{"meta":{"query_hash":"1b68a705d3ad","filters":{"topic":"Advanced Data Storage Technologies"},"cohort_total":585,"direct_labels_cover":0,"predictions_cover":585,"exported":585,"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/1b68a705d3ad","api":"https://metacan.xera.ac/api/v1/cohort?topic=Advanced+Data+Storage+Technologies"},"results":[{"id":"W112982782","doi":"","title":"Storage management for large scale systems","year":2004,"lang":"en","type":"article","venue":"University Library - University of Saskatchewan (University of Saskatchewan)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Cache; Disk buffer; Write buffer; Page cache; Cache algorithms; Cache-oblivious algorithm; Page fault; Cache coloring; Cache pollution; Lock (firearm); Overhead (engineering); Cache invalidation; Parallel computing; Operating system; CPU cache; Distributed computing; Memory management; Virtual memory","score_opus":0.007247014859292036,"score_gpt":0.16987614877395874,"score_spread":0.1626291339146667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W112982782","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":[0.15900256,0.00015046321,0.8349597,0.0011419,0.00027386835,0.0009734122,0.0011136798,0.0010844774,0.0012999285],"genre_scores_gemma":[0.6976308,0.00016365758,0.29171032,0.000032375843,0.00001803292,5.9890596e-8,0.00012444625,0.000026536516,0.010293757],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9971932,0.000106580854,0.00025767196,0.0011035376,0.0005565434,0.0007824641],"domain_scores_gemma":[0.99712247,0.00012844203,0.0006164734,0.0016097538,0.00020159218,0.00032124796],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002410293,0.00045919532,0.00081495073,0.0009525624,0.0008092367,0.00004549632,0.004629792,0.00039622036,0.000087586894],"category_scores_gemma":[0.0000063040015,0.0006920543,0.00046717763,0.0015101121,0.00072700187,0.0053215325,0.0028905252,0.0003609206,0.000045199424],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004126816,0.0051788716,0.003853467,0.0047150934,0.003372489,0.00686455,0.7995437,0.024372302,0.004681111,0.10982799,0.012083568,0.021380095],"study_design_scores_gemma":[0.0061093126,0.00039811956,0.00064252224,0.00026750902,0.00021409358,0.000016115957,0.9495696,0.0013028124,0.0008758683,0.00305969,0.036702495,0.00084188714],"about_ca_topic_score_codex":0.0033390971,"about_ca_topic_score_gemma":0.0017445346,"teacher_disagreement_score":0.54324937,"about_ca_system_score_codex":0.00040034077,"about_ca_system_score_gemma":0.00057884835,"threshold_uncertainty_score":0.9995531},"labels":[],"label_agreement":null},{"id":"W1262434878","doi":"","title":"HyLog: a high performance approach to managing disk layout","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Server; Overhead (engineering); Hard disk drive performance characteristics; Operating system; Workload; File system; File system fragmentation; Random access; Disk array; Parallel computing; Device file; Computer file","score_opus":0.014724876174036425,"score_gpt":0.22359799008767275,"score_spread":0.20887311391363633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1262434878","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":[0.050474074,0.000025449133,0.9339302,0.0014163011,0.00010947472,0.00015851451,0.0000018261078,0.0014581766,0.012425948],"genre_scores_gemma":[0.53575736,0.0000060541447,0.46366408,0.0003471773,0.000011030908,0.000021179903,0.0000016936161,0.000005201004,0.00018620394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988283,0.0000059683384,0.00013627762,0.00047536343,0.00020226579,0.00035184302],"domain_scores_gemma":[0.99879223,0.000012509386,0.000033631863,0.0010722297,0.000024516341,0.000064876156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009419323,0.00013903673,0.00012785013,0.00014843367,0.00011505536,0.00009259398,0.0016806844,0.00004379787,0.0000024381977],"category_scores_gemma":[0.000028970335,0.0001159997,0.000020340669,0.0006084762,0.000048268663,0.0009032238,0.0010964419,0.00013289167,0.00023531704],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028865852,0.00006633566,0.0001613441,0.000016089709,0.0000067330375,0.000011553745,0.00031362934,0.03350301,0.00023908507,0.86056155,0.00029677138,0.10482104],"study_design_scores_gemma":[0.0044427,0.0013790714,0.029817805,0.0002332506,0.00003259937,0.00040293197,0.0018127288,0.2828262,0.09304002,0.54850376,0.032791466,0.004717482],"about_ca_topic_score_codex":0.00004114081,"about_ca_topic_score_gemma":0.0000034551308,"teacher_disagreement_score":0.48528332,"about_ca_system_score_codex":0.00009754217,"about_ca_system_score_gemma":0.000020929085,"threshold_uncertainty_score":0.47303304},"labels":[],"label_agreement":null},{"id":"W138814728","doi":"","title":"Exposing file system mappings with MapFS","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; File system; Unix file types; Versioning file system; Operating system; SSH File Transfer Protocol; Self-certifying File System; Metadata; Unix; Journaling file system; Flexibility (engineering); Computer file; Byte; Stub file; Database; Device file; Overhead (engineering); File system fragmentation","score_opus":0.025328980955768035,"score_gpt":0.1916305174794618,"score_spread":0.16630153652369378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W138814728","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00058960175,0.000025715557,0.95469195,0.00005233129,0.000064140586,0.00008689004,0.00000836103,0.0024711993,0.0420098],"genre_scores_gemma":[0.1718127,6.383653e-7,0.82759845,0.00006635801,0.0000068526892,0.000022305612,0.0000026527791,0.000006447072,0.00048356762],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992464,0.000006469114,0.00010489989,0.00029794435,0.00012890335,0.00021539418],"domain_scores_gemma":[0.9990424,0.000025214076,0.000059231483,0.0008030211,0.000035633202,0.000034536184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051967232,0.00010044979,0.000099937984,0.000079474274,0.00007271358,0.000048260637,0.0009698818,0.00003858806,0.0001713735],"category_scores_gemma":[0.000014333258,0.00007215369,0.000014362305,0.00028111387,0.0000578865,0.000802566,0.00040895352,0.00007357884,0.00022375883],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050715944,0.000024149156,0.0001366833,0.000033777455,0.000012773813,0.00016601756,0.00064623106,0.0000043387204,0.00042046464,0.95629823,0.012354796,0.029897464],"study_design_scores_gemma":[0.0039080908,0.003475724,0.011964544,0.0023294338,0.000067678055,0.004289085,0.023911227,0.0965554,0.5752175,0.070192106,0.20124388,0.006845335],"about_ca_topic_score_codex":0.00003850902,"about_ca_topic_score_gemma":0.0000045771876,"teacher_disagreement_score":0.88610613,"about_ca_system_score_codex":0.000045403307,"about_ca_system_score_gemma":0.000016279433,"threshold_uncertainty_score":0.29423422},"labels":[],"label_agreement":null},{"id":"W13923090","doi":"","title":"Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries","year":2007,"lang":"en","type":"article","venue":"ACM/IEEE Joint Conference on Digital Libraries","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of British Columbia","funders":"","keywords":"Presentation (obstetrics); Session (web analytics); Context (archaeology); Library science; Digital library; Computer science; Schedule; Theme (computing); Panel discussion; World Wide Web; History","score_opus":0.06813986457135855,"score_gpt":0.2503614662865123,"score_spread":0.18222160171515372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W13923090","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":[0.6419086,0.00030814,0.12230305,0.022127,0.0036780133,0.0032037345,0.0016829275,0.006946442,0.19784212],"genre_scores_gemma":[0.98344743,0.000046378707,0.014167326,0.00067335693,0.0001408267,0.00004766709,0.000035964968,0.00007571642,0.0013653485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99432504,0.000024482217,0.0013259796,0.0015504409,0.0014534183,0.0013206184],"domain_scores_gemma":[0.9941116,0.0006660595,0.0010339785,0.0033473333,0.00050622836,0.0003348018],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00030090762,0.0010021672,0.0010312658,0.0005452449,0.0004430357,0.005404989,0.007890575,0.00043979246,0.000040473617],"category_scores_gemma":[0.003423403,0.0007424522,0.00034148226,0.0014443366,0.0024311312,0.016892964,0.0044966424,0.0011018276,0.00019211113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014805987,0.00034035576,0.0012945312,0.00009715395,0.00007394102,0.000040234918,0.0009520868,0.000013756308,0.0044516893,0.9419694,0.008135037,0.042483743],"study_design_scores_gemma":[0.00074125297,0.0012672361,0.0042709056,0.00074974186,0.000019017949,0.000066348475,0.0017483578,0.0005187839,0.39156,0.5916945,0.0060531097,0.0013107582],"about_ca_topic_score_codex":0.00000757015,"about_ca_topic_score_gemma":0.000004302208,"teacher_disagreement_score":0.3871083,"about_ca_system_score_codex":0.000119404845,"about_ca_system_score_gemma":0.0006256394,"threshold_uncertainty_score":0.99950266},"labels":[],"label_agreement":null},{"id":"W1454188553","doi":"","title":"Identifying trends in enterprise data protection systems","year":2015,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Backup; Computer science; Work (physics); Computer security; Data management; Risk analysis (engineering); Data access; Enterprise data management; Data Protection Act 1998; Database; Enterprise information system; Business","score_opus":0.18454189179937514,"score_gpt":0.35311086364576316,"score_spread":0.16856897184638803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1454188553","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":[0.0029762872,0.00018390566,0.9926039,0.00065654144,0.0003997499,0.000297036,0.00009787153,0.001779442,0.0010052489],"genre_scores_gemma":[0.948469,0.000016202752,0.051135655,0.00002316385,0.000034706096,0.00007480782,0.000043796863,0.000012550591,0.00019015135],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975434,0.00010583722,0.0004593412,0.00095888524,0.00050025905,0.0004322656],"domain_scores_gemma":[0.9966933,0.00005059772,0.00016559014,0.002771741,0.0001791472,0.00013959841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007334327,0.00022336973,0.0003014983,0.00047536608,0.000058371203,0.0002966479,0.0044024056,0.00021067944,0.0000044133435],"category_scores_gemma":[0.0007045941,0.00020938413,0.000028486285,0.0012430588,0.0001526829,0.003078608,0.0038085256,0.0005594004,0.000064405656],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097135715,0.0005415184,0.0010397938,0.00008288881,0.000028055483,0.0006331588,0.0016629121,0.00041136608,0.006408627,0.28629282,0.016324308,0.6864774],"study_design_scores_gemma":[0.006260281,0.0022063674,0.01096519,0.001451922,0.00006222033,0.0014898783,0.0063620578,0.6134109,0.005970955,0.116449356,0.23026305,0.005107847],"about_ca_topic_score_codex":0.00026917836,"about_ca_topic_score_gemma":0.00018181368,"teacher_disagreement_score":0.9454927,"about_ca_system_score_codex":0.00017577667,"about_ca_system_score_gemma":0.000104248065,"threshold_uncertainty_score":0.8538437},"labels":[],"label_agreement":null},{"id":"W1480033117","doi":"10.1023/a:1015185802583","title":"Integrating Web Prefetching and Caching Using Prediction Models","year":2001,"lang":"en","type":"article","venue":"World Wide Web","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.030650988922576547,"score_gpt":0.259374212231979,"score_spread":0.22872322330940242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1480033117","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":[0.17673637,0.00030948268,0.81926894,0.00038135576,0.00020646764,0.00012265494,0.0000073110477,0.00095796224,0.0020094446],"genre_scores_gemma":[0.74557006,0.000042457043,0.25409228,0.00012422971,0.000040185307,0.0000063522625,0.0000029673627,0.000012059373,0.00010939989],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987255,0.00004405662,0.00025400615,0.00046256228,0.00019754989,0.00031636833],"domain_scores_gemma":[0.99906397,0.00014506537,0.00012359583,0.00057666027,0.000033116856,0.0000576019],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028211946,0.00017202119,0.00016608936,0.0003178787,0.00029428746,0.00019292314,0.0005594926,0.000051144933,0.0000033241322],"category_scores_gemma":[0.00016092087,0.0001628211,0.000028516453,0.0006132541,0.00006201194,0.0025036577,0.00064014917,0.0003597054,0.0000032770172],"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":[0.000029293295,0.0001013087,0.03080932,0.000073759205,0.000071465016,0.00023907251,0.0023743284,0.22783373,0.06578244,0.2711029,0.0015883603,0.39999402],"study_design_scores_gemma":[0.0001666868,0.000016324111,0.00012135951,0.00010906231,0.0000058645164,0.00006348025,0.00009118988,0.97071224,0.0003267243,0.024894357,0.0033278053,0.00016491725],"about_ca_topic_score_codex":0.000071657654,"about_ca_topic_score_gemma":0.00039755052,"teacher_disagreement_score":0.7428785,"about_ca_system_score_codex":0.00012597578,"about_ca_system_score_gemma":0.000049801256,"threshold_uncertainty_score":0.66396517},"labels":[],"label_agreement":null},{"id":"W1486447605","doi":"10.5772/9904","title":"Supervisory Control for Under-Load Tap-Changing Transformers Using Discrete-Event Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Sciyo eBooks","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Supervisory control; Tap changer; Transformer; Computer science; Control (management); Control theory (sociology); Control engineering; Engineering; Electrical engineering; Voltage; Artificial intelligence","score_opus":0.0432916147104947,"score_gpt":0.2629031472671652,"score_spread":0.21961153255667049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1486447605","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000058972313,0.0009717808,0.95512354,0.00012517216,0.002006516,0.0021820406,0.00036403918,0.0009172605,0.038250655],"genre_scores_gemma":[0.28099743,0.00013510452,0.25424108,0.001275375,0.0018777937,0.0017261328,0.00019407713,0.0009248616,0.45862818],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966178,0.000020691614,0.0006357713,0.0011072572,0.00068999594,0.00092849706],"domain_scores_gemma":[0.9975549,0.00020576711,0.0003811667,0.0014776811,0.00022015013,0.00016034245],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005874139,0.0007014423,0.00080393103,0.0012895644,0.00050570455,0.00027935219,0.0019333251,0.00077639683,0.00000787135],"category_scores_gemma":[0.000036818026,0.000664628,0.00037931371,0.00011791188,0.00041738115,0.00043016547,0.00039629106,0.00084627146,0.00002416721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024855217,0.000009021952,5.047525e-7,0.00025277334,0.00015602542,0.000050154165,0.0003136024,0.00040330976,0.006200735,0.92387265,0.00005742762,0.06865893],"study_design_scores_gemma":[0.004449205,0.0006612232,0.000002249817,0.0021160399,0.00058738654,0.00039834416,0.0009300093,0.07324355,0.0058172657,0.39764073,0.50933826,0.0048157447],"about_ca_topic_score_codex":0.000025541429,"about_ca_topic_score_gemma":0.000093433584,"teacher_disagreement_score":0.7008825,"about_ca_system_score_codex":0.00046061492,"about_ca_system_score_gemma":0.00039965758,"threshold_uncertainty_score":0.9995805},"labels":[],"label_agreement":null},{"id":"W1493496517","doi":"10.1109/cwit.2015.7255143","title":"Locality-aware fountain codes for massive distributed storage systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Fountain code; Locality; Computer science; Distributed data store; Node (physics); Overhead (engineering); Code (set theory); Distributed computing; Parallel computing; Algorithm; Linear code; Operating system; Block code; Decoding methods; Engineering; Programming language","score_opus":0.04258705941261067,"score_gpt":0.2904780619818426,"score_spread":0.24789100256923194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493496517","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":[0.00045224698,0.00016595931,0.9951002,0.0011135577,0.00041577086,0.0005207897,0.0003940947,0.001615667,0.00022172065],"genre_scores_gemma":[0.8322301,0.000003447177,0.16666171,0.00013784308,0.00006319575,0.00022248103,0.00019851157,0.000016904742,0.0004658377],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985755,0.00004670335,0.0002452524,0.0004720463,0.0002792987,0.00038116222],"domain_scores_gemma":[0.9981861,0.00019136623,0.00012357601,0.0010681169,0.00029997766,0.00013085567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036135834,0.00017979187,0.00025407173,0.00008093393,0.00010093946,0.00019899134,0.0013987207,0.00011316845,0.0000016909225],"category_scores_gemma":[0.00033528186,0.00014939485,0.000044041637,0.00037154442,0.00010975969,0.00085099443,0.00060388056,0.00011178164,0.00004322902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023235598,0.000074572,0.00021115344,0.00007042007,0.00003685257,0.00007017988,0.00013591247,0.007568073,0.000088321154,0.8933351,0.0923235,0.006062699],"study_design_scores_gemma":[0.00093039055,0.00027322958,0.00002886,0.000030715437,0.000009422703,0.000025790385,0.0022234085,0.85458827,0.0017266854,0.04908553,0.090593226,0.00048448017],"about_ca_topic_score_codex":0.00007201795,"about_ca_topic_score_gemma":0.000017871318,"teacher_disagreement_score":0.8470202,"about_ca_system_score_codex":0.00029411344,"about_ca_system_score_gemma":0.00010603652,"threshold_uncertainty_score":0.60921454},"labels":[],"label_agreement":null},{"id":"W1516383521","doi":"10.1109/isce.2004.1375972","title":"Performance evaluation of a DVD processor using transaction level models","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Database transaction; Transaction processing; Computer architecture; Embedded system; Database","score_opus":0.17603862626249883,"score_gpt":0.33324362831992976,"score_spread":0.15720500205743093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1516383521","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":[0.23788579,0.00004683512,0.7610331,0.000109505796,0.00002616656,0.00012477563,0.0000017168039,0.00017873266,0.00059335027],"genre_scores_gemma":[0.6206651,0.000008105374,0.37927568,0.000013441351,0.0000061037026,0.000007932038,5.9638774e-7,0.0000024560425,0.000020644047],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990963,0.000014456975,0.00016381902,0.00019874726,0.00040353756,0.00012315094],"domain_scores_gemma":[0.99931455,0.000011162998,0.00008322221,0.00036011817,0.00021707035,0.000013861903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035387403,0.00007126947,0.000083200124,0.00010382323,0.00004960972,0.000015090012,0.00041306217,0.000043917997,0.000009751487],"category_scores_gemma":[0.00002218909,0.00006344341,0.000017251583,0.000308317,0.00003191147,0.002920017,0.000047127145,0.000058818623,0.000004731837],"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":[0.0000023921887,0.000023731889,0.000009003478,0.0000094386,0.000002891437,5.5229705e-8,0.00017377082,0.41072613,0.005425957,0.0027209823,0.0000072017992,0.58089846],"study_design_scores_gemma":[0.00018595842,0.000021187436,0.000085099666,0.000011784608,0.0000070774286,0.0000051199722,0.000026244055,0.9088911,0.08786417,0.0028047457,0.000026110707,0.00007142249],"about_ca_topic_score_codex":0.000007893307,"about_ca_topic_score_gemma":0.000010388263,"teacher_disagreement_score":0.58082706,"about_ca_system_score_codex":0.000106821346,"about_ca_system_score_gemma":0.000084453815,"threshold_uncertainty_score":0.25871474},"labels":[],"label_agreement":null},{"id":"W1524975032","doi":"10.5555/2170444.2170454","title":"Privacy-sensitive VM retrospection","year":2011,"lang":"en","type":"article","venue":"Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cloud computing; Troubleshooting; Debugging; Malware; Computer security; Software; Trusted Computing; Operating system","score_opus":0.10940546482467789,"score_gpt":0.281311435169005,"score_spread":0.17190597034432709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1524975032","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":[0.17769425,0.00035658653,0.52076167,0.0015586041,0.0016033011,0.0024167597,0.00024077701,0.0056121927,0.28975588],"genre_scores_gemma":[0.94165826,0.0019746062,0.034557935,0.00005499466,0.00014800549,0.0000014165751,0.000057801382,0.00007872198,0.02146825],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9922433,0.0012429081,0.00036948425,0.0023741042,0.0017458026,0.0020243987],"domain_scores_gemma":[0.9933208,0.00059578614,0.00034117437,0.0034611763,0.0014836865,0.0007973511],"candidate_categories":["metaepi_narrow","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0013954237,0.00071334036,0.0007714549,0.0038177765,0.0017776159,0.00023272807,0.0057795425,0.0006517839,0.00012374343],"category_scores_gemma":[0.0005816414,0.0008764746,0.00042878545,0.0071552037,0.0017632861,0.0047069704,0.0060262913,0.0022175757,0.0004912506],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013729327,0.001263413,0.0018252876,0.00018280005,0.00063301786,0.054097246,0.008646201,0.00023213761,0.01603747,0.87001795,0.018781878,0.026909685],"study_design_scores_gemma":[0.007827039,0.0034361274,0.0035117543,0.00042172067,0.00035771314,0.0006924603,0.05604745,0.009794599,0.15420139,0.016053641,0.74294955,0.0047065937],"about_ca_topic_score_codex":0.002267481,"about_ca_topic_score_gemma":0.0004919209,"teacher_disagreement_score":0.85396427,"about_ca_system_score_codex":0.0031250827,"about_ca_system_score_gemma":0.0007342632,"threshold_uncertainty_score":0.9995997},"labels":[],"label_agreement":null},{"id":"W1531774622","doi":"10.1109/mascot.2004.1348303","title":"Database server workload characterization in an e-commerce environment","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Database; Cache; Log shipping; Database server; Database tuning; Server; Server farm; Operating system; Scalability; Page cache; Workload; Web server; Cache algorithms; CPU cache; View; Database design; Client–server model; The Internet","score_opus":0.02150047015650517,"score_gpt":0.24617258175926826,"score_spread":0.2246721116027631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1531774622","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":[0.1994369,0.000016425798,0.799046,0.00096350216,0.000043191532,0.000098495235,0.000009327656,0.0003208132,0.000065384236],"genre_scores_gemma":[0.6901238,0.00006853333,0.30892658,0.00064081815,0.000012734363,0.000022573482,0.00012843814,0.000008076196,0.00006843491],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99915683,0.000016866687,0.00014169213,0.000355711,0.00013930807,0.00018959466],"domain_scores_gemma":[0.9988361,0.000009090501,0.000041304025,0.0010689754,0.000005653831,0.00003888958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009210152,0.00009821679,0.00008270697,0.00009496152,0.000036106154,0.000052270294,0.0008503929,0.000043949178,0.00002717217],"category_scores_gemma":[0.000012732663,0.00009253437,0.0000102146605,0.00024043226,0.00003450983,0.0024880245,0.0005438266,0.000107621156,0.00014768059],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016613969,0.000896454,0.010027364,0.000018960991,0.00000775793,0.00023826484,0.000817623,0.0052192765,0.18165983,0.29285437,0.000038426326,0.50820506],"study_design_scores_gemma":[0.00612706,0.00081223063,0.6239465,0.00034886244,0.000012960171,0.00007766967,0.0005826184,0.03785308,0.23488113,0.06913241,0.02305854,0.0031669233],"about_ca_topic_score_codex":0.00001964985,"about_ca_topic_score_gemma":0.000043372995,"teacher_disagreement_score":0.61391914,"about_ca_system_score_codex":0.00011043713,"about_ca_system_score_gemma":0.000013223547,"threshold_uncertainty_score":0.37734422},"labels":[],"label_agreement":null},{"id":"W1535339723","doi":"10.1109/socc.2004.1362386","title":"A novel phase detector for PAM-4 clock recovery in high speed serial links","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Overhead (engineering); Detector; Computer hardware; Phase detector; Encoding (memory); Clock recovery; Digital clock manager; Data recovery; Clock rate; Clock signal; Embedded system; Synchronous circuit; Electrical engineering; Engineering; Jitter; Telecommunications; Operating system; Voltage","score_opus":0.02631606454610349,"score_gpt":0.2809335012294548,"score_spread":0.25461743668335135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1535339723","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12941876,0.000023920353,0.8678947,0.00089931855,0.00055719906,0.00039574396,0.000051942297,0.00069932954,0.000059076432],"genre_scores_gemma":[0.2615395,0.000007723359,0.7379325,0.00029198316,0.00008569162,0.000035206423,0.000011018558,0.0000121961375,0.00008417568],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99871147,0.000006564455,0.0002683752,0.0004998835,0.00014021588,0.0003734831],"domain_scores_gemma":[0.9989542,0.000101817044,0.000082379534,0.0007671977,0.00004600678,0.000048394788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014060856,0.00016433763,0.00020905652,0.00017915438,0.000054057935,0.00008330436,0.0010471918,0.00021909004,0.000008011969],"category_scores_gemma":[0.00031837684,0.00015017072,0.00005373363,0.00044259743,0.000048345508,0.0008982873,0.0004009955,0.00022775863,0.000029593228],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048774012,0.0012128265,0.000027930768,0.000051022518,0.000037236543,0.000105788924,0.000248275,0.01174595,0.3102499,0.35220748,0.00091066456,0.32271522],"study_design_scores_gemma":[0.02993743,0.0026601725,0.00024971922,0.000089538116,0.000012465435,0.000078822566,0.00011250801,0.018744338,0.6408285,0.29440838,0.011572906,0.0013052212],"about_ca_topic_score_codex":0.0001423177,"about_ca_topic_score_gemma":0.00025087435,"teacher_disagreement_score":0.33057863,"about_ca_system_score_codex":0.00018016678,"about_ca_system_score_gemma":0.00009619532,"threshold_uncertainty_score":0.6123784},"labels":[],"label_agreement":null},{"id":"W1543756834","doi":"","title":"Simulating DB2 buffer pool management","year":2000,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Buffer (optical fiber); Storage management; TRACE (psycholinguistics); Cache; Disk buffer; Database; Circular buffer; Channel (broadcasting); Operating system; Computer network; Telecommunications","score_opus":0.1036938121967527,"score_gpt":0.40580909882530997,"score_spread":0.30211528662855724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1543756834","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":[0.40544924,0.013425301,0.3433851,0.11082468,0.00491278,0.038620315,0.0020083138,0.0030439403,0.078330345],"genre_scores_gemma":[0.9413123,0.0011641596,0.050263118,0.00007732873,0.000026689448,0.00027921647,0.000003459045,0.000020658204,0.006853051],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971344,0.00025418037,0.00039292275,0.0007024174,0.00082266616,0.00069340644],"domain_scores_gemma":[0.995045,0.001185028,0.00017140052,0.0014010267,0.0021357755,0.00006176038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006798175,0.0002541005,0.00039689272,0.00017441229,0.0007271463,0.00008819154,0.0023100136,0.00006288197,0.000024309096],"category_scores_gemma":[0.0015291608,0.00017551302,0.00008138699,0.001986104,0.00072195445,0.0005089555,0.0012009945,0.00033436672,0.00002985495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029561968,0.00019735144,0.000043679687,0.00019924196,0.00026358585,0.0000123644095,0.0029685588,0.01841057,0.0015272364,0.5936922,0.0033464301,0.37904316],"study_design_scores_gemma":[0.0061192866,0.00202619,0.00043854327,0.0022134495,0.000053495813,0.000002706193,0.052354787,0.044476338,0.25486106,0.44729224,0.1886812,0.0014807065],"about_ca_topic_score_codex":0.0000012466858,"about_ca_topic_score_gemma":0.000024440016,"teacher_disagreement_score":0.5358631,"about_ca_system_score_codex":0.000271399,"about_ca_system_score_gemma":0.00012248999,"threshold_uncertainty_score":0.71572137},"labels":[],"label_agreement":null},{"id":"W1546993490","doi":"10.1007/978-3-540-74469-6_12","title":"Adaptive Tuple Differential Coding","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Tuple; Computer science; Coding (social sciences); Skew; Encoder; Data compression; Algorithm; Tuple space; Adaptive coding; Outlier; Theoretical computer science; Artificial intelligence; Mathematics; Lossless compression; Discrete mathematics; Statistics","score_opus":0.03403773032016607,"score_gpt":0.26840111310510617,"score_spread":0.2343633827849401,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1546993490","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000030405989,0.00031210025,0.99294996,0.0002184229,0.0019886245,0.00034766784,0.00001350165,0.0007559294,0.0033833897],"genre_scores_gemma":[0.1360673,0.0000563118,0.862644,0.00053740223,0.00037721006,0.0000075620665,0.000008158136,0.000043562817,0.00025847074],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954039,0.000017074099,0.0005347542,0.0019415146,0.0011409875,0.00096179085],"domain_scores_gemma":[0.99656826,0.0005420385,0.00034994428,0.0021779458,0.00020763563,0.00015420275],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005291686,0.000650718,0.00060762005,0.0013380329,0.00031072393,0.0004089257,0.005936773,0.00047940275,0.000028279335],"category_scores_gemma":[0.00015994007,0.0006054595,0.0001296322,0.0007950364,0.0013216895,0.0010438197,0.0041694655,0.001321996,0.00007923061],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006516497,0.00001763913,0.000007443971,0.000012736121,0.000009184283,0.00022623176,0.00019980546,0.0034725196,0.00020911964,0.15315464,0.000021543774,0.84266263],"study_design_scores_gemma":[0.00039056115,0.00032247146,0.00007819266,0.00043721325,0.000010815878,0.00013691248,5.251118e-7,0.480611,0.007290556,0.50716645,0.002152904,0.0014024207],"about_ca_topic_score_codex":0.00001426816,"about_ca_topic_score_gemma":0.00007343162,"teacher_disagreement_score":0.8412602,"about_ca_system_score_codex":0.0005486913,"about_ca_system_score_gemma":0.00029915466,"threshold_uncertainty_score":0.9996397},"labels":[],"label_agreement":null},{"id":"W1551508721","doi":"10.5555/1496950.1496968","title":"Towards end-to-end quality of service: controlling I/O interference in shared storage servers","year":2008,"lang":"en","type":"article","venue":"ACM/IFIP/USENIX international conference on Middleware","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Server; Quality of service; Computer network; Operating system; End user; Database","score_opus":0.1391940978456361,"score_gpt":0.344648332403807,"score_spread":0.20545423455817088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1551508721","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":[0.6721199,0.00015081563,0.30478153,0.012328864,0.0014874266,0.000908414,0.001047772,0.00087645976,0.0062988186],"genre_scores_gemma":[0.96570987,0.0000723632,0.032755923,0.0009346988,0.000041970932,0.00007902548,0.000118781,0.000026315904,0.00026105164],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9959988,0.00018426566,0.0010456069,0.0011310615,0.0010697354,0.0005705252],"domain_scores_gemma":[0.9959581,0.00040762327,0.0005226343,0.001948287,0.0010094922,0.00015384663],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00055030815,0.00047011525,0.00069330045,0.0007430932,0.00012911741,0.00013935835,0.0063377256,0.00022917248,0.0003927807],"category_scores_gemma":[0.0014560197,0.00047680936,0.00014286244,0.0009917798,0.00020939679,0.00142653,0.0020268408,0.00064099004,0.00015283308],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001426838,0.0012577445,0.022397105,0.00032762164,0.0004231524,0.0008581472,0.016699312,0.008149088,0.05366534,0.80668867,0.0011822598,0.0869247],"study_design_scores_gemma":[0.02434959,0.0037762737,0.31982523,0.006611424,0.0000921368,0.00045104747,0.015344233,0.21388736,0.22217397,0.17286424,0.010567103,0.010057368],"about_ca_topic_score_codex":0.0011340859,"about_ca_topic_score_gemma":0.0013042691,"teacher_disagreement_score":0.63382447,"about_ca_system_score_codex":0.00042710613,"about_ca_system_score_gemma":0.00037929683,"threshold_uncertainty_score":0.9997684},"labels":[],"label_agreement":null},{"id":"W1557675393","doi":"10.1007/3-540-36389-0_30","title":"Adaptive File Cache Management for Mobile Computing","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Cache; Cache algorithms; Cache invalidation; Smart Cache; Cache pollution; Page cache; Operating system; Mobile computing; Computer network; File system; Block (permutation group theory); Distributed computing; CPU cache","score_opus":0.02461779716283751,"score_gpt":0.25351260726933345,"score_spread":0.22889481010649593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1557675393","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000027679796,0.00055435207,0.9918208,0.0001634722,0.0010250567,0.0013289413,0.00014050216,0.0007324148,0.0042316676],"genre_scores_gemma":[0.0092251375,0.00005565408,0.9888636,0.0005355681,0.00021767008,0.000100246165,0.000033303502,0.0000477534,0.000921109],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955267,0.00001755118,0.0005506915,0.00215989,0.00079911324,0.00094608567],"domain_scores_gemma":[0.9961454,0.00088432734,0.00039639382,0.0022446066,0.00021064901,0.00011859028],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0004887454,0.0006571221,0.0006097278,0.0009306017,0.00039073234,0.00036771898,0.0056164446,0.00034533703,0.00007150216],"category_scores_gemma":[0.00008964978,0.0006341573,0.00016165711,0.0007020987,0.00082182063,0.0007297208,0.0039838273,0.00074392365,0.00007517383],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031969369,0.000024981575,0.0000010195259,0.000043200012,0.000017141723,0.000095362506,0.00022313702,0.047528088,0.0000068519357,0.041636683,0.00071043125,0.90970993],"study_design_scores_gemma":[0.00031535194,0.0003559901,0.000010255374,0.00039567056,0.0000112561975,0.000046192974,0.0000010579531,0.7840487,0.00040354027,0.19440417,0.019136962,0.00087087776],"about_ca_topic_score_codex":0.000005036181,"about_ca_topic_score_gemma":0.000010035997,"teacher_disagreement_score":0.90883905,"about_ca_system_score_codex":0.0005447609,"about_ca_system_score_gemma":0.00010491945,"threshold_uncertainty_score":0.99976367},"labels":[],"label_agreement":null},{"id":"W1558936245","doi":"10.1007/0-306-47015-2_38","title":"An Efficient Transposition Algorithm for Distributed Memory Computers","year":2005,"lang":"en","type":"book-chapter","venue":"Kluwer Academic Publishers eBooks","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Parallel computing; Data exchange; Hypercube; Intel iPSC; Algorithm; Transposition (logic); Ethernet; Computer network","score_opus":0.01723482872307918,"score_gpt":0.2518102786940013,"score_spread":0.2345754499709221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1558936245","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010029579,0.00046738744,0.95724237,0.00090274744,0.0014016498,0.0014012834,0.0013983177,0.002846619,0.03432961],"genre_scores_gemma":[0.0014859317,0.00004619094,0.8984313,0.0030629288,0.0017691351,0.0005076312,0.004847035,0.00039821758,0.08945161],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9954472,0.00003924925,0.00091519306,0.0018068897,0.0008318383,0.00095961953],"domain_scores_gemma":[0.9965019,0.0002153136,0.0006039415,0.0020234126,0.00029469887,0.00036073523],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00056328886,0.00089640246,0.0007947176,0.00067085185,0.0003070837,0.00062075746,0.0051824683,0.0018400352,0.000018865276],"category_scores_gemma":[0.000038471328,0.00094309036,0.00034350992,0.00009753366,0.00047313815,0.0022114995,0.0005155486,0.0021769688,0.000029801773],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015756039,0.000027244536,2.1499307e-7,0.000038022732,0.00009998312,0.000033155746,0.0002896708,0.0012173473,0.00010180656,0.10799553,0.03298564,0.8571956],"study_design_scores_gemma":[0.0018089103,0.000371622,0.000005724999,0.00032302312,0.0001552312,0.00010918002,0.000058136844,0.22733638,0.000981162,0.06693818,0.69971687,0.0021955709],"about_ca_topic_score_codex":0.0000048380703,"about_ca_topic_score_gemma":0.000002190038,"teacher_disagreement_score":0.8550001,"about_ca_system_score_codex":0.0006969121,"about_ca_system_score_gemma":0.00024337736,"threshold_uncertainty_score":0.9994558},"labels":[],"label_agreement":null},{"id":"W1563694061","doi":"10.1023/a:1012705007864","title":"A Gracefully Degradable Declustered RAID Architecture","year":2002,"lang":"en","type":"article","venue":"Cluster Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Computer science; RAID; Prime (order theory); Control reconfiguration; Parallel computing; Computer hardware; Combinatorics; Mathematics; Embedded system","score_opus":0.02393951936800257,"score_gpt":0.23457954180919635,"score_spread":0.21064002244119379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1563694061","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011449249,0.0007218991,0.98014474,0.0027052327,0.00044600092,0.0002467447,0.0000027660653,0.0019118511,0.0023714884],"genre_scores_gemma":[0.473895,0.0000055330884,0.52441084,0.0010374838,0.00009424892,0.000006135019,0.0000028996144,0.000022678736,0.0005251586],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997801,0.00008167946,0.0003619769,0.0007447867,0.0003187436,0.00069179485],"domain_scores_gemma":[0.99795735,0.00026273684,0.00018326276,0.0014182598,0.000068041176,0.00011033798],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022489269,0.00029477777,0.00029231876,0.00024055986,0.00034670735,0.00026302697,0.0022245625,0.00012631388,0.000022004047],"category_scores_gemma":[0.00021531936,0.00026983712,0.00009688821,0.0007465508,0.00011780776,0.0005793208,0.0021852688,0.0004462486,0.00020961529],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007815286,0.00011465778,0.00036615838,0.00005837192,0.000039306025,0.00017485167,0.0021463588,0.012788085,0.00063423405,0.008106968,0.019084586,0.9564786],"study_design_scores_gemma":[0.00097159564,0.00012819246,0.00018427675,0.000096883916,0.00000867727,0.00043887814,0.000080258615,0.9416392,0.0015034877,0.012586375,0.041694645,0.00066756265],"about_ca_topic_score_codex":0.000006478782,"about_ca_topic_score_gemma":0.000008502831,"teacher_disagreement_score":0.955811,"about_ca_system_score_codex":0.00008853542,"about_ca_system_score_gemma":0.0000143973775,"threshold_uncertainty_score":0.9999754},"labels":[],"label_agreement":null},{"id":"W1567560840","doi":"10.1007/b99822","title":"Secure Data Management : VLDB 2004 Workshop, SDM 2004, Toronto, Canada, August 30, 2004, Proceedings","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Information privacy; Encryption; Access control; Computer security; XACML; Data management; SQL; Database; World Wide Web","score_opus":0.01906256170497585,"score_gpt":0.2494939043565923,"score_spread":0.23043134265161644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1567560840","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002951705,0.004002047,0.9482758,0.008615768,0.0008238369,0.00087190134,0.00017790204,0.0024193488,0.034518197],"genre_scores_gemma":[0.08425214,0.00063846615,0.89185274,0.00380205,0.00026341117,0.00012427536,0.00023868882,0.00010151318,0.018726697],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963048,0.000008316912,0.00044898325,0.0014982941,0.00074795116,0.0009916199],"domain_scores_gemma":[0.9963304,0.000030491627,0.00018255922,0.0030990208,0.00013521545,0.00022236057],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00026637476,0.00045385075,0.0003426098,0.00010076014,0.00026844622,0.00032689475,0.0074674874,0.00017096291,0.00038121158],"category_scores_gemma":[0.00010422478,0.0004196394,0.000039787745,0.0007042473,0.00012135153,0.0040588668,0.0047248774,0.00035264558,0.0001035318],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063149155,0.00009213215,0.000029351782,0.000048796217,0.00006715468,0.00020567032,0.00008872306,0.0011701486,0.00002594005,0.11286896,0.83594966,0.049447168],"study_design_scores_gemma":[0.0016789556,0.0001070474,0.00037462203,0.00021835888,0.00005575856,0.00011086688,0.002209238,0.004117317,0.0010977024,0.023936285,0.96442497,0.0016688739],"about_ca_topic_score_codex":0.12475022,"about_ca_topic_score_gemma":0.4618558,"teacher_disagreement_score":0.33710557,"about_ca_system_score_codex":0.0017563077,"about_ca_system_score_gemma":0.0004501321,"threshold_uncertainty_score":0.99982554},"labels":[],"label_agreement":null},{"id":"W1573216565","doi":"10.1109/nssmic.1992.301319","title":"Performance of the CDF DAQ system in the 1992 run","year":2003,"lang":"en","type":"article","venue":"IEEE Conference on Nuclear Science Symposium and Medical Imaging","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Verilog; Data acquisition; Event (particle physics); Computer science; Operating system; Computer hardware; Real-time computing; Embedded system; Field-programmable gate array; Physics","score_opus":0.012712606390744336,"score_gpt":0.24261925167244758,"score_spread":0.22990664528170324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573216565","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":[0.9503594,0.00006474629,0.006988013,0.0122464225,0.0011909116,0.00040558857,0.0000027168867,0.00024091471,0.02850127],"genre_scores_gemma":[0.99682254,0.00008792646,0.0022937811,0.00076395343,0.000010021722,0.0000067579026,4.5984553e-8,0.0000050651606,0.000009896779],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976951,0.00010254589,0.0002550288,0.00046063977,0.0010737682,0.0004129508],"domain_scores_gemma":[0.9986692,0.00010688083,0.00011613527,0.0009478847,0.000060823848,0.000099072124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016429786,0.00014120371,0.00016481569,0.00013955963,0.00036886733,0.00017551646,0.0032806157,0.00004768115,0.000005236507],"category_scores_gemma":[0.00033720167,0.00007856572,0.000028063969,0.0009937695,0.0019667158,0.00071122544,0.0003519746,0.0003798715,0.0000095953465],"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":[0.000007186786,0.00009426894,0.004468872,0.00007728293,0.0000028644338,0.000048886173,0.002729071,0.00009811861,0.028803505,0.9004772,0.00025239197,0.062940374],"study_design_scores_gemma":[0.0005425231,0.0001242235,0.00288346,0.0007371389,0.0000061491846,0.00037045276,0.0031225574,0.98032904,0.0073120375,0.00097262114,0.0032629925,0.00033679735],"about_ca_topic_score_codex":0.000020448528,"about_ca_topic_score_gemma":0.0000036185525,"teacher_disagreement_score":0.9802309,"about_ca_system_score_codex":0.00005885118,"about_ca_system_score_gemma":0.0002784045,"threshold_uncertainty_score":0.72464466},"labels":[],"label_agreement":null},{"id":"W1574015362","doi":"","title":"Proceedings of the 4th international symposium on Memory management","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; Presentation (obstetrics); Phone; Executive committee; Relevance (law); Originality; Operations research; Computer science; Management; Political science; Engineering; Medicine; Law","score_opus":0.01009281970268302,"score_gpt":0.23114699392411367,"score_spread":0.22105417422143064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1574015362","genre_codex":"other","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":[0.049133297,0.000012838343,0.44251168,0.026084455,0.0010630845,0.00048153804,0.0000044299145,0.0010037165,0.47970498],"genre_scores_gemma":[0.8374989,0.000014217823,0.16034232,0.0004986658,0.000013261117,0.000013899801,3.188934e-7,0.000003713935,0.0016147299],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994226,8.331504e-7,0.00008728223,0.00017533869,0.0002302894,0.000083674],"domain_scores_gemma":[0.9996215,0.000005907297,0.000054188007,0.00027220475,0.000036971407,0.000009199512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005150703,0.000055199343,0.00004354097,0.000042671563,0.000030517245,0.00002762754,0.0016706899,0.000018252753,0.000004143556],"category_scores_gemma":[0.000011517104,0.00003475986,0.00002265062,0.00018935137,0.000051133542,0.000320159,0.00085441885,0.00005806923,0.000016634001],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014006032,0.000033223616,0.00002881997,0.0000051848506,0.000008155392,0.0000014632726,0.000058941292,0.00036336493,0.0015512472,0.9889656,0.0007989283,0.008183719],"study_design_scores_gemma":[0.0011780807,0.00019007768,0.002845807,0.0001548809,0.000009016435,0.00002523177,0.00067895226,0.0014500824,0.71853,0.25368467,0.020905016,0.0003482048],"about_ca_topic_score_codex":0.000003732136,"about_ca_topic_score_gemma":9.076299e-7,"teacher_disagreement_score":0.7883656,"about_ca_system_score_codex":0.00006602462,"about_ca_system_score_gemma":0.000004778528,"threshold_uncertainty_score":0.31045854},"labels":[],"label_agreement":null},{"id":"W1574055853","doi":"10.5555/1855511.1855519","title":"Extending SSD lifetimes with disk-based write caches","year":2010,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":228,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cache; Operating system; Parallel computing; Griffin; Latency (audio); Page cache; CPU cache; Cache algorithms; Telecommunications","score_opus":0.008307244006538324,"score_gpt":0.2178177840751993,"score_spread":0.209510540068661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1574055853","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":[0.20626543,0.0019990942,0.7545641,0.006191369,0.00044594053,0.0007089076,0.0004924182,0.027873771,0.0014589493],"genre_scores_gemma":[0.6950491,0.000057697507,0.30454117,0.00005586778,0.000015056607,0.00010776408,0.000024768224,0.000018339118,0.00013025315],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983433,0.0000142714325,0.00019915885,0.00070846354,0.00024910184,0.0004857269],"domain_scores_gemma":[0.9979312,0.0002564201,0.00014718946,0.0015586385,0.000057647114,0.000048950962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001397048,0.0003137605,0.0002980767,0.0003788485,0.00031350993,0.0002212495,0.0016426368,0.0002966366,0.000049832608],"category_scores_gemma":[0.0005202545,0.00023799877,0.00003982346,0.00065663434,0.0007735491,0.0009191812,0.0009033871,0.00072737935,0.000026631918],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034862263,0.00016311792,0.0038204887,0.000093856506,0.000055991397,0.0006232509,0.00021978377,0.0001221973,0.016663361,0.13754751,0.014674539,0.825981],"study_design_scores_gemma":[0.0036543587,0.0029870702,0.019749584,0.0006248462,0.000106889835,0.0008705898,0.006258252,0.060343944,0.33008882,0.11947452,0.44993058,0.005910528],"about_ca_topic_score_codex":0.00001701018,"about_ca_topic_score_gemma":0.000046347188,"teacher_disagreement_score":0.8200705,"about_ca_system_score_codex":0.000027507935,"about_ca_system_score_gemma":0.000052767606,"threshold_uncertainty_score":0.9705308},"labels":[],"label_agreement":null},{"id":"W1581131753","doi":"10.1109/pacrim.1995.519593","title":"Exploiting group communication for reliable high volume data distribution","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Multicast; Computer science; Computer network; Throughput; Reliable multicast; Bandwidth (computing); Data transmission; Protocol (science); Transmission (telecommunications); Distributed computing; Protocol Independent Multicast; Operating system; Wireless; Telecommunications","score_opus":0.06884585825078876,"score_gpt":0.26993499186265674,"score_spread":0.20108913361186798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581131753","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00042476103,0.00024261708,0.9949061,0.0025860781,0.0001006921,0.00018947145,0.00011882242,0.0011311221,0.00030030817],"genre_scores_gemma":[0.30402753,0.00012094565,0.69400734,0.00008680844,0.00001622094,0.000046220284,0.0011861441,0.000006206505,0.00050260953],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991038,0.000014526474,0.00017580732,0.0003727936,0.00011614411,0.00021695725],"domain_scores_gemma":[0.99639237,0.00010627544,0.00009171,0.0033316845,0.000053617085,0.000024318024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024077826,0.00008430204,0.00009426056,0.0000292108,0.00023003062,0.00011395542,0.0031923808,0.00005340477,0.000022901519],"category_scores_gemma":[0.00032239791,0.0000816453,0.000014299707,0.00025125465,0.000053636526,0.002585817,0.0020388968,0.000093633855,0.0000740408],"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":[0.0000015935635,0.00006612736,0.00011186274,0.000011821295,0.0000061073756,0.0000011399409,0.000034062057,0.000064806336,0.00020380458,0.67324436,0.17615908,0.15009522],"study_design_scores_gemma":[0.0002743574,0.000056735516,0.0001498832,0.000017358681,0.0000044269746,0.000005321044,0.000077489494,0.7151683,0.0006070031,0.036441896,0.24699819,0.00019905277],"about_ca_topic_score_codex":0.000051363902,"about_ca_topic_score_gemma":0.00001610988,"teacher_disagreement_score":0.7151035,"about_ca_system_score_codex":0.000061662584,"about_ca_system_score_gemma":0.0000034548293,"threshold_uncertainty_score":0.59322906},"labels":[],"label_agreement":null},{"id":"W1582706316","doi":"10.48550/arxiv.1303.6801","title":"Enumerating Some Fractional Repetition Codes","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Luby transform code; Distributed data store; Node (physics); Code (set theory); Linear code; Network packet; Block code; Algorithm; Theoretical computer science; Distributed computing; Computer network; Decoding methods; Physics","score_opus":0.0606141456153891,"score_gpt":0.19634951598029826,"score_spread":0.13573537036490915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1582706316","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":[0.07148745,0.00010276134,0.92521644,0.0001948975,0.00060649624,0.00020344065,0.00003380775,0.0011767108,0.0009780054],"genre_scores_gemma":[0.95830786,0.00023284552,0.040376425,0.0001183288,0.00010229064,0.000003416412,0.000054006134,0.000014384989,0.0007904477],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998245,0.00006767235,0.00018376195,0.0010953551,0.000109523426,0.0002986875],"domain_scores_gemma":[0.99778664,0.00013020878,0.00032783241,0.0015273547,0.00015182042,0.00007616254],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001334718,0.0002683167,0.0002521426,0.00026141838,0.00022089,0.00017532837,0.0018307476,0.00032405375,0.0000562391],"category_scores_gemma":[0.00012672316,0.0003197058,0.00011074908,0.00032221762,0.00014656495,0.0019115228,0.0031347387,0.00077801285,0.00031833642],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034950713,0.000037805967,0.00022729675,0.000029349505,0.000036060395,0.00015047049,0.000034325112,0.09523157,0.00014153843,0.9017258,0.0007632064,0.0016190719],"study_design_scores_gemma":[0.00018088949,0.000031089716,0.0005493005,0.0000787197,0.000018700315,0.000011161925,0.00006288769,0.36716187,0.0007560746,0.6293643,0.0013104618,0.00047454037],"about_ca_topic_score_codex":0.00009801001,"about_ca_topic_score_gemma":0.000012771044,"teacher_disagreement_score":0.88682044,"about_ca_system_score_codex":0.00027507864,"about_ca_system_score_gemma":0.000113671944,"threshold_uncertainty_score":0.9999255},"labels":[],"label_agreement":null},{"id":"W1600547396","doi":"10.1007/3-540-36265-7_9","title":"Exploiting Web Document Structure to Improve Storage Management in Proxy Caches","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Cache; Storage management; Proxy (statistics); Latency (audio); Operating system; Database; Page cache; CPU cache; Cache algorithms","score_opus":0.014632604881526238,"score_gpt":0.24249495038007163,"score_spread":0.2278623454985454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1600547396","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005102948,0.00034911162,0.9931329,0.001031577,0.001392746,0.001415295,0.000025314159,0.0005607637,0.0015820249],"genre_scores_gemma":[0.18468839,0.00007172155,0.8134424,0.0010158826,0.0001923492,0.00007000731,0.000006534449,0.000055335568,0.00045735057],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99397457,0.00003204919,0.00075700204,0.0027712567,0.0012849906,0.0011801207],"domain_scores_gemma":[0.9962903,0.00020611237,0.0003519379,0.0028429509,0.00011946714,0.00018919211],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00058486004,0.0008388282,0.00069935963,0.0020444235,0.00021265086,0.000643161,0.006336641,0.00038162756,0.000026018724],"category_scores_gemma":[0.000118308155,0.00079260534,0.00009404733,0.0013672366,0.00046738278,0.0013411407,0.0060358993,0.0012769931,0.000051527426],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050311464,0.000026203374,0.000025723579,0.000086344255,0.000014600554,0.000662338,0.0008024044,0.050148144,0.00045884654,0.033619817,0.000041968236,0.9141086],"study_design_scores_gemma":[0.0011309022,0.00059765024,0.00014179849,0.0014999913,0.000020030246,0.00012200812,0.0000065333943,0.42287487,0.008124463,0.55297464,0.009362047,0.0031450938],"about_ca_topic_score_codex":0.000015820598,"about_ca_topic_score_gemma":0.000103942635,"teacher_disagreement_score":0.9109635,"about_ca_system_score_codex":0.0013032303,"about_ca_system_score_gemma":0.00015905702,"threshold_uncertainty_score":0.9994525},"labels":[],"label_agreement":null},{"id":"W161599812","doi":"10.2172/984627","title":"P-986 Letter of Intent: Medium-Energy Antiproton Physics at Fermilab","year":2009,"lang":"en","type":"report","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Antiproton; Tevatron; Fermilab; Physics; Particle physics; Nuclear physics; Particle accelerator; Collider; Proton; Large Hadron Collider; Beam (structure)","score_opus":0.03560882725623102,"score_gpt":0.28277386320272896,"score_spread":0.24716503594649794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W161599812","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000625036,0.0007679735,0.95333177,0.0012093033,0.0011605372,0.0003824749,0.00004604107,0.0012882625,0.041751154],"genre_scores_gemma":[0.054042995,0.019354884,0.79742527,0.009006861,0.003387951,0.00055951026,0.0012785314,0.00040799932,0.11453601],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99639344,0.000032230135,0.00069298025,0.0010155439,0.0013627043,0.00050307263],"domain_scores_gemma":[0.99564165,0.000072768176,0.0007585003,0.0029405286,0.0005201276,0.00006641898],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002522836,0.0005114116,0.00085369457,0.00025279712,0.00007440642,0.000053603388,0.0031793173,0.00049549545,0.00003819946],"category_scores_gemma":[0.00019722513,0.000422538,0.000224512,0.00061311433,0.00024649643,0.00064054335,0.0028802915,0.0004661592,0.00004223429],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009806974,0.0001508429,0.00011356765,0.00022567048,0.000103961764,0.00031763906,0.000039574486,0.000034920704,0.002634166,0.035016645,0.5137819,0.44757134],"study_design_scores_gemma":[0.00021006347,0.00016531079,0.00010187519,0.00022411063,0.000024539764,0.00012393932,0.0000047961744,0.00055322493,0.14422794,0.014977426,0.83867437,0.0007124109],"about_ca_topic_score_codex":0.00015734982,"about_ca_topic_score_gemma":0.000033138735,"teacher_disagreement_score":0.4468589,"about_ca_system_score_codex":0.00047175356,"about_ca_system_score_gemma":0.0003657322,"threshold_uncertainty_score":0.9998226},"labels":[],"label_agreement":null},{"id":"W16262860","doi":"10.1111/j.1365-294x.2005.02729.x","title":"Exploring the effect of directory depth on file access for FAT and NTFS file systems","year":2008,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Directory; Computer science; Computer file; Unix file types; File system; Versioning file system; File system fragmentation; File Control Block; Operating system; Database; Torrent file; Indexed file; Benchmark (surveying); Fork (system call); Data file; Self-certifying File System; Stub file","score_opus":0.0512226302420641,"score_gpt":0.27673445206876673,"score_spread":0.22551182182670262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W16262860","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":[0.8109101,0.0004186659,0.18593036,0.0001473364,0.0006224891,0.00096118153,0.0002764092,0.00035023663,0.00038322888],"genre_scores_gemma":[0.9946564,0.000029795794,0.0041383826,0.00006043835,0.000016858734,0.0010212807,0.00002906374,0.0000122029205,0.00003557306],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99913144,0.000100543366,0.00013717564,0.00031046165,0.00009372803,0.00022663503],"domain_scores_gemma":[0.99800307,0.0012400612,0.00009498621,0.0006105768,0.00002685447,0.000024444213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109667235,0.00012108966,0.00022664687,0.00009421744,0.00012978337,0.000021562426,0.00086921715,0.00005476269,0.000015229516],"category_scores_gemma":[0.00054774806,0.000086642845,0.00004211885,0.00016883826,0.00014833517,0.00025932115,0.0004986153,0.00010066922,0.000006020507],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064492604,0.00054475636,0.021244906,0.0019541637,0.0009674664,0.0030555576,0.0024410079,0.039596416,0.11992909,0.08095004,0.32690957,0.4017621],"study_design_scores_gemma":[0.0023898175,0.005747355,0.059872504,0.00015847635,0.00005239263,0.00036779966,0.000085070766,0.026885416,0.850524,0.0017799645,0.051151402,0.0009857971],"about_ca_topic_score_codex":0.000015915768,"about_ca_topic_score_gemma":0.000011485461,"teacher_disagreement_score":0.73059493,"about_ca_system_score_codex":0.000034442844,"about_ca_system_score_gemma":0.000013053372,"threshold_uncertainty_score":0.35331926},"labels":[],"label_agreement":null},{"id":"W162652620","doi":"","title":"Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; Honor; Presentation (obstetrics); Digital library; Conceptualization; China; Computer science; Political science; World Wide Web; Law","score_opus":0.041919932922080794,"score_gpt":0.23468857603142695,"score_spread":0.19276864310934616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W162652620","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":[0.31207937,0.000045551737,0.6003536,0.016988654,0.00047065783,0.0005789869,0.000035523037,0.002491877,0.0669558],"genre_scores_gemma":[0.9155511,0.0000052842565,0.08389177,0.00019601025,0.000009699836,0.0000068189524,4.440967e-7,0.000005246338,0.00033361485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991178,0.0000014098692,0.00016318655,0.00028034564,0.0002504665,0.0001868059],"domain_scores_gemma":[0.99910116,0.000026783688,0.00010876776,0.00065914856,0.00007659529,0.000027513903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038371625,0.00012023548,0.00012868969,0.000056351495,0.00007113925,0.00026072547,0.0023040131,0.000053483076,0.000004345984],"category_scores_gemma":[0.0002858011,0.00007240321,0.000040547882,0.0003735447,0.00028128977,0.002029043,0.0012632537,0.00014775706,0.000026010648],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020777757,0.000034114277,0.00010756123,0.0000073002607,0.0000035581927,0.0000011763489,0.0001814758,0.000026083697,0.0029436925,0.9903268,0.00090055645,0.005465594],"study_design_scores_gemma":[0.00019411079,0.00014808825,0.00076344446,0.000059032034,0.0000014042516,0.000011091932,0.0002426019,0.00019590993,0.40635237,0.5909935,0.0008887615,0.00014963961],"about_ca_topic_score_codex":0.0000046531136,"about_ca_topic_score_gemma":0.000001207295,"teacher_disagreement_score":0.60347176,"about_ca_system_score_codex":0.00003185246,"about_ca_system_score_gemma":0.00007188074,"threshold_uncertainty_score":0.4281468},"labels":[],"label_agreement":null},{"id":"W162738593","doi":"10.1007/978-3-642-36092-3_6","title":"Approximating Barrier Resilience for Arrangements of Non-identical Disk Sensors","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Resilience (materials science); Computer science; Geology; Materials science; Composite material","score_opus":0.01559778449589973,"score_gpt":0.2643327690871796,"score_spread":0.24873498459127988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W162738593","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039415908,0.00014092503,0.9962364,0.0002287864,0.0008854458,0.0010329424,0.000028306335,0.00021901804,0.00083403307],"genre_scores_gemma":[0.06971325,0.000018530623,0.9296132,0.00019205906,0.00011892672,0.00004948039,0.0000059311296,0.000033459753,0.00025520046],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954962,0.000019118985,0.0009124095,0.0017218852,0.0010435929,0.0008067984],"domain_scores_gemma":[0.9958784,0.0007676977,0.00063694065,0.0022135426,0.00036596638,0.00013745249],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00085560844,0.00054333126,0.00072041794,0.00077219785,0.00023245014,0.00029419296,0.005227649,0.00033897482,0.000015913667],"category_scores_gemma":[0.00082519,0.00048783072,0.00015379518,0.0005962065,0.0015614256,0.0012271925,0.002650215,0.00060872466,0.000031473643],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000101890255,0.000047035148,0.00007949371,0.0002615927,0.0000243621,0.000035106343,0.0006716692,0.025160082,0.004018012,0.04472528,0.00010069206,0.9248665],"study_design_scores_gemma":[0.00030165003,0.00020493302,0.000057679354,0.00047795463,0.000010573891,0.00001995746,0.0000011359282,0.6975461,0.015477481,0.28486684,0.00039790434,0.0006377609],"about_ca_topic_score_codex":0.000011152065,"about_ca_topic_score_gemma":0.000009522443,"teacher_disagreement_score":0.9242287,"about_ca_system_score_codex":0.00021694085,"about_ca_system_score_gemma":0.00023654857,"threshold_uncertainty_score":0.99975735},"labels":[],"label_agreement":null},{"id":"W1730322892","doi":"10.1109/mtdt.1999.782690","title":"A comparative simulation study of four multilevel DRAMs","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dram; Spice; Computer science; Process (computing); Noise (video); Electronic engineering; Scheme (mathematics); Computer engineering; Computer hardware; Engineering; Artificial intelligence; Programming language; Mathematics","score_opus":0.10750543100610468,"score_gpt":0.3489416957113162,"score_spread":0.24143626470521154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1730322892","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":[0.21280377,0.0000073162437,0.785703,0.000012233364,0.000043200565,0.00022170422,8.3762944e-7,0.00022627889,0.0009816643],"genre_scores_gemma":[0.79445106,1.7451052e-7,0.20543808,0.000011319529,0.0000013634419,0.00000778433,2.884413e-7,0.0000019004383,0.00008805349],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929124,0.00004495142,0.0001650402,0.00022597898,0.00016253552,0.00011023259],"domain_scores_gemma":[0.99907756,0.00016116827,0.00008499444,0.00057702826,0.000081784114,0.00001744198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009124543,0.0000795246,0.00015085017,0.000074852884,0.000042980242,0.000018132432,0.00045902943,0.000026552498,0.000007869559],"category_scores_gemma":[0.00012707931,0.0000659171,0.00001448492,0.00027438748,0.000032502572,0.0004794277,0.00015481474,0.00006167642,0.000016961641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017836483,0.00274835,0.0058176713,0.000014964177,0.00009645768,0.000037057092,0.014648602,0.48781595,0.002627188,0.42148298,0.0004609584,0.06423199],"study_design_scores_gemma":[0.0013070438,0.00064198725,0.0068391776,0.0000068305967,0.000006010142,0.000003703227,0.003896804,0.952579,0.0150592225,0.018439492,0.0009494166,0.00027130588],"about_ca_topic_score_codex":0.000017548597,"about_ca_topic_score_gemma":0.000025832058,"teacher_disagreement_score":0.5816473,"about_ca_system_score_codex":0.000020000021,"about_ca_system_score_gemma":0.000013459426,"threshold_uncertainty_score":0.26880214},"labels":[],"label_agreement":null},{"id":"W1750904937","doi":"","title":"A cross-platform solution for bibliographic record manipulation in digital libraries","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Digital library; Computer science; Software; World Wide Web; Architecture; Software engineering; Operating system","score_opus":0.04170727225439594,"score_gpt":0.2935998448264005,"score_spread":0.2518925725720046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1750904937","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":[0.05794493,0.00005544607,0.9393438,0.00010388702,0.00016070288,0.00022296915,0.000005922499,0.0008068745,0.0013554668],"genre_scores_gemma":[0.6698305,0.000011220057,0.32996607,0.000040192088,0.000015672045,0.0000137882525,0.000018854595,0.000005416367,0.00009824825],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999021,0.0000012075312,0.00024913982,0.00029458146,0.00012285408,0.00031124442],"domain_scores_gemma":[0.9993147,0.00014011198,0.00007260028,0.00039701382,0.000047257563,0.00002830503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021402331,0.0000983736,0.00009407812,0.0019803015,0.00008482863,0.00045720796,0.0005563544,0.000094549,0.0000038726807],"category_scores_gemma":[0.00013120746,0.00009122546,0.000040818606,0.0033268875,0.00008246619,0.007926787,0.0002766104,0.00008043321,0.000009487271],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003481903,0.000040840037,0.05398234,0.000012287025,0.0000039723714,0.000007908456,0.000063504835,0.00004247805,0.00025106457,0.36096844,0.0005030143,0.58408934],"study_design_scores_gemma":[0.0008472378,0.00025245058,0.1193329,0.000023260674,0.0000016989642,0.000015640575,0.00009122332,0.06931733,0.0049737208,0.7941968,0.010504988,0.0004427303],"about_ca_topic_score_codex":0.000021830445,"about_ca_topic_score_gemma":0.00012276482,"teacher_disagreement_score":0.6118856,"about_ca_system_score_codex":0.00003413672,"about_ca_system_score_gemma":0.000014516261,"threshold_uncertainty_score":0.5746729},"labels":[],"label_agreement":null},{"id":"W1780371484","doi":"10.5555/1960475.1960478","title":"Capo: recapitulating storage for virtual desktops","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Operating system; Virtual machine; Computer data storage; File system; Embedded system","score_opus":0.05886634402512243,"score_gpt":0.26172669483268146,"score_spread":0.20286035080755904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1780371484","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073836413,0.00003826993,0.9864559,0.000082920444,0.0002776196,0.00018632185,0.0000053710146,0.001322258,0.0042476854],"genre_scores_gemma":[0.38762647,0.0000021767705,0.61186653,0.00009801853,0.000014936664,0.00002938533,0.0000019156187,0.0000068903905,0.0003536967],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990569,0.000012447014,0.00016832729,0.0003680176,0.000110008266,0.00028433523],"domain_scores_gemma":[0.9989106,0.000097737226,0.00007310238,0.00082050444,0.000054625223,0.000043441196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017479279,0.00011621039,0.00011999148,0.00008170574,0.00011541714,0.00003842891,0.0011361362,0.00006842794,0.00003117218],"category_scores_gemma":[0.0002081008,0.00010189017,0.000040242307,0.00019977074,0.000060258517,0.00089537905,0.00046876827,0.00008837681,0.00004473203],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037126665,0.000027380303,0.000062185674,0.0000045221345,0.000006902696,0.0000100272755,0.0005986326,0.00003052033,0.0018267722,0.8226867,0.0013027936,0.17343986],"study_design_scores_gemma":[0.0017692926,0.0015385282,0.0025252532,0.00005013351,0.000020437223,0.00007556899,0.0018792179,0.15648775,0.26659104,0.5317087,0.035524067,0.0018299749],"about_ca_topic_score_codex":0.000024869858,"about_ca_topic_score_gemma":0.000015319622,"teacher_disagreement_score":0.38024282,"about_ca_system_score_codex":0.000038547456,"about_ca_system_score_gemma":0.000024139725,"threshold_uncertainty_score":0.41549605},"labels":[],"label_agreement":null},{"id":"W1820421154","doi":"10.14288/sa.v1i1.186333","title":"An Exploration of Finding Aid Technologies and NoSQL Databases","year":2015,"lang":"en","type":"article","venue":"Open Collections","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"NoSQL; Database; Computer science; Relational database; Field (mathematics); Class (philosophy); Focus (optics); Data science; World Wide Web; Scalability","score_opus":0.14728489649694465,"score_gpt":0.3514805648574647,"score_spread":0.20419566836052006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1820421154","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007666881,0.00009278987,0.99159783,0.00050093414,0.00011945572,0.00029205554,0.000043730433,0.0006649548,0.005921561],"genre_scores_gemma":[0.21387066,0.00008664945,0.78362817,0.000021458327,0.0000089111445,0.00014746003,0.000021171258,0.0000084477915,0.0022070562],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99935395,0.000023511253,0.00013318226,0.00027210297,0.00010435555,0.000112897134],"domain_scores_gemma":[0.99900943,0.00005240822,0.00008484937,0.0007365747,0.00008722672,0.000029505456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016216897,0.000074932716,0.00011754941,0.00014227981,0.0005044267,0.00047539218,0.0010158481,0.000038445636,0.0000038350595],"category_scores_gemma":[0.00038498497,0.00007202621,0.000007715876,0.0012671418,0.000112815054,0.0067084422,0.0011484306,0.00007988824,0.0000023201228],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007040922,0.0006696142,0.00093204674,0.00003515277,0.000067523026,0.00003858,0.0020893791,0.0029530008,0.0054995148,0.48929933,0.29132593,0.20701951],"study_design_scores_gemma":[0.0024497407,0.0018806531,0.0001124802,0.00013226259,0.00003594941,0.00013560301,0.035554167,0.05057219,0.19832987,0.5895259,0.12020563,0.0010655965],"about_ca_topic_score_codex":0.0005403275,"about_ca_topic_score_gemma":0.0005382237,"teacher_disagreement_score":0.21310398,"about_ca_system_score_codex":0.000041993266,"about_ca_system_score_gemma":0.00008310087,"threshold_uncertainty_score":0.4863459},"labels":[],"label_agreement":null},{"id":"W1826588871","doi":"10.1007/s00107-006-0106-z","title":"Impact of Aspen Log Storage with and without Protection on OSB Performance","year":2006,"lang":"de","type":"article","venue":"European Journal of Wood and Wood Products","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Intertek (Canada)","funders":"FPInnovations","keywords":"Bark (sound); Pulp and paper industry; Penetration (warfare); Fungal growth; Stain; Woodworking; Horticulture; Botany; Biology; Staining; Mathematics; Engineering; Ecology","score_opus":0.017187694316880657,"score_gpt":0.22902340022471226,"score_spread":0.2118357059078316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1826588871","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":[0.9841779,0.0047394517,0.009420594,0.0005824795,0.00030064778,0.00033989802,0.000012684293,0.00005283825,0.00037352796],"genre_scores_gemma":[0.9881931,0.00052758923,0.01060789,0.000014509798,0.0005028637,7.927003e-7,0.0000017330549,0.000036027017,0.00011548042],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99792314,0.0002700333,0.00056585704,0.0004867477,0.0004184715,0.00033576688],"domain_scores_gemma":[0.9977739,0.00002272189,0.0011270229,0.0006240804,0.00035300874,0.00009930857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010123784,0.00033997963,0.00046047644,0.00033287183,0.00016570413,0.0001608464,0.0005729307,0.00004252285,0.0000022756806],"category_scores_gemma":[0.00014910912,0.00023219414,0.00005064597,0.00052142335,0.00034113316,0.0011113377,0.00026978445,0.0006442761,0.000010468419],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027747185,0.0017408837,0.024499023,0.001109583,0.0010466167,0.0013506243,0.0034217504,0.008737177,0.057662155,0.0008941705,0.003727225,0.89303607],"study_design_scores_gemma":[0.013165922,0.10622544,0.69471216,0.006158377,0.0006918897,0.0070860637,0.00036475583,0.0025494164,0.15276276,0.0009537817,0.01254727,0.0027821518],"about_ca_topic_score_codex":0.000008724761,"about_ca_topic_score_gemma":0.0000010440895,"teacher_disagreement_score":0.8902539,"about_ca_system_score_codex":0.00005992235,"about_ca_system_score_gemma":0.00013527242,"threshold_uncertainty_score":0.94686025},"labels":[],"label_agreement":null},{"id":"W1835784777","doi":"10.1109/lman.1993.665362","title":"Achieving METARING performance without insertion buffers","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Insertion loss; Optoelectronics; Materials science","score_opus":0.01837839677714667,"score_gpt":0.24371218551105936,"score_spread":0.2253337887339127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1835784777","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":[0.37334675,0.000054779346,0.621936,0.0006518675,0.00006074049,0.00005292798,1.564809e-7,0.0010809593,0.002815786],"genre_scores_gemma":[0.62426215,0.000024576895,0.3753129,0.0001661875,0.000017382321,0.0000057860025,6.0752836e-7,0.0000037569262,0.00020664377],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919176,0.000010699233,0.00013708266,0.0002786663,0.00015646002,0.00022533446],"domain_scores_gemma":[0.9992375,0.000022025755,0.000047787562,0.0006382397,0.00002369281,0.000030761617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014468656,0.000102425955,0.00009955019,0.000103850965,0.00011585859,0.00007182885,0.00087235955,0.00004554406,0.000010286122],"category_scores_gemma":[0.00004878936,0.0000864942,0.000021164149,0.00025855587,0.000035790756,0.0025434126,0.00045767042,0.00015434225,0.00014174945],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003538662,0.000023344895,0.014842215,0.000009315145,0.000010101128,0.0000019471338,0.00014033243,0.002711386,0.009162051,0.03861123,0.00016497739,0.93431956],"study_design_scores_gemma":[0.0006958302,0.00020076954,0.075938225,0.0000626222,0.000013317969,0.00007415172,0.00013099966,0.6847618,0.17649695,0.0014656245,0.05920693,0.0009527237],"about_ca_topic_score_codex":0.000008169206,"about_ca_topic_score_gemma":0.000015337435,"teacher_disagreement_score":0.93336684,"about_ca_system_score_codex":0.00007323891,"about_ca_system_score_gemma":0.000013161578,"threshold_uncertainty_score":0.3527131},"labels":[],"label_agreement":null},{"id":"W1836172604","doi":"10.1109/isit.1993.748415","title":"Efficient Coding/decoding Strategies for Channels With Memory","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Burst error; Computer science; Interleaving; Error detection and correction; Decoding methods; Algorithm; Turbo code; Channel (broadcasting); Concatenated error correction code; Theoretical computer science; Block code; Telecommunications","score_opus":0.02623863353084225,"score_gpt":0.26866237224969247,"score_spread":0.24242373871885023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1836172604","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":[0.008150264,0.000065444176,0.9846006,0.0013048585,0.00013315315,0.00027868166,0.0000037006841,0.0012124896,0.0042508105],"genre_scores_gemma":[0.5334034,0.0000021506423,0.4661055,0.0001477749,0.000036967598,0.000030155732,0.0000010995153,0.0000063198895,0.00026662764],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989868,0.000005987587,0.00013564261,0.000376196,0.00016417279,0.00033120415],"domain_scores_gemma":[0.9991629,0.00010169949,0.000063362815,0.0005661378,0.00006771854,0.000038172424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014717049,0.00013749221,0.00013262745,0.00011728825,0.00012928278,0.00018796227,0.000878454,0.000045453726,0.00000996571],"category_scores_gemma":[0.000033589306,0.00010169938,0.00002782462,0.00024261793,0.00007674294,0.0005573993,0.00024933537,0.00008090679,0.000031062682],"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":[0.000008609485,0.000038417318,0.000002183133,0.000013914014,0.000009586804,0.0000060834786,0.00033791168,0.09237014,0.0009225015,0.84586644,0.0013462421,0.059077956],"study_design_scores_gemma":[0.00069526274,0.00023536899,0.000008468938,0.00002827861,0.0000052002747,0.000032947763,0.0013689654,0.9379376,0.039782107,0.01173404,0.007762685,0.00040905416],"about_ca_topic_score_codex":0.000003101469,"about_ca_topic_score_gemma":0.000013598343,"teacher_disagreement_score":0.84556746,"about_ca_system_score_codex":0.00006087766,"about_ca_system_score_gemma":0.000053714677,"threshold_uncertainty_score":0.41471803},"labels":[],"label_agreement":null},{"id":"W184466170","doi":"","title":"Using Versioning to Simplify the Implementation of a Highly-Available File System","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; File system; High availability; Maintainability; Storage area network; Software versioning; Replication (statistics); Context (archaeology); Key (lock); Operating system; Software; Computer data storage; Software engineering","score_opus":0.03977489290125855,"score_gpt":0.30886694706906825,"score_spread":0.2690920541678097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W184466170","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":[0.03207614,0.000022458318,0.96527666,0.00031975424,0.000085892025,0.00019540743,0.00002740457,0.00039320925,0.0016030915],"genre_scores_gemma":[0.6627943,0.0000023451678,0.33692908,0.0001028083,0.000010948184,0.000012206866,0.0000051306833,0.000004468118,0.0001387308],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99928606,0.000016944494,0.00015957313,0.0001966284,0.00016183688,0.00017894311],"domain_scores_gemma":[0.9991492,0.000085785265,0.000082069084,0.00060723675,0.000052545118,0.000023174185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012588341,0.00006747319,0.000086595464,0.000082113096,0.00013386132,0.000043191085,0.0007397649,0.000023180104,0.00023474926],"category_scores_gemma":[0.000028259712,0.00004748685,0.000019365985,0.0005882185,0.000020771437,0.00044775938,0.0005815335,0.000044525124,0.000096495554],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026294541,0.000067342226,0.003039614,0.00011661827,0.000078156605,0.00008502212,0.0022310559,0.011518568,0.090615034,0.49489188,0.24466665,0.15266374],"study_design_scores_gemma":[0.0016557535,0.00063023716,0.0018972909,0.0003241025,0.000047115373,0.00029839005,0.042114332,0.28513122,0.40626878,0.003027198,0.2574353,0.0011702796],"about_ca_topic_score_codex":0.00039472798,"about_ca_topic_score_gemma":0.000028401133,"teacher_disagreement_score":0.6307181,"about_ca_system_score_codex":0.00010032322,"about_ca_system_score_gemma":0.000030444171,"threshold_uncertainty_score":0.25703397},"labels":[],"label_agreement":null},{"id":"W185404545","doi":"","title":"iSCSI Simulation for Internet Applications.","year":2004,"lang":"en","type":"article","venue":"International Conference on Internet Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"iSCSI; SCSI; Computer science; Computer network; The Internet; Operating system; Storage area network; Embedded system; Computer data storage; Fibre Channel","score_opus":0.05931540375867069,"score_gpt":0.3435425664538979,"score_spread":0.28422716269522724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W185404545","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":[0.0026702224,0.000015995893,0.9877852,0.0016675589,0.0007333122,0.000536623,0.000017593991,0.0007447361,0.005828722],"genre_scores_gemma":[0.8440986,0.000003391292,0.15483858,0.00045366012,0.00014751728,0.00007068846,0.000053498243,0.000015236546,0.000318823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823225,0.000018403542,0.00044083106,0.00067868066,0.00033923998,0.00029058082],"domain_scores_gemma":[0.9984916,0.00023852887,0.00028520552,0.0005101211,0.0004150162,0.00005953535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019913024,0.00023197032,0.00018437832,0.00027460634,0.000068263624,0.00036606024,0.0024101762,0.00009868354,0.000033718232],"category_scores_gemma":[0.00020817803,0.00023537873,0.00009571188,0.00018830322,0.00008630423,0.0006173916,0.00066080963,0.00023301576,0.00017608372],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023983524,0.000061126215,0.000031977284,0.0000066935536,0.000028500946,0.0000035430123,0.00021507323,0.027024925,0.00019404653,0.8983405,0.00019113146,0.073878504],"study_design_scores_gemma":[0.0010663832,0.00017321484,0.00007142297,0.00012617554,0.0000037936452,0.000013442782,0.000057666828,0.83449465,0.005829627,0.14306179,0.01480415,0.0002976908],"about_ca_topic_score_codex":0.000029778206,"about_ca_topic_score_gemma":0.000009166586,"teacher_disagreement_score":0.8414284,"about_ca_system_score_codex":0.00029956942,"about_ca_system_score_gemma":0.000063757194,"threshold_uncertainty_score":0.95984656},"labels":[],"label_agreement":null},{"id":"W185974372","doi":"","title":"Falkon: A Proposal for Project Globus Incubation","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; National laboratory; Art history; Management; Computer science; Art; Engineering; Engineering