{"meta":{"query_hash":"69ae6be6d940","filters":{"venue":"Parallel and Distributed Computing and Networks"},"cohort_total":17,"direct_labels_cover":0,"predictions_cover":17,"exported":17,"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/69ae6be6d940","api":"https://metacan.xera.ac/api/v1/cohort?venue=Parallel+and+Distributed+Computing+and+Networks"},"results":[{"id":"W126718644","doi":"10.2316/p.2010.676-050","title":"An Experimental Model of Relay Deployment Planning Tool for a Wireless Sensor Network System to Monitor Civil Engineering Structures","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Software deployment; Default gateway; Wireless sensor network; Computer science; Relay; Reliability (semiconductor); Wireless; Key distribution in wireless sensor networks; Wireless network; Computer network; Distributed computing; Real-time computing; Telecommunications","score_opus":0.009502822532146127,"score_gpt":0.23839230228129166,"score_spread":0.22888947974914553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W126718644","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46581694,0.00026447105,0.5331986,0.00001661622,0.00034132568,0.00018225488,0.000008631851,0.00016713548,0.00000401751],"genre_scores_gemma":[0.86630315,0.000005125085,0.13314508,0.000044313234,0.0004186709,0.000023891676,0.000031010364,0.000026326143,0.0000024112796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99803966,0.000046927555,0.00044442705,0.0006255311,0.00020221363,0.0006412604],"domain_scores_gemma":[0.998784,0.00025603682,0.00017135165,0.000414794,0.00008330291,0.00029049316],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032944573,0.00032424988,0.00042509558,0.00006402987,0.00034763588,0.00020208441,0.00040022106,0.000196468,2.5331403e-7],"category_scores_gemma":[0.00001159498,0.0003105615,0.00006702245,0.0002337183,0.000045952176,0.000119190765,0.00025859068,0.00029533167,1.12666676e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059408896,0.0000374287,0.0006898016,0.0000376027,0.000028923861,0.0000046991026,0.00029287286,0.9842431,0.0018643519,0.011049017,0.0001439106,0.0015488627],"study_design_scores_gemma":[0.0005766411,0.00014638089,0.0006570861,0.00015635698,0.000015935506,0.000029499528,0.00008235118,0.9975065,0.00041333417,0.0000219294,0.000028582244,0.00036537615],"about_ca_topic_score_codex":0.000012331839,"about_ca_topic_score_gemma":0.0000026911807,"teacher_disagreement_score":0.40048623,"about_ca_system_score_codex":0.000027541668,"about_ca_system_score_gemma":0.000015086086,"threshold_uncertainty_score":0.9999347},"labels":[],"label_agreement":null},{"id":"W1455550877","doi":"10.2316/p.2010.676-052","title":"A Wait-Free Dynamic Storage Allocator by Adopting the Helping Queue Pattern","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Allocator; Queue; Operating system; Computer network","score_opus":0.004837392620360122,"score_gpt":0.21460570756073702,"score_spread":0.2097683149403769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1455550877","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1138444,0.0025107663,0.8813001,0.0012778428,0.00054114586,0.00018594955,0.00006304017,0.00020611034,0.00007065054],"genre_scores_gemma":[0.9970773,0.000095147276,0.0020855402,0.00039361036,0.00018812086,0.000012475174,0.00010014706,0.000014827434,0.00003283993],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980263,0.00010864872,0.00040569084,0.00061762764,0.00022173581,0.00062000315],"domain_scores_gemma":[0.998498,0.00026330774,0.0002153856,0.0007190534,0.000075080854,0.00022916027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065877626,0.0003058585,0.00032528967,0.000028636441,0.00080464536,0.00064566144,0.00094398553,0.00017466475,0.0000022253726],"category_scores_gemma":[0.000055006225,0.00022988593,0.00006733748,0.0002954275,0.0001392733,0.00018985574,0.00068993436,0.0006784143,0.0000027536705],"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":[0.00006387165,0.00036028493,0.017851623,0.00024578132,0.0003419218,0.00014059845,0.002400604,0.08351307,0.0008692216,0.019213134,0.053968526,0.82103133],"study_design_scores_gemma":[0.00063183124,0.000036287565,0.005317559,0.00008322212,0.000012200487,0.00009591012,0.000096987096,0.98475504,0.0000025529737,0.00020121946,0.0084378,0.00032936665],"about_ca_topic_score_codex":0.0001657333,"about_ca_topic_score_gemma":0.00006573414,"teacher_disagreement_score":0.901242,"about_ca_system_score_codex":0.000017735094,"about_ca_system_score_gemma":0.000026385615,"threshold_uncertainty_score":0.9374476},"labels":[],"label_agreement":null},{"id":"W2111977021","doi":"10.2316/p.2010.676-039","title":"Task