,0.0001726087,0.001915641,0.00001402384,0.0002154704,0.00002437076,0.0002734508,0.5303525,0.2993986,0.1101322,0.00005578891,0.05725237],"study_design_scores_gemma":[0.0006278915,0.000202673,0.007104369,0.00008472683,0.00001727368,0.0004467038,0.0004938761,0.0004103769,0.3243211,0.6594865,0.006533382,0.0002711699],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5610201,0.0006818088,0.4368326,0.0009295503,0.0001214949,0.0001351939,0.00001139629,0.000003190401,0.0002646732],"genre_scores_gemma":[0.9850237,0.0003581351,0.01406551,0.000258085,0.0002266069,0.00001533201,0.00002289955,0.000006908726,0.00002278803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5493543,"threshold_uncertainty_score":0.3387735,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1991109541","doi":"10.1142/s1469026802000476","title":"STABILITY OF INFORMATION GRANULATION AND INFORMATION GRANULES","year":2002,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canadian Space Agency; University of Alberta","funders":"","keywords":"Computer science; Stability (learning theory); Granulation; Inference; Artificial intelligence; Machine learning","authors":[{"name":"Witold Pedrycz","is_ca":true},{"name":"George Vukovich","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02279419322593393,"gpt":0.2657192544528736,"spread":0.2429250612269397,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002453449,0.00009403662,0.0001434309,0.000252866,0.00008809265,0.0001770318,0.0004584558,0.00004144698,0.00002068224],"category_scores_gemma":[0.00004518357,0.00008669896,0.00005328326,0.0002788799,0.0001122588,0.003554159,0.00009146055,0.0001144948,0.0000109105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002347106,"about_ca_system_score_gemma":0.00002592045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006978995,"about_ca_topic_score_gemma":7.819318e-7,"domain_scores_codex":[0.9986281,0.00002681026,0.0007490139,0.00009006538,0.0004204377,0.00008559506],"domain_scores_gemma":[0.9978443,0.0002436856,0.0005961856,0.0001240692,0.001115622,0.00007611716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008284805,0.00006290631,0.0004694262,0.00001439994,0.00002784117,2.273619e-7,0.0004517815,0.01052555,0.00003276907,0.6057215,0.0001602842,0.382525],"study_design_scores_gemma":[0.0005788425,0.0001730456,0.01463451,0.00007733673,0.00003154193,0.0002706293,0.0003289429,0.4689783,0.00194386,0.4674743,0.04520329,0.0003053184],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009174338,0.0001994226,0.9867248,0.003098267,0.00009548317,0.0001780966,0.00002082917,0.00001824992,0.000490516],"genre_scores_gemma":[0.9648753,0.000552687,0.03412699,0.0003218185,0.00008452032,0.00001789437,0.00001664285,0.000002134572,0.000002024582],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9557009,"threshold_uncertainty_score":0.3535481,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4395455684","doi":"10.1142/s1469026824500081","title":"A Hybrid Method for Multiple Sclerosis Lesion Segmentation Using Wavelet and Dense U-Net","year":2024,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Segmentation; Artificial intelligence; Pattern recognition (psychology); Wavelet; Deep learning; Lesion; Image segmentation; Computer vision; Medicine; Pathology","authors":[{"name":"Ali Alijamaat","is_ca":false},{"name":"Seyed Mohsen Mirhosseini","is_ca":false},{"name":"Reyhaneh Aliakbari","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1556429860091171,"gpt":0.3883873247729894,"spread":0.2327443387638723,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003230372,0.0001052735,0.0001101476,0.0002812382,0.0001564475,0.0002573014,0.000159009,0.00003183962,0.0000161459],"category_scores_gemma":[0.0001650785,0.00009886333,0.00007150846,0.0001515782,0.00008819565,0.0003538701,0.00003272737,0.0001213807,0.000005890618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000740619,"about_ca_system_score_gemma":0.00008071191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006588486,"about_ca_topic_score_gemma":0.00000118123,"domain_scores_codex":[0.9988365,0.00005779601,0.0004421525,0.0002499165,0.0003211987,0.00009250311],"domain_scores_gemma":[0.9981424,0.001167938,0.0002088997,0.00005341341,0.0003513373,0.00007605684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001094595,0.00010998,0.00003692639,0.00004590498,0.00005853726,0.00000760391,0.0003561671,0.02929508,0.2071158,0.06085784,0.0002495948,0.7017571],"study_design_scores_gemma":[0.0002378778,0.0000766508,0.000410059,0.0001089113,0.00003888656,0.0009693208,0.0002043987,0.7824937,0.1177316,0.09049492,0.00709188,0.0001417962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05448082,0.0002013857,0.9433222,0.001323203,0.0002702697,0.0002730759,0.00006942723,0.00002690014,0.00003274334],"genre_scores_gemma":[0.9244742,0.0003094728,0.07445876,0.0004121426,0.0002296316,0.00004876121,0.00001500545,0.00001370391,0.00003834837],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8699933,"threshold_uncertainty_score":0.4031529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2072651133","doi":"10.1142/s1469026802000567","title":"AN