physics; Economics","score_opus":0.02517338261447477,"score_gpt":0.30914253263295194,"score_spread":0.28396915001847717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W185974372","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011549414,0.000025914967,0.9933226,0.00076255685,0.00014953877,0.00055873464,0.0000034819602,0.0013049525,0.0027172607],"genre_scores_gemma":[0.12693864,0.0000017429307,0.8726205,0.0001308159,0.00003095116,0.000036939517,0.000006018044,0.0000047462495,0.00022962809],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99919975,0.0000051933052,0.0001402492,0.00027444767,0.0001347692,0.00024558938],"domain_scores_gemma":[0.99931127,0.000072521296,0.000053508586,0.00046501833,0.00007293843,0.000024765526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030303915,0.00008099802,0.00007479424,0.00011664305,0.00007228947,0.000053638145,0.00067399937,0.000057408473,0.000001562606],"category_scores_gemma":[0.00025337876,0.00006511942,0.000023901932,0.00039233075,0.00004033866,0.0007178301,0.00026372093,0.000054891618,0.000011564686],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000080111495,0.000023022565,0.00007332759,0.000008871498,0.0000029376376,0.000005275885,0.0000679701,0.0000056212552,0.00059867353,0.77615035,0.0025804501,0.22047547],"study_design_scores_gemma":[0.0011514095,0.0008821095,0.00078262755,0.000017931512,0.000006945003,0.000069633774,0.0003836473,0.037936766,0.09822945,0.7952941,0.06458063,0.0006647663],"about_ca_topic_score_codex":0.000010368274,"about_ca_topic_score_gemma":0.000067422305,"teacher_disagreement_score":0.2198107,"about_ca_system_score_codex":0.00006287401,"about_ca_system_score_gemma":0.00009939227,"threshold_uncertainty_score":0.26554927},"labels":[],"label_agreement":null},{"id":"W1905719725","doi":"10.5555/2750482.2750499","title":"A tale of two erasure codes in HDFS","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Erasure code; Distributed data store; Erasure; Overhead (engineering); Computer data storage; Replication (statistics); Code (set theory); Reliability (semiconductor); Distributed computing; Decoding methods; Operating system; Algorithm; Power (physics)","score_opus":0.037125538853891325,"score_gpt":0.2965676975896702,"score_spread":0.2594421587357789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1905719725","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":[0.055584792,0.00015907569,0.93808305,0.00038072318,0.00008025239,0.000068242385,0.0000032166436,0.00034253698,0.0052981246],"genre_scores_gemma":[0.7051275,0.0000026634332,0.29468527,0.000041370276,0.000003059896,0.0000035860119,6.186702e-7,0.0000017988342,0.00013412807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99945563,0.000013005727,0.00011594538,0.00015988945,0.00013724915,0.00011829109],"domain_scores_gemma":[0.9993359,0.00003280444,0.00003751343,0.00052821054,0.000040174906,0.000025417683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015885534,0.000053368356,0.00010403082,0.000090239206,0.0000068675513,0.000013098947,0.0007540277,0.000027074893,0.0000036407016],"category_scores_gemma":[0.00014661407,0.000044086057,0.000010981175,0.00036831322,0.000060270548,0.00047180706,0.00041184516,0.00006436796,0.000022019696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074597965,0.00013818697,0.012571773,0.000013366732,0.0000074182644,0.00007396349,0.0008588932,0.0017579325,0.0056626657,0.8690928,0.007878528,0.101936966],"study_design_scores_gemma":[0.0031086726,0.0004302264,0.0036006744,0.000066286266,0.0000038415264,0.000060332164,0.001058078,0.072937414,0.22977558,0.67179674,0.016466599,0.0006955305],"about_ca_topic_score_codex":0.0000878136,"about_ca_topic_score_gemma":0.00018123652,"teacher_disagreement_score":0.6495427,"about_ca_system_score_codex":0.000027152388,"about_ca_system_score_gemma":0.000037859885,"threshold_uncertainty_score":0.17977773},"labels":[],"label_agreement":null},{"id":"W1924303716","doi":"10.1109/ccece.2001.933718","title":"Scalability of computer clusters","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Scalability; Virtual file system; File system; Network File System; Computer cluster; Node (physics); Distributed computing; Operating system; Self-certifying File System","score_opus":0.02326152372786274,"score_gpt":0.23608636434339292,"score_spread":0.21282484061553017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1924303716","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":[0.0074128145,0.00003485412,0.98811126,0.0008164128,0.00011145542,0.00006030261,0.0000014269342,0.00050878635,0.0029426683],"genre_scores_gemma":[0.5022621,0.000004038458,0.49752176,0.00011876463,0.0000054890347,0.000001416857,2.0797023e-7,0.000001532571,0.0000846823],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993704,0.000013699168,0.00014234288,0.00022260718,0.000121812154,0.00012914953],"domain_scores_gemma":[0.9989878,0.000046797624,0.000044232034,0.0008636727,0.000034165274,0.000023323035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007050922,0.00006262946,0.00010202929,0.000053821128,0.00002231481,0.000015323252,0.00090650487,0.000034902536,0.00005942055],"category_scores_gemma":[0.000030594558,0.000051327897,0.00002806584,0.0002577991,0.00011625569,0.00043458157,0.0006012057,0.000058310034,0.00006735808],"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":[0.0000012640171,0.00015145936,0.0012827567,0.000022781422,0.000010246817,0.000008723418,0.00023056034,0.0004841736,0.0005278138,0.1629151,0.0167971,0.817568],"study_design_scores_gemma":[0.00038931821,0.00019141391,0.002702268,0.0000120661525,0.000002418773,0.000018822731,0.000027232029,0.9528722,0.014246234,0.021100324,0.008149833,0.00028787498],"about_ca_topic_score_codex":0.000004927494,"about_ca_topic_score_gemma":0.000001892131,"teacher_disagreement_score":0.95238805,"about_ca_system_score_codex":0.000018719524,"about_ca_system_score_gemma":0.0000025009563,"threshold_uncertainty_score":0.20930909},"labels":[],"label_agreement":null},{"id":"W1939476686","doi":"10.1109/spdp.1995.530725","title":"Characterization and management of I/O on multiprogrammed parallel systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Replication (statistics); Variety (cybernetics); Parallel computing; Resource management (computing); Parallel processing; Characterization (materials science); Distributed computing; Data management; Artificial intelligence; Database","score_opus":0.029459493337623835,"score_gpt":0.23584722399619093,"score_spread":0.20638773065856708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1939476686","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":[0.011504501,0.00007230028,0.9868052,0.00023286344,0.00007105202,0.00022862593,0.000002046937,0.00034513167,0.00073830155],"genre_scores_gemma":[0.7512844,0.0004613985,0.24742179,0.000039931376,0.000004455513,0.000040381343,0.000004934165,0.0000040473365,0.00073865626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949735,0.0000079966185,0.00010962804,0.00018160304,0.0001052308,0.00009816317],"domain_scores_gemma":[0.99951,0.00001245823,0.000057324796,0.00038889507,0.000014294701,0.000017051116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038286908,0.000060100218,0.000076626755,0.000056057834,0.000022927736,0.000032601674,0.00028695798,0.000024868372,0.000002640289],"category_scores_gemma":[0.000004802004,0.000049203816,0.000007923308,0.0001473896,0.00003062124,0.00025096518,0.00017872143,0.000027350488,0.000015236661],"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":[0.0000020106004,0.000073253366,0.00012627491,0.00007455113,0.000014769627,0.000014514043,0.00006636599,0.000090670124,0.0014669914,0.52519995,0.000103687955,0.47276697],"study_design_scores_gemma":[0.0018649567,0.00056434044,0.010777847,0.00025752943,0.000014687094,0.000025870539,0.00033492656,0.9280886,0.00903286,0.0012963122,0.047085587,0.0006564733],"about_ca_topic_score_codex":0.0000029604041,"about_ca_topic_score_gemma":2.8798132e-7,"teacher_disagreement_score":0.92799795,"about_ca_system_score_codex":0.000009808985,"about_ca_system_score_gemma":4.082066e-7,"threshold_uncertainty_score":0.20064734},"labels":[],"label_agreement":null},{"id":"W1944137603","doi":"10.1109/iscas.1993.394147","title":"A logic-enhanced memory for digital data recovery circuits","year":2002,"lang":"en","type":"article","venue":"1993 IEEE International Symposium on Circuits and Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Digital data; Digital electronics; Semiconductor memory; Pixel; Computer hardware; Logic gate; Range (aeronautics); Electronic circuit; Artificial intelligence; Algorithm; Data transmission; Electrical engineering; Engineering","score_opus":0.07417229178957581,"score_gpt":0.2825442226492954,"score_spread":0.2083719308597196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1944137603","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":[0.007027931,0.0006551341,0.9622734,0.0018331744,0.00654903,0.0008646292,0.0015127887,0.00071043475,0.01857345],"genre_scores_gemma":[0.9960109,0.00020797928,0.00046252485,0.0002832228,0.0004131393,0.000120920144,0.00014444225,0.000024225666,0.0023326236],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975988,0.000027910159,0.00046674156,0.0010177315,0.00052996323,0.00035880646],"domain_scores_gemma":[0.99768645,0.0003876361,0.000273752,0.0013898732,0.00016724068,0.000095056996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027603938,0.00026612097,0.00030806576,0.00016616726,0.0001597473,0.00079698395,0.002762155,0.00013842912,0.000008768133],"category_scores_gemma":[0.00023653173,0.00024175116,0.000063269435,0.00017935772,0.00008269417,0.0023379296,0.00040648042,0.00016464759,0.00009302456],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030487028,0.00072558614,0.00015409786,0.000266359,0.0005300384,0.00015555721,0.00085540826,0.0050237593,0.045984622,0.15716411,0.058260936,0.730849],"study_design_scores_gemma":[0.0054886034,0.00204458,0.0002679126,0.0010612432,0.00006331722,0.0009784591,0.00060527446,0.7117047,0.009808208,0.01815831,0.24652545,0.0032939825],"about_ca_topic_score_codex":0.000016948754,"about_ca_topic_score_gemma":0.000003872417,"teacher_disagreement_score":0.988983,"about_ca_system_score_codex":0.0001413507,"about_ca_system_score_gemma":0.000017125441,"threshold_uncertainty_score":0.9858326},"labels":[],"label_agreement":null},{"id":"W1963517151","doi":"10.1007/s00366-007-0080-z","title":"Toward interoperable mesh, geometry and field components for PDE simulation development","year":2007,"lang":"en","type":"article","venue":"Engineering With Computers","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Interoperability; Petascale computing; Computer science; Component (thermodynamics); Discretization; Computational science; Field (mathematics); Mesh generation; Distributed computing; Polygon mesh; Supercomputer; Computer graphics (images); Engineering; Parallel computing; Finite element method; World Wide Web; Mathematics; Structural engineering","score_opus":0.01800327637098658,"score_gpt":0.23236629198376457,"score_spread":0.21436301561277799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963517151","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":[0.07994309,0.000052082774,0.9189404,0.00010674361,0.00030784914,0.00015873929,6.782215e-7,0.0004827831,0.0000076079605],"genre_scores_gemma":[0.51124674,0.0000010760167,0.4886636,0.00005561495,0.0000122571855,0.00000483029,0.000002891224,0.0000063632074,0.0000065952395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991891,0.000002476641,0.00015572624,0.00027186717,0.00012173746,0.00025913963],"domain_scores_gemma":[0.9992927,0.00033055857,0.00003876956,0.0002471307,0.000036094556,0.00005477806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015642759,0.00013637832,0.00013029661,0.0001932712,0.00005820199,0.00006668655,0.00038215457,0.000045329278,4.4000774e-7],"category_scores_gemma":[0.000051352596,0.00012271602,0.00001333186,0.00020255,0.000013985792,0.000351379,0.00025009696,0.00009995314,0.0000016790735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055756675,0.000051219668,0.0007759799,0.00018642416,0.0001022651,0.0000548042,0.0014155313,0.7184457,0.002016334,0.007963796,0.0003244677,0.2686077],"study_design_scores_gemma":[0.0005300283,0.00017522757,0.0021998354,0.00011532228,0.0000031018562,0.000018118708,0.000020363448,0.97117436,0.013664229,0.0000631531,0.0117347445,0.00030150785],"about_ca_topic_score_codex":0.0000025262464,"about_ca_topic_score_gemma":9.358517e-7,"teacher_disagreement_score":0.43130368,"about_ca_system_score_codex":0.0000637059,"about_ca_system_score_gemma":0.000009868676,"threshold_uncertainty_score":0.5004214},"labels":[],"label_agreement":null},{"id":"W1964212654","doi":"10.1016/j.parco.2015.03.009","title":"Scalable connectionless RDMA over unreliable datagrams","year":2015,"lang":"en","type":"article","venue":"Parallel Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Advanced Scientific Computing Research; National Science Foundation of Sri Lanka; Office of Science; Natural Sciences and Engineering Research Council of Canada; Savannah River Operations Office, U.S. Department of Energy; Ontario Innovation Trust; U.S. Department of Energy","keywords":"Remote direct memory access; InfiniBand; Datagram; Computer science; Connectionless communication; Scalability; Operating system; Computer network; The Internet; Network packet","score_opus":0.04617615889508019,"score_gpt":0.29136573708861596,"score_spread":0.24518957819353576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964212654","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":[0.011683654,0.0003487127,0.9810965,0.0003904897,0.00090941874,0.00015749325,0.000004304672,0.0017477506,0.003661665],"genre_scores_gemma":[0.5278034,0.000008074553,0.47151005,0.00027675007,0.000096221,0.0000060844477,0.000018743507,0.000015900596,0.00026476217],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981046,0.000052485677,0.00029898967,0.0006348265,0.00036411852,0.00054497947],"domain_scores_gemma":[0.99814606,0.00017409804,0.00016220193,0.001236837,0.0001307166,0.00015007441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050905335,0.0002101406,0.00025045493,0.00012416008,0.00022707727,0.0002675197,0.0017666102,0.00009518159,0.000007776088],"category_scores_gemma":[0.0003732002,0.00020463915,0.00004167659,0.00070418057,0.00009477613,0.0011650973,0.001828644,0.0002693671,0.00029109645],"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":[0.000030593063,0.0002650162,0.006910679,0.000053736192,0.00007642418,0.00017523437,0.0009913227,0.20698296,0.00045507203,0.54297316,0.10314164,0.13794418],"study_design_scores_gemma":[0.0010680229,0.000110272325,0.0005128049,0.00005194997,0.0000063231296,0.00008227063,0.00023223666,0.8737125,0.0006591465,0.03986403,0.08314854,0.000551928],"about_ca_topic_score_codex":0.00012560893,"about_ca_topic_score_gemma":0.000010389074,"teacher_disagreement_score":0.6667295,"about_ca_system_score_codex":0.00013205025,"about_ca_system_score_gemma":0.00008273298,"threshold_uncertainty_score":0.8344942},"labels":[],"label_agreement":null},{"id":"W1966142043","doi":"10.1109/cluster.2013.6702617","title":"Mercury: Enabling remote procedure call for high-performance computing","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Porting; Asynchronous communication; Remote procedure call; Distributed computing; Operating system; Interface (matter); Supercomputer; Network interface; Computer network; Software","score_opus":0.01664069227391344,"score_gpt":0.24821812336883226,"score_spread":0.23157743109491882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966142043","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":[0.07439885,0.00006831323,0.9211111,0.0017353586,0.00019152813,0.00051197864,0.0000017258739,0.0016191271,0.00036201748],"genre_scores_gemma":[0.504647,0.000010729287,0.49473637,0.00029918752,0.000034488286,0.000011481199,0.0000032756338,0.000008796009,0.00024868513],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864227,0.000008022633,0.00023578756,0.00048822968,0.00016877319,0.00045690275],"domain_scores_gemma":[0.9988211,0.000116873445,0.00010593651,0.0007500278,0.00015337774,0.000052716117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015659248,0.00016818772,0.00017781687,0.00010893343,0.00020519937,0.0001525269,0.0013488949,0.00008924735,0.000007501453],"category_scores_gemma":[0.00019042598,0.00013880001,0.000026616524,0.00037936593,0.000055855686,0.0014601981,0.0006228586,0.00015645618,0.000112712376],"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":[0.0000034290535,0.000026513657,0.0001396597,0.00012600452,0.000016584543,0.0000029570429,0.00018286779,0.0015015969,0.006193085,0.080340184,0.00916743,0.9022997],"study_design_scores_gemma":[0.0004087466,0.00015806597,0.00072527316,0.00006186845,0.000004025936,0.000022098215,0.00006881842,0.9199845,0.051841553,0.021491835,0.004792722,0.00044047897],"about_ca_topic_score_codex":0.00006902163,"about_ca_topic_score_gemma":0.000004811948,"teacher_disagreement_score":0.9184829,"about_ca_system_score_codex":0.000054674496,"about_ca_system_score_gemma":0.00003928522,"threshold_uncertainty_score":0.56601},"labels":[],"label_agreement":null},{"id":"W1967003152","doi":"10.1117/12.410907","title":"&lt;title&gt;Disk-striping scalability in the Exedra media server&lt;/title&gt;","year":2000,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Data striping; Scalability; Server; Computer science; The Internet; Component (thermodynamics); Focus (optics); Computer network; Operating system; Distributed computing; Physics","score_opus":0.012239565058477361,"score_gpt":0.2285182685290935,"score_spread":0.21627870347061612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967003152","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":[0.9773398,0.00019044233,0.00036069474,0.0027220908,0.0002283674,0.00030201205,0.00002712943,0.00019487091,0.018634565],"genre_scores_gemma":[0.69002163,0.00034901573,0.30799448,0.00029896508,0.00046413645,0.00015534592,0.000012945196,0.000058550595,0.0006449198],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99851215,2.8782738e-8,0.00036659677,0.0003209266,0.0005187427,0.00028154012],"domain_scores_gemma":[0.9992307,0.00014597918,0.00013022783,0.00012889819,0.0003201357,0.00004410368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052944495,0.00018428218,0.00021469829,0.00007074447,0.000051742263,0.00009790988,0.0019005616,0.0001365356,0.00007328528],"category_scores_gemma":[0.0005194141,0.00013731587,0.00021816998,0.00045222198,0.00019207782,0.00057720486,0.0002216923,0.00028572613,0.000026383987],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010483841,0.000068712245,0.00009432581,0.00010676802,0.000049422888,3.0514013e-7,0.0002035367,0.00005422111,0.017629534,0.96305776,0.010304976,0.008419968],"study_design_scores_gemma":[0.0037562454,0.0007807466,0.0124189565,0.0014210602,0.00024498752,0.00015627689,0.0023466162,0.2243217,0.080625765,0.1596756,0.51144785,0.0028042092],"about_ca_topic_score_codex":0.0000024511987,"about_ca_topic_score_gemma":2.5168845e-7,"teacher_disagreement_score":0.80338216,"about_ca_system_score_codex":0.000119480086,"about_ca_system_score_gemma":0.000025568903,"threshold_uncertainty_score":0.55995786},"labels":[],"label_agreement":null},{"id":"W1969742982","doi":"10.1109/69.979978","title":"A comprehensive analytical performance model for disk devices under random workloads","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo; University of Toronto","keywords":"Optical disc; Computer science; Disk array; Magnetic storage; Server; Computer data storage; Optical storage; Constant (computer programming); Hard disk drive performance characteristics; Computer hardware; Computer network; Operating system","score_opus":0.06566339483825503,"score_gpt":0.28485298537923814,"score_spread":0.2191895905409831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969742982","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":[0.0021604316,0.001247209,0.9954811,0.00011416532,0.00019733568,0.00018662462,0.00012938616,0.0004442514,0.000039551465],"genre_scores_gemma":[0.90097076,0.0005143831,0.098252684,0.00003800412,0.000023222565,0.00004786324,0.000010710032,0.000016111804,0.00012627832],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896836,0.0000067018864,0.00018131142,0.00047962056,0.00009247612,0.00027149834],"domain_scores_gemma":[0.9986171,0.0002539734,0.00002525805,0.0009841353,0.00004490026,0.000074603005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006862899,0.00018842456,0.00020684973,0.00017186803,0.00016127645,0.00007883846,0.00083676924,0.000075835356,0.0000038765884],"category_scores_gemma":[0.00000786153,0.00017650923,0.000037115246,0.00030463643,0.000048465652,0.001168474,0.00003218074,0.00020321562,0.000018684173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025998796,0.00014567135,0.000003946306,0.00015409371,0.00007852583,0.000002582754,0.0002496,0.79483235,0.00019580664,0.0023393012,0.0006164752,0.20135565],"study_design_scores_gemma":[0.0006901464,0.00004509256,0.000015533229,0.000049388636,0.000025330237,0.000009700158,0.00001441826,0.9957642,0.0005609631,0.00006891644,0.0025456434,0.0002106478],"about_ca_topic_score_codex":7.453552e-7,"about_ca_topic_score_gemma":0.0000054808056,"teacher_disagreement_score":0.8988103,"about_ca_system_score_codex":0.00003202083,"about_ca_system_score_gemma":0.000010477686,"threshold_uncertainty_score":0.7197838},"labels":[],"label_agreement":null},{"id":"W1972270193","doi":"10.5555/1404595.1404620","title":"Improving the performance of Apache web server","year":2007,"lang":"en","type":"article","venue":"Spring Simulation Multiconference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Operating system; Instruction prefetch; Web server; Cache; Page cache; Web page; Static web page; Database; World Wide Web; Cache algorithms; CPU cache; The Internet","score_opus":0.029023122195173716,"score_gpt":0.2764486911011595,"score_spread":0.24742556890598577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972270193","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":[0.51160187,0.000018930934,0.48797008,0.000031931122,0.00007345934,0.00008768006,8.117198e-7,0.00017012554,0.00004514738],"genre_scores_gemma":[0.9204112,0.0000055200685,0.07950884,0.000030125033,0.000016210362,0.0000026631774,6.98274e-7,0.0000061695637,0.000018553012],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893683,0.000018787388,0.00028517476,0.00025692114,0.0002518569,0.0002504119],"domain_scores_gemma":[0.9982936,0.00038634182,0.00020618158,0.00093499164,0.00014949992,0.000029401373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055555155,0.00011610165,0.00011484991,0.000098280405,0.0001288748,0.000048598224,0.0010893113,0.00006276302,0.0000042869706],"category_scores_gemma":[0.00034091854,0.00008798169,0.00003131065,0.0003238914,0.00011949053,0.0007677013,0.00046067472,0.0001914364,0.000016719996],"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":[0.00002347239,0.0000631755,0.06824904,0.00010137996,0.000018640507,0.0000051672537,0.00086867204,0.36119607,0.0915104,0.08155186,0.0000020562425,0.39641005],"study_design_scores_gemma":[0.00017522353,0.000025782847,0.033939037,0.000022860484,0.000002830808,7.626143e-7,0.000044575216,0.92100483,0.044338036,0.00017858163,0.00015808201,0.000109374356],"about_ca_topic_score_codex":0.000041855877,"about_ca_topic_score_gemma":0.00002612886,"teacher_disagreement_score":0.5598088,"about_ca_system_score_codex":0.000043013904,"about_ca_system_score_gemma":0.000045531233,"threshold_uncertainty_score":0.3587789},"labels":[],"label_agreement":null},{"id":"W1975686539","doi":"10.4304/jcm.7.1.28-38","title":"Low-Overhead Dynamic Sampling for Redundant Traffic Elimination","year":2012,"lang":"en","type":"article","venue":"Journal of Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Byte; Redundancy (engineering); Network packet; Overhead (engineering); Data redundancy; Throughput; Traverse; Sampling (signal processing); Algorithm; Real-time computing; Computer network; Detector; Computer hardware","score_opus":0.06176264834551478,"score_gpt":0.3605533027415574,"score_spread":0.29879065439604263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975686539","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":[0.010088365,0.0024975764,0.9813013,0.0055816905,0.00024219362,0.0001165617,0.0000080378095,0.000084631516,0.00007961074],"genre_scores_gemma":[0.54398215,0.0003540892,0.45558873,0.000033495966,0.000016863396,0.0000065491313,0.0000039720035,0.0000043911828,0.000009787691],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918324,0.000044109616,0.0003725144,0.00006413495,0.00015273533,0.00018329777],"domain_scores_gemma":[0.997421,0.0004937229,0.00044939635,0.0013410368,0.000241235,0.00005360554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005907682,0.00007430798,0.0001369719,0.00018826396,0.00021447081,0.000054630786,0.0024412035,0.000048389848,0.0000012190706],"category_scores_gemma":[0.00045768073,0.00006802244,0.00009900044,0.0002538565,0.000083293264,0.0015410384,0.00037360808,0.00023246143,0.000005024647],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016394499,0.0006306295,0.00003759416,0.00003070297,0.00007216523,6.796146e-7,0.0018589064,0.0029667197,0.00808442,0.30600375,0.0013065685,0.6789915],"study_design_scores_gemma":[0.003909892,0.0013405746,0.015772775,0.00089181424,0.00029567478,0.0012175996,0.0038954467,0.48555636,0.011288216,0.12227514,0.35197225,0.0015842582],"about_ca_topic_score_codex":3.8495654e-7,"about_ca_topic_score_gemma":0.000004626624,"teacher_disagreement_score":0.6774072,"about_ca_system_score_codex":0.0001443555,"about_ca_system_score_gemma":0.00006017906,"threshold_uncertainty_score":0.4536404},"labels":[],"label_agreement":null},{"id":"W1976808991","doi":"10.1007/s12024-013-9486-7","title":"Ensuring integrity of forensic data in a shared practice environment","year":2013,"lang":"en","type":"letter","venue":"Forensic Science Medicine and Pathology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint John Regional Hospital","funders":"","keywords":"Forensic science; Computer science; Computer security; Geography; Archaeology","score_opus":0.0711536255556927,"score_gpt":0.310264358751804,"score_spread":0.2391107331961113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976808991","genre_codex":"commentary","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075227446,0.004026931,0.12301912,0.86108756,0.0017468045,0.0010304294,0.00015959467,0.00025666947,0.0011501528],"genre_scores_gemma":[0.019533765,0.002039143,0.68674463,0.28978357,0.0010137283,0.00010680395,0.0005494173,0.000054286495,0.00017464743],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959572,0.00014713858,0.0006564943,0.0016560967,0.0008538614,0.0007292334],"domain_scores_gemma":[0.9945224,0.0009396745,0.00059270347,0.0037243834,0.00014662635,0.000074211566],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0021852304,0.00036252005,0.00077808765,0.0009077718,0.000106231244,0.000043458083,0.0045266855,0.00047000672,0.000021004347],"category_scores_gemma":[0.00485376,0.0002760588,0.00002481182,0.00088648207,0.0054232944,0.0019177326,0.004946464,0.0019892042,0.000018158064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016550697,0.00007510173,0.0007528034,0.00028369884,0.00002798723,0.005809619,0.0043471255,0.00001456903,0.0016235079,0.0057686623,0.5982588,0.3830216],"study_design_scores_gemma":[0.0027764912,0.0025052337,0.004840326,0.0018174439,0.00017802946,0.0065578995,0.0020381932,0.028190332,0.0015641296,0.06811544,0.87933505,0.002081461],"about_ca_topic_score_codex":0.00031627968,"about_ca_topic_score_gemma":0.000022819935,"teacher_disagreement_score":0.57130396,"about_ca_system_score_codex":0.0001090252,"about_ca_system_score_gemma":0.00017783162,"threshold_uncertainty_score":0.9999692},"labels":[],"label_agreement":null},{"id":"W1977407043","doi":"10.1145/2797022.2797023","title":"MemScope","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Ministry of Science ICT and Future Planning; Ministry of Science, ICT and Future Planning","keywords":"Computer science","score_opus":0.049599479310216396,"score_gpt":0.2810887996581179,"score_spread":0.23148932034790148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977407043","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00042331952,0.00006771775,0.951856,0.0011288392,0.00013731734,0.000025869394,2.7488778e-7,0.0012390899,0.045121558],"genre_scores_gemma":[0.17048767,0.0000025409413,0.82807195,0.0003041712,0.000010390554,0.0000037470727,4.818469e-7,0.0000021332714,0.0011169274],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961793,0.0000044690173,0.000046590834,0.0001325362,0.00010006651,0.000098421784],"domain_scores_gemma":[0.9993505,0.000011252457,0.000012828255,0.0005555756,0.000028925051,0.000040941304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007203854,0.000037219826,0.00004004762,0.00003321127,0.000013487119,0.000033176755,0.0008291619,0.00001873763,0.000005811437],"category_scores_gemma":[0.00009915317,0.000028883045,0.0000067327433,0.0001845521,0.000023695888,0.0006025871,0.00048656636,0.000036881018,0.00045033568],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.057947e-7,0.000007877093,0.0000453886,4.3881488e-7,0.0000012699066,0.000014643719,0.000052424846,0.000030179413,0.00015679307,0.87362635,0.043592177,0.08247207],"study_design_scores_gemma":[0.00038036445,0.00012494161,0.000095911375,0.0000033713618,9.821971e-7,0.000040883795,0.00017710768,0.013694865,0.036959995,0.44741654,0.5008212,0.00028383135],"about_ca_topic_score_codex":0.0000064213687,"about_ca_topic_score_gemma":0.000002714256,"teacher_disagreement_score":0.45722902,"about_ca_system_score_codex":0.00001993959,"about_ca_system_score_gemma":0.00002285533,"threshold_uncertainty_score":0.5788304},"labels":[],"label_agreement":null},{"id":"W197953939","doi":"10.1007/978-3-319-10347-1_6","title":"SGCN: Further Aspects and Issues","year":2014,"lang":"en","type":"book-chapter","venue":"SpringerBriefs in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","score_opus":0.0163262809418515,"score_gpt":0.24924814858888047,"score_spread":0.23292186764702896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W197953939","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000109318906,0.00117221,0.949599,0.0014003469,0.0011698409,0.0003004086,0.0000036195756,0.0008565965,0.045388613],"genre_scores_gemma":[0.03552111,0.0007138821,0.9479318,0.0009447899,0.00053634524,0.000019636083,0.000002441239,0.00008610181,0.014243862],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958617,0.000018522991,0.00047376956,0.0020270755,0.000882559,0.0007363453],"domain_scores_gemma":[0.996626,0.00013929246,0.00029041205,0.002629635,0.00014205553,0.00017259222],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009036823,0.00055488735,0.00059516926,0.0008946054,0.00020445573,0.0006115161,0.004882698,0.00027221412,0.000020042646],"category_scores_gemma":[0.00008638935,0.0005511164,0.000065850836,0.00041514565,0.0017628883,0.0010900432,0.0059521305,0.0007027557,0.00014048022],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010179807,0.0000062047748,0.000016663109,0.000021704918,0.0000044279527,0.000097191805,0.00016388057,0.00011949702,0.000045176912,0.73792344,0.00013524549,0.26146555],"study_design_scores_gemma":[0.0005150717,0.00036248474,0.00062039675,0.00073546614,0.00000979842,0.00022273044,0.0000038276225,0.089882664,0.0014626842,0.6765105,0.22764434,0.0020300332],"about_ca_topic_score_codex":0.000026978436,"about_ca_topic_score_gemma":0.000025921137,"teacher_disagreement_score":0.2594355,"about_ca_system_score_codex":0.00022718104,"about_ca_system_score_gemma":0.00018498753,"threshold_uncertainty_score":0.99969405},"labels":[],"label_agreement":null},{"id":"W1980726110","doi":"10.1016/j.cpc.2006.11.010","title":"A standard format for Les Houches Event Files","year":2006,"lang":"en","type":"article","venue":"Computer Physics Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":464,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Computer science; Programming language; XML; Event (particle physics); Fortran; Parsing; Information retrieval; Operating system; Physics","score_opus":0.03850612663368104,"score_gpt":0.29148583823416746,"score_spread":0.25297971160048643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980726110","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023720224,0.0005327917,0.9955442,0.0018246634,0.00009918272,0.00033262893,0.0001268566,0.0008825243,0.000419966],"genre_scores_gemma":[0.13450491,0.00006733057,0.8648871,0.00008436161,0.00008495905,0.00017283089,0.00015828495,0.000013567259,0.000026615298],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999036,0.000039950723,0.00026519847,0.0002593696,0.00014706285,0.00025240073],"domain_scores_gemma":[0.9958814,0.0003710127,0.00015445081,0.0033979851,0.00016673919,0.00002844431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011178116,0.0001622408,0.00018717506,0.00006360389,0.0005132436,0.00016933729,0.0036050356,0.000052520933,8.005997e-7],"category_scores_gemma":[0.000014451104,0.00016217763,0.00010453892,0.00031238815,0.00020300402,0.00080222625,0.0023365465,0.0001602972,0.000013655075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016580034,0.00008977932,0.000038749262,0.0000113833285,0.000011482148,2.680912e-7,0.00011533197,0.0015187243,0.00008120641,0.7676757,0.012150701,0.21830504],"study_design_scores_gemma":[0.00027810066,0.00007181494,0.00019679999,0.000028074064,0.000007095621,0.0000032550674,0.000023777566,0.5431432,0.00083202345,0.3585423,0.09663994,0.0002336277],"about_ca_topic_score_codex":0.000023209743,"about_ca_topic_score_gemma":0.000027676555,"teacher_disagreement_score":0.5416245,"about_ca_system_score_codex":0.00008382297,"about_ca_system_score_gemma":0.00004515391,"threshold_uncertainty_score":0.6699113},"labels":[],"label_agreement":null},{"id":"W1981345850","doi":"10.1177/1094342010372928","title":"High-performance Physics Simulations Using Multi-core CPUs and GPGPUs in a Volunteer Computing Context","year":2010,"lang":"en","type":"article","venue":"The International Journal of High Performance Computing Applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"D-Wave Systems (Canada)","funders":"","keywords":"Context (archaeology); CUDA; Parallel computing; Computer science; Core (optical fiber); Computational science; Supercomputer; Many core; Computer architecture; Physics; Telecommunications","score_opus":0.028602298249578183,"score_gpt":0.29799596955056074,"score_spread":0.2693936713009826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981345850","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":[0.5616871,0.000047275153,0.43728286,0.00037015902,0.0004108079,0.00013368219,0.000006895837,0.000057154277,0.0000040532655],"genre_scores_gemma":[0.80825686,0.000033654178,0.1912232,0.00014799311,0.0003102671,0.000003794622,0.000005353845,0.000013591239,0.000005275993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982645,0.000022840497,0.0006929073,0.0002849475,0.0004570194,0.00027780578],"domain_scores_gemma":[0.9977237,0.00035614966,0.00074224756,0.0005330422,0.00059073797,0.000054120086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050714525,0.00020287008,0.00025994296,0.00026313993,0.00038567508,0.00018149079,0.002106011,0.00007892303,0.0000024239105],"category_scores_gemma":[0.000090791924,0.00016665235,0.000043435004,0.00051559065,0.00024831295,0.00095195236,0.0007836602,0.00086660957,0.0000069514913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003025019,0.00027689847,0.03716865,0.000027556782,0.00009690121,0.000011337005,0.0012697201,0.4740629,0.014288945,0.041572798,0.000041323427,0.43115273],"study_design_scores_gemma":[0.0007957934,0.000041111896,0.02789537,0.00010549875,0.000011350795,0.00027360138,0.00007104001,0.9640198,0.0040923725,0.0020975005,0.00040402717,0.0001925706],"about_ca_topic_score_codex":0.00008216676,"about_ca_topic_score_gemma":0.000034064433,"teacher_disagreement_score":0.4899569,"about_ca_system_score_codex":0.00013283057,"about_ca_system_score_gemma":0.00011084924,"threshold_uncertainty_score":0.67958856},"labels":[],"label_agreement":null},{"id":"W1981436544","doi":"10.1002/jnm.519","title":"Evaluation of dissipation within an ILGA for computational electromagnetics","year":2004,"lang":"en","type":"article","venue":"International Journal of Numerical Modelling Electronic Networks Devices and Fields","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Communications Research Centre Canada; University of Manitoba; Defence Research and Development Canada","funders":"","keywords":"Dissipation; Dispersion relation; Massively parallel; Isotropy; Computer science; Computer simulation; Computational science; Applied mathematics; Statistical physics; Physics; Computational physics; Mathematics; Parallel computing; Simulation; Optics; Quantum mechanics","score_opus":0.02980035892014708,"score_gpt":0.309066854816817,"score_spread":0.2792664958966699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981436544","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":[0.020513,0.001000944,0.97738445,0.0007571827,0.00021319358,0.000099935205,0.0000017790098,0.000020859536,0.000008675487],"genre_scores_gemma":[0.846407,0.00011595665,0.1532667,0.00009214498,0.00009834749,0.0000047973845,0.000008922894,0.0000053902963,7.609414e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986054,0.000039953324,0.00042319827,0.00016046842,0.00060681737,0.00016422017],"domain_scores_gemma":[0.9982373,0.00011561588,0.00047139393,0.00011394084,0.0010200478,0.00004168382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007481013,0.000093582334,0.00015557224,0.00010925439,0.000044013897,0.000060531267,0.0005589827,0.00008446125,0.0000015223894],"category_scores_gemma":[0.000058232275,0.00008352924,0.000053929063,0.00012785666,0.000033190387,0.0006075433,0.00004938165,0.00023422514,8.665279e-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":[0.000027403974,0.00005647002,0.00002442733,0.0000023350165,0.000051967803,7.907657e-7,0.000109601104,0.89956445,0.0000060536568,0.06465647,0.0000041417447,0.035495885],"study_design_scores_gemma":[0.0004952661,0.00062793854,0.000059675505,0.000022927841,0.000029002178,0.000038527563,0.00001336731,0.7444883,0.000040093313,0.25408703,0.000034232253,0.000063656495],"about_ca_topic_score_codex":0.0000113388805,"about_ca_topic_score_gemma":0.000013808514,"teacher_disagreement_score":0.825894,"about_ca_system_score_codex":0.00013720563,"about_ca_system_score_gemma":0.0002089829,"threshold_uncertainty_score":0.34062237},"labels":[],"label_agreement":null},{"id":"W1984059574","doi":"10.1002/mop.10182","title":"On the implementation of adjacent channel interference suppression for direct digital six‐port receivers","year":2002,"lang":"en","type":"article","venue":"Microwave and Optical Technology Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Interference (communication); Microwave; Port (circuit theory); Channel (broadcasting); Adjacent-channel interference; Electronic engineering; Electrical engineering; Engineering; Computer science; Telecommunications","score_opus":0.019339771018165558,"score_gpt":0.25035890633138524,"score_spread":0.2310191353132197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984059574","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":[0.49715972,0.00010049911,0.46632302,0.035274405,0.00012291834,0.00043586758,0.000040160838,0.00032558633,0.00021781439],"genre_scores_gemma":[0.9856932,0.000051675717,0.013612723,0.00056697894,0.000006303862,0.00004542769,0.0000057425555,0.000006974216,0.000010929514],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907345,0.000008942423,0.00019480163,0.0003638877,0.000092300266,0.00026664633],"domain_scores_gemma":[0.9991739,0.00019837661,0.00009180912,0.0004794914,0.000032675376,0.00002376679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000770355,0.00013845124,0.00016446864,0.00016737347,0.00009275805,0.000041306204,0.00065317424,0.000103894614,0.0000063528096],"category_scores_gemma":[0.00013729636,0.00009820846,0.000040400053,0.00024432442,0.00041413362,0.00025430895,0.0004048725,0.00017636688,0.0000068294976],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003671892,0.00013243378,0.0004758426,0.0000341339,0.00007434476,0.000031123964,0.0004400531,0.000013236549,0.42222992,0.17068566,0.017906768,0.38793978],"study_design_scores_gemma":[0.00067283603,0.0006341988,0.00015877644,0.00007023085,0.000015168858,0.000030381418,0.00080156216,0.0016278818,0.9750513,0.018508459,0.00212819,0.0003010467],"about_ca_topic_score_codex":8.8774306e-7,"about_ca_topic_score_gemma":0.0000015034675,"teacher_disagreement_score":0.55282134,"about_ca_system_score_codex":0.00003302801,"about_ca_system_score_gemma":0.000003922967,"threshold_uncertainty_score":0.40048248},"labels":[],"label_agreement":null},{"id":"W1986339028","doi":"10.5594/j16429","title":"A Distributed Programming Environment Using IT-Based Technology","year":2001,"lang":"en","type":"article","venue":"SMPTE Journal","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Computer science; Metadata; Interoperability; Scalability; Common Object Request Broker Architecture; Standardization; Reconfigurability; Middleware (distributed applications); Modular design; Database; World Wide Web; Operating system; Multimedia","score_opus":0.025974775020870505,"score_gpt":0.2688423328894756,"score_spread":0.24286755786860512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986339028","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01832216,0.00028744756,0.9759541,0.004681688,0.0001621449,0.0001064321,0.0000047527956,0.00045740468,0.000023875118],"genre_scores_gemma":[0.32754633,0.00006742439,0.6721698,0.00013231007,0.000049317674,0.000007696277,0.0000034097554,0.00001166768,0.000012043162],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998586,0.000028538452,0.00029311082,0.00029584105,0.00029591745,0.00050056423],"domain_scores_gemma":[0.99895084,0.000028785747,0.00023394449,0.0006561014,0.00004170103,0.00008861808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024167588,0.00016423891,0.0001710696,0.00033269843,0.00031687718,0.00015199464,0.0012496931,0.00012441415,0.000026662503],"category_scores_gemma":[0.00011424994,0.00014695224,0.000060727907,0.00065640616,0.00016680702,0.00056704576,0.0004141228,0.0005056251,0.000034358756],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025995701,0.00031132897,0.0073357765,0.000010906611,0.000060956852,0.0026733838,0.00008136129,0.01762264,0.011212249,0.007920897,0.00096219993,0.9517823],"study_design_scores_gemma":[0.0023413114,0.0006699522,0.000858289,0.0001996239,0.000047939007,0.009238278,0.0005209984,0.20320071,0.012396141,0.050409418,0.7189498,0.0011675323],"about_ca_topic_score_codex":0.000001827212,"about_ca_topic_score_gemma":0.0000012662565,"teacher_disagreement_score":0.95061475,"about_ca_system_score_codex":0.0002981538,"about_ca_system_score_gemma":0.000077225166,"threshold_uncertainty_score":0.59925383},"labels":[],"label_agreement":null},{"id":"W1987787762","doi":"10.1109/lcomm.2014.2332491","title":"An Efficient Binary Locally Repairable Code for Hadoop Distributed File System","year":2014,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Distributed data store; Overhead (engineering); Code (set theory); Reliability (semiconductor); Locality; Binary number; Distributed computing; File system; Reduction (mathematics); Computational complexity theory; Distributed database; Parallel computing; Operating system; Algorithm; Arithmetic; Mathematics; Set (abstract data type)","score_opus":0.025381863078514245,"score_gpt":0.27268824284696064,"score_spread":0.24730637976844638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987787762","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":[0.0035393464,0.000057875084,0.9851164,0.007372336,0.00019090141,0.0004215692,0.0010448083,0.0021611499,0.00009559252],"genre_scores_gemma":[0.5033386,0.000005271665,0.49495256,0.0007342253,0.000019200425,0.00034665767,0.0005757374,0.000016636155,0.000011130401],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985455,0.00017838198,0.00032557026,0.00043528856,0.00017155166,0.0003436627],"domain_scores_gemma":[0.9916,0.0005786745,0.00018826853,0.0074288268,0.0001282814,0.000075982505],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00043344975,0.00017079197,0.00020358551,0.00013328576,0.0005798156,0.00013508262,0.0057889298,0.0000771541,0.0000028241068],"category_scores_gemma":[0.0001992747,0.00017390605,0.00006937013,0.0004929705,0.0002745336,0.00042600575,0.0006569237,0.0002094809,0.00004830831],"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":[0.000035588197,0.0008196055,0.00010309624,0.00020086573,0.00008871064,0.000013422896,0.00054878934,0.26631653,0.060121592,0.24103218,0.40439168,0.026327953],"study_design_scores_gemma":[0.00026235866,0.00009772264,0.00010850495,0.00006587901,0.000008923807,0.000011653663,0.00007805269,0.91423845,0.0014077927,0.00019612035,0.08328299,0.00024152505],"about_ca_topic_score_codex":0.000020037613,"about_ca_topic_score_gemma":0.000016883328,"teacher_disagreement_score":0.6479219,"about_ca_system_score_codex":0.00020792877,"about_ca_system_score_gemma":0.00003498697,"threshold_uncertainty_score":0.9995902},"labels":[],"label_agreement":null},{"id":"W1988210464","doi":"10.1587/transinf.e93.d.1644","title":"A Buffer Management Issue in Designing SSDs for LFSs","year":2010,"lang":"en","type":"article","venue":"IEICE Transactions on Information and Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Korea Evaluation Institute of Industrial Technology","keywords":"Computer science; Write buffer; Buffer (optical fiber); Key (lock); TRACE (psycholinguistics); Cache; SystemC; Bandwidth (computing); Embedded system; Operating system; Computer network; CPU cache; Cache algorithms; Telecommunications","score_opus":0.013631603583770911,"score_gpt":0.2517852567567775,"score_spread":0.23815365317300657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988210464","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":[0.0013709705,0.000013408778,0.9957118,0.00029069599,0.00060853275,0.000533128,0.000012726578,0.0002597507,0.0011989732],"genre_scores_gemma":[0.8990697,0.000027891381,0.10011013,0.00015757869,0.0000129843875,0.0004020121,0.0000059535173,0.0000045435813,0.00020919416],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932617,0.000011526238,0.0002715385,0.00011854201,0.00012351826,0.00014872002],"domain_scores_gemma":[0.99947286,0.000066949746,0.00007173682,0.00031554594,0.000041514213,0.000031419804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026170115,0.000089941575,0.000099841636,0.0003262465,0.00012944496,0.0001889231,0.0002703352,0.00007287046,0.0000035769326],"category_scores_gemma":[0.00001009743,0.000083596984,0.000019421228,0.00024878795,0.000023506944,0.0020373194,0.0000075524295,0.00015448626,0.00003507096],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003902159,0.00008066731,0.000030806936,0.0004886111,0.000035353867,0.0000039467855,0.0038457543,0.015164974,0.00069686054,0.23016235,0.0008142364,0.7486374],"study_design_scores_gemma":[0.002670297,0.00025842138,0.0004484836,0.00018705236,0.000017907178,0.00007790206,0.0068386607,0.63117033,0.004264043,0.0022520318,0.3511426,0.000672255],"about_ca_topic_score_codex":0.000026567059,"about_ca_topic_score_gemma":0.000022783152,"teacher_disagreement_score":0.89769876,"about_ca_system_score_codex":0.00002877728,"about_ca_system_score_gemma":0.000009607144,"threshold_uncertainty_score":0.3408986},"labels":[],"label_agreement":null},{"id":"W1990084070","doi":"10.5555/2591272.2591287","title":"MixApart: decoupled analytics for shared storage systems","year":2013,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Analytics; Workflow; Database; Workload; Data analysis; Information repository; Scheduling (production processes); Computer data storage; Enterprise data management; Data management; Distributed computing; Operating system; Enterprise information system; Data mining","score_opus":0.02060331253979083,"score_gpt":0.24072101460749992,"score_spread":0.2201177020677091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990084070","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":[0.015782153,0.0042147445,0.9650227,0.0016813239,0.00045543702,0.0016486206,0.00088045775,0.010011438,0.00030316034],"genre_scores_gemma":[0.73662394,0.00037691867,0.2590301,0.00009768586,0.000047485235,0.0021391273,0.00018552267,0.000050035356,0.0014492002],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978543,0.000020413614,0.00040173583,0.000814132,0.0002464317,0.0006630128],"domain_scores_gemma":[0.997275,0.0005341271,0.0002404958,0.0016844806,0.00019924232,0.00006668118],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016883262,0.00036593358,0.00049183855,0.00042652272,0.0003101914,0.0005301917,0.0019991293,0.0003896797,0.00007574032],"category_scores_gemma":[0.0013329157,0.00031931364,0.000083820996,0.0006652013,0.0003152059,0.0015746686,0.0012017435,0.00030929246,0.000093390525],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017083203,0.00016429428,0.00041310533,0.00037857195,0.00016701812,0.000113562804,0.00036039224,0.0013000773,0.0035698905,0.12145227,0.71103996,0.16102375],"study_design_scores_gemma":[0.001594099,0.0010108534,0.0019524188,0.00025615544,0.00005740841,0.0001460581,0.004958495,0.63997537,0.004582212,0.08540969,0.25787216,0.002185079],"about_ca_topic_score_codex":0.00004033809,"about_ca_topic_score_gemma":0.000009943053,"teacher_disagreement_score":0.72084177,"about_ca_system_score_codex":0.00010469252,"about_ca_system_score_gemma":0.00004515326,"threshold_uncertainty_score":0.9999259},"labels":[],"label_agreement":null},{"id":"W1990240141","doi":"","title":"MixApart: decoupled analytics for shared storage systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Analytics; Workflow; Scalability; Database; Enterprise data management; Information repository; Computer data storage; Data analysis; Scheduling (production processes); Enterprise information system; Operating system; Data mining; Engineering","score_opus":0.04216266041229279,"score_gpt":0.2875636270283382,"score_spread":0.24540096661604544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990240141","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":[0.0020458763,0.00069138786,0.99408805,0.00021593859,0.00072566787,0.00035149942,0.00003216621,0.0011385966,0.000710801],"genre_scores_gemma":[0.64669305,0.000010578545,0.35179865,0.00010626218,0.00009404641,0.00009629933,0.000017048395,0.000013158367,0.0011709022],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882555,0.000012975384,0.00021446071,0.00027792674,0.00017567445,0.0004933919],"domain_scores_gemma":[0.9984504,0.0002353096,0.00009640418,0.0010340029,0.000081650825,0.00010223823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028060074,0.00014218097,0.0001946936,0.00011942708,0.00009946486,0.00013224076,0.0011504163,0.000084418396,0.000015238672],"category_scores_gemma":[0.00031350384,0.00012048355,0.000052911022,0.0003281167,0.00003804661,0.0015350601,0.00039117964,0.00007688771,0.00009452968],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008906997,0.00014984753,0.0019573132,0.00009315571,0.00006201347,0.0000074504082,0.00028073342,0.0023647079,0.0012996398,0.9102401,0.07540631,0.008129803],"study_design_scores_gemma":[0.00067102566,0.00012460872,0.0010374174,0.000025801588,0.000022498216,0.0000344027,0.00027202268,0.80489755,0.0032561002,0.0039020244,0.18512285,0.0006337103],"about_ca_topic_score_codex":0.0000076840415,"about_ca_topic_score_gemma":0.0000047267035,"teacher_disagreement_score":0.9063381,"about_ca_system_score_codex":0.00008585085,"about_ca_system_score_gemma":0.000022833925,"threshold_uncertainty_score":0.49131763},"labels":[],"label_agreement":null},{"id":"W1992254899","doi":"10.1109/ipdps.2014.78","title":"DEX: Self-Healing Expanders","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; Ministry of Education, India; United States-Israel Binational Science Foundation; Nanyang Technological University; Queen's University Belfast","keywords":"Expander graph; Overhead (engineering); Computer science; Constant (computer programming); Probabilistic logic; Degree (music); Distributed hash table; Distributed algorithm; Bounded function; Binary logarithm; Hash function; Distributed computing; Algorithm; Theoretical computer science; Mathematics; Discrete mathematics; Peer-to-peer","score_opus":0.0133155090860572,"score_gpt":0.24502596378750702,"score_spread":0.23171045470144983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992254899","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018217353,0.00002557754,0.9847903,0.0007544439,0.00013124506,0.00004226074,1.8184083e-7,0.002954175,0.009480042],"genre_scores_gemma":[0.44743562,0.0000065443855,0.55212194,0.00034888502,0.000013030715,0.0000037051261,4.3179836e-7,0.0000030694077,0.0000667832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999332,0.000014416317,0.000091046335,0.00024819394,0.000115649425,0.00019867584],"domain_scores_gemma":[0.99912024,0.00007331965,0.000030318115,0.00072146504,0.000019772098,0.0000349039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013164313,0.00007196618,0.000075674034,0.00006131982,0.000069942245,0.00005387653,0.00089419895,0.000040769286,0.000006920701],"category_scores_gemma":[0.000084042986,0.000060432543,0.000018038738,0.00019469198,0.000025441826,0.0005172765,0.00038116102,0.00007592403,0.000119152064],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.013686e-7,0.000018744573,0.00021837302,0.000005906408,0.000005435106,0.0000036813299,0.0001451748,0.00024212958,0.00044161698,0.80896294,0.0024003359,0.18755516],"study_design_scores_gemma":[0.0007284119,0.00019383569,0.0006132712,0.000018055416,0.000006073994,0.000042297495,0.00029428795,0.48541707,0.0346613,0.2931453,0.18411058,0.000769494],"about_ca_topic_score_codex":0.000007731485,"about_ca_topic_score_gemma":0.0000053447557,"teacher_disagreement_score":0.51581764,"about_ca_system_score_codex":0.0000256999,"about_ca_system_score_gemma":0.000011258146,"threshold_uncertainty_score":0.24643676},"labels":[],"label_agreement":null},{"id":"W1992331625","doi":"10.1145/1247480.1247523","title":"Storage workload estimation for database management systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Workload; Computer science; Database; Information repository; Computer data storage; Converged storage; Database tuning; Distributed database; Component (thermodynamics); Database design; Distributed computing; Operating system; View","score_opus":0.024048417398515997,"score_gpt":0.28889561917047546,"score_spread":0.2648472017719595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992331625","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035806993,0.00022959507,0.99509734,0.00014352848,0.0004268462,0.0005379797,0.000010355871,0.0011760184,0.0020202412],"genre_scores_gemma":[0.14438727,0.000013753967,0.85476595,0.000071359915,0.000018865725,0.000054687524,0.000018206036,0.0000063133557,0.0006636011],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900496,0.0000062842323,0.00019275202,0.00033653507,0.0001825887,0.00027687004],"domain_scores_gemma":[0.99876565,0.000105999155,0.000072207666,0.0009783921,0.00003705561,0.00004067721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005007078,0.00010211354,0.00009434469,0.00016162454,0.000092003356,0.00009891358,0.00087558024,0.00003869377,0.0000021276767],"category_scores_gemma":[0.00005104098,0.00009126212,0.000021259038,0.00032945618,0.000027473368,0.0009223209,0.00044307683,0.0000545258,0.000048984966],"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":[0.0000043967557,0.000027405038,0.000009828902,0.000058362108,0.00001039175,0.000036189278,0.000022062619,0.0021861591,0.00016944663,0.73995906,0.003985513,0.2535312],"study_design_scores_gemma":[0.0008508296,0.00011160055,0.0001939435,0.00013295797,0.00001543662,0.000026461941,0.00066911033,0.9282465,0.0042230505,0.014922241,0.050071552,0.00053634547],"about_ca_topic_score_codex":0.00000923751,"about_ca_topic_score_gemma":0.0000059681574,"teacher_disagreement_score":0.9260603,"about_ca_system_score_codex":0.00008490565,"about_ca_system_score_gemma":0.0000061747214,"threshold_uncertainty_score":0.37215614},"labels":[],"label_agreement":null},{"id":"W1993356916","doi":"10.1145/367742.367747","title":"Accelerating shared virtual memory via general-purpose network interface support","year":2001,"lang":"en","type":"article","venue":"ACM Transactions on Computer Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Asynchronous communication; Distributed shared memory; Polling; Shared memory; Distributed computing; Interface (matter); Overhead (engineering); Protocol (science); Cache coherence; Network interface; Embedded system; Software; Cache; Computer network; Operating system; Memory management; CPU cache; Overlay; Uniform memory access","score_opus":0.03383171766731335,"score_gpt":0.2650948084156319,"score_spread":0.23126309074831852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993356916","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":[0.0029727842,0.0001582765,0.98733836,0.00047460914,0.006160511,0.0005353935,0.000019804313,0.0021328952,0.00020735251],"genre_scores_gemma":[0.52459633,0.00005244441,0.47233605,0.00046453092,0.00092685793,0.00017960813,0.000020526988,0.000056794197,0.0013668828],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99708056,0.00014948758,0.0006562839,0.0009644344,0.0004462804,0.0007029516],"domain_scores_gemma":[0.9965677,0.00024108274,0.0002170744,0.0026922715,0.00012749592,0.00015436325],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032074066,0.00041963448,0.0004603567,0.00025854656,0.00047842512,0.0005397874,0.0032994847,0.00020360108,0.000045745186],"category_scores_gemma":[0.000014783371,0.00041471492,0.00013919256,0.0009108266,0.0000791887,0.0016312385,0.00023261439,0.0005326237,0.00031270907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022811428,0.0001555852,0.00003074298,0.00002427804,0.0001017661,0.00019344529,0.0004933557,0.5186138,0.000594271,0.0015944409,0.0085190665,0.46965644],"study_design_scores_gemma":[0.0010359441,0.0010317743,0.00010469517,0.00019522829,0.000026429101,0.001094759,0.00012179207,0.94673115,0.0024433695,0.0007787644,0.045367725,0.0010683641],"about_ca_topic_score_codex":0.00006896453,"about_ca_topic_score_gemma":0.000025282901,"teacher_disagreement_score":0.5216235,"about_ca_system_score_codex":0.00018993799,"about_ca_system_score_gemma":0.000058825342,"threshold_uncertainty_score":0.9998305},"labels":[],"label_agreement":null},{"id":"W1995202031","doi":"10.1145/1272996.1273018","title":"Secure file system versioning at the block level","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; File system; Exploit; Software versioning; Operating system; Virtual file system; SSH File Transfer Protocol; Self-certifying File System; Block (permutation group theory); Versioning file system; Computer security; Unix file types; Database; Computer file; Stub file; Software","score_opus":0.023113378760248496,"score_gpt":0.24135612192919656,"score_spread":0.21824274316894807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995202031","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":[0.0043085497,0.00011118738,0.97875714,0.0005763003,0.00025951394,0.00010587409,0.000043051834,0.0013479673,0.014490387],"genre_scores_gemma":[0.76034504,0.0000024078527,0.23341608,0.00025247852,0.00003716027,0.0000070357787,0.000010745497,0.000007757235,0.0059212735],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991736,0.000010052275,0.00011614972,0.0002474595,0.0001985312,0.00025419914],"domain_scores_gemma":[0.99875623,0.00025095552,0.00005425687,0.00087553856,0.000032696647,0.000030295065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002344795,0.000086238426,0.00007270337,0.00004736071,0.00027597288,0.000043813212,0.0012045607,0.000056197427,0.00010005634],"category_scores_gemma":[0.00007678509,0.000053336888,0.00002747258,0.00031788388,0.000059234037,0.0002819453,0.001325637,0.00011919891,0.00039562272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008929398,0.000022769344,0.00016509365,0.000030834708,0.000023656445,0.000223002,0.0005903443,0.0005157404,0.002615999,0.4318712,0.50974375,0.054188665],"study_design_scores_gemma":[0.0008009188,0.00017516372,0.0031099585,0.00017028868,0.0000145218855,0.00080687145,0.0070032845,0.04128656,0.12741287,0.002546581,0.81566626,0.0010067512],"about_ca_topic_score_codex":0.00001897326,"about_ca_topic_score_gemma":0.000056496352,"teacher_disagreement_score":0.7560365,"about_ca_system_score_codex":0.00015146796,"about_ca_system_score_gemma":0.00001373544,"threshold_uncertainty_score":0.5085062},"labels":[],"label_agreement":null},{"id":"W1997068591","doi":"10.1145/1162349.1162352","title":"Distribution sort with randomized cycling","year":2006,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Randomized algorithm; sort; Probabilistic logic; Out-of-core algorithm; Merge sort; Algorithm; Merge (version control); Computation; Task (project management); Parallel computing; Sorting algorithm","score_opus":0.008534024332847286,"score_gpt":0.23201901844973358,"score_spread":0.2234849941168863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997068591","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":[0.08967423,0.00018280378,0.9036688,0.0060651097,0.00021310705,0.00006888396,0.000002291486,0.00004790721,0.000076857286],"genre_scores_gemma":[0.8211565,0.000015261809,0.17865002,0.00005204229,0.00007260143,0.000001219226,6.985801e-7,0.0000029935568,0.00004864263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99931145,0.00004661211,0.00023504914,0.00006966488,0.00023392272,0.000103330174],"domain_scores_gemma":[0.9983364,0.00018387752,0.0004281438,0.00095594424,0.00008272479,0.000012927964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048524892,0.00005968131,0.00018762077,0.00003078084,0.00007474666,0.00005126161,0.0027018772,0.000025027939,9.788057e-7],"category_scores_gemma":[0.0013045886,0.000028371502,0.00008692349,0.000200464,0.000095022064,0.0004702571,0.0006254545,0.00017682048,0.0000020152365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02220543,0.00073329266,0.011323986,0.00006358552,0.0006057521,0.0007990823,0.00055887876,0.068012595,0.027598474,0.6211489,0.137304,0.10964604],"study_design_scores_gemma":[0.053737786,0.00013284017,0.00450615,0.00016878912,0.00008258067,0.0011451477,0.0000465521,0.004340949,0.041048016,0.88502717,0.00948866,0.0002753539],"about_ca_topic_score_codex":0.0000050378594,"about_ca_topic_score_gemma":0.0000020276882,"teacher_disagreement_score":0.73148227,"about_ca_system_score_codex":0.000050883005,"about_ca_system_score_gemma":0.000031594995,"threshold_uncertainty_score":0.5020805},"labels":[],"label_agreement":null},{"id":"W1998799629","doi":"10.1109/dsn.2012.6263919","title":"Practical scrubbing: Getting to the bad sector at the right time","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Microsoft Research","keywords":"Data scrubbing; Computer science; Throughput; Workload; Scrubber; Operating system; Engineering; Waste management","score_opus":0.029418690241669605,"score_gpt":0.29443658888101204,"score_spread":0.26501789863934244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998799629","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004510705,0.0001131378,0.9112273,0.07099176,0.00035201464,0.00027649355,0.0000033491606,0.000854282,0.011670954],"genre_scores_gemma":[0.35009572,0.0000043157693,0.63316935,0.006623812,0.00034710337,0.00005986708,0.000002710799,0.000020184474,0.009676953],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988029,0.000067814966,0.0001345573,0.00025783997,0.00027909043,0.00045780867],"domain_scores_gemma":[0.9978273,0.0006284882,0.00006107045,0.0013766572,0.000032278214,0.00007420141],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00062110095,0.000118412216,0.00009019246,0.000034479115,0.0003995011,0.00012083505,0.001435014,0.00004945337,0.00028970317],"category_scores_gemma":[0.0007314008,0.000053466763,0.000033440887,0.00036118203,0.00009267156,0.0009747326,0.002373845,0.00021543086,0.0039907224],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006402599,0.00006618782,0.00037742988,0.0000029704993,0.000024670264,0.000016142798,0.0008763959,0.00006472465,0.0052689384,0.4227218,0.5389721,0.03160225],"study_design_scores_gemma":[0.00008174477,0.00003946483,0.00069693424,0.0000063653893,0.000006899378,0.00014171118,0.00008515301,0.0070367116,0.030421268,0.0019469805,0.95929253,0.00024423894],"about_ca_topic_score_codex":0.0000074227946,"about_ca_topic_score_gemma":0.000013655285,"teacher_disagreement_score":0.42077482,"about_ca_system_score_codex":0.000087036125,"about_ca_system_score_gemma":0.000020997091,"threshold_uncertainty_score":0.9967848},"labels":[],"label_agreement":null},{"id":"W1999578216","doi":"10.1109/icde.2007.368974","title":"Optimizing Concurrency Through Automated Lock Memory Tuning in DB2","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Lock (firearm); Asynchronous communication; Concurrency; Embedded system; Parallel computing; Distributed computing; Real-time computing; Computer network","score_opus":0.028176012672147144,"score_gpt":0.30300386262164425,"score_spread":0.2748278499494971,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999578216","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008702638,0.00032667065,0.9717683,0.0002382095,0.0002639151,0.00012357142,9.96611e-7,0.0053471504,0.013228514],"genre_scores_gemma":[0.44433564,0.000014250174,0.55539775,0.00015650732,0.000009076629,0.0000034129566,0.0000019465663,0.0000062378767,0.00007518288],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985792,0.000018391713,0.00031130505,0.00042330465,0.00019333424,0.00047447215],"domain_scores_gemma":[0.99894196,0.00015169552,0.00008583311,0.00074239774,0.000040409253,0.000037712427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003541313,0.00015253997,0.0001769009,0.00018836242,0.00007276986,0.000059776656,0.0012091651,0.00009701106,0.00001599567],"category_scores_gemma":[0.00015905211,0.00014266097,0.000025803482,0.00091904914,0.000089170244,0.0015301235,0.00075178256,0.00024253356,0.0000613826],"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":[0.000015679412,0.00022827006,0.0011685869,0.0000560195,0.000029394116,0.00135513,0.0062637688,0.011392348,0.017127663,0.63644713,0.006164578,0.3197514],"study_design_scores_gemma":[0.0017688317,0.00018468998,0.0016232344,0.00018110377,0.000005729326,0.0001305732,0.0028275663,0.8430419,0.11046553,0.031411834,0.007045244,0.0013137839],"about_ca_topic_score_codex":0.00006285469,"about_ca_topic_score_gemma":0.00005142802,"teacher_disagreement_score":0.83164954,"about_ca_system_score_codex":0.00011305917,"about_ca_system_score_gemma":0.000036753427,"threshold_uncertainty_score":0.5817545},"labels":[],"label_agreement":null},{"id":"W2000440777","doi":"10.1145/2815400.2815424","title":"Opportunistic storage maintenance","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Backup; Computer science; Cache; Computer data storage; Storage management; Database; Maintenance engineering; Information repository; Data loss; Reliability engineering; Embedded system; Operating system; Engineering","score_opus":0.060547034070842234,"score_gpt":0.27420206848254064,"score_spread":0.21365503441169842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000440777","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003324088,0.00004405734,0.9709115,0.0014196138,0.00026670287,0.000061191866,0.0000035304395,0.0014717906,0.025489205],"genre_scores_gemma":[0.46042848,0.000008662743,0.53410673,0.00063671544,0.000020854808,0.000012096252,0.0000038956928,0.000007523313,0.004775031],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991702,0.000012727206,0.00011253037,0.00027989168,0.0001899542,0.00023471338],"domain_scores_gemma":[0.99874824,0.000029345685,0.000045375775,0.0009810037,0.00007633046,0.000119673234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017444298,0.00009030935,0.00009662672,0.00006346196,0.00003338619,0.000058251462,0.0012952976,0.0000379014,0.000010298872],"category_scores_gemma":[0.0003322801,0.00007319046,0.000016880422,0.00026369654,0.000076772776,0.00070949923,0.0006456609,0.00009131227,0.00030874152],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011778799,0.0000143947545,0.000028407987,0.0000014677589,0.0000020727782,0.00013821649,0.000044313358,0.00004920546,0.000117942254,0.9175695,0.050121725,0.031911578],"study_design_scores_gemma":[0.0007571525,0.00024693098,0.0002007855,0.000016911172,0.0000038563376,0.00020173787,0.00045151968,0.06303821,0.0018739026,0.41826597,0.51428354,0.0006595073],"about_ca_topic_score_codex":0.000009011399,"about_ca_topic_score_gemma":0.0000038650564,"teacher_disagreement_score":0.49930355,"about_ca_system_score_codex":0.00007419312,"about_ca_system_score_gemma":0.000079225225,"threshold_uncertainty_score":0.39683506},"labels":[],"label_agreement":null},{"id":"W2001122975","doi":"10.5555/1251028.1251037","title":"Second-tier cache management using write hints","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cache; Cache algorithms; Server; Cache invalidation; Operating system; Online transaction processing; Smart Cache; Cache pollution; Cache coloring; Database; Page cache; Computer network; Transaction processing; CPU cache; Database transaction","score_opus":0.02654347480167777,"score_gpt":0.2700641872325278,"score_spread":0.24352071243085002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001122975","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008824881,0.00009811574,0.9626239,0.000595422,0.00011716126,0.00010383363,0.000002225119,0.00085976714,0.026774688],"genre_scores_gemma":[0.16645326,0.000011007255,0.8285246,0.0006395891,0.000025050267,0.000004893335,0.0000011627243,0.0000062915847,0.004334154],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990885,0.000010125832,0.0001425689,0.00034083836,0.00016088822,0.00025704547],"domain_scores_gemma":[0.99898744,0.000014189615,0.00004313522,0.0008996982,0.000019867359,0.000035685734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010039019,0.00010833967,0.000092862436,0.0001234937,0.00007619989,0.0000772515,0.0010563766,0.000043177264,0.00023993848],"category_scores_gemma":[0.0000086612945,0.0000955439,0.000026741396,0.00027515469,0.00004124393,0.0010726599,0.0010358978,0.000095837444,0.00037298893],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015354933,0.000055344375,0.00010798347,0.000015166218,0.000033099015,0.00007181533,0.00009719563,0.0012667086,0.0011083089,0.27837116,0.011640371,0.7072313],"study_design_scores_gemma":[0.00057640293,0.000039599017,0.00067204743,0.000023598646,0.000012181447,0.000048266527,0.00022243829,0.19940822,0.025850866,0.021471411,0.7510036,0.00067135814],"about_ca_topic_score_codex":0.0000039542733,"about_ca_topic_score_gemma":0.00002083234,"teacher_disagreement_score":0.73936325,"about_ca_system_score_codex":0.000110659246,"about_ca_system_score_gemma":0.0000074292593,"threshold_uncertainty_score":0.47941425},"labels":[],"label_agreement":null},{"id":"W2002911697","doi":"10.1088/1742-6596/331/7/072062","title":"Understanding<i>I/O</i>patterns and performance of CMS Data Analysis across T2s worldwide","year":2011,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Aggregate (composite); Computer science; Work (physics); Large Hadron Collider; Grid; Range (aeronautics); Data science; Database; Engineering; Geography; Physics; Particle physics; Nanotechnology","score_opus":0.1794940059190914,"score_gpt":0.29980135393909013,"score_spread":0.12030734801999873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002911697","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":[0.19412991,0.00005219307,0.8053775,0.00010411888,0.00009450671,0.000033564716,0.0000630398,0.00003146176,0.00011372892],"genre_scores_gemma":[0.93945783,0.00040674213,0.060062807,0.000021021317,0.000023395516,6.237033e-7,0.0000054048173,0.00000576171,0.000016434791],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987507,0.00002820355,0.00042428126,0.0002576179,0.000309006,0.00023019416],"domain_scores_gemma":[0.9978349,0.000056702476,0.00072778336,0.0010951214,0.00022582838,0.00005963608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032503981,0.00015548203,0.00042367927,0.0001371853,0.000096208496,0.00009890716,0.0021460885,0.00004506071,0.000008007768],"category_scores_gemma":[0.000055616874,0.0001300121,0.00006135153,0.00068408786,0.00035060456,0.0043570194,0.0012144787,0.00023594503,9.232972e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030280824,0.00030764763,0.27898157,0.00027475163,0.0016731911,0.00011056583,0.014716906,0.00027341684,0.0029445828,0.41569754,0.00024316888,0.28447384],"study_design_scores_gemma":[0.0019024538,0.0032897303,0.17838028,0.00071110635,0.0010123291,0.00025682658,0.015325273,0.029755639,0.42267647,0.34438372,0.00056691584,0.0017392585],"about_ca_topic_score_codex":0.000016756838,"about_ca_topic_score_gemma":0.00007020953,"teacher_disagreement_score":0.7453279,"about_ca_system_score_codex":0.00003440764,"about_ca_system_score_gemma":0.00008447146,"threshold_uncertainty_score":0.53017396},"labels":[],"label_agreement":null},{"id":"W2007164296","doi":"10.1016/j.eswa.2012.07.072","title":"Personal bankruptcy prediction by mining credit card data","year":2012,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Credit card; Bankruptcy; Computer science; Bankruptcy prediction; Support vector machine; Creditor; Data mining; Sequence (biology); Machine learning; Credit score; Artificial intelligence; Classifier (UML); Domain (mathematical analysis); Feature vector; Finance; Business; Payment; Mathematics","score_opus":0.036000725602709296,"score_gpt":0.2815176768203451,"score_spread":0.24551695121763584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007164296","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":[0.00036371654,0.0055198655,0.99050736,0.0004050198,0.00028918308,0.0005803071,0.00049244607,0.001117519,0.00072455616],"genre_scores_gemma":[0.78628355,0.00008629477,0.20838931,0.00011666454,0.0008810322,0.002731197,0.0010274381,0.000036381094,0.00044812806],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984717,0.000029978883,0.00022775702,0.0005491997,0.00035229773,0.0003690761],"domain_scores_gemma":[0.99735045,0.000081139704,0.00014121232,0.0022345681,0.00006593851,0.00012667156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021441105,0.00016760705,0.0001654248,0.000080747384,0.00027946348,0.000111514855,0.0017448837,0.000085174775,0.000003755518],"category_scores_gemma":[0.000029977933,0.00014141756,0.000015679014,0.00044236003,0.00009386635,0.0019208157,0.0005436163,0.0001231294,0.00006770378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010910584,0.00036917624,0.0054067085,0.00006686486,0.00014389768,0.0000038505,0.0052522155,0.00009712267,0.006933566,0.058483098,0.87441486,0.048817743],"study_design_scores_gemma":[0.00019558612,0.000036954578,0.00018758887,0.00003140334,0.000008546567,0.0001036744,0.0016314705,0.025414899,0.00035786396,0.000025904568,0.9717482,0.0002579467],"about_ca_topic_score_codex":0.00007761985,"about_ca_topic_score_gemma":0.0000027082763,"teacher_disagreement_score":0.78591985,"about_ca_system_score_codex":0.0001016293,"about_ca_system_score_gemma":0.000044229,"threshold_uncertainty_score":0.5766841},"labels":[],"label_agreement":null},{"id":"W2013125727","doi":"10.1002/mds.1199","title":"Methods for digital video recording, storage, and communication of movement disorders","year":2001,"lang":"en","type":"review","venue":"Movement Disorders","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre","funders":"","keywords":"Digitization; Computer science; Sophistication; Multimedia; Video recording; Digital video; Movement (music); The Internet; Telecommunications; World Wide Web","score_opus":0.03987400649928964,"score_gpt":0.3686132440265623,"score_spread":0.3287392375272727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013125727","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.802238e-7,0.49894246,0.4987891,0.00033651164,0.00011878915,0.0012573296,0.000076164455,0.0001756466,0.0003035091],"genre_scores_gemma":[0.0000023704758,0.74104017,0.25767666,0.00017500648,0.000007684198,0.0006583752,0.00016617413,0.00004649334,0.0002270727],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972168,0.00016009399,0.0009629298,0.0008950795,0.0002739122,0.000491157],"domain_scores_gemma":[0.9958628,0.00073631364,0.0009814074,0.0022787882,0.00006420586,0.000076502656],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006614138,0.00059806457,0.0013096114,0.00043580527,0.00019372268,0.00019753454,0.0024699646,0.000250972,0.000008520257],"category_scores_gemma":[0.0003536523,0.0005581389,0.00036192077,0.000765377,0.00026983587,0.0009783565,0.001927334,0.00031163174,0.0000029972682],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026751025,0.00011955324,0.000010122874,0.0018732363,0.0001251839,2.1543525e-7,0.000060875413,0.000014397726,5.6007707e-7,0.016298532,0.0022052482,0.9792894],"study_design_scores_gemma":[0.00028657197,0.00015967095,0.0000023518824,0.0010132203,0.00008529324,1.2541832e-7,0.00011691864,0.00063822063,0.0000027496053,0.2809013,0.71634746,0.00044612965],"about_ca_topic_score_codex":0.00007786218,"about_ca_topic_score_gemma":0.00008847858,"teacher_disagreement_score":0.9788433,"about_ca_system_score_codex":0.00024035212,"about_ca_system_score_gemma":0.00008224898,"threshold_uncertainty_score":0.999687},"labels":[],"label_agreement":null},{"id":"W2016019951","doi":"10.1109/hoti.2007.12","title":"Assessing the Ability of Computation/Communication Overlap and Communication Progress in Modern Interconnects","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Myrinet; InfiniBand; Computer science; Ethernet; Latency (audio); Implementation; Computation; Computer network; Computer architecture; Benchmark (surveying); Distributed computing; Low latency (capital markets); Telecommunications; Message passing; Software engineering","score_opus":0.03324145928726949,"score_gpt":0.35115443437687877,"score_spread":0.31791297508960925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016019951","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":[0.37972656,0.0007054222,0.6182032,0.0007954603,0.0000098272785,0.00012967351,3.0220653e-7,0.00010597848,0.00032355147],"genre_scores_gemma":[0.69851804,0.000024872132,0.30141336,0.000031415704,8.3176474e-7,0.000005635283,0.0000028346954,0.0000022856964,7.3119804e-7],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999187,0.0001119527,0.0002843764,0.00017364684,0.00012508013,0.000117928044],"domain_scores_gemma":[0.9978598,0.00070146204,0.00016383413,0.0011747696,0.00008622448,0.000013916138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011875373,0.00007106204,0.000105520354,0.000092234324,0.000093209834,0.0000994362,0.0010678387,0.000047711153,4.3727005e-7],"category_scores_gemma":[0.00015097244,0.000053395324,0.000012948065,0.0003420778,0.00035369082,0.0014183131,0.000981004,0.00017022119,4.1623198e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036715535,0.00008718084,0.028283982,0.000020284328,0.000004746898,6.8964306e-7,0.0020053452,0.00026126078,0.0007173658,0.11722507,0.000010541396,0.8513799],"study_design_scores_gemma":[0.00033959048,0.000034621087,0.41447082,0.000091206784,0.0000027950507,0.000008940942,0.003324393,0.34558475,0.0039000462,0.23206012,0.000029926478,0.00015277394],"about_ca_topic_score_codex":0.00004003035,"about_ca_topic_score_gemma":0.00011941816,"teacher_disagreement_score":0.8512271,"about_ca_system_score_codex":0.00005530414,"about_ca_system_score_gemma":0.000017142162,"threshold_uncertainty_score":0.2177398},"labels":[],"label_agreement":null},{"id":"W2016265567","doi":"10.1002/cpe.1154","title":"Towards building a conflict‐free mobile distributed file system","year":2007,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Operating system; Cache; Self-certifying File System; File system fragmentation; Computer network; File system; Mobile database; Virtual file system; File server; Mobile computing; Distributed File System; Network File System; Distributed computing; Device file; Computer file; Mobile station; SSH File Transfer Protocol; Base