Execution Availability Prediction in the Enterprise Desktop Grid","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Distributed computing; Grid; Grid computing; Bayesian network; Task (project management); Artificial intelligence","score_opus":0.007695744150670312,"score_gpt":0.22246649868464108,"score_spread":0.21477075453397076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111977021","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32258615,0.0004591766,0.67514586,0.0003755273,0.0007637667,0.00022054819,0.000026584443,0.0001554487,0.00026695145],"genre_scores_gemma":[0.9977467,0.000046730514,0.001460596,0.00016181153,0.00039007352,0.000012119732,0.000164805,0.000006077763,0.000011099308],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979495,0.00027604672,0.00046859917,0.00060176,0.00022378954,0.00048030444],"domain_scores_gemma":[0.9988248,0.0003110711,0.00015624019,0.0005034076,0.00006408521,0.00014039168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014897124,0.0002463757,0.0002647441,0.00005788103,0.00043646013,0.0004499731,0.00056477776,0.00017842502,0.0000026397945],"category_scores_gemma":[0.000068207475,0.00018651984,0.000060399492,0.00044986347,0.00013400675,0.00019732818,0.0002684249,0.00065046654,0.0000048115753],"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":[0.00025898585,0.0010518066,0.5862787,0.00022065437,0.00013142005,0.00013264474,0.006154748,0.19941862,0.0002707544,0.041632984,0.034443494,0.13000521],"study_design_scores_gemma":[0.00058730773,0.000079798716,0.15526405,0.0000470651,0.000009516373,0.00014169043,0.000072419825,0.8377471,0.0000011192268,0.0010372404,0.004810021,0.00020268424],"about_ca_topic_score_codex":0.0001064158,"about_ca_topic_score_gemma":0.000029021727,"teacher_disagreement_score":0.6751605,"about_ca_system_score_codex":0.000017914517,"about_ca_system_score_gemma":0.000026980475,"threshold_uncertainty_score":0.7606058},"labels":[],"label_agreement":null},{"id":"W2316020023","doi":"10.2316/journal.211.2012.1.211-1047","title":"MARKET-BASED DISTRIBUTED OPTIMIZATION APPROACHES FOR THREE CLASSES OF RESOURCE ALLOCATION PROBLEMS","year":2012,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Advanced Research in Systems and Signal Processing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Resource allocation; Resource (disambiguation); Distributed computing; Operations research; Computer network","score_opus":0.032512434201298956,"score_gpt":0.24403398256872483,"score_spread":0.21152154836742587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2316020023","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055051716,0.005492193,0.9883298,0.000034438446,0.000048292393,0.000295407,0.000044579276,0.00010131647,0.00014874521],"genre_scores_gemma":[0.98972267,0.000052331965,0.009514332,0.0000046568325,0.00014570884,0.000026227675,0.00051220326,0.000017662145,0.000004183835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991111,0.000035411038,0.00026704362,0.00014822408,0.0000974906,0.00034072073],"domain_scores_gemma":[0.9994004,0.00025453835,0.000083110666,0.000088090215,0.00005514191,0.00011876283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041719747,0.00014410273,0.00021123342,0.000032750122,0.00017742987,0.000046692956,0.000060121267,0.00010306992,0.0000015017349],"category_scores_gemma":[0.00003908694,0.00012801147,0.000031410123,0.00015817827,0.000066011475,0.00009974822,0.000028105558,0.000115957824,5.1945758e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035963425,0.000023747374,0.0026879963,0.00036136812,0.000026002313,9.264451e-8,0.000031018488,0.9818501,0.000011699876,0.00019370069,0.00041644022,0.014361883],"study_design_scores_gemma":[0.00047760858,0.00003353345,0.0015714002,0.00015071008,0.000017470215,0.000002757158,0.00006755507,0.9964901,0.00001613492,0.0001012819,0.00092376536,0.00014765406],"about_ca_topic_score_codex":0.000003343507,"about_ca_topic_score_gemma":0.0000011424908,"teacher_disagreement_score":0.9842175,"about_ca_system_score_codex":0.000019434232,"about_ca_system_score_gemma":0.000008486148,"threshold_uncertainty_score":0.52201563},"labels":[],"label_agreement":null},{"id":"W2316535507","doi":"10.2316/p.2010.676-055","title":"Is Iterative Deepening Search a Complete and Optimal Algorithm for Java PathFinder?","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Pathfinder; Computer science; Java; Algorithm; Iterative