INTELLIGENT HYBRID APPROACH FOR CONTENT-BASED IMAGE RETRIEVAL","year":2002,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Nipissing University","funders":"","keywords":"Computer science; Artificial intelligence; Artificial neural network; Pattern recognition (psychology); Feature extraction; Multilayer perceptron; Image retrieval; Benchmark (surveying); Feature (linguistics); Content-based image retrieval; Image (mathematics); Perceptron; Data mining","authors":[{"name":"Sanjeev R. Kulkarni","is_ca":true},{"name":"Brijesh Verma","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07467256335619954,"gpt":0.3267128633933928,"spread":0.2520403000371933,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004179786,0.0001519583,0.0001850722,0.0002970808,0.0001337392,0.00035213,0.001080802,0.00004692554,0.00003171958],"category_scores_gemma":[0.00007881841,0.0001383544,0.0001463965,0.0002329121,0.000148294,0.0007977101,0.00005217646,0.0001576002,0.000009868168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007269493,"about_ca_system_score_gemma":0.0000741318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001956364,"about_ca_topic_score_gemma":8.426508e-8,"domain_scores_codex":[0.9982629,0.00004577224,0.0006874747,0.0002869813,0.0005632395,0.000153665],"domain_scores_gemma":[0.9966385,0.00028976,0.0004680809,0.0002166862,0.002233668,0.0001532873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001599502,0.002146944,0.0001128965,0.00004900317,0.0002204527,0.00001714494,0.0003797664,0.01167816,0.01070721,0.5407203,0.0006706703,0.4331375],"study_design_scores_gemma":[0.0003159161,0.0003354295,0.0001038233,0.00002600563,0.00002162405,0.0002713475,0.0001487279,0.7874011,0.1390809,0.06520926,0.006828621,0.0002572285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003934021,0.0002809574,0.9967009,0.001901486,0.0001273621,0.0003469533,0.00003179509,0.00006528835,0.0001519003],"genre_scores_gemma":[0.4749535,0.000124795,0.5240055,0.0005387198,0.0002328491,0.00004455063,0.0000370177,0.00001013659,0.00005299422],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.775723,"threshold_uncertainty_score":0.5641928,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1972768104","doi":"10.1142/s1469026811003148","title":"VIRTUAL INSTRUMENTATION BASED SYSTEMS FOR REAL-TIME PATH PLANNING OF MOBILE ROBOTS USING BIO-INSPIRED NEURAL NETWORKS","year":2011,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Artificial neural network; Instrumentation (computer programming); Motion planning; Robot; Path (computing); Software; Mobile robot; Artificial intelligence; Trajectory; Controller (irrigation); Real-time computing; Computer network","authors":[{"name":"Abdallah Hammad","is_ca":true},{"name":"Simon X. Yang","is_ca":true},{"name":"Mohamed Tarek Elewa","is_ca":false},{"name":"Hala Mansour","is_ca":false},{"name":"SALAH ALI","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05692463903864865,"gpt":0.3222258162242942,"spread":0.2653011771856456,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003772567,0.0001368338,0.0002248683,0.0002981662,0.0001007063,0.00009756452,0.0006898997,0.00006006219,0.000004457365],"category_scores_gemma":[0.00002701063,0.0001338551,0.00009297256,0.0002333437,0.0000874441,0.0004819494,0.00006401927,0.0001049769,0.00000144171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006406219,"about_ca_system_score_gemma":0.0001423967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003113697,"about_ca_topic_score_gemma":6.908147e-8,"domain_scores_codex":[0.9983556,0.00005229564,0.0008074746,0.0002078497,0.0004329652,0.0001438132],"domain_scores_gemma":[0.9974738,0.0004116783,0.0008674872,0.0001247306,0.001030664,0.00009162161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000326924,0.0001044235,0.0005915262,0.000007678219,0.00006548126,0.000004709815,0.0003761243,0.9725938,0.0002432607,0.009044764,0.00001964685,0.01691593],"study_design_scores_gemma":[0.0002359245,0.0002449678,0.001027805,0.0001080922,0.00002123102,0.0001057594,0.000163778,0.994163,0.0005799652,0.003203579,0.00002636118,0.0001195511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.021972,0.0001692507,0.9770185,0.0000406876,0.0003956497,0.0003177395,0.00002092288,0.00002502955,0.00004023323],"genre_scores_gemma":[0.7308913,0.00002002715,0.2688088,0.00004131839,0.0001600781,0.00003890004,0.00002575883,0.000008713204,0.000005073519],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7089193,"threshold_uncertainty_score":0.5458453,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2062972627","doi":"10.1142/s1469026806002039","title":"A