station","score_opus":0.022824646860885416,"score_gpt":0.3300688373834963,"score_spread":0.30724419052261087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016265567","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":[0.024117108,0.0018760826,0.9722486,0.00017439612,0.00026808132,0.00019527387,0.00010151632,0.00048443998,0.00053449214],"genre_scores_gemma":[0.90696526,0.00012356987,0.09263831,0.00014320224,0.000024853707,0.0000610924,0.00003312945,0.000004916961,0.0000056767904],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99866074,0.000042912194,0.00029178086,0.00047812375,0.00022313246,0.00030329192],"domain_scores_gemma":[0.9984801,0.0006501595,0.0002235713,0.00037723433,0.00016333358,0.00010562836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003715136,0.0001587125,0.00017337393,0.000086636195,0.00032902273,0.00022645849,0.000494254,0.00007528172,0.000007830768],"category_scores_gemma":[0.0008139586,0.00015377357,0.000018002127,0.0004157657,0.00016832366,0.0023623921,0.0006108211,0.00017465874,0.000005069343],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003540912,0.00009273381,0.00008537757,0.00008995389,0.000019907466,0.00015665864,0.012304077,0.00011367299,0.00054984406,0.34451964,0.0018929945,0.64013976],"study_design_scores_gemma":[0.003379162,0.001258613,0.00291565,0.0004842405,0.000065380795,0.0022214768,0.119688265,0.3020712,0.009656941,0.010159414,0.54607004,0.0020295675],"about_ca_topic_score_codex":0.000023401852,"about_ca_topic_score_gemma":0.0000012940029,"teacher_disagreement_score":0.88284814,"about_ca_system_score_codex":0.000042446016,"about_ca_system_score_gemma":0.000041008458,"threshold_uncertainty_score":0.6270704},"labels":[],"label_agreement":null},{"id":"W2017139832","doi":"10.1145/944747.944754","title":"A study of iSCSI extensions for RDMA (iSER)","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hewlett-Packard (Canada)","funders":"","keywords":"iSCSI; Remote direct memory access; Computer science; Computer network; Internet protocol suite; Operating system; Protocol (science); SCSI; Embedded system; Fibre Channel; Computer data storage; The Internet","score_opus":0.04617744445200687,"score_gpt":0.303996622127321,"score_spread":0.2578191776753141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017139832","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":[0.060263067,0.00003590599,0.93741053,0.000120347366,0.00009741737,0.00040148612,0.0000026449552,0.00034848784,0.0013200965],"genre_scores_gemma":[0.6209777,0.0000017688819,0.37871185,0.000045483255,0.0000018847253,0.00003563156,2.7987048e-7,0.0000032278078,0.00022216258],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99932307,0.000016007452,0.00014872002,0.00025344876,0.00010909649,0.00014966147],"domain_scores_gemma":[0.9988237,0.00011213466,0.000053751395,0.00090612884,0.00008191407,0.00002234746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011611205,0.00007160313,0.000123428,0.00007670266,0.000059456837,0.000015002664,0.00063590135,0.000027475919,0.0000061236874],"category_scores_gemma":[0.00036664947,0.000056694782,0.000025041885,0.0002926888,0.000030184825,0.00030267716,0.00022329192,0.000042919073,0.0000075805647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003709958,0.0006241955,0.0004200434,0.000006982661,0.000018064784,0.000014242528,0.000557521,0.00015357525,0.0022971563,0.9711555,0.0048351795,0.01991381],"study_design_scores_gemma":[0.00873805,0.00807513,0.0058455993,0.000055137058,0.000074899945,0.00013137405,0.027062628,0.018939978,0.21108983,0.6114792,0.10668135,0.0018268006],"about_ca_topic_score_codex":0.000005167638,"about_ca_topic_score_gemma":0.000016712174,"teacher_disagreement_score":0.56071466,"about_ca_system_score_codex":0.00001066609,"about_ca_system_score_gemma":0.000020028168,"threshold_uncertainty_score":0.23119462},"labels":[],"label_agreement":null},{"id":"W2018790444","doi":"10.1145/1111609.1111611","title":"Scalable and fault-tolerant support for variable bit-rate data in the exedra streaming server","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scalability; Variable bitrate; Quality of service; Server; Computer network; Fault tolerance; Reservation; Data striping; Distributed computing; Data center; Bandwidth (computing); Operating system","score_opus":0.037220397397639556,"score_gpt":0.2858605521830322,"score_spread":0.24864015478539264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018790444","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":[0.011682869,0.00009995129,0.98458296,0.002418549,0.00013931413,0.00041100036,0.0002695578,0.00027257344,0.00012320722],"genre_scores_gemma":[0.58165854,0.00007618151,0.41703585,0.0006621689,0.000031327785,0.00009714227,0.000051612948,0.000019007459,0.00036819943],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998463,0.000057593265,0.00025707026,0.0006431554,0.00020534704,0.00037383323],"domain_scores_gemma":[0.99621373,0.00046082586,0.0000702772,0.0031754225,0.000036198206,0.000043557375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073780003,0.00018947345,0.0001935456,0.0001736047,0.00029665724,0.00018134824,0.0028306958,0.000097950695,0.000023090814],"category_scores_gemma":[0.000097206146,0.000150602,0.000027885799,0.0005705352,0.000079901474,0.0022314496,0.00012627793,0.00030218024,0.000019689907],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012552622,0.0012281652,0.0001389157,0.00017205862,0.000119261415,0.00013101991,0.0030047006,0.06489815,0.0041132127,0.026579777,0.0047488105,0.8947404],"study_design_scores_gemma":[0.004291991,0.000745974,0.0016431075,0.00017475315,0.00011241141,0.00022850606,0.0018571544,0.49443918,0.0075734854,0.023129743,0.46427152,0.00153218],"about_ca_topic_score_codex":0.00007091475,"about_ca_topic_score_gemma":0.00020914547,"teacher_disagreement_score":0.8932082,"about_ca_system_score_codex":0.00006826527,"about_ca_system_score_gemma":0.00006083775,"threshold_uncertainty_score":0.6141371},"labels":[],"label_agreement":null},{"id":"W2019388894","doi":"10.1143/jjap.40.1661","title":"25 Gbyte Read-Only Memory Disk by Injection-Compression Molding Process","year":2001,"lang":"en","type":"article","venue":"Japanese Journal of Applied Physics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Replica; Jitter; Materials science; Residual; Equalizer; Compression molding; Optical disc; Molding (decorative); Process (computing); Optics; Computer science; Composite material; Physics; Mold; Telecommunications; Algorithm","score_opus":0.011511296566206792,"score_gpt":0.2591294070097732,"score_spread":0.24761811044356644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019388894","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":[0.7616766,0.000052705574,0.23589948,0.000118145974,0.00015372223,0.0001230941,0.000001941276,0.00021038234,0.0017639163],"genre_scores_gemma":[0.9841473,0.000037123176,0.015478169,0.00011683419,0.00016077043,0.000009095892,0.0000024258604,0.0000168881,0.000031411393],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99843574,0.000019085423,0.00042299333,0.000289444,0.00052760163,0.00030513783],"domain_scores_gemma":[0.9984888,0.00011037455,0.0005690807,0.0005554746,0.00017403628,0.00010226356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023114638,0.00020522451,0.00030299794,0.00010668422,0.00019945554,0.00009483653,0.0013567521,0.000073231786,0.000008814978],"category_scores_gemma":[0.000040076564,0.00016560224,0.00007285866,0.00081519666,0.00009124398,0.0015878874,0.00026417116,0.00043204255,0.000014604279],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025839658,0.00063984696,0.00063495623,0.00006282239,0.000089900874,0.00011504159,0.0062078633,0.050958183,0.29714897,0.01926926,0.0019824337,0.6226323],"study_design_scores_gemma":[0.0049179527,0.0010061946,0.0013315285,0.000363085,0.00009589813,0.0026249602,0.010137805,0.0678101,0.51340806,0.38979527,0.0064152307,0.0020939],"about_ca_topic_score_codex":0.000004305707,"about_ca_topic_score_gemma":5.801234e-7,"teacher_disagreement_score":0.6205384,"about_ca_system_score_codex":0.00008448036,"about_ca_system_score_gemma":0.000056874378,"threshold_uncertainty_score":0.6753063},"labels":[],"label_agreement":null},{"id":"W2024499203","doi":"10.1145/2656045.2656049","title":"Building high-performance smartphones via non-volatile memory","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ministry of Science and Technology of the People's Republic of China; Ministry of Education of the People's Republic of China; Chongqing Science and Technology Commission; National Natural Science Foundation of China","keywords":"Computer science; NAND gate; Embedded system; Non-volatile memory; Mobile device; Pace; Memory management; Factor (programming language); Flash memory; Operating system; Computer hardware; Semiconductor memory; Logic gate","score_opus":0.007075853948216137,"score_gpt":0.2183643512071312,"score_spread":0.21128849725891508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024499203","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":[0.1407223,0.000016161195,0.85315377,0.000255228,0.0004328092,0.000079601705,6.9304804e-7,0.0011690032,0.004170441],"genre_scores_gemma":[0.55737275,0.0000039557244,0.4420382,0.00022712651,0.000035029894,0.0000060880484,9.423516e-7,0.0000067483943,0.00030914563],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988348,0.000015255452,0.00018785712,0.00042026088,0.00020694677,0.00033486975],"domain_scores_gemma":[0.99852276,0.00009599826,0.000078823236,0.0012089924,0.000043161104,0.000050271672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020206007,0.00016002283,0.00017331634,0.00013233755,0.00013235463,0.000071214396,0.0015045991,0.00007346723,0.000025221972],"category_scores_gemma":[0.00006466883,0.0001356026,0.000024486804,0.000398853,0.00008017051,0.0013590107,0.0008180175,0.00015046982,0.00031832184],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000047854164,0.000039449253,0.00051558187,0.00003240078,0.000011987425,0.0000073965302,0.0000840145,0.0019922287,0.034701712,0.1669562,0.0042132917,0.79144096],"study_design_scores_gemma":[0.00038581606,0.00016383355,0.0040927664,0.000026241596,0.000003749476,0.000024270355,0.00001167252,0.624111,0.32449225,0.03420697,0.011987107,0.00049430045],"about_ca_topic_score_codex":0.000040547377,"about_ca_topic_score_gemma":0.000007907259,"teacher_disagreement_score":0.79094666,"about_ca_system_score_codex":0.00003918795,"about_ca_system_score_gemma":0.000022873437,"threshold_uncertainty_score":0.55297136},"labels":[],"label_agreement":null},{"id":"W2026501437","doi":"10.1109/msst.2014.6855534","title":"Analytical modeling of garbage collection algorithms in hotness-aware flash-based solid state drives","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Garbage collection; Workload; Computer science; Flash (photography); Algorithm; Data collection; Field (mathematics); Ordinary differential equation; Variety (cybernetics); State (computer science); Garbage; Simulation; Database; Differential equation; Artificial intelligence; Operating system; Mathematics; Statistics; Programming language","score_opus":0.020798285093060226,"score_gpt":0.28074152000731917,"score_spread":0.25994323491425897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026501437","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":[0.021984989,0.000010053903,0.9764321,0.0002082233,0.000075367774,0.00011018734,0.000004153607,0.00041233763,0.0007625754],"genre_scores_gemma":[0.7597894,0.000004809658,0.2400462,0.0000663424,0.0000057313755,0.000009437024,0.0000035437783,0.000006744967,0.00006779427],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873096,0.00004588612,0.0003174095,0.0003982912,0.00023668304,0.00027077226],"domain_scores_gemma":[0.9990174,0.00011348582,0.00007507724,0.00065836083,0.0000935366,0.000042131906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002450557,0.00013406415,0.00024674684,0.00028728097,0.000056199897,0.000042843574,0.0006844586,0.00007226637,0.000005622283],"category_scores_gemma":[0.000114357084,0.00012128121,0.000040661005,0.0007272596,0.000119173834,0.00052055443,0.00026157143,0.00015448357,0.000009341162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022428228,0.00016658576,0.00063317316,0.000044232518,0.000014746357,0.000020222067,0.0002434044,0.896025,0.0010588899,0.0716106,0.00016328122,0.029997425],"study_design_scores_gemma":[0.0003378532,0.0000882133,0.000067140376,0.000021452499,0.0000020586062,0.0000014650777,0.000034530876,0.9733519,0.010385574,0.01550282,0.000066967026,0.00014001653],"about_ca_topic_score_codex":0.00009511721,"about_ca_topic_score_gemma":0.00020784272,"teacher_disagreement_score":0.7378044,"about_ca_system_score_codex":0.00007185851,"about_ca_system_score_gemma":0.00005029218,"threshold_uncertainty_score":0.49457043},"labels":[],"label_agreement":null},{"id":"W2029622211","doi":"10.1145/1176617.1176666","title":"An evaluation of secialized Java bytecodes","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Java; Computer science; strictfp; Java applet; Operating system; Profiling (computer programming); Java concurrency; Real time Java; Java annotation; Programming language","score_opus":0.03331486795191202,"score_gpt":0.31757471824432665,"score_spread":0.28425985029241463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029622211","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":[0.09968076,0.000085584245,0.89399093,0.00008835757,0.00009536342,0.00011148989,0.0000020732111,0.00051005004,0.0054354193],"genre_scores_gemma":[0.70117706,0.0000019161178,0.29874465,0.000014445237,0.000012375443,0.000004564818,0.000006190714,0.0000021530507,0.000036650137],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99918514,0.00004322079,0.0001449073,0.00019122794,0.00033607,0.00009945128],"domain_scores_gemma":[0.9989878,0.000024199548,0.00006835564,0.000699597,0.00020912444,0.000010904061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040860497,0.00005635697,0.00008160626,0.00008146284,0.0000290387,0.00002606696,0.0006692348,0.000038187925,0.00004052635],"category_scores_gemma":[0.0000837559,0.000048680096,0.000013741449,0.00031591975,0.00004589404,0.000772648,0.00011310671,0.00003117587,0.000012638385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004372025,0.00011380213,0.00043955972,0.0000044174403,0.0000044728667,0.0000015056229,0.000054692264,0.00461404,0.054018952,0.6295134,0.0022700683,0.3089607],"study_design_scores_gemma":[0.0005714808,0.0001189175,0.0035484058,0.000005016249,0.000009336701,0.0000037940586,0.00005054072,0.3367023,0.24954064,0.40751487,0.0017598238,0.00017487408],"about_ca_topic_score_codex":0.00008224419,"about_ca_topic_score_gemma":0.00006209915,"teacher_disagreement_score":0.6014963,"about_ca_system_score_codex":0.000031697557,"about_ca_system_score_gemma":0.000041928284,"threshold_uncertainty_score":0.19851168},"labels":[],"label_agreement":null},{"id":"W2030524750","doi":"10.1108/00242530610689329","title":"Integrating digital libraries and virtual learning environments","year":2006,"lang":"en","type":"article","venue":"Library Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Digital library; Metadata; World Wide Web; Virtual learning environment; Multimedia; Digital content","score_opus":0.00783938370383463,"score_gpt":0.1994095692742482,"score_spread":0.19157018557041355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030524750","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003828668,0.3578643,0.614979,0.003932255,0.00013804629,0.00049957674,0.000022519413,0.0027275614,0.016008064],"genre_scores_gemma":[0.22727302,0.13017172,0.6233598,0.0042621526,0.00022442418,0.00011123213,0.00040597972,0.000111710026,0.014079995],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99915683,0.000030087145,0.0002165484,0.00031128383,0.00011216178,0.00017307587],"domain_scores_gemma":[0.9994162,0.00008523488,0.00009951456,0.00036601856,0.0000013570071,0.000031704854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003706081,0.00014047438,0.00019845522,0.00003923559,0.00008987332,0.00036477894,0.00061012106,0.000036123143,0.000019952078],"category_scores_gemma":[0.000069997994,0.00011485148,0.00003167607,0.00023454473,0.00010658174,0.008577,0.0011325586,0.00018902055,0.000054156328],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.08781e-7,0.000017121787,0.0023778814,0.00015087372,0.0000048142115,0.000037234277,0.00001854111,0.0000066806533,0.00007183975,0.3577278,0.004653046,0.6349335],"study_design_scores_gemma":[0.00009958376,0.00009838405,0.0006285205,0.0010185473,0.000005593521,0.000050533818,0.000025175743,0.00059534685,0.0006625891,0.026305832,0.97020525,0.00030464848],"about_ca_topic_score_codex":4.9738037e-7,"about_ca_topic_score_gemma":3.5405538e-8,"teacher_disagreement_score":0.9655522,"about_ca_system_score_codex":0.0000049493538,"about_ca_system_score_gemma":0.000011992843,"threshold_uncertainty_score":0.6218118},"labels":[],"label_agreement":null},{"id":"W2034699325","doi":"10.1145/1037957.1037960","title":"Simulating the dynamics of auroral phenomena","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Waterloo","funders":"","keywords":"Geophysics; Computer science; Physics; Ray tracing (physics); Computer graphics; Statistical physics; Computational physics; Computer graphics (images); Optics","score_opus":0.022343931857622183,"score_gpt":0.2661314956976375,"score_spread":0.24378756384001532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034699325","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":[0.005638048,0.000048645295,0.9878976,0.0056841783,0.00010367019,0.000106794105,0.000023334198,0.00034811872,0.00014961696],"genre_scores_gemma":[0.84541786,0.00004714094,0.15420713,0.00026274903,0.000012343741,0.000009458788,0.0000020751213,0.000008011057,0.000033262026],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912924,0.000026111995,0.00020877265,0.0002256783,0.00021818338,0.00019199001],"domain_scores_gemma":[0.9979832,0.00032139383,0.0000925663,0.0015222287,0.000055284083,0.00002533448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014142464,0.00011517973,0.00011200798,0.00017007343,0.00022972652,0.000030067296,0.0016730804,0.00006447848,0.0000064519577],"category_scores_gemma":[0.000059666236,0.0000887006,0.00007635021,0.00086523924,0.00018477764,0.00046958696,0.00004072458,0.00032394752,0.000007642048],"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":[0.0000059050744,0.00012128832,0.000052927655,0.000007932275,0.000030561223,0.0000016036105,0.00035539392,0.07798662,0.00010154186,0.2699857,0.000023607938,0.6513269],"study_design_scores_gemma":[0.00037194602,0.00018350854,0.0002982577,0.000022652088,0.000022588194,0.00001017789,0.00030318028,0.89210093,0.002879103,0.100341156,0.003182441,0.00028403205],"about_ca_topic_score_codex":0.000009884979,"about_ca_topic_score_gemma":0.00013761142,"teacher_disagreement_score":0.8397798,"about_ca_system_score_codex":0.000046912424,"about_ca_system_score_gemma":0.000021187994,"threshold_uncertainty_score":0.36171058},"labels":[],"label_agreement":null},{"id":"W2038534629","doi":"10.1147/rd.474.0373","title":"Fifty years of IBM innovation with information storage on magnetic tape","year":2003,"lang":"en","type":"article","venue":"IBM Journal of Research and Development","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"International Development Research Centre","keywords":"IBM; Magnetic tape; Calculator; Corporation; Digital storage; Operating system; Computer data storage; Information storage; Computer science; Engineering; Tape recorder; Computer hardware; Electrical engineering; Database; Business; Materials science; Nanotechnology; Finance","score_opus":0.03959904124507397,"score_gpt":0.30774600503218896,"score_spread":0.268146963787115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038534629","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":[0.6147704,0.00027531647,0.38381982,0.00027251325,0.000086070395,0.00015718563,0.0000013413872,0.00002505889,0.00059227087],"genre_scores_gemma":[0.71980137,0.00010280319,0.28000045,0.000039737526,0.000005259783,0.0000034154975,0.0000014039169,0.0000028325937,0.00004272819],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986512,0.000042269745,0.0003179552,0.00007996652,0.0007289204,0.00017967062],"domain_scores_gemma":[0.9988405,0.000102455415,0.0001902022,0.00018186212,0.00063990016,0.00004505534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001129361,0.000059143098,0.00010719651,0.00075317343,0.000066226334,0.00006377196,0.00033105112,0.000034199744,0.000006167323],"category_scores_gemma":[0.00044364936,0.000045786954,0.0000061344003,0.0009058753,0.00010335357,0.0008998602,0.00010256964,0.00025877936,0.000007149723],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016875632,0.00013300379,0.0014752988,0.000075165524,0.000030767078,0.00011047777,0.0020459762,0.00028461163,0.0006703605,0.06733558,0.0026976091,0.9249724],"study_design_scores_gemma":[0.008156133,0.0165026,0.16223776,0.0013258517,0.00000778166,0.0010311386,0.0045167664,0.00067506055,0.15852764,0.048837855,0.5971157,0.0010657064],"about_ca_topic_score_codex":0.0000011439231,"about_ca_topic_score_gemma":0.0000010505166,"teacher_disagreement_score":0.9239067,"about_ca_system_score_codex":0.00008304636,"about_ca_system_score_gemma":0.00038085855,"threshold_uncertainty_score":0.18671377},"labels":[],"label_agreement":null},{"id":"W2040412318","doi":"10.1109/issst.2011.5936911","title":"Electrical cost savings and clean energy usage potential for HPC workloads","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Electricity; Renewable energy; Grid; Computer science; Adaptation (eye); Wind power; Environmental science; Electricity generation; Environmental economics; Power (physics); Electrical engineering; Engineering","score_opus":0.021890153210332598,"score_gpt":0.23567797562083317,"score_spread":0.21378782241050057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040412318","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":[0.0028265386,0.00007922455,0.99456245,0.0001606505,0.00009918092,0.00011632259,0.0000025027448,0.00061719364,0.0015359516],"genre_scores_gemma":[0.57632065,0.00004377935,0.42289588,0.00029864872,0.000022314429,0.000030755466,0.0000020217383,0.000007994884,0.0003779591],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990103,0.000011655462,0.00013713336,0.00040179436,0.00010948467,0.0003296337],"domain_scores_gemma":[0.99930304,0.000059846017,0.000050539733,0.00048398855,0.000036513902,0.00006604559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008714914,0.0001185609,0.00012572769,0.00010112083,0.00010305619,0.00008404508,0.00080330623,0.000086517095,0.000015177185],"category_scores_gemma":[0.00007775906,0.000102082144,0.00003245368,0.0002544128,0.000094296454,0.0007306169,0.000526013,0.000085075786,0.000008140459],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000091138245,0.000028480255,0.000062267216,0.0000016931845,0.0000058487367,0.000014215663,0.00004471523,0.0000015055166,0.00090323447,0.26580665,0.0024104922,0.73071176],"study_design_scores_gemma":[0.0025845082,0.0014299268,0.0071475985,0.000034581077,0.00004375066,0.00029396926,0.00022970058,0.15374587,0.27615097,0.4635563,0.09297538,0.0018074632],"about_ca_topic_score_codex":0.000040815798,"about_ca_topic_score_gemma":0.000023920717,"teacher_disagreement_score":0.7289043,"about_ca_system_score_codex":0.000026779453,"about_ca_system_score_gemma":0.000013436522,"threshold_uncertainty_score":0.4162789},"labels":[],"label_agreement":null},{"id":"W2041093720","doi":"10.1145/1296907.1296914","title":"Path","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Demand paging; Instruction prefetch; Page fault; Virtual memory; Memory management; Extended memory; Overhead (engineering); Memory map; Operating system; Distributed computing; Shared memory; Overlay","score_opus":0.014945818197084813,"score_gpt":0.26086841360072105,"score_spread":0.24592259540363623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041093720","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012889543,0.000030065734,0.9723235,0.00026746085,0.000084214465,0.000021961652,2.0470121e-7,0.0011510947,0.024832563],"genre_scores_gemma":[0.3527123,0.000002300272,0.6467305,0.0002201329,0.000007051183,5.306157e-7,2.3131878e-7,0.0000012636444,0.00032571255],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996042,0.0000014908653,0.000056075114,0.00012607523,0.00007453035,0.00013762453],"domain_scores_gemma":[0.99945855,0.00003090276,0.0000135451555,0.00046524807,0.000012169398,0.000019606161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012321302,0.000034201737,0.000031185886,0.000041839827,0.000024604766,0.000017544218,0.0006294281,0.000020995827,0.000008780343],"category_scores_gemma":[0.000038744587,0.000027142232,0.000008724515,0.00019326461,0.00002127222,0.00034071426,0.00028709028,0.000042323965,0.00013792184],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.3024505e-7,0.000005291423,0.00009710762,5.387046e-7,5.504695e-7,0.000025674299,0.000014834935,8.2884014e-7,0.00067500584,0.7878157,0.001698079,0.20966619],"study_design_scores_gemma":[0.00041241827,0.00016214499,0.00954187,0.000009706776,0.0000015307304,0.00009303804,0.00023659963,0.0060517145,0.20114669,0.46490967,0.3168291,0.0006055353],"about_ca_topic_score_codex":0.0000027155031,"about_ca_topic_score_gemma":0.0000039266597,"teacher_disagreement_score":0.35142332,"about_ca_system_score_codex":0.000013377437,"about_ca_system_score_gemma":0.0000047817207,"threshold_uncertainty_score":0.17727524},"labels":[],"label_agreement":null},{"id":"W2046666664","doi":"10.1145/371920.372061","title":"N for the price of 1","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Research Nova Scotia; National Science Foundation","keywords":"Citation; Library science; DEPT; Computer science; Operations research; World Wide Web; Engineering; Medicine","score_opus":0.028994638476327373,"score_gpt":0.2772121038124163,"score_spread":0.2482174653360889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046666664","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034851508,0.000089177716,0.99432355,0.002108509,0.000049306,0.00009120452,8.76153e-7,0.00018410131,0.002804762],"genre_scores_gemma":[0.23141757,0.0000476413,0.7673079,0.00021456252,0.000009304122,0.000021207201,2.5603526e-7,0.000001980721,0.0009796139],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99974716,0.0000017534545,0.00005184299,0.000077817975,0.000048617247,0.00007280857],"domain_scores_gemma":[0.99928534,0.00018016383,0.000025522182,0.00047832716,0.000025533274,0.000005085423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006543036,0.000025045681,0.00003351131,0.00001599565,0.000029299232,0.000008414653,0.0008482649,0.000012063862,0.000005213344],"category_scores_gemma":[0.000093762865,0.000013864522,0.00001378015,0.00016394007,0.00003294747,0.00017478471,0.00019069496,0.000019543626,0.000005008577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014152517,0.000008952038,0.00006450286,0.0000018681476,0.0000032631672,6.357189e-7,0.000029290608,0.00006054154,0.0005747161,0.8418193,0.0045008897,0.15293463],"study_design_scores_gemma":[0.00030631776,0.00013512405,0.0011342815,0.000004783019,0.0000037699892,0.000022439817,0.000196522,0.07449686,0.04017031,0.1844685,0.69891375,0.00014736889],"about_ca_topic_score_codex":0.0000035815374,"about_ca_topic_score_gemma":0.0000023784103,"teacher_disagreement_score":0.6944128,"about_ca_system_score_codex":0.000004679549,"about_ca_system_score_gemma":0.000006368893,"threshold_uncertainty_score":0.15763015},"labels":[],"label_agreement":null},{"id":"W2048276667","doi":"10.1145/2660267.2660333","title":"The UNIX Process Identity Crisis","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Unix; Identity crisis; Process (computing); Computer science; Identity (music); Operating system; Psychology; Social psychology; Art","score_opus":0.011737622227373973,"score_gpt":0.28054203862257954,"score_spread":0.2688044163952056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048276667","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":[0.001838444,0.00004056393,0.9890496,0.0041461177,0.0001393124,0.00004686507,3.447948e-7,0.0008642407,0.003874516],"genre_scores_gemma":[0.9235856,0.000020118754,0.07555556,0.00047953313,0.000018587478,0.00001365995,3.634126e-7,0.0000037677987,0.00032281355],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993556,0.000017867427,0.00008531445,0.00019931144,0.00017502432,0.00016684759],"domain_scores_gemma":[0.99885625,0.00009067686,0.000038121052,0.0009400721,0.000053874115,0.000021022526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024266826,0.000058744918,0.00005242249,0.000026674721,0.00021955752,0.00020081826,0.0022436322,0.000026311489,0.000003552456],"category_scores_gemma":[0.00025819743,0.00003476581,0.000015807302,0.00032998496,0.000064970656,0.0012986832,0.000556954,0.00007937968,0.00011302591],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.1489097e-7,0.0000049305086,0.00005579414,0.0000019619913,0.0000017771885,6.9867724e-7,0.000034031487,0.000020608222,0.00002706478,0.94765997,0.0046228343,0.047569994],"study_design_scores_gemma":[0.000083968465,0.000032982396,0.0003701338,0.0000025306563,0.0000016206739,0.0000058972605,0.00027430808,0.0153167825,0.007266015,0.908074,0.068428256,0.00014349018],"about_ca_topic_score_codex":0.000012371012,"about_ca_topic_score_gemma":0.000054042448,"teacher_disagreement_score":0.92174715,"about_ca_system_score_codex":0.000013459327,"about_ca_system_score_gemma":0.0000108863505,"threshold_uncertainty_score":0.4169264},"labels":[],"label_agreement":null},{"id":"W2048849600","doi":"10.1109/mm.2010.21","title":"Making Address-Correlated Prefetching Practical","year":2010,"lang":"en","type":"article","venue":"IEEE Micro","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Metadata; Computer science; Latency (audio); Bandwidth (computing); Computer architecture; Storage management; Chip; Embedded system; Parallel computing; Operating system; Computer network; Telecommunications","score_opus":0.04634996544834779,"score_gpt":0.3359082008276234,"score_spread":0.2895582353792756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048849600","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":[0.13997413,0.000044025615,0.85348713,0.0011958535,0.0019670816,0.00014294754,0.0000064588226,0.0015020312,0.001680325],"genre_scores_gemma":[0.589044,0.0000030289264,0.41060442,0.00019625433,0.00005490446,0.000007571669,0.0000014724311,0.000010797428,0.00007758056],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99886376,0.000022388123,0.00018206435,0.0004296854,0.00016166599,0.0003404362],"domain_scores_gemma":[0.9985707,0.0001649358,0.00011296101,0.001059241,0.000050024035,0.000042179585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018535148,0.00014189337,0.00012908595,0.00010525238,0.00013645327,0.00016320653,0.0011120527,0.00016279673,0.000020273934],"category_scores_gemma":[0.000368834,0.0001326621,0.000037091562,0.00029222757,0.00010208826,0.0011175196,0.0004599212,0.0008702048,0.00027031312],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006467843,0.000055635566,0.00017596438,0.0000077483555,0.000013701312,0.00019027041,0.00025074516,0.000037114056,0.9231891,0.02947869,0.00589086,0.040703688],"study_design_scores_gemma":[0.00067216676,0.00009044459,0.0007342519,0.00007721853,0.00001864586,0.0010922517,0.00007059117,0.014535781,0.8274594,0.030098127,0.12427296,0.00087817357],"about_ca_topic_score_codex":0.0000065643226,"about_ca_topic_score_gemma":0.000016350814,"teacher_disagreement_score":0.44906983,"about_ca_system_score_codex":0.000028356959,"about_ca_system_score_gemma":0.000052079526,"threshold_uncertainty_score":0.54098034},"labels":[],"label_agreement":null},{"id":"W2051005649","doi":"10.1145/1294046.1294120","title":"Image baby image!","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Scripting language; Process (computing); Operating system; USB; Component (thermodynamics); Task (project management); Embedded system; Computer hardware; Software","score_opus":0.012406985595377945,"score_gpt":0.2715276988288309,"score_spread":0.2591207132334529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051005649","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00088708627,0.000036729278,0.9428189,0.00079768826,0.00013304703,0.000057803674,0.0000011824294,0.0018073017,0.053460274],"genre_scores_gemma":[0.041433834,0.000006098498,0.9575499,0.0003271614,0.00002023936,0.0000020833709,0.0000013422225,0.000005566843,0.00065372384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99910647,0.0000052535834,0.00013412301,0.00029001344,0.00015515783,0.00030898087],"domain_scores_gemma":[0.9988693,0.00007255446,0.0000364138,0.00092634215,0.00004848993,0.000046871377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024631788,0.00009123701,0.00008059534,0.00010388286,0.000060011087,0.00008113042,0.0012535963,0.000043754786,0.00005081275],"category_scores_gemma":[0.00013155045,0.00007699144,0.000025850411,0.00037331274,0.0001037794,0.0013020984,0.0007061569,0.00011237051,0.0006369983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036284098,0.000053493543,0.00016114154,0.000007101774,0.0000068793747,0.00035753482,0.000094131654,0.000001158737,0.07517414,0.5470297,0.0317085,0.34540263],"study_design_scores_gemma":[0.00075869914,0.00018569868,0.005689138,0.000014060551,0.000005114974,0.00018435057,0.0003365505,0.009968571,0.6254172,0.18662648,0.16978666,0.0010274862],"about_ca_topic_score_codex":0.000009553433,"about_ca_topic_score_gemma":0.000010098389,"teacher_disagreement_score":0.5502431,"about_ca_system_score_codex":0.00003566956,"about_ca_system_score_gemma":0.00001234134,"threshold_uncertainty_score":0.81875366},"labels":[],"label_agreement":null},{"id":"W2052678402","doi":"10.1109/infocom.2014.6847953","title":"Cooperative repair with minimum-storage regenerating codes for distributed storage","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Distributed data store; Construct (python library); Bandwidth (computing); Maintenance engineering; Computer data storage; Distributed computing; Computer network; Reliability engineering; Computer hardware; Engineering","score_opus":0.01569603938885384,"score_gpt":0.2511052586258648,"score_spread":0.23540921923701097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052678402","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010906995,0.00008514448,0.9844099,0.00060806476,0.00012469685,0.00044437367,0.000115241266,0.0027423513,0.0005632328],"genre_scores_gemma":[0.40304604,0.000002494744,0.59614176,0.00023770546,0.000047612306,0.00011996057,0.00007644157,0.000016520982,0.00031145898],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982891,0.00006811705,0.00027069027,0.0007229649,0.00022815629,0.00042095286],"domain_scores_gemma":[0.99785525,0.000396178,0.00015027856,0.0012580283,0.000260142,0.000080125385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003643636,0.00026010844,0.00030497028,0.000086077234,0.00034929434,0.00015778014,0.0009898532,0.00009848371,0.0000071010463],"category_scores_gemma":[0.0006615866,0.0001928419,0.00005959545,0.00046217718,0.00017578942,0.0009132397,0.00036703527,0.00015737803,0.0000128715965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046499503,0.00009833041,0.00014560358,0.00004188521,0.00006316901,0.00002545413,0.00030123795,0.015463718,0.0037966152,0.9472023,0.02034741,0.012467732],"study_design_scores_gemma":[0.0014100699,0.0013792223,0.00012542645,0.000064673724,0.000018926028,0.000042752916,0.00036570345,0.9067249,0.051264197,0.0033046908,0.034445,0.00085447135],"about_ca_topic_score_codex":0.000010922244,"about_ca_topic_score_gemma":0.00006879128,"teacher_disagreement_score":0.94389766,"about_ca_system_score_codex":0.00009616085,"about_ca_system_score_gemma":0.00006164114,"threshold_uncertainty_score":0.78638643},"labels":[],"label_agreement":null},{"id":"W2053615160","doi":"10.1007/s10796-007-9045-4","title":"EXEM: Efficient XML data exchange management for mobile applications","year":2007,"lang":"en","type":"article","venue":"Information Systems Frontiers","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; Systems, Applications & Products in Data Processing (Canada)","funders":"","keywords":"Computer science; Lossy compression; Lossless compression; XML; XML database; Metadata; Data exchange; XML framework; Efficient XML Interchange; Database; Data compression; Operating system; Algorithm","score_opus":0.020480859552067347,"score_gpt":0.271055292835289,"score_spread":0.25057443328322165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053615160","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038082642,0.0005619496,0.9913928,0.00005333489,0.0010479775,0.0026598747,0.00019055755,0.0007463415,0.0033091074],"genre_scores_gemma":[0.07572694,0.00007890328,0.9193488,0.00020893532,0.000118708675,0.002994476,0.0010097931,0.00001709735,0.0004963518],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985814,0.000009047621,0.00049703557,0.00026620258,0.00032000986,0.00032628427],"domain_scores_gemma":[0.9974815,0.000038736525,0.00028758164,0.0020154698,0.000113717084,0.00006298411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008887293,0.00013292994,0.00015126096,0.00037382316,0.00018623406,0.00020596257,0.0021651897,0.00007447069,7.1883926e-7],"category_scores_gemma":[0.000021838014,0.00012902822,0.000027838794,0.0004921054,0.00004676405,0.0024895717,0.00076217856,0.000066261324,0.00009644011],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011919492,0.00004166243,0.00003084126,0.00043202235,0.00005229667,0.0000019655322,0.0008255499,0.0074832817,0.000008167029,0.12974913,0.12416937,0.73719376],"study_design_scores_gemma":[0.0002894116,0.000020355003,0.000022515424,0.0000135416,0.0000065169793,0.0000054367206,0.0026887665,0.112092935,0.00006426986,0.00020038502,0.8844434,0.00015245557],"about_ca_topic_score_codex":0.000007791316,"about_ca_topic_score_gemma":0.0000010590576,"teacher_disagreement_score":0.76027405,"about_ca_system_score_codex":0.0001732653,"about_ca_system_score_gemma":0.000017130582,"threshold_uncertainty_score":0.5261618},"labels":[],"label_agreement":null},{"id":"W2054526666","doi":"10.1109/tpds.2014.2366113","title":"Exploiting Pipelined Encoding Process to Boost Erasure-Coded Data Archival","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Center for Scientific Review; National Key Research and Development Program of China; Canadian Psychological Association; National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; National Science Foundation","keywords":"Computer science; Redundancy (engineering); Encoding (memory); Data redundancy; Erasure code; Theoretical computer science; Parallel computing; Algorithm; Decoding methods; Database; Artificial intelligence; Operating system","score_opus":0.04636769643603276,"score_gpt":0.28526109257458027,"score_spread":0.23889339613854751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054526666","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":[0.003902758,0.00005232568,0.9928367,0.00046676875,0.0005036906,0.0004105943,0.00077307515,0.0008985001,0.00015558985],"genre_scores_gemma":[0.9766937,0.000018538125,0.02285448,0.00007787185,0.00005702092,0.0001184475,0.0001152599,0.000016235861,0.000048475402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978017,0.00009918395,0.00043414853,0.00086129946,0.00035653842,0.00044710192],"domain_scores_gemma":[0.9978173,0.00023970012,0.00012756801,0.0015345538,0.000085748616,0.00019516585],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00041873986,0.00026920938,0.00034311457,0.00017368165,0.00040450913,0.00028526175,0.0015636941,0.000086053486,0.0000014359639],"category_scores_gemma":[0.00009504206,0.00024665505,0.000036005116,0.0005033235,0.00006719842,0.0008949879,0.000036953854,0.00028573774,0.00003815592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115869516,0.00024725086,0.000052562227,0.0002256676,0.00008046269,0.000026627838,0.0006896628,0.93550175,0.0054432726,0.0070275734,0.0013753503,0.04921392],"study_design_scores_gemma":[0.0010136442,0.00024413575,0.00007730736,0.00023908545,0.000028778752,0.00010374083,0.000678234,0.9892138,0.0017138211,0.001316346,0.0046719317,0.00069913635],"about_ca_topic_score_codex":0.000057117246,"about_ca_topic_score_gemma":0.000020941538,"teacher_disagreement_score":0.9727909,"about_ca_system_score_codex":0.000046667177,"about_ca_system_score_gemma":0.000040193863,"threshold_uncertainty_score":0.99999857},"labels":[],"label_agreement":null},{"id":"W2054801486","doi":"10.5555/1251028.1251041","title":"A security model for full-text file system search in multi-user environments","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Search engine indexing; Implementation; Permission; File system; Unix file types; Computer file; Index (typography); Operating system; Database; Stub file; Information retrieval; World Wide Web; Programming language","score_opus":0.03595323238126699,"score_gpt":0.2804554281163199,"score_spread":0.2445021957350529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054801486","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004170678,0.000047306294,0.9942825,0.00028443823,0.000028281995,0.00042102142,0.00014798662,0.00043097103,0.00018685509],"genre_scores_gemma":[0.41119537,0.000005825503,0.5868896,0.000061502426,0.0000081254875,0.00013936798,0.000013824934,0.000008156627,0.0016781975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987459,0.00001871791,0.00020281854,0.0004646398,0.00019216616,0.0003757407],"domain_scores_gemma":[0.99901026,0.00008112949,0.000038334136,0.000810026,0.000011965113,0.000048279227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017689522,0.00013053135,0.00014952915,0.000120718556,0.00006571109,0.00004222735,0.001100251,0.000094763,0.000035209574],"category_scores_gemma":[0.00003850495,0.00011739682,0.000035809462,0.00017072711,0.000048235095,0.00079677626,0.0007374873,0.00014376754,0.00017140922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060962862,0.0010783061,0.0002836985,0.00023471127,0.00003939772,0.000050708746,0.003341386,0.46309555,0.007176011,0.38716483,0.032182198,0.10529224],"study_design_scores_gemma":[0.0004589428,0.000025117683,0.000037899666,0.0000139793065,8.028998e-7,0.0000051313473,0.00014693101,0.99094784,0.0021577799,0.00032721035,0.00573439,0.00014396412],"about_ca_topic_score_codex":0.000014833529,"about_ca_topic_score_gemma":0.00013062239,"teacher_disagreement_score":0.5278523,"about_ca_system_score_codex":0.00024384956,"about_ca_system_score_gemma":0.000024389445,"threshold_uncertainty_score":0.47873032},"labels":[],"label_agreement":null},{"id":"W2056207853","doi":"10.1109/tcomm.2015.2424416","title":"Update-Efficient Error-Correcting Product-Matrix Codes","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Science Council; Syracuse University","keywords":"Vandermonde matrix; Computer science; Decoding methods; Algorithm; Overhead (engineering); Fountain code; Error detection and correction; Encoding (memory); Encoder; Luby transform code; Hamming code; Node (physics); Concatenated error correction code; Block code; Reed–Solomon error correction; Engineering","score_opus":0.067804828299535,"score_gpt":0.3306793863381466,"score_spread":0.2628745580386116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056207853","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":[0.0015785227,0.0004571398,0.988247,0.0059367474,0.0006773419,0.0003151485,0.00003907357,0.0017225803,0.0010264445],"genre_scores_gemma":[0.728116,0.00007383524,0.27137062,0.00008581568,0.000010149844,0.00012063883,0.000007171111,0.000014484686,0.00020133439],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849254,0.0001467427,0.00032440436,0.00042941768,0.00030039274,0.00030648045],"domain_scores_gemma":[0.99396384,0.0002609489,0.0001327809,0.005286043,0.0002370281,0.00011933371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040065075,0.00019298078,0.00018656248,0.0002923587,0.0006367551,0.00012453648,0.0037056906,0.00007134588,0.0000069283706],"category_scores_gemma":[0.00008866448,0.00019509418,0.000071167204,0.0011083174,0.00026386543,0.00056594773,0.000069008245,0.00058104534,0.00036065606],"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":[0.00003900968,0.00253595,0.000036291567,0.000025668442,0.00013777812,0.000013160705,0.0046354476,0.41185188,0.002181383,0.07674233,0.0064462386,0.49535486],"study_design_scores_gemma":[0.0015687223,0.00035912008,0.000057392386,0.00014618233,0.00009338902,0.00028777274,0.0028787395,0.7900165,0.10751946,0.018326635,0.07716543,0.0015806505],"about_ca_topic_score_codex":0.000055603057,"about_ca_topic_score_gemma":0.000116387164,"teacher_disagreement_score":0.7265374,"about_ca_system_score_codex":0.00021420025,"about_ca_system_score_gemma":0.00015158513,"threshold_uncertainty_score":0.79557097},"labels":[],"label_agreement":null},{"id":"W2058217961","doi":"10.1145/2803140.2803141","title":"Write Amplification","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Database; Auxiliary memory; Computer data storage; Variety (cybernetics); Storage efficiency; Storage management; Storage model; Operating system; Artificial intelligence","score_opus":0.06350774556598623,"score_gpt":0.2880212804358741,"score_spread":0.22451353486988787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058217961","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005861258,0.000042506035,0.9855454,0.0013880241,0.00008672407,0.00003381403,4.5417255e-7,0.0011283256,0.01118861],"genre_scores_gemma":[0.3203591,0.0000028892755,0.67892843,0.00018107789,0.000009204886,0.0000056521535,0.0000018380464,0.0000017911549,0.0005099778],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99961966,0.000005276452,0.000055427387,0.00014313766,0.000094394985,0.00008209594],"domain_scores_gemma":[0.9992911,0.000012315737,0.000019584386,0.00060139055,0.000042330237,0.000033245116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008197604,0.0000346851,0.000033359673,0.00003913852,0.000016739317,0.00003970784,0.00064434705,0.000020493702,0.0000024793615],"category_scores_gemma":[0.00009250041,0.000028972416,0.00000628781,0.00019560903,0.000021966873,0.00061006454,0.00023836279,0.000034319986,0.00036219583],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.141961e-7,0.0000068241825,0.00007554188,3.8232884e-7,6.5576876e-7,0.0000019357067,0.00004296353,0.000021603511,0.00031607458,0.8978317,0.009626875,0.09207516],"study_design_scores_gemma":[0.00032429796,0.00008532139,0.00090709125,0.0000034233929,0.0000012577061,0.000027826334,0.00022748302,0.029220698,0.020834927,0.5844694,0.36361086,0.00028742655],"about_ca_topic_score_codex":0.0000052991954,"about_ca_topic_score_gemma":0.0000016714378,"teacher_disagreement_score":0.353984,"about_ca_system_score_codex":0.00002439602,"about_ca_system_score_gemma":0.000015705195,"threshold_uncertainty_score":0.46554154},"labels":[],"label_agreement":null},{"id":"W2058927306","doi":"10.1145/2483574.2483578","title":"DeepSea","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scalability; Distributed computing; File system; Independence (probability theory); Big data; Fault tolerance; Parallel computing; Database; Data mining; Operating system","score_opus":0.012820158282698862,"score_gpt":0.23056070914084126,"score_spread":0.2177405508581424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058927306","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020569533,0.000025254105,0.977276,0.0017135771,0.000057960475,0.00005600873,1.3360433e-7,0.0012574208,0.017556679],"genre_scores_gemma":[0.3184422,0.000003154804,0.6803566,0.0003808896,0.000005057394,0.000016238546,2.8156987e-7,0.0000016987378,0.000793859],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996319,0.0000031888576,0.00004764624,0.000134776,0.000064069754,0.00011841821],"domain_scores_gemma":[0.99937135,0.000019829951,0.000011882417,0.0005537203,0.000021819782,0.000021395608],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000019301828,0.000038380593,0.000035354158,0.000033205608,0.000025520305,0.00006056356,0.0008147586,0.000019610243,0.00012043012],"category_scores_gemma":[0.000035096204,0.00002914246,0.000009173829,0.00014847092,0.00002465394,0.0009594962,0.00040329262,0.00003922727,0.0022542218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.5457496e-8,0.0000062962795,0.00010428565,6.4368623e-7,0.0000011732386,0.0000025305055,0.00001362731,0.000005005744,0.0010162027,0.70401686,0.019781888,0.27505147],"study_design_scores_gemma":[0.000182913,0.000062522726,0.0044174995,0.0000033618555,7.815413e-7,0.000025897201,0.000085900865,0.038497727,0.038714755,0.8530855,0.0645776,0.0003455442],"about_ca_topic_score_codex":0.000019326575,"about_ca_topic_score_gemma":0.000001551186,"teacher_disagreement_score":0.31638524,"about_ca_system_score_codex":0.000009734292,"about_ca_system_score_gemma":0.000005027867,"threshold_uncertainty_score":0.99852264},"labels":[],"label_agreement":null},{"id":"W2059346393","doi":"10.5555/1251028.1251050","title":"VXA: a virtual architecture for durable compressed archives","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; x86; Virtualization; Operating system; Executable; Architecture; Embedded system; Host (biology); Computer architecture; Cloud computing; Software","score_opus":0.013461662959710506,"score_gpt":0.24587604610740565,"score_spread":0.23241438314769514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059346393","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010907744,0.000087491746,0.98899883,0.0051298346,0.00007513795,0.00025252576,0.000016046013,0.0013021696,0.003047162],"genre_scores_gemma":[0.15585394,0.000008976933,0.8419369,0.0005305276,0.000055685865,0.000060460115,0.0000066244843,0.00000891369,0.0015380007],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990159,0.000013483811,0.0001479455,0.00038256214,0.00011754655,0.00032251695],"domain_scores_gemma":[0.9988112,0.0002900383,0.0000493421,0.00078358786,0.00001702439,0.00004880071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004973613,0.00013626524,0.00014597017,0.000115246025,0.00012029079,0.00007609849,0.0014007626,0.000045895944,0.000012113983],"category_scores_gemma":[0.00008977036,0.00010947853,0.000054206204,0.00016302051,0.00010852669,0.0004631918,0.00047041406,0.00013403466,0.00003375191],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001579201,0.000054715085,0.000008665232,0.000007847403,0.000012420078,0.0000034133004,0.0002721886,0.0071051084,0.011202289,0.4512186,0.006448648,0.52365035],"study_design_scores_gemma":[0.0011239935,0.00031337127,0.00012542261,0.00001956728,0.000005293941,0.000039779596,0.000114198156,0.22372963,0.09798295,0.1372173,0.5388273,0.0005011773],"about_ca_topic_score_codex":0.0000028342433,"about_ca_topic_score_gemma":0.000024203671,"teacher_disagreement_score":0.5323787,"about_ca_system_score_codex":0.000014936391,"about_ca_system_score_gemma":0.0000238434,"threshold_uncertainty_score":0.4464405},"labels":[],"label_agreement":null},{"id":"W2066529295","doi":"10.1145/1851476.1851497","title":"A GPU accelerated storage system","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Graphics processing unit; Graphics; Multi-core processor; Computation; General-purpose computing on graphics processing units; Drop (telecommunication); Massively parallel; CUDA; Parallel computing; Computer graphics (images); Algorithm","score_opus":0.021605674159969224,"score_gpt":0.2561999158499223,"score_spread":0.23459424168995308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066529295","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":[0.03406653,0.000014973943,0.9488407,0.0003662216,0.0006735466,0.000113953756,0.0000031543182,0.004678267,0.011242695],"genre_scores_gemma":[0.73318344,7.510909e-7,0.2663463,0.00006842265,0.000021436357,0.000012822035,0.0000015594571,0.000005438427,0.00035983897],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914366,0.00001089065,0.00013099365,0.00033085115,0.00015290952,0.00023070734],"domain_scores_gemma":[0.9985556,0.000037871472,0.00005118968,0.0012434049,0.00006016821,0.000051735926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000118805394,0.00010752299,0.000111633875,0.00009709559,0.00008963506,0.00013993363,0.0016407339,0.00009020275,0.000029945706],"category_scores_gemma":[0.00007005808,0.00008661041,0.000022521563,0.00043558885,0.00005334356,0.0008708997,0.0006004561,0.00026864884,0.0003524804],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010282047,0.000017456137,0.000054090888,0.000009066565,0.0000047308845,0.00006976176,0.00004007957,0.000017444565,0.037343014,0.93083507,0.0030447913,0.028563477],"study_design_scores_gemma":[0.0017891355,0.00030728255,0.0034133482,0.00006106209,0.000014615013,0.00086197857,0.00091953925,0.39952165,0.34318194,0.019990942,0.22772886,0.0022096524],"about_ca_topic_score_codex":0.00001663088,"about_ca_topic_score_gemma":0.000024302697,"teacher_disagreement_score":0.9108441,"about_ca_system_score_codex":0.000030924486,"about_ca_system_score_gemma":0.00003023916,"threshold_uncertainty_score":0.45305398},"labels":[],"label_agreement":null},{"id":"W2067931298","doi":"10.1109/icdew.2013.6547459","title":"Materialized views for eventually consistent record stores","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materialized view; Computer science; Serialization; Scalability; Key (lock); Server; Database; Distributed database; Distributed computing; World Wide Web; Operating system; View","score_opus":0.04385118915386157,"score_gpt":0.2831152029454153,"score_spread":0.23926401379155374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067931298","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007860205,0.0000720589,0.9869251,0.0017167031,0.00067231595,0.0007362048,0.000009059201,0.0010122054,0.0009961396],"genre_scores_gemma":[0.029447109,0.000025193816,0.9673958,0.0005669115,0.000026887481,0.00046666918,0.00000778092,0.000010097106,0.0020535965],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990543,0.000021213813,0.00023536615,0.0003305814,0.00010619302,0.00025232672],"domain_scores_gemma":[0.99887896,0.00008629161,0.00009281091,0.00080779806,0.000090592766,0.000043542677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011268834,0.00012118201,0.00018078384,0.00006364793,0.0000695053,0.00015569013,0.0009889316,0.000053988577,0.00018587003],"category_scores_gemma":[0.00014193662,0.00009255705,0.000053085467,0.000107368054,0.00005620971,0.0007387216,0.0004369532,0.000038874456,0.0003020321],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012673599,0.00006432125,0.00006499788,0.00003401477,0.000026801856,0.0000037913549,0.00011650406,0.0000049352484,0.024324885,0.3804982,0.17702684,0.41782203],"study_design_scores_gemma":[0.0010809769,0.00035737254,0.00040358424,0.000025441695,0.000007801612,0.000015434067,0.00015463204,0.0061422973,0.032267414,0.19598302,0.76301545,0.0005465647],"about_ca_topic_score_codex":0.00004876399,"about_ca_topic_score_gemma":0.000021454533,"teacher_disagreement_score":0.58598864,"about_ca_system_score_codex":0.00003973365,"about_ca_system_score_gemma":0.000022837638,"threshold_uncertainty_score":0.38821125},"labels":[],"label_agreement":null},{"id":"W2070556972","doi":"10.1145/2380776.2380784","title":"dbTrento","year":2012,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universidad de Zaragoza; University of Alberta","keywords":"Citation; Computer science; Library science; Database; World Wide Web","score_opus":0.03247796109390363,"score_gpt":0.278870893944344,"score_spread":0.24639293285044037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070556972","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":[0.032557297,0.0006155676,0.9596804,0.0014468569,0.001426168,0.000111143876,0.0000031520228,0.0015204841,0.00263893],"genre_scores_gemma":[0.5277145,0.000041403986,0.47145095,0.00020394017,0.00011051829,0.000019409943,0.0000026393327,0.000009039448,0.00044760207],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990487,0.000019346198,0.00012913048,0.0002453569,0.00014860506,0.000408875],"domain_scores_gemma":[0.9978678,0.0001201627,0.00006235661,0.0018474592,0.000022369846,0.00007981791],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013146353,0.00011390893,0.000113935406,0.000089388646,0.00006987113,0.000040764713,0.0021956232,0.00006665328,0.000031921925],"category_scores_gemma":[0.0004337749,0.00010005806,0.000036752008,0.0003239031,0.000044538105,0.0014925397,0.001495388,0.00013543582,0.0004585843],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019352458,0.00005243778,0.0066821836,0.000004127714,0.0000081654225,0.000005910725,0.00016021018,0.0000020797254,0.0011553337,0.0539113,0.013431847,0.92458445],"study_design_scores_gemma":[0.0004480944,0.00017349339,0.007207872,0.000023720691,0.000010352983,0.00006237875,0.00011594495,0.0013346218,0.023461582,0.14047252,0.82588947,0.000799939],"about_ca_topic_score_codex":0.000014811184,"about_ca_topic_score_gemma":0.000005737323,"teacher_disagreement_score":0.92378455,"about_ca_system_score_codex":0.000046002133,"about_ca_system_score_gemma":0.000012019312,"threshold_uncertainty_score":0.58943266},"labels":[],"label_agreement":null},{"id":"W2071417930","doi":"10.1145/1996130.1996153","title":"VMFlock","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Cloud computing; Scalability; Data deduplication; Virtual machine; Transfer (computing); Set (abstract data type); Distributed computing; Operating system; Database","score_opus":0.044998965301199116,"score_gpt":0.2384023861248156,"score_spread":0.19340342082361647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071417930","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006700986,0.000019661935,0.9165245,0.00009861399,0.000076217046,0.000022539733,2.3340216e-7,0.0012321098,0.081355974],"genre_scores_gemma":[0.2910169,0.0000029098326,0.7083407,0.00013779299,0.000003218553,0.0000028757763,1.2747904e-7,0.0000015269558,0.0004939242],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99965525,0.0000030048518,0.00004735072,0.00013875794,0.000051881543,0.00010373153],"domain_scores_gemma":[0.99935657,0.000007624293,0.000013322638,0.0005934762,0.0000120316345,0.000016985896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028569832,0.000038230464,0.000035308483,0.00003548581,0.000022075485,0.000010782511,0.0008916562,0.00002013429,0.00006163253],"category_scores_gemma":[0.000022266016,0.000030128698,0.00000997218,0.00014339415,0.000026626105,0.00046044556,0.00040403713,0.000037851303,0.0003796078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.3909377e-7,0.000008962464,0.00015009013,4.1493863e-7,0.0000010869941,0.000010555549,0.00007490291,2.7888169e-7,0.00013391452,0.93756413,0.00204606,0.060009368],"study_design_scores_gemma":[0.00020004762,0.00013396135,0.0036384866,0.000004139549,0.0000016147022,0.000058642476,0.0001049438,0.0043177996,0.15308324,0.78386116,0.0542178,0.0003781482],"about_ca_topic_score_codex":0.000009646778,"about_ca_topic_score_gemma":0.0000025467207,"teacher_disagreement_score":0.2903468,"about_ca_system_score_codex":0.0000068085105,"about_ca_system_score_gemma":0.000005546413,"threshold_uncertainty_score":0.4879217},"labels":[],"label_agreement":null},{"id":"W2072541977","doi":"10.1109/icde.2013.6544839","title":"Main-memory hash joins on multi-core CPUs: Tuning to the underlying hardware","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":271,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Technical University of Athens; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Computer science; Translation lookaside buffer; Joins; Parallel computing; Cache; Hash function; Hash join; Join (topology); Computer hardware; Physical address; Programming language","score_opus":0.09762164541659316,"score_gpt":0.3044105359448007,"score_spread":0.20678889052820756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072541977","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":[0.010129747,0.000037621852,0.9773249,0.007883632,0.00030844758,0.0004961121,0.000005674528,0.0014800171,0.0023338548],"genre_scores_gemma":[0.5227963,0.000005643816,0.47079006,0.0039120805,0.000027892547,0.00009893422,0.0000028293794,0.000018035314,0.0023482812],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985278,0.000025779194,0.00019078667,0.0005258433,0.0002820803,0.00044770923],"domain_scores_gemma":[0.9978865,0.00017113221,0.00006395682,0.001726093,0.00006368193,0.00008863579],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00016618232,0.00019646622,0.00015101356,0.00014726486,0.0003399108,0.00028444245,0.0021247019,0.000071982766,0.00006526528],"category_scores_gemma":[0.00029626986,0.00012833704,0.000046929752,0.00047628555,0.000073207935,0.0008185611,0.0013235353,0.0002904336,0.0016828725],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004444351,0.00013291484,0.00031171256,0.000022358623,0.00003694121,0.00008648124,0.002586675,0.0066423477,0.010554748,0.16960265,0.08891606,0.72110265],"study_design_scores_gemma":[0.0027738202,0.0012097959,0.026848147,0.00057860813,0.000025591773,0.00020232557,0.020702947,0.70823896,0.027370673,0.047011297,0.16149053,0.0035473204],"about_ca_topic_score_codex":0.00011271511,"about_ca_topic_score_gemma":0.00013430657,"teacher_disagreement_score":0.71755534,"about_ca_system_score_codex":0.00008664409,"about_ca_system_score_gemma":0.000035968536,"threshold_uncertainty_score":0.9990944},"labels":[],"label_agreement":null},{"id":"W2074881976","doi":"10.1145/2806887","title":"The RAMCloud Storage System","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Computer Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":270,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Samsung; Defense Advanced Research Projects Agency; NetApp; National Science Foundation; VMware; Cisco Systems; Semiconductor Research Corporation","keywords":"Computer science; Backup; Polling; Latency (audio); Operating system; Dram; Computer network; Computer data storage; RAID; Storage area network; Auxiliary memory; Server; File server; Converged storage; Data loss; Information repository; Computer hardware","score_opus":0.034513631060890206,"score_gpt":0.25022715018956915,"score_spread":0.21571351912867895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074881976","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":[0.0003792779,0.0005048951,0.9839557,0.0009781022,0.010974725,0.00042961293,0.000013868354,0.0024873472,0.00027647038],"genre_scores_gemma":[0.86411226,0.000020934194,0.13463432,0.00010090381,0.00040769883,0.0001862548,0.000002813725,0.00003315565,0.0005016654],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978217,0.00020223351,0.00041103107,0.0005636074,0.00056081096,0.0004406127],"domain_scores_gemma":[0.9955403,0.0004369747,0.00015836232,0.003514751,0.00018144459,0.00016813318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062219356,0.00026192542,0.00027126554,0.00015462609,0.000552458,0.0006083895,0.003964731,0.00012447231,3.8288547e-7],"category_scores_gemma":[0.00003373562,0.00018607831,0.00009301765,0.0006265228,0.000108984845,0.00067579944,0.00012877978,0.00035762583,0.0003167256],"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":[0.000050279214,0.0002302151,0.000016768035,0.0001394321,0.00025893783,0.00030156373,0.0014391945,0.23313664,0.000055214452,0.25582552,0.035903852,0.4726424],"study_design_scores_gemma":[0.0012236169,0.0006349955,0.000043124386,0.00021777731,0.000023981478,0.00074114854,0.0014158092,0.71401983,0.0004264818,0.0016078247,0.27886745,0.000777931],"about_ca_topic_score_codex":0.00005874124,"about_ca_topic_score_gemma":0.000012530747,"teacher_disagreement_score":0.863733,"about_ca_system_score_codex":0.00036718082,"about_ca_system_score_gemma":0.00009315894,"threshold_uncertainty_score":0.7588053},"labels":[],"label_agreement":null},{"id":"W2076293269","doi":"10.1007/s11265-014-0930-z","title":"Latest Advances on Design and Implementation of DSP Systems","year":2014,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; BCH code; Implementation; Computer engineering; Error detection and correction; Digital signal processing; Embedded system; Computer architecture; Computer hardware; Algorithm","score_opus":0.020552999207606382,"score_gpt":0.2902257298881509,"score_spread":0.2696727306805445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076293269","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":[0.010737622,0.0057711992,0.982851,0.00009559307,0.00027176895,0.00016531651,0.0000018106969,0.00005797964,0.000047691236],"genre_scores_gemma":[0.9685396,0.00006494486,0.03126343,0.000012115715,0.000096127646,0.000005330939,3.3218996e-7,0.000009089179,0.000009041884],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838585,0.00013109586,0.00067644555,0.00018223921,0.00045015936,0.00017421729],"domain_scores_gemma":[0.99778974,0.00025064076,0.0014041503,0.0001851292,0.00031480918,0.000055533208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001179671,0.00013632349,0.0003522178,0.00024672176,0.000095648225,0.00020114532,0.00056027045,0.000056756668,4.7921355e-7],"category_scores_gemma":[0.00006188047,0.000102545135,0.000028853035,0.0002602898,0.000069915994,0.001505478,0.000065569366,0.00015682583,0.0000012991754],"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":[0.000121471036,0.00015813817,0.0024137525,0.002675225,0.00010192594,0.000071321636,0.0017081351,0.15277347,0.04331395,0.03962454,0.0010471259,0.7559909],"study_design_scores_gemma":[0.005098274,0.010219657,0.0014767951,0.009417295,0.0001478169,0.0028589875,0.0094393855,0.8486576,0.07713007,0.014531126,0.019503266,0.0015197102],"about_ca_topic_score_codex":0.000009539225,"about_ca_topic_score_gemma":3.6366382e-7,"teacher_disagreement_score":0.95780194,"about_ca_system_score_codex":0.000055018918,"about_ca_system_score_gemma":0.000080549005,"threshold_uncertainty_score":0.41816694},"labels":[],"label_agreement":null},{"id":"W2076404941","doi":"10.1088/1742-6596/513/3/032095","title":"Experience of a low-maintenance distributed data management system","year":2014,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen Mary University of London; Canadian Institute for Theoretical Astrophysics","keywords":"Backup; Software deployment; Computer science; Overhead (engineering); Data management; File system; Management system; Production (economics); Simple (philosophy); Database; Operating system; Engineering; Operations management","score_opus":0.028840983696049725,"score_gpt":0.25977105620035346,"score_spread":0.23093007250430372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076404941","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":[0.004598353,0.000042805037,0.99428886,0.00022251958,0.0003018116,0.0000813361,0.000060048445,0.000091825765,0.00031243582],"genre_scores_gemma":[0.8693835,0.0000630836,0.13045637,0.000015486727,0.00004369866,0.000003422036,0.000008882301,0.000005945021,0.000019617182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984337,0.000051285773,0.0005402363,0.00029042098,0.0004434994,0.00024086598],"domain_scores_gemma":[0.9968198,0.00006495247,0.00087341,0.0017335602,0.00044762687,0.000060630075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031362672,0.00016702167,0.00039287686,0.00006943852,0.0000683904,0.00010173737,0.0041322284,0.000040033974,0.000001680622],"category_scores_gemma":[0.00015234145,0.00013568485,0.0000528739,0.00040289137,0.00028623,0.002946806,0.0015123464,0.00017975603,0.000004109498],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023371414,0.00005522368,0.000069542584,0.0001868693,0.00003882409,0.000037459227,0.00041456873,0.00017313188,0.0020435273,0.860864,0.00035643537,0.13573706],"study_design_scores_gemma":[0.0032345697,0.0018172325,0.0037298189,0.0054072626,0.00014912525,0.00065184094,0.021733651,0.07711421,0.60024804,0.2541274,0.029866004,0.0019208287],"about_ca_topic_score_codex":0.0000033135072,"about_ca_topic_score_gemma":0.0000015924121,"teacher_disagreement_score":0.86478513,"about_ca_system_score_codex":0.00005291631,"about_ca_system_score_gemma":0.000067743385,"threshold_uncertainty_score":0.76787776},"labels":[],"label_agreement":null},{"id":"W2079253715","doi":"10.1177/1094342014548864","title":"Extreme-scale computing services over MPI: Experiences, observations and features proposal for next-generation message passing interface","year":2014,"lang":"en","type":"article","venue":"The International Journal of High Performance Computing Applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Advanced Scientific Computing Research; Division of Mathematical Sciences; Argonne National Laboratory; Natural Sciences and Engineering Research Council of Canada; Office of Science","keywords":"Computer science; Message Passing Interface; Software portability; Message passing; Implementation; Workaround; Interface (matter); Supercomputer; Distributed computing; Scale (ratio); Programming paradigm; Operating system; Software engineering; Programming language","score_opus":0.03491654217823178,"score_gpt":0.2863399186556468,"score_spread":0.25142337647741503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079253715","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":[0.39656204,0.00018520147,0.6005813,0.00206802,0.00033137374,0.00017424452,0.000004540551,0.00007737341,0.000015952852],"genre_scores_gemma":[0.7066469,0.000035616267,0.29261902,0.00021270425,0.00043134697,0.000023419538,0.000009953665,0.00000913767,0.000011900868],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984329,0.000042995365,0.0005249556,0.00028306572,0.0005087607,0.00020733845],"domain_scores_gemma":[0.99788725,0.0003100003,0.0007023962,0.00038959086,0.0006643802,0.000046383484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078183686,0.00016730647,0.00019099684,0.00015448287,0.0006121501,0.0005440084,0.0020930008,0.000057698344,0.0000017731487],"category_scores_gemma":[0.00006483341,0.0001267373,0.00005109377,0.00024345343,0.00015057327,0.0012613605,0.0005735056,0.00025970468,0.0000013587337],"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":[0.000054783617,0.00023213794,0.0025961476,0.00012099944,0.00018104445,0.0000018247414,0.010889342,0.06372809,0.041758128,0.18307437,0.0025610009,0.69480217],"study_design_scores_gemma":[0.0005921302,0.0001299523,0.0059715076,0.00018499476,0.000022597622,0.00017213907,0.0010286251,0.95814466,0.016308414,0.0083859535,0.008796322,0.00026271454],"about_ca_topic_score_codex":0.00001597248,"about_ca_topic_score_gemma":0.000019234154,"teacher_disagreement_score":0.8944166,"about_ca_system_score_codex":0.00011235554,"about_ca_system_score_gemma":0.000090875525,"threshold_uncertainty_score":0.5245885},"labels":[],"label_agreement":null},{"id":"W2079342791","doi":"10.1016/j.cpc.2010.07.049","title":"Parallel hyperbolic PDE simulation on clusters: Cell versus GPU","year":2010,"lang":"en","type":"article","venue":"Computer Physics Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computational science; Parallel computing; Computer science; CUDA; Computer graphics (images)","score_opus":0.055911662447553565,"score_gpt":0.30974416340631483,"score_spread":0.25383250095876125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079342791","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002307089,0.000045177676,0.99150807,0.0014070324,0.000695579,0.00023342526,0.00001012543,0.00095543993,0.002838067],"genre_scores_gemma":[0.44711044,0.000024219236,0.5524444,0.00022373875,0.00009766231,0.000028025524,0.000040539493,0.0000134886595,0.000017498276],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987906,0.00007354256,0.00023912646,0.00040504325,0.00021365602,0.00027800957],"domain_scores_gemma":[0.9923119,0.0008332208,0.00016408702,0.0064962506,0.00012266576,0.00007185161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010154219,0.0002119732,0.00017984507,0.00009557645,0.00039726653,0.00018139111,0.004879009,0.0001019436,0.0000023972013],"category_scores_gemma":[0.000034253262,0.00022298661,0.00008025617,0.0004910077,0.00022485074,0.00085311016,0.002874226,0.0006910041,0.00028686944],"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":[0.0000151870145,0.00055148086,0.00003075515,0.0000088752795,0.000025699466,0.0000021188741,0.00059345627,0.140382,0.0010317386,0.609005,0.0012809009,0.24707282],"study_design_scores_gemma":[0.00060145237,0.00009335839,0.00016961919,0.000008712151,0.0000063331036,9.935613e-7,0.0000100279585,0.95901287,0.00024032814,0.021631815,0.017973965,0.0002505538],"about_ca_topic_score_codex":0.000006866082,"about_ca_topic_score_gemma":0.000012554081,"teacher_disagreement_score":0.8186308,"about_ca_system_score_codex":0.00004856378,"about_ca_system_score_gemma":0.000044463242,"threshold_uncertainty_score":0.90931296},"labels":[],"label_agreement":null},{"id":"W2080490796","doi":"10.1109/ccece.2007.60","title":"vanDisk: An Exploration in Peer-To-Peer Collaborative Back-Up Storage","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Backup; Computer science; Data loss; User space; Redundancy (engineering); Data redundancy; Raw data; File system; Encryption; Data recovery; Computer data storage; Operating system; Data management; Overhead (engineering); Database","score_opus":0.03833670546209494,"score_gpt":0.3190593839697419,"score_spread":0.280722678507647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080490796","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":[0.022926068,0.00002057037,0.96899706,0.0032518555,0.00039849413,0.00035669707,0.000013801513,0.0006135422,0.0034219061],"genre_scores_gemma":[0.507245,0.0000050088042,0.48895505,0.0004245741,0.000036158046,0.000025390727,0.00003146177,0.000013210894,0.0032641545],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99813014,0.00004427919,0.00028943404,0.00056778913,0.0005638365,0.00040452887],"domain_scores_gemma":[0.9982938,0.00009272792,0.00007745294,0.00096881815,0.00044836797,0.00011880575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089619996,0.00017889969,0.00017957916,0.0004072487,0.00008315784,0.00015270096,0.0010801954,0.00010767351,0.000038986534],"category_scores_gemma":[0.0004432452,0.000165219,0.000017031334,0.0019612724,0.00005811201,0.005023986,0.0004215376,0.00018724463,0.00034146098],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014597797,0.00046584243,0.0015702295,0.000017710665,0.0000206209,0.0003766872,0.022810908,0.0064130905,0.00977198,0.6269397,0.048491392,0.28297582],"study_design_scores_gemma":[0.0052340194,0.0031077662,0.016229143,0.00010828244,0.00001371268,0.000042532425,0.047298655,0.050419927,0.21269251,0.15133765,0.50955683,0.003958996],"about_ca_topic_score_codex":0.00003729215,"about_ca_topic_score_gemma":0.0013496072,"teacher_disagreement_score":0.4843189,"about_ca_system_score_codex":0.00019401425,"about_ca_system_score_gemma":0.0000666038,"threshold_uncertainty_score":0.6737435},"labels":[],"label_agreement":null},{"id":"W2081128697","doi":"10.1145/1509084.1509091","title":"Exploiting multithreaded architectures to improve the hash join operation","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Hash join; Parallel computing; Hash function; Xeon; Pentium; Shared memory; Operating system; Computer architecture; Programming language","score_opus":0.033960884497086154,"score_gpt":0.26178196334906506,"score_spread":0.22782107885197891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081128697","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":[0.08511096,0.000026146938,0.9092779,0.0037788358,0.00011683581,0.0002535809,0.000002101052,0.0008431444,0.00059045537],"genre_scores_gemma":[0.6281601,0.0000030199706,0.3706275,0.00090606697,0.000031669628,0.00004632265,9.520181e-7,0.00000509368,0.00021927497],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99910915,0.000022233224,0.00014127481,0.00032738448,0.00017678559,0.00022317871],"domain_scores_gemma":[0.9989735,0.0000919125,0.000035646866,0.0008278636,0.00003470357,0.000036362446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000102600985,0.00010692697,0.000087983935,0.00007192618,0.00030740927,0.000078633435,0.0010946419,0.000033911852,0.000006970308],"category_scores_gemma":[0.0002636829,0.000065412576,0.000024409175,0.0002392604,0.00007632996,0.0003036352,0.0006596873,0.00014254016,0.00010087384],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012314345,0.000081675564,0.00037674146,0.0000092912405,0.000022754033,0.000085860134,0.007684886,0.019186115,0.19138405,0.12009627,0.008046122,0.6530139],"study_design_scores_gemma":[0.00062953477,0.00029681713,0.0030121428,0.000019990539,0.0000035580817,0.00018836858,0.0007082437,0.12211558,0.8481663,0.015434013,0.008757589,0.00066784705],"about_ca_topic_score_codex":0.0000523971,"about_ca_topic_score_gemma":0.000049458795,"teacher_disagreement_score":0.65678227,"about_ca_system_score_codex":0.000029401015,"about_ca_system_score_gemma":0.000024154988,"threshold_uncertainty_score":0.26674476},"labels":[],"label_agreement":null},{"id":"W2081462964","doi":"10.1145/2757667.2757671","title":"Algebraic modeling of write amplification in hotness-aware SSD","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Garbage collection; Computer science; Workload; Flash (photography); Metric (unit); Garbage; Ordinary differential equation; Algebraic number; Computer engineering; Theoretical computer science; Algorithm; Differential equation; Programming language; Mathematics","score_opus":0.07416723793347138,"score_gpt":0.292091146157393,"score_spread":0.21792390822392163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081462964","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":[0.031860955,0.00010110144,0.96662986,0.0003853643,0.00005538673,0.00008004262,0.0000019914576,0.0003414493,0.00054385385],"genre_scores_gemma":[0.8218549,0.000008484121,0.17805515,0.00003399316,0.000004313562,0.000008420438,0.00000421007,0.0000034740478,0.000027031176],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992349,0.000013477532,0.00020224186,0.00024428463,0.00016572814,0.00013936998],"domain_scores_gemma":[0.9990924,0.000024132281,0.00005782303,0.00070002896,0.0000949031,0.000030734936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001942685,0.00007042739,0.00011121102,0.00016509979,0.000013134335,0.000020965876,0.00083593733,0.000051876206,0.0000017778442],"category_scores_gemma":[0.00011075114,0.00006443307,0.000013486645,0.0004923567,0.000034848705,0.0008103312,0.0003362414,0.00007974136,0.000020123784],"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":[0.000009470363,0.00011081705,0.0017073129,0.000028100329,0.0000063686707,0.000012488794,0.0009365044,0.092178635,0.0019267929,0.80776227,0.00049108104,0.094830155],"study_design_scores_gemma":[0.00018112763,0.00002268931,0.00011987381,0.000012718402,6.964266e-7,0.0000029278833,0.0003148836,0.9009007,0.0024227733,0.09581232,0.00011098317,0.000098300305],"about_ca_topic_score_codex":0.00006925967,"about_ca_topic_score_gemma":0.000032560834,"teacher_disagreement_score":0.8087221,"about_ca_system_score_codex":0.000048170412,"about_ca_system_score_gemma":0.000042184267,"threshold_uncertainty_score":0.26275045},"labels":[],"label_agreement":null},{"id":"W2083437586","doi":"10.1007/s11227-009-0342-1","title":"Cost-aware caching schemes in heterogeneous storage systems","year":2009,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Thrashing; Cache; Partition (number theory); Workload; Disk buffer; Scheme (mathematics); Choking; Parallel computing; Byte; Distributed computing; Cache algorithms; Computer network; CPU cache; Operating system","score_opus":0.03329468887582841,"score_gpt":0.2822184076849176,"score_spread":0.2489237188090892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083437586","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":[0.35819662,0.001660087,0.6391512,0.00051059463,0.00026986306,0.00009846787,8.0691694e-7,0.00009398066,0.000018366913],"genre_scores_gemma":[0.9798439,0.00005533954,0.019823948,0.00015504085,0.000109237546,4.3328808e-7,3.6889085e-7,0.000007967226,0.0000037229884],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839914,0.00017354211,0.0005646798,0.00015875467,0.00034888936,0.00035497878],"domain_scores_gemma":[0.99876577,0.00026541462,0.00028451518,0.0005279946,0.000101740006,0.00005458927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013659893,0.00016147253,0.00030100538,0.0002483522,0.00017157446,0.00012801283,0.00201799,0.000065977576,8.2796e-7],"category_scores_gemma":[0.00016272548,0.00011125769,0.00006277468,0.00042612126,0.0000490096,0.00094538945,0.00031953945,0.00063201564,0.0000044499047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016080621,0.00007110569,0.00049263495,0.000017296881,0.000022810773,0.0006055412,0.0019683058,0.8972977,0.004042712,0.0026757,0.00015152589,0.09263858],"study_design_scores_gemma":[0.0013305516,0.00064611685,0.0018553053,0.0008876526,0.000026607197,0.0081650065,0.0029701437,0.9713215,0.006225673,0.00377873,0.0021149064,0.0006777601],"about_ca_topic_score_codex":0.000020799067,"about_ca_topic_score_gemma":0.0000029489593,"teacher_disagreement_score":0.62164736,"about_ca_system_score_codex":0.00017478163,"about_ca_system_score_gemma":0.00005178264,"threshold_uncertainty_score":0.45369568},"labels":[],"label_agreement":null},{"id":"W2085092676","doi":"10.1016/j.jocs.2012.08.017","title":"Efficient