method; Parallel computing; Operating system; World Wide Web","score_opus":0.024177024768679133,"score_gpt":0.2810436833405228,"score_spread":0.2568666585718437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2316535507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049939934,0.0005913546,0.9477091,0.00029626847,0.00011682178,0.00020433411,0.000033367585,0.0010881311,0.000020723142],"genre_scores_gemma":[0.5734983,0.000024177905,0.4261276,0.00018890719,0.00010516197,0.0000092321125,0.000032281914,0.000007986165,0.0000063109355],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855584,0.00005330287,0.00023389867,0.00057435513,0.00012495325,0.00045767947],"domain_scores_gemma":[0.9985671,0.0007914157,0.00008493703,0.00023438984,0.000120284625,0.0002018537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005132113,0.0002265773,0.00027626223,0.00005788328,0.0006581091,0.00049603643,0.00023798122,0.00013727983,0.0000010853194],"category_scores_gemma":[0.000056012395,0.00020689677,0.00004192225,0.00017235025,0.0001437136,0.0001330051,0.00042051208,0.00038729183,4.394646e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035035508,0.0000723333,0.009849011,0.000052953208,0.00007638052,0.000028586132,0.002291855,0.0024942812,0.000058236965,0.004834369,0.0058412547,0.9743657],"study_design_scores_gemma":[0.00058555586,0.00014965006,0.00407693,0.000059413458,0.0000107809,0.00014200919,0.000018754194,0.9891248,0.000014048843,0.005192135,0.00035809365,0.00026782556],"about_ca_topic_score_codex":0.00004624312,"about_ca_topic_score_gemma":0.000001881256,"teacher_disagreement_score":0.9866305,"about_ca_system_score_codex":0.0000069029966,"about_ca_system_score_gemma":0.000022034843,"threshold_uncertainty_score":0.8437006},"labels":[],"label_agreement":null},{"id":"W2318920610","doi":"10.2316/p.2010.676-028","title":"Development of a Network on Chip for Parallel Processing Systems","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; System on a chip; Computer architecture; Parallel computing; Parallel processing; Chip; Embedded system; Telecommunications","score_opus":0.01733670780103963,"score_gpt":0.2481187648224218,"score_spread":0.23078205702138216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2318920610","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05312501,0.0009813405,0.9442346,0.00007075567,0.0009440525,0.00032890146,0.0000033074675,0.00011009178,0.00020192002],"genre_scores_gemma":[0.9530163,0.000016506787,0.046241075,0.00006480868,0.00056378567,0.000032413303,0.000025605294,0.00001110177,0.0000284305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99835336,0.000051000938,0.00053775887,0.00044931256,0.00014539777,0.00046319724],"domain_scores_gemma":[0.9989777,0.00023859428,0.0002857719,0.00022661535,0.00012002228,0.00015126856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007647131,0.00022591834,0.00037959006,0.000044261385,0.00057735684,0.00026027876,0.00026715052,0.00016409674,5.824983e-7],"category_scores_gemma":[0.00001967842,0.00018884054,0.000054959844,0.00021175186,0.000055416578,0.000092152644,0.00013985485,0.00026537103,5.925172e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015578874,0.00012749089,0.0021717388,0.0002611346,0.000105177176,0.0000041394437,0.00093628216,0.7669791,0.0000490199,0.10309141,0.0031861193,0.122932576],"study_design_scores_gemma":[0.00063815905,0.000087476685,0.0018249907,0.0002343058,0.000008203177,0.000034230805,0.000063051346,0.9896735,0.0000033934032,0.00039890775,0.0067941006,0.00023969517],"about_ca_topic_score_codex":0.000008224669,"about_ca_topic_score_gemma":0.000012612952,"teacher_disagreement_score":0.89989126,"about_ca_system_score_codex":0.0000108831155,"about_ca_system_score_gemma":0.000044190918,"threshold_uncertainty_score":0.77006936},"labels":[],"label_agreement":null},{"id":"W2319792364","doi":"10.2316/p.2010.676-054","title":"Constructing Non-Dominated <em>m</em>-Group Coteries for Group Mutual Exclusion","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Group (periodic table); Mutual exclusion; Computer science; Physics; Mathematics; Theoretical computer