MEMETIC ALGORITHM FOR PERFORMING MEMORY ASSIGNMENT IN DUAL-BANK DSPS","year":2006,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo; University of Guelph","funders":"","keywords":"Computer science; Parallel computing; Memetic algorithm; Digital signal processing; Compiler; Memory bandwidth; Digital signal processor; Interleaved memory; Computer memory; Semiconductor memory; Algorithm; Computer hardware; Local search (optimization); Programming language","authors":[{"name":"Gary Gréwal","is_ca":true},{"name":"Stelian Coros","is_ca":true},{"name":"Marc J. Ventresca","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01913398475210874,"gpt":0.3074125670904509,"spread":0.2882785823383422,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005129917,0.0001126323,0.0001545765,0.000385337,0.00008973962,0.0001530955,0.0004614266,0.00004367614,0.000006255248],"category_scores_gemma":[0.00002500443,0.0001097349,0.00007932544,0.000233807,0.00005273318,0.0003587442,0.00008402054,0.0001220503,0.000003367816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008774488,"about_ca_system_score_gemma":0.0001143108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001735476,"about_ca_topic_score_gemma":0.000002357743,"domain_scores_codex":[0.9985678,0.0000322513,0.0006526767,0.0001978799,0.0004148138,0.0001345395],"domain_scores_gemma":[0.9984037,0.0003772958,0.0003489853,0.00009717296,0.0007229509,0.00004988847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006929878,0.0001924397,0.0001058427,0.000005532167,0.00002927509,0.000008737379,0.0001266932,0.5015359,0.00003947881,0.1113717,0.0003332016,0.3862443],"study_design_scores_gemma":[0.0002349727,0.00006925826,0.0004588329,0.00004589159,0.000006239246,0.0001839772,0.00004604247,0.7528172,0.001421887,0.2416014,0.002983261,0.0001310422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007212806,0.0002741578,0.9970271,0.001164204,0.0001494714,0.0002291816,0.000006625576,0.00003358709,0.0003943718],"genre_scores_gemma":[0.4696938,0.00005300585,0.5296625,0.0001876759,0.0002551429,0.00005756699,0.0000134949,0.000006238512,0.00007060946],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4689725,"threshold_uncertainty_score":0.4474857,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1963955771","doi":"10.1142/s146902680300080x","title":"MAPPING REFERENCE CODE TO IRREGULAR DSPS WITHIN THE RETARGETABLE, OPTIMIZING COMPILER COGEN(T)","year":2003,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Unreachable code; Dead code; Compiler; Parallel computing; Code generation; Programming language; Code (set theory); Object code; Redundant code; Set (abstract data type); Schedule; Abstraction; Dead code elimination; Operating system","authors":[{"name":"Gary Gréwal","is_ca":true},{"name":"Charles Thomas Wilson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0412803169757754,"gpt":0.3028998724390257,"spread":0.2616195554632503,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007324914,0.0001650147,0.0001815354,0.0002488962,0.0003635018,0.000274609,0.001433939,0.00005088123,0.00002856242],"category_scores_gemma":[0.00008346821,0.0001319933,0.00008646372,0.0006121424,0.000129405,0.0004848761,0.0001615567,0.0002828836,0.00005517595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007410556,"about_ca_system_score_gemma":0.0002336329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000677687,"about_ca_topic_score_gemma":0.000002738074,"domain_scores_codex":[0.997993,0.00008774608,0.0007693459,0.0003036889,0.000665873,0.0001803485],"domain_scores_gemma":[0.9973167,0.000419993,0.0004577429,0.0002791299,0.001355859,0.000170561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004615364,0.00009435235,0.0001036725,0.000002755152,0.00007029041,0.000003402797,0.0004838975,0.2551626,0.0001671676,0.7331163,0.0004947694,0.01029621],"study_design_scores_gemma":[0.0003286746,0.0001158515,0.002542392,0.0001132859,0.00002658428,0.001173061,0.001272362,0.1680303,0.002159324,0.5890368,0.2347197,0.0004815966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0020058,0.0004564524,0.9895613,0.006161309,0.0002452366,0.0002866886,0.00001950227,0.00003021832,0.001233535],"genre_scores_gemma":[0.6318509,0.00009693958,0.366416,0.001225762,0.0001786719,0.00007958747,0.00001272999,0.000009825909,0.0001296027],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6298451,"threshold_uncertainty_score":0.5382529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2146234362","doi":"10.1142/s146902680400129x","title":"EVALUATION