SIMD solution of multiple systems of stiff IVPs","year":2012,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"SIMD; Computer science; Parallel computing; Applied mathematics; Mathematics","score_opus":0.023765874126207582,"score_gpt":0.2824321634234131,"score_spread":0.25866628929720553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085092676","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":[0.31183523,0.00034803498,0.68711615,0.00006481908,0.0005110497,0.000055798017,0.0000045589313,0.000016736278,0.00004764747],"genre_scores_gemma":[0.7865113,0.0000022771521,0.21344104,0.000007544246,0.0000327884,5.959834e-7,3.065633e-7,0.000002028183,0.00000208948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979473,0.00003859089,0.0005867674,0.00012999131,0.0010520393,0.00024531723],"domain_scores_gemma":[0.99738246,0.0003730592,0.0010156983,0.00023721899,0.0008940099,0.000097559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014957186,0.00008303481,0.00021446738,0.00040028483,0.00009973751,0.000037421756,0.0013021132,0.000031460633,0.0000011502802],"category_scores_gemma":[0.00071166334,0.00006702103,0.00005731808,0.000880332,0.00052253634,0.0009744828,0.0003178345,0.00011734561,0.000003043051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000076056845,0.00013766119,0.0015912135,0.000017702867,0.0000062267704,0.0000010435965,0.00029736073,0.93495804,0.014853383,0.043842297,0.00006904267,0.0042184284],"study_design_scores_gemma":[0.0003565542,0.00020034211,0.027669651,0.000092603856,0.0000064313517,0.00014548276,0.00013915739,0.9610035,0.006624449,0.0034919998,0.00015729341,0.00011256654],"about_ca_topic_score_codex":0.000008863139,"about_ca_topic_score_gemma":2.9108412e-7,"teacher_disagreement_score":0.4746761,"about_ca_system_score_codex":0.00012241356,"about_ca_system_score_gemma":0.00027540937,"threshold_uncertainty_score":0.27330384},"labels":[],"label_agreement":null},{"id":"W2088271809","doi":"10.1109/msst.2014.6855555","title":"DedupT: Deduplication for tape systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Data deduplication; Computer science; Fragmentation (computing); Overhead (engineering); Database; Distributed computing; Operating system","score_opus":0.017619575532661472,"score_gpt":0.25841188505943075,"score_spread":0.24079230952676928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088271809","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043247233,0.000085375745,0.9953599,0.00073000183,0.00021073304,0.0002357173,0.0000018807851,0.0010962557,0.0018476895],"genre_scores_gemma":[0.48839322,0.0000029384817,0.5109152,0.0001820697,0.000033821118,0.00013667888,0.0000046738473,0.00000497185,0.00032639975],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938285,0.0000094050065,0.000112262445,0.0002576405,0.00008180659,0.00015605072],"domain_scores_gemma":[0.9989229,0.00012412711,0.00005454928,0.00081421784,0.000058648002,0.00002555766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015748896,0.00006590957,0.000080477024,0.00005176342,0.00006657603,0.00007794049,0.0008709555,0.000044898712,0.0000011565378],"category_scores_gemma":[0.00018382014,0.00005520563,0.000018897552,0.00015161351,0.000024138131,0.00043130954,0.0001751959,0.000033741435,0.000068085574],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7680737e-7,0.000006225518,0.000022960294,0.000007798287,0.0000018521112,7.1525655e-8,0.000007883015,0.00014977911,0.0007936117,0.9271338,0.0038000317,0.06807549],"study_design_scores_gemma":[0.00023930597,0.00010616288,0.00021260772,0.000009008572,0.0000035514217,0.000011042048,0.000030096893,0.6022069,0.009972006,0.07835547,0.30863288,0.00022098805],"about_ca_topic_score_codex":0.000007658583,"about_ca_topic_score_gemma":0.00000241951,"teacher_disagreement_score":0.84877837,"about_ca_system_score_codex":0.00002559405,"about_ca_system_score_gemma":0.000009924616,"threshold_uncertainty_score":0.22512202},"labels":[],"label_agreement":null},{"id":"W2089778585","doi":"10.1088/1742-6596/219/7/072024","title":"dCache with tape storage for High Energy Physics applications","year":2010,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute of Particle Physics; University of Victoria","funders":"SLAC National Accelerator Laboratory; Deutsches Elektronen-Synchrotron; Fermilab; CERN; University of Victoria","keywords":"Interface (matter); Computer data storage; Computer science; Operating system; Consistency (knowledge bases); Energy storage; Database; Storage area network; Node (physics); Magnetic tape; Computer hardware; Physics","score_opus":0.01652353031106086,"score_gpt":0.24157308444703118,"score_spread":0.22504955413597033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089778585","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":[0.0016606841,0.000025334537,0.9969811,0.00073089026,0.00021229207,0.0001209284,0.000028321989,0.00011204127,0.00012843987],"genre_scores_gemma":[0.67148304,0.000025731873,0.3280361,0.00005445963,0.000270519,0.000040698706,0.0000060411194,0.000012192562,0.0000711871],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989775,0.000014166335,0.0002661105,0.00022930531,0.00027922174,0.00023369658],"domain_scores_gemma":[0.9978106,0.00010601462,0.00056468655,0.00070057093,0.0007471058,0.00007102394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106039864,0.00018741077,0.0002896651,0.000051315827,0.00015948458,0.00017812054,0.0013950947,0.00007090745,0.0000035464523],"category_scores_gemma":[0.00003655144,0.00014639903,0.0000660266,0.00033970317,0.00027397205,0.0022773377,0.00018959562,0.00036367803,0.000002527368],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012225081,0.000052139672,0.000010107275,0.000008930774,0.000022732404,0.0000034959398,0.00008761458,0.0000810097,0.013995048,0.7627142,0.000117138334,0.22289535],"study_design_scores_gemma":[0.0003121809,0.00036625596,0.000054909196,0.000017626702,0.000019495446,0.000039819282,0.00011961485,0.00035698322,0.2731703,0.7120528,0.013275501,0.00021448328],"about_ca_topic_score_codex":0.000004826402,"about_ca_topic_score_gemma":0.000020601845,"teacher_disagreement_score":0.6698224,"about_ca_system_score_codex":0.000025049874,"about_ca_system_score_gemma":0.0002726817,"threshold_uncertainty_score":0.5969979},"labels":[],"label_agreement":null},{"id":"W2095394405","doi":"10.1016/j.jcp.2014.10.022","title":"A mesh partitioning algorithm for preserving spatial locality in arbitrary geometries","year":2014,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Locality; Partition (number theory); Space partitioning; Algorithm; Computer science; Cluster analysis; Metric (unit); Heuristic; Slicing; Domain (mathematical analysis); Polygon mesh; Metric space; Mathematics; Artificial intelligence; Discrete mathematics; Combinatorics","score_opus":0.01903047656072321,"score_gpt":0.27482301936119113,"score_spread":0.2557925428004679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095394405","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059091803,0.000054614746,0.9931878,0.00047313288,0.00018843416,0.00008787077,0.00001012992,0.000045411693,0.000043442204],"genre_scores_gemma":[0.4354215,0.0000024278759,0.5642787,0.00011022039,0.00017014741,0.0000039233164,0.000006445446,0.0000046725686,0.0000019651254],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988624,0.000041689807,0.00041077923,0.00014960187,0.000368838,0.00016671419],"domain_scores_gemma":[0.9983659,0.0007076064,0.00038815034,0.00017125746,0.00032683424,0.000040294784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048238056,0.00009736928,0.00022039181,0.00015292238,0.00007706158,0.000091989124,0.000611232,0.0000380091,0.0000012125429],"category_scores_gemma":[0.00030111754,0.00009418427,0.000078428915,0.00042643782,0.00006217442,0.0012934443,0.00017622387,0.00020378754,0.0000015958245],"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":[0.000013240588,0.00012604441,0.00038652358,0.00002555863,0.000026800655,0.000008218637,0.00013139404,0.3719396,0.000032871063,0.11688851,0.00046791672,0.5099533],"study_design_scores_gemma":[0.0003157827,0.00008525512,0.0014887879,0.000026888323,0.0000024966182,0.000008832171,0.000009984083,0.4975613,0.00044963084,0.4996333,0.00035593152,0.000061787585],"about_ca_topic_score_codex":0.000006342989,"about_ca_topic_score_gemma":0.0000018357648,"teacher_disagreement_score":0.5098915,"about_ca_system_score_codex":0.00006346834,"about_ca_system_score_gemma":0.00010600927,"threshold_uncertainty_score":0.3840723},"labels":[],"label_agreement":null},{"id":"W2096199010","doi":"10.1109/hpcs.2005.32","title":"Hpcbench &amp;#8212; A Linux-Based Network Benchmark for High Performance Networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Myrinet; Computer science; Gigabit Ethernet; Benchmark (surveying); Supercomputer; Ethernet; Gigabit; Operating system; Network interface controller; Network performance; Process (computing); Computer network; Computer architecture; Distributed computing; Message passing; Telecommunications","score_opus":0.015301022359144111,"score_gpt":0.2430115794312595,"score_spread":0.2277105570721154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096199010","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0078033064,0.00037616186,0.98669285,0.0018974815,0.00047986305,0.00045421626,0.0000068982763,0.0015859994,0.00070321694],"genre_scores_gemma":[0.39444697,0.00003828155,0.60346544,0.001083123,0.00034640235,0.000111097055,0.000038611157,0.000015173897,0.00045491333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978147,0.000024184745,0.00037527445,0.0006866602,0.0002546727,0.0008445018],"domain_scores_gemma":[0.9976991,0.00035937136,0.00015189916,0.0015739071,0.00011915998,0.00009656845],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038758726,0.00029947938,0.00029183325,0.00011063774,0.00031297252,0.0001404604,0.0019680776,0.00019740936,0.000055435798],"category_scores_gemma":[0.00010046796,0.00025590253,0.0000800047,0.0007600036,0.00011173174,0.0010903508,0.0004745256,0.0002775076,0.00006855037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032258038,0.000081570965,0.0009251764,0.000022287346,0.00001993597,0.0000024255091,0.000028004903,0.46139038,0.000052026295,0.09330766,0.05909625,0.385042],"study_design_scores_gemma":[0.00057142426,0.00017604449,0.0006657292,0.00003328392,0.0000078737885,0.0000061198384,0.0000035713188,0.8529254,0.0011076253,0.004858854,0.13918673,0.00045731504],"about_ca_topic_score_codex":0.000008966551,"about_ca_topic_score_gemma":0.000061303705,"teacher_disagreement_score":0.39153504,"about_ca_system_score_codex":0.00011730273,"about_ca_system_score_gemma":0.00007425559,"threshold_uncertainty_score":0.99998933},"labels":[],"label_agreement":null},{"id":"W2097108039","doi":"10.1109/isce.1997.658402","title":"Storage rebuild for automatic failure recovery in video-on-demand servers","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Server; Redundancy (engineering); Computer science; Scalability; Spare part; Fault tolerance; Computer network; Video on demand; Video server; High availability; RAID; Distributed computing; Real-time computing; Operating system; Engineering","score_opus":0.02007749949889014,"score_gpt":0.23842866879802962,"score_spread":0.21835116929913947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097108039","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020272955,0.00015925438,0.97090137,0.0047614854,0.0002506473,0.00054993725,0.000015405909,0.0016165238,0.0014724206],"genre_scores_gemma":[0.30797276,0.000048412432,0.6894307,0.0009726586,0.000026863168,0.00012916485,0.0000050032572,0.00002136751,0.0013930692],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866843,0.00002730713,0.0002547835,0.00050245743,0.00018788657,0.00035912803],"domain_scores_gemma":[0.99844813,0.00029431633,0.00008731584,0.0010984304,0.000026695652,0.000045127374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002119641,0.0001737396,0.00021317613,0.0002624897,0.00007445628,0.00009459179,0.0012062491,0.00011467322,0.000064572756],"category_scores_gemma":[0.00034440603,0.00015415723,0.00005885678,0.00051901914,0.000045075747,0.0012367886,0.00030160396,0.00016404458,0.0001277869],"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":[0.000020173242,0.0003748029,0.00028853217,0.00021412683,0.000049804257,0.00020133423,0.00074707856,0.011949682,0.0009366384,0.18918192,0.35830802,0.4377279],"study_design_scores_gemma":[0.0021362852,0.00074964523,0.0006473137,0.00021843868,0.000008307735,0.000033711367,0.00029295014,0.85810155,0.004960936,0.0858905,0.045982692,0.0009776984],"about_ca_topic_score_codex":0.000008218128,"about_ca_topic_score_gemma":0.000056007237,"teacher_disagreement_score":0.8461518,"about_ca_system_score_codex":0.0001429229,"about_ca_system_score_gemma":0.000012092992,"threshold_uncertainty_score":0.6286349},"labels":[],"label_agreement":null},{"id":"W2097633955","doi":"10.1109/icdim.2007.4444199","title":"Automated and scheduled maintenance of digital library collections","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Scheduling (production processes); Operating system; Software; Digital library; Data collection; Task (project management); Software engineering; Engineering","score_opus":0.009324418058649477,"score_gpt":0.2337010443449127,"score_spread":0.22437662628626323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097633955","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":[0.01500136,0.000059636935,0.96472424,0.0003896482,0.0000499932,0.00007480909,0.000016277038,0.003442929,0.016241131],"genre_scores_gemma":[0.62039334,0.00001168189,0.37811255,0.000040480856,0.0000033600952,0.0000016239601,0.00000235183,0.000003964552,0.0014306826],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994698,0.000002779538,0.000135039,0.00017097084,0.000072046605,0.00014933915],"domain_scores_gemma":[0.9994921,0.00008050602,0.000047425725,0.0003255429,0.00002247097,0.000031930835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047334357,0.000060823313,0.00008345669,0.00014261881,0.0000569411,0.00008680495,0.00036682983,0.000038613372,0.000008481953],"category_scores_gemma":[0.00009481156,0.000050550603,0.00001313798,0.0008600867,0.00012168884,0.0014315892,0.0004415976,0.000054468757,0.000006948938],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002256335,0.00014781102,0.0048622964,0.000027107957,0.000032744647,0.00007983589,0.00010831997,0.000043274853,0.0032517172,0.88246393,0.046898093,0.0620623],"study_design_scores_gemma":[0.0025849927,0.0007772981,0.020933012,0.00012955838,0.0000117764475,0.0005264157,0.0011190146,0.2786779,0.34071672,0.27383825,0.07933644,0.0013486099],"about_ca_topic_score_codex":0.00000123836,"about_ca_topic_score_gemma":0.0000013336978,"teacher_disagreement_score":0.60862565,"about_ca_system_score_codex":0.000009297278,"about_ca_system_score_gemma":0.00002205315,"threshold_uncertainty_score":0.20613939},"labels":[],"label_agreement":null},{"id":"W2097731133","doi":"10.1002/sat.1038","title":"Security in DVB‐RCS2","year":2013,"lang":"en","type":"article","venue":"International Journal of Satellite Communications and Networking","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advantech AMT (Canada)","funders":"","keywords":"Computer science; Digital Video Broadcasting; Telecommunications; Return channel; Digital television; Computer security; Broadcasting (networking); Channel (broadcasting)","score_opus":0.02613235225917008,"score_gpt":0.29094738567780143,"score_spread":0.26481503341863133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097731133","genre_codex":"review","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":[0.12812865,0.4164905,0.37476346,0.059529636,0.0041916086,0.0007277292,0.000010349686,0.00039257566,0.015765516],"genre_scores_gemma":[0.8488641,0.08451246,0.06637358,0.00016948674,0.000064201005,0.00000381703,0.0000023469813,0.000003469156,0.0000065340314],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992137,0.000051794414,0.0003627861,0.00008988361,0.00017210204,0.000109722525],"domain_scores_gemma":[0.99869895,0.0002342131,0.0002601915,0.00053420255,0.00023817012,0.000034290737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029268107,0.00006794244,0.00011031452,0.00021910013,0.00005007787,0.000169448,0.0024832746,0.00003867986,0.000004033202],"category_scores_gemma":[0.000026392865,0.000061591934,0.000030262008,0.00020635466,0.00009692384,0.0010490958,0.0009722685,0.00028107085,0.000005659364],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002286966,0.000040364677,0.0048689772,0.0000013794945,0.000019462166,0.000010825077,0.00035300117,0.000008662836,0.00017312619,0.026446385,0.00003254045,0.96804297],"study_design_scores_gemma":[0.0007710223,0.00009426589,0.013310204,0.0004550432,0.0000064294036,0.00044071602,0.00042581925,0.028228553,0.00023112257,0.32882267,0.62691206,0.00030209648],"about_ca_topic_score_codex":0.000025935053,"about_ca_topic_score_gemma":0.000025268182,"teacher_disagreement_score":0.9677409,"about_ca_system_score_codex":0.00005896833,"about_ca_system_score_gemma":0.000020167745,"threshold_uncertainty_score":0.46145836},"labels":[],"label_agreement":null},{"id":"W2097802100","doi":"10.1109/tencon.1992.271994","title":"Performance results of CSMA/CD Ethernet with various acknowledgement schemes","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Ethernet; Computer science; Computer network; Acknowledgement; Ethernet flow control; Scheme (mathematics); Synchronous Ethernet; Ethernet over SDH; Real-time computing; Embedded system; Mathematics","score_opus":0.01587607737034687,"score_gpt":0.23789813669353974,"score_spread":0.22202205932319286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097802100","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":[0.08308531,0.00018352874,0.83341813,0.00018990062,0.00015252265,0.00023812141,0.000006859174,0.0007340286,0.08199159],"genre_scores_gemma":[0.6403992,0.000026700409,0.3583375,0.000031693577,0.0000038429043,0.000008876423,0.0000015052116,0.0000053085655,0.0011853755],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989714,0.000020626605,0.00021246797,0.00034450373,0.00021879846,0.00023222805],"domain_scores_gemma":[0.9986032,0.000049865856,0.000114681025,0.0010716949,0.00012879548,0.00003175167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022333836,0.00012985601,0.00014612023,0.00008606442,0.00004899378,0.000024347297,0.00086429407,0.00005049816,0.000017923763],"category_scores_gemma":[0.00014560042,0.00009223544,0.00001697604,0.00044381668,0.00011994411,0.00048517287,0.00024680005,0.00010974117,0.00007811846],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001349508,0.0004966881,0.0039336737,0.00013374277,0.00010710428,0.00004161662,0.0015183731,0.0015121633,0.0033668873,0.60227466,0.010691994,0.37578818],"study_design_scores_gemma":[0.003931866,0.0022386983,0.001611042,0.00014928212,0.000019915291,0.000063951054,0.00047563584,0.021260215,0.5380307,0.006735342,0.4244406,0.0010427979],"about_ca_topic_score_codex":0.0000054850566,"about_ca_topic_score_gemma":0.000021572207,"teacher_disagreement_score":0.5955393,"about_ca_system_score_codex":0.000036700374,"about_ca_system_score_gemma":0.000062095416,"threshold_uncertainty_score":0.37612522},"labels":[],"label_agreement":null},{"id":"W2098130516","doi":"10.1109/sfcs.2000.892128","title":"Cache-oblivious B-trees","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":157,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Block size; Data structure; Auxiliary memory; Binary logarithm; B-tree; Computer science; Parallel computing; Tree (set theory); Combinatorics; Upper and lower bounds; Block (permutation group theory); Memory hierarchy; Cache; Cache-oblivious algorithm; Amortized analysis; CPU cache; Mathematics; Key (lock); Cache algorithms; Operating system","score_opus":0.027118369087160112,"score_gpt":0.23417700906956748,"score_spread":0.20705863998240737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098130516","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":[0.001665879,0.00035070523,0.96494263,0.0019758896,0.00014287504,0.000053080705,0.000001287991,0.002319496,0.028548151],"genre_scores_gemma":[0.66568315,0.000043713335,0.33057314,0.00035094697,0.00001666263,0.0000073088427,4.888292e-7,0.0000046105124,0.0033199883],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993248,0.000007898049,0.0000870682,0.00025102365,0.00012893767,0.00020027003],"domain_scores_gemma":[0.9990246,0.00003965459,0.000025697924,0.0008593185,0.0000185984,0.000032091204],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000038789818,0.0000792199,0.00007418079,0.00007835812,0.000055280016,0.000060898037,0.0011552069,0.000040529692,0.00014085993],"category_scores_gemma":[0.00006748973,0.00006461705,0.000021476173,0.00032049106,0.00005186714,0.0006574229,0.00048587058,0.00008245694,0.0008163166],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.748363e-7,0.00006793067,0.00032131333,0.0000022646022,0.0000069322004,0.00007843112,0.00017909873,0.0000628881,0.0007869629,0.4384012,0.06893499,0.49115774],"study_design_scores_gemma":[0.0009934563,0.00040655813,0.0027246776,0.000023302964,0.000009196813,0.00029887207,0.0002620792,0.2674094,0.04033962,0.17506471,0.5109098,0.001558304],"about_ca_topic_score_codex":0.000011062788,"about_ca_topic_score_gemma":0.000020502415,"teacher_disagreement_score":0.66401726,"about_ca_system_score_codex":0.000022233095,"about_ca_system_score_gemma":0.0000026979783,"threshold_uncertainty_score":0.9999617},"labels":[],"label_agreement":null},{"id":"W2098666492","doi":"10.1145/545214.545244","title":"Experiences with VI communication for database storage","year":2002,"lang":"en","type":"article","venue":"ACM SIGARCH Computer Architecture News","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Implementation; Exploit; Database; Kernel (algebra); Software deployment; Operating system; Linux kernel; Distributed computing; Embedded system; Software engineering","score_opus":0.02720468784387153,"score_gpt":0.2631199432918902,"score_spread":0.23591525544801867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098666492","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017849607,0.0005455558,0.9746678,0.0048134704,0.00017640209,0.0007235789,0.000025189152,0.0010422221,0.00015619663],"genre_scores_gemma":[0.23380384,0.000037202983,0.7648203,0.00079529034,0.00010675966,0.00033108421,0.00003798554,0.000023546541,0.00004403319],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99769044,0.00012338883,0.0003057084,0.00086373603,0.00043415223,0.00058259076],"domain_scores_gemma":[0.99398637,0.0009063891,0.00017100784,0.004691896,0.000108007385,0.0001363058],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00020404559,0.0003425991,0.00031423254,0.00026284036,0.0003925612,0.00024481426,0.006149531,0.0000875558,0.000021114722],"category_scores_gemma":[0.000211661,0.0002656215,0.00007503011,0.0006086989,0.00035122395,0.0008956022,0.00274414,0.000441263,0.000023561734],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048363752,0.00021455802,0.00009307529,0.000059312977,0.000058876634,0.000057577894,0.024717847,0.0030664143,0.00092824816,0.00938558,0.017630288,0.94373983],"study_design_scores_gemma":[0.005858546,0.0043904106,0.0003377612,0.00048586403,0.000057772537,0.0008083544,0.0030349987,0.5929214,0.013859427,0.056875885,0.31769854,0.0036710745],"about_ca_topic_score_codex":0.000022218685,"about_ca_topic_score_gemma":0.00008870973,"teacher_disagreement_score":0.9400688,"about_ca_system_score_codex":0.000058636047,"about_ca_system_score_gemma":0.000030264535,"threshold_uncertainty_score":0.9999796},"labels":[],"label_agreement":null},{"id":"W2098881120","doi":"10.1109/hotos.1999.798369","title":"Elephant: the file system that never forgets","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Unix file types; File Control Block; Versioning file system; Computer science; Computer file; Stub file; File system; Operating system; File system fragmentation; Virtual file system; Self-certifying File System; SSH File Transfer Protocol; Directory; Fork (system call); Database; Device file; File server; Torrent file; Journaling file system","score_opus":0.018222592210603482,"score_gpt":0.2212282270985724,"score_spread":0.2030056348879689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098881120","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":[0.00022096097,0.0001981743,0.9686413,0.0005374098,0.00026229728,0.00015155035,0.00001688426,0.001356194,0.028615266],"genre_scores_gemma":[0.7291657,0.000013906335,0.26635987,0.0007095894,0.000016440625,0.00007142348,0.0000050206995,0.0000118157295,0.0036462345],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991776,0.000032729968,0.00009575894,0.0002610126,0.00017666658,0.00025628193],"domain_scores_gemma":[0.9985978,0.00014301846,0.000050109793,0.0011584787,0.000024399953,0.000026212832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013940106,0.00010184507,0.000091651695,0.00003774193,0.00015638034,0.00008094859,0.0012712097,0.000046348658,0.00011998465],"category_scores_gemma":[0.000106068765,0.000058533522,0.000032290223,0.00026634274,0.000053647378,0.0008783333,0.00032295048,0.000096991724,0.0002714736],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.2363874e-7,0.000006789879,0.000031509615,0.0000053912163,0.0000049849987,0.000015680254,0.00004806406,0.000016154663,0.00005366209,0.9251723,0.06610593,0.0085392],"study_design_scores_gemma":[0.0002151361,0.00004283717,0.00029256105,0.000024922676,0.000004036661,0.00016810949,0.0010767014,0.0076095643,0.030376967,0.014170824,0.94569725,0.00032108923],"about_ca_topic_score_codex":0.000009241692,"about_ca_topic_score_gemma":0.000007923856,"teacher_disagreement_score":0.9110015,"about_ca_system_score_codex":0.00004534619,"about_ca_system_score_gemma":0.000020156189,"threshold_uncertainty_score":0.34893346},"labels":[],"label_agreement":null},{"id":"W2099195886","doi":"10.1109/nas.2007.42","title":"PKI-Based Authentication Mechanisms in Grid Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Public key infrastructure; Computer science; Computer security; Authentication (law); Grid computing; Grid; Public-key cryptography; Encryption","score_opus":0.015863853912856014,"score_gpt":0.2572118093256899,"score_spread":0.24134795541283385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099195886","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":[0.0018994292,0.00004462971,0.99534696,0.00031257523,0.0005684609,0.00015731085,0.0000015039823,0.00083704764,0.0008320861],"genre_scores_gemma":[0.6711434,0.000001100565,0.32866868,0.00008055806,0.000013984779,0.000010893394,0.000003512272,0.0000037244931,0.00007415745],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912584,0.000013052976,0.0001919888,0.00026398982,0.00017629775,0.00022882283],"domain_scores_gemma":[0.99910426,0.00007998214,0.000056571,0.00069983775,0.000030425905,0.000028892355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046659427,0.00007715044,0.000085893735,0.00022954977,0.000030847394,0.00005060686,0.0007866891,0.0000610915,0.0000041005596],"category_scores_gemma":[0.00007373845,0.00006827215,0.000014387888,0.0004996074,0.000024816545,0.00039605136,0.00015137487,0.00008242532,0.000075745054],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001675461,0.000029371715,0.00006774971,0.0000069270254,0.0000010296205,0.000021210817,0.00003275117,0.0003487254,0.005358831,0.98619616,0.00022428925,0.0077112527],"study_design_scores_gemma":[0.0012229269,0.00022206365,0.004884677,0.000092265356,0.0000050144276,0.00003127463,0.0006459652,0.59432185,0.25216544,0.13458954,0.010994498,0.00082449446],"about_ca_topic_score_codex":0.000050527924,"about_ca_topic_score_gemma":0.00004068478,"teacher_disagreement_score":0.85160667,"about_ca_system_score_codex":0.00009000589,"about_ca_system_score_gemma":0.000020862732,"threshold_uncertainty_score":0.27840576},"labels":[],"label_agreement":null},{"id":"W2100343205","doi":"","title":"Reliable writeback for client-side flash caches","year":2014,"lang":"en","type":"article","venue":"TSpace (University of Toronto)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Reliability (semiconductor); Cache; Client-side; Flash (photography); False sharing; Cache coherence; Consistency (knowledge bases); Data consistency; Computer data storage; Database; Operating system; Data retention; Storage management; Computer network; CPU cache; Computer security; Cache algorithms","score_opus":0.0176692899574635,"score_gpt":0.23624701426257777,"score_spread":0.21857772430511427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100343205","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01174225,0.00022170953,0.958327,0.0015672931,0.00016120604,0.00020091886,0.000012180098,0.00046481623,0.02730266],"genre_scores_gemma":[0.42636696,0.0000865971,0.56903166,0.000044041124,0.000019054434,6.049623e-7,0.0000069113103,0.000007907187,0.0044362457],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991243,0.000018949713,0.00007246522,0.00035858105,0.00015482398,0.00027091833],"domain_scores_gemma":[0.99874556,0.00010517499,0.00013444517,0.00086154806,0.00009069799,0.00006258197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017647784,0.00011498816,0.00020683899,0.000037611615,0.00017046065,0.00001917631,0.001368405,0.00009288719,0.00016756682],"category_scores_gemma":[0.00008508445,0.00014139841,0.00007857499,0.000083354986,0.00013827984,0.0013247044,0.00061415555,0.00006765766,0.000047585192],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008913041,0.0001527934,0.0007274035,0.0001392396,0.00007292105,0.00001326885,0.0049682097,0.0005760771,0.005688502,0.34911636,0.03275774,0.60569835],"study_design_scores_gemma":[0.0051848353,0.0018954849,0.048194245,0.00018320174,0.00011803811,0.000018625566,0.014590395,0.15010266,0.010718267,0.020372214,0.7468112,0.00181082],"about_ca_topic_score_codex":0.005386698,"about_ca_topic_score_gemma":0.0065224776,"teacher_disagreement_score":0.71405345,"about_ca_system_score_codex":0.00016492876,"about_ca_system_score_gemma":0.000028959093,"threshold_uncertainty_score":0.8143112},"labels":[],"label_agreement":null},{"id":"W2101721476","doi":"10.1145/2039239.2039248","title":"Using declarative invariants for protecting file-system integrity","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; File system; Commit; Database transaction; Consistency (knowledge bases); Metadata; Database; Data integrity; Transaction processing system; Distributed transaction; Operating system; Transaction processing; Programming language","score_opus":0.24472601777339237,"score_gpt":0.322151297844076,"score_spread":0.07742528007068361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101721476","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018901074,0.000008976011,0.9935812,0.000025139077,0.00014446798,0.0005828447,0.000038480524,0.0011072862,0.0026215136],"genre_scores_gemma":[0.2564654,1.3838121e-7,0.7433622,0.00002422677,0.000012955737,0.000094950956,0.0000019599613,0.0000057729217,0.000032419848],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990548,0.00003976456,0.00018309803,0.00037193915,0.00009681511,0.00025358677],"domain_scores_gemma":[0.99898964,0.00014306241,0.00012538835,0.00059871865,0.00010985658,0.000033359604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029804907,0.000120773664,0.00014499512,0.00008851813,0.00021864336,0.00005301182,0.00094323803,0.00009166356,0.000031514995],"category_scores_gemma":[0.00063093635,0.00009825604,0.000034463017,0.0002886886,0.000047238904,0.0010666016,0.0005321003,0.0002290647,0.000017423974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023147846,0.00006397164,0.0001579549,0.000087937005,0.00003619193,0.000035283138,0.002358115,0.000021881548,0.0040556495,0.9387278,0.0011950505,0.053237017],"study_design_scores_gemma":[0.0007302272,0.00037430046,0.00037909232,0.00024582012,0.0000126379455,0.00016817809,0.0054214024,0.6038669,0.29447132,0.09205414,0.0014480776,0.000827936],"about_ca_topic_score_codex":0.0001253102,"about_ca_topic_score_gemma":0.000027195105,"teacher_disagreement_score":0.84667367,"about_ca_system_score_codex":0.00011082961,"about_ca_system_score_gemma":0.00005645338,"threshold_uncertainty_score":0.4006765},"labels":[],"label_agreement":null},{"id":"W2103172403","doi":"10.1109/ipdps.2007.370240","title":"A Utility-based Approach to Cost-Aware Caching in Heterogeneous Storage Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cache; Thrashing; Burstiness; Partition (number theory); Cache algorithms; Workload; Scheme (mathematics); Parallel computing; Disk buffer; Multitenancy; Computer network; CPU cache; Distributed computing; Operating system","score_opus":0.03398584122647023,"score_gpt":0.2786042204948897,"score_spread":0.24461837926841948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103172403","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":[0.023659933,0.00009115483,0.9725245,0.0000915326,0.00019735043,0.000686305,0.000010006932,0.0011586483,0.0015805501],"genre_scores_gemma":[0.8374174,5.9679667e-7,0.16216055,0.00029071176,0.0000129178725,0.000045516525,0.0000070417,0.00001157561,0.000053673168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99803615,0.000053236447,0.0003404208,0.0006821808,0.00031497452,0.00057301566],"domain_scores_gemma":[0.99828035,0.00014158081,0.00006618442,0.0013380515,0.00004793807,0.00012592667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007198987,0.00020219428,0.00024547486,0.0004195077,0.00008586044,0.00012030174,0.0015553271,0.000117839845,0.0000017863341],"category_scores_gemma":[0.0000937594,0.00018583429,0.000038517228,0.00088945194,0.00004467473,0.000389823,0.00039990383,0.00026051028,0.00002920156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058080688,0.00058997504,0.0048813345,0.00017098713,0.000019842031,0.0008249162,0.00083675125,0.87358016,0.0009126069,0.037245296,0.00077139,0.08010868],"study_design_scores_gemma":[0.00044365716,0.0000819557,0.0006520287,0.000037825208,0.0000018698803,0.00006245666,0.00032178336,0.986881,0.004207242,0.00021809245,0.006638686,0.00045337924],"about_ca_topic_score_codex":0.00021420135,"about_ca_topic_score_gemma":0.00018519339,"teacher_disagreement_score":0.8137575,"about_ca_system_score_codex":0.00019417921,"about_ca_system_score_gemma":0.000044985227,"threshold_uncertainty_score":0.75781024},"labels":[],"label_agreement":null},{"id":"W2103315535","doi":"10.1145/1416944.1416947","title":"An analysis of data corruption in the storage stack","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":284,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Division of Computer and Network Systems; Division of Computing and Communication Foundations; National Science Foundation","keywords":"Checksum; Computer science; Operating system","score_opus":0.08433212693739993,"score_gpt":0.33107942013400443,"score_spread":0.2467472931966045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103315535","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":[0.14568646,0.00005549269,0.85317814,0.00029211515,0.00009434967,0.00015828013,0.00027817997,0.00022126903,0.00003570264],"genre_scores_gemma":[0.92296815,0.00011507282,0.076627396,0.00012894467,0.0000081575,0.000019604895,0.00010008616,0.000008797112,0.000023769548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981834,0.0001670536,0.00032691928,0.0006140639,0.00046892322,0.0002396184],"domain_scores_gemma":[0.99276656,0.0002921829,0.00013975275,0.006706207,0.00005497302,0.000040301187],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00048907474,0.000168223,0.0002899964,0.00079236034,0.00020762088,0.00003831371,0.0056731305,0.00009652583,0.000029979326],"category_scores_gemma":[0.000068824316,0.00013676481,0.00007806792,0.0031729576,0.00018133593,0.002266901,0.00007439893,0.00036383444,0.000013837902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015855138,0.0039464324,0.002433568,0.000043561056,0.00078814407,0.000794809,0.013624433,0.56857777,0.0051793,0.009063963,0.0008522413,0.39453724],"study_design_scores_gemma":[0.0015975768,0.00113976,0.09934744,0.00004083991,0.0006488963,0.00012826339,0.003835082,0.87937504,0.0023957815,0.0028806918,0.007409712,0.0012009065],"about_ca_topic_score_codex":0.00015302357,"about_ca_topic_score_gemma":0.00038373165,"teacher_disagreement_score":0.7772817,"about_ca_system_score_codex":0.00008760113,"about_ca_system_score_gemma":0.00005260222,"threshold_uncertainty_score":0.9997066},"labels":[],"label_agreement":null},{"id":"W2107142121","doi":"10.1109/icpads.2008.110","title":"Orchestra: Extensible Block-Level Support for Resource and Data Sharing in Networked Storage Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; File system; Block (permutation group theory); Flexibility (engineering); File sharing; Object storage; Shared resource; Distributed computing; Storage area network; Operating system; Computer data storage; Computer network; The Internet","score_opus":0.1585405433690978,"score_gpt":0.3123323770058353,"score_spread":0.1537918336367375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107142121","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":[0.016066836,0.00044655366,0.9810642,0.00022600831,0.00012005517,0.00047911113,0.000060983595,0.0006946499,0.0008416175],"genre_scores_gemma":[0.59140706,0.0000852715,0.4063944,0.00012612555,0.00006239989,0.00005093906,0.00007475166,0.00002308013,0.0017759555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980659,0.000018158342,0.00030989238,0.0009882282,0.00017871046,0.00043915055],"domain_scores_gemma":[0.9970361,0.00018406005,0.00009067997,0.0025815952,0.000039219944,0.00006831957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005862149,0.00017009968,0.0002608377,0.000159326,0.00014359987,0.000100142584,0.0028426314,0.00010281111,0.0000014444807],"category_scores_gemma":[0.00022302689,0.00015700274,0.000015086957,0.0004202484,0.000116700336,0.0011004849,0.0031437783,0.00017842837,0.000005172166],"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":[0.00021803047,0.00069193717,0.028974252,0.0008343859,0.00019689326,0.004158631,0.0030809124,0.08778141,0.0038126498,0.4545032,0.31651253,0.099235155],"study_design_scores_gemma":[0.0010040198,0.00014294032,0.0031879763,0.0000684572,0.0000064420706,0.0006368788,0.00028101585,0.9340504,0.0002788192,0.0020502692,0.05775516,0.00053761085],"about_ca_topic_score_codex":0.00006978919,"about_ca_topic_score_gemma":0.000037050664,"teacher_disagreement_score":0.846269,"about_ca_system_score_codex":0.000051387273,"about_ca_system_score_gemma":0.000058800408,"threshold_uncertainty_score":0.6402386},"labels":[],"label_agreement":null},{"id":"W2108864584","doi":"10.1109/icis.2012.49","title":"Feasibility Evaluation of a Secured Architecture for 2-Party Mobile Payments (SA2pMP)","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Computer security; Mobile payment; Architecture; Non-repudiation; Java; Confidentiality; Authentication (law); Mobile device; Payment; Anonymity; Mobile computing; Cryptography; Process (computing); Embedded system; Computer network; Operating system; World Wide Web","score_opus":0.06159871054760551,"score_gpt":0.34975944236646656,"score_spread":0.28816073181886104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108864584","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":[0.13189818,0.00024529616,0.8658577,0.00010153147,0.00017393785,0.0011277725,0.00003067063,0.00026617752,0.00029869328],"genre_scores_gemma":[0.73786795,0.0000013983828,0.2618235,0.00003272855,0.00001536495,0.000218468,0.0000113095475,0.0000039482466,0.000025330119],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988144,0.00006044838,0.00019684211,0.00026639597,0.0003930359,0.00026886663],"domain_scores_gemma":[0.99861914,0.00010179858,0.00011575334,0.0009305326,0.00018620821,0.000046595902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010278437,0.00010405932,0.00014188462,0.000068323076,0.000047691967,0.0000141548735,0.0006242979,0.00006555128,0.000025221454],"category_scores_gemma":[0.00036717326,0.00008031608,0.0000525881,0.00023208358,0.000059708713,0.0006006798,0.00030145867,0.00007023528,0.0000067228607],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005392891,0.000829224,0.008561638,0.0001108629,0.000059084512,3.0048176e-7,0.0022034221,0.002464183,0.016389674,0.06674981,0.004040854,0.89853704],"study_design_scores_gemma":[0.005225238,0.00086843036,0.020605147,0.000047538568,0.00012898589,0.00002130089,0.0007001126,0.1419199,0.37350774,0.43266013,0.023263989,0.0010514868],"about_ca_topic_score_codex":0.0000048593124,"about_ca_topic_score_gemma":0.000010122221,"teacher_disagreement_score":0.89748555,"about_ca_system_score_codex":0.000090333204,"about_ca_system_score_gemma":0.00004400023,"threshold_uncertainty_score":0.32751948},"labels":[],"label_agreement":null},{"id":"W2109887171","doi":"10.1109/icpc.2011.15","title":"MTF: A Scalable Exchange Format for Traces of High Performance Computing Systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; TRACE (psycholinguistics); Scalability; Interoperability; Profiling (computer programming); Supercomputer; Visualization; Software; Distributed computing; Database; Computer architecture; Operating system; Data mining","score_opus":0.04273994929484595,"score_gpt":0.23893530420617692,"score_spread":0.19619535491133097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109887171","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":[0.096683465,0.000293291,0.90024984,0.000027108983,0.00029695814,0.0003273547,0.000009899612,0.00060084806,0.0015112311],"genre_scores_gemma":[0.69392735,0.00002569996,0.3058416,0.00001984783,0.0000133213225,0.000024000165,0.0000019309055,0.0000059669696,0.00014028774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989835,0.000010372731,0.00028592022,0.00025739725,0.00014853163,0.00031426313],"domain_scores_gemma":[0.99897516,0.000076429125,0.00018589917,0.0006402911,0.000090567766,0.00003163398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025816826,0.00012462966,0.00022809705,0.00012266512,0.0001016492,0.000034067543,0.0011578358,0.0000663366,0.0000059171684],"category_scores_gemma":[0.000032510652,0.00010104076,0.00003174643,0.0002742171,0.000074327865,0.0013004416,0.00044093194,0.00006566921,0.00001338429],"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":[0.00004320626,0.00019738043,0.0014311491,0.0015156104,0.000051150397,0.0000061055807,0.0035948742,0.0009793601,0.00093901815,0.6915691,0.0048716264,0.29480144],"study_design_scores_gemma":[0.00101011,0.0008090068,0.0018018857,0.00020615391,0.000013091094,0.000053959095,0.0007866235,0.8791955,0.10335971,0.007014234,0.0051844986,0.00056523696],"about_ca_topic_score_codex":0.00009986647,"about_ca_topic_score_gemma":0.000005041491,"teacher_disagreement_score":0.87821615,"about_ca_system_score_codex":0.000031626627,"about_ca_system_score_gemma":0.000014347111,"threshold_uncertainty_score":0.41203225},"labels":[],"label_agreement":null},{"id":"W2110322986","doi":"10.1145/2078861.2078864","title":"A study of practical deduplication","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":472,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Data deduplication; Backup; Computer file; Versioning file system; Database; Metadata; Operating system; File system; Journaling file system; Torrent file; Redundancy (engineering); Unix file types; Block (permutation group theory); Stub file","score_opus":0.060825716607118115,"score_gpt":0.34191669874171865,"score_spread":0.28109098213460054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110322986","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":[0.11195773,0.00003453527,0.88659453,0.00046770944,0.00019884814,0.00025363328,0.0000052911532,0.00036669758,0.000121038975],"genre_scores_gemma":[0.8258139,0.0000066893194,0.17401005,0.000049730083,0.000012261378,0.00006866473,7.8986477e-7,0.0000074405557,0.000030495834],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99901783,0.000055318644,0.00019935306,0.00024558176,0.00026058897,0.00022130301],"domain_scores_gemma":[0.9976996,0.00023265036,0.00010219243,0.0018519342,0.000050491686,0.00006309478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019581358,0.000111302936,0.00013762021,0.00017427035,0.000110006185,0.000018895475,0.00078805105,0.000062541614,0.00001571376],"category_scores_gemma":[0.00013690628,0.00010505372,0.000035607853,0.00053756894,0.00004778194,0.0012901863,0.000040552077,0.00022892465,0.00006744152],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013806684,0.02471308,0.0019333465,0.0000554769,0.0003104922,0.00006853678,0.015833305,0.0039534336,0.01031769,0.08639187,0.0016413456,0.85464334],"study_design_scores_gemma":[0.020706618,0.02351654,0.15274706,0.00029057002,0.0011965225,0.001954351,0.06600766,0.019995166,0.5010775,0.077438384,0.12660743,0.00846222],"about_ca_topic_score_codex":0.00001340181,"about_ca_topic_score_gemma":0.000007078559,"teacher_disagreement_score":0.84618115,"about_ca_system_score_codex":0.00006321313,"about_ca_system_score_gemma":0.000024013088,"threshold_uncertainty_score":0.4283966},"labels":[],"label_agreement":null},{"id":"W2110392960","doi":"10.1109/hpdc.2000.868638","title":"Using idle workstations to implement predictive prefetching","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Instruction prefetch; Node (physics); Overhead (engineering); Workstation; Idle; Latency (audio); Parallel computing; Real-time computing; Operating system; Distributed computing; Cache","score_opus":0.09251097730147671,"score_gpt":0.32582116714916337,"score_spread":0.23331018984768664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110392960","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042851977,0.00003347168,0.9910637,0.00092220725,0.00010974888,0.0002017931,0.0000092442315,0.0008138234,0.0025608225],"genre_scores_gemma":[0.35053855,0.0000032005173,0.649097,0.000199503,0.000012049663,0.00001649419,8.513567e-7,0.000004013125,0.0001283154],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991506,0.0000133104095,0.00013905624,0.0002943492,0.0001588245,0.00024391028],"domain_scores_gemma":[0.9992302,0.000050246697,0.000038051803,0.000588501,0.000038016424,0.000054972203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000067657056,0.00008538646,0.00007483501,0.0001259001,0.00014850561,0.000085004634,0.00066981744,0.000025051057,0.000072978786],"category_scores_gemma":[0.000077963436,0.000078082696,0.00001793646,0.00048934156,0.000013971545,0.00085912773,0.0006729156,0.00008445384,0.00007524391],"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":[0.0000032755704,0.00013913913,0.00045694443,0.000007704995,0.000039876533,0.00002736216,0.004614312,0.043737922,0.0036137453,0.6034665,0.01724248,0.3266507],"study_design_scores_gemma":[0.00024349337,0.00014967857,0.000340768,0.000027350923,0.0000065652494,0.000016385913,0.00071990426,0.95260686,0.004954415,0.026609674,0.013974559,0.00035037004],"about_ca_topic_score_codex":0.000019546496,"about_ca_topic_score_gemma":0.000016562773,"teacher_disagreement_score":0.9088689,"about_ca_system_score_codex":0.000106416766,"about_ca_system_score_gemma":0.000008046506,"threshold_uncertainty_score":0.318412},"labels":[],"label_agreement":null},{"id":"W2110393482","doi":"10.1109/grid.2010.5697971","title":"Towards automating the configuration of a distributed storage system","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Flexibility (engineering); Overhead (engineering); Distributed computing; Object storage; Computer data storage; Software deployment; Converged storage; Embedded system; Task (project management); Distributed data store; Information repository; Operating system; Systems engineering; Engineering","score_opus":0.012594729904001033,"score_gpt":0.24751741188268575,"score_spread":0.2349226819786847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110393482","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":[0.025423335,0.000008469535,0.9706378,0.00057674095,0.00025218638,0.00013359047,0.00001813858,0.0011309498,0.001818803],"genre_scores_gemma":[0.88270885,2.530266e-7,0.11722374,0.00001642503,0.000011684379,0.000012301208,0.000006309905,0.0000026822847,0.000017738514],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999324,0.000021458629,0.00018962927,0.0001620255,0.0001788971,0.00012396964],"domain_scores_gemma":[0.99881214,0.000082891645,0.00014470647,0.0008562081,0.00008654766,0.000017513552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000249184,0.000073506424,0.00010170074,0.000036107627,0.00009255997,0.000059890317,0.0010776974,0.00005413742,0.000007474731],"category_scores_gemma":[0.0002467892,0.000044899938,0.000024468056,0.00029847497,0.00011990896,0.00042323343,0.00028365047,0.00016012165,0.000012603856],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.6109e-7,0.0000073915485,0.000015231384,0.000015820006,0.0000042853594,0.0000032340847,0.00011243103,0.00006022222,0.030735781,0.9396691,0.0002705358,0.029105404],"study_design_scores_gemma":[0.0002973237,0.00007420717,0.0026441047,0.000037284233,0.0000080447,0.00007237893,0.0012602502,0.6171056,0.36954224,0.0059596784,0.0027364152,0.00026244766],"about_ca_topic_score_codex":0.000030350318,"about_ca_topic_score_gemma":0.000013070916,"teacher_disagreement_score":0.93370944,"about_ca_system_score_codex":0.000024089752,"about_ca_system_score_gemma":0.000039092076,"threshold_uncertainty_score":0.20026478},"labels":[],"label_agreement":null},{"id":"W2110940180","doi":"10.1109/spdp.1996.570344","title":"Fast deterministic sorting on large parallel machines","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Sorting; Sorting algorithm; Parallel computing; Sorting network; sort; Quicksort; Algorithm; Parallel algorithm","score_opus":0.027714846978223042,"score_gpt":0.26610458432294826,"score_spread":0.2383897373447252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110940180","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":[0.002782228,0.00005582256,0.97791183,0.0007096441,0.0001333559,0.000076595694,0.0000044399367,0.0014338691,0.016892198],"genre_scores_gemma":[0.7372142,0.00001138728,0.2608835,0.0005799341,0.000022774453,0.000011753818,0.000001391838,0.000007635487,0.0012674282],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989854,0.0000135998225,0.00016821089,0.000348926,0.0001611422,0.00032270915],"domain_scores_gemma":[0.9989874,0.000087995875,0.0000699642,0.0007994791,0.000016090125,0.00003911164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006995225,0.0001282867,0.00011781365,0.000084504965,0.00013386246,0.00007445883,0.0010084909,0.000045583998,0.000093836316],"category_scores_gemma":[0.00019163592,0.00010250047,0.00003165832,0.00020594898,0.000035564095,0.00038847828,0.0004755064,0.00013211106,0.0006153641],"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":[0.0000017220159,0.00012244664,0.00060142955,0.000008673783,0.000006642544,0.00015085317,0.000173549,0.000369708,0.0001634163,0.5132505,0.0039102007,0.4812408],"study_design_scores_gemma":[0.00045248866,0.00021146784,0.00065798074,0.00002041791,0.0000031686368,0.000048943515,0.000054909953,0.9562167,0.0005809917,0.030574543,0.010738863,0.00043955364],"about_ca_topic_score_codex":0.0000024763292,"about_ca_topic_score_gemma":0.000009265736,"teacher_disagreement_score":0.95584697,"about_ca_system_score_codex":0.000020677742,"about_ca_system_score_gemma":0.0000030536578,"threshold_uncertainty_score":0.7909466},"labels":[],"label_agreement":null},{"id":"W2111784404","doi":"10.1109/icdcs.1993.287729","title":"Disk cache replacement policies for network fileservers","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Workstation; Cache; Locality of reference; Server; Operating system; File server; TRACE (psycholinguistics); Locality; Cache algorithms; Simple (philosophy); Database; CPU cache; Parallel computing; Computer network","score_opus":0.039985590265764856,"score_gpt":0.2634735135983115,"score_spread":0.22348792333254663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111784404","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000598155,0.0002447862,0.9890737,0.0037083111,0.0001979869,0.00024510507,0.000011805971,0.0010250383,0.004895119],"genre_scores_gemma":[0.11072957,0.000089679896,0.8796715,0.001147728,0.00010164621,0.00013454106,0.000009259121,0.000012902324,0.008103185],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99904794,0.000010146139,0.00014409782,0.0003101352,0.00012710884,0.00036058956],"domain_scores_gemma":[0.99879044,0.000118898766,0.000055728626,0.00096738094,0.000028865972,0.000038681403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000108343076,0.00010791216,0.00010946405,0.000042720807,0.00013675597,0.00006869009,0.0010356678,0.000046511057,0.00008129104],"category_scores_gemma":[0.00011791746,0.00008943588,0.000044472443,0.00028777137,0.000054397733,0.00046404958,0.0005385521,0.00006287871,0.000057861016],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035892617,0.00003265546,0.00028522452,0.000008504322,0.000015120743,0.0000027712374,0.00017072524,0.002020925,0.00003590453,0.4281812,0.53265053,0.03659283],"study_design_scores_gemma":[0.00068059616,0.0003832926,0.00034653602,0.0000186129,0.000008238628,0.000011548072,0.00022075091,0.22463453,0.002235651,0.056846138,0.71409833,0.0005157568],"about_ca_topic_score_codex":0.00002343816,"about_ca_topic_score_gemma":0.00002660159,"teacher_disagreement_score":0.37133506,"about_ca_system_score_codex":0.000055560766,"about_ca_system_score_gemma":0.0000050054787,"threshold_uncertainty_score":0.36470896},"labels":[],"label_agreement":null},{"id":"W2111814008","doi":"10.1109/tpds.2010.157","title":"ThriftStore: Finessing Reliability Trade-Offs in Replicated Storage Systems","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Throughput; Bandwidth (computing); Reliability (semiconductor); Architecture; High availability; Computer data storage; Computer network; Distributed computing; Systems architecture; Embedded system; Operating system; Wireless","score_opus":0.0165005753718929,"score_gpt":0.24743473369973393,"score_spread":0.23093415832784103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111814008","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":[0.048876803,0.00029782223,0.9465823,0.00051164057,0.0017585914,0.0006219324,0.00035491356,0.000934382,0.00006158955],"genre_scores_gemma":[0.99646276,0.00004220002,0.0030797427,0.000018901173,0.000030617888,0.00025958984,0.000035876514,0.000018339255,0.000051972776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997495,0.00013603439,0.000646552,0.0009244906,0.0003260932,0.00047181634],"domain_scores_gemma":[0.99770266,0.00022936332,0.00020288498,0.0016472398,0.00006452639,0.00015332182],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000516559,0.00033285422,0.00048319122,0.00022767452,0.00030648994,0.0002813826,0.00079013826,0.0003482691,0.000002602246],"category_scores_gemma":[0.000052018426,0.00029772753,0.00007312554,0.0008900009,0.00020825192,0.00080682134,0.000012376392,0.00085969595,0.000015375144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010108464,0.00065473974,0.0005568066,0.00027406265,0.000045860572,0.0001476372,0.00034754327,0.9694066,0.009068834,0.010608,0.0010435134,0.0077452967],"study_design_scores_gemma":[0.0024738389,0.00028192034,0.004276909,0.00027926324,0.00003300858,0.00044196512,0.0006699708,0.9764062,0.00086547754,0.0009686791,0.012024215,0.0012785593],"about_ca_topic_score_codex":0.00037309687,"about_ca_topic_score_gemma":0.00007955546,"teacher_disagreement_score":0.94758594,"about_ca_system_score_codex":0.00012902911,"about_ca_system_score_gemma":0.00007042615,"threshold_uncertainty_score":0.9999475},"labels":[],"label_agreement":null},{"id":"W2112363973","doi":"10.1109/icdcs.1995.500051","title":"Write caching in distributed file systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; False sharing; Locality; Cache; Server; Operating system; File server; Locality of reference; Disk buffer; Working set; Set (abstract data type); Computer network; CPU cache; Distributed computing; Cache algorithms","score_opus":0.02268571062857998,"score_gpt":0.22740399676305845,"score_spread":0.20471828613447846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112363973","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":[0.0016018666,0.0002820552,0.99348325,0.0003831596,0.00012769715,0.00009607942,0.00012638215,0.0010274352,0.002872109],"genre_scores_gemma":[0.9351796,0.000024751129,0.06391622,0.00006580058,0.00001395582,0.00003297586,0.000039366696,0.0000056257754,0.00072171463],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992441,0.000019133622,0.00014911949,0.0002501755,0.000116015275,0.00022147571],"domain_scores_gemma":[0.9991992,0.00009392301,0.000037458944,0.00062940706,0.000014097046,0.000025872823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007061446,0.00007948631,0.0001048568,0.00009637273,0.00004256439,0.000088522116,0.0008321155,0.00004707961,0.00013765747],"category_scores_gemma":[0.00010466322,0.000069674265,0.000013959765,0.00047151936,0.000024367357,0.0006950594,0.0002636945,0.00013357872,0.0001879527],"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":[0.0000021580747,0.00025261662,0.0021469041,0.00005868393,0.000017362705,0.0006930232,0.00065821473,0.02288321,0.00085550937,0.47682965,0.37306184,0.12254084],"study_design_scores_gemma":[0.00024019703,0.000032449247,0.00083811616,0.00004179323,7.2483664e-7,0.000039959785,0.00013166506,0.93075114,0.00028959537,0.0017138692,0.065650865,0.0002696088],"about_ca_topic_score_codex":0.00008972358,"about_ca_topic_score_gemma":0.000024769004,"teacher_disagreement_score":0.9335777,"about_ca_system_score_codex":0.000066104614,"about_ca_system_score_gemma":0.000002800361,"threshold_uncertainty_score":0.28412342},"labels":[],"label_agreement":null},{"id":"W2114316312","doi":"10.1109/hicss.1999.773042","title":"Evaluation of the JIAJIA software DSM system on high performance computer architectures","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Center for High Performance Computing; National Science Foundation","keywords":"Computer science; Scalability; IBM; Distributed shared memory; Suite; Usability; Replication (statistics); Computer architecture; Software; Distributed computing; Operating system; Distributed memory; Consistency (knowledge bases); System software; Shared memory; Memory management; Uniform memory access","score_opus":0.021790776632056447,"score_gpt":0.2448394294747407,"score_spread":0.22304865284268424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114316312","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":[0.2916943,0.00004027924,0.70613945,0.00009602326,0.00041890048,0.0002580814,0.0000028353456,0.00042978983,0.000920367],"genre_scores_gemma":[0.829764,9.752137e-7,0.17008981,0.00008811749,0.0000115983485,0.00001624943,5.453327e-7,0.0000048452034,0.000023824457],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984459,0.0001593083,0.00017758347,0.00028055822,0.0007680263,0.0001685735],"domain_scores_gemma":[0.9983881,0.00009307442,0.00011987891,0.0012031065,0.00017861818,0.000017211483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006620464,0.00011848553,0.00012250022,0.000079681646,0.00011160157,0.00002659609,0.0010729139,0.000052207397,0.0000069310636],"category_scores_gemma":[0.00015889737,0.00007082509,0.00003415367,0.0003370824,0.000073247786,0.00014151284,0.00025792306,0.00013431949,0.000020248639],"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":[0.0000034453437,0.0000488094,0.00081613805,0.00005951169,0.00002470973,0.000001270331,0.00016026404,0.13211504,0.00017754787,0.31077057,0.00066567323,0.555157],"study_design_scores_gemma":[0.0014097801,0.00047695095,0.059048746,0.00037726297,0.00005984728,0.0000927944,0.000100588215,0.6859166,0.22012776,0.030185524,0.001561565,0.0006426004],"about_ca_topic_score_codex":0.000005819508,"about_ca_topic_score_gemma":0.0000030888502,"teacher_disagreement_score":0.5545144,"about_ca_system_score_codex":0.00011615387,"about_ca_system_score_gemma":0.00007184431,"threshold_uncertainty_score":0.28881633},"labels":[],"label_agreement":null},{"id":"W2114345510","doi":"10.1109/cnsr.2011.21","title":"Tuning Open-iSCSI for Operation over WAN Links","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"iSCSI; Computer science; Throughput; Computer network; SCSI; Operating system; Computer data storage; Wireless","score_opus":0.07885874074965683,"score_gpt":0.3057196574736718,"score_spread":0.22686091672401498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114345510","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010669075,0.0000176699,0.98634785,0.00030069792,0.00015885841,0.0002949572,0.0000033436045,0.0005284302,0.011281301],"genre_scores_gemma":[0.21154742,0.0000039524343,0.78716177,0.00044311595,0.000013818387,0.00005035981,0.0000052778864,0.000005996998,0.00076826],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99933356,0.000008108686,0.00012015302,0.00029645392,0.000071419905,0.00017028667],"domain_scores_gemma":[0.99918807,0.000030886535,0.00004060691,0.0006717052,0.000041951513,0.000026785963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014264257,0.00007980081,0.000087431625,0.000053159343,0.00011795504,0.00016630969,0.0017913075,0.00008908844,0.000056785593],"category_scores_gemma":[0.00007689345,0.00006565025,0.000017743392,0.00012091193,0.000030754312,0.002123734,0.0011793661,0.000106364045,0.000038084836],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004529099,0.000026941978,0.00009883273,0.0000031095763,0.000004951734,0.0000032721473,0.00035953635,0.000013048429,0.00184436,0.88309234,0.0037801778,0.11076889],"study_design_scores_gemma":[0.002160558,0.0008326521,0.0027092325,0.000045118155,0.000012490126,0.000024612324,0.00053920294,0.2754998,0.21515031,0.36069825,0.14118679,0.0011409962],"about_ca_topic_score_codex":0.000043564483,"about_ca_topic_score_gemma":0.000031246695,"teacher_disagreement_score":0.52239406,"about_ca_system_score_codex":0.000024663581,"about_ca_system_score_gemma":0.000026008596,"threshold_uncertainty_score":0.33287248},"labels":[],"label_agreement":null},{"id":"W2114891487","doi":"10.1109/ast.1996.506631","title":"Java and JDBC: tools supporting data-centric business application development","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Operating system; Software deployment; The Internet; Porting; Unix; Software engineering; Windows NT; User interface; Java; World Wide Web; Software","score_opus":0.06223660820217076,"score_gpt":0.2747926066338407,"score_spread":0.21255599843166995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114891487","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003109842,0.00026356653,0.99367964,0.0009884333,0.00004446195,0.00016736862,0.000004031798,0.0007005733,0.0010420604],"genre_scores_gemma":[0.311016,0.00011393413,0.6884038,0.00016268285,0.000014393775,0.00002097742,0.000048699447,0.000006037472,0.00021351103],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99887824,0.000007085549,0.00022130024,0.0005006042,0.00016093173,0.00023182153],"domain_scores_gemma":[0.9985491,0.00005469906,0.000102547514,0.0012014138,0.000055109947,0.000037143214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016238804,0.00010068418,0.00009927921,0.00008679593,0.000111213565,0.00014595159,0.0013347635,0.000041723684,0.000017952641],"category_scores_gemma":[0.00020421234,0.00008836244,0.00000419449,0.0005910177,0.00003783763,0.0017689303,0.0017870098,0.000064645945,0.00011548193],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.1658667e-7,0.000019932886,0.00042625514,0.000008117902,0.000002679486,0.000005250042,0.000052705625,0.0000054234606,0.00020341828,0.010709135,0.0012047857,0.9873621],"study_design_scores_gemma":[0.00073661766,0.000028164703,0.028755687,0.000028804583,0.000010579223,0.00014995695,0.00021119729,0.2231276,0.009868137,0.003968704,0.7320939,0.001020655],"about_ca_topic_score_codex":0.0000051551065,"about_ca_topic_score_gemma":0.000006716553,"teacher_disagreement_score":0.9863414,"about_ca_system_score_codex":0.000034802284,"about_ca_system_score_gemma":0.00001754061,"threshold_uncertainty_score":0.36033157},"labels":[],"label_agreement":null},{"id":"W2115798340","doi":"10.1109/hipc.2010.5713192","title":"iWARP redefined: Scalable connectionless communication over high-speed Ethernet","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Datagram; Computer science; InfiniBand; Computer network; Connectionless communication; Scalability; Remote direct memory access; Ethernet; Operating system; Embedded system; Distributed computing; Network packet","score_opus":0.01358151366525739,"score_gpt":0.25452464263290064,"score_spread":0.24094312896764325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115798340","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":[0.11531986,0.00009053133,0.85982066,0.0064966828,0.0005887723,0.00022970425,0.000011425437,0.0030973926,0.014344944],"genre_scores_gemma":[0.6968469,0.000022252598,0.30192423,0.00022671749,0.000018091705,0.000009075034,0.000011275089,0.000008805839,0.00093266554],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99905413,0.00003147114,0.00017888346,0.00033344718,0.00018332501,0.00021872084],"domain_scores_gemma":[0.9973808,0.0001605775,0.00009676626,0.0022339064,0.000084440384,0.000043535376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023710997,0.0001239981,0.00013336586,0.000098118,0.0001642345,0.00013955309,0.0018018326,0.00014329588,0.00019681356],"category_scores_gemma":[0.00018341567,0.00010960959,0.000025977226,0.00040631197,0.000152264,0.0009456652,0.00088226865,0.00039184926,0.00022514339],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026340924,0.000038055532,0.00021943817,0.0000020441516,0.000006015179,0.0000018070394,0.000051066094,0.0000483694,0.015966997,0.95474637,0.007962404,0.020954784],"study_design_scores_gemma":[0.0014764746,0.00014096816,0.0069787805,0.000026236674,0.000011519513,0.0000725253,0.00018369361,0.061635654,0.17832096,0.5977722,0.15240642,0.0009746072],"about_ca_topic_score_codex":0.00056859833,"about_ca_topic_score_gemma":0.0005333873,"teacher_disagreement_score":0.58152705,"about_ca_system_score_codex":0.000032628825,"about_ca_system_score_gemma":0.000026706315,"threshold_uncertainty_score":0.44697493},"labels":[],"label_agreement":null},{"id":"W2115870684","doi":"10.1109/icdcs.1990.89274","title":"Disk cache performance for distributed systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Cache; Page cache; Disk buffer; Operating system; Cache algorithms; Block size; Block (permutation group theory); Parallel computing; Cache invalidation; Cache pollution; CPU cache; Locality of reference; TRACE (psycholinguistics); File system","score_opus":0.0333135820871159,"score_gpt":0.23618983498123425,"score_spread":0.20287625289411834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115870684","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":[0.0026993372,0.00028822268,0.99384224,0.0004980552,0.00024655717,0.00023898542,0.00004981452,0.0011866869,0.00095011515],"genre_scores_gemma":[0.9035344,0.000045235523,0.09501848,0.00004404264,0.000025603927,0.00009920128,0.00001544255,0.0000061877995,0.001211386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992015,0.0000068694644,0.00014051067,0.0002734488,0.000116667296,0.00026101054],"domain_scores_gemma":[0.9990362,0.00007142042,0.000050951174,0.0007605245,0.000045954454,0.000034982964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007480279,0.00009893855,0.00011270704,0.00004419195,0.00011130761,0.00008784887,0.0010017207,0.000051163803,0.000008463652],"category_scores_gemma":[0.00008222889,0.00007814309,0.000026401727,0.0002638496,0.0000433697,0.000740461,0.0002509293,0.000066912755,0.000085861364],"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":[0.0000058905866,0.00015230848,0.0013856927,0.00015469763,0.00003641789,0.000014998673,0.00019965449,0.0056763017,0.00059802976,0.6047222,0.11072177,0.27633205],"study_design_scores_gemma":[0.00022398231,0.00008444239,0.00018505126,0.000009903881,0.0000024134047,0.0000146233915,0.00003665603,0.91128397,0.0013379027,0.00069777574,0.085942164,0.0001811132],"about_ca_topic_score_codex":0.000004836534,"about_ca_topic_score_gemma":0.0000011877261,"teacher_disagreement_score":0.9056077,"about_ca_system_score_codex":0.000050018647,"about_ca_system_score_gemma":0.000004225793,"threshold_uncertainty_score":0.3186583},"labels":[],"label_agreement":null},{"id":"W2116377465","doi":"10.1109/hpcs.2006.18","title":"Design, Deployment and Bench of a Large Infiniband HPC Cluster","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke","funders":"Cisco Systems","keywords":"InfiniBand; Software deployment; Computer science; Benchmark (surveying); Cluster (spacecraft); Computer architecture; Supercomputer; Operating system","score_opus":0.014615354897189117,"score_gpt":0.24793024243660572,"score_spread":0.2333148875394166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116377465","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":[0.015678652,0.00020416065,0.9824987,0.0004725757,0.000030447158,0.00012872923,0.000002895344,0.0002634019,0.00072045164],"genre_scores_gemma":[0.54651994,0.000011854105,0.45314658,0.0001446301,0.000004934516,0.000007750658,0.0000010949143,0.000003398291,0.00015981024],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993157,0.000016111258,0.0001531281,0.00021907924,0.00012231618,0.00017369278],"domain_scores_gemma":[0.9993856,0.00007689924,0.000054520067,0.0004371275,0.00002819154,0.000017649962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013975648,0.0000805694,0.00010758,0.000076258104,0.000036625665,0.000028510243,0.00038312518,0.000043209995,0.000008022505],"category_scores_gemma":[0.000023096813,0.00006432827,0.000012125364,0.0001722076,0.000052971125,0.00037862797,0.00051292,0.000050127885,0.0000057252246],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003137244,0.00049954455,0.009887096,0.00007848578,0.000040401654,0.000060227663,0.00056233455,0.0015216885,0.021211721,0.81642836,0.046261024,0.103417724],"study_design_scores_gemma":[0.0029266905,0.0007863811,0.011270504,0.000057576686,0.000021768443,0.000096594005,0.00016864554,0.114482075,0.5626704,0.267322,0.039153066,0.0010442892],"about_ca_topic_score_codex":0.000030985644,"about_ca_topic_score_gemma":0.000030304975,"teacher_disagreement_score":0.54910636,"about_ca_system_score_codex":0.000013265534,"about_ca_system_score_gemma":0.000012642296,"threshold_uncertainty_score":0.26232305},"labels":[],"label_agreement":null},{"id":"W2116490604","doi":"10.1109/wescan.1991.160552","title":"An approach to benchmarking storage reclamation strategies","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Lisp; Computer science; Interpreter; Garbage collection; Pascal (unit); Programming language; Storage management; Modular design; Operating system; Database; Virtual machine; Garbage","score_opus":0.036061467414193804,"score_gpt":0.2607875548474177,"score_spread":0.22472608743322392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116490604","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005221095,0.00003399802,0.949659,0.00025440942,0.00010163451,0.00014308284,0.0000014414484,0.0014816395,0.043103702],"genre_scores_gemma":[0.48100427,0.0000042239008,0.5187426,0.000109197135,0.000022410684,0.000015862543,0.000003603339,0.0000041880803,0.000093611874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989371,0.000028596914,0.00014573122,0.00044076485,0.00020685823,0.0002409609],"domain_scores_gemma":[0.99876976,0.000023896098,0.000046081983,0.0010560146,0.00003853174,0.00006569369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013645047,0.00011976029,0.00010374531,0.00016380612,0.00011645076,0.00033379009,0.0012543036,0.00006111081,0.00003506736],"category_scores_gemma":[0.000029402467,0.00010779189,0.000017559158,0.00055568013,0.000030498308,0.0030639237,0.00024987038,0.000108402724,0.00009552246],"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":[8.2034086e-7,0.00010418722,0.000022673232,0.000007799282,0.000003830972,0.0000060575503,0.001005076,0.011529441,0.0019037878,0.74696153,0.003080984,0.23537378],"study_design_scores_gemma":[0.00013364424,0.00018911385,0.00058052054,0.000008484454,0.0000020531986,0.000020664107,0.0011226459,0.9684512,0.001676598,0.022252759,0.0051471367,0.0004151605],"about_ca_topic_score_codex":0.000010799914,"about_ca_topic_score_gemma":0.0000042874767,"teacher_disagreement_score":0.95692176,"about_ca_system_score_codex":0.000055067714,"about_ca_system_score_gemma":0.0000084896155,"threshold_uncertainty_score":0.4395626},"labels":[],"label_agreement":null},{"id":"W2117183326","doi":"10.1109/sc.2005.63","title":"SCTP versus TCP for MPI","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stream Control Transmission Protocol; Computer science; Transmission Control Protocol; Computer network; Message passing; Transport layer; Message Passing Interface; Middleware (distributed applications); Protocol (science); Distributed computing; Operating system; Layer (electronics); Network packet","score_opus":0.03924608240404513,"score_gpt":0.3029611437317632,"score_spread":0.26371506132771805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117183326","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005922288,0.0000646169,0.98816824,0.003397723,0.000241372,0.00010431258,0.00000348845,0.0011708033,0.0062572444],"genre_scores_gemma":[0.080985144,0.0000070125907,0.91761863,0.00029055326,0.00004926198,0.000024035437,0.0000018789694,0.0000041405624,0.0010193458],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994279,0.0000027773854,0.000079645084,0.00022317932,0.000082268874,0.00018419659],"domain_scores_gemma":[0.9992245,0.00009990067,0.000024447014,0.0005984728,0.000028114475,0.000024606998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005674105,0.00006369467,0.00006269903,0.000049014878,0.000055184162,0.00004072891,0.0009024032,0.0000362701,0.000018037646],"category_scores_gemma":[0.000116707066,0.000054497392,0.00002525041,0.00014347794,0.00003304003,0.0006790188,0.0003099498,0.00004324196,0.00016992805],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007431227,0.000013116502,0.0000033768056,0.0000015791062,0.0000036046872,0.0000010943677,0.000020102758,0.00009100475,0.0002814701,0.55719167,0.022585472,0.41980007],"study_design_scores_gemma":[0.0009743145,0.00014933372,0.000027986134,0.000002535418,0.000002202055,0.000003420421,0.000039220646,0.036600653,0.032440536,0.018108875,0.9114452,0.00020569428],"about_ca_topic_score_codex":0.0000017839401,"about_ca_topic_score_gemma":0.000016698279,"teacher_disagreement_score":0.88885975,"about_ca_system_score_codex":0.000038541322,"about_ca_system_score_gemma":0.000014869223,"threshold_uncertainty_score":0.2222339},"labels":[],"label_agreement":null},{"id":"W2117703974","doi":"10.1109/vtsa.2003.1252545","title":"The performance and reliability enhancement of ETOX p-channel flash EEPROM cell with p-doped floating-gate","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"EEPROM; EPROM; Flash (photography); Charge trap flash; Reliability (semiconductor); Computer science; Channel (broadcasting); Flash memory; Electrical engineering; Logic gate; Electronic engineering; Optoelectronics; Materials science; Computer hardware; Engineering; NAND gate; Physics","score_opus":0.007670187997594879,"score_gpt":0.21036266264731956,"score_spread":0.20269247464972467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117703974","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":[0.5195446,0.00007338619,0.47854766,0.00052908907,0.000038140686,0.00019826669,0.0000014397052,0.00016719755,0.00090020103],"genre_scores_gemma":[0.7992651,0.00018482794,0.20023839,0.00003900448,0.000004368406,0.000015452004,8.349615e-7,0.0000048632414,0.0002471783],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99888575,0.000015266329,0.00022506839,0.0003863294,0.00023530376,0.000252254],"domain_scores_gemma":[0.998629,0.000072580726,0.0001386037,0.0010376457,0.000088815235,0.00003340423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003083546,0.00013558131,0.00013880717,0.000030593434,0.00019458524,0.000048167727,0.00078472553,0.000038816906,0.000001877236],"category_scores_gemma":[0.000048184775,0.000078853234,0.000015449985,0.00025567418,0.00028816724,0.00053180807,0.00061227725,0.00013740036,0.000011457267],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066869706,0.0023517886,0.0057321354,0.0015952295,0.00019412131,0.00009371556,0.015393649,0.22936648,0.14733851,0.23206548,0.002939715,0.36226046],"study_design_scores_gemma":[0.000859345,0.00082093093,0.0008663019,0.000047961457,0.00000575978,0.0000086012005,0.00023000673,0.023140568,0.96227586,0.009973645,0.0014956052,0.00027543414],"about_ca_topic_score_codex":0.000028664688,"about_ca_topic_score_gemma":0.000021314636,"teacher_disagreement_score":0.81493735,"about_ca_system_score_codex":0.00004915696,"about_ca_system_score_gemma":0.000050456198,"threshold_uncertainty_score":0.32155415},"labels":[],"label_agreement":null},{"id":"W2119092821","doi":"10.1145/2366231.2337161","title":"RAIDR","year":2012,"lang":"en","type":"article","venue":"ACM SIGARCH Computer Architecture News","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":449,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada; Samsung; National Science Foundation","keywords":"Dram; Memory controller; Computer science; Row; Dynamic random-access memory; CAS latency; Embedded system; Universal memory; Static random-access memory; Computer hardware; Overhead (engineering); Memory refresh; Controller (irrigation); Data retention; Semiconductor memory; Operating system; Computer memory","score_opus":0.01983698611201415,"score_gpt":0.2647596643035801,"score_spread":0.24492267819156596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119092821","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066570896,0.0004765376,0.98393756,0.0046881884,0.0011114889,0.00029722866,0.000006344951,0.0018593235,0.0009662635],"genre_scores_gemma":[0.21174018,0.000016259317,0.78558534,0.0018159134,0.0007097335,0.00003288001,0.000009976137,0.00002584347,0.00006384222],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99731773,0.00013008529,0.00031834404,0.0006582415,0.00049601845,0.0010795847],"domain_scores_gemma":[0.99548703,0.0005580849,0.00011536372,0.0034996646,0.000056728513,0.00028312908],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002942983,0.00036093133,0.0003230135,0.00033376235,0.00019253882,0.00014657118,0.0051872265,0.00013690934,0.00001948426],"category_scores_gemma":[0.00029419185,0.0003024271,0.00012645991,0.0007180988,0.00017382271,0.0010472281,0.0053039123,0.00065617973,0.00028847225],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063817024,0.0000845375,0.0013159607,0.000014072032,0.00002743816,0.000024042265,0.0012343217,0.00046210192,0.00090439385,0.032344017,0.010625674,0.95295703],"study_design_scores_gemma":[0.0011567472,0.00046717754,0.0076756314,0.000061939376,0.000017288252,0.0006520096,0.000034217974,0.005830993,0.009740255,0.18701112,0.7858293,0.0015233216],"about_ca_topic_score_codex":0.00001691806,"about_ca_topic_score_gemma":0.000009732431,"teacher_disagreement_score":0.9514337,"about_ca_system_score_codex":0.000071408824,"about_ca_system_score_gemma":0.000046631427,"threshold_uncertainty_score":0.9999428},"labels":[],"label_agreement":null},{"id":"W2119156399","doi":"10.1109/ipdps.2009.5160895","title":"Improving RDMA-based MPI eager protocol for frequently-used buffers","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Remote direct memory access; InfiniBand; Computer science; Communication source; Protocol (science); Computer network; Latency (audio); Message passing; Operating system; Low latency (capital markets); Parallel