science","score_opus":0.008023754977007557,"score_gpt":0.22823139202830117,"score_spread":0.22020763705129362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2319792364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28528756,0.000864076,0.71169424,0.00011442633,0.0011593935,0.00039374048,0.00012860126,0.00021666224,0.00014130099],"genre_scores_gemma":[0.97330564,0.000076269986,0.025246833,0.00011941253,0.00055998197,0.000032841184,0.00059501076,0.00002620244,0.000037783648],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969183,0.000101975056,0.0007388643,0.0009946513,0.0003060839,0.00094013236],"domain_scores_gemma":[0.9979992,0.00048357892,0.00040553385,0.00051068416,0.00022075335,0.00038024905],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009322646,0.0005050887,0.00070388307,0.00008534094,0.0011357832,0.0008671766,0.000604206,0.00037784118,0.0000050614804],"category_scores_gemma":[0.00006673186,0.0004641304,0.0001396451,0.00046897432,0.00024929934,0.00037455643,0.0006477597,0.0005278066,0.00000342381],"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":[0.0007548152,0.00055863976,0.01005123,0.00051953207,0.00036715658,0.00015419471,0.002930404,0.008670057,0.006295787,0.19220811,0.017130263,0.7603598],"study_design_scores_gemma":[0.0027283037,0.00023023144,0.005306326,0.00023019499,0.00003425806,0.0002472124,0.00033600695,0.9763285,0.000026306545,0.0008586351,0.012972178,0.0007018303],"about_ca_topic_score_codex":0.000027440317,"about_ca_topic_score_gemma":0.00012642777,"teacher_disagreement_score":0.96765846,"about_ca_system_score_codex":0.000032563104,"about_ca_system_score_gemma":0.0000347113,"threshold_uncertainty_score":0.999781},"labels":[],"label_agreement":null},{"id":"W2320450249","doi":"10.2316/p.2010.676-037","title":"Low-Complex Task Scheduling Algorithms for Hierarchical Embedded Many-Core Architectures and Dynamic Applications","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Parallel computing; Processor scheduling; Dynamic priority scheduling; Many core; Scheduling (production processes); Distributed computing; Multi-core processor; Fair-share scheduling; Task (project management); Algorithm; Computer network; Mathematical optimization; Resource (disambiguation)","score_opus":0.014159194591029291,"score_gpt":0.28127375390317066,"score_spread":0.2671145593121414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320450249","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043383494,0.00057213946,0.95449615,0.0004280384,0.00010025566,0.0004516088,0.000024465904,0.0004982049,0.00004562752],"genre_scores_gemma":[0.62399346,0.000073998046,0.37548527,0.00015285768,0.00012616043,0.000035324556,0.00011291773,0.000011323208,0.000008674465],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828273,0.00004744781,0.0003518092,0.0007074583,0.00012694503,0.00048359996],"domain_scores_gemma":[0.99872714,0.00042362345,0.00014886113,0.00034775076,0.00009145032,0.00026114477],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036828243,0.00028348202,0.0003257248,0.0000987507,0.0007894644,0.00034854873,0.00038509577,0.00018586546,9.866123e-7],"category_scores_gemma":[0.000042771862,0.0002630692,0.000060942344,0.0002555415,0.00021548361,0.000065031556,0.00039799162,0.0004945494,4.5698232e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073630574,0.00019942681,0.001290864,0.00016174781,0.00010100953,0.0000080571735,0.0006251482,0.39382142,0.00065730565,0.05681634,0.0006092904,0.54563576],"study_design_scores_gemma":[0.00060130033,0.00006921264,0.0032656894,0.000035926936,0.000014506901,0.000077534525,0.000014466212,0.9819328,0.0000115011035,0.012999825,0.00065443385,0.00032278552],"about_ca_topic_score_codex":0.000007634304,"about_ca_topic_score_gemma":0.000004305914,"teacher_disagreement_score":0.5881114,"about_ca_system_score_codex":0.000008769684,"about_ca_system_score_gemma":0.000026446382,"threshold_uncertainty_score":0.9999822},"labels":[],"label_agreement":null},{"id":"W2323848889","doi":"10.2316/p.2010.676-079","title":"Agglomeration of Dependent Tasks for Efficient Scheduling in Grid Environment","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Grid; Scheduling (production processes); Economies of agglomeration; Distributed computing; Grid computing; Parallel computing; Mathematical optimization; Chemical