OF SELECTING INTERVAL VALUES OF INPUT VARIABLES IN CONNECTIONIST NETWORKS","year":2004,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Connectionism; Variable (mathematics); Selection (genetic algorithm); Interval (graph theory); Artificial neural network; Feature selection; Entropy (arrow of time); Value (mathematics); Artificial intelligence; Principle of maximum entropy; Backpropagation; Data mining; Machine learning; Mathematics","authors":[{"name":"David Chiu","is_ca":true},{"name":"BOGDAN J. BUCZYNSKI","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03888642290138364,"gpt":0.3370188435194664,"spread":0.2981324206180828,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001259428,0.0001033904,0.0002046276,0.0003042512,0.00006334494,0.00006546191,0.0006554992,0.00004983703,0.00000886431],"category_scores_gemma":[0.0001001535,0.0001008725,0.00008313436,0.0005629346,0.000116741,0.0004101715,0.00009806797,0.0001725556,0.000001118306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001094483,"about_ca_system_score_gemma":0.0002835421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005405191,"about_ca_topic_score_gemma":0.00001640981,"domain_scores_codex":[0.9979519,0.00007974334,0.0009051235,0.0001813047,0.0007764081,0.0001055],"domain_scores_gemma":[0.9961526,0.0003695829,0.0007410857,0.0001266825,0.002558494,0.00005159298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007363552,0.0001799664,0.0003587013,0.000004337569,0.00005234213,6.052613e-7,0.0001727124,0.769686,0.0001479401,0.1773981,0.00001019708,0.05198162],"study_design_scores_gemma":[0.000405571,0.000105663,0.003591923,0.0001601275,0.00003557255,0.0001120854,0.0001474324,0.4641647,0.002751064,0.5282987,0.0001218279,0.0001052649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04697128,0.0004234183,0.9511623,0.0007840159,0.0001630205,0.0002012566,0.000004430152,0.000009176742,0.0002810453],"genre_scores_gemma":[0.9703013,0.0001485957,0.02929617,0.00006169781,0.0001504845,0.00002657849,0.000006356936,0.000005405033,0.00000343917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.92333,"threshold_uncertainty_score":0.4113463,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2198849238","doi":"10.1142/s1469026815500248","title":"A Soft Sensor Based on the Integration of Tikhonov Extreme Learning Machine and Accelerated Kernels for Real-Time Estimation of Automotive Catalyst Temperatures","year":2015,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence and Applications","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Automotive industry; Computer science; Automotive engine; Tikhonov regularization; Mechatronics; Soft sensor; Artificial neural network; Transient (computer programming); Generalization; Artificial intelligence; Automotive engineering; Inverse problem; Process (computing)","authors":[{"name":"Ahmad Mozaffari","is_ca":true},{"name":"Nasser L. Azad","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05362392772180808,"gpt":0.3325191441223505,"spread":0.2788952164005424,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006435182,0.0001073674,0.0001689301,0.000222898,0.00008702291,0.00009544797,0.0003712435,0.00003612931,0.000006287095],"category_scores_gemma":[0.0004274727,0.00007806162,0.00005892079,0.0002097487,0.0000957837,0.000224031,0.00004464117,0.0001416423,0.000002127706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003214887,"about_ca_system_score_gemma":0.0001499569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004228882,"about_ca_topic_score_gemma":0.000001140253,"domain_scores_codex":[0.9987946,0.00008597767,0.0004929278,0.0001512779,0.000402626,0.00007263415],"domain_scores_gemma":[0.9965033,0.001030245,0.0005927807,0.00009600225,0.001716828,0.00006085559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008531103,0.0001330924,0.0002146348,0.00001142273,0.00006343584,8.869749e-7,0.0008631169,0.9014744,0.0008779367,0.03788863,0.0001351824,0.05825195],"study_design_scores_gemma":[0.0002292184,0.0002255433,0.0009618265,0.00007986905,0.00001482613,0.00003337237,0.0001630378,0.9741526,0.003868973,0.01997464,0.0002243795,0.00007174626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03355951,0.00005808665,0.9631632,0.002785829,0.00005329187,0.0001962772,0.00001949334,0.00001603116,0.0001482671],"genre_scores_gemma":[0.9538346,0.00001773554,0.04584385,0.0001144944,0.00005972556,0.00001817966,0.0000469567,0.000006175216,0.00005829605],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9202751,"threshold_uncertainty_score":0.3183261,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}