computing","score_opus":0.031485872231888166,"score_gpt":0.31573567383385437,"score_spread":0.2842498016019662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119156399","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010639723,0.000001841249,0.9254345,0.0017550137,0.000056430486,0.06993282,0.000005363962,0.0020811567,0.0006264619],"genre_scores_gemma":[0.01682333,3.7852235e-8,0.85736924,0.0013562832,0.000031473443,0.12416698,0.0000043906034,0.000012960086,0.00023532177],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99848104,0.000017338758,0.00025735403,0.0005683622,0.00022636574,0.00044955217],"domain_scores_gemma":[0.99840987,0.0001186096,0.00013281388,0.0011937544,0.0000794107,0.000065525346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020112653,0.00020275403,0.0001847395,0.00014964085,0.00013712113,0.00015590143,0.0015044751,0.000106523796,0.000018217954],"category_scores_gemma":[0.00023281055,0.00016709365,0.00008016081,0.00033415522,0.00005901733,0.00092035497,0.00015621008,0.00013634596,0.000026489866],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080308135,0.0003572315,0.00011257495,0.000121607205,0.000015241893,0.00004832165,0.00010521881,0.000809773,0.07580727,0.2406338,0.014329963,0.6675787],"study_design_scores_gemma":[0.0052899146,0.0016836828,0.0002632097,0.000066560504,0.000008283249,0.0000083914865,0.00005378515,0.25887102,0.60871285,0.077313274,0.04662696,0.0011020905],"about_ca_topic_score_codex":0.000012327498,"about_ca_topic_score_gemma":0.0000068735953,"teacher_disagreement_score":0.6664766,"about_ca_system_score_codex":0.00010156389,"about_ca_system_score_gemma":0.00009652086,"threshold_uncertainty_score":0.6813881},"labels":[],"label_agreement":null},{"id":"W2120546611","doi":"10.1109/mcom.2005.1404599","title":"Reliability and availability assessment of storage area network extension solutions","year":2005,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Computer science; Reliability (semiconductor); Extension (predicate logic); Reliability engineering","score_opus":0.04949572754347941,"score_gpt":0.3121210339585831,"score_spread":0.2626253064151037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120546611","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":[0.021317283,0.0015128847,0.96801436,0.0060122064,0.00015152799,0.0003667199,0.00003260912,0.00054810673,0.0020443157],"genre_scores_gemma":[0.5411462,0.00047374782,0.4582227,0.00005465679,0.000014132509,0.000029071789,0.000010587966,0.0000046216805,0.000044248536],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850833,0.00019011456,0.00044800685,0.00039822047,0.00019086472,0.000264486],"domain_scores_gemma":[0.99204767,0.0004892201,0.00022540998,0.00689913,0.00027690627,0.00006168858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009635651,0.00014608314,0.00024337842,0.00008703946,0.00035875302,0.000036765516,0.0021995027,0.000081629434,0.0000108648865],"category_scores_gemma":[0.00032717283,0.00014200158,0.000045971778,0.00058794103,0.0006590566,0.0008054017,0.0022648245,0.00033645018,0.00001953804],"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":[0.000023942133,0.0031088756,0.009999302,0.00013437457,0.000089970585,0.0000052900837,0.0006084477,0.09608299,0.03632839,0.46641082,0.06963702,0.31757057],"study_design_scores_gemma":[0.00046466972,0.00013446363,0.116823845,0.00006545632,0.000026076501,0.000021416316,0.00003055478,0.7644624,0.00027430346,0.029132422,0.08818365,0.00038074338],"about_ca_topic_score_codex":0.000011111883,"about_ca_topic_score_gemma":0.000115410854,"teacher_disagreement_score":0.6683794,"about_ca_system_score_codex":0.0001587921,"about_ca_system_score_gemma":0.00008130777,"threshold_uncertainty_score":0.5790656},"labels":[],"label_agreement":null},{"id":"W2121474533","doi":"10.1145/1165389.945452","title":"Decentralized user authentication in a global file system","year":2003,"lang":"en","type":"article","venue":"ACM SIGOPS Operating Systems Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; SSH File Transfer Protocol; Authentication (law); Email authentication; Authentication protocol; Server; Authentication server; Internet Authentication Service; Access control; Network File System; File server; Torrent file; Chip Authentication Program; Self-certifying File System; Computer access control; Computer security; File system; Challenge-Handshake Authentication Protocol; Computer network; Operating system; Computer file; Stub file","score_opus":0.022063659784322454,"score_gpt":0.2935727824131349,"score_spread":0.27150912262881244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121474533","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":[0.0034100895,0.4031347,0.5778848,0.001164603,0.0018601584,0.0058379434,0.00024078306,0.0030655623,0.0034013719],"genre_scores_gemma":[0.54216033,0.0093739135,0.44527096,0.0006562562,0.000048806578,0.0019246764,0.00011959643,0.00005183485,0.000393645],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99737144,0.000489798,0.00080637843,0.00059593515,0.00031702826,0.00041940817],"domain_scores_gemma":[0.9971575,0.00019338648,0.0002670163,0.0021912057,0.00012033679,0.00007053474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009606912,0.00024046731,0.0005620307,0.000054278047,0.00011932706,0.00022434624,0.0017833286,0.00009433366,0.000032621163],"category_scores_gemma":[0.0041105594,0.00020381225,0.000063470114,0.0011267704,0.000032230306,0.00074857037,0.00035225897,0.0001494498,0.00022029973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012440343,0.000100715486,0.0023383156,0.008608775,0.000042624622,0.00013494544,0.00019165249,0.00038114248,0.00036781305,0.94461477,0.023548286,0.019669725],"study_design_scores_gemma":[0.0033261015,0.0002897969,0.0018127676,0.12023018,0.00015384775,0.0026144518,0.001635388,0.046116855,0.0010196614,0.001981868,0.8171225,0.0036965574],"about_ca_topic_score_codex":0.00008458415,"about_ca_topic_score_gemma":0.000012310964,"teacher_disagreement_score":0.9426329,"about_ca_system_score_codex":0.0004214736,"about_ca_system_score_gemma":0.000109928114,"threshold_uncertainty_score":0.8311222},"labels":[],"label_agreement":null},{"id":"W2121544412","doi":"10.1353/pla.2005.0018","title":"Digital Authenticity and Integrity: Digital Cultural Heritage Documents as Research Resources","year":2005,"lang":"en","type":"article","venue":"portal Libraries and the Academy","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cultural heritage; Research integrity; Digitization; History; Computer science; Political science; Archaeology; Public relations; Telecommunications","score_opus":0.03372216407443585,"score_gpt":0.305842893570072,"score_spread":0.27212072949563615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121544412","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":[0.9359814,0.004654546,0.0023832037,0.02930943,0.00007275111,0.0004251676,0.000089213456,0.0006972725,0.02638703],"genre_scores_gemma":[0.9939646,0.0002708902,0.0027277484,0.0002846496,0.00008716071,0.000015489139,0.000008847582,0.000009772137,0.0026308366],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99850225,0.00003931102,0.00023349532,0.0004302445,0.00039559478,0.000399124],"domain_scores_gemma":[0.99916077,0.0002981985,0.000079554324,0.00033274642,0.00002316588,0.00010559201],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00028101256,0.00017263455,0.00019818718,0.00007682604,0.0004359936,0.002927553,0.0011746056,0.00012845383,0.000010542922],"category_scores_gemma":[0.00042915993,0.000103593695,0.00003818295,0.00029067855,0.0018419217,0.009950668,0.0030353435,0.0007901819,0.00003007166],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005453279,0.000025864301,0.0018107978,0.000009835276,0.00003211664,0.00001943053,0.002509599,6.134177e-7,0.000011688741,0.8706978,0.0021758717,0.12265187],"study_design_scores_gemma":[0.000985861,0.00010607989,0.0020555612,0.000042048734,0.000008131723,0.00021127901,0.0041541234,0.0011219952,0.0007342913,0.5487363,0.44147846,0.00036587752],"about_ca_topic_score_codex":0.000010941499,"about_ca_topic_score_gemma":0.000001073679,"teacher_disagreement_score":0.4393026,"about_ca_system_score_codex":0.000010564209,"about_ca_system_score_gemma":0.000017033517,"threshold_uncertainty_score":0.9981075},"labels":[],"label_agreement":null},{"id":"W2122317274","doi":"","title":"Towards Automatic Initial Buffer Configuration","year":2003,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Buffer (optical fiber); Write buffer; Skew; Workload; Throughput; Task (project management); Circular buffer; Process (computing); Page fault; Database; Distributed computing; Parallel computing; Memory management; Operating system; Cache algorithms; Cache; Wireless; Virtual memory; CPU cache; Engineering","score_opus":0.013846975090097347,"score_gpt":0.23132477647112004,"score_spread":0.21747780138102268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122317274","genre_codex":"empirical","genre_gemma":"other","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":[0.88072604,0.00025733942,0.10532259,0.0015734286,0.0018076075,0.00080822705,0.000088498535,0.0016543731,0.007761873],"genre_scores_gemma":[0.11591528,0.0002568994,0.3386668,0.0001025836,0.000054600154,0.0000039013617,0.0017115542,0.00007344463,0.5432149],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9986756,0.000059964717,0.00015260554,0.0004764378,0.0003664975,0.00026889675],"domain_scores_gemma":[0.99856746,0.000029061439,0.0003422302,0.0008073165,0.00019531888,0.000058607875],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010600028,0.00025768523,0.00038846544,0.00036518744,0.00017341175,0.000051510153,0.0013712314,0.00037367764,0.00015943842],"category_scores_gemma":[0.000052860236,0.0003034823,0.00011147822,0.00035194858,0.0001070914,0.0009876587,0.00015085128,0.00028494725,0.00012941666],"study_design_candidate":"qualitative","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":[0.00014635068,0.00042235013,0.00005011149,0.0016599854,0.00050026603,0.00085051445,0.20145191,0.00016602714,0.019279506,0.1673023,0.024464713,0.58370596],"study_design_scores_gemma":[0.007972986,0.0023903502,0.009232745,0.0022541033,0.0009401338,0.00013167804,0.5045529,0.03688014,0.32782492,0.07527737,0.02500944,0.007533223],"about_ca_topic_score_codex":0.0028977974,"about_ca_topic_score_gemma":0.0040594763,"teacher_disagreement_score":0.7648108,"about_ca_system_score_codex":0.00011834791,"about_ca_system_score_gemma":0.00017254829,"threshold_uncertainty_score":0.9999417},"labels":[],"label_agreement":null},{"id":"W2123075778","doi":"10.1109/hpcasia.2005.58","title":"On the benefits of a workflow-aware file system in high-performance computing systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Dataflow; Workflow; Versioning file system; File system; File system fragmentation; Unix file types; Self-certifying File System; Distributed computing; Operating system; Namespace; sync; Distributed File System; Workflow management system; Computer file; Database; Device file; Computer network; Stub file","score_opus":0.015362686185418577,"score_gpt":0.21545262075824503,"score_spread":0.20008993457282645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123075778","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":[0.6121335,0.00028752448,0.3830025,0.0005920621,0.0003439386,0.0004930491,0.00005953341,0.0011776058,0.0019103169],"genre_scores_gemma":[0.97118104,0.0000061231467,0.028614605,0.00006916206,0.000030016585,0.00002301023,0.0000042230013,0.0000071538684,0.00006468874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880856,0.000034880934,0.00033174167,0.00029568493,0.00025808843,0.00027104776],"domain_scores_gemma":[0.99835694,0.00044325157,0.00015593665,0.0009750335,0.000048586546,0.000020245243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027149153,0.000135101,0.00021110318,0.0001369005,0.00008233933,0.00004981573,0.0014344539,0.00006619713,0.000011933663],"category_scores_gemma":[0.00006102429,0.000088268294,0.000020106723,0.00064190873,0.000046214744,0.00038660644,0.00047412704,0.00017701834,0.00007160358],"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":[0.0000039632505,0.0000356946,0.0002210627,0.0000781661,0.000006092144,0.0000039957613,0.00014365464,0.32530013,0.000018692162,0.5923907,0.003083081,0.078714736],"study_design_scores_gemma":[0.00020669219,0.0000763566,0.0018673622,0.0008338366,0.0000012515069,0.000014180511,0.0002556199,0.9938063,0.0022113386,0.0001116672,0.00044033787,0.00017505276],"about_ca_topic_score_codex":0.000051898693,"about_ca_topic_score_gemma":0.000018180115,"teacher_disagreement_score":0.6685062,"about_ca_system_score_codex":0.00014622907,"about_ca_system_score_gemma":0.00001888549,"threshold_uncertainty_score":0.35994765},"labels":[],"label_agreement":null},{"id":"W2124165114","doi":"10.1109/icppw.2006.70","title":"Servers Reintegration in Disconnection-Resilient File Systems for Mobile Clients","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Self-certifying File System; Operating system; Server; File system fragmentation; SSH File Transfer Protocol; File system; File server; Disconnection; Device file; Torrent file; Computer file; Computer network","score_opus":0.011835234930429695,"score_gpt":0.2530773056362876,"score_spread":0.2412420707058579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124165114","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":[0.023526443,0.00009805221,0.9737661,0.000084996354,0.0003863012,0.00065766746,0.000099249766,0.00051357236,0.0008676345],"genre_scores_gemma":[0.92520535,0.000009033653,0.071230836,0.00002777011,0.00003650607,0.00094614155,0.00019844514,0.0000091648335,0.0023367614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910057,0.000015599187,0.00022246754,0.00033751628,0.00012314355,0.0002007149],"domain_scores_gemma":[0.9992749,0.00011534997,0.00007179398,0.00047738958,0.00004479472,0.000015751464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106343294,0.00009469421,0.000108339176,0.00013756931,0.00006436843,0.00008850468,0.00045946543,0.000056247412,0.000017923665],"category_scores_gemma":[0.000068871894,0.000079494785,0.00003045512,0.00033500826,0.000024851277,0.0007719276,0.0001222034,0.000060236976,0.000023957084],"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":[0.000016877204,0.00024727648,0.0014036581,0.00005595449,0.000007393983,0.000010695745,0.000114575094,0.1495567,0.001324734,0.7065175,0.12493563,0.015808975],"study_design_scores_gemma":[0.0012367684,0.0004473623,0.003116188,0.00010506503,0.0000043798955,0.000013453562,0.0014200349,0.870366,0.011605332,0.02900298,0.08207004,0.0006124228],"about_ca_topic_score_codex":0.0007830419,"about_ca_topic_score_gemma":0.000586205,"teacher_disagreement_score":0.90253526,"about_ca_system_score_codex":0.00014228234,"about_ca_system_score_gemma":0.000017353748,"threshold_uncertainty_score":0.32417032},"labels":[],"label_agreement":null},{"id":"W2125038582","doi":"10.1007/s10723-014-9307-6","title":"The Case for Workflow-Aware Storage:An Opportunity Study","year":2014,"lang":"en","type":"article","venue":"Journal of Grid Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Biotech (Canada); University of British Columbia","funders":"","keywords":"Workflow; Computer science; Workflow technology; Workflow engine; Workflow management system; Information repository; Database; Scheduling (production processes); Distributed computing; Computer data storage; Operating system; Engineering","score_opus":0.04286547957294007,"score_gpt":0.31290132723584496,"score_spread":0.2700358476629049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125038582","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":[0.18792963,0.00008745859,0.8098671,0.00051050476,0.0012673996,0.000185693,0.0000017892951,0.00013049673,0.000019922256],"genre_scores_gemma":[0.87103486,0.000004669338,0.12830101,0.00010105503,0.000536249,0.0000020941811,4.5390632e-7,0.000011513827,0.000008100961],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983528,0.0002099706,0.0005855044,0.00023664912,0.00028110933,0.00033392294],"domain_scores_gemma":[0.9967518,0.0010463517,0.00078875944,0.0008720255,0.00038391098,0.00015714276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028558143,0.000159192,0.00027408404,0.00012436758,0.0008307054,0.00032298884,0.0020820296,0.00004760233,6.4760144e-7],"category_scores_gemma":[0.001122071,0.00010755128,0.000097400385,0.00028480162,0.00006800111,0.0007991365,0.00063729985,0.00044438572,0.000001304154],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002633508,0.0002334452,0.00043704308,0.000011268343,0.00005394087,0.0015129277,0.00071398733,0.007828335,0.000030090023,0.0066862637,0.0024322304,0.9800341],"study_design_scores_gemma":[0.0022779608,0.0042193052,0.0014258001,0.00010639194,0.00006336924,0.01010671,0.006152801,0.93035924,0.0002274773,0.02220271,0.02224635,0.0006118757],"about_ca_topic_score_codex":0.00000776264,"about_ca_topic_score_gemma":0.000027896176,"teacher_disagreement_score":0.9794223,"about_ca_system_score_codex":0.000080775084,"about_ca_system_score_gemma":0.000102477505,"threshold_uncertainty_score":0.63891983},"labels":[],"label_agreement":null},{"id":"W2126928797","doi":"10.1109/apads.1993.588822","title":"Data reorganization in parallel database systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; IBM (Canada)","funders":"","keywords":"Computer science; Backup; Database; Parallel database; Lock (firearm); Database theory; Distributed database; Database testing; Database server; Database tuning; Distributed computing; Database design; Data mining; View","score_opus":0.07352551327834649,"score_gpt":0.27114467788470303,"score_spread":0.19761916460635653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126928797","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002185478,0.00044788804,0.9961788,0.0006763652,0.00014558989,0.000119818054,0.00004719876,0.0007360799,0.0014296877],"genre_scores_gemma":[0.35345003,0.00029603596,0.6449909,0.000165887,0.000027134814,0.000010628936,0.00022867345,0.000011350263,0.0008193758],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906427,0.000022751577,0.00016716844,0.00043363107,0.0001448728,0.00016732074],"domain_scores_gemma":[0.99700207,0.000041948017,0.000045352444,0.002865904,0.000021006015,0.00002371105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001476896,0.00007585174,0.00008850119,0.00011072004,0.000032444714,0.00008366216,0.0026782965,0.0000382392,0.00002942931],"category_scores_gemma":[0.00025011896,0.00006781817,0.0000034680486,0.00067261845,0.00002608786,0.0024582038,0.0019253104,0.00008899966,0.00025416532],"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":[0.0000014791098,0.00017078845,0.0015584824,0.00003627671,0.000007549984,0.00020665993,0.00014594576,0.0028799106,0.0009048984,0.82781494,0.13559769,0.030675394],"study_design_scores_gemma":[0.00022538954,0.000014044111,0.00013264688,0.00001745924,0.0000010224628,0.000026344986,0.000062150255,0.96670675,0.00014323341,0.0011050378,0.03139079,0.0001751488],"about_ca_topic_score_codex":0.00004362114,"about_ca_topic_score_gemma":0.000044979734,"teacher_disagreement_score":0.96382684,"about_ca_system_score_codex":0.000032927095,"about_ca_system_score_gemma":0.000006238099,"threshold_uncertainty_score":0.4976986},"labels":[],"label_agreement":null},{"id":"W2127833829","doi":"10.1145/2525528.2525529","title":"Annotation for automation","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; File system; Computer file; Unix file types; Metadata; Self-certifying File System; SSH File Transfer Protocol; Virtual file system; Versioning file system; Operating system; Journaling file system; File format; File Control Block; Implementation; Database; Device file; Programming language; Stub file","score_opus":0.0164904203775759,"score_gpt":0.26172654476895413,"score_spread":0.24523612439137824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127833829","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025427775,0.000006391466,0.99346447,0.001700151,0.00006622658,0.00021183256,6.9838603e-7,0.0011394847,0.00086797593],"genre_scores_gemma":[0.2004684,6.7163916e-7,0.799051,0.00013443167,0.000005933346,0.00010072721,0.000004166935,0.0000015350108,0.00023315058],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997107,0.0000025435208,0.00005845722,0.00010731893,0.0000457859,0.00007522182],"domain_scores_gemma":[0.99963015,0.00003840389,0.000024785084,0.00024305932,0.00005426607,0.000009329488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030972893,0.000030624386,0.000028835433,0.00003971256,0.00003352609,0.000058534763,0.000284066,0.00001966593,0.0000115072535],"category_scores_gemma":[0.0000734841,0.00002545502,0.000008946788,0.000104803046,0.000009861627,0.0013408868,0.000064378764,0.000014418763,0.00015651008],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2440158e-7,0.0000049682562,0.000013785887,0.0000026476293,9.4615393e-7,7.311731e-8,0.00003199207,0.000047599042,0.0024985801,0.549863,0.012087817,0.43544847],"study_design_scores_gemma":[0.00012836461,0.000044794524,0.001903943,0.0000018440641,5.3094453e-7,0.0000016144778,0.000036387835,0.5880769,0.017328903,0.38570207,0.006684684,0.000089936926],"about_ca_topic_score_codex":0.0000062602335,"about_ca_topic_score_gemma":0.0000010238434,"teacher_disagreement_score":0.5880293,"about_ca_system_score_codex":0.000013713844,"about_ca_system_score_gemma":0.0000053054637,"threshold_uncertainty_score":0.20116726},"labels":[],"label_agreement":null},{"id":"W2133682093","doi":"10.1109/dcs.1988.12556","title":"On the communication cost of distributed database processing","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Sorting; Distributed database; Testbed; Ethernet; Hash function; Join (topology); Workstation; Distributed computing; Distributed memory; Transfer (computing); Parallel computing; Computer network; Shared memory; Operating system; Algorithm","score_opus":0.03626312723508093,"score_gpt":0.28437182446551806,"score_spread":0.24810869723043713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133682093","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":[0.0012739626,0.00008677929,0.9951924,0.000980038,0.000012282648,0.00011497022,0.000020219068,0.00019112148,0.0021282164],"genre_scores_gemma":[0.8214856,0.000013637495,0.17831266,0.00012961522,5.285526e-7,0.000012816832,0.000019374818,0.0000019978343,0.000023765699],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995403,0.00004496933,0.00009990616,0.00011714441,0.00011075761,0.00008687307],"domain_scores_gemma":[0.99828416,0.00020505453,0.00007637666,0.0013748471,0.00004886416,0.000010686483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021540775,0.000050072525,0.000053245756,0.000027382239,0.0000991725,0.000030803465,0.0011249274,0.000018293136,0.000011264954],"category_scores_gemma":[0.00061139715,0.0000307618,0.000009130581,0.00037602772,0.000100910474,0.00037814083,0.00025766378,0.000094029034,0.000009688221],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.222495e-7,0.000025859925,0.000014468899,0.0000027921458,0.0000011241711,4.3142236e-7,0.000026095939,0.000053726784,0.00036883814,0.9812258,0.0017256833,0.01655449],"study_design_scores_gemma":[0.00073103316,0.00014113278,0.0004323532,0.00020874167,0.000010106534,0.000023777795,0.0012467199,0.08544151,0.46827185,0.38714904,0.055803187,0.0005405261],"about_ca_topic_score_codex":0.0000052899627,"about_ca_topic_score_gemma":0.0000050023646,"teacher_disagreement_score":0.82021165,"about_ca_system_score_codex":0.000019307843,"about_ca_system_score_gemma":0.000022565851,"threshold_uncertainty_score":0.20904137},"labels":[],"label_agreement":null},{"id":"W2136009993","doi":"","title":"Disk access analysis for system performance optimization","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Heuristics; Scheduling (production processes); Bottleneck; Workload; Disk buffer; Dynamic priority scheduling; Distributed computing; Cache; Real-time computing; Parallel computing; Operating system; Embedded system; Schedule; Mathematical optimization","score_opus":0.01688185645144113,"score_gpt":0.2579688079904091,"score_spread":0.24108695153896798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136009993","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":[0.0019747673,0.0000245802,0.994361,0.00011926779,0.00006899869,0.00015564746,0.00000786772,0.0011634685,0.0021244118],"genre_scores_gemma":[0.5556945,0.000003018345,0.44406596,0.000012419487,0.000011800308,0.0000359473,0.00002162543,0.0000026780906,0.00015203297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992865,0.000006022985,0.00015555297,0.00027699178,0.00011213025,0.00016281554],"domain_scores_gemma":[0.9991941,0.00003797294,0.00007997594,0.00060486415,0.00006938486,0.000013717505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008352422,0.00007972518,0.00012575452,0.00021477348,0.00010902227,0.00016960577,0.0011016417,0.000038194517,0.000003380928],"category_scores_gemma":[0.000014274331,0.00006572159,0.00004890689,0.0011931693,0.000021912918,0.001548133,0.0002913391,0.000028437264,0.000004792361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013146256,0.00000892246,0.0029279517,0.00001754323,0.000018790814,5.738884e-7,0.000002993258,0.9071408,0.000007360994,0.08623666,0.00026864835,0.0033684582],"study_design_scores_gemma":[0.00008801874,0.000014482794,0.0017313934,0.0000031611244,0.000024554492,0.0000010880169,0.000010567375,0.9959993,0.0014078184,0.0003016627,0.00032126653,0.0000967082],"about_ca_topic_score_codex":0.000028231358,"about_ca_topic_score_gemma":0.000015329153,"teacher_disagreement_score":0.55371976,"about_ca_system_score_codex":0.00006256127,"about_ca_system_score_gemma":0.000009773195,"threshold_uncertainty_score":0.26800486},"labels":[],"label_agreement":null},{"id":"W2137545744","doi":"10.1145/2629629","title":"Composing Multi-Ported Memories on FPGAs","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Reconfigurable Technology and Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Porting; Field-programmable gate array; Computer science; Block (permutation group theory); Logic block; Embedded system; Construct (python library); Computer architecture; Parallel computing; Computer hardware; Operating system; Programming language; Mathematics","score_opus":0.02717674377287044,"score_gpt":0.2572444427445407,"score_spread":0.2300676989716703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137545744","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":[0.013349531,0.00034557085,0.97841495,0.0027340592,0.0008259168,0.0003420796,0.000015019019,0.0029087677,0.0010640951],"genre_scores_gemma":[0.9634155,0.00009406773,0.03569373,0.00012221771,0.000012644519,0.00011499477,0.0000035250648,0.00001863198,0.00052468834],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983095,0.00007455102,0.00036943992,0.0006843983,0.0001587089,0.00040339163],"domain_scores_gemma":[0.99748105,0.00028680507,0.0001595451,0.0019346502,0.00007572967,0.00006219691],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003060303,0.0002746586,0.0003982916,0.00090263865,0.0005521714,0.000119806755,0.0013047578,0.00040799187,0.000008208042],"category_scores_gemma":[0.00015869901,0.00025043293,0.0000468924,0.0008689407,0.00032404784,0.00041547787,0.000023826611,0.0005992893,0.00008466888],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040392966,0.00032350342,0.00018933522,0.00010341312,0.00015228499,0.000046714882,0.0001998301,0.005911004,0.008522774,0.26571953,0.0002690535,0.7185222],"study_design_scores_gemma":[0.0059797005,0.004032053,0.00065145735,0.0012911009,0.0001316197,0.001939507,0.003538851,0.27834594,0.47648016,0.12374416,0.100558646,0.0033067977],"about_ca_topic_score_codex":0.00002291435,"about_ca_topic_score_gemma":0.000017873643,"teacher_disagreement_score":0.950066,"about_ca_system_score_codex":0.00005975908,"about_ca_system_score_gemma":0.000021757913,"threshold_uncertainty_score":0.9999948},"labels":[],"label_agreement":null},{"id":"W2137776299","doi":"10.5383/juspn.01.01.002","title":"Stenog-Shell Framework for Anonymous File Exchange","year":2010,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Advanced Data Storage Technologies","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":"Shell (structure); Computer science; Operating system; Materials science; Composite material","score_opus":0.016046377316010996,"score_gpt":0.2576752301299648,"score_spread":0.2416288528139538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137776299","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":[0.005497526,0.0057820445,0.98311406,0.00044893412,0.0044729915,0.00037547853,0.000086488,0.00010703785,0.000115454706],"genre_scores_gemma":[0.62682843,0.0012341744,0.36636358,0.00036654779,0.004669192,0.000081508086,0.00001377865,0.000054024382,0.00038878113],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99841297,0.000048480237,0.00054576993,0.00029899945,0.00026927792,0.00042447908],"domain_scores_gemma":[0.997097,0.0009246974,0.000752998,0.0006134157,0.00044865956,0.00016323947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056254806,0.00022496015,0.00048896344,0.00015728634,0.00021249859,0.00028392827,0.0010890461,0.00036399183,0.000029509265],"category_scores_gemma":[0.0004097263,0.00017642917,0.00013247674,0.00024059473,0.00010466587,0.0006728197,0.00029132882,0.0008276802,0.0000029493629],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025119618,0.0003690978,0.0009082303,0.0008643286,0.00045982836,0.0009819164,0.0033200076,0.012035563,0.004216889,0.28641543,0.34244353,0.34773397],"study_design_scores_gemma":[0.0028627831,0.004518877,0.0014746974,0.0017359584,0.00015292475,0.008091152,0.0023960066,0.18846981,0.00074828294,0.05262289,0.73508054,0.0018460839],"about_ca_topic_score_codex":0.000016422235,"about_ca_topic_score_gemma":0.000027559643,"teacher_disagreement_score":0.6213309,"about_ca_system_score_codex":0.000034944875,"about_ca_system_score_gemma":0.000067205205,"threshold_uncertainty_score":0.71945727},"labels":[],"label_agreement":null},{"id":"W2138678503","doi":"10.1109/allerton.2011.6120325","title":"Distributed storage with communication costs","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Redundancy (engineering); Computer science; Distributed data store; Node (physics); Computer network; Distributed computing; Data redundancy; Minification; Reliability (semiconductor); Process (computing); Engineering; Operating system","score_opus":0.027138778196125243,"score_gpt":0.23571168584883861,"score_spread":0.20857290765271336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138678503","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":[0.003825531,0.00004967551,0.98559356,0.00022522539,0.000018956993,0.000087546934,0.0000075403955,0.0011990406,0.008992925],"genre_scores_gemma":[0.5826299,0.000007329473,0.41723487,0.00005312416,9.716962e-7,0.000009934024,0.000012563601,0.0000028653278,0.00004843119],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994803,0.000019596207,0.000080761994,0.00018110173,0.00010063507,0.00013758955],"domain_scores_gemma":[0.9983393,0.00002985152,0.000053035044,0.0014960133,0.00005210513,0.000029723518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007007805,0.00007530803,0.00007017333,0.00004234336,0.00007547198,0.000030786483,0.0014482822,0.000033244192,0.000020944788],"category_scores_gemma":[0.000029542252,0.00005541667,0.000009164573,0.000309624,0.00010022316,0.00080090645,0.00051996205,0.00009672213,0.000056675442],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009340043,0.000078841906,0.00089329784,0.0000024678263,0.000011342335,0.000025954869,0.0002773623,0.000010659749,0.00014932359,0.9589256,0.002543749,0.037072048],"study_design_scores_gemma":[0.0066863396,0.0032762294,0.15807648,0.0003405977,0.00007497993,0.00064632006,0.004572557,0.096587606,0.25560057,0.35275733,0.11586353,0.005517448],"about_ca_topic_score_codex":0.0000586377,"about_ca_topic_score_gemma":0.00005447919,"teacher_disagreement_score":0.60616827,"about_ca_system_score_codex":0.000057546567,"about_ca_system_score_gemma":0.000014668081,"threshold_uncertainty_score":0.26912928},"labels":[],"label_agreement":null},{"id":"W2138872609","doi":"10.1145/1837915.1837917","title":"Understanding latent sector errors and how to protect against them","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":135,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Redundancy (engineering); Data redundancy; Field (mathematics); Data reliability; RAID; Reliability engineering; Reliability (semiconductor); Risk analysis (engineering); Data science; Data mining; Database; Operating system; Engineering","score_opus":0.09323359745007599,"score_gpt":0.2628923816478992,"score_spread":0.1696587841978232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138872609","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":[0.08005654,0.000006664321,0.91233265,0.0058238953,0.00044476974,0.00037538665,0.000025949701,0.00081278844,0.00012133522],"genre_scores_gemma":[0.8236674,0.000010910822,0.17589211,0.00019638344,0.000015860369,0.000064441636,0.0000010349654,0.000016384703,0.00013543667],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988338,0.000025170866,0.00010367308,0.00050404994,0.00023000843,0.0003033049],"domain_scores_gemma":[0.9983208,0.00011731242,0.000051725357,0.0013595815,0.000028879476,0.00012165391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016022073,0.00019344667,0.00015621704,0.00021991308,0.0003286751,0.00016369818,0.0010018145,0.00011880856,0.00001685142],"category_scores_gemma":[0.00010019519,0.00017566352,0.000046225254,0.000507075,0.00009812331,0.0006491905,0.00006840431,0.00055715756,0.000036336714],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013601089,0.0005784007,0.00029510664,0.00013369319,0.00023947873,0.00040951424,0.005083422,0.008056994,0.33707723,0.07611509,0.0024635976,0.56941146],"study_design_scores_gemma":[0.007989707,0.003880618,0.0059124217,0.0006130149,0.00018556643,0.00093072467,0.0063871993,0.055563178,0.55783015,0.22056462,0.13127217,0.008870655],"about_ca_topic_score_codex":0.0000063379853,"about_ca_topic_score_gemma":0.000076535485,"teacher_disagreement_score":0.7436109,"about_ca_system_score_codex":0.00013154195,"about_ca_system_score_gemma":0.000028600143,"threshold_uncertainty_score":0.71633506},"labels":[],"label_agreement":null},{"id":"W2142117893","doi":"10.1145/1456469.1456480","title":"Configurable security for scavenged storage systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Scalability; Throughput; Computer data storage; Idle; Protocol (science); Cryptographic protocol; Computer network; Distributed computing; Embedded system; Computer security; Operating system; Cryptography; Wireless","score_opus":0.02915520142147487,"score_gpt":0.24915898152176766,"score_spread":0.22000378010029278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142117893","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":[0.005393942,0.00044627342,0.9872192,0.0002673378,0.00041384628,0.00040991293,0.000021733036,0.0016227008,0.004205019],"genre_scores_gemma":[0.9013592,0.00003311477,0.09710467,0.00008922619,0.00003255173,0.000098729564,0.0000068137906,0.000009038483,0.0012666549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897563,0.000019183011,0.00017071274,0.00036731924,0.00016758044,0.00029956386],"domain_scores_gemma":[0.99874467,0.00012593596,0.00007110499,0.0009093406,0.00009695958,0.000051965464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015996731,0.000121629215,0.0001813191,0.000080097685,0.00022075274,0.000055909284,0.0010640074,0.00007749459,0.000006711681],"category_scores_gemma":[0.00013315579,0.00010657018,0.00004201823,0.00023427112,0.0000914954,0.00074800954,0.00020408988,0.00010216693,0.000056406334],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007474053,0.00006752724,0.000054910324,0.000052489217,0.000018821458,0.000072423245,0.00037690523,0.0008365212,0.0013248222,0.913817,0.081769876,0.0016012666],"study_design_scores_gemma":[0.0020080367,0.00047267624,0.00026761057,0.00004797347,0.0000098629625,0.00054273696,0.0005321191,0.4743928,0.03475721,0.055541318,0.430227,0.0012006457],"about_ca_topic_score_codex":0.000028733566,"about_ca_topic_score_gemma":0.0000028700879,"teacher_disagreement_score":0.8959653,"about_ca_system_score_codex":0.00005931452,"about_ca_system_score_gemma":0.00004573242,"threshold_uncertainty_score":0.4345806},"labels":[],"label_agreement":null},{"id":"W2144425137","doi":"10.1109/tst.2013.6522585","title":"Erasure coding for cloud storage systems: A survey","year":2013,"lang":"en","type":"article","venue":"Tsinghua Science & Technology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Erasure; Computer science; Cloud computing; Cloud storage; Erasure code; Coding (social sciences); Operating system; Algorithm; Decoding methods; Mathematics; Programming language; Statistics","score_opus":0.03159143285073643,"score_gpt":0.2828868283690719,"score_spread":0.25129539551833546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144425137","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":[0.078862555,0.00027174636,0.9134513,0.0024757227,0.0007440501,0.0009702076,0.000018219898,0.0030380497,0.00016810713],"genre_scores_gemma":[0.8438792,0.000009986066,0.15558024,0.00007927429,0.000026468642,0.00028494856,0.0000037762459,0.000018790743,0.00011728745],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99674433,0.00004058199,0.0003636348,0.0011965291,0.00052460044,0.0011303064],"domain_scores_gemma":[0.99651235,0.0002626679,0.00027480637,0.002142229,0.00069554395,0.000112419046],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0014016738,0.0002967783,0.00039258835,0.0015602815,0.00074088766,0.00056696567,0.00539264,0.0002547757,0.0000053209224],"category_scores_gemma":[0.0014945825,0.00024587565,0.000035191886,0.0060650073,0.002522538,0.0023961405,0.001239037,0.00036598535,0.000111101675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014393683,0.00011804327,0.003577329,0.00006345151,0.000024516921,0.000037918006,0.00027115352,0.0011520655,0.06824885,0.87572426,0.0031231788,0.04764482],"study_design_scores_gemma":[0.0044227326,0.0043650637,0.010313761,0.00069945835,0.00005502901,0.0017186003,0.0044333525,0.5084109,0.15107815,0.22672597,0.08210862,0.005668389],"about_ca_topic_score_codex":0.00010737543,"about_ca_topic_score_gemma":0.00003417101,"teacher_disagreement_score":0.7650167,"about_ca_system_score_codex":0.00036046797,"about_ca_system_score_gemma":0.0003457754,"threshold_uncertainty_score":0.99999934},"labels":[],"label_agreement":null},{"id":"W2145350315","doi":"10.1007/978-3-642-37119-6_2","title":"Proofs of Retrievability via Fountain Code","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Retrievability; Mathematical proof; Security parameter; Computer science; Fountain code; Theoretical computer science; Protocol (science); Scheme (mathematics); Gas meter prover; Chaining; Overhead (engineering); Set (abstract data type); Mathematics; Algorithm; Cryptography; Block code; Linear code; Programming language; Decoding methods","score_opus":0.01837433778645371,"score_gpt":0.25439297149301476,"score_spread":0.23601863370656107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145350315","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012982907,0.00043362976,0.99527395,0.000609171,0.00087989855,0.0007545416,0.000020879668,0.0004621493,0.0014359487],"genre_scores_gemma":[0.123951495,0.000032251683,0.8753253,0.0003294335,0.00011295107,0.000018576868,0.000006273127,0.000032255582,0.00019142992],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953968,0.000034034903,0.00077949266,0.0019225281,0.00115623,0.0007109094],"domain_scores_gemma":[0.99449843,0.0006104751,0.0005925585,0.0037142802,0.00046223775,0.000122006844],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0009858541,0.0005763771,0.00076324004,0.00081515877,0.0001513861,0.00021096856,0.0069621564,0.00049729994,0.000037140297],"category_scores_gemma":[0.00051079347,0.0005126499,0.00012858228,0.0010109509,0.0022585376,0.0012778705,0.0039139856,0.0010248421,0.00006903483],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005415837,0.000036363832,0.00007841079,0.000080395504,0.000009056098,0.000036429083,0.00019305272,0.0038408102,0.00064465555,0.049622186,0.00004007896,0.9454132],"study_design_scores_gemma":[0.00020110473,0.00028595066,0.00013785755,0.00023888527,0.0000055912633,0.000049893886,1.524395e-7,0.16994353,0.0136049185,0.81294376,0.0019027519,0.00068561896],"about_ca_topic_score_codex":0.00003100056,"about_ca_topic_score_gemma":0.000066743036,"teacher_disagreement_score":0.94472754,"about_ca_system_score_codex":0.0004904356,"about_ca_system_score_gemma":0.00046017527,"threshold_uncertainty_score":0.9997325},"labels":[],"label_agreement":null},{"id":"W2145978337","doi":"","title":"CLIC: client-informed caching for storage servers","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cache; False sharing; Server; Storage management; TRACE (psycholinguistics); File server; Scheme (mathematics); Semantics (computer science); Database; Distributed computing; Computer network; CPU cache; Cache algorithms","score_opus":0.02324039796018276,"score_gpt":0.2962690817731962,"score_spread":0.2730286838130135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145978337","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066848216,0.000033365344,0.9859351,0.0018206117,0.00020020676,0.0002685072,0.000006837547,0.001601647,0.003448908],"genre_scores_gemma":[0.4898003,0.000009760331,0.5083532,0.0012822606,0.000022621998,0.000014358959,0.000009358696,0.000005140101,0.00050303683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99893963,0.000007430098,0.00019179135,0.00032986267,0.00016068252,0.0003705744],"domain_scores_gemma":[0.9988876,0.00010801965,0.00007973253,0.0008243691,0.000041634645,0.000058643975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000152996,0.00013179354,0.00013835666,0.00011821492,0.00014950175,0.00010083547,0.0013050941,0.00007009623,0.000005280309],"category_scores_gemma":[0.00021855983,0.00011325926,0.00006028657,0.00027484892,0.000029554914,0.0015584051,0.00023115303,0.00011345811,0.000033805343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011450027,0.000050161296,0.00006633546,0.000013671111,0.000009115274,0.000014184694,0.0002571743,0.0019442256,0.0008480575,0.5969777,0.0133786565,0.38642922],"study_design_scores_gemma":[0.003825099,0.0019043642,0.0040183035,0.00007455761,0.0000221976,0.00007354726,0.00088461785,0.26461902,0.032251347,0.22899088,0.46128422,0.0020518557],"about_ca_topic_score_codex":0.0000076281653,"about_ca_topic_score_gemma":0.000018349163,"teacher_disagreement_score":0.4831155,"about_ca_system_score_codex":0.000106525105,"about_ca_system_score_gemma":0.000046491543,"threshold_uncertainty_score":0.46185786},"labels":[],"label_agreement":null},{"id":"W2146532238","doi":"10.1145/1352592.1352598","title":"Parallax","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":120,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Storage virtualization; Converged storage; Virtualization; Snapshot (computer storage); Computer data storage; Architecture; Object storage; Cache; Temporal isolation among virtual machines; Embedded system; Operating system; Information repository; Computer hardware; Cloud computing","score_opus":0.0303635747919952,"score_gpt":0.2465893093168184,"score_spread":0.21622573452482322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146532238","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004829391,0.000047836904,0.9788892,0.0006505057,0.000058206155,0.000024402041,2.596556e-7,0.0013678527,0.014132299],"genre_scores_gemma":[0.4368206,0.000024875726,0.5618892,0.00022506807,0.0000055703294,0.0000029715584,3.0853633e-7,0.0000014492432,0.0010299879],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996227,0.0000032241169,0.00004897057,0.000141074,0.00007573354,0.00010832489],"domain_scores_gemma":[0.9994102,0.0000165421,0.000012532468,0.0005318115,0.000011540424,0.000017367593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000018627701,0.000039207993,0.000041812065,0.00003180406,0.000055149216,0.000008854041,0.00071807636,0.000019224735,0.0000150425385],"category_scores_gemma":[0.000027902155,0.000031377454,0.000011319773,0.00016350995,0.00004855607,0.00042914643,0.00029262446,0.00003998209,0.0003174133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.1767655e-7,0.000014713311,0.00058787817,7.4560086e-7,0.0000022602262,0.0001244477,0.000065393564,0.00003802361,0.00047110484,0.9322414,0.026216097,0.040237546],"study_design_scores_gemma":[0.0007324733,0.00022816373,0.013552099,0.000007009446,0.0000017561721,0.0011856515,0.00006523717,0.027962226,0.08576713,0.30891028,0.56062406,0.0009639252],"about_ca_topic_score_codex":0.0000038768544,"about_ca_topic_score_gemma":0.000001089773,"teacher_disagreement_score":0.62333107,"about_ca_system_score_codex":0.000010099152,"about_ca_system_score_gemma":0.000010977861,"threshold_uncertainty_score":0.40798116},"labels":[],"label_agreement":null},{"id":"W2147041723","doi":"10.1145/2385603.2385608","title":"Recon","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; File system; Versioning file system; Journaling file system; Operating system; Unix file types; Metadata; Computer file; Self-certifying File System; Device file; Checksum; Consistency (knowledge bases); Database; Stub file","score_opus":0.03381219576754611,"score_gpt":0.27451664065352516,"score_spread":0.24070444488597903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147041723","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":[0.0039278073,0.00016161743,0.9914702,0.0009170008,0.0009207951,0.00006889524,0.000013955087,0.0011716733,0.0013480324],"genre_scores_gemma":[0.7429593,0.00003731724,0.25595707,0.00026703914,0.000035273133,0.00003466508,0.0000016947298,0.000011586939,0.0006960176],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99904406,0.000029019551,0.00013632137,0.00025803997,0.00017532617,0.00035720735],"domain_scores_gemma":[0.99793327,0.00012819696,0.000046861765,0.0017778227,0.000022931776,0.0000909352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015036078,0.00013509748,0.00011777464,0.00017089369,0.00017495631,0.000040447765,0.0012677914,0.00008536783,0.000082379556],"category_scores_gemma":[0.000056531753,0.00012959685,0.000057225163,0.00041741124,0.000054106084,0.0015672541,0.000033742454,0.00026750044,0.00058179884],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007748367,0.0002475186,0.000045693618,0.000007283392,0.000023784798,0.000012392259,0.00045550463,0.00047480286,0.0013680572,0.018041212,0.0013239336,0.97799206],"study_design_scores_gemma":[0.0015666918,0.00068278547,0.0032938444,0.000075030825,0.000057348232,0.00032457415,0.0006425243,0.0033420292,0.11676735,0.039733086,0.8314376,0.0020771604],"about_ca_topic_score_codex":0.000006345163,"about_ca_topic_score_gemma":0.0000031062036,"teacher_disagreement_score":0.9759149,"about_ca_system_score_codex":0.00009335486,"about_ca_system_score_gemma":0.000015246544,"threshold_uncertainty_score":0.7478041},"labels":[],"label_agreement":null},{"id":"W2147174702","doi":"10.1109/pccc.1989.37398","title":"Improving file system performance by dynamically restructuring disk space","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Unix; Computer science; Operating system; Unix file types; File system; Restructuring; Database; Fragmentation (computing); Computer file; Stub file","score_opus":0.00410540347185554,"score_gpt":0.1851812900577233,"score_spread":0.18107588658586776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147174702","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":[0.043498196,0.00007145221,0.94882524,0.00006734596,0.0001965166,0.0001241172,0.000034904544,0.0018235618,0.0053586364],"genre_scores_gemma":[0.5732899,0.0000046872665,0.4259941,0.000019239476,0.0000052508944,0.000015371455,0.0000067427295,0.000008588842,0.0006561599],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987556,0.000024553536,0.00018262003,0.00046378048,0.00020400781,0.00036947234],"domain_scores_gemma":[0.9987019,0.00007406299,0.0000953262,0.001038075,0.000032341846,0.000058352645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011500639,0.00015653844,0.00013983883,0.00006528446,0.00016004726,0.00011888159,0.0010706418,0.00007345861,0.000035819252],"category_scores_gemma":[0.00018070293,0.00013327386,0.000025950341,0.00030141041,0.0000588674,0.0010004498,0.00042697156,0.00017946328,0.00005964783],"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":[0.0000069067605,0.00003358375,0.00056096434,0.0002482461,0.000018020879,0.00005017898,0.000093097966,0.00079528854,0.03127351,0.7910699,0.012164815,0.16368544],"study_design_scores_gemma":[0.0007109532,0.0003661958,0.0010735218,0.00015833245,0.000009235862,0.00031390565,0.000562924,0.8253568,0.14963229,0.002692806,0.017769855,0.0013531665],"about_ca_topic_score_codex":0.00002145187,"about_ca_topic_score_gemma":0.000003573901,"teacher_disagreement_score":0.82456154,"about_ca_system_score_codex":0.00015431186,"about_ca_system_score_gemma":0.000033177446,"threshold_uncertainty_score":0.54347503},"labels":[],"label_agreement":null},{"id":"W2148270217","doi":"10.1109/fusion.1995.534287","title":"Control systems of the TFTR Tritium Purification System","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tritium; Context (archaeology); Tokamak Fusion Test Reactor; Control system; Tritium illumination; Nuclear engineering; Environmental science; Computer science; Engineering; Nuclear physics; Tokamak; Plasma; Physics; Electrical engineering","score_opus":0.019139949706678237,"score_gpt":0.20912134107484384,"score_spread":0.1899813913681656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148270217","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":[0.0011283269,0.00051765883,0.9932273,0.000655767,0.00041437513,0.00032299143,0.000009554105,0.0006536796,0.0030703682],"genre_scores_gemma":[0.9920858,0.0000053594035,0.007433725,0.000027240389,0.000015485608,0.000034118988,2.5387766e-7,0.0000034042116,0.00039461174],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921834,0.00004838197,0.00021739512,0.00018878539,0.00019979241,0.00012731856],"domain_scores_gemma":[0.99846536,0.00009197782,0.00014461696,0.0012120076,0.00007007635,0.00001598555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013255936,0.000069227724,0.00012890468,0.000047769616,0.000061296494,0.000042014388,0.001381108,0.000050030783,0.000002873779],"category_scores_gemma":[0.00009209834,0.000043042,0.000035088033,0.0003319408,0.000061314546,0.00032594707,0.00013701175,0.00006725422,0.000043252607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.082066e-7,0.000024006531,0.000095547526,0.00005160722,0.000007779617,0.0000017818296,0.000035785644,0.00060881994,0.002719774,0.9910117,0.0019700248,0.0034724579],"study_design_scores_gemma":[0.00093817385,0.00007468648,0.00041336793,0.00011851108,0.000013912131,0.00006119753,0.00050738174,0.96484476,0.022474516,0.00059540477,0.009699026,0.00025905573],"about_ca_topic_score_codex":0.000022655197,"about_ca_topic_score_gemma":0.0000010529068,"teacher_disagreement_score":0.9909575,"about_ca_system_score_codex":0.000050682695,"about_ca_system_score_gemma":0.0000056468566,"threshold_uncertainty_score":0.2566465},"labels":[],"label_agreement":null},{"id":"W2150713456","doi":"10.1109/padsw.2000.884646","title":"The effect of average parallelism and CPU-I/O overlap on application speedup","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Speedup; Parallel computing; Computer science; Parallelism (grammar); Central processing unit; Data parallelism; Task parallelism; Operating system","score_opus":0.00798378583512093,"score_gpt":0.2273835621053955,"score_spread":0.21939977627027457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150713456","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":[0.046567213,0.0004400311,0.9429614,0.0015770326,0.0000835411,0.0003617012,0.0000022725824,0.0004319764,0.007574842],"genre_scores_gemma":[0.9884322,0.00015538817,0.010918657,0.00006538369,0.000009514522,0.000020119995,5.201376e-7,0.0000035095975,0.00039465283],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941605,0.000022991599,0.00010117934,0.00020756046,0.00013313732,0.00011910428],"domain_scores_gemma":[0.998845,0.00032810436,0.000059057176,0.0007395914,0.000010407976,0.000017853072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012546673,0.00007927738,0.0000888586,0.00003224063,0.00008519982,0.00003627256,0.0005766331,0.000036285917,0.0000042037295],"category_scores_gemma":[0.000076515666,0.00004617811,0.000018003268,0.0001384375,0.00008993169,0.00019576777,0.0002313304,0.0000785872,0.000047386107],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007329238,0.000014349909,0.0003360325,0.000009647223,0.000007209543,0.0000028683698,0.000055645665,0.00016678718,0.001601702,0.3214773,0.0021105087,0.6742106],"study_design_scores_gemma":[0.0025839075,0.003154845,0.0097815655,0.000054220178,0.000018191617,0.00006379282,0.00007030328,0.55933255,0.20472965,0.078381285,0.14090599,0.0009237206],"about_ca_topic_score_codex":0.0000060335465,"about_ca_topic_score_gemma":0.0000021164499,"teacher_disagreement_score":0.941865,"about_ca_system_score_codex":0.000012840831,"about_ca_system_score_gemma":0.0000011216372,"threshold_uncertainty_score":0.18830885},"labels":[],"label_agreement":null},{"id":"W2151351790","doi":"10.1109/mascot.2002.1167063","title":"A self-tuning page cleaner for DB2","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Computer science; Disk buffer; Cache; Database; Performance tuning; Throughput; Parallel computing; Operating system; Buffer (optical fiber); Algorithm; Wireless","score_opus":0.022086068604706584,"score_gpt":0.25762714728321234,"score_spread":0.23554107867850577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151351790","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00049973687,0.000056580986,0.9863661,0.00029001737,0.00012073191,0.00015915997,0.0000016160977,0.0017500952,0.010755963],"genre_scores_gemma":[0.12144411,0.000007775729,0.8776869,0.00027541158,0.000007262538,0.000029368497,8.8321764e-7,0.000006612442,0.00054163265],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99928176,0.000012236164,0.000099856865,0.00027737784,0.0000866619,0.00024211597],"domain_scores_gemma":[0.9991517,0.000101942904,0.000035256286,0.0006482236,0.00003260778,0.000030282741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014676298,0.0000845991,0.00008542184,0.000060543614,0.00008986985,0.000057383015,0.00065460877,0.0000464513,0.000009972708],"category_scores_gemma":[0.00020020512,0.00007119575,0.00003026979,0.00022045188,0.000021772501,0.0005379614,0.00017288067,0.00006547132,0.000040101582],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.273409e-7,0.00001637981,0.000021723452,0.000006298959,0.0000045573693,0.0000055082414,0.000060812567,0.0000145262675,0.0005315371,0.9815351,0.002345521,0.015457554],"study_design_scores_gemma":[0.0005593544,0.00014494988,0.000022524548,0.000007035558,0.0000052017813,0.000036410784,0.00020962997,0.04416454,0.026998965,0.20022291,0.7272382,0.0003903042],"about_ca_topic_score_codex":9.412281e-7,"about_ca_topic_score_gemma":0.0000026051584,"teacher_disagreement_score":0.78131217,"about_ca_system_score_codex":0.000029343966,"about_ca_system_score_gemma":0.000021399543,"threshold_uncertainty_score":0.29032785},"labels":[],"label_agreement":null},{"id":"W2151536027","doi":"10.1109/lcomm.2005.1437363","title":"Low-frequency performance of guided scrambling DC-free codes","year":2005,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Scrambling; Computer science; Algorithm; Coding (social sciences); Mathematics; Statistics","score_opus":0.04577684230644586,"score_gpt":0.2944407753261159,"score_spread":0.24866393301967005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151536027","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":[0.42331132,0.00046640917,0.5361214,0.037899688,0.00014544846,0.00022398657,0.000021983073,0.0008067916,0.0010029274],"genre_scores_gemma":[0.5353623,0.00026016857,0.46342385,0.00088798674,0.00001475999,0.000025235162,0.0000064968854,0.0000075195762,0.000011643926],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987596,0.00006489158,0.0004236859,0.00025696272,0.00022929364,0.0002655423],"domain_scores_gemma":[0.9913731,0.00019643769,0.00023485516,0.008040482,0.000117170435,0.00003795719],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00027597693,0.00014892028,0.00018881548,0.00023796152,0.000248141,0.00005347003,0.009554368,0.00005978419,0.0000037263628],"category_scores_gemma":[0.0001834659,0.00015545634,0.000054533328,0.0006508852,0.00045765474,0.0013493827,0.00152229,0.00028823217,0.000051670544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007133322,0.00038027053,0.0022140038,0.000087437606,0.00007956918,0.000005217275,0.0013429028,0.0127312,0.72684366,0.088822156,0.02968892,0.13779755],"study_design_scores_gemma":[0.0019467559,0.00019626759,0.0029500783,0.0005166419,0.00004560246,0.00009729756,0.00017945645,0.22212163,0.73411703,0.0069493554,0.029312475,0.0015674146],"about_ca_topic_score_codex":0.000024121215,"about_ca_topic_score_gemma":0.000030247438,"teacher_disagreement_score":0.20939043,"about_ca_system_score_codex":0.00011256331,"about_ca_system_score_gemma":0.000040875977,"threshold_uncertainty_score":0.9958044},"labels":[],"label_agreement":null},{"id":"W2152102944","doi":"10.14778/2536354.2536355","title":"Hybrid storage management for database systems","year":2013,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Database; Workload; Storage management; Data striping; Computer data storage; Flash (photography); Operating system; Distributed computing","score_opus":0.01574298037299049,"score_gpt":0.22913046462758513,"score_spread":0.21338748425459464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152102944","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":[0.07523427,0.0011059326,0.898228,0.004107407,0.0025489032,0.009450664,0.00017470661,0.0015089551,0.00764118],"genre_scores_gemma":[0.826055,0.000058848975,0.17140229,0.00012277681,0.000039807946,0.0013257551,0.0000041020244,0.000018128374,0.0009733048],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99861205,0.000003202095,0.00029309533,0.000408166,0.0003536451,0.00032983843],"domain_scores_gemma":[0.9988942,0.00003789157,0.0002710086,0.00057865283,0.00017157284,0.000046668134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024750008,0.00016778373,0.00018524713,0.000107861764,0.00012433442,0.00015176652,0.0025344265,0.00002442576,0.0000036485187],"category_scores_gemma":[0.000073939984,0.000115431234,0.00007021053,0.00021855623,0.0000761857,0.0010311749,0.00185766,0.00009019385,0.000022963433],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008479612,0.00014261523,0.000098146535,0.000676112,0.00008981577,0.0000018356325,0.00012072632,0.00012262672,0.03355996,0.8658372,0.08056906,0.018773401],"study_design_scores_gemma":[0.0032944516,0.0005451636,0.00072332396,0.0008933597,0.00013799552,0.00010987407,0.0021672917,0.08687318,0.6075168,0.16779839,0.12850915,0.0014309793],"about_ca_topic_score_codex":0.000029866484,"about_ca_topic_score_gemma":1.6162515e-7,"teacher_disagreement_score":0.7508207,"about_ca_system_score_codex":0.00011255758,"about_ca_system_score_gemma":0.000008906808,"threshold_uncertainty_score":0.47096375},"labels":[],"label_agreement":null},{"id":"W2154787987","doi":"10.1109/aciids.2009.64","title":"Processing Exact Results for Sliding Window Joins over Time-Sequence, Streaming Data Using a Disk Archive","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Joins; Sliding window protocol; Computer science; Data stream mining; Window (computing); Data stream; Tuple; Real-time computing; Auxiliary memory; Algorithm; Disk buffer; Memory management; Sequence (biology); Parallel computing; Data mining; Computer hardware; Operating system; Mathematics","score_opus":0.08587831246637272,"score_gpt":0.3385252855022013,"score_spread":0.25264697303582856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154787987","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077290623,0.0000811459,0.98894644,0.00035601854,0.00005697735,0.00037674254,0.0003628173,0.0009944949,0.0010962738],"genre_scores_gemma":[0.2705151,0.000008007003,0.7290353,0.00012366526,0.000054245975,0.0000045323122,0.00014710959,0.000011722465,0.00010025207],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978201,0.000024548794,0.0003298026,0.0010073873,0.00027629882,0.0005418656],"domain_scores_gemma":[0.9974167,0.00023120399,0.00024219115,0.0019835136,0.000054993936,0.000071419585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034168502,0.0002406929,0.00024984503,0.00021699346,0.0003421806,0.00035183894,0.002676544,0.00007454353,0.0000018343571],"category_scores_gemma":[0.00069550745,0.00020931217,0.00004032834,0.00052994397,0.00006913014,0.003976826,0.0011683156,0.00018466773,0.000007181112],"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":[0.00006261738,0.00013358051,0.00006559739,0.00003746749,0.0000210828,0.000070059315,0.0003935153,0.0011926354,0.09417842,0.021229804,0.0024620513,0.8801532],"study_design_scores_gemma":[0.0006857517,0.00012547494,0.00044052463,0.0001782171,0.000014586304,0.000038734448,0.0000717033,0.97019523,0.007418983,0.018061366,0.002329923,0.00043948574],"about_ca_topic_score_codex":0.000022825525,"about_ca_topic_score_gemma":0.000007106292,"teacher_disagreement_score":0.9690026,"about_ca_system_score_codex":0.000106364925,"about_ca_system_score_gemma":0.00013449731,"threshold_uncertainty_score":0.85355026},"labels":[],"label_agreement":null},{"id":"W2156694107","doi":"10.19173/irrodl.v13i5.1251","title":"An e-book hub service based on a cloud platform","year":2012,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cloud computing; Computer science; Scalability; World Wide Web; Multimedia; Usability; Mobile device; Service provider; Digital content; Service (business); Operating system","score_opus":0.10638097594609482,"score_gpt":0.43945556367515776,"score_spread":0.33307458772906295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156694107","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":[0.06706465,0.09928362,0.6014608,0.17749535,0.0011431212,0.0062146843,0.0004283878,0.00068775594,0.04622161],"genre_scores_gemma":[0.9816266,0.007630679,0.008094431,0.0022209298,0.00006366385,0.00010577968,0.00017860168,0.00000954857,0.00006980964],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984042,0.00023444927,0.00022697101,0.00021109403,0.00064323633,0.0002800381],"domain_scores_gemma":[0.9983438,0.0007287925,0.00010662146,0.0005393748,0.00021171385,0.00006968174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043995483,0.00008453668,0.00015922291,0.00012548619,0.00013194162,0.00014758046,0.0032765542,0.0000333055,0.00005870812],"category_scores_gemma":[0.0013970122,0.00005774166,0.000019591364,0.0006414157,0.00009874988,0.001229532,0.0013806982,0.00057407876,0.000027708367],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024886118,0.0007937536,0.020285508,0.0018958155,0.00004867556,0.000040587784,0.0004571932,0.0025423847,0.0003652436,0.6163845,0.012415479,0.34452203],"study_design_scores_gemma":[0.0017324489,0.0006152336,0.0083001815,0.014738277,0.000008685113,0.000044929588,0.0016252876,0.2293737,0.0016188067,0.013117947,0.72833437,0.00049014576],"about_ca_topic_score_codex":0.00010602803,"about_ca_topic_score_gemma":0.000006611542,"teacher_disagreement_score":0.9145619,"about_ca_system_score_codex":0.000107137064,"about_ca_system_score_gemma":0.0000846385,"threshold_uncertainty_score":0.60887074},"labels":[],"label_agreement":null},{"id":"W2157302797","doi":"10.1109/ismvl.2004.1319965","title":"A study of multiple-valued magnetoresistive RAM (MRAM) using binary MTJ devices","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Magnetoresistive random-access memory; Tunnel magnetoresistance; Magnetoresistance; Materials science; Transistor; Binary number; Electrical engineering; Magnetic storage; Non-volatile memory; Random access memory; Optoelectronics; Computer science; Engineering; Computer hardware; Nanotechnology; Physics; Voltage; Mathematics; Magnetic field","score_opus":0.04510890402314838,"score_gpt":0.30445318549622885,"score_spread":0.2593442814730805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157302797","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":[0.6193749,0.00009306454,0.37948972,0.000043638625,0.00008129994,0.00030660795,0.0000028289305,0.00048543958,0.00012251023],"genre_scores_gemma":[0.6415107,0.0000017302845,0.35841843,0.000029764666,0.0000073767737,0.0000093230865,8.786225e-7,0.000006504805,0.00001525906],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986143,0.00003903826,0.0002894151,0.00048480803,0.00030797452,0.00026448106],"domain_scores_gemma":[0.9985931,0.000096693395,0.00016576557,0.0009992357,0.00010242921,0.000042806616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013372039,0.00017678262,0.00024626346,0.0002102215,0.0001128583,0.000045895053,0.0013338648,0.00006345481,0.0000052622922],"category_scores_gemma":[0.00019320792,0.00015006641,0.000037103542,0.0007008723,0.00011960137,0.00085268467,0.0011067766,0.00012465284,0.0000131313045],"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":[0.000466994,0.017691303,0.09302785,0.00034648454,0.000807359,0.0035718412,0.028632479,0.29364136,0.10966537,0.2964738,0.0006115117,0.15506364],"study_design_scores_gemma":[0.03210924,0.01772276,0.25570464,0.0006713514,0.00032269268,0.00030795476,0.07133623,0.38799337,0.16415904,0.062654264,0.0014340822,0.0055843703],"about_ca_topic_score_codex":0.0004569601,"about_ca_topic_score_gemma":0.00026896133,"teacher_disagreement_score":0.23381953,"about_ca_system_score_codex":0.00010570907,"about_ca_system_score_gemma":0.0000679455,"threshold_uncertainty_score":0.6119531},"labels":[],"label_agreement":null},{"id":"W2157535433","doi":"10.1145/1551609.1551643","title":"Exploring data reliability tradeoffs in replicated storage systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Reliability (semiconductor); Throughput; Computer data storage; Idle; Exploit; Data reliability; Storage area network; Architecture; Information repository; Embedded system; Computer network; Reliability engineering; Distributed computing; Operating system; Database; Engineering; Wireless; Computer security","score_opus":0.20597177595878044,"score_gpt":0.30556857790621683,"score_spread":0.09959680194743639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157535433","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":[0.017926788,0.00030536627,0.9729709,0.0034928662,0.00026181893,0.0003406622,0.0000152562225,0.0025799046,0.0021064554],"genre_scores_gemma":[0.8558082,0.000104666964,0.14384508,0.00014139405,0.000017584325,0.00002304512,0.000019752026,0.0000053837844,0.00003489085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980378,0.000057837304,0.00035472403,0.0009777514,0.00024265103,0.0003292405],"domain_scores_gemma":[0.99375725,0.000118313066,0.00007409273,0.0059625106,0.00003764574,0.00005019834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072900916,0.00014346202,0.00020971034,0.00015103111,0.000048637437,0.00010044712,0.0039027636,0.000060804094,0.0000013700169],"category_scores_gemma":[0.00070922496,0.00012741932,0.000015253153,0.000916337,0.000044907516,0.005922222,0.00097298727,0.00023693002,0.000029409432],"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":[0.000030146242,0.0005973155,0.00042931043,0.000046654313,0.000012383731,0.00049155805,0.00067797734,0.011979596,0.0036740475,0.6661002,0.005950788,0.31001002],"study_design_scores_gemma":[0.0015539576,0.0005611899,0.01862086,0.00019472872,0.000011050543,0.00018872076,0.0015073345,0.8138922,0.006150429,0.022808354,0.13271046,0.0018007223],"about_ca_topic_score_codex":0.00010422786,"about_ca_topic_score_gemma":0.000005943409,"teacher_disagreement_score":0.83788145,"about_ca_system_score_codex":0.00013479013,"about_ca_system_score_gemma":0.000028495586,"threshold_uncertainty_score":0.7252371},"labels":[],"label_agreement":null},{"id":"W2157953951","doi":"10.1016/j.ipl.2007.08.034","title":"Compact Hilbert indices: Space-filling curves for domains with unequal side lengths","year":2007,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Hilbert curve; Hilbert R-tree; Hilbert space; Dimension (graph theory); Mathematics; Hilbert manifold; Representation (politics); Grid; Reproducing kernel Hilbert space; Space (punctuation); Rigged Hilbert space; Pure mathematics; Algorithm; Mathematical analysis; Computer science; Geometry","score_opus":0.015010405668049061,"score_gpt":0.26037189541166983,"score_spread":0.24536148974362076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157953951","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":[0.018476129,0.00012368242,0.9731841,0.006396667,0.0000986366,0.0003366523,0.00001186418,0.0008425626,0.0005297109],"genre_scores_gemma":[0.6509243,0.000014175397,0.34045622,0.00845791,0.000040311304,0.0000141666505,0.00007129673,0.000013479325,0.000008105495],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99851644,0.000009525035,0.0004230453,0.00020509757,0.00039744505,0.00044842734],"domain_scores_gemma":[0.99872655,0.00020180883,0.00048052365,0.00039142324,0.00013514253,0.000064569096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005260255,0.00020001434,0.00018326532,0.0003346469,0.00031183052,0.00031873662,0.000773643,0.000067067034,9.39463e-7],"category_scores_gemma":[0.00018671548,0.00016609044,0.0000341851,0.00060764205,0.00013643946,0.008582957,0.00008772465,0.00019939804,0.000014938706],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002731575,0.00012439034,0.001875808,0.0035075487,0.00012839067,0.00005290129,0.02087218,0.037370592,0.005920687,0.03704459,0.018298956,0.8745308],"study_design_scores_gemma":[0.012246322,0.0015463157,0.007070099,0.008734868,0.00018261775,0.0005424321,0.011603295,0.28620258,0.18383995,0.009997192,0.47121888,0.006815449],"about_ca_topic_score_codex":0.000012890804,"about_ca_topic_score_gemma":0.000009886084,"teacher_disagreement_score":0.86771536,"about_ca_system_score_codex":0.00013009072,"about_ca_system_score_gemma":0.000078869554,"threshold_uncertainty_score":0.6772972},"labels":[],"label_agreement":null},{"id":"W2158438173","doi":"10.1109/tpds.2012.239","title":"GPUs as Storage System Accelerators","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Graphics processing unit; Multi-core processor; Leverage (statistics); Graphics; Embedded system; Coprocessor; Distributed computing; Parallel computing; Operating system","score_opus":0.022007362855716958,"score_gpt":0.24918552118173387,"score_spread":0.2271781583260169,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158438173","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":[0.012343914,0.00093085266,0.9823636,0.00009307832,0.0018517361,0.00036697334,0.0003173469,0.0014056613,0.0003268748],"genre_scores_gemma":[0.9968953,0.00004962911,0.0026037327,0.000030207895,0.00005495411,0.00017114427,0.000018695417,0.000016421607,0.00015988745],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823767,0.000097043616,0.0003583801,0.00043519653,0.0003220395,0.0005496493],"domain_scores_gemma":[0.9985729,0.0001051894,0.0001361318,0.00086275296,0.00006432751,0.00025871716],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023089282,0.00028773857,0.00033349267,0.00016617862,0.0003902543,0.00021466882,0.00060968654,0.0001916906,0.0000050958206],"category_scores_gemma":[0.000009153015,0.0002526509,0.00007386502,0.00050679443,0.000086834385,0.0012182012,0.000011618877,0.00028510785,0.00020350833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024555784,0.0016480583,0.00068475836,0.001033321,0.0006396643,0.0003580216,0.0019148401,0.60663784,0.0035547332,0.33725995,0.009959578,0.036063712],"study_design_scores_gemma":[0.012267286,0.0027275295,0.0028695082,0.0016253036,0.0005348116,0.0073655685,0.023928646,0.75321096,0.019767288,0.0019288756,0.16465358,0.009120619],"about_ca_topic_score_codex":0.00009604542,"about_ca_topic_score_gemma":0.0000030582337,"teacher_disagreement_score":0.9845514,"about_ca_system_score_codex":0.0001996766,"about_ca_system_score_gemma":0.00003578809,"threshold_uncertainty_score":0.99999255},"labels":[],"label_agreement":null},{"id":"W2159986814","doi":"10.1016/s0166-218x(99)00228-0","title":"Asymptotically optimal erasure-resilient codes for large disk arrays","year":2000,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Erasure; Set (abstract data type); Reliability (semiconductor); Mathematics; Erasure code; Asymptotically optimal algorithm; Combinatorial design; Discrete mathematics; Computer science; Algorithm; Theoretical computer science; Decoding methods; Power (physics)","score_opus":0.012609322674955221,"score_gpt":0.2590491422078882,"score_spread":0.246439819532933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159986814","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006015046,0.00005027807,0.98481584,0.00032496182,0.000052893738,0.00076889346,0.00013738283,0.00095806766,0.006876667],"genre_scores_gemma":[0.15072426,0.000028336699,0.84849703,0.00015122863,0.00003559679,0.0002616187,0.00003872824,0.00003522797,0.00022794786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99790925,0.000008735515,0.0004454157,0.00057895837,0.00039539437,0.00066225627],"domain_scores_gemma":[0.99800146,0.00028127574,0.00013148159,0.0014235177,0.00005248247,0.00010981167],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031661234,0.0003126086,0.00040233193,0.00007370698,0.00023064428,0.0001738032,0.0015963906,0.00013942756,0.00006481917],"category_scores_gemma":[0.00011030519,0.00026490272,0.00010867201,0.00028054006,0.000117839256,0.000319982,0.0003439101,0.0001915723,0.0001899964],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013982004,0.00015732943,0.000001922858,0.000081997285,0.000028683153,0.0000042415627,0.000564088,0.0010363159,0.0018169017,0.98504996,0.0008029517,0.01044165],"study_design_scores_gemma":[0.0018734133,0.00025820223,0.00004256598,0.00009505995,0.00007786235,0.000027462713,0.00083630125,0.28273037,0.025585538,0.66112965,0.02603408,0.0013094965],"about_ca_topic_score_codex":5.473928e-7,"about_ca_topic_score_gemma":0.0000022207503,"teacher_disagreement_score":0.32392028,"about_ca_system_score_codex":0.00005315533,"about_ca_system_score_gemma":0.000036252924,"threshold_uncertainty_score":0.99998033},"labels":[],"label_agreement":null},{"id":"W2161185769","doi":"10.1145/1740390.1740394","title":"The case for a versatile storage system","year":2010,"lang":"en","type":"article","venue":"ACM SIGOPS Operating Systems Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of Chicago","keywords":"Computer science; Scalability; Bottleneck; Software deployment; Distributed computing; Computer data storage; Node (physics); Scale (ratio); Converged storage; Embedded system; Information repository; Operating system","score_opus":0.025641117034383078,"score_gpt":0.2957139233546717,"score_spread":0.2700728063202886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161185769","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":[0.005539499,0.21419449,0.75511026,0.004374204,0.007511006,0.00880251,0.00012663787,0.0035178275,0.0008235672],"genre_scores_gemma":[0.77425957,0.0028152326,0.21770291,0.00047290692,0.0004521702,0.0036631909,0.000019157402,0.00007836168,0.0005365122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979749,0.00016522007,0.00065765914,0.00055044837,0.0002222547,0.00042957094],"domain_scores_gemma":[0.99441844,0.0012287198,0.0003314564,0.0036796506,0.0002624596,0.00007924512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020660395,0.00025255024,0.0004646864,0.00003971689,0.0010082629,0.00057151786,0.0031030097,0.00010092856,0.0000014635089],"category_scores_gemma":[0.004834313,0.00016056042,0.00010489924,0.0003965882,0.000084654595,0.0006585723,0.00086689775,0.0003595445,0.00006273027],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025331285,0.00003443731,0.000026502577,0.013173013,0.00009636852,0.0014004208,0.00033311424,0.00018764417,0.0033447403,0.72534007,0.042467542,0.21359363],"study_design_scores_gemma":[0.00077674666,0.00027070267,0.0000046823698,0.0090250755,0.000104086605,0.01789952,0.0017026822,0.11974248,0.00069434167,0.00038383648,0.8481714,0.0012244041],"about_ca_topic_score_codex":0.00008729333,"about_ca_topic_score_gemma":0.00005584371,"teacher_disagreement_score":0.8057039,"about_ca_system_score_codex":0.00009050231,"about_ca_system_score_gemma":0.00009336901,"threshold_uncertainty_score":0.7754845},"labels":[],"label_agreement":null},{"id":"W2162634718","doi":"10.1109/wpc.2002.1021337","title":"Compression techniques to simplify the analysis of large execution traces","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Compression (physics); Data compression; Parallel computing; Algorithm; Materials science","score_opus":0.017201219624180617,"score_gpt":0.30681135148501354,"score_spread":0.2896101318608329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162634718","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":[0.011920244,0.000064853746,0.98501533,0.0006271698,0.000026246842,0.00014264151,0.00000884842,0.0005021387,0.0016925118],"genre_scores_gemma":[0.75346017,0.000012454655,0.24622072,0.00022775416,0.0000017921873,0.000015507407,0.0000022515676,0.0000021344335,0.000057201723],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992198,0.00004736294,0.00016799403,0.00022962019,0.00017796924,0.0001572742],"domain_scores_gemma":[0.9988409,0.000094694136,0.000076759075,0.0009077538,0.00005672053,0.000023119705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028140921,0.000078859186,0.00015484614,0.00025670393,0.000088027664,0.00002907202,0.0008964595,0.000047714064,0.00001900415],"category_scores_gemma":[0.00013679892,0.000047389334,0.000055064716,0.0017993163,0.000040326613,0.00030256924,0.00027859583,0.00007251526,0.000005195593],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033973668,0.00010439735,0.000628333,0.0000051247025,0.000098649856,0.000002709882,0.0003534723,0.0007035031,0.03106566,0.8891434,0.004943784,0.072947554],"study_design_scores_gemma":[0.000096437,0.00009694848,0.0036385488,0.000014297562,0.00008564785,0.0000028999805,0.00048631325,0.013795108,0.8754001,0.01743523,0.08870479,0.0002436792],"about_ca_topic_score_codex":0.0000136767385,"about_ca_topic_score_gemma":0.000029429599,"teacher_disagreement_score":0.8717082,"about_ca_system_score_codex":0.000019493345,"about_ca_system_score_gemma":0.000009252527,"threshold_uncertainty_score":0.1932481},"labels":[],"label_agreement":null},{"id":"W2163357394","doi":"10.1109/icpc.2012.6240481","title":"Identifying computational phases from inter-process communication traces of HPC applications","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; TRACE (psycholinguistics); Abstraction; Process (computing); Task (project management); Supercomputer; Distributed computing; Software; Computation; Parallel computing; Programming language; Systems engineering","score_opus":0.046719978168715176,"score_gpt":0.34485849306731176,"score_spread":0.29813851489859655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163357394","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":[0.016715394,0.00080341625,0.98102504,0.0002596079,0.000037876933,0.00012066246,0.000025318193,0.00037998974,0.00063271803],"genre_scores_gemma":[0.6085729,0.000014465076,0.39127928,0.000031238833,0.000008596725,0.00003578313,0.00004296184,0.000002686855,0.000012064147],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99930817,0.00002151802,0.00022450234,0.0001603129,0.00015722429,0.00012826946],"domain_scores_gemma":[0.99873906,0.00026913834,0.0001631488,0.0007036867,0.000093979674,0.000030974563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011075243,0.0000772205,0.00010677813,0.000091976515,0.00009287762,0.000042709635,0.0013198558,0.000037468202,0.00003246088],"category_scores_gemma":[0.00004090829,0.00007304271,0.000024491641,0.0003078288,0.00012012772,0.0017385808,0.00037392756,0.000085982465,0.000025817231],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059024214,0.00060376344,0.007292576,0.00004489817,0.00006312605,4.409952e-7,0.0035067669,0.0017108918,0.0041478947,0.6449973,0.0009831706,0.33664328],"study_design_scores_gemma":[0.0007225874,0.00004793495,0.0076461746,0.000099405406,0.00003060048,0.000013996982,0.0042686914,0.05132088,0.10823124,0.821438,0.0055815894,0.00059888174],"about_ca_topic_score_codex":0.000036546724,"about_ca_topic_score_gemma":0.000008742458,"teacher_disagreement_score":0.5918575,"about_ca_system_score_codex":0.000021836997,"about_ca_system_score_gemma":0.000014905254,"threshold_uncertainty_score":0.29785955},"labels":[],"label_agreement":null},{"id":"W2167467832","doi":"10.1109/pacrim.1991.160738","title":"An