engineering; Geology","score_opus":0.00901608136508937,"score_gpt":0.22867053079723326,"score_spread":0.2196544494321439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2323848889","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3321705,0.00055373705,0.6664184,0.00009623597,0.00045888918,0.00021377864,0.000019676903,0.000042087362,0.000026721931],"genre_scores_gemma":[0.9795605,0.000042733485,0.02000222,0.000027994629,0.0002296081,0.000012164991,0.000112811,0.000007438779,0.0000045453007],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99840784,0.00006439477,0.00048551674,0.0004832648,0.00016585259,0.00039315794],"domain_scores_gemma":[0.99905837,0.00027871123,0.00021431333,0.00027244835,0.000045733963,0.00013042301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075817923,0.00020184294,0.00032184325,0.00007432992,0.0002017776,0.00013430085,0.00027556022,0.00014069233,0.0000011138837],"category_scores_gemma":[0.000036977362,0.00019110183,0.000055078333,0.00017595474,0.00006931569,0.00006266135,0.00022708965,0.00026901782,7.804356e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002462116,0.000096490876,0.005213727,0.00004316691,0.00001708645,0.0000032931698,0.00020159358,0.97439796,0.00020311913,0.008472252,0.00007262001,0.011254077],"study_design_scores_gemma":[0.0010118812,0.000077497985,0.010055559,0.000065199,0.000008610957,0.000024423243,0.000032267013,0.987641,0.000032881286,0.00033481582,0.00050390686,0.0002119667],"about_ca_topic_score_codex":0.000040075887,"about_ca_topic_score_gemma":0.000008346332,"teacher_disagreement_score":0.64739,"about_ca_system_score_codex":0.000016085105,"about_ca_system_score_gemma":0.000022912027,"threshold_uncertainty_score":0.7792906},"labels":[],"label_agreement":null},{"id":"W2326709443","doi":"10.2316/journal.211.2014.4.211-1012","title":"FAST PARALLEL ALGORITHM FOR DISCRETE FOURIER TRANSFORM IN MULTI-MESH NETWORK","year":2014,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Kalyani; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Computer science; Discrete Fourier transform (general); Algorithm; Fourier transform; Parallel computing; Fast Fourier transform; Computational science; Fourier analysis; Short-time Fourier transform; Mathematics","score_opus":0.008951030432034537,"score_gpt":0.23761053121289902,"score_spread":0.22865950078086447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2326709443","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017964109,0.0014172036,0.9959123,0.00009298892,0.00011762265,0.00033949097,0.00005554292,0.0001705787,0.000097854594],"genre_scores_gemma":[0.7170922,0.0006864176,0.28114894,0.00006662838,0.00046077426,0.00009363037,0.00037691323,0.00003796366,0.000036500518],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882734,0.00001677233,0.00029698902,0.00028819442,0.000059026504,0.00051169907],"domain_scores_gemma":[0.9994946,0.00016666598,0.000038927312,0.00013038948,0.000020817048,0.00014861011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018679645,0.00023039525,0.00030808474,0.00002504733,0.0002301145,0.00005852022,0.00008623453,0.00012303224,0.0000014598455],"category_scores_gemma":[0.0000056571776,0.00021828274,0.00005402753,0.0001626276,0.000057324643,0.000064712855,0.000031761014,0.00021619133,6.639969e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061158385,0.000012212492,0.00027431047,0.000015072471,0.000015529049,5.467871e-7,0.00003808034,0.68784845,6.038051e-7,0.000671042,0.00029993372,0.31081814],"study_design_scores_gemma":[0.0013924636,0.00003495114,0.0025196383,0.000052960724,0.00001670778,0.000006013754,0.000042180058,0.98691094,7.7125884e-7,0.0017666838,0.006968221,0.00028849574],"about_ca_topic_score_codex":0.000011250104,"about_ca_topic_score_gemma":0.000023436287,"teacher_disagreement_score":0.7152958,"about_ca_system_score_codex":0.000015301399,"about_ca_system_score_gemma":0.0000037452348,"threshold_uncertainty_score":0.8901312},"labels":[],"label_agreement":null},{"id":"W2326867708","doi":"10.2316/journal.211.2011.1.211-1009","title":"HIGH THROUGHPUT – SYSTEM-ORIENTED SCHEDULER FOR AVOIDING HASTE PROBLEM IN COMPUTATIONAL GRIDS","year":2011,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Throughput; Distributed computing; Parallel computing; Operating system; Wireless","score_opus":0.013190586720886195,"score_gpt":0.20810309092967647,"score_spread":0.19491250420879028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2326867708","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029775567,0.00050724804,0.96891147,0.000010903555,0.00019655838,0.00019983854,0.000026169093,0.00023724769,0.00013497712],"genre_scores_gemma":[0.8603111,0.000044223467,0.13925274,0.000008717836,0.00007953943,0.000013874172,0.00027091228,0.000015479878,0.0000034455604],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991873,0.000022621029,0.0002515491,0.00021510589,0.000052765106,0.00027064033],"domain_scores_gemma":[0.99965096,0.00012858771,0.000050577564,0.00006548951,0.000038126575,0.000066235196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016048613,0.00015964989,0.00020404378,0.000042511372,0.