improved desynchronizer with reduced waiting time jitter for digital TDM systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Jitter; Computer science; Reduction (mathematics); Real-time computing; Telecommunications; Mathematics","score_opus":0.015718101566633114,"score_gpt":0.22067900270704338,"score_spread":0.20496090114041027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167467832","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":[0.026450863,0.00006082125,0.969436,0.0003570704,0.0000837035,0.0004557439,0.000019050975,0.0017416223,0.0013951552],"genre_scores_gemma":[0.81653136,8.898316e-7,0.18188833,0.00007525241,0.00005120665,0.00007611732,0.0000105086265,0.000019851288,0.0013465032],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987325,0.000009479703,0.00018687829,0.000521852,0.00014493377,0.0004043409],"domain_scores_gemma":[0.9986752,0.00007980444,0.00009220472,0.0009990362,0.00008559355,0.00006810987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074741634,0.0001760078,0.00017948521,0.00007875729,0.00012081957,0.00053760066,0.0010212304,0.00007064801,0.00001677099],"category_scores_gemma":[0.000058269055,0.00012931133,0.000029050321,0.00021541918,0.00007314076,0.002626931,0.00019183508,0.00008958292,0.00009618026],"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":[0.000064097396,0.0005946362,0.00021780697,0.00019578899,0.00019219684,0.00013994655,0.0010472197,0.0019359291,0.15917866,0.07248013,0.0234339,0.7405197],"study_design_scores_gemma":[0.00044713385,0.00041824544,0.0000062116947,0.000022593611,0.0000041071453,0.00006361725,0.00009061167,0.9896393,0.0064701014,0.0004214502,0.0021080733,0.0003085625],"about_ca_topic_score_codex":0.0000052141627,"about_ca_topic_score_gemma":9.338003e-7,"teacher_disagreement_score":0.9877034,"about_ca_system_score_codex":0.00007050802,"about_ca_system_score_gemma":0.000013825148,"threshold_uncertainty_score":0.5273163},"labels":[],"label_agreement":null},{"id":"W2168193772","doi":"10.1109/icpp.2008.34","title":"The MAP3S Static-and-Regular Mesh Simulation and Wavefront Parallel-Programming Patterns","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Parallel computing; Polygon mesh; Scripting language; Distributed memory; Asynchronous communication; Computation; Memory footprint; Programming paradigm; Distributed computing; Programming language; Shared memory; Computer graphics (images)","score_opus":0.026117773178392204,"score_gpt":0.2647671616772429,"score_spread":0.2386493884988507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168193772","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":[0.05017932,0.00024992955,0.94763774,0.0012839033,0.000053470212,0.00016134567,0.0000018067864,0.00039794456,0.000034555444],"genre_scores_gemma":[0.71119344,0.00020150459,0.28831995,0.00010663849,0.000009888733,0.000013659692,0.0000020958487,0.0000049614337,0.0001478464],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991552,0.000023552884,0.00014430897,0.0002835744,0.00016757686,0.00022577748],"domain_scores_gemma":[0.99911726,0.00021655101,0.00005610171,0.0005392015,0.000030564446,0.000040329007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011657748,0.00010696332,0.00009574992,0.000035647863,0.00034021432,0.00011026541,0.0003973711,0.000037822763,0.0000018994704],"category_scores_gemma":[0.00007614796,0.000070011134,0.000014170277,0.00009199221,0.00016616273,0.0005323077,0.00047743978,0.00008314032,0.0000047121816],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005957655,0.000019244273,0.00476916,0.000011100549,0.000019092096,0.000053707518,0.00089741783,0.0027931337,0.000051908235,0.07553058,0.00035722644,0.91549146],"study_design_scores_gemma":[0.0005741042,0.00016245633,0.01860333,0.000015839776,0.00000744032,0.000083965075,0.0006621168,0.90289956,0.00036563116,0.028391995,0.047819503,0.0004140783],"about_ca_topic_score_codex":0.00002652853,"about_ca_topic_score_gemma":0.000029848215,"teacher_disagreement_score":0.9150774,"about_ca_system_score_codex":0.000018768504,"about_ca_system_score_gemma":0.000009622644,"threshold_uncertainty_score":0.28549713},"labels":[],"label_agreement":null},{"id":"W2171562271","doi":"10.1109/dftvs.1994.630029","title":"Defect and fault tolerant scan chains","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Yield (engineering); Chain (unit); Fault tolerance; Computer science; Flow (mathematics); Scan chain; Fault (geology); Reliability engineering; Algorithm; Parallel computing; Mathematics; Engineering; Distributed computing; Biology; Materials science; Physics; Geometry","score_opus":0.020958442513807008,"score_gpt":0.22611046169002502,"score_spread":0.205152019176218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171562271","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":[0.016932111,0.0005641909,0.970267,0.0033999302,0.0000753268,0.000078478864,0.00000217177,0.0011174566,0.007563332],"genre_scores_gemma":[0.81899095,0.0001016522,0.17904879,0.000952193,0.000007619642,0.000006868366,4.1696958e-7,0.000004261446,0.0008872488],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993755,0.000007932606,0.00007488496,0.00026779753,0.0000977325,0.00017610576],"domain_scores_gemma":[0.99936485,0.000034101322,0.000021424452,0.00052917073,0.000013720296,0.0000367236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046365367,0.00007824418,0.000081051476,0.000062348976,0.00006778971,0.0000599455,0.0004854125,0.000029546452,0.00003053815],"category_scores_gemma":[0.000043543125,0.00006238621,0.000019009845,0.00019586178,0.00006318721,0.00042055402,0.0003829223,0.000073138486,0.00006758729],"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":[5.9186465e-7,0.00003142341,0.00028165532,0.0000044958824,0.000007958308,0.000045836965,0.000232815,0.000044963905,0.00085727853,0.26326004,0.015590819,0.7196421],"study_design_scores_gemma":[0.00079270906,0.00029341792,0.001615532,0.000024551613,0.0000060926322,0.00023761006,0.00015880763,0.7815182,0.00885123,0.017004801,0.18872473,0.00077229546],"about_ca_topic_score_codex":0.000012310834,"about_ca_topic_score_gemma":0.000016897693,"teacher_disagreement_score":0.8020588,"about_ca_system_score_codex":0.000016443591,"about_ca_system_score_gemma":0.0000023994658,"threshold_uncertainty_score":0.25440356},"labels":[],"label_agreement":null},{"id":"W2171837867","doi":"10.1109/isnetcod.2011.5978915","title":"Pipelined Regeneration with Regenerating Codes for Distributed Storage Systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Regeneration (biology); Computer science; Redundancy (engineering); Process (computing); Distributed data store; Data redundancy; Computer data storage; Computer network; Distributed computing; Database; Computer hardware; Operating system; Biology","score_opus":0.038173165719421226,"score_gpt":0.2431296144483664,"score_spread":0.20495644872894517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171837867","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027953207,0.00019863326,0.99466,0.0001394107,0.00018152206,0.00042776298,0.00006764268,0.0012521535,0.0002775298],"genre_scores_gemma":[0.41447625,0.0000038555404,0.5850408,0.000030674524,0.000037965907,0.00012326906,0.00007812744,0.000009587704,0.00019946144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893665,0.000026812457,0.00022260021,0.00041186437,0.00015188,0.00025016352],"domain_scores_gemma":[0.9987662,0.000056423843,0.00014052421,0.0008042079,0.00018927551,0.000043393706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001999044,0.00014999924,0.0001663918,0.000069640344,0.00018467271,0.00012061691,0.0006698445,0.000069449736,0.000002513553],"category_scores_gemma":[0.00012065678,0.00011029278,0.000022379325,0.00028507647,0.000051775784,0.00082240184,0.00014908801,0.000068418354,0.000005639423],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024451187,0.000046370114,0.00008977106,0.0000287988,0.000020338628,0.000012025125,0.00018306017,0.0073028975,0.0052386867,0.9758668,0.004359976,0.0068268073],"study_design_scores_gemma":[0.0007181498,0.00044966018,0.00006129302,0.000044009543,0.000012753433,0.00004175485,0.0002782572,0.8008684,0.19210523,0.002665353,0.0022878652,0.00046728272],"about_ca_topic_score_codex":0.00004337737,"about_ca_topic_score_gemma":0.000051018473,"teacher_disagreement_score":0.97320145,"about_ca_system_score_codex":0.000057605426,"about_ca_system_score_gemma":0.00004044843,"threshold_uncertainty_score":0.44976088},"labels":[],"label_agreement":null},{"id":"W2175650819","doi":"10.1007/978-3-540-85760-0_88","title":"Model Fusion Experiments for the CLSR Task at CLEF 2007","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Clef; Computer science; Information retrieval; Query expansion; Search engine indexing; Task (project management); Thesaurus; Natural language processing; Artificial intelligence; Relevance feedback; Image retrieval","score_opus":0.03839992547543713,"score_gpt":0.2800932661691769,"score_spread":0.24169334069373977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2175650819","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000036415415,0.0023861686,0.9930759,0.00079448137,0.0017052568,0.00088059704,0.00003242175,0.0004553452,0.00063338183],"genre_scores_gemma":[0.020599976,0.0006462105,0.975101,0.0020993322,0.00030834804,0.00007973612,0.0000138007445,0.0000554429,0.0010961809],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958586,0.000013147472,0.00048382723,0.0017968871,0.0010107321,0.0008367824],"domain_scores_gemma":[0.99569654,0.0007115206,0.0003353365,0.00294248,0.0002039682,0.000110122506],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00046489597,0.0006004206,0.00046890156,0.00047578994,0.0008736388,0.0002358876,0.0070589297,0.00040048058,0.000008638989],"category_scores_gemma":[0.00015402336,0.00044031974,0.0001608121,0.0004141188,0.0013706732,0.00078635785,0.0053603663,0.0006688686,0.000045361918],"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":[0.000022271242,0.00003809186,0.000007202125,0.000023142167,0.000016495305,0.00006646316,0.0010250066,0.23718259,0.0010815369,0.014579091,0.0028810955,0.74307704],"study_design_scores_gemma":[0.0002693374,0.00011966591,0.0000071662835,0.000092859016,0.000005439095,0.00007429159,2.4025195e-7,0.9107997,0.00367027,0.06885762,0.015544524,0.000558909],"about_ca_topic_score_codex":0.0000073338174,"about_ca_topic_score_gemma":0.000025105011,"teacher_disagreement_score":0.7425181,"about_ca_system_score_codex":0.00063940306,"about_ca_system_score_gemma":0.00031437818,"threshold_uncertainty_score":0.99980485},"labels":[],"label_agreement":null},{"id":"W2186809718","doi":"","title":"Service-Oriented Programming in MPI","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Concurrency; Cohesion (chemistry); Distributed computing; Data structure; Message passing; Service (business); Parallel computing; Cluster (spacecraft); Programming language","score_opus":0.013695795785110414,"score_gpt":0.24379289440406574,"score_spread":0.23009709861895533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186809718","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058450762,0.000034358764,0.9352013,0.0030817362,0.00009302534,0.00027612102,3.1644208e-7,0.0014400318,0.0014223836],"genre_scores_gemma":[0.2766465,0.0000025876427,0.72267234,0.00046032958,0.000005586213,0.000087626504,0.0000017509551,0.0000041663084,0.00011912188],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925596,0.000008819213,0.00012366036,0.00025490348,0.00010837392,0.00024830044],"domain_scores_gemma":[0.9992547,0.000024979441,0.000029112862,0.00061041274,0.000051612504,0.000029185592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055849483,0.00007602739,0.000076858705,0.00010746557,0.000026337642,0.000070409835,0.0008293807,0.000041785355,0.00003060363],"category_scores_gemma":[0.000045766323,0.00006319689,0.000010235143,0.0008424396,0.000021104668,0.0012329147,0.0006055595,0.000097227516,0.00041319546],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.264287e-7,0.00005972343,0.0022737046,0.000010121534,0.000002643533,0.000017379683,0.00026163162,0.00003894151,0.000991887,0.16302426,0.0011849174,0.83213425],"study_design_scores_gemma":[0.0026887446,0.00041977642,0.039865717,0.00015325405,0.0000049830705,0.00009400289,0.0047241845,0.38522562,0.04011937,0.21101725,0.3134183,0.0022687751],"about_ca_topic_score_codex":0.0003674846,"about_ca_topic_score_gemma":0.00022027039,"teacher_disagreement_score":0.82986546,"about_ca_system_score_codex":0.00003409535,"about_ca_system_score_gemma":0.000012442532,"threshold_uncertainty_score":0.53109294},"labels":[],"label_agreement":null},{"id":"W2189138427","doi":"10.1002/cpe.3724","title":"VMBackup: an efficient framework for online virtual machine image backup and recovery","year":2015,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Crandall University; University of New Brunswick","funders":"","keywords":"Backup; Data deduplication; Computer science; Throughput; Volume (thermodynamics); Partition (number theory); Operating system; Locality; Backup software; File system; Parallel computing","score_opus":0.04548490342768,"score_gpt":0.36892786904675084,"score_spread":0.3234429656190708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2189138427","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1543995,0.0019285838,0.8420461,0.00089517643,0.00031695963,0.00019131228,0.000029157263,0.00015877436,0.000034442466],"genre_scores_gemma":[0.43365404,0.00032386725,0.56549305,0.00042373507,0.000034870533,0.000029632041,0.000027623832,0.0000064938363,0.0000066657985],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874735,0.00007106852,0.00023330495,0.00056418957,0.00017488425,0.0002092254],"domain_scores_gemma":[0.9984352,0.00073275395,0.00018514231,0.00028113788,0.00020257123,0.00016319541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028894327,0.00016925344,0.0001729999,0.00007562407,0.00021288292,0.0002942733,0.00027687193,0.000080529244,0.000001197948],"category_scores_gemma":[0.0016756091,0.00015909987,0.000013795155,0.00021341808,0.00026962036,0.0028147704,0.00033368863,0.00018429598,0.0000023799437],"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":[0.00011267746,0.00021200281,0.000055436954,0.000025549463,0.00001106764,0.000016838703,0.010246908,0.0006417164,0.00018437789,0.1605614,0.00016621554,0.8277658],"study_design_scores_gemma":[0.0018238049,0.0025699488,0.00041856157,0.00009847508,0.00003310058,0.00033394742,0.02033252,0.86857104,0.00042693157,0.08864411,0.015936457,0.00081109774],"about_ca_topic_score_codex":0.000012832747,"about_ca_topic_score_gemma":0.0000019589806,"teacher_disagreement_score":0.86792934,"about_ca_system_score_codex":0.00001899741,"about_ca_system_score_gemma":0.00005524183,"threshold_uncertainty_score":0.6487905},"labels":[],"label_agreement":null},{"id":"W2196290691","doi":"10.1109/lcomm.2015.2496235","title":"Allocation for Heterogeneous Storage Nodes","year":2015,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Computer science; Node (physics); Distributed data store; Set (abstract data type); Computer data storage; Distributed computing; Storage efficiency; Limit (mathematics); Computer network; Mathematical optimization; Database; Mathematics","score_opus":0.08255395868495606,"score_gpt":0.31217187219852766,"score_spread":0.22961791351357158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2196290691","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":[0.008160166,0.0003740934,0.9716865,0.018396782,0.00024577105,0.00028525674,0.000015462509,0.0007350713,0.000100926045],"genre_scores_gemma":[0.5573292,0.000023855713,0.44093424,0.001460572,0.000017846525,0.00017934733,0.000029451716,0.000010197772,0.000015318781],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999136,0.00006531398,0.00019631977,0.00025719416,0.00013579085,0.00020941785],"domain_scores_gemma":[0.9953724,0.00019547423,0.00011317753,0.0041256873,0.00013024604,0.00006301468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025106137,0.00011801583,0.00011552056,0.00012215298,0.00018737114,0.0000999922,0.004063657,0.000049892256,4.2130668e-7],"category_scores_gemma":[0.00017312648,0.00012493471,0.000044936613,0.00028576684,0.00018343562,0.00067198643,0.0005733602,0.00012648437,0.000048282756],"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":[0.000049031496,0.00075834955,0.0004949182,0.000071868286,0.0002257805,0.00002655951,0.005087768,0.11216144,0.18460912,0.26539993,0.18004252,0.2510727],"study_design_scores_gemma":[0.0022210781,0.0002622211,0.00019949315,0.000056354165,0.000047397854,0.00012992439,0.0003476001,0.59817624,0.05674738,0.047043033,0.2932769,0.0014923689],"about_ca_topic_score_codex":0.000015713289,"about_ca_topic_score_gemma":0.000017423641,"teacher_disagreement_score":0.549169,"about_ca_system_score_codex":0.00015490843,"about_ca_system_score_gemma":0.00003730678,"threshold_uncertainty_score":0.7551353},"labels":[],"label_agreement":null},{"id":"W2198834745","doi":"","title":"Optimizing key-value stores for hybrid storage architectures","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); University of Toronto","funders":"","keywords":"Computer science; Key (lock); Associative array; Byte; Latency (audio); Database; Computer data storage; Throughput; Data access; Distributed computing; Operating system; Telecommunications","score_opus":0.013847699532386765,"score_gpt":0.253994088109063,"score_spread":0.24014638857667622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2198834745","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007406624,0.00012635312,0.98803097,0.00072970265,0.0003457919,0.00025287524,0.000010945004,0.0017566085,0.0013401249],"genre_scores_gemma":[0.3222459,0.0000027477874,0.67707384,0.0003691073,0.000055063487,0.000041410316,0.0000040653226,0.000012871818,0.00019500162],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986646,0.000035454384,0.00017984933,0.0005235947,0.00019860694,0.00039785798],"domain_scores_gemma":[0.99831444,0.00033912467,0.000084985935,0.0011499366,0.000046892743,0.00006463498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027250356,0.00018576471,0.00020003004,0.00016300667,0.00017610616,0.00012107384,0.0017045557,0.00004750923,0.000006079256],"category_scores_gemma":[0.00047789558,0.00015367629,0.00007246876,0.00015839252,0.00009564281,0.00032879025,0.00063614926,0.00014838445,0.000021012082],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012669606,0.00003851018,0.000019469448,0.000031284715,0.000020160187,0.00000987389,0.00034763277,0.04472299,0.0025458308,0.72697943,0.007435262,0.21783686],"study_design_scores_gemma":[0.0006869847,0.0003662814,0.00010905623,0.000024646633,0.000008621533,0.000042103475,0.00006695601,0.62534916,0.068643026,0.18311428,0.12094459,0.0006442682],"about_ca_topic_score_codex":0.000010293314,"about_ca_topic_score_gemma":0.000009126427,"teacher_disagreement_score":0.5806262,"about_ca_system_score_codex":0.000046096222,"about_ca_system_score_gemma":0.000022549235,"threshold_uncertainty_score":0.6266737},"labels":[],"label_agreement":null},{"id":"W2205921534","doi":"10.5555/2591305.2591334","title":"Checking the integrity of transactional mechanisms","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Journaling file system; Versioning file system; File system; Commit; Operating system; Unix file types; Database transaction; Metadata; Self-certifying File System; Overhead (engineering); Database; Stub file; Computer file","score_opus":0.021601762048756648,"score_gpt":0.2494147445418021,"score_spread":0.22781298249304544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2205921534","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":[0.0006822313,0.0000075879507,0.9954224,0.0015246447,0.00010409671,0.00003671801,9.374814e-7,0.00025360825,0.0019677756],"genre_scores_gemma":[0.6300366,0.0000014898504,0.369814,0.00010169814,0.000004349377,0.000002738541,2.3003835e-7,0.0000012626001,0.00003761212],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995378,0.000018414492,0.00009051249,0.00012855532,0.00013852987,0.00008618023],"domain_scores_gemma":[0.9993444,0.0001038111,0.000039586317,0.00047134497,0.000031048687,0.000009795659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024344685,0.000047589685,0.000063196814,0.00002927086,0.000050027753,0.000015521251,0.00092621613,0.00003209623,0.00001807262],"category_scores_gemma":[0.000074626434,0.000028060402,0.000025895026,0.00015448515,0.000060132268,0.0002657062,0.000113677765,0.0001358145,0.000009152225],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4136328e-7,0.0000062797776,0.0000039176584,0.000001431941,0.000002015037,1.2599976e-7,0.000031583073,0.000035751415,0.0037599318,0.9319237,0.000055696357,0.06417914],"study_design_scores_gemma":[0.00008973056,0.000045198198,0.0002825018,0.000005382341,0.0000018146164,0.000008654221,0.00007816273,0.049441207,0.2129407,0.7340328,0.002995863,0.000077999684],"about_ca_topic_score_codex":0.000014044269,"about_ca_topic_score_gemma":0.000009098778,"teacher_disagreement_score":0.62935436,"about_ca_system_score_codex":0.000010492421,"about_ca_system_score_gemma":0.000010490417,"threshold_uncertainty_score":0.17211555},"labels":[],"label_agreement":null},{"id":"W2211113829","doi":"10.1109/tpds.2016.2623309","title":"Beehive: Erasure Codes for Fixing Multiple Failures in Distributed Storage Systems","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Replication (statistics); Erasure code; Overhead (engineering); Fault tolerance; Distributed data store; Erasure; Distributed computing; Transfer (computing); Reliability (semiconductor); Storage efficiency; Computer data storage; Parallel computing; Database; Decoding methods; Algorithm; Computer hardware; Operating system; Mathematics","score_opus":0.021082824733172027,"score_gpt":0.24937216893755124,"score_spread":0.2282893442043792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2211113829","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":[0.0062429006,0.0006556606,0.98176646,0.0005467784,0.00087584514,0.0010864895,0.00810021,0.0007190432,0.0000066104235],"genre_scores_gemma":[0.99572957,0.000088631925,0.0030975332,0.000011519746,0.000034869263,0.00078182295,0.00011625926,0.000022193793,0.00011760122],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99757737,0.00013309781,0.00059833383,0.0007899966,0.0003029529,0.00059825316],"domain_scores_gemma":[0.9978812,0.00081460946,0.0002094531,0.0008168192,0.00012885581,0.000149111],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003324568,0.0003706288,0.0005428836,0.00024146507,0.00033824958,0.00024768867,0.0007105792,0.0002589393,0.0000016064265],"category_scores_gemma":[0.00008704906,0.00027592218,0.00010079834,0.0004883908,0.00014847975,0.0008641192,0.000014026565,0.00021924873,0.0000125492825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031863226,0.00046002195,0.0009585604,0.00043926205,0.00019487093,0.00010513635,0.00024592792,0.9655244,0.008903435,0.011551127,0.0034913428,0.007807336],"study_design_scores_gemma":[0.0121266665,0.0009218321,0.0019303972,0.0017270895,0.00009191773,0.00025674506,0.002190521,0.9385277,0.0033327602,0.0017993291,0.034659866,0.0024351755],"about_ca_topic_score_codex":0.00024972408,"about_ca_topic_score_gemma":0.00016117223,"teacher_disagreement_score":0.9894867,"about_ca_system_score_codex":0.00025227288,"about_ca_system_score_gemma":0.000055879347,"threshold_uncertainty_score":0.9999693},"labels":[],"label_agreement":null},{"id":"W2213340640","doi":"10.1145/2814342","title":"Non-volatile storage","year":2015,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.08029819176554973,"score_gpt":0.3173603981552479,"score_spread":0.2370622063896982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2213340640","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060592163,0.0057322006,0.6026739,0.29045367,0.0011357415,0.0011276264,0.00005975055,0.0017862014,0.03643877],"genre_scores_gemma":[0.4817436,0.000022026248,0.51807487,0.00005845934,0.000002841642,0.000010940779,0.0000016934408,0.0000029528069,0.00008260761],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99949086,0.00004201251,0.00013656144,0.0001071237,0.00013231584,0.000091126094],"domain_scores_gemma":[0.93679446,0.00012622931,0.000119674696,0.062833,0.00010136283,0.00002525758],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.00021236323,0.00005728796,0.00008396805,0.00004696187,0.00011503914,0.000021366162,0.07907902,0.000033040535,8.929316e-7],"category_scores_gemma":[0.006159337,0.00004250197,0.00003292796,0.00043877086,0.0002547654,0.00038666057,0.07725951,0.00015234532,0.00003312915],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006373291,0.0003462769,0.004470384,0.000016140986,0.00004779671,0.0000012338719,0.0032152277,0.0012122986,0.005345749,0.4589197,0.49213365,0.03428517],"study_design_scores_gemma":[0.00026064794,0.000038067126,0.0028017503,0.000028243352,0.000006997229,0.0000073818683,0.00023665321,0.02107874,0.0063964888,0.9018569,0.06713552,0.00015261755],"about_ca_topic_score_codex":0.000021303074,"about_ca_topic_score_gemma":0.000012633512,"teacher_disagreement_score":0.4429372,"about_ca_system_score_codex":0.00004393395,"about_ca_system_score_gemma":0.00007304746,"threshold_uncertainty_score":0.93020344},"labels":[],"label_agreement":null},{"id":"W2238818653","doi":"10.1016/j.jenvrad.2015.12.025","title":"Tritium dynamics in soils and plants grown under three irrigation regimes at a tritium processing facility in Canada","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Radioactivity","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa; Canadian Nuclear Safety Commission","funders":"Canadian Nuclear Safety Commission","keywords":"Tritium; Soil water; Environmental science; Irrigation; Hydrology (agriculture); Agronomy; Soil science; Nuclear physics; Geology; Biology; Physics","score_opus":0.010916967664449608,"score_gpt":0.2042589671859587,"score_spread":0.1933419995215091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2238818653","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":[0.86757904,0.00033379305,0.1309641,0.00085392164,0.00007096925,0.000096310396,0.00007057931,0.000010439737,0.000020843407],"genre_scores_gemma":[0.99732524,0.00015673344,0.0024600704,0.000027620978,0.000009524166,0.0000029668704,0.0000015800881,0.0000046508103,0.0000116393285],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99874157,0.00006590517,0.0003448133,0.00026217767,0.00033752684,0.0002479979],"domain_scores_gemma":[0.9991107,0.00026657383,0.0003132524,0.00023345469,0.0000043405107,0.00007166395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031466747,0.00014252728,0.00027081184,0.00013289422,0.00005609062,0.000022009874,0.00035029784,0.00006635054,0.000003670223],"category_scores_gemma":[0.00008323794,0.00011002829,0.000026324346,0.00010315573,0.0001440072,0.0017750954,0.00022537509,0.00023633809,5.875668e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020532528,0.00035001582,0.38079312,0.000041908625,0.000025690953,0.000585244,0.00015311356,0.0007192457,0.02596357,0.0004483234,0.000040806808,0.5906736],"study_design_scores_gemma":[0.002828007,0.00015664715,0.95841026,0.00018884441,0.0000067102133,0.00044498034,0.00047547265,0.013236306,0.011549907,0.012252802,0.00008083073,0.00036924126],"about_ca_topic_score_codex":0.008227497,"about_ca_topic_score_gemma":0.292548,"teacher_disagreement_score":0.5903044,"about_ca_system_score_codex":0.0060316953,"about_ca_system_score_gemma":0.00018172326,"threshold_uncertainty_score":0.9983768},"labels":[],"label_agreement":null},{"id":"W2259034356","doi":"","title":"TFN: Open Source and Innovation","year":2007,"lang":"en","type":"article","venue":"˜The œopen source business resource","topic":"Advanced Data Storage Technologies","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":"Open source; Business; Computer science; Operating system; Software","score_opus":0.033204892508496404,"score_gpt":0.292048794531601,"score_spread":0.2588439020231046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2259034356","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":[0.026214667,0.00026649726,0.95716566,0.0037015737,0.00011674484,0.001081929,0.0000051791467,0.00073641783,0.01071134],"genre_scores_gemma":[0.8618094,0.000035742265,0.10775242,0.007307272,0.00030335438,0.00015667912,0.000065157685,0.00016664296,0.02240337],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970182,0.000101654754,0.0006287819,0.001011812,0.0005106651,0.0007288875],"domain_scores_gemma":[0.99615115,0.00039121974,0.00049090007,0.0025126303,0.00036051223,0.00009361724],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0022094978,0.00039065033,0.00042312648,0.0004884691,0.0008953828,0.0021969439,0.010183028,0.00020197035,0.000019654748],"category_scores_gemma":[0.00036671764,0.00030465992,0.000030279101,0.005870904,0.00047018914,0.002121154,0.015505136,0.00037398783,0.000080287755],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012302736,0.00011596794,0.0011697982,0.000033882632,0.0000392691,0.000052896372,0.0014300599,0.001154261,0.001562076,0.0559785,0.011121917,0.9272183],"study_design_scores_gemma":[0.00085200253,0.00004571892,0.0065624015,0.000062602085,0.000011647638,0.00017167219,0.0008915357,0.0030534077,0.0007061856,0.005092801,0.9820201,0.00052991847],"about_ca_topic_score_codex":0.00037072267,"about_ca_topic_score_gemma":0.00011465002,"teacher_disagreement_score":0.9708982,"about_ca_system_score_codex":0.00010764269,"about_ca_system_score_gemma":0.000089414585,"threshold_uncertainty_score":0.9999406},"labels":[],"label_agreement":null},{"id":"W2265567111","doi":"10.14288/1.0165568","title":"Support for configuration and provisioning of intermediate storage systems","year":2014,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.008113819742226087,"score_gpt":0.18669342802813035,"score_spread":0.17857960828590427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2265567111","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":[0.38205335,0.00003792453,0.6173622,0.000017746432,0.00009185158,0.00018721279,0.000050102295,0.000085036976,0.00011461531],"genre_scores_gemma":[0.9862183,0.000019956,0.013594557,0.000006485514,0.0000069266885,9.3698367e-7,0.000012729221,0.0000042018373,0.00013593952],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993594,0.000023479524,0.00010937428,0.0002651894,0.00011938207,0.00012317441],"domain_scores_gemma":[0.9992331,0.000080551756,0.00019508597,0.0003054311,0.0001488103,0.00003696487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021320915,0.000028374541,0.00018878854,0.000046982852,0.00009682092,0.00007268982,0.0004647327,0.0000613489,0.00000197787],"category_scores_gemma":[0.00010363361,0.000090661,0.000030227297,0.00011819869,0.00019922206,0.0006992854,0.00023775561,0.000051717463,0.0000012578703],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000532653,0.00003322491,0.0009115225,0.00024906878,0.000015134561,0.000015234123,0.00022770402,0.000071060334,0.0016445521,0.000915847,0.0010455272,0.9948658],"study_design_scores_gemma":[0.0022219867,0.0009745544,0.87622964,0.00043314716,0.000032570562,0.00007856458,0.0017671045,0.11047196,0.00007339427,0.0037069232,0.0035873763,0.00042278707],"about_ca_topic_score_codex":0.0026569222,"about_ca_topic_score_gemma":0.0033333893,"teacher_disagreement_score":0.994443,"about_ca_system_score_codex":0.000023681088,"about_ca_system_score_gemma":0.000030046032,"threshold_uncertainty_score":0.40164894},"labels":[],"label_agreement":null},{"id":"W2277915713","doi":"","title":"Flash reliability in production: the expected and the unexpected","year":2016,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":184,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Reliability (semiconductor); Metric (unit); Flash (photography); Field (mathematics); Production (economics); Reliability engineering; Range (aeronautics); Scale (ratio); Real-time computing; Mathematics","score_opus":0.008727170278136739,"score_gpt":0.21130584997615653,"score_spread":0.2025786796980198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2277915713","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":[0.6725746,0.00930959,0.1036655,0.19661736,0.00069138425,0.0022948612,0.00014618573,0.013951718,0.00074882683],"genre_scores_gemma":[0.9847454,0.0008958662,0.0135526555,0.00004739187,0.000016539358,0.00034489256,0.0000021300125,0.0000082640645,0.00038686552],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986502,0.00008596651,0.0002273569,0.000586189,0.00016455,0.0002857619],"domain_scores_gemma":[0.9975211,0.00067365693,0.00010589042,0.0016305835,0.000055595792,0.000013192989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036370146,0.00018034024,0.00022312757,0.00013874908,0.0002481667,0.00008173898,0.0012261033,0.00014830836,0.000012445377],"category_scores_gemma":[0.0038509588,0.00007549809,0.000025640968,0.000782663,0.0019356611,0.0005993869,0.0014334432,0.00028784884,0.000009716497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097174816,0.00007420188,0.0017970947,0.000028634211,0.000028236449,0.000057873483,0.0016952481,0.000013145701,0.003160614,0.17658861,0.03743336,0.7790258],"study_design_scores_gemma":[0.0043661357,0.00040987614,0.03507878,0.00032755997,0.000025505498,0.00034218366,0.010775312,0.0022199226,0.03201387,0.7661018,0.14694968,0.0013894215],"about_ca_topic_score_codex":0.000017655593,"about_ca_topic_score_gemma":0.000046837577,"teacher_disagreement_score":0.7776364,"about_ca_system_score_codex":0.000053995722,"about_ca_system_score_gemma":0.000021219606,"threshold_uncertainty_score":0.71320236},"labels":[],"label_agreement":null},{"id":"W2291347940","doi":"10.14288/1.0073830","title":"Evaluation of the performance of frequency and chronological pairing techniques in synthesising long-term streamflow","year":2013,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pairing; Streamflow; Term (time); Environmental science; Climatology; Geology; Econometrics; Computer science; Mathematics; Geography; Physics","score_opus":0.015335849389966254,"score_gpt":0.19937092376839421,"score_spread":0.18403507437842795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2291347940","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":[0.9928393,0.00018320487,0.0064795343,0.000042010077,0.00001867515,0.00028075397,0.0000073286396,0.000065122214,0.00008406952],"genre_scores_gemma":[0.98087007,0.00011511348,0.01900279,0.0000025127538,0.0000018087167,0.0000013570337,6.0179957e-7,0.000002502181,0.000003228542],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991759,0.000072262286,0.0001230416,0.0002256782,0.00028291828,0.00012017461],"domain_scores_gemma":[0.99915594,0.00004769861,0.00017128549,0.00040507945,0.00020410535,0.000015873811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038890337,0.00003193832,0.0001616359,0.00005479525,0.00006699112,0.000024934789,0.00069819565,0.000077446224,0.000011531234],"category_scores_gemma":[0.0001137422,0.00007222074,0.000030190487,0.00028633283,0.0003949342,0.00087342405,0.00047152946,0.00009495812,5.5121126e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.7026774e-7,0.0000310759,0.14761855,0.00004105971,0.000005037767,0.0000024338929,0.000048100945,0.000012467107,0.0037964706,0.000006167196,0.00000520521,0.8484331],"study_design_scores_gemma":[0.00016568314,0.000058578382,0.99121475,0.00033458573,0.00001142635,0.000012597338,0.000120630975,0.0060820845,0.00079006323,0.0011399502,1.9846327e-7,0.000069453396],"about_ca_topic_score_codex":0.0077190627,"about_ca_topic_score_gemma":0.014885324,"teacher_disagreement_score":0.84836364,"about_ca_system_score_codex":0.00008605582,"about_ca_system_score_gemma":0.00005372002,"threshold_uncertainty_score":0.9988886},"labels":[],"label_agreement":null},{"id":"W2296025542","doi":"","title":"sRoute: Treating the Storage Stack Like a Network.","year":2016,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Protocol stack; Computer network; Forwarding plane; Network packet; Operating system; Routing table; Distributed computing; Hypervisor; Throughput; Latency (audio); Stack (abstract data type); Routing protocol; Cloud computing; Wireless; Virtualization","score_opus":0.013229454221848585,"score_gpt":0.22493190732168838,"score_spread":0.2117024530998398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296025542","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":[0.017180357,0.0054027867,0.94996977,0.009295253,0.0005325191,0.00064098136,0.00037462852,0.015077454,0.0015262419],"genre_scores_gemma":[0.8813971,0.00127039,0.114054635,0.00030615216,0.000097447875,0.00034423472,0.000016418006,0.000044392185,0.0024692018],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979002,0.00005528669,0.00030307472,0.0007450769,0.00028156483,0.0007148154],"domain_scores_gemma":[0.99685997,0.0007148971,0.00021904244,0.00210193,0.00006373773,0.000040399806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028567927,0.0003415299,0.00032674606,0.00016282142,0.00052638265,0.00019659115,0.0024367191,0.0002747031,0.000059999496],"category_scores_gemma":[0.00071200635,0.00018180335,0.00006924354,0.00076624413,0.000696731,0.0010784643,0.0024554248,0.00036224996,0.000073119874],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001098525,0.000032218613,0.0004525205,0.000016251817,0.000042963384,0.00016052909,0.00022991166,0.0000644796,0.00089131505,0.07712897,0.13705106,0.7839188],"study_design_scores_gemma":[0.0014840798,0.00090332894,0.0037971926,0.00044885228,0.000044052867,0.00027899683,0.0038461778,0.0066487943,0.0046756747,0.18106951,0.79485637,0.0019469678],"about_ca_topic_score_codex":0.000013488392,"about_ca_topic_score_gemma":0.00002393751,"teacher_disagreement_score":0.86421674,"about_ca_system_score_codex":0.00010141372,"about_ca_system_score_gemma":0.000041754512,"threshold_uncertainty_score":0.7413725},"labels":[],"label_agreement":null},{"id":"W2310916783","doi":"10.5539/cis.v10n4p22","title":"Marketplaces for Digital Data: Quo Vadis?","year":2017,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":23,"is_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":"Commoditization; Computer science; Focus (optics); Data science; Status quo; Work (physics)","score_opus":0.036448094563854866,"score_gpt":0.30180217195152825,"score_spread":0.26535407738767336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2310916783","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":[0.0019082398,0.000018089855,0.9941801,0.0007872223,0.0004915662,0.00015362875,0.00006303686,0.00019715376,0.002200967],"genre_scores_gemma":[0.54162955,0.00003992495,0.45781386,0.00038933405,0.00005578378,0.0000109042885,0.000031537555,0.000002217101,0.000026858768],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907863,0.0000023111754,0.00017857448,0.00027921534,0.00024094948,0.00022031415],"domain_scores_gemma":[0.9976054,0.00006686564,0.00018877609,0.0019351951,0.00013863757,0.000065127024],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0004972246,0.00008636831,0.00008839014,0.00015253022,0.0009929781,0.00457915,0.0052197417,0.000025812024,5.700403e-7],"category_scores_gemma":[0.0004310518,0.000071912335,0.000011449334,0.00015269127,0.0006045214,0.092115864,0.004247262,0.00005198963,0.000020584985],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026733728,0.0000049239034,0.00027078032,0.000013796722,0.0000017605023,3.808678e-7,0.00017751665,0.000020654788,0.0000099058625,0.1099653,0.0035359836,0.88599634],"study_design_scores_gemma":[0.00033875118,0.00006920384,0.009809544,0.000017851686,0.000001304022,0.00002416951,0.000037648973,0.79937845,0.00024540682,0.0066922465,0.1831762,0.0002092365],"about_ca_topic_score_codex":0.0000014919477,"about_ca_topic_score_gemma":3.7044975e-7,"teacher_disagreement_score":0.88578707,"about_ca_system_score_codex":0.000017753553,"about_ca_system_score_gemma":0.000070946095,"threshold_uncertainty_score":0.9964542},"labels":[],"label_agreement":null},{"id":"W2335524246","doi":"10.1061/40628(268)34","title":"Comparison of HPC Methods for Long-Term Contaminant Modeling","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Message Passing Interface; Supercomputer; Grid; Speedup; Tributary; Domain decomposition methods; Parallel computing; Computational science; Fortran; Message passing; Geology","score_opus":0.14638383335329264,"score_gpt":0.4307498180346125,"score_spread":0.28436598468131985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335524246","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036223023,0.00070462504,0.99439305,0.00019893385,0.00017220825,0.00020711657,0.0000025379006,0.0003875059,0.00031171992],"genre_scores_gemma":[0.37721792,0.000015287063,0.6226214,0.000021585034,0.0000063248885,0.000015585814,0.0000011088331,0.0000042231745,0.000096551994],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990826,0.000024039544,0.00029336265,0.0002895943,0.000093743954,0.00021664918],"domain_scores_gemma":[0.9988464,0.00020077858,0.00010478028,0.000740384,0.000079493475,0.000028166738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020531754,0.00010429746,0.0002697383,0.00009074442,0.000055856322,0.000026215926,0.0010241887,0.000062144216,0.000013457668],"category_scores_gemma":[0.00015278939,0.000086813256,0.00005277664,0.0001826471,0.0000495522,0.00042521022,0.00037524774,0.00007742739,0.000006789691],"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":[0.000003391992,0.000117077456,0.0010740752,0.000039736344,0.0000151222475,0.0000019559511,0.00033166315,0.0030053882,0.0036387001,0.08537422,0.00045283072,0.90594584],"study_design_scores_gemma":[0.00018930505,0.000099427634,0.000047117675,0.000011897881,0.0000045587353,0.0000030698745,0.000044467928,0.95522946,0.04025111,0.0036877396,0.00031912158,0.00011269483],"about_ca_topic_score_codex":0.0000042827955,"about_ca_topic_score_gemma":0.0000049997534,"teacher_disagreement_score":0.9522241,"about_ca_system_score_codex":0.000026010674,"about_ca_system_score_gemma":0.0000053870895,"threshold_uncertainty_score":0.35401416},"labels":[],"label_agreement":null},{"id":"W2347294433","doi":"","title":"An Incremental Hash Algorithm for Hard Disk Integrity Check","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hash function; Computer science; Double hashing; Rolling hash; Hash chain; SHA-2; Hash tree; Secure Hash Algorithm; Cryptographic hash function; Collision resistance; Algorithm; Hash table; Function (biology); MDC-2; SWIFFT","score_opus":0.020783012111091927,"score_gpt":0.2959857010537808,"score_spread":0.2752026889426889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2347294433","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006372966,0.00007401032,0.99536234,0.0014064135,0.000027318072,0.0010656755,0.00011388717,0.0012490101,0.00006404532],"genre_scores_gemma":[0.010657514,0.000009508843,0.98760045,0.00086053857,0.00013439998,0.00052354933,0.0001620327,0.000011093269,0.000040901778],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99854904,0.000016848084,0.0002650012,0.00069961936,0.00013080299,0.0003386787],"domain_scores_gemma":[0.99853075,0.00004143976,0.00010151619,0.0011282648,0.0001039572,0.000094058065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014340157,0.00020064577,0.00018226527,0.00012257052,0.0002825423,0.00022390728,0.0022129864,0.00010157487,0.000002766014],"category_scores_gemma":[0.0000013063719,0.00020252439,0.000074166004,0.0003921009,0.000075676304,0.00085361896,0.00029514066,0.00022187413,0.000053231604],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.780344e-7,0.0001947036,0.000014533166,0.0000029466592,0.000006636148,6.8921906e-7,0.000067375535,0.000010075126,0.015261216,0.03079871,0.0031099173,0.9505323],"study_design_scores_gemma":[0.0010859205,0.0004640788,0.002983826,0.000019723087,0.000020512734,0.000059207618,0.00007687949,0.16201115,0.08231549,0.13706829,0.6129808,0.000914126],"about_ca_topic_score_codex":0.000007611723,"about_ca_topic_score_gemma":0.000003185833,"teacher_disagreement_score":0.9496182,"about_ca_system_score_codex":0.00010838594,"about_ca_system_score_gemma":0.000039645707,"threshold_uncertainty_score":0.82587045},"labels":[],"label_agreement":null},{"id":"W2349956703","doi":"","title":"Data Reusing Algorithm of Cholesky Decomposition on Clusters","year":2011,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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":"Cholesky decomposition; Computer science; Parallel computing; Overhead (engineering); Decomposition; Minimum degree algorithm; Reuse; Algorithm; Operating system; Incomplete Cholesky factorization","score_opus":0.051950806661547395,"score_gpt":0.30322432943867234,"score_spread":0.25127352277712495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2349956703","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044020492,0.000055650788,0.99778455,0.00019008582,0.000028712915,0.00039205255,0.00012867026,0.00045665677,0.000523428],"genre_scores_gemma":[0.010258885,0.0000143753205,0.98921114,0.00025303225,0.00003713658,0.00006574749,0.00013836025,0.000011639014,0.000009669795],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987517,0.000021259753,0.00028226504,0.0006118141,0.00013230268,0.00020067122],"domain_scores_gemma":[0.9971513,0.000049455943,0.00017336954,0.0025139786,0.0000680784,0.00004378321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012525369,0.00014162481,0.00015113602,0.00018468377,0.000121655656,0.000039505507,0.003437335,0.00006711115,0.0000031478621],"category_scores_gemma":[0.0000011710724,0.00014534216,0.00003151276,0.00046179557,0.00010479756,0.0006504093,0.0018226185,0.00014176736,0.00006943757],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019960357,0.00017474234,0.0000098960245,0.0000100669,0.00001535709,0.0000024123735,0.000177296,0.00003610238,0.0053668986,0.018976104,0.0014977641,0.97373134],"study_design_scores_gemma":[0.0015685062,0.00039663227,0.0027985652,0.00021010412,0.00006208071,0.0002016515,0.00013823855,0.17116088,0.27356872,0.060429845,0.48794183,0.0015229436],"about_ca_topic_score_codex":0.00001268954,"about_ca_topic_score_gemma":0.0000022339586,"teacher_disagreement_score":0.97220844,"about_ca_system_score_codex":0.000044037875,"about_ca_system_score_gemma":0.000024526928,"threshold_uncertainty_score":0.63874805},"labels":[],"label_agreement":null},{"id":"W2350336675","doi":"","title":"A Novel Fault-Tolerance Design of Parallel File System","year":2004,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Replication (statistics); Scalability; Fault tolerance; Cluster (spacecraft); Node (physics); Crash; File system; Distributed computing; Parallel computing; Operating system","score_opus":0.018149759806290727,"score_gpt":0.23844487589867625,"score_spread":0.22029511609238553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2350336675","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000610358,0.00014891454,0.9975508,0.00022163382,0.000017125902,0.0007897451,0.00015659892,0.0009456876,0.000108453125],"genre_scores_gemma":[0.02067799,0.0000070892515,0.978314,0.00009390742,0.000033135682,0.000806971,0.00003209741,0.000012840252,0.0000219825],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99874085,0.0000120620525,0.00033399713,0.0005032215,0.00015060489,0.00025927695],"domain_scores_gemma":[0.99844664,0.00009087939,0.00019277063,0.0011078834,0.000111412584,0.000050433242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079807454,0.00017127348,0.00022073713,0.00012663958,0.00013047982,0.00005344146,0.0019312981,0.00008256824,0.0000038822545],"category_scores_gemma":[0.0000016355664,0.00017220891,0.000055715904,0.0006517261,0.00010492816,0.00035699835,0.0004953363,0.00012723435,0.00012346568],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000058142773,0.0004245308,0.000004331319,0.00013096373,0.000039804127,0.000007358385,0.00044715477,0.26978955,0.0938645,0.5212936,0.0044761407,0.10951624],"study_design_scores_gemma":[0.00594911,0.00040636098,0.00083725573,0.0007229467,0.000048544312,0.0011018573,0.00033254994,0.25159675,0.18800554,0.061649147,0.48669043,0.0026594903],"about_ca_topic_score_codex":0.000020192463,"about_ca_topic_score_gemma":0.000001356491,"teacher_disagreement_score":0.4822143,"about_ca_system_score_codex":0.000116079755,"about_ca_system_score_gemma":0.00007750679,"threshold_uncertainty_score":0.70224756},"labels":[],"label_agreement":null},{"id":"W2354555150","doi":"","title":"A Research of MPI-Based Pseudo-random Sequence Parallel Encrypt Algorithm","year":2004,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Encryption; Sequence (biology); Parallel algorithm; Computation; Algorithm; Parallel computing; Random sequence; Mathematics; Distribution (mathematics)","score_opus":0.04655243412140466,"score_gpt":0.3421390333069575,"score_spread":0.29558659918555286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2354555150","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00056974025,0.0001911749,0.9957632,0.0017199347,0.000016144182,0.0009335739,0.000046349687,0.0006093878,0.00015050193],"genre_scores_gemma":[0.029172461,0.000028606362,0.96973693,0.00018225049,0.00004392512,0.00077357003,0.00002815251,0.000015176845,0.000018915383],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997925,0.000059479833,0.0003958872,0.0007263579,0.0004109381,0.00048237958],"domain_scores_gemma":[0.99758834,0.00023869293,0.00013987267,0.0015916808,0.0003499743,0.000091426016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043188964,0.0001900536,0.0002525862,0.0003971376,0.00026933037,0.00009654436,0.0029789836,0.00011923187,0.000003872379],"category_scores_gemma":[0.0000054799466,0.00018870055,0.00008402167,0.0016817126,0.00044930293,0.000420165,0.0008018948,0.0003775903,0.00015175843],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008048515,0.000445879,0.00002316951,0.0000508184,0.00002688984,0.00002034427,0.00031795076,0.010805433,0.044495426,0.23897167,0.0010076043,0.7038268],"study_design_scores_gemma":[0.0053324467,0.00036080123,0.000349351,0.00016702416,0.000017978899,0.00013719121,0.00012419104,0.08286808,0.20086761,0.48784205,0.22084475,0.0010885262],"about_ca_topic_score_codex":0.00007043432,"about_ca_topic_score_gemma":0.000006448404,"teacher_disagreement_score":0.7027382,"about_ca_system_score_codex":0.00017285788,"about_ca_system_score_gemma":0.00027219,"threshold_uncertainty_score":0.7694985},"labels":[],"label_agreement":null},{"id":"W2354728713","doi":"","title":"Reducing Embedded Linux System Based on CF Card","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Operating system; File system; Embedded system; Flash (photography); Set (abstract data type); Card reader; Computer hardware; Programming language","score_opus":0.007693858344591762,"score_gpt":0.2283470728563963,"score_spread":0.22065321451180453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2354728713","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00051786436,0.00007295731,0.99326223,0.0005753312,0.000047839017,0.0006435017,0.000026927913,0.002516019,0.0023373174],"genre_scores_gemma":[0.19098638,8.35179e-7,0.8080077,0.00021523288,0.00016288446,0.0004741235,0.0000499508,0.000018867575,0.000084015795],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998349,0.000029883877,0.0003243871,0.0007513313,0.0002018754,0.0003434914],"domain_scores_gemma":[0.99799603,0.000104722836,0.0001410415,0.0016150866,0.0000912033,0.00005193229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011698379,0.00021958357,0.00020489539,0.00023956737,0.00027030698,0.00017715972,0.0016455373,0.000102817365,0.000001452788],"category_scores_gemma":[0.000001066948,0.00022143303,0.00008059898,0.0007201952,0.00006672957,0.0002445944,0.00036287526,0.00019836551,0.00027766873],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061916126,0.00039179638,0.00008760879,0.00013404358,0.00002337968,0.00003325192,0.00013304749,0.071383305,0.035879035,0.46724874,0.03104273,0.39363688],"study_design_scores_gemma":[0.00079705665,0.00009219355,0.00054503506,0.00013670427,0.000019300816,0.00008662869,0.000050775754,0.42641875,0.063147835,0.006061366,0.50174165,0.000902665],"about_ca_topic_score_codex":0.000035854868,"about_ca_topic_score_gemma":0.0000030013396,"teacher_disagreement_score":0.47069895,"about_ca_system_score_codex":0.00021634068,"about_ca_system_score_gemma":0.000056208923,"threshold_uncertainty_score":0.90297765},"labels":[],"label_agreement":null},{"id":"W2357474494","doi":"","title":"A Study Methods to Improve NAPI Polling Mechanism","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Polling; Computer science; Daemon; Network packet; Interrupt; Computer network; Real-time computing; Embedded system; Microcontroller","score_opus":0.020961980693664554,"score_gpt":0.34967926109076325,"score_spread":0.3287172803970987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2357474494","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016578876,0.000060131173,0.9943051,0.00046771238,0.00006797351,0.0018694797,0.0000075642674,0.0013775169,0.00018664576],"genre_scores_gemma":[0.031814143,0.0000014894956,0.96679705,0.0006343795,0.00009626369,0.00056152925,0.000003315964,0.000019646146,0.0000721902],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99806273,0.000038679926,0.00038322766,0.0008669991,0.00017396935,0.00047439817],"domain_scores_gemma":[0.99795073,0.00017957874,0.00010846847,0.0015084642,0.00011213494,0.0001406002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008288228,0.00021753418,0.00021368163,0.0003523818,0.00026654135,0.00015750043,0.0023868966,0.00007837303,0.000002154792],"category_scores_gemma":[0.0000048870797,0.00022094673,0.00005572032,0.0012471433,0.00003058427,0.000335969,0.0017120789,0.00021795937,0.0001909454],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014799787,0.00018379319,0.00001303502,0.000003283758,0.000017768742,0.000008149618,0.00067667797,0.00002233902,0.09430006,0.14571005,0.00016425151,0.7588991],"study_design_scores_gemma":[0.00072782754,0.00038995413,0.0006196438,0.000012110583,0.000024197192,0.00007061686,0.0007905618,0.0019584612,0.51909363,0.113753065,0.36160532,0.0009546062],"about_ca_topic_score_codex":0.000015679378,"about_ca_topic_score_gemma":0.000012581789,"teacher_disagreement_score":0.7579445,"about_ca_system_score_codex":0.00011687589,"about_ca_system_score_gemma":0.000030375526,"threshold_uncertainty_score":0.90099466},"labels":[],"label_agreement":null},{"id":"W2363783838","doi":"","title":"A Disk Scheduling Scheme with QoS Guaranteeing","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Computer science; Workload; Scheduling (production processes); Scheme (mathematics); Quality of service; Video server; Real-time computing; Server; Computer network; Distributed computing; Operating system","score_opus":0.00836128466471132,"score_gpt":0.2192626022034552,"score_spread":0.2109013175387439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2363783838","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030165879,0.00012694602,0.9616903,0.00055373413,0.000060686372,0.00008742127,0.000001044179,0.0017648448,0.0055491105],"genre_scores_gemma":[0.39220032,0.0000020609825,0.607513,0.000060764953,0.000027657969,0.000008123857,0.0000014770503,0.0000056854988,0.00018091907],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990173,0.000006886086,0.00013197123,0.00036634842,0.00019276311,0.00028475036],"domain_scores_gemma":[0.99908835,0.000037043927,0.00005439325,0.00076058635,0.00003921057,0.000020440817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007075436,0.00012518349,0.00011311089,0.00009226555,0.000106183346,0.0001126548,0.0008872766,0.00004211478,0.00000783732],"category_scores_gemma":[0.000030502035,0.00009166075,0.000020907066,0.0004638238,0.000079474834,0.0009887705,0.00037022278,0.00012957008,0.00005974834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000043560162,0.000039255083,0.0017345264,0.000008049351,0.0000075606727,0.000088079454,0.00002752972,0.0014526945,0.0054395464,0.9762496,0.0004015063,0.014547328],"study_design_scores_gemma":[0.0029692894,0.0005365403,0.0041262168,0.00028646356,0.000020537613,0.00042127425,0.0006201912,0.57332367,0.18409294,0.19750103,0.033529185,0.0025726338],"about_ca_topic_score_codex":0.00005685116,"about_ca_topic_score_gemma":0.00003929043,"teacher_disagreement_score":0.7787485,"about_ca_system_score_codex":0.000032696942,"about_ca_system_score_gemma":0.00002394016,"threshold_uncertainty_score":0.3737817},"labels":[],"label_agreement":null},{"id":"W2365345367","doi":"10.1109/isit.2016.7541297","title":"On storage allocation for maximum service rate in distributed storage systems","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Probabilistic logic; Replication (statistics); Service (business); Distributed data store; Exponential distribution; Computer data storage; Access time; Distributed computing; Storage efficiency; Computer network; Database; Operating system; Mathematics; Statistics","score_opus":0.026759069418296543,"score_gpt":0.2708120462032406,"score_spread":0.2440529767849441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2365345367","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":[0.0029212972,0.00016499114,0.98685086,0.0034449901,0.0018335654,0.0018948214,0.0009468026,0.0017006242,0.00024202268],"genre_scores_gemma":[0.9390985,0.00006044711,0.055929594,0.0006228595,0.00015960813,0.0021492844,0.0012298538,0.00008998637,0.0006599027],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969006,0.00017363922,0.0005974038,0.0014166277,0.0003346956,0.0005770296],"domain_scores_gemma":[0.9954796,0.00061529496,0.00047796193,0.003035289,0.000308354,0.000083519204],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009344816,0.00050766097,0.00057163346,0.00041730178,0.00009220546,0.00029730998,0.0034314825,0.0005498266,0.0000053238296],"category_scores_gemma":[0.0004903096,0.00041421002,0.000085071864,0.0005080856,0.000050261133,0.00065791584,0.0027078057,0.0005509005,0.000094418385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011385437,0.00031519766,0.000031138232,0.0013891216,0.000099441175,0.00012330762,0.00027043666,0.16558017,0.0019316523,0.7995201,0.015274814,0.015350766],"study_design_scores_gemma":[0.0015374878,0.00018943257,0.0003585281,0.0011336415,0.00001778098,0.0000075445637,0.00012733224,0.6370963,0.0020093687,0.34628323,0.009741514,0.0014978603],"about_ca_topic_score_codex":0.00011020361,"about_ca_topic_score_gemma":0.000101905534,"teacher_disagreement_score":0.9361772,"about_ca_system_score_codex":0.00087346014,"about_ca_system_score_gemma":0.00019864277,"threshold_uncertainty_score":0.99983096},"labels":[],"label_agreement":null},{"id":"W2365737598","doi":"","title":"Secure Access Mechanism in Smart Card File Systems","year":2004,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Smart card; Mechanism (biology); Computer security; Operating system; OpenPGP card; Embedded system; Smart card application protocol data unit","score_opus":0.013687853968190045,"score_gpt":0.25797552630032294,"score_spread":0.2442876723321329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2365737598","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00059024047,0.00017683933,0.9962491,0.0006997815,0.000053766445,0.00087690743,0.00014761965,0.00090792903,0.00029784787],"genre_scores_gemma":[0.09370847,0.000025800688,0.90352356,0.00034731784,0.00007990947,0.0020863437,0.00014253201,0.000022566772,0.000063486485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985654,0.000018197059,0.0002893396,0.0006321901,0.0001524275,0.0003424406],"domain_scores_gemma":[0.9986391,0.00005307567,0.000103908205,0.001078651,0.000064743144,0.000060539078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008807962,0.00018682628,0.00020351254,0.0002503033,0.00013069274,0.00029383236,0.0027304336,0.00011604101,0.000007535188],"category_scores_gemma":[0.0000015934258,0.00019402972,0.00004492511,0.00096398924,0.00004873485,0.0008012247,0.0012392136,0.00023210616,0.00020315741],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001190543,0.00018822102,0.00005421834,0.000052073534,0.00001823163,0.000030724783,0.000364812,0.007147967,0.003395438,0.9251212,0.008347254,0.05527868],"study_design_scores_gemma":[0.0009894095,0.00005255662,0.00082211266,0.00011353325,0.000007687217,0.00016530506,0.000081851635,0.007556628,0.014502754,0.25451756,0.7203528,0.0008377643],"about_ca_topic_score_codex":0.00013678108,"about_ca_topic_score_gemma":0.000046141537,"teacher_disagreement_score":0.7120056,"about_ca_system_score_codex":0.00020622481,"about_ca_system_score_gemma":0.000075254095,"threshold_uncertainty_score":0.7912302},"labels":[],"label_agreement":null},{"id":"W2371839255","doi":"","title":"Design and Implement for Smart IC Card File System","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; File system; Operating system; USable; Embedded system; Device file; Self-certifying File System; Virtual file system; Smart card; OpenPGP card; Computer file; Computer hardware; SSH File Transfer Protocol; Smart card application protocol data unit; World Wide Web","score_opus":0.018645985245611743,"score_gpt":0.2680699546070988,"score_spread":0.24942396936148709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2371839255","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006960209,0.00014590175,0.9969892,0.00021772459,0.00002091929,0.0015907122,0.00010986033,0.00079155306,0.00006452603],"genre_scores_gemma":[0.008979887,0.0000033044241,0.9894891,0.00012537386,0.00005014475,0.0012323479,0.00006552312,0.0000117190875,0.00004262457],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988627,0.000011423881,0.0002443917,0.00047495717,0.00008390532,0.0003226631],"domain_scores_gemma":[0.99882597,0.00030141798,0.000088856905,0.0006438074,0.00007620551,0.0000637189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002920886,0.00013689627,0.00014098,0.000120772114,0.0002373529,0.0000949069,0.0008020533,0.000057013895,0.0000020470723],"category_scores_gemma":[0.0000011584259,0.00013690714,0.00003330693,0.00027134037,0.000038855196,0.00019849975,0.00047255956,0.0000694392,0.000027840284],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042941715,0.000045090197,0.000020648235,0.00007622961,0.000027619206,0.0000033939912,0.0001909096,0.00006982073,0.010149775,0.14143331,0.04360805,0.8043709],"study_design_scores_gemma":[0.00038832575,0.00007385495,0.0002557483,0.000018877698,0.000011116481,0.00008308675,0.000082725055,0.009666211,0.032792028,0.005283567,0.95103264,0.00031182505],"about_ca_topic_score_codex":0.000006254542,"about_ca_topic_score_gemma":0.0000027875938,"teacher_disagreement_score":0.90742457,"about_ca_system_score_codex":0.00010206748,"about_ca_system_score_gemma":0.00002583263,"threshold_uncertainty_score":0.5582911},"labels":[],"label_agreement":null},{"id":"W2373342844","doi":"","title":"Design of NAND Flash Memory-based Embedded File System","year":2006,"lang":"en","type":"article","venue":"Jisuanji yingyong yanjiu","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Computer science; Flash file system; NAND gate; File system; Embedded system; Flash (photography); Flash memory emulator; Flash memory; Block (permutation group theory); Operating system; Computer hardware; Computer memory; Semiconductor memory; Logic gate","score_opus":0.017510722838874258,"score_gpt":0.23364003085311233,"score_spread":0.21612930801423808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2373342844","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":[0.008859212,0.00022086407,0.9861197,0.00007634293,0.00026225837,0.00042233846,0.000059270482,0.0018677011,0.0021123197],"genre_scores_gemma":[0.5816938,0.000001526957,0.4176427,0.00004440173,0.000050696344,0.000060057686,0.000037066464,0.000028892642,0.00044085042],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976989,0.00010557773,0.00054054236,0.0006453604,0.000501047,0.0005085743],"domain_scores_gemma":[0.9973036,0.00046790464,0.0003929104,0.0016119634,0.00016047456,0.000063146465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003818928,0.00029795239,0.00044531422,0.0003192155,0.00016678583,0.00010774812,0.0017310854,0.00018543996,0.000055050255],"category_scores_gemma":[0.00018426344,0.0002812723,0.00010231683,0.00085100136,0.00017687112,0.0006219926,0.00040056754,0.00020879909,0.00013715461],"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":[0.00020148081,0.0011162315,0.0013487601,0.0017426109,0.00019288737,0.0011757588,0.00087259104,0.26062697,0.16119097,0.1529537,0.35628456,0.062293492],"study_design_scores_gemma":[0.0021767998,0.00044440952,0.0010888793,0.0005910065,0.000048485388,0.00008144928,0.00033934435,0.52868974,0.45337403,0.005364001,0.0065032206,0.0012986092],"about_ca_topic_score_codex":0.000057583227,"about_ca_topic_score_gemma":0.000006446517,"teacher_disagreement_score":0.5728346,"about_ca_system_score_codex":0.00016693813,"about_ca_system_score_gemma":0.00013867154,"threshold_uncertainty_score":0.99996394},"labels":[],"label_agreement":null},{"id":"W2377100104","doi":"","title":"The Data Encrypt System of Hard Disk Based on the DSP","year":2005,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Encryption; Scheme (mathematics); Disk encryption; Disk encryption hardware; Software; Digital signal processing; Embedded system; Computer hardware; Operating system; Filesystem-level encryption; Multiple encryption","score_opus":0.024882308071314987,"score_gpt":0.2544978956833124,"score_spread":0.2296155876119974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2377100104","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013145458,0.00018066527,0.98852,0.009613173,0.000021681852,0.0006466666,0.00010011614,0.0004483815,0.00033784052],"genre_scores_gemma":[0.08648655,0.000017855931,0.91237473,0.0005364741,0.000100708625,0.00038439632,0.00004012565,0.000011860151,0.00004732702],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99875176,0.00004772156,0.00028317573,0.0004857365,0.00020598965,0.00022564114],"domain_scores_gemma":[0.9946794,0.0005685342,0.00016987501,0.0044833813,0.00006847591,0.000030332432],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0003461095,0.00013812527,0.00012117328,0.000056598605,0.00043739853,0.00013990005,0.007154976,0.00004509337,0.0000017053079],"category_scores_gemma":[0.0000058701785,0.00008049279,0.000040778345,0.00047446287,0.00018350643,0.00027297286,0.0014597065,0.00017363013,0.00011654016],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021888081,0.000077392164,0.000027000555,0.0000152033845,0.00001668264,5.3324504e-7,0.000058253157,0.0012013023,0.0018805007,0.44042528,0.02144412,0.53485155],"study_design_scores_gemma":[0.00009835708,0.00001398355,0.0001720814,0.000017857688,0.0000055290016,0.000005256736,0.000030150593,0.23170619,0.004647144,0.0008027341,0.76239485,0.000105893836],"about_ca_topic_score_codex":0.000005720826,"about_ca_topic_score_gemma":0.000006239473,"teacher_disagreement_score":0.7409507,"about_ca_system_score_codex":0.000063394145,"about_ca_system_score_gemma":0.000047604277,"threshold_uncertainty_score":0.9982168},"labels":[],"label_agreement":null},{"id":"W2379939836","doi":"","title":"The file system design of mobile payment application for RF-SIM card","year":2011,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Operating system; OpenPGP card; Encryption; Mobile payment; Java Card; Debugging; Smart card; Realization (probability); File system; Card security code; Subscriber identity module; Card reader; Embedded system; Smart card application protocol data unit; Payment; Credit card; Mobile computing; Java; World Wide Web; Java applet","score_opus":0.022448747998793362,"score_gpt":0.24177157783905517,"score_spread":0.2193228298402618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2379939836","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024720255,0.00025288993,0.9955617,0.00005671438,0.000022966722,0.0031627938,0.00017463666,0.00054429576,0.0001992817],"genre_scores_gemma":[0.020973818,0.000024281484,0.9613555,0.000033387947,0.000037433012,0.017448805,0.00005512181,0.000015200898,0.000056456287],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988035,0.000023427197,0.0003629396,0.0004420449,0.00011693432,0.00025116594],"domain_scores_gemma":[0.99787056,0.00030615478,0.00025422554,0.0013615652,0.00016798989,0.0000394813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021891194,0.00014676206,0.00016919473,0.0000679139,0.00031281295,0.000042621905,0.0019967575,0.0000679132,0.0000021382011],"category_scores_gemma":[0.0000018240039,0.00011535952,0.00006858874,0.00035749722,0.000113719136,0.00018188985,0.00043218542,0.000075677875,0.00004482495],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007204388,0.00011676015,0.00000896906,0.00006400047,0.000038260085,3.0082836e-7,0.00042286448,0.0005940327,0.006403694,0.18800148,0.0150849195,0.7892575],"study_design_scores_gemma":[0.0003105248,0.00015771535,0.000100755286,0.000025132671,0.000021474263,0.000016954195,0.0002472795,0.04251654,0.077049166,0.014222612,0.8650147,0.00031716115],"about_ca_topic_score_codex":0.000014116256,"about_ca_topic_score_gemma":0.000001790649,"teacher_disagreement_score":0.84992975,"about_ca_system_score_codex":0.00008875235,"about_ca_system_score_gemma":0.000048356258,"threshold_uncertainty_score":0.47042248},"labels":[],"label_agreement":null},{"id":"W2380499005","doi":"","title":"Solving the Problem of the Bottleneck of Storage in a High-speed Data Acquisition System","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; SCSI; Bottleneck; Computer data storage; Data acquisition; Computer hardware; Speedup; Real-time computing; Embedded system; Operating system","score_opus":0.015195536549012295,"score_gpt":0.25040058350008576,"score_spread":0.23520504695107347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2380499005","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":[0.012676624,0.00019029736,0.9853583,0.000519803,0.000021496253,0.0009123968,0.0000613263,0.00016062442,0.000099120305],"genre_scores_gemma":[0.5211089,0.000003920164,0.47875834,0.00004178559,0.000024523551,0.00003346604,0.000016309134,0.0000063806747,0.000006321875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99866855,0.00004128176,0.00046694174,0.00040648333,0.00019805289,0.00021869387],"domain_scores_gemma":[0.99688315,0.00017884282,0.00034267706,0.0024872583,0.00008947957,0.000018605893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063789106,0.00011850361,0.00017630808,0.00012150832,0.0001225426,0.00003348315,0.0046756472,0.0000654126,6.5551586e-7],"category_scores_gemma":[0.000001782671,0.000079548954,0.000035621604,0.0010436724,0.00015883012,0.00036696202,0.0025393267,0.00016849984,0.0000056451727],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000102135655,0.0003539527,0.0013490283,0.00034979323,0.000050420942,0.000004829455,0.0014022727,0.003575437,0.14695357,0.5262258,0.0021643713,0.31756032],"study_design_scores_gemma":[0.004060905,0.00024640816,0.13166587,0.0017300298,0.00014474199,0.0003823586,0.002459256,0.19419281,0.4121437,0.055731572,0.1951787,0.0020636315],"about_ca_topic_score_codex":0.00007222423,"about_ca_topic_score_gemma":0.000043554377,"teacher_disagreement_score":0.5084323,"about_ca_system_score_codex":0.00009184482,"about_ca_system_score_gemma":0.000045494766,"threshold_uncertainty_score":0.86885935},"labels":[],"label_agreement":null},{"id":"W2383432666","doi":"","title":"Fault-tolerance Storage Scheme Based on RS Code","year":2010,"lang":"en","type":"article","venue":"Jisuanji gongcheng","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Alberta Paraplegic Foundation","funders":"","keywords":"Computer science; Fault tolerance; Scheme (mathematics); Computer data storage; Reliability (semiconductor); Construct (python library); Reliability engineering; Code (set theory); Distributed data store; Fault (geology); Embedded system; Storage efficiency; Distributed computing; Database; Computer hardware; Computer network","score_opus":0.015850724471855367,"score_gpt":0.2698606023715801,"score_spread":0.25400987789972473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2383432666","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":[0.2923715,0.000055394914,0.6956865,0.0026070247,0.0027273274,0.00036201856,0.000051542458,0.0026696878,0.0034689947],"genre_scores_gemma":[0.73964465,0.0000040553637,0.25932324,0.0006464844,0.00015298292,0.000038522154,0.0000073518545,0.000027714868,0.00015500229],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997767,0.000031957137,0.0002953893,0.0008566153,0.00048431574,0.00056475546],"domain_scores_gemma":[0.99596775,0.00019112174,0.00022457665,0.0033787363,0.000101996244,0.00013584213],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033665614,0.00031961087,0.00028564307,0.00019617994,0.00039149905,0.00029718375,0.003305757,0.0002437238,0.00003583462],"category_scores_gemma":[0.0007171005,0.00030598405,0.000094596864,0.00044892274,0.00026325686,0.0011033373,0.00070456794,0.0010182104,0.00031247357],"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":[0.00012988434,0.0011199377,0.010320032,0.00017035333,0.0000735014,0.0008596595,0.00068261666,0.01000507,0.2640875,0.5863159,0.017439172,0.108796395],"study_design_scores_gemma":[0.00157612,0.00022253495,0.009350638,0.00008129594,0.000009403521,0.000019587886,0.000058441776,0.8009838,0.09620756,0.005167373,0.0851265,0.0011967648],"about_ca_topic_score_codex":0.000015310166,"about_ca_topic_score_gemma":0.000057358215,"teacher_disagreement_score":0.7909787,"about_ca_system_score_codex":0.00007972946,"about_ca_system_score_gemma":0.000077883415,"threshold_uncertainty_score":0.9999392},"labels":[],"label_agreement":null},{"id":"W2384770151","doi":"","title":"Research of Secured Transferring Mechanism of Embedded NAS","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Confidentiality; IPsec; Computer security; Protocol (science); Mechanism (biology); Field (mathematics); Data security; Computer network; Encryption; The Internet; Operating system","score_opus":0.03440273599147873,"score_gpt":0.3320373622567921,"score_spread":0.29763462626531334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2384770151","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040536197,0.00012448063,0.9940536,0.00050209573,0.000008892373,0.0005374088,0.000015870528,0.00027486135,0.00042919698],"genre_scores_gemma":[0.45796162,0.000014207898,0.5419084,0.000027444536,0.000013231506,0.000054256325,0.0000047572885,0.0000044927197,0.000011606972],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986634,0.000039495953,0.0003502467,0.00040440573,0.00026855062,0.00027387578],"domain_scores_gemma":[0.99848104,0.00009411222,0.000089278394,0.0010494868,0.00024261193,0.000043498454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029681777,0.00011417915,0.00021205947,0.00034295412,0.000102788676,0.000026502936,0.001986469,0.00008717434,0.0000028413033],"category_scores_gemma":[0.0000020446635,0.00011763419,0.000061917206,0.0011524912,0.00011749709,0.00026877568,0.0003021993,0.00022052295,0.000013427169],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016015896,0.00010085538,0.0000010200165,0.000015843623,0.0000068931563,8.664425e-7,0.00045783177,0.00006569788,0.27144477,0.5946377,0.00019474402,0.13307217],"study_design_scores_gemma":[0.0002568256,0.00012823903,0.00011443561,0.00002856796,0.000003874692,0.000012126608,0.0000877028,0.003591349,0.735313,0.25016743,0.010147208,0.00014923219],"about_ca_topic_score_codex":0.0000061253427,"about_ca_topic_score_gemma":0.0000018288052,"teacher_disagreement_score":0.46386823,"about_ca_system_score_codex":0.000035679197,"about_ca_system_score_gemma":0.000049099293,"threshold_uncertainty_score":0.4796983},"labels":[],"label_agreement":null},{"id":"W2386196181","doi":"","title":"Judgment of Automatically Hierarchical Storage Critical Point in Chinese PC Environment","year":2011,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Tree traversal; File system fragmentation; Data striping; File size; Point (geometry); Preamble; Operating system; Algorithm; Data file; Device file; Computer network","score_opus":0.014497620867014139,"score_gpt":0.24920851796578114,"score_spread":0.234710897098767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2386196181","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007203161,0.00008761119,0.9905227,0.0008979624,0.00001641097,0.00053779996,0.000013082339,0.0003219558,0.00039935918],"genre_scores_gemma":[0.26676413,0.000010807286,0.732753,0.00013151228,0.000014528536,0.00030428832,0.000004919188,0.000009616504,0.0000072484468],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983596,0.000045267472,0.0005041889,0.0005566304,0.00020668907,0.00032759778],"domain_scores_gemma":[0.9985091,0.0001617254,0.00008811572,0.0011173789,0.000029908246,0.00009374277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001835228,0.000196086,0.00026521436,0.00022436983,0.000063577194,0.000026714142,0.0015682615,0.00009382233,0.000032980795],"category_scores_gemma":[0.0000073544834,0.00018036252,0.000066611,0.00040030017,0.00029330625,0.00033283385,0.001172533,0.00025454507,0.000093755945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011319981,0.002176348,0.0012434063,0.00010295064,0.00002964813,0.000045248245,0.0022084592,0.00039155042,0.016975116,0.7211448,0.00041539883,0.25525576],"study_design_scores_gemma":[0.0019105462,0.00056928035,0.08749578,0.00013320848,0.00003077482,0.00018959693,0.00011718222,0.08925094,0.031425335,0.75081164,0.03642367,0.0016420396],"about_ca_topic_score_codex":0.000011369915,"about_ca_topic_score_gemma":0.000002406376,"teacher_disagreement_score":0.25956097,"about_ca_system_score_codex":0.00010153111,"about_ca_system_score_gemma":0.000033286346,"threshold_uncertainty_score":0.735497},"labels":[],"label_agreement":null},{"id":"W2393190965","doi":"","title":"Xen-based Virtual Disk Scheduling Algorithm","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Data Storage Technologies","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; Virtual machine; Scheduling (production processes); Dynamic priority scheduling; Virtualization; Distributed computing; Fair-share scheduling; Operating system; Algorithm; Mathematical optimization; Cloud computing; Schedule","score_opus":0.007052656956907088,"score_gpt":0.2436838172126376,"score_spread":0.2366311602557305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2393190965","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015014259,0.000036471174,0.9949985,0.001102877,0.00008551305,0.00044489434,0.000032322092,0.0016712976,0.00012668106],"genre_scores_gemma":[0.030237203,0.0000026773614,0.9686021,0.0005047683,0.00015549698,0.00039805216,0.00004108225,0.000018244174,0.000040367606],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985498,0.000013599389,0.00025249124,0.00066804123,0.00016914582,0.00034687453],"domain_scores_gemma":[0.9981517,0.00011695312,0.00010694146,0.0014265102,0.000100135585,0.00009772936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000120987526,0.00020338804,0.00015889865,0.00018177947,0.00029096028,0.00020649868,0.0023659114,0.00012895429,0.000009842229],"category_scores_gemma":[0.0000031292575,0.00020638769,0.00006931079,0.00064878503,0.00016240444,0.00045946988,0.00068138377,0.00046867598,0.00033298656],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.683048e-7,0.000085582855,0.00003217718,0.0000030939946,0.0000059320023,0.0000026087837,0.00003030283,0.00038787498,0.028731737,0.075658515,0.00038709005,0.8946747],"study_design_scores_gemma":[0.00045226945,0.00004524842,0.00032338884,0.000008484946,0.000007713795,0.000036976922,0.000015456108,0.27735603,0.0558417,0.017037122,0.64833623,0.00053937855],"about_ca_topic_score_codex":0.0000062841896,"about_ca_topic_score_gemma":0.000006191974,"teacher_disagreement_score":0.89413536,"about_ca_system_score_codex":0.000034347635,"about_ca_system_score_gemma":0.00007725205,"threshold_uncertainty_score":0.84162456},"labels":[],"label_agreement":null},{"id":"W2399852705","doi":"10.5281/zenodo.3782956","title":"Project to set up Service for Seccure Remote Access to Files from Data File Linkages","year":2007,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Quebec Statistical Institute","funders":"","keywords":"Computer science; Database; Service (business); Set (abstract data type); World Wide Web; Business; Programming language","score_opus":0.14138178389263406,"score_gpt":0.34974422183086756,"score_spread":0.2083624379382335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399852705","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021851112,0.000029982268,0.9705263,0.0034724919,0.00018554837,0.0012696479,0.017174985,0.0027389023,0.0024170298],"genre_scores_gemma":[0.04310479,0.000078682686,0.8700829,0.0071184807,0.00082614814,8.4136246e-7,0.07387547,0.002975408,0.0019372831],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976464,0.00009172922,0.00028405906,0.0010268722,0.00040031626,0.000550653],"domain_scores_gemma":[0.9963094,0.00016918642,0.00011242573,0.0025957236,0.0006238598,0.0001894221],"candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00077707693,0.0001938306,0.00017649276,0.00037926342,0.0011319766,0.0015454964,0.010338284,0.00009271476,0.0016895225],"category_scores_gemma":[0.002883993,0.00020052408,0.000025342582,0.001724749,0.000048750822,0.001526057,0.016842844,0.0002463383,0.003137389],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031754404,0.000019794585,6.734455e-7,0.00003064155,0.000016101607,0.000012382274,0.0010943176,0.00007985358,0.00125785,0.00048237032,0.7822969,0.21467738],"study_design_scores_gemma":[0.00023468652,0.00016090994,0.00025538733,0.00005121163,0.0000052945,0.000017322009,0.00036740693,0.0054151393,0.0019582678,0.00070113083,0.99057657,0.0002566959],"about_ca_topic_score_codex":0.0001268021,"about_ca_topic_score_gemma":0.00001801914,"teacher_disagreement_score":0.21442069,"about_ca_system_score_codex":0.00012390983,"about_ca_system_score_gemma":0.000011556554,"threshold_uncertainty_score":0.999491},"labels":[],"label_agreement":null},{"id":"W2406137460","doi":"","title":"Integrating SSD Caching into Database Systems.","year":2014,"lang":"en","type":"article","venue":"IEEE Data(base) Engineering Bulletin","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cache; Page cache; Cache algorithms; Cache pollution; Cache coloring; Cache invalidation; Smart Cache; Operating system; Write buffer; Database; Parallel computing; CPU cache","score_opus":0.017475425414346702,"score_gpt":0.23469413177487156,"score_spread":0.21721870636052484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406137460","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019415792,0.0003989064,0.99238086,0.0007191677,0.0014483411,0.00021759825,0.00034115094,0.002471212,0.00008118663],"genre_scores_gemma":[0.30199522,0.000028980918,0.696574,0.00014876407,0.0003132452,0.00005377873,0.00077295414,0.00006506705,0.000047987043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99717814,0.00007969352,0.00055616663,0.0011273043,0.0004298121,0.00062888354],"domain_scores_gemma":[0.9943968,0.00049736263,0.00018878568,0.004693148,0.00006676296,0.00015713653],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013234094,0.0004156575,0.00039322983,0.0002910385,0.00021318496,0.00040393492,0.0047900258,0.00012936373,0.000010524293],"category_scores_gemma":[0.0021491563,0.00040845328,0.000042094864,0.0004457324,0.000064253996,0.001014619,0.0022284493,0.0006921005,0.00033318295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018482597,0.00021202824,0.00009980708,0.0014024655,0.00016099295,0.00053431775,0.0006862494,0.41101187,0.11660167,0.18259145,0.21676588,0.06991477],"study_design_scores_gemma":[0.0002512378,0.000040982934,0.000005873614,0.00030420456,0.000010932488,0.000059034377,0.0000608531,0.68720484,0.0047220485,0.00007830692,0.30671582,0.000545889],"about_ca_topic_score_codex":0.00047580677,"about_ca_topic_score_gemma":0.00001687693,"teacher_disagreement_score":0.30005366,"about_ca_system_score_codex":0.00013897644,"about_ca_system_score_gemma":0.000038694743,"threshold_uncertainty_score":0.99983674},"labels":[],"label_agreement":null},{"id":"W2406955896","doi":"10.14778/2732219.2732227","title":"Multi-core, main-memory joins","year":2013,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":247,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Computer science; Hash join; Joins; Merge sort; Parallel computing; Join (topology); sort; Merge (version control); Hash function; Merge algorithm; SIMD; Theoretical computer science; Sorting algorithm; Database; Programming language; Mathematics","score_opus":0.025084745881657163,"score_gpt":0.23972005889048253,"score_spread":0.21463531300882538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406955896","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":[0.8213486,0.0009483462,0.13314387,0.015207855,0.0020279726,0.0050245067,0.000040970746,0.0032463418,0.019011538],"genre_scores_gemma":[0.7174404,0.00003140084,0.2813375,0.00027594803,0.000022863938,0.00014803898,3.528418e-7,0.000012247413,0.0007312035],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986787,0.0000025456607,0.00026379075,0.00036623367,0.00034696877,0.00034175487],"domain_scores_gemma":[0.9990351,0.00002954086,0.00024601497,0.00048375258,0.00015195974,0.000053631356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015331377,0.0001712422,0.00017982107,0.00010089971,0.00011487442,0.00008625915,0.002377629,0.00005808849,0.00001778731],"category_scores_gemma":[0.00020367735,0.000114008966,0.00008094415,0.00040837718,0.00016046836,0.0009050202,0.0019709168,0.00018189696,0.00008834002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005622714,0.00037227696,0.0024753208,0.00013199996,0.00006200668,0.00000252169,0.0010935223,0.000048989543,0.73581636,0.16327415,0.034097325,0.06261987],"study_design_scores_gemma":[0.0012631797,0.00017609917,0.013307141,0.00014629545,0.000019301426,0.00006153323,0.000941706,0.010638284,0.87452143,0.09271867,0.005639162,0.0005671781],"about_ca_topic_score_codex":0.000056718487,"about_ca_topic_score_gemma":0.0000018366054,"teacher_disagreement_score":0.14819363,"about_ca_system_score_codex":0.00010706523,"about_ca_system_score_gemma":0.000021492471,"threshold_uncertainty_score":0.4649151},"labels":[],"label_agreement":null},{"id":"W2418598077","doi":"10.1145/2908557","title":"Write Skew and Zipf Distribution","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Zipf's law; Computer science; Skew; Workload; Benchmark (surveying); Block (permutation group theory); Class (philosophy); Variety (cybernetics); Parallel computing; Artificial intelligence; Operating system","score_opus":0.01648730979935262,"score_gpt":0.2471854480837103,"score_spread":0.23069813828435767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2418598077","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":[0.0082438355,0.000095947675,0.98661345,0.0037231576,0.00021252104,0.00010447347,0.00016008267,0.0007820768,0.00006448037],"genre_scores_gemma":[0.9345832,0.0002105366,0.06469554,0.00010406218,0.000014502643,0.000030123085,0.000004746073,0.000009269182,0.000348048],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990373,0.000026608803,0.0001374432,0.000402027,0.0001668997,0.0002296826],"domain_scores_gemma":[0.99840915,0.00018604698,0.00004705958,0.001256287,0.000035235505,0.00006621284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000098777775,0.00013724205,0.0001189694,0.000091910864,0.00019617165,0.000052934578,0.0007606256,0.00008305671,0.00002182132],"category_scores_gemma":[0.000081815015,0.00010045493,0.000037679583,0.0002870713,0.00013147152,0.000945597,0.000046704157,0.0001348132,0.000097793236],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009838845,0.00006352244,0.000019075336,0.0000057916436,0.000013229621,0.000022972434,0.000051127576,0.00002013357,0.0038599158,0.021342281,0.00044564423,0.9741465],"study_design_scores_gemma":[0.0056406474,0.001620176,0.011229073,0.00043172424,0.00009423251,0.0004697603,0.00022135556,0.002676843,0.15633628,0.32082084,0.49773246,0.002726616],"about_ca_topic_score_codex":0.0000063531734,"about_ca_topic_score_gemma":0.0000071495306,"teacher_disagreement_score":0.9714199,"about_ca_system_score_codex":0.000099405974,"about_ca_system_score_gemma":0.000017764829,"threshold_uncertainty_score":0.40964332},"labels":[],"label_agreement":null},{"id":"W2440703972","doi":"10.1109/imw.2016.7495285","title":"NAND Flash Memory Revolution","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"NAND gate; Computer science; Flash file system; Flash memory; Flash (photography); Computer hardware; Flash memory emulator; Racetrack memory; Semiconductor memory; Embedded system; Computer memory; Mass storage; Charge trap flash; Logic gate; Memory refresh","score_opus":0.01380230087260963,"score_gpt":0.23357148039745948,"score_spread":0.21976917952484984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2440703972","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002777799,0.000082082304,0.9850728,0.0023623542,0.00016399042,0.00004733068,0.0000010350079,0.0011735989,0.008319018],"genre_scores_gemma":[0.37853548,0.00007059481,0.60951585,0.00021602146,0.000032629418,0.0000118784355,3.7305787e-7,0.0000055627024,0.011611595],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99943817,0.000009327969,0.0000783659,0.00022317244,0.00010253504,0.00014843547],"domain_scores_gemma":[0.99918044,0.00004790012,0.0000287548,0.0006942183,0.00002588823,0.00002281853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000078032936,0.000056557954,0.00005569449,0.000052328553,0.000041192787,0.000016340664,0.0006823675,0.00003675677,0.000023800298],"category_scores_gemma":[0.0001272346,0.000032528056,0.000015483589,0.00014889419,0.00006013737,0.00087668543,0.000411002,0.00002991321,0.0005081004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010863976,0.000008748056,0.00011571537,0.0000018069023,0.000002400383,0.000007971611,0.000014052678,0.0000013672961,0.02012398,0.2943832,0.03212384,0.6532158],"study_design_scores_gemma":[0.0010239906,0.00017667506,0.0035798862,0.000069951515,0.0000038730345,0.00007222153,0.000038231297,0.001521144,0.31034946,0.3693394,0.31317678,0.0006483559],"about_ca_topic_score_codex":0.0000024255532,"about_ca_topic_score_gemma":0.000004352554,"teacher_disagreement_score":0.65256745,"about_ca_system_score_codex":0.000046549347,"about_ca_system_score_gemma":0.000013641147,"threshold_uncertainty_score":0.6530772},"labels":[],"label_agreement":null},{"id":"W2440761015","doi":"10.1109/tcomm.2016.2581163","title":"A Class of Binary Locally Repairable Codes","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Erasure code; Binary number; Locality; Binary code; Block code; Erasure; Code (set theory); Computer science; Mathematics; Discrete mathematics; Algorithm; Arithmetic; Decoding methods","score_opus":0.03640963298082039,"score_gpt":0.28290905033410435,"score_spread":0.24649941735328396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2440761015","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":[0.00072842906,0.00014579527,0.99065036,0.0061340975,0.000107605505,0.00015084363,0.00007642073,0.00078509154,0.0012213506],"genre_scores_gemma":[0.76454127,0.0007146717,0.2341969,0.00006756049,0.0000020536881,0.00007464734,0.0000011840277,0.00000879317,0.00039289857],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990165,0.00009441523,0.00029280825,0.0002487554,0.00016631112,0.00018115898],"domain_scores_gemma":[0.9941911,0.0006031689,0.00011900175,0.0049118632,0.00013065914,0.000044191274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001667963,0.00011769044,0.00015919529,0.00021947922,0.00026348353,0.000018347337,0.0030217539,0.0000805501,0.000017444105],"category_scores_gemma":[0.00002999709,0.00009154108,0.000081411556,0.00059492944,0.00045232853,0.00064997305,0.000041082756,0.00018929405,0.000082422484],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046267556,0.0017145035,0.000033892393,0.000031982192,0.00015580571,0.000007374006,0.00046823276,0.0030304433,0.16522717,0.2741734,0.0028075504,0.5523034],"study_design_scores_gemma":[0.0031883642,0.0018503033,0.0005804022,0.0009871497,0.00011684615,0.000107626605,0.00047275986,0.089264534,0.67917204,0.10343829,0.11914787,0.0016738],"about_ca_topic_score_codex":0.000025758172,"about_ca_topic_score_gemma":0.000089142886,"teacher_disagreement_score":0.76381284,"about_ca_system_score_codex":0.00008445817,"about_ca_system_score_gemma":0.00008107953,"threshold_uncertainty_score":0.56152207},"labels":[],"label_agreement":null},{"id":"W2464321731","doi":"10.1109/bigdatasecurity-hpsc-ids.2016.35","title":"Parallel Simulation of Full-Field Polymer Flooding","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; CMG Reservoir Simulation Foundation; University of Calgary","keywords":"Scalability; Computer science; Grid; Reservoir simulation; Flooding (psychology); Computational science; Residual oil; Field (mathematics); Simulation; Parallel computing; Petroleum engineering; Geology","score_opus":0.0231334882041856,"score_gpt":0.275364808527053,"score_spread":0.2522313203228674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2464321731","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":[0.00829414,0.00006198318,0.98891354,0.0011989942,0.00007344074,0.00004076246,0.0000010198543,0.00036544495,0.0010507063],"genre_scores_gemma":[0.8314725,0.0000068557706,0.16812177,0.00007540664,0.000008479631,0.000002167519,1.3390434e-7,0.0000024058572,0.0003102509],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99945676,0.000007676672,0.00012703458,0.0001727544,0.00011273886,0.00012304434],"domain_scores_gemma":[0.999127,0.00024063927,0.000058148264,0.000528349,0.000028591981,0.000017325492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005336993,0.00005779182,0.00007652035,0.00006939655,0.000023103314,0.000009974225,0.0005372305,0.000044136545,0.000038015467],"category_scores_gemma":[0.00015652344,0.000035838257,0.000021680646,0.00014745875,0.00002816975,0.0006467106,0.00029130146,0.000027753387,0.000038237064],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000116152805,0.00002633427,0.00039464043,0.0000051345583,0.000010216587,0.0000042531756,0.000057954814,0.0023559157,0.10786889,0.45685813,0.0005858353,0.43182108],"study_design_scores_gemma":[0.00082637195,0.0003128838,0.00031303448,0.000058391408,0.000005008422,0.000008810272,0.000050325903,0.116114736,0.8211167,0.058671195,0.0021457407,0.0003768499],"about_ca_topic_score_codex":0.0000049726877,"about_ca_topic_score_gemma":0.0000030684573,"teacher_disagreement_score":0.8231784,"about_ca_system_score_codex":0.000011127913,"about_ca_system_score_gemma":0.00000929136,"threshold_uncertainty_score":0.14614417},"labels":[],"label_agreement":null},{"id":"W2471127798","doi":"10.1109/lpt.2016.2590983","title":"336 Gb/s in Direct Detection Below KP4 FEC Threshold for Intra Data Center Applications","year":2016,"lang":"en","type":"article","venue":"IEEE Photonics Technology Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ericsson (Canada); McGill University","funders":"","keywords":"Data center; Center (category theory); Optics; Computer science; Optoelectronics; Physics; Computer network","score_opus":0.021558323843048083,"score_gpt":0.26820378788373067,"score_spread":0.24664546404068258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471127798","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":[0.048944533,0.000104471204,0.92936313,0.017865952,0.0003698371,0.0010277857,0.00020834306,0.0020743099,0.000041639003],"genre_scores_gemma":[0.87532437,0.00016981308,0.12187396,0.0011380884,0.000032086642,0.0013800615,0.00002532279,0.000039693903,0.000016577413],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975738,0.000017050108,0.0004002289,0.0012018792,0.00016805714,0.00063899765],"domain_scores_gemma":[0.99567866,0.00015911151,0.00019544833,0.0038770225,0.00005010438,0.00003964218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003138654,0.00026573217,0.00029262708,0.00073766784,0.00015339574,0.000048660735,0.0044765347,0.00032932544,0.0000011708324],"category_scores_gemma":[0.00015491975,0.00022411246,0.000048885755,0.0010666751,0.0004077452,0.0009491168,0.0011305994,0.00036195407,0.000039264123],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019672012,0.00013396308,0.0011596178,0.00002165125,0.00004088763,0.000025992405,0.000023006509,0.000052176554,0.7165215,0.013983531,0.0017574203,0.2662606],"study_design_scores_gemma":[0.0017438028,0.00013376832,0.00015561341,0.00007355457,0.000017944274,0.00008262609,0.000022006618,0.01219561,0.86015266,0.028228555,0.096449636,0.00074425264],"about_ca_topic_score_codex":0.000008437336,"about_ca_topic_score_gemma":0.00014586296,"teacher_disagreement_score":0.82637984,"about_ca_system_score_codex":0.0003171793,"about_ca_system_score_gemma":0.00003851187,"threshold_uncertainty_score":0.9139041},"labels":[],"label_agreement":null},{"id":"W2473099193","doi":"10.1109/tpds.2016.2586059","title":"Durable Address Translation in PCM-based Flash Storage Systems","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Phase-change memory; Dram; Embedded system; Flash memory; Universal memory; Dynamic random-access memory; Overhead (engineering); Flash file system; Reliability (semiconductor); Non-volatile random-access memory; Computer hardware; Memory management; Semiconductor memory; Power (physics); Interleaved memory; Operating system; Computer memory; Memory refresh; Layer (electronics)","score_opus":0.0283094782003634,"score_gpt":0.2456543544431696,"score_spread":0.2173448762428062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2473099193","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":[0.004735766,0.00061918376,0.99118495,0.00047775212,0.0007981241,0.00060833065,0.00082000816,0.0006727037,0.00008318725],"genre_scores_gemma":[0.99749404,0.00009552193,0.0018697908,0.000015029901,0.000017223258,0.00030464062,0.000023733017,0.000016143105,0.00016388342],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796265,0.00015632996,0.00049677835,0.0006206985,0.00033233702,0.0004312306],"domain_scores_gemma":[0.9985335,0.00034691728,0.00014511091,0.0007838381,0.00007126236,0.000119355085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027724466,0.00027913315,0.00037277985,0.00029515996,0.00018650427,0.00017121129,0.0005384982,0.00021440291,0.0000045381967],"category_scores_gemma":[0.0000145870445,0.0002097592,0.00006466981,0.00058351946,0.000108379085,0.0008846528,0.000003896522,0.00020215272,0.000052028976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000086574626,0.00019335916,0.00007489424,0.00012737076,0.00003046425,0.00006543469,0.000082470215,0.9836034,0.0037200819,0.0027921689,0.00046168707,0.008762081],"study_design_scores_gemma":[0.006448933,0.00044403004,0.00054156437,0.0010228093,0.000036286223,0.00010669849,0.00043172002,0.9761853,0.0021678663,0.0005160701,0.0108837625,0.001214965],"about_ca_topic_score_codex":0.00013618227,"about_ca_topic_score_gemma":0.0000623813,"teacher_disagreement_score":0.9927583,"about_ca_system_score_codex":0.00019357514,"about_ca_system_score_gemma":0.00006166939,"threshold_uncertainty_score":0.85537314},"labels":[],"label_agreement":null},{"id":"W2491802577","doi":"10.1109/infocom.2016.7524628","title":"Reducing access latency in erasure coded cloud storage with local block migration","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Erasure code; Computer science; Server; Latency (audio); Cloud storage; Data striping; Cloud computing; Block (permutation group theory); Erasure; File server; Distributed data store; Computer network; Distributed computing; Operating system; Decoding methods; Algorithm; Telecommunications","score_opus":0.018279267161777628,"score_gpt":0.258097494909511,"score_spread":0.23981822774773337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2491802577","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":[0.17697282,0.000038399394,0.8194789,0.0023562321,0.00009960399,0.00013721208,0.000002644535,0.000613245,0.0003008905],"genre_scores_gemma":[0.9352611,0.000022614786,0.06421988,0.00008019651,0.000020644187,0.0000185321,0.0000013808066,0.000008828723,0.00036687206],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987738,0.00003288911,0.00019795635,0.00048211773,0.00022768023,0.00028556003],"domain_scores_gemma":[0.99891007,0.00007851408,0.000085538275,0.0008199804,0.00006492818,0.00004097473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015979027,0.00014618704,0.00015130149,0.00016119397,0.000055677232,0.00009033413,0.001217674,0.000085097985,0.000013579074],"category_scores_gemma":[0.000072596566,0.00008538492,0.000015960275,0.00060478604,0.000108364125,0.002009295,0.00043123405,0.00012765765,0.000032085183],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017544033,0.000441136,0.024653861,0.00007077212,0.00005773547,0.0007738603,0.001600521,0.019914882,0.059353355,0.15196756,0.01368976,0.7273011],"study_design_scores_gemma":[0.009260247,0.0018698772,0.049456175,0.001551245,0.00003368375,0.00041522976,0.000904535,0.20161438,0.63919103,0.074950114,0.016527638,0.004225818],"about_ca_topic_score_codex":0.00015484127,"about_ca_topic_score_gemma":0.00086649205,"teacher_disagreement_score":0.75828826,"about_ca_system_score_codex":0.00013314102,"about_ca_system_score_gemma":0.000062903295,"threshold_uncertainty_score":0.3481896},"labels":[],"label_agreement":null},{"id":"W2498947459","doi":"10.1108/rmj-07-2015-0028","title":"Archives as a trusted third party in maintaining and preserving digital records in the cloud environment","year":2016,"lang":"en","type":"article","venue":"Records Management Journal","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Tianjin University","keywords":"Cloud computing; Accountability; Originality; Business; Computer science; Internet privacy; Computer security; Political science; Law","score_opus":0.014321985889785113,"score_gpt":0.23478529185319866,"score_spread":0.22046330596341354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2498947459","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":[0.23541094,0.00033232884,0.7332653,0.009509379,0.00041848907,0.0005629828,0.0000060024076,0.00015848041,0.020336129],"genre_scores_gemma":[0.94271535,0.003189428,0.05277971,0.00026824142,0.00009342157,0.00005016125,0.0000012198366,0.000016003762,0.0008864636],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983442,0.00014400076,0.00038277602,0.000376689,0.0003117872,0.00044054867],"domain_scores_gemma":[0.998849,0.00029950298,0.00018352894,0.0006087034,0.00000448519,0.000054777953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007758433,0.00017281182,0.0001716706,0.0003486329,0.000120683384,0.00036211277,0.0015182954,0.000038631584,0.00002019639],"category_scores_gemma":[0.00013350982,0.00010357688,0.000040521423,0.00025287247,0.00010503513,0.001360811,0.0013734293,0.0003374426,0.000018308841],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003860168,0.00007692717,0.015510558,0.000012797006,0.000025976564,0.0006748813,0.0008458069,0.000069598245,0.000027581782,0.028729921,0.0005743212,0.953413],"study_design_scores_gemma":[0.002770609,0.000566922,0.05711264,0.0007321347,0.00001538305,0.0006230893,0.005201112,0.0060228417,0.00006672147,0.8287095,0.097518116,0.00066092366],"about_ca_topic_score_codex":0.0000076198658,"about_ca_topic_score_gemma":0.000020632784,"teacher_disagreement_score":0.9527521,"about_ca_system_score_codex":0.0001165667,"about_ca_system_score_gemma":0.000013503145,"threshold_uncertainty_score":0.42237425},"labels":[],"label_agreement":null},{"id":"W2510263867","doi":"10.1109/isit.2016.7541296","title":"Bandwidth adaptive &amp; error resilient regenerating codes with minimum repair bandwidth","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Distributed data store; Bandwidth (computing); Linear network coding; Coding (social sciences); Distributed computing; Computer network; Mathematics","score_opus":0.028236109347974908,"score_gpt":0.258848734211119,"score_spread":0.23061262486314407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2510263867","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020708919,0.00025064373,0.97088355,0.0018854418,0.00013358149,0.0002640736,0.000021078216,0.0028556988,0.0029970282],"genre_scores_gemma":[0.29784998,0.000026069518,0.69776773,0.00020670687,0.000037742015,0.00004618234,0.0000030058993,0.000018196386,0.0040444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99776703,0.000069495276,0.00030757074,0.00091703737,0.00041695667,0.0005219169],"domain_scores_gemma":[0.9974381,0.00028225005,0.0001661701,0.0018486327,0.00015602016,0.0001088296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002837756,0.0002834345,0.00027656285,0.00015260863,0.0002184104,0.000072925,0.0011557298,0.000099487545,0.00004030232],"category_scores_gemma":[0.0002873735,0.00015491323,0.000065040396,0.00046590256,0.00027297137,0.001129788,0.0007150996,0.00013421885,0.00012312667],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025353368,0.00023443936,0.0039458354,0.000029844912,0.00015942207,0.00018904154,0.0007223867,0.00080829026,0.02151346,0.7383343,0.074388646,0.1594208],"study_design_scores_gemma":[0.011815579,0.0071131303,0.007119003,0.0021690424,0.00014120097,0.00090877357,0.0021039518,0.054273687,0.58140934,0.0644456,0.2606929,0.0078077856],"about_ca_topic_score_codex":0.000026763957,"about_ca_topic_score_gemma":0.00039616725,"teacher_disagreement_score":0.6738887,"about_ca_system_score_codex":0.00012668256,"about_ca_system_score_gemma":0.00009450292,"threshold_uncertainty_score":0.63171786},"labels":[],"label_agreement":null},{"id":"W2513699951","doi":"10.1023/a:1012857830230","title":"Tracing Lineage of Array Data","year":2001,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Computer science; Lineage (genetic); Data structure; TRACE (psycholinguistics); Computation; Theoretical computer science; Algorithm; Programming language","score_opus":0.057932765758531964,"score_gpt":0.29900964598331875,"score_spread":0.2410768802247868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2513699951","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":[0.0033863536,0.00043509275,0.9939422,0.00010662604,0.0008726936,0.00010080394,0.000015888834,0.000055918335,0.0010844221],"genre_scores_gemma":[0.9386359,0.0003652372,0.060801502,0.000052114105,0.00009395131,0.0000012294377,0.000014305916,0.0000038019743,0.00003196112],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979606,0.000030023064,0.0013315275,0.0000710725,0.0004755132,0.00013124965],"domain_scores_gemma":[0.9968576,0.000102266094,0.0016338269,0.00089461356,0.00046314203,0.00004854812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010161815,0.00009341735,0.00025016634,0.00040299766,0.0000370717,0.00013062303,0.002215764,0.0000604132,0.0000040805994],"category_scores_gemma":[0.00041093034,0.00007196771,0.00004921696,0.00042596395,0.000031433785,0.00783077,0.00023886604,0.00018999106,0.00003882395],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016911763,0.00031250485,0.0016397847,0.00084047945,0.00039598843,0.000119476994,0.012317128,0.110032074,0.0052888882,0.093200065,0.021911746,0.75377274],"study_design_scores_gemma":[0.00078315084,0.0006048878,0.00013543932,0.0010901791,0.00003240917,0.0036048968,0.010303015,0.17162271,0.10801857,0.0006915548,0.7025954,0.0005178058],"about_ca_topic_score_codex":0.000008952787,"about_ca_topic_score_gemma":6.266754e-7,"teacher_disagreement_score":0.93524957,"about_ca_system_score_codex":0.000064771055,"about_ca_system_score_gemma":0.000064993495,"threshold_uncertainty_score":0.56771195},"labels":[],"label_agreement":null},{"id":"W2527982577","doi":"10.1109/jsac.2016.2603663","title":"Mitigation of Inter-Cell Interference in Flash Memory With Capacity-Approaching Variable-Length Constrained Sequence Codes","year":2016,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Division of Electrical, Communications and Cyber Systems; Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Computer science; Flash memory; Sequence (biology); Algorithm; Interference (communication); Constraint (computer-aided design); Computer hardware; Telecommunications; Mathematics","score_opus":0.04302865943478798,"score_gpt":0.27316601394612766,"score_spread":0.23013735451133968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527982577","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":[0.1856627,0.000054010452,0.8105174,0.0011667678,0.000078901074,0.00022717826,0.00003277153,0.0001527321,0.00210758],"genre_scores_gemma":[0.7377447,0.00018209557,0.26197234,0.000044875524,0.0000055771757,0.000023815695,0.0000038166595,0.0000091777,0.000013614091],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981528,0.00041324855,0.0006228583,0.00029223264,0.00021764543,0.00030122825],"domain_scores_gemma":[0.99616927,0.0011929021,0.00051412254,0.0016832763,0.00037317016,0.000067238376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067187945,0.00019612044,0.000299772,0.0006010716,0.00014116327,0.00007383305,0.0032454117,0.00010449531,0.0000049436844],"category_scores_gemma":[0.00062593486,0.00014388835,0.000027483682,0.0013975877,0.0005103782,0.0011322745,0.00031330116,0.0009782794,0.0000049160685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031345736,0.0024279351,0.012265602,0.00011050648,0.0001551897,0.000089336754,0.0074272803,0.0076466473,0.56106806,0.21864091,0.00031325815,0.18954183],"study_design_scores_gemma":[0.013133652,0.0035884334,0.0068461704,0.016560784,0.00008472016,0.0022692415,0.0032252024,0.20884793,0.5271238,0.21411183,0.0010507478,0.0031574836],"about_ca_topic_score_codex":0.00003565339,"about_ca_topic_score_gemma":0.00040220754,"teacher_disagreement_score":0.552082,"about_ca_system_score_codex":0.00038309902,"about_ca_system_score_gemma":0.00031981064,"threshold_uncertainty_score":0.6030836},"labels":[],"label_agreement":null},{"id":"W2535194862","doi":"10.1109/ipps.1998.669927","title":"Using PI/OT to support complex parallel I/O","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Template; Computer science; Code (set theory); Pi; Source code; Programming language; Parallel computing; Mathematics; Set (abstract data type)","score_opus":0.17347582774738535,"score_gpt":0.3279133197847427,"score_spread":0.15443749203735735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2535194862","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001315562,0.000016043254,0.98480994,0.0015093418,0.000100247424,0.00012260173,0.0000039436113,0.0011548833,0.010967445],"genre_scores_gemma":[0.23144217,0.0000036822034,0.7665818,0.0011799355,0.000014643727,0.0000049289306,0.0000014766146,0.000006194524,0.00076521124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892795,0.000010605156,0.00016202072,0.0003749615,0.00019278578,0.00033169685],"domain_scores_gemma":[0.9988338,0.000028248203,0.00003780552,0.0009845159,0.000033885975,0.00008174469],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006318234,0.00012035595,0.00013573264,0.00012087045,0.00009531274,0.000083988605,0.0013511182,0.000042634332,0.00046660827],"category_scores_gemma":[0.000052552277,0.00010878925,0.0000284584,0.0004479725,0.000047666555,0.0006181044,0.00092320424,0.00008275821,0.0009368267],"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":[0.0000037650693,0.0001692739,0.0004961448,0.000012295883,0.000020891839,0.00024186094,0.0005090393,0.00824142,0.010934165,0.49293998,0.19563904,0.2907921],"study_design_scores_gemma":[0.000540008,0.0003715301,0.00079373503,0.0000116769725,0.000005629974,0.00019259595,0.00012007048,0.67470086,0.0039000395,0.019619536,0.29886818,0.00087614305],"about_ca_topic_score_codex":0.000017283139,"about_ca_topic_score_gemma":0.00001016597,"teacher_disagreement_score":0.66645944,"about_ca_system_score_codex":0.000054207285,"about_ca_system_score_gemma":0.0000079434885,"threshold_uncertainty_score":0.99984103},"labels":[],"label_agreement":null},{"id":"W2539233741","doi":"10.1109/iwqos.2016.7590388","title":"Zebra: Demand-aware erasure coding for distributed storage systems","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Erasure code; Computer science; Erasure; Distributed data store; Coding (social sciences); On demand; Distributed computing; Computer network; Decoding methods; Telecommunications; Multimedia","score_opus":0.023177639231397457,"score_gpt":0.2541247473978902,"score_spread":0.23094710816649275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2539233741","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":[0.00079854514,0.00015978428,0.9945942,0.0013013963,0.00047691813,0.00038810947,0.00026710314,0.0019254156,0.00008850443],"genre_scores_gemma":[0.94269603,0.000016609456,0.056453843,0.000056270204,0.00005408448,0.000115097115,0.000018322804,0.000014053882,0.00057569257],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99869144,0.000024714993,0.00022404238,0.00048249576,0.00019212006,0.00038520183],"domain_scores_gemma":[0.9984183,0.00032708776,0.000108350985,0.00095514365,0.0001259658,0.000065198044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023749708,0.00016607961,0.00021553521,0.00008212931,0.0001557728,0.00011908595,0.001240573,0.000107038286,0.0000062731497],"category_scores_gemma":[0.00029721032,0.000102460945,0.000052484087,0.00025805374,0.00006370549,0.0010189451,0.00043593094,0.000064839725,0.000043478394],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014568066,0.00004744667,0.00045111476,0.00009055844,0.000046619454,0.0000403398,0.000049441787,0.00031229475,0.010892454,0.9048317,0.051455606,0.03176785],"study_design_scores_gemma":[0.008700121,0.0011498547,0.0019553227,0.00111044,0.000070376926,0.00028017483,0.0009031887,0.34338954,0.1006654,0.08155345,0.45622513,0.003997014],"about_ca_topic_score_codex":0.0000053856047,"about_ca_topic_score_gemma":0.00000461253,"teacher_disagreement_score":0.94189745,"about_ca_system_score_codex":0.00013187001,"about_ca_system_score_gemma":0.00003265585,"threshold_uncertainty_score":0.4178236},"labels":[],"label_agreement":null},{"id":"W2540534323","doi":"","title":"Automated Storage Layout For Database Systems","year":2011,"lang":"en","type":"book","venue":"UWSpace (University of Waterloo)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo","keywords":"Database; Workload; Computer science; Database tuning; Information repository; Computer data storage; Database design; Converged storage; Database testing; Storage area network; Database administrator; Distributed computing; View; Operating system","score_opus":0.02360760125376264,"score_gpt":0.21120006410297565,"score_spread":0.18759246284921302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2540534323","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038819714,0.0021807938,0.9452359,0.0011232754,0.0032210469,0.004263405,0.0072188308,0.015763316,0.017111426],"genre_scores_gemma":[0.0002129123,0.000062295716,0.119718276,0.000012109379,0.000033618064,0.000001935835,0.00049033505,0.000037963528,0.87943053],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99817115,0.00004027415,0.0001859787,0.0008279328,0.0003241246,0.00045053835],"domain_scores_gemma":[0.99690175,0.000095652504,0.00053261465,0.0021148482,0.00024219202,0.00011296773],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002209883,0.00038728045,0.00066205085,0.00049419305,0.00021356673,0.000048660713,0.0034400742,0.00046536943,0.000021028942],"category_scores_gemma":[0.000033900655,0.00044594868,0.00017071604,0.00017589297,0.00032056446,0.0011437451,0.0017052338,0.00031798094,0.00013912117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012087606,0.00017060587,0.000009843615,0.001993082,0.0004866484,0.00084898307,0.025298273,0.0006172163,0.00094569754,0.25407797,0.71143323,0.0039975895],"study_design_scores_gemma":[0.0043706293,0.0014344166,0.000044886707,0.002281288,0.0006141881,0.00011969032,0.019195605,0.2654029,0.00080978073,0.0123648085,0.6892,0.004161809],"about_ca_topic_score_codex":0.0036751449,"about_ca_topic_score_gemma":0.0010893873,"teacher_disagreement_score":0.8623191,"about_ca_system_score_codex":0.00029268867,"about_ca_system_score_gemma":0.00025281907,"threshold_uncertainty_score":0.99979925},"labels":[],"label_agreement":null},{"id":"W2547356383","doi":"10.1109/ccece.2016.7726758","title":"Write improvement strategies for serial NOR dataflash memory","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Serial communication; Embedded system; Efficient energy use; Power (physics); Consistency (knowledge bases); Data consistency; Energy (signal processing); Computer hardware; Database; Electrical engineering; Artificial intelligence; Engineering","score_opus":0.022013790169577354,"score_gpt":0.2665560023776994,"score_spread":0.24454221220812203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2547356383","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036983457,0.00001676275,0.9914413,0.0016128152,0.0004937953,0.00033250547,0.0001086487,0.0009786339,0.0013171675],"genre_scores_gemma":[0.14197534,0.000027365728,0.85381037,0.0004160372,0.00017125261,0.00014377045,0.0000150180795,0.000017277784,0.003423544],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988989,0.0000067559995,0.00018214704,0.00045023253,0.00014491532,0.00031705177],"domain_scores_gemma":[0.9985862,0.00011150205,0.000068561625,0.0011330821,0.000060143437,0.00004054597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013801146,0.00013390258,0.00012555739,0.00006417592,0.00006910388,0.00014353482,0.0014726035,0.000056098037,0.00003102637],"category_scores_gemma":[0.00007255355,0.00008205398,0.00003532609,0.00010987236,0.000083510444,0.0023695165,0.0008541065,0.000038641858,0.00010030494],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013136942,0.000025327045,0.0000044117614,0.000012021173,0.00001134551,0.0000038471076,0.00002909497,0.000006953061,0.12784708,0.4514036,0.013825884,0.40681732],"study_design_scores_gemma":[0.0028570301,0.0009789208,0.00007594269,0.000038296985,0.000010580939,0.000010704109,0.0006702007,0.0023451264,0.4652902,0.3680403,0.15886144,0.00082126487],"about_ca_topic_score_codex":0.0000105225035,"about_ca_topic_score_gemma":0.000049053146,"teacher_disagreement_score":0.40599605,"about_ca_system_score_codex":0.00004950737,"about_ca_system_score_gemma":0.00007647416,"threshold_uncertainty_score":0.33460644},"labels":[],"label_agreement":null},{"id":"W2547485880","doi":"10.1109/ccece.2016.7726822","title":"TEFS: A flash file system for use on memory constrained devices","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Reading (process); Operating system; Flash file system; File system; Flash (photography); Flash memory; Table (database); File Control Block; Random access; Computer file; File size; Interface (matter); Embedded system; Computer hardware; Stub file; Database; Computer memory","score_opus":0.029140634139565687,"score_gpt":0.25092714000227584,"score_spread":0.22178650586271015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2547485880","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001669057,0.000012773759,0.9916093,0.00066660426,0.00020657957,0.00033661062,0.00041052027,0.0022685733,0.0028200033],"genre_scores_gemma":[0.2634828,0.0000024175959,0.732431,0.00031119958,0.000035481076,0.0001846158,0.000010415446,0.000012949352,0.0035290993],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990109,0.000015446436,0.0001651174,0.00040684763,0.00013948754,0.00026216163],"domain_scores_gemma":[0.99792135,0.0009890511,0.00008422395,0.0008926403,0.000068025074,0.000044733333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001023895,0.0001303546,0.00014958839,0.00009597192,0.00007776534,0.00008917639,0.0009522816,0.000067563094,0.00005925888],"category_scores_gemma":[0.00036965692,0.00007660572,0.000043443313,0.00014423691,0.00009749347,0.0009887236,0.0002735951,0.000039257207,0.0002952877],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019334128,0.000041124564,0.000036042395,0.00006865031,0.000028420003,0.000033271717,0.000044158114,0.0000107862525,0.004421364,0.4779716,0.10592402,0.4114012],"study_design_scores_gemma":[0.0057476694,0.0017697865,0.0006050939,0.0017004561,0.00003375693,0.00021245056,0.0014162817,0.032248102,0.34471303,0.014680907,0.5945041,0.0023683526],"about_ca_topic_score_codex":0.0000052655528,"about_ca_topic_score_gemma":0.000019798936,"teacher_disagreement_score":0.4885801,"about_ca_system_score_codex":0.00007972738,"about_ca_system_score_gemma":0.000037728263,"threshold_uncertainty_score":0.37954244},"labels":[],"label_agreement":null},{"id":"W2553051330","doi":"10.1109/allerton.2015.7447076","title":"Near-optimal multi-version codes","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Server; Computer science; Coding (social sciences); Distributed data store; Storage efficiency; Theoretical computer science; Distributed computing; Algorithm; Computer network; Mathematics; Operating system","score_opus":0.04492166448017335,"score_gpt":0.2847865207008237,"score_spread":0.23986485622065037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2553051330","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0115929935,0.00006283728,0.98463374,0.00058230106,0.00014655999,0.000054248172,0.0000027658737,0.0013696745,0.0015548463],"genre_scores_gemma":[0.17265487,0.0000033209205,0.82653594,0.00013110116,0.000006491899,0.0000027293781,0.000002523979,0.000003291001,0.000659752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932855,0.000011609751,0.00007934248,0.0002408103,0.0001636149,0.00017609421],"domain_scores_gemma":[0.99920344,0.000023920818,0.000029026498,0.00061591744,0.00005852857,0.00006916769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000110560286,0.00007663967,0.00007797142,0.000039526945,0.000060501265,0.000087712455,0.00093700265,0.000047514575,0.000009884971],"category_scores_gemma":[0.00013775354,0.000062510044,0.000016654754,0.00020959253,0.00008621109,0.0008696515,0.00084279326,0.000079968915,0.00059675024],"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":[0.0000407319,0.00044636545,0.004559478,0.000017637914,0.00003924081,0.00035911912,0.0020780386,0.019496538,0.0042884005,0.39404306,0.291311,0.2833204],"study_design_scores_gemma":[0.0010800482,0.00021181516,0.00042665968,0.000008015778,0.000002932639,0.000039875336,0.0005140484,0.8090737,0.020075228,0.0045654057,0.16360533,0.00039693946],"about_ca_topic_score_codex":0.000025109823,"about_ca_topic_score_gemma":0.000006351172,"teacher_disagreement_score":0.7895772,"about_ca_system_score_codex":0.00004652606,"about_ca_system_score_gemma":0.000041466625,"threshold_uncertainty_score":0.7670216},"labels":[],"label_agreement":null},{"id":"W2559804471","doi":"10.1109/mascots.2016.23","title":"Write Amplification with Write Skew","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Garbage collection; Computer science; Skew; NAND gate; Key (lock); Simple (philosophy); Flash (photography); Parallel computing; Algorithm; Garbage; Operating system; Programming language; Logic gate; Telecommunications","score_opus":0.015085308354946777,"score_gpt":0.2322020196964039,"score_spread":0.2171167113414571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559804471","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017483116,0.00003432985,0.9897505,0.0041883998,0.000038959093,0.0000820935,0.0000033127517,0.0012960506,0.0028580376],"genre_scores_gemma":[0.40585062,0.00003244743,0.59233844,0.00019372783,0.000012755764,0.000017998289,0.0000012579812,0.00000590878,0.0015468347],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999248,0.00000890495,0.00009674159,0.00032294722,0.0001450955,0.00017829455],"domain_scores_gemma":[0.9987552,0.00006274189,0.000049415397,0.0010474082,0.000052367097,0.000032870994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007037245,0.00008406016,0.00007152724,0.00007116955,0.000051226332,0.000049503433,0.00086120004,0.000035231664,0.000020050113],"category_scores_gemma":[0.000042158706,0.00004406698,0.000011796261,0.0002656298,0.000084641426,0.0010527542,0.00023969218,0.000041344036,0.00033273562],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002230812,0.000011348744,0.00032534447,0.0000016541734,0.000003166856,0.000005357995,0.000015545149,0.0000010785117,0.0065480256,0.63483274,0.0010729433,0.3571806],"study_design_scores_gemma":[0.002005403,0.0006583393,0.018986253,0.00018224641,0.0000120999575,0.00017388629,0.00010571477,0.0021077322,0.18099488,0.33702984,0.45628837,0.0014552405],"about_ca_topic_score_codex":0.000004973742,"about_ca_topic_score_gemma":0.0000091562915,"teacher_disagreement_score":0.45521542,"about_ca_system_score_codex":0.000034266388,"about_ca_system_score_gemma":0.000017146607,"threshold_uncertainty_score":0.4276754},"labels":[],"label_agreement":null},{"id":"W2567395862","doi":"10.1145/2947658","title":"An Adaptive Demand-Based Caching Mechanism for NAND Flash Memory Storage Systems","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Design Automation of Electronic Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Hong Kong Polytechnic University; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Computer science; Flash file system; Cache; NAND gate; Embedded system; Flash memory; Exploit; Overhead (engineering); Locality of reference; Memory footprint; Locality; Overlay; Parallel computing; Computer hardware; Distributed computing; Operating system; Computer memory; Computer network; Semiconductor memory","score_opus":0.02651266147675879,"score_gpt":0.2594698317725862,"score_spread":0.2329571702958274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567395862","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":[0.0018914206,0.0002327193,0.99414045,0.00018787032,0.00052984076,0.0016792562,0.000048675432,0.0012769214,0.000012835108],"genre_scores_gemma":[0.904966,0.00001630468,0.09406589,0.00001873513,0.000025742855,0.00073471136,0.000004184454,0.000032558044,0.00013589258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974034,0.00039610255,0.00058836146,0.00062313105,0.00044497766,0.0005440405],"domain_scores_gemma":[0.99643344,0.0010678548,0.00047084288,0.0016581244,0.0002891166,0.00008061637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001052119,0.00029353832,0.00041392783,0.00048742982,0.00028989644,0.000099992394,0.001461189,0.00020822437,0.0000032495007],"category_scores_gemma":[0.00014349075,0.00023368525,0.00010577511,0.00041118695,0.00006447302,0.0013590106,0.000010513532,0.00016512204,0.000018075738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014335179,0.00021016228,6.8203974e-7,0.00014366074,0.00014703778,0.000003851298,0.00018683962,0.72668123,0.09338751,0.15026061,0.00013033242,0.028704727],"study_design_scores_gemma":[0.0012414798,0.001931657,0.0000033529104,0.00026889986,0.000036926634,0.000026036312,0.00013494787,0.8774019,0.11014789,0.008383785,0.00009120754,0.000331936],"about_ca_topic_score_codex":0.000031352833,"about_ca_topic_score_gemma":0.000008222986,"teacher_disagreement_score":0.90307456,"about_ca_system_score_codex":0.00065493205,"about_ca_system_score_gemma":0.00030626007,"threshold_uncertainty_score":0.95294076},"labels":[],"label_agreement":null},{"id":"W2572664398","doi":"10.1109/cloud.2016.0118","title":"Storage Benchmarking for Workload Aware Storage Platform","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ericsson (Canada)","funders":"","keywords":"Benchmarking; Workload; Computer science; Converged storage; Computer data storage; Information repository; Operating system; Storage area network; Database; Distributed computing; Embedded system","score_opus":0.027752605742791238,"score_gpt":0.26391097414127285,"score_spread":0.23615836839848162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2572664398","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":[0.00334182,0.00014485291,0.9915953,0.0011999874,0.00055888965,0.00033774477,0.000031213425,0.0017127569,0.0010773775],"genre_scores_gemma":[0.5646323,0.000044631455,0.43345386,0.0002513233,0.000115314644,0.0001052371,0.0000042994884,0.000020945696,0.0013720881],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983284,0.000009820637,0.00024633083,0.0006277326,0.0002468934,0.00054085633],"domain_scores_gemma":[0.998016,0.00038974022,0.00012387695,0.001303652,0.00008248478,0.000084219355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024581238,0.00021981743,0.00021303027,0.00016993958,0.00019577287,0.00010267884,0.0017661025,0.00012828918,0.00005721815],"category_scores_gemma":[0.00017628058,0.00014310532,0.00008342131,0.000334887,0.00009649137,0.0019980336,0.00082201115,0.00010301764,0.000085294465],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025462969,0.000028997163,0.00007347523,0.000013524818,0.000015650572,0.000025976397,0.00006950326,0.00004702714,0.0011696126,0.16578078,0.0088297175,0.82392025],"study_design_scores_gemma":[0.0060631097,0.0034467583,0.0016648357,0.0008542609,0.00003820366,0.00013891458,0.00056431134,0.07548302,0.060576122,0.33755347,0.50963724,0.003979767],"about_ca_topic_score_codex":0.00000394451,"about_ca_topic_score_gemma":0.00003774214,"teacher_disagreement_score":0.8199405,"about_ca_system_score_codex":0.00018750613,"about_ca_system_score_gemma":0.000056003097,"threshold_uncertainty_score":0.5835666},"labels":[],"label_agreement":null},{"id":"W2574626727","doi":"","title":"GarCoSim: A Framework for Automated Memory Management Research and Evaluation","year":2016,"lang":"en","type":"article","venue":"Scalable Information Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Garbage collection; Computer science; Heap (data structure); Memory management; Memory leak; Garbage; Manual memory management; Storage management; Benchmark (surveying); Virtual machine; Virtual memory; TRACE (psycholinguistics); Operating system; Programming language; Overlay","score_opus":0.0655612538902776,"score_gpt":0.3619225487499782,"score_spread":0.2963612948597006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2574626727","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":[0.001199707,0.00014577266,0.99197507,0.00065790367,0.0004016466,0.0016048346,0.000021846718,0.0012759924,0.0027172319],"genre_scores_gemma":[0.5645903,0.000087467924,0.4326005,0.0000846516,0.000053112573,0.002058974,0.000027706592,0.000012084397,0.00048520937],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983168,0.00007593525,0.0003660848,0.0002088292,0.0007112373,0.00032107375],"domain_scores_gemma":[0.99810517,0.000349581,0.0001537045,0.0007336606,0.00060653454,0.000051328137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002595982,0.00009779164,0.000122471,0.00040982102,0.00022310903,0.00034753035,0.00059596804,0.00010781887,0.0000037304249],"category_scores_gemma":[0.0004365695,0.00006914548,0.000014225928,0.00057305227,0.00008824829,0.003946916,0.0003802078,0.00007721743,0.0001809343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012122271,0.000011661904,0.000028767408,0.00020570715,0.00001901984,6.245887e-7,0.0003102091,0.00044529635,0.000054729073,0.7455625,0.012122222,0.24122716],"study_design_scores_gemma":[0.0016107599,0.00022029012,0.00037159157,0.0007215854,0.00000900687,0.000023103628,0.0017532601,0.7852406,0.0010782608,0.13812654,0.070501745,0.00034328163],"about_ca_topic_score_codex":0.000007238296,"about_ca_topic_score_gemma":5.2352084e-7,"teacher_disagreement_score":0.7847953,"about_ca_system_score_codex":0.00022870177,"about_ca_system_score_gemma":0.00004162846,"threshold_uncertainty_score":0.3351243},"labels":[],"label_agreement":null},{"id":"W2574861468","doi":"10.14778/3025111.3025123","title":"Skipping-oriented partitioning for columnar layouts","year":2016,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Flexibility (engineering); Workload; Column (typography); Big data; Analytics; Database; Data access; Distributed computing; Tuple; Data science; Data mining; Mathematics","score_opus":0.01434291533108535,"score_gpt":0.23476807476105574,"score_spread":0.2204251594299704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2574861468","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":[0.11725757,0.00019034992,0.8644633,0.012862764,0.000805689,0.0016032393,0.000063818836,0.0010286086,0.0017246163],"genre_scores_gemma":[0.89365506,0.000022688997,0.10550037,0.00012394342,0.00003544641,0.0002452632,5.232312e-7,0.000010727757,0.0004059721],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99891526,0.0000025113204,0.00023067441,0.00031657808,0.0002465552,0.00028840252],"domain_scores_gemma":[0.99914396,0.00007436513,0.00025237608,0.00028304875,0.00021134291,0.000034919198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020751003,0.00011681113,0.0001429627,0.00006379831,0.00015128404,0.00003933007,0.0012148201,0.0000423013,0.0000036040608],"category_scores_gemma":[0.00045207326,0.000068390524,0.00007458227,0.00028216143,0.00012035885,0.0006330317,0.0007509695,0.000051977673,0.0000067881774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024381512,0.00009930131,0.0029571836,0.00007087794,0.000042924246,3.314782e-7,0.00038364908,0.000011560366,0.1741098,0.7808163,0.0075515946,0.03393211],"study_design_scores_gemma":[0.0010390027,0.00020857065,0.0010894346,0.00027359748,0.000015310983,0.000010339279,0.00015946254,0.00044938462,0.857893,0.097135395,0.041492693,0.00023380577],"about_ca_topic_score_codex":0.0000034211646,"about_ca_topic_score_gemma":0.0000013059796,"teacher_disagreement_score":0.77639747,"about_ca_system_score_codex":0.00010462975,"about_ca_system_score_gemma":0.000019042704,"threshold_uncertainty_score":0.27888846},"labels":[],"label_agreement":null},{"id":"W2582747851","doi":"10.1109/tcomm.2017.2712186","title":"On the Average Locality of Locally Repairable Codes","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Locality; Computer science; Telecommunications","score_opus":0.05614801475095951,"score_gpt":0.3056711569567056,"score_spread":0.2495231422057461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2582747851","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":[0.000901327,0.00004222565,0.98377055,0.009415524,0.00013180023,0.00021575521,0.0000656144,0.00034855513,0.0051086457],"genre_scores_gemma":[0.94576466,0.0002603712,0.0534278,0.00020707546,0.0000026519226,0.00007811656,0.0000016192516,0.0000080811005,0.0002495972],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99899125,0.00013236268,0.0002552788,0.0002422094,0.00021271806,0.0001661683],"domain_scores_gemma":[0.9866584,0.0008736461,0.00022466309,0.012092823,0.00011637422,0.000034100998],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.00038459175,0.00012519762,0.00015421878,0.000082332095,0.001774233,0.000121320045,0.0070128385,0.0000729915,0.000018611243],"category_scores_gemma":[0.0001295445,0.00009704758,0.00009245777,0.00018586678,0.00083271804,0.0005111876,0.00007082364,0.00047051202,0.000065039225],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002401582,0.0008754184,0.000015339405,0.000014611714,0.00008776097,0.000003026793,0.000381179,0.015206265,0.0012521559,0.8952658,0.0013961907,0.0854782],"study_design_scores_gemma":[0.0012382903,0.0007644904,0.0010992492,0.00040951776,0.00007204473,0.00002787168,0.0003542164,0.36841717,0.19497149,0.40958518,0.022073818,0.0009866501],"about_ca_topic_score_codex":0.00014237757,"about_ca_topic_score_gemma":0.00028661106,"teacher_disagreement_score":0.9448634,"about_ca_system_score_codex":0.0000610837,"about_ca_system_score_gemma":0.00006165262,"threshold_uncertainty_score":0.9995253},"labels":[],"label_agreement":null},{"id":"W2583233440","doi":"","title":"An analysis of data corruption in the storage stack","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Checksum; Computer science; Operating system","score_opus":0.09062221339042517,"score_gpt":0.33647297026609246,"score_spread":0.2458507568756673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2583233440","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":[0.17665914,0.000028500279,0.8227924,0.00013473295,0.00001646984,0.00005275614,0.00003041938,0.00012338476,0.00016216209],"genre_scores_gemma":[0.8681769,0.00003160498,0.13160926,0.00008450857,0.0000030795543,0.0000020304635,0.000076602824,0.0000015018609,0.0000145658705],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991707,0.000053104905,0.00015293258,0.00029769941,0.00021704636,0.00010846801],"domain_scores_gemma":[0.99658954,0.000078217876,0.000067739085,0.0032270276,0.0000256771,0.000011801223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032375503,0.000057630576,0.00012802338,0.00027231703,0.000040408548,0.000018018825,0.0037960012,0.000030523555,0.000011315969],"category_scores_gemma":[0.000058218942,0.0000382671,0.00001752237,0.0018654737,0.00008679099,0.0017568402,0.0005161391,0.00008132696,0.000004846975],"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":[0.000036468453,0.0017432647,0.12898219,0.00002520835,0.00041493506,0.00062607345,0.011123824,0.07982938,0.00707744,0.45460144,0.008237282,0.3073025],"study_design_scores_gemma":[0.00011161842,0.00007127348,0.1018194,0.0000015872138,0.000027921289,0.000008333959,0.0005880645,0.8952206,0.00026807722,0.00083969557,0.0009313464,0.00011208004],"about_ca_topic_score_codex":0.00013239063,"about_ca_topic_score_gemma":0.0003381582,"teacher_disagreement_score":0.81539124,"about_ca_system_score_codex":0.000018470117,"about_ca_system_score_gemma":0.000018417139,"threshold_uncertainty_score":0.7053978},"labels":[],"label_agreement":null},{"id":"W2584388001","doi":"10.5555/2208461.2208468","title":"Recon: verifying file system consistency at runtime","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; File system; Versioning file system; Journaling file system; Unix file types; Operating system; Computer file; Self-certifying File System; File Control Block; Metadata; Device file; Consistency (knowledge bases); Database; Stub file","score_opus":0.025794155292794857,"score_gpt":0.23764791434289,"score_spread":0.21185375905009515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584388001","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":[0.0054270662,0.0014952786,0.7780299,0.00044799267,0.0018029392,0.00022198595,0.00009863144,0.0067910263,0.20568515],"genre_scores_gemma":[0.5270535,0.000009032593,0.4677655,0.00016121262,0.000061222876,0.00004141122,0.000017909628,0.000011640181,0.004878561],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990246,0.000020409614,0.00017314478,0.00025739736,0.00014278946,0.00038160427],"domain_scores_gemma":[0.9987056,0.00012307569,0.00007794127,0.0009909567,0.000029948578,0.00007246141],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014439727,0.0001168467,0.00014849799,0.00006628539,0.00016651355,0.000044702076,0.00080543704,0.00007152129,0.0005544353],"category_scores_gemma":[0.00009392331,0.000099955745,0.00003696274,0.00022999973,0.000060440303,0.0011924648,0.001041533,0.000089084395,0.0020216538],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044130657,0.000058560563,0.0018125875,0.00009920711,0.000032190277,0.000045036883,0.00037298395,0.0000102333215,0.001994572,0.6974522,0.20928143,0.0888366],"study_design_scores_gemma":[0.0006895031,0.00014626246,0.003392594,0.00019376773,0.000020816839,0.0009706584,0.0014148906,0.01427422,0.035567135,0.001456667,0.9404179,0.0014556098],"about_ca_topic_score_codex":0.00001038467,"about_ca_topic_score_gemma":0.000003167364,"teacher_disagreement_score":0.73113644,"about_ca_system_score_codex":0.0001757913,"about_ca_system_score_gemma":0.000015444144,"threshold_uncertainty_score":0.9987554},"labels":[],"label_agreement":null},{"id":"W2585172182","doi":"10.5555/1960475.1960476","title":"A study of practical deduplication","year":2011,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":193,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Data deduplication; Computer science; Backup; Computer file; Database; Metadata; Versioning file system; Operating system; File system; Redundancy (engineering); Torrent file; Journaling file system","score_opus":0.05731833433081558,"score_gpt":0.28889520902454924,"score_spread":0.23157687469373367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2585172182","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":[0.46712527,0.0005661758,0.5216766,0.00051307504,0.00010721542,0.0007821167,0.000060101658,0.007160636,0.002008815],"genre_scores_gemma":[0.8018571,0.000039654,0.19796766,0.000009405079,0.0000019172273,0.000096983196,0.0000025523866,0.0000049469922,0.000019735278],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99908096,0.00001931115,0.00020226851,0.00037581674,0.00014213295,0.00017953326],"domain_scores_gemma":[0.9985246,0.00010455269,0.00015521616,0.0011422348,0.00005709849,0.000016270373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100714635,0.00012512505,0.00018728372,0.00021336359,0.00007537093,0.000020828642,0.00081991544,0.00012763492,0.000022027738],"category_scores_gemma":[0.0006102265,0.000106320265,0.00001741085,0.00046859434,0.00020877096,0.0006485566,0.0010472223,0.0001948308,0.000011251371],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040258477,0.0021081762,0.004191218,0.00005257761,0.00009391186,0.00039169207,0.0071359384,0.0000040579835,0.0019818582,0.42124823,0.017232431,0.54551965],"study_design_scores_gemma":[0.0037339982,0.014019515,0.08683333,0.00017711562,0.00014274911,0.0008272717,0.15722159,0.006188385,0.16960171,0.53117955,0.027105372,0.0029694324],"about_ca_topic_score_codex":0.000025136467,"about_ca_topic_score_gemma":0.000010545771,"teacher_disagreement_score":0.5425502,"about_ca_system_score_codex":0.000017037908,"about_ca_system_score_gemma":0.00001936884,"threshold_uncertainty_score":0.43356144},"labels":[],"label_agreement":null},{"id":"W2585930566","doi":"10.5555/1855511.1855517","title":"Understanding latent sector errors and how to protect against them","year":2010,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Redundancy (engineering); Computer science; Field (mathematics); Data redundancy; Reliability engineering; Data reliability; RAID; Reliability (semiconductor); Latent variable; Risk analysis (engineering); Data mining; Database; Engineering; Machine learning; Operating system","score_opus":0.06511193931774845,"score_gpt":0.2381260531265218,"score_spread":0.17301411380877335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2585930566","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":[0.3578531,0.00025642427,0.6158576,0.013714261,0.0003812128,0.00095997716,0.00022393436,0.010179251,0.0005742541],"genre_scores_gemma":[0.8604815,0.00007963341,0.13907942,0.00007608356,0.000012536834,0.00012490666,0.000006592767,0.00001544137,0.00012390161],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99859947,0.000014211243,0.00012481435,0.000648661,0.00018933164,0.000423504],"domain_scores_gemma":[0.9986956,0.00012480577,0.00009236228,0.0009917355,0.00003355261,0.000061928185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000159369,0.0002594574,0.0002503342,0.0002905449,0.00029088656,0.00026766126,0.0010255901,0.00028500435,0.00001579828],"category_scores_gemma":[0.000742807,0.0002139862,0.000029368317,0.00054803764,0.00035947858,0.00065918016,0.0016688854,0.00059596443,0.000013843729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003332037,0.000105607876,0.0023717363,0.00017089036,0.00009428481,0.0005110692,0.001528642,0.000050560346,0.12016931,0.34658828,0.05722999,0.47114632],"study_design_scores_gemma":[0.0026761983,0.0022587115,0.007976684,0.000566357,0.000053035652,0.0008229056,0.019166073,0.023186725,0.21974126,0.46878666,0.2488091,0.005956279],"about_ca_topic_score_codex":0.0000049885844,"about_ca_topic_score_gemma":0.000035017736,"teacher_disagreement_score":0.5026284,"about_ca_system_score_codex":0.00006645223,"about_ca_system_score_gemma":0.00002253939,"threshold_uncertainty_score":0.8726104},"labels":[],"label_agreement":null},{"id":"W2587291453","doi":"10.29173/cais723","title":"Holographic Storage: Overcoming Limitations of the Optical Disk Medium for Applications in Libraries, Archives, and Information Centers","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Advanced Data Storage Technologies","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":true,"ca_institutions":"","funders":"","keywords":"Holography; Microform; Computer science; Information storage; Optical disc; Space (punctuation); Computer data storage; Digital holography; Scale (ratio); Information technology; Computer graphics (images); Digital media; Multimedia; World Wide Web; Information retrieval; Computer hardware; Library science; Optics; Physics; Operating system","score_opus":0.022274754522820964,"score_gpt":0.2257571208880378,"score_spread":0.20348236636521683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587291453","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":[0.93432945,0.00011622957,0.056490384,0.0063774437,0.000078764344,0.0013721838,0.00019673804,0.00008150283,0.0009573175],"genre_scores_gemma":[0.9706692,0.00011026796,0.028939592,0.0000794023,0.0000071953586,0.00017281534,0.0000058031087,0.0000056101926,0.000010099754],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99898297,0.000011287935,0.00039870036,0.00018285339,0.00020319577,0.000220991],"domain_scores_gemma":[0.99475753,0.0005097942,0.0005472573,0.0002962563,0.003841694,0.000047476828],"candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00016650584,0.00013909978,0.00023123756,0.00021403952,0.00010587289,0.0007505497,0.0020776244,0.00008266074,5.1014246e-7],"category_scores_gemma":[0.008530606,0.00009556587,0.000069490394,0.0005608688,0.00076102413,0.017782947,0.0011072151,0.00019563612,1.8418977e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036785197,0.00014499114,0.09094605,0.00032270604,0.00004561658,7.234043e-8,0.022900667,0.000034763376,0.012820312,0.82662255,0.0005543746,0.04557112],"study_design_scores_gemma":[0.0010440075,0.00029585123,0.7244727,0.00034878709,0.000054223186,0.000013872789,0.007916739,0.00834283,0.03504957,0.20473737,0.017328018,0.0003960484],"about_ca_topic_score_codex":0.000033909764,"about_ca_topic_score_gemma":0.0000060942702,"teacher_disagreement_score":0.6335266,"about_ca_system_score_codex":0.000017083812,"about_ca_system_score_gemma":0.000104998944,"threshold_uncertainty_score":0.99982095},"labels":[],"label_agreement":null},{"id":"W2592041560","doi":"10.1109/tnsm.2017.2679191","title":"Practical Network Coding for the Update Problem in Cloud Storage Systems","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Cloud computing; Linear network coding; Cloud storage; Distributed computing; Coding (social sciences); Computer network; Operating system","score_opus":0.03417553641555506,"score_gpt":0.2830107472452313,"score_spread":0.24883521082967622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592041560","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":[0.0000905159,0.00015762266,0.98610026,0.010117361,0.0016259087,0.0011674374,0.000006796213,0.00022555135,0.00050854124],"genre_scores_gemma":[0.7686317,0.0026585406,0.22549212,0.0016178739,0.00034442876,0.00097537047,0.000003343398,0.00003410803,0.00024252656],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985323,0.00005245259,0.00026034086,0.0004751879,0.00019316177,0.00048653642],"domain_scores_gemma":[0.99811006,0.00026530804,0.00017706209,0.001359015,0.000039221675,0.00004933262],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00067246816,0.00019495246,0.00020328253,0.000057762267,0.0013225737,0.0005739469,0.001169048,0.00007767559,0.0000018020328],"category_scores_gemma":[0.000003157105,0.00015348881,0.00004100322,0.00027564025,0.00006284419,0.0006479556,0.00006506773,0.00028683714,0.000010962968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047767917,0.00005317845,0.000009309721,0.00012198902,0.000082820465,0.000032978467,0.000075861455,0.8247632,9.4426025e-7,0.124931596,0.0038810505,0.04599932],"study_design_scores_gemma":[0.00081317825,0.000087426386,0.00019923135,0.00020833428,0.000070949995,0.000013737914,0.00025589237,0.9151733,0.000009945671,0.0063380837,0.07651278,0.00031715294],"about_ca_topic_score_codex":0.000052982406,"about_ca_topic_score_gemma":0.000338659,"teacher_disagreement_score":0.76854116,"about_ca_system_score_codex":0.00006385653,"about_ca_system_score_gemma":0.000014174551,"threshold_uncertainty_score":0.9999776},"labels":[],"label_agreement":null},{"id":"W2604156411","doi":"10.1145/3036669.3036680","title":"A Fast, Robust Network Flow-based Standard-Cell Legalization Method for Minimizing Maximum Movement","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Calgary","funders":"Mentor Graphics","keywords":"Legalization; Computer science; Standard cell; Path (computing); Design flow; Mathematical optimization; Algorithm; Enhanced Data Rates for GSM Evolution; Flow (mathematics); Theoretical computer science; Embedded system; Mathematics; Integrated circuit; Artificial intelligence; Computer network","score_opus":0.033304823114278695,"score_gpt":0.29592833384239875,"score_spread":0.26262351072812007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604156411","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002375249,0.00008483773,0.9948122,0.0016707982,0.0004174299,0.00048240568,0.0000319431,0.0006905028,0.0017861148],"genre_scores_gemma":[0.0017626581,0.0000069992866,0.996997,0.0005776181,0.00006962416,0.0000944897,0.000017510205,0.00001819872,0.00045588834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984818,0.000030600073,0.00024878114,0.00054803485,0.0002591358,0.00043160908],"domain_scores_gemma":[0.9976013,0.000106973326,0.00026565682,0.001833447,0.00013772145,0.000054943182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005367903,0.00018872805,0.00022610564,0.000073540075,0.00064957223,0.00051801454,0.0018518962,0.000090414724,0.000014303171],"category_scores_gemma":[0.0001922025,0.00017080327,0.000072324874,0.0001302554,0.00005788273,0.0010131645,0.0006573251,0.00009264355,0.0000060029365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053551106,0.000062268315,0.00011707007,0.000058883677,0.000020417503,0.000013201909,0.00006981081,0.56752783,0.0006717879,0.08046482,0.028307814,0.32263252],"study_design_scores_gemma":[0.00088988396,0.00013523879,0.000023601904,0.000024878793,0.0000086808595,5.8333893e-7,0.000033280718,0.91889983,0.022475425,0.03162069,0.025642637,0.000245266],"about_ca_topic_score_codex":0.000022682427,"about_ca_topic_score_gemma":0.00005147876,"teacher_disagreement_score":0.351372,"about_ca_system_score_codex":0.00010836681,"about_ca_system_score_gemma":0.00008230991,"threshold_uncertainty_score":0.6965155},"labels":[],"label_agreement":null},{"id":"W2604260473","doi":"","title":"Decibel: Isolation and Sharing in Disaggregated Rack-Scale Storage","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rack; Computer science; Isolation (microbiology); Abstraction; Scheduling (production processes); Shared resource; Computer data storage; Converged storage; Embedded system; Operating system; Distributed computing; Computer hardware; Information repository; Engineering","score_opus":0.02167406538979515,"score_gpt":0.28038742514472575,"score_spread":0.2587133597549306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604260473","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":[0.30252513,0.00007142551,0.6950631,0.0006096472,0.000078772704,0.000086786364,0.0000012885426,0.00034912536,0.0012147162],"genre_scores_gemma":[0.87626106,0.000028954311,0.12343931,0.000031878666,0.0000071976847,0.0000062498525,0.0000013672911,0.0000046306095,0.0002193553],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992429,0.0000066361727,0.00012028441,0.0003665372,0.00009038028,0.00017328963],"domain_scores_gemma":[0.99859226,0.00003075604,0.000092811875,0.001236572,0.000017262964,0.000030317598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013878911,0.00008478005,0.000102131555,0.00008703838,0.00019727106,0.00030292806,0.0011903914,0.00005625042,0.0000045739052],"category_scores_gemma":[0.00017058112,0.00007639757,0.0000101768455,0.00009154528,0.00008876246,0.0022687681,0.0014312408,0.000109568515,0.0000134285],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016245724,0.00008460484,0.23914826,0.000024165898,0.000009965891,0.00012447048,0.0009272588,0.00032690016,0.0071222223,0.13775386,0.0004636899,0.61399835],"study_design_scores_gemma":[0.0010535892,0.00006976736,0.38678032,0.000078301746,0.000002990924,0.000027680486,0.00012351408,0.5184817,0.006959237,0.08421905,0.001699063,0.0005048144],"about_ca_topic_score_codex":0.00008708814,"about_ca_topic_score_gemma":0.00039120458,"teacher_disagreement_score":0.61349356,"about_ca_system_score_codex":0.000036797355,"about_ca_system_score_gemma":0.00000754254,"threshold_uncertainty_score":0.31154025},"labels":[],"label_agreement":null},{"id":"W2616838521","doi":"","title":"Improving Storage System Reliability with Proactive Error Prediction","year":2017,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"RAID; Computer science; Redundancy (engineering); Reliability (semiconductor); Reliability engineering; Error detection and correction; Vulnerability (computing); Real-time computing; Algorithm; Engineering; Computer security","score_opus":0.026163643038317887,"score_gpt":0.26953802949831174,"score_spread":0.24337438645999385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2616838521","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":[0.034182526,0.000013237079,0.9584292,0.00060839806,0.00020745664,0.0007023234,0.00017523742,0.0035899382,0.002091651],"genre_scores_gemma":[0.8503267,0.0000026138046,0.14937778,0.000016225707,0.00003581899,0.0001275063,0.000005672919,0.00001591358,0.000091733156],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747896,0.000066276196,0.0003501509,0.0011004267,0.0005160624,0.0004880996],"domain_scores_gemma":[0.99505013,0.00010535665,0.00046311037,0.0037888284,0.00047869803,0.000113863476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046366933,0.0003081245,0.00035941903,0.00009961715,0.0007217698,0.0004565396,0.0034963253,0.00026062175,0.0000038712233],"category_scores_gemma":[0.0010703582,0.00024087842,0.000057812318,0.0001882979,0.0007102365,0.003424788,0.0018598624,0.0006740468,0.0000307054],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035288106,0.00053919223,0.0046294886,0.00040152672,0.00008661144,0.0005606748,0.0009436366,0.0002832898,0.015344099,0.78891927,0.0012161484,0.18672317],"study_design_scores_gemma":[0.009105833,0.011668516,0.3119217,0.0025279163,0.0003919631,0.0020981834,0.0075707226,0.4638712,0.105656564,0.057163052,0.019527674,0.008496663],"about_ca_topic_score_codex":0.000120443234,"about_ca_topic_score_gemma":0.00005282071,"teacher_disagreement_score":0.8161442,"about_ca_system_score_codex":0.0003070487,"about_ca_system_score_gemma":0.00020695257,"threshold_uncertainty_score":0.9822737},"labels":[],"label_agreement":null},{"id":"W2623963253","doi":"10.1007/s00607-017-0560-y","title":"Performance impacts of hybrid cloud storage","year":2017,"lang":"en","type":"article","venue":"Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Cloud computing; Computer science; Cloud storage; Operating system","score_opus":0.023440478562033733,"score_gpt":0.2770958936438562,"score_spread":0.25365541508182243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623963253","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":[0.58062464,0.00007652217,0.41774392,0.0001100999,0.00045579858,0.000047456695,0.0000018853048,0.00025212308,0.00068755244],"genre_scores_gemma":[0.89141244,0.0000149683565,0.10845321,0.000027107448,0.00006502125,5.614225e-7,9.3927633e-7,0.000006742442,0.000018995042],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902743,0.000013577098,0.00020366143,0.0002877831,0.0001759147,0.000291658],"domain_scores_gemma":[0.9974794,0.00006385468,0.00042284376,0.0019325158,0.000064861546,0.00003654323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027283354,0.00011554905,0.00018624881,0.00007148271,0.00043606095,0.00012814587,0.0028695518,0.000026186162,0.0000015993013],"category_scores_gemma":[0.00038185483,0.00011341346,0.000038230693,0.00007829184,0.00017302224,0.0008861119,0.0021399623,0.00015956131,0.000020305357],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008442244,0.00006666113,0.029232569,0.00014319803,0.000027862734,0.00013333428,0.0005016832,0.0035583605,0.0057731634,0.018067596,0.0022057786,0.94028133],"study_design_scores_gemma":[0.00055484404,0.00018149229,0.064613596,0.0002952256,0.0000058997134,0.00011026437,0.000040560408,0.82680464,0.10229706,0.002414085,0.002221832,0.00046049614],"about_ca_topic_score_codex":0.000009520991,"about_ca_topic_score_gemma":7.9790397e-7,"teacher_disagreement_score":0.9398208,"about_ca_system_score_codex":0.00003693518,"about_ca_system_score_gemma":0.000030280096,"threshold_uncertainty_score":0.5332389},"labels":[],"label_agreement":null},{"id":"W2733974844","doi":"10.1109/fccm.2017.42","title":"A Case for Common-Case: On FPGA Acceleration of Erasure Coding","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Erasure code; Computer science; Erasure; Decoding methods; Coding (social sciences); Reliability (semiconductor); Field-programmable gate array; Replication (statistics); Throughput; Reliability engineering; Embedded system; Power (physics); Operating system; Algorithm; Engineering","score_opus":0.1021398524045299,"score_gpt":0.34502577627432074,"score_spread":0.24288592386979085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2733974844","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":[0.05313905,0.000010667357,0.9442193,0.0007520921,0.00014121878,0.0002417326,0.000024494186,0.00024571165,0.0012257589],"genre_scores_gemma":[0.82146525,0.0000025949334,0.1783778,0.000045709894,0.000013824997,0.000020557303,0.0000019106374,0.0000039776837,0.00006839615],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994031,0.000008776461,0.00014237652,0.0002241852,0.00008872627,0.000132817],"domain_scores_gemma":[0.9982475,0.00013919438,0.00017057979,0.0013526407,0.00006850504,0.000021550231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000154356,0.00008281837,0.00012762634,0.000059114143,0.0004990185,0.00016225319,0.0007975008,0.000057251575,0.0000041828907],"category_scores_gemma":[0.00027926028,0.00007019411,0.000030328114,0.000046065485,0.00006506028,0.0008972346,0.00036239513,0.000074685966,0.000004521951],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017188071,0.000072871124,0.00018237598,0.000043774464,0.000016584338,0.004330331,0.00018627197,0.00016027743,0.0021457574,0.56487095,0.0033208684,0.42465273],"study_design_scores_gemma":[0.0030616685,0.0014454464,0.0005832404,0.0001405191,0.000031225318,0.021247562,0.00060740346,0.25410065,0.6367053,0.0687767,0.01222283,0.0010775008],"about_ca_topic_score_codex":0.0000515606,"about_ca_topic_score_gemma":0.00022202452,"teacher_disagreement_score":0.76832616,"about_ca_system_score_codex":0.00002444676,"about_ca_system_score_gemma":0.000011445167,"threshold_uncertainty_score":0.38380975},"labels":[],"label_agreement":null},{"id":"W2735440174","doi":"10.1109/icdcs.2017.191","title":"On Data Parallelism of Erasure Coding in Distributed Storage Systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Erasure; Erasure code; Parallel computing; Parallelism (grammar); Distributed data store; Coding (social sciences); Computer data storage; Decoding methods; Distributed computing; Operating system; Algorithm; Programming language; Mathematics","score_opus":0.07172803663815756,"score_gpt":0.31339455550148476,"score_spread":0.24166651886332718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735440174","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":[0.013475126,0.0000924654,0.9841733,0.00049973786,0.0003073302,0.00015984823,0.00021681143,0.00026238814,0.0008129955],"genre_scores_gemma":[0.977457,0.000019679757,0.022374582,0.000014921562,0.000009814757,0.000005812738,0.000050594346,0.000004458283,0.00006313679],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998919,0.000025123714,0.00021683615,0.00042300744,0.00021738773,0.00019864825],"domain_scores_gemma":[0.99453175,0.00010816976,0.0002184649,0.0050806794,0.00003406449,0.000026849033],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00032789528,0.000106261774,0.00020905171,0.00008276455,0.00011463636,0.00016163196,0.005696387,0.0000715703,0.000002552965],"category_scores_gemma":[0.0007483866,0.00008876409,0.000012976786,0.00010792416,0.00009352736,0.0013342442,0.0023946625,0.00015655976,0.00001281597],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010851444,0.00009041801,0.0016020436,0.000049798484,0.000014917162,0.0001513884,0.000062162515,0.0035675366,0.0007905019,0.975884,0.009338906,0.00843743],"study_design_scores_gemma":[0.0018866253,0.00022193202,0.026812587,0.0004862376,0.000008377033,0.000027071797,0.00025841923,0.9314447,0.0029252723,0.024253936,0.010834978,0.00083984],"about_ca_topic_score_codex":0.00017359214,"about_ca_topic_score_gemma":0.000054865315,"teacher_disagreement_score":0.96398187,"about_ca_system_score_codex":0.00004494266,"about_ca_system_score_gemma":0.000024815352,"threshold_uncertainty_score":0.99968326},"labels":[],"label_agreement":null},{"id":"W2735827543","doi":"10.1145/3092950","title":"Exploiting