00018755074,0.00003224134,0.00004390647,0.00009079582,0.000001018518],"category_scores_gemma":[0.000012314935,0.00015747345,0.000021212605,0.00009946885,0.00003833154,0.00006272111,0.00003537117,0.00016805831,3.9349587e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029591369,0.000014027336,0.0006034055,0.00011117361,0.000020577556,0.0000021191092,0.0001516083,0.97851086,5.4705765e-7,0.019176051,0.000069355374,0.0013106836],"study_design_scores_gemma":[0.0008483663,0.00003453269,0.0025169211,0.00012656522,0.00001480593,0.000009506351,0.00014035821,0.99326956,0.0000069796392,0.0027884196,0.000058607995,0.00018535901],"about_ca_topic_score_codex":0.000021582526,"about_ca_topic_score_gemma":0.0000027856147,"teacher_disagreement_score":0.8305355,"about_ca_system_score_codex":0.0000318434,"about_ca_system_score_gemma":0.000004836504,"threshold_uncertainty_score":0.6421581},"labels":[],"label_agreement":null},{"id":"W2327189209","doi":"10.2316/p.2010.676-066","title":"Stream Experiments: Toward Latency Hiding in GPGPU","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; General-purpose computing on graphics processing units; Latency (audio); Parallel computing; Computer graphics (images); Graphics; Telecommunications","score_opus":0.013934640081271593,"score_gpt":0.25797018275291095,"score_spread":0.24403554267163935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2327189209","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22406065,0.0011796473,0.7738616,0.00018040938,0.00035169072,0.00008200549,0.0000059951853,0.00010865585,0.0001693367],"genre_scores_gemma":[0.9794577,0.00016745922,0.020097481,0.00007293373,0.00013521213,0.00000403809,0.00005166672,0.000005775161,0.000007768284],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988016,0.000039465165,0.0002419706,0.00043963533,0.00011225093,0.00036506492],"domain_scores_gemma":[0.99937946,0.000102615304,0.0000757423,0.00025880654,0.000026116772,0.0001572554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022097376,0.00017231074,0.00020411672,0.000049910108,0.00021210936,0.00023368298,0.0003047978,0.000113837836,0.0000043108525],"category_scores_gemma":[0.000016829452,0.00014779664,0.000025321924,0.00020815825,0.000049874237,0.0002482898,0.00055004796,0.00034474971,0.0000015681015],"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":[0.00008886149,0.0005529944,0.09674122,0.0000666852,0.00006679758,0.00020078913,0.002594433,0.03421814,0.0008534468,0.05859043,0.004226164,0.8018],"study_design_scores_gemma":[0.0006177013,0.000040097268,0.021763526,0.000054108088,0.0000029333448,0.000030817588,0.000058357993,0.9749356,0.000022993638,0.0012557019,0.0009985085,0.00021967589],"about_ca_topic_score_codex":0.00010273655,"about_ca_topic_score_gemma":0.0000069155067,"teacher_disagreement_score":0.94071746,"about_ca_system_score_codex":0.000008491398,"about_ca_system_score_gemma":0.0000140202965,"threshold_uncertainty_score":0.6026972},"labels":[],"label_agreement":null},{"id":"W2328826103","doi":"10.2316/journal.211.2012.1.211-1056","title":"APPROXIMATION ALGORITHMS FOR SP-MULTICAST TREES IN 2D GRIDS1","year":2012,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Multicast; Computer science; Protocol Independent Multicast; Algorithm; Computer network","score_opus":0.019647432898477316,"score_gpt":0.25912727150880427,"score_spread":0.23947983861032696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328826103","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.067585275,0.0015833493,0.93010587,0.00014165133,0.0002499785,0.00019083191,0.000010412661,0.000086834494,0.000045799505],"genre_scores_gemma":[0.9578514,0.000058129317,0.04169135,0.00007020936,0.00023461726,0.000014849493,0.00006505593,0.0000061584174,0.000008217389],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988267,0.00007267828,0.00023997322,0.00029357825,0.000081263715,0.00048580964],"domain_scores_gemma":[0.99929625,0.0002810075,0.00007895034,0.00015576713,0.00003048076,0.00015755091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059278664,0.00016588096,0.00021225869,0.000059315455,0.00023603515,0.0001315557,0.00017517182,0.000091827096,7.176467e-7],"category_scores_gemma":[0.000025271494,0.0001466643,0.000043121796,0.00024881813,0.00006170095,0.00026540956,0.00014206296,0.00014142113,9.2410625e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010152143,0.00048964954,0.034010224,0.00007748226,0.00006926255,0.000007607108,0.0024525742,0.09385393,0.000043654312,0.18235764,0.0005787169,0.68595773],"study_design_scores_gemma":[0.00082164677,0.000049611906,0.035041317,0.000036213893,0.000008059695,0.000021780377,0.00008529424,0.9582262,0.000008486313,0.0052563534,0.00024691864,0.00019809433],"about_ca_topic_score_codex":0.0000087415,"about_ca_topic_score_gemma":0.0000016406264,"teacher_disagreement_score":0.8902661,"about_ca_system_score_codex":0.000010598095,"about_ca_system_score_gemma":0.0000062273566,"threshold_uncertainty_score":0.5980796},"labels":[],"label_agreement":null},{"id":"W2331476467","doi":"10.2316/journal.211.2013.3.211-1053","title":"A GPGPU PROGRAMMING FRAMEWORK BASED ON A SHARED-MEMORY MODEL","year":2013,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Computer science; General-purpose computing on graphics processing units; Parallel computing; Programming paradigm; Shared memory; CUDA; Computer architecture; Programming language; Computer graphics (images); Graphics","score_opus":0.01196231576734502,"score_gpt":0.2428184954972875,"score_spread":0.2308561797299425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2331476467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036745952,0.000544205,0.9932184,0.00078481605,0.000086142376,0.0003369165,0.0000037894483,0.00093193696,0.00041915738],"genre_scores_gemma":[0.6522454,0.000035021723,0.34682804,0.00073434395,0.0000675115,0.000026556998,0.00003078435,0.000011521462,0.00002082902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981285,0.000092610724,0.00033814088,0.0006652254,0.00021086489,0.0005646961],"domain_scores_gemma":[0.9986972,0.0003325282,0.00015236612,0.00043998772,0.00010797633,0.00026994635],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030619794,0.00030827872,0.00030928696,0.00009956618,0.000502856,0.00070087094,0.00043555355,0.00020441577,0.000004615524],"category_scores_gemma":[0.00006256646,0.00027834513,0.000068601024,0.00039004805,0.00008602597,0.00019961478,0.0003209843,0.0004179248,0.0000058735113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009529984,0.000072800154,0.0004987508,0.00001569666,0.000010820824,0.000004115781,0.00012555957,0.92054576,7.8745126e-7,0.0046684085,0.002201975,0.071845815],"study_design_scores_gemma":[0.00037748154,0.000114835595,0.0010930855,0.00017892975,0.0000070515657,0.000010512123,0.000014146722,0.9931528,0.0000025685147,0.0045472165,0.00015589134,0.00034548846],"about_ca_topic_score_codex":0.000029110744,"about_ca_topic_score_gemma":4.405824e-7,"teacher_disagreement_score":0.6485708,"about_ca_system_score_codex":0.000022992808,"about_ca_system_score_gemma":0.000033854863,"threshold_uncertainty_score":0.99996686},"labels":[],"label_agreement":null},{"id":"W2332854854","doi":"10.2316/p.2010.676-024","title":"A Proactive Fault Tolerance Framework for High-Performance Computing","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Oak Ridge National Laboratory; UT-Battelle; Battelle; Advanced Scientific Computing Research; U.S. Department of Energy","keywords":"Computer science; Fault tolerance; Distributed computing; Software fault tolerance","score_opus":0.010664129001635528,"score_gpt":0.24455976510648292,"score_spread":0.2338956361048474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2332854854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33221304,0.0003723451,0.66546345,0.0002482191,0.00091379887,0.00036740545,0.000024209692,0.00032144468,0.000076099925],"genre_scores_gemma":[0.88926005,0.000042905096,0.10959452,0.00020482462,0.0007319748,0.000019162542,0.000108389664,0.00002126137,0.000016922715],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972702,0.00008876851,0.00056273356,0.0009544438,0.00023530358,0.00088851963],"domain_scores_gemma":[0.99778545,0.00085988804,0.00033039812,0.00052199425,0.00019901943,0.00030327335],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007215222,0.0004432928,0.0005620768,0.00007196546,0.001001198,0.00059506827,0.00068413815,0.0003303125,0.0000014199169],"category_scores_gemma":[0.000106239095,0.00041087368,0.00008128429,0.00046423037,0.00016138772,0.00025773613,0.00044280788,0.0008100568,0.0000032055536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017985076,0.0002488748,0.012451716,0.00026562024,0.00021896505,0.000017675595,0.0012980639,0.47199607,0.00008599427,0.28811347,0.0016500333,0.22347367],"study_design_scores_gemma":[0.0010005955,0.00016931555,0.016794335,0.00017920198,0.000021024098,0.00009329116,0.00003724106,0.9741933,0.000029177309,0.005365695,0.0015692235,0.0005476465],"about_ca_topic_score_codex":0.000035321264,"about_ca_topic_score_gemma":0.000003326102,"teacher_disagreement_score":0.557047,"about_ca_system_score_codex":0.000019275296,"about_ca_system_score_gemma":0.00004888036,"threshold_uncertainty_score":0.9998343},"labels":[],"label_agreement":null},{"id":"W2334476329","doi":"10.2316/p.2010.676-062","title":"Effect of Atmospheric Turbulent Channel on Bit-Error-Rate of Optical Wireless Link","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Bit error rate; Channel (broadcasting); Bit (key); Link (geometry); Wireless; Optical wireless; Optical link; Computer network; Telecommunications; Optical fiber","score_opus":0.00624956024363951,"score_gpt":0.2249653852044506,"score_spread":0.2187158249608111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2334476329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9289415,0.000950754,0.06940119,0.00015088925,0.00009324496,0.00010915234,0.000005283518,0.00021718755,0.00013084049],"genre_scores_gemma":[0.99795717,0.00047632933,0.0014723293,0.000008529364,0.00003858572,0.0000056559425,0.000025999554,0.000013935171,0.0000014387903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925834,0.00004008077,0.00026632496,0.00015210774,0.000063430045,0.00021974597],"domain_scores_gemma":[0.99897534,0.0005771505,0.0000642485,0.00027592585,0.00003335774,0.00007398127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025412033,0.00016982197,0.00033926996,0.000014163624,0.00006179643,0.00001755765,0.00016814188,0.00020295993,0.000001782224],"category_scores_gemma":[0.000050834966,0.00014052213,0.00004231756,0.0001711641,0.00019839317,0.000021314296,0.00011819431,0.00045079016,7.9485216e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016116045,0.00008209082,0.0019054998,0.0003167573,0.000116146286,0.000004985573,0.00007992913,0.80772954,0.0011761388,0.009954478,0.00017393695,0.17829932],"study_design_scores_gemma":[0.00046779535,0.00025657145,0.0038431028,0.00009778072,0.00001713035,0.000005160111,0.000015319783,0.9932049,0.001701327,0.00020540407,0.000043762015,0.00014177451],"about_ca_topic_score_codex":0.000006785139,"about_ca_topic_score_gemma":0.0000012997141,"teacher_disagreement_score":0.18547532,"about_ca_system_score_codex":0.0000058438022,"about_ca_system_score_gemma":0.0000030920644,"threshold_uncertainty_score":0.5730326},"labels":[],"label_agreement":null},{"id":"W2334768140","doi":"10.2316/p.2010.676-042","title":"On the Parallelization of Meshless Methods for the Solution of the Diffusion Equation","year":2010,"lang":"en","type":"article","venue":"Parallel and Distributed Computing and Networks","topic":"Numerical methods in engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Diffusion; Computational science; Diffusion equation; Parallel computing; Mathematical optimization; Mathematics; Thermodynamics; Physics","score_opus":0.01859003992244724,"score_gpt":0.28478120479035607,"score_spread":0.26619116486790884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2334768140","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061819877,0.00057518587,0.9367473,0.00015762064,0.00041887895,0.00021696027,0.000004860885,0.00003325498,0.000026025069],"genre_scores_gemma":[0.96605617,0.00011329182,0.033710733,0.00001655257,0.000072327464,0.000011566803,0.00000811168,0.000009438594,0.0000018205525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942076,0.000085625186,0.0002027317,0.00009261513,0.000066525725,0.00013174256],"domain_scores_gemma":[0.997578,0.0021145497,0.000078868106,0.00016943416,0.00003715881,0.000021965927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006956635,0.00009683749,0.00013408132,0.000012565126,0.00017150112,0.00001547284,0.000121480014,0.00007453756,0.0000013520444],"category_scores_gemma":[0.000260624,0.000049931103,0.000044010107,0.00014981926,0.00007934799,0.00001700169,0.00005444127,0.00020350283,3.208845e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012492457,0.000008028328,0.00016302924,0.000027930198,0.00002078255,1.1127779e-8,0.00007746177,0.90443194,0.0021688167,0.010060346,0.000079678044,0.08294946],"study_design_scores_gemma":[0.00016702415,0.000017659937,0.0046017035,0.00003755242,0.000026397445,0.0000010789436,0.00002559643,0.99121696,0.00042736545,0.0032195507,0.00019840448,0.00006068214],"about_ca_topic_score_codex":0.0000074608383,"about_ca_topic_score_gemma":0.000001335699,"teacher_disagreement_score":0.90423626,"about_ca_system_score_codex":0.0000055462815,"about_ca_system_score_gemma":0.0000032665087,"threshold_uncertainty_score":0.20361313},"labels":[],"label_agreement":null}]}