Stable Data Dependency in Stream Processing Acceleration on FPGAs","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Computer science; Field-programmable gate array; Scalability; Parallel computing; Acceleration; Dependency (UML); Block (permutation group theory); Stream processing; Algorithm; Computer architecture; Embedded system; Artificial intelligence","score_opus":0.10256638575069063,"score_gpt":0.34055404989018234,"score_spread":0.2379876641394917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735827543","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":[0.03427942,0.0000965744,0.9623821,0.00032670522,0.0008270655,0.00043733756,0.000029013057,0.000979394,0.0006423951],"genre_scores_gemma":[0.9151035,0.000015630301,0.084632255,0.000035520552,0.000078836856,0.000030359486,0.00001951675,0.000027616796,0.000056742494],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99711806,0.00010610383,0.0005787595,0.0011393644,0.0005096842,0.0005480487],"domain_scores_gemma":[0.99282795,0.0002762202,0.00051264185,0.006214303,0.000099082376,0.00006978813],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007363939,0.0003055517,0.00035265356,0.00035594983,0.0014315279,0.0014194454,0.0065212483,0.00015724172,0.0000024276385],"category_scores_gemma":[0.00041287768,0.00031091453,0.000039575836,0.00035072546,0.000072069735,0.0034773336,0.00033798214,0.0006047561,0.000038386963],"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":[0.000019747189,0.00028685515,0.00020346176,0.00012443255,0.000027624345,0.0000778414,0.0010998488,0.18767622,0.00070049346,0.003115749,0.000073183364,0.80659455],"study_design_scores_gemma":[0.0008172011,0.00015580948,0.0003118111,0.0009556715,0.000011252109,0.000049914564,0.0015097832,0.9894462,0.00402029,0.0019537301,0.00023847293,0.00052986585],"about_ca_topic_score_codex":0.00026228718,"about_ca_topic_score_gemma":0.000108472974,"teacher_disagreement_score":0.8808241,"about_ca_system_score_codex":0.00022945798,"about_ca_system_score_gemma":0.00011627189,"threshold_uncertainty_score":0.9999343},"labels":[],"label_agreement":null},{"id":"W2740127658","doi":"","title":"Proactive error prediction to improve storage system reliability","year":2017,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Reliability engineering; Computer science; Reliability (semiconductor); Engineering","score_opus":0.030187405010132444,"score_gpt":0.29538371699287713,"score_spread":0.2651963119827447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2740127658","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":[0.029816857,0.000009971694,0.95905966,0.0020343496,0.0006427237,0.0011417576,0.00046303828,0.003813485,0.0030181645],"genre_scores_gemma":[0.8787538,0.0000027892336,0.12066843,0.000053344684,0.000059454276,0.00023718644,0.0000054649013,0.0000159658,0.00020357542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9971317,0.0000720771,0.0004385145,0.001283904,0.00052269344,0.0005511345],"domain_scores_gemma":[0.99423534,0.000115690156,0.00032436653,0.004614791,0.0005183534,0.00019144792],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005659557,0.00031848944,0.00039655066,0.00013167242,0.0006267584,0.00044325303,0.004603156,0.00030755292,0.0000060555785],"category_scores_gemma":[0.0024033266,0.00028327093,0.00008618827,0.00023052255,0.0004169412,0.0025628612,0.003242543,0.0006189838,0.00015063304],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018436999,0.00043372935,0.0010548454,0.00018457261,0.000052758165,0.00021771042,0.0009785285,0.00016750989,0.03444136,0.7989787,0.0057411552,0.15756476],"study_design_scores_gemma":[0.0063406844,0.011254399,0.30685148,0.0017979078,0.00025880046,0.0006486984,0.005441751,0.15464918,0.22905603,0.16170874,0.1131291,0.008863233],"about_ca_topic_score_codex":0.000077332035,"about_ca_topic_score_gemma":0.000030725518,"teacher_disagreement_score":0.8489369,"about_ca_system_score_codex":0.0003918656,"about_ca_system_score_gemma":0.00016168448,"threshold_uncertainty_score":0.999962},"labels":[],"label_agreement":null},{"id":"W2740361432","doi":"","title":"Cache Modeling and Optimization using Miniature Simulations.","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Computer science; Cache; Parallel computing","score_opus":0.054731808000028234,"score_gpt":0.3096117099209188,"score_spread":0.25487990192089055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2740361432","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013583493,0.00006095192,0.98545754,0.00039756697,0.000056225395,0.000049456943,0.000001905639,0.00022361908,0.00016921236],"genre_scores_gemma":[0.47621426,0.000005015394,0.5237334,0.000022416432,0.000006092288,3.2720524e-7,9.022482e-7,0.0000018774855,0.00001573339],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958473,0.0000045461666,0.0000672392,0.00018860746,0.00006574637,0.00008911384],"domain_scores_gemma":[0.9991501,0.000015731377,0.000054923923,0.0007238642,0.000037705,0.000017655628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000041607964,0.000056093737,0.0000550496,0.000042930016,0.00037858114,0.00025788715,0.0005074224,0.000052733525,0.0000022124434],"category_scores_gemma":[0.00016283743,0.0000497052,0.000007022158,0.00004185786,0.00003594256,0.0015123358,0.00050671695,0.000058189842,7.30241e-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":[2.914251e-7,0.0000022154513,0.00009799089,0.0000012337608,0.0000013073115,0.0000012725023,0.000027454176,0.9870084,0.00013171257,0.008136827,0.000006690741,0.0045846244],"study_design_scores_gemma":[0.00007029941,0.0000035749683,0.000019782308,0.000004549903,0.0000016659965,0.000003702226,0.000012059523,0.99553007,0.0001851882,0.0040717428,0.00003096716,0.000066374014],"about_ca_topic_score_codex":0.00001907426,"about_ca_topic_score_gemma":0.0000062107943,"teacher_disagreement_score":0.46263078,"about_ca_system_score_codex":0.0000151267295,"about_ca_system_score_gemma":0.000011283925,"threshold_uncertainty_score":0.2911778},"labels":[],"label_agreement":null},{"id":"W2749587897","doi":"10.1109/itw.2017.8278018","title":"Product matrix minimum storage regenerating codes with flexible number of helpers","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Distributed data store; Computer science; Coding (social sciences); Computer data storage; Distributed computing; Code (set theory); Computer network; Mathematics; Computer hardware; Set (abstract data type)","score_opus":0.031032613942401588,"score_gpt":0.31788930520672276,"score_spread":0.2868566912643212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749587897","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036728334,0.0011029347,0.9504797,0.0010008237,0.0006547229,0.0006877261,0.00008797419,0.0018319308,0.0074258638],"genre_scores_gemma":[0.30777305,0.00007262493,0.68903035,0.00001994463,0.00007388571,0.000059527432,0.000026269674,0.000028207585,0.0029161344],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99733025,0.000048856138,0.0004138464,0.0012775053,0.00051004655,0.00041947464],"domain_scores_gemma":[0.99349374,0.00006532869,0.00082478864,0.005279104,0.0002736962,0.00006333731],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003727931,0.00043583338,0.0006355493,0.00015791379,0.00021378287,0.0003224051,0.0043199225,0.00022941682,0.000021820671],"category_scores_gemma":[0.00029452622,0.00034209373,0.00008707132,0.00018218085,0.00038584677,0.0007525073,0.005379063,0.00061899977,0.00003222735],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014711417,0.00060538476,0.00909003,0.0030355179,0.00078222255,0.00046892327,0.0028248467,0.084163964,0.016661234,0.7089199,0.026706485,0.14659439],"study_design_scores_gemma":[0.0018359139,0.0005066851,0.0008065583,0.0026949542,0.00016235036,0.000513202,0.0009461753,0.069330916,0.8419347,0.066520736,0.009824106,0.004923749],"about_ca_topic_score_codex":0.00016921017,"about_ca_topic_score_gemma":0.00003564928,"teacher_disagreement_score":0.8252734,"about_ca_system_score_codex":0.00009923423,"about_ca_system_score_gemma":0.00033394265,"threshold_uncertainty_score":0.9999031},"labels":[],"label_agreement":null},{"id":"W2757999899","doi":"10.1016/j.jss.2017.09.023","title":"R-SHT: A state history tree with R-Tree properties for analysis and visualization of highly parallel system traces","year":2017,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; TRACE (psycholinguistics); Visualization; Data structure; Benchmark (surveying); Debugging; Tree (set theory); Tree structure; Data mining; Parallel computing; Theoretical computer science; Programming language","score_opus":0.03187600293634714,"score_gpt":0.2520617234829176,"score_spread":0.22018572054657048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757999899","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":[0.12351601,0.006820154,0.8692567,0.00004784822,0.0001178187,0.000171154,0.000011780738,0.0000513022,0.000007233377],"genre_scores_gemma":[0.9523878,0.00015718165,0.04729205,0.000003094905,0.000022855618,0.000010887525,7.9587846e-7,0.000007767924,0.000117545016],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989792,0.000031987714,0.0004261671,0.00017642726,0.00026449378,0.000121739766],"domain_scores_gemma":[0.9977679,0.000054850087,0.0013344031,0.00042079404,0.00036963593,0.000052376003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037614853,0.0001213486,0.00049127196,0.00026244513,0.00016290844,0.00015117278,0.00048427592,0.00005652751,9.035691e-8],"category_scores_gemma":[0.00013089045,0.00007694373,0.000055710952,0.000088157074,0.00014733341,0.0011168831,0.00009429343,0.00006487704,6.6147095e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002200843,0.00062029413,0.38366425,0.021179771,0.008777388,0.00075060554,0.030147515,0.018385204,0.008464733,0.0745977,0.0037092313,0.44750246],"study_design_scores_gemma":[0.028015802,0.020542003,0.36435923,0.021157153,0.006129001,0.004254851,0.027927697,0.45258167,0.009682307,0.0042869137,0.055377413,0.005685963],"about_ca_topic_score_codex":0.00009495468,"about_ca_topic_score_gemma":0.000106932384,"teacher_disagreement_score":0.8288718,"about_ca_system_score_codex":0.00008983047,"about_ca_system_score_gemma":0.000066531175,"threshold_uncertainty_score":0.31376743},"labels":[],"label_agreement":null},{"id":"W2760103885","doi":"10.1145/3127479.3131623","title":"Latency reduction and load balancing in coded storage systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Latency (audio); Erasure code; Distributed data store; Load balancing (electrical power); Computer network; Computer data storage; Distributed computing; Erasure; Real-time computing; Operating system; Decoding methods; Telecommunications","score_opus":0.019646131703268992,"score_gpt":0.26125890173708044,"score_spread":0.24161277003381146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760103885","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":[0.23477541,0.00048387228,0.7589421,0.0007304048,0.00078163366,0.00020495565,0.0000018869791,0.0006363926,0.0034432926],"genre_scores_gemma":[0.96756345,0.00005065834,0.031972755,0.0000072830826,0.000016999016,0.000009226944,4.4081867e-7,0.000003519959,0.00037564713],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992789,0.000013555512,0.00012414235,0.0002953195,0.00012539378,0.00016270357],"domain_scores_gemma":[0.9988211,0.000014835062,0.00009998991,0.0010070337,0.000032116324,0.000024943625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021809693,0.00007757771,0.00011583445,0.00006612446,0.00016551689,0.00025341232,0.0007405337,0.00005640813,0.0000011087025],"category_scores_gemma":[0.00015823125,0.000068205576,0.000007821443,0.00006795879,0.00007449308,0.0014164131,0.0005200111,0.000106077045,0.0000121020275],"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":[0.000025220774,0.00013635303,0.018519415,0.0002030368,0.00002940224,0.00053378224,0.0025272113,0.0031003666,0.057509974,0.692536,0.0042335237,0.2206457],"study_design_scores_gemma":[0.003281504,0.00034005355,0.10506883,0.00053364976,0.000012004362,0.0007485111,0.0023715808,0.7951722,0.01930962,0.06277707,0.008569222,0.0018157541],"about_ca_topic_score_codex":0.00036696225,"about_ca_topic_score_gemma":0.000043006254,"teacher_disagreement_score":0.7920718,"about_ca_system_score_codex":0.00009390194,"about_ca_system_score_gemma":0.000024929892,"threshold_uncertainty_score":0.27813426},"labels":[],"label_agreement":null},{"id":"W2767352027","doi":"10.1145/3126908.3126918","title":"Leveraging near data processing for high-performance checkpoint/restart","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science; Overhead (engineering); Interrupt; Node (physics); Parallel computing; Point (geometry); Distributed computing; Computer network; Operating system; Embedded system; Engineering","score_opus":0.07987576569479052,"score_gpt":0.31246934311799834,"score_spread":0.23259357742320783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767352027","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":[0.03628122,0.00006080535,0.9595358,0.0021951017,0.00025391366,0.00019689347,0.00001352623,0.00084922975,0.000613558],"genre_scores_gemma":[0.5352539,0.000009998644,0.46437666,0.00008609564,0.000030663494,0.000013390111,0.000014202727,0.000007698942,0.00020744123],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865,0.0000045767647,0.00018028998,0.0006375519,0.00017093364,0.00035663403],"domain_scores_gemma":[0.99535805,0.00003569035,0.00019033354,0.0043154773,0.000069400354,0.00003107834],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00031648262,0.00014120189,0.0001501827,0.000042798052,0.0011667064,0.0009836548,0.007046932,0.000053136304,0.0000039359684],"category_scores_gemma":[0.000370086,0.0001219609,0.000013472966,0.00007606158,0.00018903581,0.0062029585,0.0037908081,0.0001252145,0.000032158434],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046384353,0.000023688213,0.0005546546,0.000071314906,0.000007432494,0.000007925166,0.00010301617,0.00010766246,0.0007097345,0.018825084,0.002690717,0.97689414],"study_design_scores_gemma":[0.0005945725,0.00007591809,0.0038767494,0.00007768819,0.000006636587,0.000016124694,0.000042946256,0.923177,0.030124916,0.014618506,0.026950266,0.0004386434],"about_ca_topic_score_codex":0.00003032583,"about_ca_topic_score_gemma":0.000009465334,"teacher_disagreement_score":0.9764555,"about_ca_system_score_codex":0.000032466953,"about_ca_system_score_gemma":0.00009018305,"threshold_uncertainty_score":0.9983254},"labels":[],"label_agreement":null},{"id":"W2767619012","doi":"","title":"Bandwidth Adaptive & Error Resilient MBR Exact Repair Regenerating Codes","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Distributed data store; Computer science; Upper and lower bounds; Robustness (evolution); Distributed computing; Flexibility (engineering); Bandwidth (computing); Computer network; Mathematics","score_opus":0.1026855839811293,"score_gpt":0.22664498258174504,"score_spread":0.12395939860061574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767619012","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":[0.08697534,0.00059548614,0.9037677,0.00017839967,0.0008895061,0.00053426076,0.00011513705,0.0029623595,0.0039818124],"genre_scores_gemma":[0.92481977,0.00028798357,0.07259845,0.000050306466,0.00008277869,0.000003673789,0.000029781753,0.000029704019,0.0020975722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99658895,0.00016672225,0.00029545973,0.0021734696,0.00018192324,0.00059345714],"domain_scores_gemma":[0.9933674,0.0001642529,0.0007476191,0.005319471,0.0002403127,0.00016097869],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0004015971,0.00053444854,0.00056830334,0.00034650406,0.0006792918,0.00023369648,0.0051873177,0.00047932964,0.000011504168],"category_scores_gemma":[0.00039462018,0.0005922461,0.0003045499,0.0003368336,0.00044381229,0.0011624955,0.0087050265,0.0010542031,0.00007803983],"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":[0.000077424396,0.00013124016,0.0016165373,0.000090741916,0.00021964466,0.0020457224,0.00030290583,0.3004387,0.00013862304,0.68523496,0.004516869,0.0051865955],"study_design_scores_gemma":[0.0007872476,0.0002626478,0.0015516891,0.000542169,0.00012286713,0.00002573925,0.00032061327,0.89841944,0.0029303068,0.08977189,0.0035585419,0.0017068322],"about_ca_topic_score_codex":0.00021399204,"about_ca_topic_score_gemma":0.00018258061,"teacher_disagreement_score":0.8378444,"about_ca_system_score_codex":0.00047752468,"about_ca_system_score_gemma":0.00029691035,"threshold_uncertainty_score":0.9996529},"labels":[],"label_agreement":null},{"id":"W2770600168","doi":"10.1145/3149482","title":"CosaFS","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Science and Technology Planning Project of Guangdong Province; Huazhong University of Science and Technology; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; File system; Cache; Operating system; Throughput; Rendering (computer graphics); Computer data storage; Metadata; Computer hardware; Computer graphics (images); Wireless","score_opus":0.03547877908856033,"score_gpt":0.2948514264524252,"score_spread":0.25937264736386484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770600168","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":[0.002539023,0.00003439282,0.9905389,0.003351895,0.00066640973,0.0001113133,0.000025838686,0.0009145065,0.001817744],"genre_scores_gemma":[0.81312,0.00003791144,0.18581961,0.0001771271,0.00001930813,0.000030277577,0.0000011313579,0.000011013964,0.0007836165],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99898773,0.000016302622,0.00012763016,0.0004052106,0.00021247391,0.00025062347],"domain_scores_gemma":[0.9945214,0.0000832117,0.00010567851,0.0051905653,0.000037026286,0.00006213854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010428143,0.00014440544,0.00013753027,0.00012169254,0.0009632744,0.0002697138,0.0042602383,0.000085254025,0.00004002021],"category_scores_gemma":[0.00014855393,0.00013904161,0.00006581836,0.00010941851,0.00016404413,0.001459628,0.000093417126,0.00028452513,0.00034960473],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012394772,0.00015759731,0.000029656307,0.000008200891,0.000032760345,0.00015174734,0.00017167584,0.0007924995,0.0012647336,0.03279024,0.001233707,0.96335477],"study_design_scores_gemma":[0.004249518,0.0012894752,0.01461681,0.00018981345,0.00008285444,0.0003138331,0.00036862324,0.019198941,0.14380212,0.31829736,0.49443632,0.0031543428],"about_ca_topic_score_codex":0.000022503096,"about_ca_topic_score_gemma":0.000022324197,"teacher_disagreement_score":0.9602004,"about_ca_system_score_codex":0.00006832524,"about_ca_system_score_gemma":0.000028651308,"threshold_uncertainty_score":0.7916654},"labels":[],"label_agreement":null},{"id":"W2774310322","doi":"10.1109/iceca.2017.8203701","title":"Construction of estimated level based balanced binary search tree","year":2017,"lang":"en","type":"article","venue":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Tree traversal; Binary search tree; Binary tree; Computer science; Data structure; Tree (set theory); Binary number; Block (permutation group theory); Linked list; Memory management; Self-balancing binary search tree; Node (physics); Optimal binary search tree; Key (lock); Auxiliary memory; Tree structure; Algorithm; Interval tree; Mathematics; Arithmetic; Semiconductor memory; Computer hardware; Operating system; Engineering; Combinatorics","score_opus":0.09255252992105223,"score_gpt":0.3422129583233829,"score_spread":0.24966042840233066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2774310322","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":[0.35977462,0.0020493085,0.58322024,0.045083445,0.00027928076,0.00055066566,0.00012327709,0.0008391808,0.008079973],"genre_scores_gemma":[0.81391335,0.0015626964,0.18435107,0.00001749124,0.000003118845,0.000019299761,0.000031300544,0.000007343423,0.00009433369],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987114,0.000046610377,0.00034893275,0.00036590305,0.00026755838,0.00025961376],"domain_scores_gemma":[0.99576175,0.00011327855,0.0007670572,0.002557158,0.00076566095,0.000035086636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031605593,0.00017913281,0.00030680405,0.0004949503,0.0003317278,0.00011220073,0.0046935133,0.00024060994,0.0000165872],"category_scores_gemma":[0.00064370927,0.00018863556,0.000043551423,0.00021782052,0.0017780277,0.000838738,0.0014187344,0.00046168032,0.00000487997],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003144955,0.00008125708,0.007703876,0.000017870541,0.000047926067,0.0000015494868,0.00005014254,0.00004261202,0.05594147,0.8945577,0.00009000622,0.04143413],"study_design_scores_gemma":[0.0030181734,0.00074162555,0.036592398,0.0005797389,0.000035210374,0.00007581016,0.0006617913,0.30439952,0.49193043,0.16019385,0.0010512286,0.00072022335],"about_ca_topic_score_codex":0.000062902494,"about_ca_topic_score_gemma":0.00017334544,"teacher_disagreement_score":0.73436385,"about_ca_system_score_codex":0.00008419976,"about_ca_system_score_gemma":0.00027684032,"threshold_uncertainty_score":0.8721793},"labels":[],"label_agreement":null},{"id":"W2778066394","doi":"10.1016/j.jpdc.2017.12.009","title":"A light-weight log-based hybrid storage system","year":2017,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; File system; Computer data storage; Cloud storage; Flash file system; Operating system; Object storage; Cloud computing; Block (permutation group theory); Flash memory; File system fragmentation; Device file; Embedded system; Database; Computer file; Computer memory; Semiconductor memory","score_opus":0.01692915884015002,"score_gpt":0.2556039834049273,"score_spread":0.2386748245647773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2778066394","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":[0.049980115,0.0006248227,0.9469855,0.0014099074,0.00058064697,0.00007225862,0.000019047426,0.00017960525,0.00014810705],"genre_scores_gemma":[0.9066963,0.000007855735,0.09310632,0.000041584954,0.00013165912,7.1995976e-7,0.000003818291,0.0000074275135,0.0000043020545],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984738,0.000053592074,0.0005263257,0.0002802001,0.0003251449,0.00034093022],"domain_scores_gemma":[0.9973313,0.00011720163,0.0013132598,0.0008686769,0.00021798897,0.00015152333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048698022,0.00020307655,0.0004166545,0.00013239669,0.0006967376,0.0005232425,0.001972311,0.00007009174,8.1522114e-7],"category_scores_gemma":[0.00028916268,0.00016284465,0.00010828472,0.000101679034,0.00009028728,0.0008477165,0.00070777937,0.00035319652,0.0000046993855],"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":[0.0005967992,0.0014087174,0.03874642,0.001321769,0.00095476996,0.028095877,0.0008740882,0.15632856,0.007740182,0.46732634,0.04594114,0.25066534],"study_design_scores_gemma":[0.004204314,0.00070698094,0.016091753,0.0009020922,0.00007355982,0.0027892566,0.0002788355,0.9492268,0.0032378142,0.00924964,0.012357007,0.0008819475],"about_ca_topic_score_codex":0.0000044943604,"about_ca_topic_score_gemma":6.658975e-7,"teacher_disagreement_score":0.8567162,"about_ca_system_score_codex":0.00011087571,"about_ca_system_score_gemma":0.00008985167,"threshold_uncertainty_score":0.6640612},"labels":[],"label_agreement":null},{"id":"W2778206737","doi":"10.1080/01576895.2017.1409125","title":"Records storage in the cloud: are we modelling the cost?","year":2018,"lang":"en","type":"article","venue":"Archives and Manuscripts","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Cloud computing; Activity-based costing; Process (computing); Computer science; Cloud storage; Data science; Business; Accounting","score_opus":0.0589952931023371,"score_gpt":0.26260479703369655,"score_spread":0.20360950393135946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2778206737","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":[0.024110705,0.00075496803,0.96151465,0.010835528,0.0003710609,0.0002501096,0.0000070596852,0.0001357641,0.002020149],"genre_scores_gemma":[0.9520986,0.0011829059,0.04519829,0.0010715101,0.00014054714,0.00004155467,0.0000016884179,0.000008093901,0.00025682285],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991087,0.00008115837,0.00012603388,0.00030245574,0.00012314858,0.00025854612],"domain_scores_gemma":[0.9988978,0.00019023794,0.00006620133,0.0008129038,0.000009108055,0.000023783281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018908971,0.00011401398,0.00010110671,0.000071260256,0.0002604729,0.00012591992,0.0013639046,0.000025899368,0.0000013123392],"category_scores_gemma":[0.000027029191,0.00006315989,0.000023588782,0.00019764203,0.0003554055,0.0003233774,0.00058506057,0.00022363885,0.000007751375],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033091095,0.000074516,0.0004615626,0.000026623691,0.000016187265,0.00011196374,0.019625692,0.001621517,0.00021269103,0.49561083,0.0111772,0.47102812],"study_design_scores_gemma":[0.00026402823,0.00013910943,0.0024474878,0.00007008888,0.000004777219,0.000048467347,0.0023298177,0.27346638,0.00020111277,0.42928094,0.29151756,0.00023025779],"about_ca_topic_score_codex":0.0000580255,"about_ca_topic_score_gemma":0.000111834954,"teacher_disagreement_score":0.9279879,"about_ca_system_score_codex":0.0000072125044,"about_ca_system_score_gemma":0.000010039927,"threshold_uncertainty_score":0.25755855},"labels":[],"label_agreement":null},{"id":"W2783190786","doi":"10.1109/tetc.2018.2794260","title":"<i>Mist</i>: Efficient Dissemination of Erasure-Coded Data in Data Centers","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Emerging Topics in Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Erasure code; Erasure; Server; Replication (statistics); Dissemination; Overhead (engineering); Computer network; Distributed computing; Decoding methods; Operating system; Algorithm; Telecommunications","score_opus":0.04416996101109297,"score_gpt":0.33364871506652244,"score_spread":0.28947875405542944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783190786","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":[0.042485252,0.00003615289,0.9554744,0.0005587791,0.0009617371,0.00014707388,0.000054220076,0.00018498341,0.00009740324],"genre_scores_gemma":[0.8726691,0.000015305703,0.12720616,0.00003107213,0.000036027985,0.0000016972781,0.000018959938,0.000008939778,0.0000127296735],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981428,0.00006331726,0.00046835165,0.0007256952,0.0003025942,0.0002972525],"domain_scores_gemma":[0.9966974,0.0002545521,0.000147546,0.002817917,0.000055597786,0.00002694275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006967961,0.00014860045,0.00020097611,0.00038376107,0.00011447232,0.000038722395,0.0032820883,0.00007129728,0.0000034920351],"category_scores_gemma":[0.000117380194,0.000163722,0.000019313162,0.0009594355,0.00012658552,0.00047826508,0.00017185386,0.0003277961,0.000003378665],"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":[0.000029207682,0.00070726546,0.0007539371,0.000099092285,0.000029950183,0.000032581433,0.0026351686,0.18690747,0.00356158,0.0024692644,0.0003604183,0.80241406],"study_design_scores_gemma":[0.00024268622,0.0000338661,0.00050607015,0.0002687618,0.000004102983,0.000004225134,0.00010552677,0.9889055,0.009209325,0.00019920769,0.0003570543,0.00016366265],"about_ca_topic_score_codex":0.00008973044,"about_ca_topic_score_gemma":0.00033143212,"teacher_disagreement_score":0.83018386,"about_ca_system_score_codex":0.000094680174,"about_ca_system_score_gemma":0.000036180234,"threshold_uncertainty_score":0.6676389},"labels":[],"label_agreement":null},{"id":"W2785926820","doi":"10.1109/vtcfall.2017.8288123","title":"Minimizing the Update Complexity of Facebook HDFS-RAID Locally Repairable Code","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; RAID; Erasure code; Overhead (engineering); Block (permutation group theory); Direct-sequence spread spectrum; Distributed data store; Reliability (semiconductor); Code (set theory); Locality; Distributed computing; Operating system; Computer network; Decoding methods; Spread spectrum; Power (physics); Algorithm; Programming language","score_opus":0.07662710328223978,"score_gpt":0.3006446878406892,"score_spread":0.22401758455844945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785926820","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015802436,0.00004409921,0.9683142,0.0059865215,0.00016308535,0.00030079807,0.000020664267,0.00070003374,0.022890372],"genre_scores_gemma":[0.47517037,0.000028980543,0.52344805,0.00041020586,0.000013156108,0.00002074013,0.000002295259,0.00000849431,0.0008976986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99880666,0.000033386386,0.00025500072,0.00037847392,0.0002400874,0.00028642133],"domain_scores_gemma":[0.99578685,0.00008062552,0.00031509437,0.0036910498,0.000090514266,0.00003587696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038789315,0.00013655786,0.00020894122,0.000041782372,0.0005738379,0.000197889,0.0048012547,0.000058640704,0.000044649976],"category_scores_gemma":[0.0003311555,0.00009104656,0.00005771714,0.000079086785,0.0011161328,0.0010243828,0.0025684116,0.00016997688,0.000119213524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001081762,0.000038611295,0.00037892026,0.000017240483,0.000025890036,0.000020275593,0.0001571109,0.00015056923,0.0019621179,0.9385407,0.011894111,0.046803616],"study_design_scores_gemma":[0.001164669,0.00024217904,0.00573216,0.0001046986,0.000021203297,0.000061786006,0.0004188314,0.1385963,0.1729395,0.4433464,0.23653243,0.0008398453],"about_ca_topic_score_codex":0.00009617971,"about_ca_topic_score_gemma":0.00015381104,"teacher_disagreement_score":0.49519432,"about_ca_system_score_codex":0.0000310564,"about_ca_system_score_gemma":0.00005661186,"threshold_uncertainty_score":0.8922005},"labels":[],"label_agreement":null},{"id":"W2790464890","doi":"10.1002/spe.2566","title":"Recovering disk storage metrics from low‐level trace events","year":2018,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Tracing; TRACE (psycholinguistics); Computer data storage; Block (permutation group theory); Stateful firewall; Page fault; Key (lock); Object storage; Distributed computing; Virtual memory; Operating system; Memory management","score_opus":0.03428704090859698,"score_gpt":0.30703009444557244,"score_spread":0.2727430535369755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790464890","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":[0.15733333,0.00092857506,0.83993393,0.0003890356,0.00057161547,0.000110858135,0.00003230674,0.0006085219,0.000091814705],"genre_scores_gemma":[0.5357002,0.00024864287,0.46354023,0.00035253822,0.000067274115,0.000026268557,0.0000032935768,0.000011318798,0.00005025269],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99817884,0.000060734725,0.00023767003,0.0007507029,0.00039182673,0.00038020665],"domain_scores_gemma":[0.99756086,0.000881197,0.00022682257,0.0010607514,0.0001557568,0.000114603914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023456189,0.00021011937,0.00018882354,0.0001249611,0.00034357046,0.00019940897,0.0012168337,0.000111116606,0.000020702159],"category_scores_gemma":[0.0062636193,0.0002026832,0.000030496216,0.00081724266,0.00022039808,0.0062264362,0.0010558153,0.00026260794,0.00009508338],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094773335,0.00024757808,0.0032558043,0.000025793837,0.00004247115,0.00021760634,0.024950918,0.000025083593,0.0024808873,0.0032176725,0.001029821,0.9644116],"study_design_scores_gemma":[0.0037859264,0.0025464608,0.027695099,0.0005581444,0.0001645969,0.00076261087,0.040574845,0.020628458,0.1153119,0.09140834,0.6905555,0.0060080765],"about_ca_topic_score_codex":0.00019015894,"about_ca_topic_score_gemma":0.000015536689,"teacher_disagreement_score":0.9584035,"about_ca_system_score_codex":0.00008212168,"about_ca_system_score_gemma":0.000050464834,"threshold_uncertainty_score":0.8265181},"labels":[],"label_agreement":null},{"id":"W2793353921","doi":"10.1145/3158644","title":"Survey and Analysis of Kernel and Userspace Tracers on Linux","year":2018,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Linux kernel; User space; Overhead (engineering); Tracing; Operating system; Kernel (algebra); Stack (abstract data type); System call; Legacy system; Software; Embedded system; Software engineering","score_opus":0.09269364725147568,"score_gpt":0.35807121965084,"score_spread":0.2653775723993643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793353921","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008089007,0.8075264,0.19062331,0.000021387335,0.0002118361,0.00026292194,0.00020111569,0.00032053405,0.000023607001],"genre_scores_gemma":[0.0018741634,0.9540013,0.043828443,0.000017605178,0.000030775805,0.0000037571533,0.00016658941,0.000038674563,0.00003870678],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99557626,0.0017837158,0.0006647013,0.0012363524,0.00033233708,0.00040662749],"domain_scores_gemma":[0.99051845,0.005591735,0.00088561693,0.0027422425,0.00016593016,0.00009604438],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0053707976,0.0005209869,0.0022513778,0.0009992076,0.00013916254,0.0001359821,0.0025882064,0.0003503219,0.0000015139086],"category_scores_gemma":[0.0036351087,0.0004512497,0.00022480043,0.0030601057,0.00039756836,0.00020648776,0.003021073,0.000450643,0.000007978867],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.7461e-7,0.000022327084,0.001592372,0.0007208828,0.00067918,0.00000855406,0.000080659636,0.000027182765,8.164937e-8,0.00027840238,0.00019745056,0.996392],"study_design_scores_gemma":[0.002043993,0.002537026,0.36250156,0.023703743,0.009257202,0.0001567686,0.00017016642,0.10780442,0.000028677232,0.0022546875,0.47958255,0.009959207],"about_ca_topic_score_codex":0.00022034798,"about_ca_topic_score_gemma":0.00020526773,"teacher_disagreement_score":0.98643285,"about_ca_system_score_codex":0.00007478459,"about_ca_system_score_gemma":0.000099779245,"threshold_uncertainty_score":0.99979395},"labels":[],"label_agreement":null},{"id":"W2794411052","doi":"","title":"Spiffy: Enabling File-System Aware Storage Applications","year":2018,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; File system; Operating system; Storage management; Database; Embedded system","score_opus":0.015267887340029294,"score_gpt":0.24012387223767964,"score_spread":0.22485598489765035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794411052","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":[0.0008499035,0.0027339496,0.971773,0.0008264265,0.00023119441,0.0006416306,0.0018504558,0.019257298,0.0018361032],"genre_scores_gemma":[0.75647944,0.00031582496,0.23988095,0.00022946757,0.0002030886,0.0016226284,0.0003336241,0.000062002626,0.00087300065],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977293,0.000027547258,0.00035190058,0.0009843997,0.00029066126,0.00061616034],"domain_scores_gemma":[0.997014,0.00024469348,0.00023801606,0.0022721558,0.0001686465,0.00006248743],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015668367,0.00036323298,0.00037912553,0.0004875248,0.00067337404,0.00024219134,0.0023727375,0.00038963178,0.0002913298],"category_scores_gemma":[0.00036194015,0.00033140017,0.000064163185,0.0012403409,0.00076163106,0.00080325216,0.0021662053,0.00043917767,0.00030314433],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010553019,0.00007452217,0.0000719194,0.00017086147,0.000055023094,0.00018996005,0.00033940782,0.000024773963,0.0010602345,0.14325614,0.3545849,0.5001617],"study_design_scores_gemma":[0.00036291435,0.00038963987,0.0002802665,0.0001779913,0.000017125172,0.00017404824,0.0040970366,0.012360786,0.009323646,0.012151406,0.95969087,0.0009742708],"about_ca_topic_score_codex":0.000020112768,"about_ca_topic_score_gemma":0.000013220475,"teacher_disagreement_score":0.75562954,"about_ca_system_score_codex":0.00015597844,"about_ca_system_score_gemma":0.00006173851,"threshold_uncertainty_score":0.9999138},"labels":[],"label_agreement":null},{"id":"W2794450234","doi":"10.1515/jmc-2017-0058","title":"A survey and refinement of repairable threshold schemes","year":2018,"lang":"en","type":"article","venue":"Journal of Mathematical Cryptology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Metric (unit); Theoretical computer science; Scheme (mathematics); Algorithm; Mathematics","score_opus":0.04044575581766818,"score_gpt":0.305518014241802,"score_spread":0.26507225842413384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794450234","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13760144,0.00036045877,0.85919195,0.002274789,0.00011834979,0.00005636423,0.0000021978697,0.00004440391,0.00035005546],"genre_scores_gemma":[0.4909168,0.000026290754,0.50892043,0.0000986127,0.000022261067,9.1543757e-7,1.518179e-7,0.000003917524,0.000010642114],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988588,0.000056410932,0.00055584236,0.00014096606,0.00021251742,0.00017542759],"domain_scores_gemma":[0.998526,0.00025908125,0.00043171854,0.00044074323,0.00028843456,0.000054036092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010075601,0.00009209314,0.0003881682,0.00013805008,0.000035197707,0.000016268234,0.0006748619,0.00008253641,0.00001994601],"category_scores_gemma":[0.0013691193,0.00006571337,0.000041578776,0.00019971836,0.00025793066,0.0002672177,0.00041975337,0.00016376804,0.000009382419],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000533994,0.00022588299,0.0015589432,0.00009572806,0.00007307744,0.000057402158,0.0002762992,0.0000016357917,0.0029650654,0.9804362,0.0069294716,0.0073269135],"study_design_scores_gemma":[0.00085096154,0.0020652832,0.002438051,0.00013623352,0.000021436052,0.00095507485,0.00017106757,0.0043667243,0.018692348,0.96581644,0.0042753792,0.00021100199],"about_ca_topic_score_codex":0.0000010581165,"about_ca_topic_score_gemma":0.0000028786471,"teacher_disagreement_score":0.35331535,"about_ca_system_score_codex":0.0000172725,"about_ca_system_score_gemma":0.0000432598,"threshold_uncertainty_score":0.26797134},"labels":[],"label_agreement":null},{"id":"W2803003303","doi":"10.1109/tcomm.2018.2827053","title":"Improving the Update Complexity of Locally Repairable Codes","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Direct-sequence spread spectrum; Locality; Distributed data store; Code (set theory); Distributed computing; Spread spectrum; RAID; Parallel computing; Operating system; Computer network; Code division multiple access; Programming language","score_opus":0.06153721891667427,"score_gpt":0.29612880835058936,"score_spread":0.2345915894339151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803003303","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":[0.0004860866,0.00009859771,0.99312115,0.0043503963,0.00014980775,0.00019855396,0.000057239977,0.000585529,0.0009526288],"genre_scores_gemma":[0.6776385,0.00011339037,0.32197556,0.0001689227,0.0000054112847,0.000039713806,0.0000023798123,0.000006600215,0.000049562703],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898773,0.00012522361,0.0002925144,0.00023323103,0.00017263989,0.00018864362],"domain_scores_gemma":[0.9936872,0.0003034826,0.00016033764,0.005597496,0.00021961972,0.000031830183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003022397,0.00011593728,0.00014057898,0.00011248184,0.0008933329,0.000053161224,0.0042822757,0.000056980334,0.00001728123],"category_scores_gemma":[0.000031099495,0.000092896364,0.00006952617,0.0006824282,0.0018991228,0.00048834144,0.00007241282,0.00033991228,0.00007268675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032826392,0.0008376354,0.0000133355425,0.000026458229,0.00012899152,0.0000013730364,0.0012397435,0.0018866683,0.016495567,0.65889066,0.0014856274,0.31896114],"study_design_scores_gemma":[0.0006918976,0.0005819102,0.00022526958,0.00010141463,0.000070768845,0.00004383373,0.0005556009,0.5714516,0.29621452,0.10840129,0.021053229,0.0006086413],"about_ca_topic_score_codex":0.00019536848,"about_ca_topic_score_gemma":0.000743157,"teacher_disagreement_score":0.67715234,"about_ca_system_score_codex":0.00005379553,"about_ca_system_score_gemma":0.000073634204,"threshold_uncertainty_score":0.7957605},"labels":[],"label_agreement":null},{"id":"W2804180774","doi":"10.1615/tfec2018.hte.022887","title":"Experimental Study of a Latent Storage System using a Vertical-Finned Tube and Shell Heat Exchanger: Early Results","year":2018,"lang":"en","type":"article","venue":"Proceeding of 3rd Thermal and Fluids Engineering Conference (TFEC)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Shell and tube heat exchanger; Heat exchanger; Tube (container); Shell (structure); Latent heat; Materials science; Mechanics; Mechanical engineering; Thermodynamics; Engineering; Physics; Composite material","score_opus":0.03526208954765787,"score_gpt":0.2474417458274219,"score_spread":0.21217965627976404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804180774","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":[0.9287903,0.00029206203,0.07023228,0.000013289691,0.00011282401,0.0002765366,0.0000073557253,0.00023571668,0.000039662187],"genre_scores_gemma":[0.990088,0.000006827034,0.009828879,0.0000023387975,0.000038210263,0.000016781949,5.976355e-7,0.000014771368,0.0000035863304],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99869204,0.000012125484,0.0003519181,0.00042500973,0.00023246005,0.00028644133],"domain_scores_gemma":[0.99938214,0.000043829885,0.000055842185,0.00028667523,0.00014973026,0.00008179623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020610762,0.00022378152,0.00034320925,0.00017560471,0.00007890183,0.00007237034,0.00042013027,0.00007240014,0.0000014110732],"category_scores_gemma":[0.000055280616,0.00020027524,0.000022831495,0.0002500992,0.0001504551,0.00051710923,0.000590883,0.00012636723,7.246065e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067116,0.00015144705,0.0014591172,0.00020720501,0.000038780312,0.0000102562135,0.0075897495,0.00013222727,0.984828,0.0044323807,0.0000015465218,0.0010821824],"study_design_scores_gemma":[0.0017271319,0.0030217508,0.0070627327,0.00059063046,0.00003652234,0.000038571936,0.0022551026,0.46808386,0.51667595,0.000033379903,0.0000069826197,0.0004674034],"about_ca_topic_score_codex":0.00006400923,"about_ca_topic_score_gemma":5.467109e-7,"teacher_disagreement_score":0.46815205,"about_ca_system_score_codex":0.00004048732,"about_ca_system_score_gemma":0.000020432019,"threshold_uncertainty_score":0.81669873},"labels":[],"label_agreement":null},{"id":"W2806169442","doi":"","title":"UNIST SAIL System for TAC 2017 Cold Start Slot Filling.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Advanced Data Storage Technologies","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","score_opus":0.019889214540509813,"score_gpt":0.2735448833744794,"score_spread":0.2536556688339696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806169442","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":[0.0015755619,0.0005151364,0.994746,0.0003148003,0.000059351365,0.00043185544,0.00012693072,0.00026097646,0.0019693384],"genre_scores_gemma":[0.96070564,0.00007487092,0.038185116,0.000014328521,0.0000358562,0.00042514197,0.000013276082,0.000007159432,0.00053860154],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993552,0.00001739367,0.00016288967,0.0002503687,0.00007555865,0.00013857623],"domain_scores_gemma":[0.9977377,0.00023995429,0.00025484883,0.0016224016,0.00011321331,0.000031872067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039835213,0.000099959645,0.00016301365,0.000047170815,0.00083403155,0.00014590667,0.0013949188,0.000053320087,8.462945e-7],"category_scores_gemma":[0.000106426414,0.0000901205,0.000026132175,0.0000616865,0.00061104534,0.0005115607,0.00036003874,0.000056326415,0.000005913457],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011946679,0.0000123013915,0.000012053097,0.00006871553,0.000008643494,3.2005127e-7,0.00006753184,0.000006445223,0.0013179681,0.9840109,0.00028638466,0.014196832],"study_design_scores_gemma":[0.00027343674,0.00006689243,0.00007881289,0.000023534612,0.000019683075,0.0000066296266,0.0007655953,0.00039323187,0.08799844,0.795691,0.11448506,0.00019763791],"about_ca_topic_score_codex":0.000008760216,"about_ca_topic_score_gemma":0.0000036125614,"teacher_disagreement_score":0.9591301,"about_ca_system_score_codex":0.000016009957,"about_ca_system_score_gemma":0.00003217444,"threshold_uncertainty_score":0.64147806},"labels":[],"label_agreement":null},{"id":"W2806873315","doi":"","title":"CMUML System for KBP 2015 Cold Start Slot Filling.","year":2015,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.021649632561801836,"score_gpt":0.2699259499754247,"score_spread":0.24827631741362285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806873315","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":[0.0012988985,0.0012183245,0.99550754,0.00023937692,0.00005366969,0.00044090647,0.0000704339,0.0003886256,0.00078219996],"genre_scores_gemma":[0.93146604,0.00002507799,0.06758281,0.000024958259,0.000037767397,0.0005452904,0.0000169247,0.000008105168,0.00029302022],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999332,0.000027348347,0.0001795993,0.00022575168,0.000099698045,0.00013560664],"domain_scores_gemma":[0.99867916,0.00025957567,0.00011944928,0.0007001613,0.00018782496,0.0000538112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005611335,0.0000950195,0.00015591698,0.00006772764,0.00011657903,0.000038381844,0.00063555624,0.000051093193,5.910926e-7],"category_scores_gemma":[0.000088691035,0.00008427168,0.000020240834,0.00022773998,0.0002571191,0.00035402866,0.00020735206,0.000050513885,0.000008014809],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001699484,0.000014903524,0.0000056384865,0.000043852866,0.0000072360563,1.7398278e-7,0.00019248405,0.000038707098,0.00056269154,0.9918214,0.0006606859,0.006635202],"study_design_scores_gemma":[0.00026861922,0.000091936716,0.0000046502914,0.000010245453,0.000013146454,0.0000063144535,0.0020745154,0.0005844228,0.057684466,0.8530752,0.08604126,0.00014518785],"about_ca_topic_score_codex":0.000004433838,"about_ca_topic_score_gemma":0.0000013182805,"teacher_disagreement_score":0.93016714,"about_ca_system_score_codex":0.000024648863,"about_ca_system_score_gemma":0.000052862575,"threshold_uncertainty_score":0.34364995},"labels":[],"label_agreement":null},{"id":"W2808200030","doi":"10.1109/icdcs.2018.00019","title":"Parallelism-Aware Locally Repairable Code for Distributed Storage Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Server; Computer science; Erasure code; Overhead (engineering); Distributed data store; Bottleneck; File server; Distributed computing; Parallel computing; Distributed database; Operating system; Decoding methods; Embedded system; Algorithm","score_opus":0.02603272360650484,"score_gpt":0.27202607362378056,"score_spread":0.24599335001727574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808200030","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":[0.0004287138,0.00010938085,0.99367356,0.0007291774,0.0006095396,0.0005119874,0.00031025673,0.0031123997,0.00051501096],"genre_scores_gemma":[0.54448926,0.0000138695,0.45221153,0.00033060994,0.000175461,0.00023192703,0.00012027431,0.000027228582,0.002399817],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998377,0.0000265709,0.00029002072,0.0006127772,0.00022097307,0.0004726232],"domain_scores_gemma":[0.9978316,0.00011749579,0.00012349975,0.001551304,0.0002958094,0.000080313344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002687443,0.00018639631,0.00023715824,0.000077592296,0.00023656004,0.00017980032,0.0016968638,0.00012692316,0.000011248209],"category_scores_gemma":[0.00023247713,0.00015769618,0.000056943485,0.00040058483,0.00017977417,0.0008288292,0.0005762158,0.000103396174,0.00011209109],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043128955,0.00011565944,0.0001125483,0.00009965959,0.000056579793,0.000056332872,0.00012987135,0.0030067312,0.00065124163,0.6598487,0.3268225,0.009057044],"study_design_scores_gemma":[0.00056723476,0.00043235268,0.00005469919,0.00003884251,0.0000068164463,0.000031309413,0.0001505492,0.65043885,0.002509436,0.009366996,0.33599404,0.00040886653],"about_ca_topic_score_codex":0.00003265708,"about_ca_topic_score_gemma":0.00004473798,"teacher_disagreement_score":0.6504817,"about_ca_system_score_codex":0.0001178054,"about_ca_system_score_gemma":0.00006754977,"threshold_uncertainty_score":0.64306635},"labels":[],"label_agreement":null},{"id":"W2808383901","doi":"10.1109/icdcs.2018.00034","title":"EC-Store: Bridging the Gap between Storage and Latency in Distributed Erasure Coded Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Erasure code; Computer science; Distributed data store; Erasure; Computer data storage; Fault tolerance; Cloud storage; Replication (statistics); Scalability; Latency (audio); Decoding methods; Distributed computing; Data access; Cloud computing; Operating system; Database","score_opus":0.028624449935271173,"score_gpt":0.2603135139406116,"score_spread":0.23168906400534042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808383901","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":[0.10712401,0.0003580508,0.8896655,0.001356348,0.00022662026,0.00026223075,0.00005843241,0.0006854999,0.00026330186],"genre_scores_gemma":[0.9912304,0.000016459495,0.008460392,0.000056181732,0.000091711925,0.000016229384,0.000014343497,0.000008592709,0.00010563216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986886,0.00007104699,0.00024500265,0.00042996468,0.000219202,0.0003462035],"domain_scores_gemma":[0.99868894,0.00015580984,0.00009608652,0.0009418759,0.00006942806,0.00004784394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042516386,0.00015981228,0.00021423603,0.00009640967,0.00018754104,0.00018431312,0.001171855,0.000093369395,0.0000034628956],"category_scores_gemma":[0.00016412645,0.00010786064,0.000018144357,0.0006260854,0.00025855078,0.00066307303,0.0007473606,0.00023250387,0.000028023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039825285,0.00019736533,0.19698073,0.00023569733,0.00019697336,0.0004679197,0.004590859,0.0013694487,0.007225767,0.5647125,0.058790423,0.16519247],"study_design_scores_gemma":[0.0035753062,0.00089960994,0.29029158,0.0005199565,0.000061373736,0.00023669188,0.002039956,0.5799774,0.0113814855,0.039385054,0.06870552,0.0029260945],"about_ca_topic_score_codex":0.00018975913,"about_ca_topic_score_gemma":0.00007273276,"teacher_disagreement_score":0.88410646,"about_ca_system_score_codex":0.00008835243,"about_ca_system_score_gemma":0.000029353618,"threshold_uncertainty_score":0.4398429},"labels":[],"label_agreement":null},{"id":"W2808680666","doi":"10.1109/wcnc.2018.8377404","title":"Data allocation for multi-class distributed storage systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Innovates - Technology Futures","keywords":"Computer science; Quality of service; Computer network; Computer data storage; Distributed computing; Class (philosophy); Distributed data store; Data recovery","score_opus":0.10377135571798643,"score_gpt":0.3341702140818454,"score_spread":0.23039885836385895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808680666","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021723146,0.00007657619,0.9960142,0.00053261995,0.0006016417,0.00040685336,0.00074252934,0.0013213536,0.00008699089],"genre_scores_gemma":[0.31674662,0.000005075729,0.68177533,0.00008708566,0.00010062033,0.000064715896,0.0008150278,0.0000107718615,0.0003947689],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988373,0.00001812235,0.00018735792,0.0005656658,0.00014281477,0.00024875428],"domain_scores_gemma":[0.996849,0.00007930773,0.00009623723,0.002760062,0.0001748893,0.000040528565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026630083,0.00011296804,0.00012333492,0.00006105095,0.00014085013,0.00015259288,0.0031877754,0.000072908275,0.0000026028097],"category_scores_gemma":[0.0004071273,0.00009651722,0.000013893359,0.0002992363,0.000111307054,0.0014254196,0.001380556,0.00005914004,0.0000789746],"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":[0.000016396069,0.00021386,0.00006900407,0.000079103054,0.000057337562,0.000009797533,0.00011779759,0.00056861644,0.0052486556,0.76758313,0.18592711,0.040109213],"study_design_scores_gemma":[0.0002535351,0.00006204591,0.000051374096,0.000007695432,0.0000031284626,0.0000048561856,0.00005966175,0.8758485,0.0014613741,0.00047198086,0.1216426,0.0001332764],"about_ca_topic_score_codex":0.000025960591,"about_ca_topic_score_gemma":0.000054528744,"teacher_disagreement_score":0.87527984,"about_ca_system_score_codex":0.00007020513,"about_ca_system_score_gemma":0.00003965729,"threshold_uncertainty_score":0.5923733},"labels":[],"label_agreement":null},{"id":"W2847452149","doi":"10.1007/978-981-13-0599-3_5","title":"3D NAND Flash Memories","year":2018,"lang":"en","type":"book-chapter","venue":"Springer series in advanced microelectronics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"NAND gate; Flash (photography); Computer science; Planar; Computer hardware; Solid-state; Lithography; Process (computing); State (computer science); Logic gate; Materials science; Engineering; Optoelectronics; Algorithm; Computer graphics (images); Operating system; Art; Engineering physics","score_opus":0.007954823010122004,"score_gpt":0.2233056752329622,"score_spread":0.21535085222284017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2847452149","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015308906,0.05993941,0.48169598,0.001388157,0.006410914,0.0029079537,0.00019962121,0.007126961,0.4388001],"genre_scores_gemma":[0.00068095775,0.012269459,0.62224793,0.00026534256,0.00026731184,0.00009835053,0.000059347465,0.00027588895,0.36383542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958264,0.000020040345,0.0007676393,0.0016482671,0.00044130857,0.0012963022],"domain_scores_gemma":[0.99608177,0.00009285242,0.00052223465,0.0029881105,0.00021638027,0.000098660654],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023550996,0.0009597354,0.00093070953,0.00054594775,0.00020981836,0.00018562569,0.0033428553,0.0006708767,0.00010615609],"category_scores_gemma":[0.00014865835,0.001056145,0.00016086646,0.00029619163,0.0007923552,0.0018583972,0.0024948185,0.0014876837,0.00033734043],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010802585,0.00003600577,0.000008260446,0.00014671685,0.000100329846,0.0002602216,0.00042332272,0.0001367819,0.005247634,0.84493196,0.0023768125,0.14622392],"study_design_scores_gemma":[0.00034432526,0.00034647644,0.000002406725,0.00020078092,0.000012929959,0.000084111125,0.0000151431295,0.000042300962,0.02483302,0.23364285,0.739552,0.0009236288],"about_ca_topic_score_codex":0.0000016993376,"about_ca_topic_score_gemma":0.00032207367,"teacher_disagreement_score":0.7371752,"about_ca_system_score_codex":0.0009870627,"about_ca_system_score_gemma":0.00040233383,"threshold_uncertainty_score":0.9991889},"labels":[],"label_agreement":null},{"id":"W2867850715","doi":"10.1007/978-981-13-0599-3_7","title":"Memory Driven Design Methodologies for Optimal SSD Performance","year":2018,"lang":"en","type":"book-chapter","venue":"Springer series in advanced microelectronics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"Computer science; Cloud computing; Electronics; Server; Constraint (computer-aided design); Solid-state; State (computer science); Distributed computing; Embedded system; Operating system; Engineering; Electrical engineering; Mechanical engineering; Algorithm","score_opus":0.03801412947484514,"score_gpt":0.2784674212272179,"score_spread":0.24045329175237276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2867850715","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021008062,0.0048273993,0.986083,0.00019583124,0.00086286,0.0015211665,0.000047457637,0.0013176627,0.0049345647],"genre_scores_gemma":[0.00032797822,0.0063728346,0.94819844,0.00010471741,0.00012335132,0.00030598565,0.000036268277,0.00016892368,0.04436151],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956044,0.000053183583,0.00081558817,0.0017283703,0.0003326343,0.0014658215],"domain_scores_gemma":[0.9959942,0.0005070186,0.0006446444,0.0024854105,0.00028607095,0.00008266681],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00070970244,0.0009861571,0.0010855342,0.0005736632,0.00026728216,0.00013389596,0.003820266,0.0007330987,0.000032857373],"category_scores_gemma":[0.00038447583,0.0010603367,0.00021996116,0.00022801316,0.0007422187,0.0018941239,0.0019300623,0.0012034011,0.000066815104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010023041,0.000058499645,0.000003682486,0.0005786575,0.0002772385,0.000105324776,0.000925254,0.039077885,0.016663792,0.36126775,0.0024416337,0.577598],"study_design_scores_gemma":[0.0013495019,0.0026077135,0.000004560326,0.0005162596,0.00006195267,0.00014835501,0.00010151436,0.004252822,0.29070982,0.24136241,0.45630023,0.00258485],"about_ca_topic_score_codex":8.6762356e-7,"about_ca_topic_score_gemma":0.000024318213,"teacher_disagreement_score":0.5750131,"about_ca_system_score_codex":0.0010031469,"about_ca_system_score_gemma":0.00048417153,"threshold_uncertainty_score":0.99918467},"labels":[],"label_agreement":null},{"id":"W2885627084","doi":"","title":"RaMP: A Lightweight {RDMA} Abstraction for Loosely Coupled Applications","year":2018,"lang":"en","type":"article","venue":"IEEE International Conference on Cloud Computing Technology and Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Remote direct memory access; Computer science; Abstraction; Operating system; Programming language; Computer architecture","score_opus":0.04702370220814162,"score_gpt":0.33856655467386165,"score_spread":0.29154285246572004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885627084","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":[0.060918313,0.000022174318,0.9277591,0.006845492,0.0013666841,0.00036588663,0.000009770288,0.0010478745,0.0016646971],"genre_scores_gemma":[0.8631906,0.000020592926,0.1362365,0.00021785281,0.00017711744,0.00006728473,0.0000025691552,0.0000063611415,0.00008114209],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99799675,0.000010004301,0.00030083722,0.0009207119,0.00036922318,0.00040247414],"domain_scores_gemma":[0.99798924,0.00016042533,0.00024938863,0.00072864234,0.0008045381,0.000067751775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005226342,0.00019141495,0.00017513627,0.00086172135,0.00079302257,0.00026802957,0.0030786053,0.00017177754,0.000007020147],"category_scores_gemma":[0.00029027852,0.00018176471,0.00003141716,0.0012395063,0.0019738767,0.0005290907,0.0005340915,0.00030258158,0.00005722446],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001086513,0.000044420798,0.00005417659,0.000003139297,0.0000081659755,0.0000021483727,0.00005129701,0.000020988948,0.021088047,0.90255153,0.00012250419,0.07604274],"study_design_scores_gemma":[0.00043014786,0.000381843,0.00022462265,0.00005845574,0.000004804198,0.00008153405,0.00009650393,0.44230688,0.06902163,0.48019165,0.0068727178,0.0003292127],"about_ca_topic_score_codex":0.0000038834323,"about_ca_topic_score_gemma":0.000006024845,"teacher_disagreement_score":0.80227226,"about_ca_system_score_codex":0.000111658235,"about_ca_system_score_gemma":0.00017885985,"threshold_uncertainty_score":0.741215},"labels":[],"label_agreement":null},{"id":"W2885725796","doi":"","title":"Geriatrix: aging what you see and what you don't see a file system aging approach for modern storage systems","year":2018,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute","funders":"","keywords":"File system; Computer science; Fragmentation (computing); Operating system; Software; Computer data storage; Flash memory; Embedded system","score_opus":0.02811065537350997,"score_gpt":0.2673739611441406,"score_spread":0.2392633057706306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885725796","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":[0.0036372135,0.002802166,0.98695827,0.00039620532,0.0007500025,0.0013294462,0.00043806215,0.0034657319,0.00022289775],"genre_scores_gemma":[0.804215,0.00033050016,0.19423203,0.000094764655,0.00026508086,0.0004479535,0.00009193891,0.00005622587,0.00026650142],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956951,0.00013763613,0.0007263926,0.0017794119,0.00061847013,0.0010429955],"domain_scores_gemma":[0.9961073,0.00041930337,0.000417108,0.0021785072,0.00061996654,0.0002578243],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008394773,0.00059784844,0.00079196144,0.0003270175,0.00053721055,0.0032670838,0.0027416002,0.00045424985,0.000012145656],"category_scores_gemma":[0.0003663725,0.00055272866,0.00012525822,0.0006669381,0.0006151012,0.009372517,0.0023240955,0.00058593473,0.00002740329],"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":[0.00023455021,0.0006044655,0.0001735762,0.003765751,0.00031137172,0.00036225768,0.011594889,0.0019467234,0.018020157,0.35901785,0.01878582,0.5851826],"study_design_scores_gemma":[0.0016516634,0.00092737906,0.00011423533,0.002376208,0.00009456272,0.0007782877,0.027103994,0.9237275,0.0026984208,0.0050059482,0.03310764,0.0024141541],"about_ca_topic_score_codex":0.000052482712,"about_ca_topic_score_gemma":0.000013521209,"teacher_disagreement_score":0.92178077,"about_ca_system_score_codex":0.00025639965,"about_ca_system_score_gemma":0.00015457023,"threshold_uncertainty_score":0.99969244},"labels":[],"label_agreement":null},{"id":"W2886216368","doi":"","title":"Remote regions: a simple abstraction for remote memory","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Remote direct memory access; Remote procedure call; Abstraction; Operating system; Host (biology); Interface (matter); Memory map; Memory management; Registered memory; Shared memory; Semiconductor memory","score_opus":0.03903986553302542,"score_gpt":0.30954988692390784,"score_spread":0.2705100213908824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886216368","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00073418516,0.000032455577,0.9890463,0.0021211612,0.0003132702,0.0002630475,0.0000040209375,0.0015408813,0.0059446753],"genre_scores_gemma":[0.05435364,0.000019921934,0.94320786,0.0005269404,0.00014341132,0.0000027517528,0.0000062404465,0.00001107485,0.001728158],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989781,0.000010296078,0.00017667499,0.00042583744,0.00013467095,0.00027441484],"domain_scores_gemma":[0.9984095,0.00012579506,0.00010026511,0.0011898977,0.00013323428,0.000041278825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001841291,0.00011257413,0.00011162525,0.00011014552,0.0001706147,0.0000655988,0.0008794128,0.00008815144,0.000016248896],"category_scores_gemma":[0.00039140577,0.00010048934,0.00004531976,0.00029083274,0.00012568975,0.0008979187,0.00029648098,0.000091920585,0.00018432029],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000124897615,0.000012519191,8.930162e-7,0.000009000893,0.000008271055,0.0000063483794,0.00007174595,0.00001467106,0.0028434645,0.063297756,0.042068135,0.89165473],"study_design_scores_gemma":[0.00035260117,0.00025581446,0.0000674523,0.000014782146,0.000004910569,0.000054590222,0.00012309756,0.12348059,0.047790002,0.58944947,0.23813199,0.00027470035],"about_ca_topic_score_codex":0.00008565275,"about_ca_topic_score_gemma":0.000093960116,"teacher_disagreement_score":0.89138,"about_ca_system_score_codex":0.00006244455,"about_ca_system_score_gemma":0.000031903925,"threshold_uncertainty_score":0.40978366},"labels":[],"label_agreement":null},{"id":"W2886549997","doi":"10.1109/isncc.2018.8530893","title":"Ensemble-based Adaptive Single-shot Multi-box Detector","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Single shot; Detector; Selection (genetic algorithm); Shot (pellet); Artificial intelligence; One shot; Pattern recognition (psychology); Algorithm; Data mining; Engineering","score_opus":0.09882987179631089,"score_gpt":0.2967603792482437,"score_spread":0.19793050745193283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886549997","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00218155,0.00016038833,0.98961747,0.00029484663,0.0011683361,0.0006312849,0.000072952585,0.004395366,0.0014778081],"genre_scores_gemma":[0.30729422,0.0000048480756,0.69200605,0.00028456884,0.000075561664,0.00009347441,0.000026338425,0.000031646967,0.000183291],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9966926,0.00008393008,0.00043804754,0.0016864365,0.00046281927,0.0006361413],"domain_scores_gemma":[0.995057,0.0002276379,0.00037771667,0.003887188,0.00032371221,0.00012674193],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022450807,0.0005992493,0.0005294145,0.00039920458,0.00014017623,0.00028067347,0.004655887,0.00062600814,0.00003880909],"category_scores_gemma":[0.00031103633,0.00054604496,0.00017778513,0.0004063071,0.0003800004,0.00045214142,0.006642134,0.00083313626,0.00030906682],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039081465,0.0034026369,0.00059059233,0.0009238393,0.00071220275,0.0015451444,0.001505588,0.018807447,0.12735733,0.06725704,0.020383192,0.7571242],"study_design_scores_gemma":[0.0010984888,0.00079948036,0.00014505003,0.00034600974,0.000032302658,0.000019258721,0.000065659704,0.3135455,0.65472275,0.02239902,0.0048236973,0.0020028003],"about_ca_topic_score_codex":0.00006434609,"about_ca_topic_score_gemma":0.00014211434,"teacher_disagreement_score":0.75512135,"about_ca_system_score_codex":0.0003662949,"about_ca_system_score_gemma":0.00027324987,"threshold_uncertainty_score":0.9996991},"labels":[],"label_agreement":null},{"id":"W2886599235","doi":"10.1016/j.future.2018.08.018","title":"Performance modeling for MPI applications with low overhead fine-grained profiling","year":2018,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"National Key Research and Development Program of China; University of Illinois at Urbana-Champaign; National Natural Science Foundation of China","keywords":"Computer science; Profiling (computer programming); Scalability; Cloud computing; Distributed computing; Supercomputer; Parallel computing; Operating system","score_opus":0.021085172923819222,"score_gpt":0.24377648626985715,"score_spread":0.22269131334603792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886599235","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049091727,0.00023473393,0.9853786,0.00033619534,0.006984627,0.0012590662,0.000021596761,0.00083331286,0.00004266175],"genre_scores_gemma":[0.13494878,0.000008385597,0.82797784,0.00013157292,0.035817217,0.0008873977,0.00013950784,0.00002494551,0.00006434514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984082,0.00002880723,0.00034178337,0.00065013004,0.0002548725,0.0003162356],"domain_scores_gemma":[0.998237,0.000027151737,0.00017060802,0.0010218156,0.00048635138,0.00005707393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020680351,0.00022779084,0.00022111175,0.00014278953,0.00047197295,0.0002998726,0.0008350244,0.00011618763,5.716818e-7],"category_scores_gemma":[0.0000058121464,0.00018643629,0.00003787045,0.00044167932,0.000047048707,0.0008407387,0.00017949253,0.000112729474,0.000020149098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004758461,0.00013622305,0.00022411662,0.00050507276,0.000113335125,0.0000044175836,0.00091911695,0.60240746,0.0071732635,0.21716991,0.051778626,0.11952091],"study_design_scores_gemma":[0.00033378717,0.00024216886,0.0000044655644,0.00003796592,0.000005006165,0.000028003962,0.000023712933,0.96927196,0.0032154017,0.000028774628,0.026559403,0.00024936502],"about_ca_topic_score_codex":0.0000030692966,"about_ca_topic_score_gemma":0.000014292636,"teacher_disagreement_score":0.36686453,"about_ca_system_score_codex":0.000076941746,"about_ca_system_score_gemma":0.00008382335,"threshold_uncertainty_score":0.7602651},"labels":[],"label_agreement":null},{"id":"W2887594472","doi":"","title":"Breaking Apart the {VFS} for Managing File Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Business","score_opus":0.02454009769179471,"score_gpt":0.2675380536129685,"score_spread":0.2429979559211738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887594472","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006402265,0.00006254537,0.9852355,0.0013805665,0.00046613108,0.00024911726,0.000023828634,0.0009538776,0.011564422],"genre_scores_gemma":[0.49164125,0.0000065245213,0.50364107,0.0010531825,0.0003429486,0.00029361012,0.00001368037,0.000019071891,0.0029886602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992533,0.000011330338,0.00011455333,0.00026421648,0.000110449524,0.00024619096],"domain_scores_gemma":[0.9987062,0.00022118368,0.000059222708,0.0009359766,0.000060537543,0.00001687587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017564533,0.00008111945,0.00008203388,0.000046813668,0.00025650815,0.00017766918,0.001446924,0.000031004645,0.00003207698],"category_scores_gemma":[0.00010003591,0.000050864022,0.00002507873,0.00022453243,0.00010920367,0.00047724482,0.00056344294,0.000046140744,0.000088153654],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000147272,0.0000056373665,0.000008016696,0.0000115806915,0.000008569825,0.0000021941783,0.000121449135,0.000054397427,0.00018967097,0.7716339,0.177033,0.050930068],"study_design_scores_gemma":[0.00014460049,0.000090561385,0.00004925826,0.00003792657,0.0000039103006,0.00003859841,0.00041933253,0.3264075,0.0022844046,0.04897774,0.6213304,0.00021579584],"about_ca_topic_score_codex":0.000027123095,"about_ca_topic_score_gemma":0.000015086403,"teacher_disagreement_score":0.7226562,"about_ca_system_score_codex":0.000026887985,"about_ca_system_score_gemma":0.000011295815,"threshold_uncertainty_score":0.2688769},"labels":[],"label_agreement":null},{"id":"W2892776878","doi":"10.1109/allerton.2018.8635867","title":"Universal and Dynamic Locally Repairable Codes with Maximal Recoverability via Sum-Rank Codes","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Locality; Erasure code; Disjoint sets; Reed–Solomon error correction; Discrete mathematics; Finite field; Code (set theory); Erasure; Mathematics; Cartesian product; Computer science; Linear code; Algorithm; Block code; Decoding methods","score_opus":0.008435974958480879,"score_gpt":0.22603481012118376,"score_spread":0.21759883516270287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892776878","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":[0.112594634,0.00004834218,0.8836101,0.0005720972,0.00006285476,0.00014844583,0.000013489797,0.0012481273,0.0017018844],"genre_scores_gemma":[0.6008369,0.000021877513,0.39876544,0.000110421606,0.0000067303954,0.000003566756,0.0000035756643,0.000007302643,0.00024420934],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856913,0.000040724866,0.00016699184,0.0006839429,0.00019957918,0.00033965983],"domain_scores_gemma":[0.99849784,0.00011560334,0.000075804426,0.0010955477,0.00014548753,0.00006972162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002452345,0.00018536813,0.0002126652,0.000088622925,0.00019496218,0.00010105703,0.0008008588,0.000089474954,0.000030358502],"category_scores_gemma":[0.00007838133,0.00014482703,0.000021738237,0.00037341748,0.00083964743,0.0013062842,0.0006280739,0.00015123536,0.000030300866],"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":[0.0012220436,0.00071932824,0.05415405,0.00024564014,0.00032491016,0.0005793975,0.0013715198,0.0006713216,0.016930612,0.30697045,0.005094618,0.6117161],"study_design_scores_gemma":[0.0029458904,0.0042732023,0.02804679,0.00014051727,0.00004942049,0.00053611,0.0008774231,0.7812043,0.021649124,0.14699554,0.011291424,0.0019902647],"about_ca_topic_score_codex":0.00016462772,"about_ca_topic_score_gemma":0.00096798106,"teacher_disagreement_score":0.78053296,"about_ca_system_score_codex":0.00012258565,"about_ca_system_score_gemma":0.0000724453,"threshold_uncertainty_score":0.5905875},"labels":[],"label_agreement":null},{"id":"W2895152529","doi":"10.7202/1051299ar","title":"Making Music with My Friends: Collaborations with the ecm+","year":2018,"lang":"en","type":"article","venue":"Circuit Musiques contemporaines","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Visual arts; Sociology; Psychology; Art","score_opus":0.06546042340924547,"score_gpt":0.2740791498566452,"score_spread":0.20861872644739976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895152529","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":[0.01600951,0.00021408069,0.9280412,0.004218555,0.00016816932,0.00061320094,0.000022288099,0.0016398334,0.049073122],"genre_scores_gemma":[0.97140366,0.000003695301,0.026283124,0.0015399724,0.00018667392,0.00014504702,0.00000890881,0.000029793666,0.00039913697],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983346,0.00007383245,0.00023182237,0.00062658946,0.00034429788,0.00038888113],"domain_scores_gemma":[0.99720085,0.0001677104,0.00026246306,0.0016603399,0.0006560652,0.000052580916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002627389,0.00028485942,0.0002508029,0.00016558962,0.00055683515,0.00038063448,0.0016997361,0.00008173604,0.000016275464],"category_scores_gemma":[0.000111251036,0.00016874081,0.000029857963,0.0015131484,0.001011927,0.0013873313,0.00032541147,0.0002024562,0.00003068694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030504165,0.000061008737,0.001244593,0.000022412643,0.00010548248,0.00015064862,0.01374596,0.000016858556,0.0009618778,0.96453434,0.0056877695,0.013438556],"study_design_scores_gemma":[0.0037117447,0.0044581145,0.005463516,0.0009062232,0.00015364008,0.0007879726,0.019382693,0.005378786,0.013899379,0.2534704,0.6886835,0.0037040152],"about_ca_topic_score_codex":0.000022892373,"about_ca_topic_score_gemma":0.00088002096,"teacher_disagreement_score":0.95539415,"about_ca_system_score_codex":0.000069304,"about_ca_system_score_gemma":0.00025593667,"threshold_uncertainty_score":0.68810505},"labels":[],"label_agreement":null},{"id":"W2895759845","doi":"10.22148/16.025","title":"Stable Random Projection: Lightweight, General-Purpose Dimensionality Reduction for Digitized Libraries","year":2018,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"sort; Computer science; Dimensionality reduction; Digital library; Projection (relational algebra); Random projection; Reduction (mathematics); Computer graphics (images); World Wide Web; Multimedia; Information retrieval; Artificial intelligence; Mathematics; Algorithm; Art","score_opus":0.036973478959737065,"score_gpt":0.2909724707646574,"score_spread":0.2539989918049203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895759845","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06972648,0.0005460573,0.92302865,0.0042106067,0.0015338127,0.00031422084,0.000018019107,0.00025126062,0.00037088842],"genre_scores_gemma":[0.23610817,0.00022417783,0.7582468,0.00016048856,0.0018023516,0.000010676279,0.000014875402,0.00001531408,0.0034171487],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986131,0.000039625163,0.00054387026,0.00021704928,0.00035138082,0.00023498044],"domain_scores_gemma":[0.99785244,0.00008139112,0.00057756825,0.00032834488,0.0010821372,0.00007810834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031184038,0.00015891885,0.0003436482,0.00013846565,0.00030596353,0.000310086,0.0006470841,0.0000852128,0.000009039355],"category_scores_gemma":[0.00034792745,0.00009982896,0.0001745555,0.00051415834,0.00022379952,0.0034732008,0.00018270545,0.00017849909,0.0000051734155],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022309253,0.00057529856,0.00017890177,0.00013021094,0.00083438074,0.000092307666,0.0023696746,0.001266608,0.07589925,0.547153,0.32102785,0.048241593],"study_design_scores_gemma":[0.005280604,0.0017419698,0.00016185416,0.00013531471,0.00019031895,0.0013059988,0.0007220225,0.033740193,0.28635108,0.33591327,0.33376417,0.0006932069],"about_ca_topic_score_codex":0.0000029912987,"about_ca_topic_score_gemma":0.0000017261261,"teacher_disagreement_score":0.21123973,"about_ca_system_score_codex":0.00009995425,"about_ca_system_score_gemma":0.00012213619,"threshold_uncertainty_score":0.4070907},"labels":[],"label_agreement":null},{"id":"W2896639624","doi":"10.1016/j.jpdc.2018.10.004","title":"Automatic generation of benchmarks for I/O-intensive parallel applications","year":2018,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"University of Illinois at Urbana-Champaign; National Natural Science Foundation of China","keywords":"Computer science; Parallel computing; Benchmark (surveying); TRACE (psycholinguistics); Computation; Supercomputer; Overhead (engineering); Parallel I/O; Parallel algorithm; Algorithm; Programming language","score_opus":0.03221570556506162,"score_gpt":0.2941877268886827,"score_spread":0.2619720213236211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896639624","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":[0.032084037,0.00033745985,0.96662927,0.00053438806,0.00012698962,0.00019472497,0.000026548398,0.00004511036,0.000021500671],"genre_scores_gemma":[0.5817568,0.000015101227,0.41802445,0.0000491834,0.00012332526,0.0000039252773,0.000023017528,0.0000028227519,0.0000013657767],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989025,0.000024482322,0.00055376923,0.00017594437,0.00015893359,0.00018439481],"domain_scores_gemma":[0.99778175,0.00018068419,0.00075617636,0.00026964105,0.00095129607,0.00006046978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028323493,0.00011381818,0.00027520093,0.00010916914,0.00017054645,0.000056094064,0.00051747664,0.000064917054,0.0000026965179],"category_scores_gemma":[0.0002971505,0.000096168005,0.00007105752,0.00024894997,0.0001425324,0.0003355372,0.000204824,0.00011262922,8.191698e-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":[0.00010747792,0.0003932307,0.0023323128,0.0002937404,0.00041814838,0.00003305284,0.0017914512,0.033511434,0.012156267,0.33074424,0.03187299,0.5863457],"study_design_scores_gemma":[0.0009511253,0.00051338883,0.0013577812,0.000069902024,0.000032471555,0.00016830635,0.00035657056,0.96672887,0.0012076214,0.026201772,0.00223151,0.00018068275],"about_ca_topic_score_codex":0.000001986298,"about_ca_topic_score_gemma":0.0000014226453,"teacher_disagreement_score":0.9332174,"about_ca_system_score_codex":0.000033618864,"about_ca_system_score_gemma":0.000057977097,"threshold_uncertainty_score":0.39216173},"labels":[],"label_agreement":null},{"id":"W2899166719","doi":"10.1016/j.future.2018.10.030","title":"Optimizing the cost of DBaaS object placement in hybrid storage systems","year":2018,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Université de Bretagne Occidentale; Providence Health Care","keywords":"Computer science; Scalability; Provisioning; Cloud computing; Context (archaeology); Distributed computing; Heuristic; Class (philosophy); Object (grammar); Cloud storage; State (computer science); Algorithm; Operating system","score_opus":0.023409867619538983,"score_gpt":0.24893654108682337,"score_spread":0.2255266734672844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899166719","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":[0.0028809279,0.0019190923,0.9455953,0.0002875071,0.047971927,0.0009360652,0.000020902917,0.0002839598,0.00010429895],"genre_scores_gemma":[0.828896,0.000058720838,0.13163528,0.00023092866,0.038560573,0.00032522864,0.00006697522,0.00003778556,0.00018850481],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99769723,0.00028430845,0.0006472508,0.00056549814,0.00046633134,0.00033940564],"domain_scores_gemma":[0.99781483,0.000081078,0.00039043155,0.0014192425,0.00024724228,0.000047145946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007419872,0.00024898406,0.000357025,0.00024279424,0.00021620789,0.00036132758,0.0014788453,0.00009839333,0.0000021881401],"category_scores_gemma":[0.000017550767,0.00018332254,0.000051166604,0.00057006715,0.000101791426,0.0006126178,0.00053942134,0.00020579838,0.000025274408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015270967,0.00009845959,0.000094643365,0.00013260172,0.00007376365,0.00005597772,0.00304172,0.66872907,0.0024829344,0.06532269,0.25048625,0.009466594],"study_design_scores_gemma":[0.0003591763,0.00016964883,0.000040300954,0.00008117771,0.0000041025755,0.000073828356,0.00029266093,0.9014934,0.002183006,0.0000054477614,0.095077775,0.00021951427],"about_ca_topic_score_codex":0.000065713655,"about_ca_topic_score_gemma":0.000042745807,"teacher_disagreement_score":0.82601506,"about_ca_system_score_codex":0.00019977124,"about_ca_system_score_gemma":0.00008159717,"threshold_uncertainty_score":0.74756765},"labels":[],"label_agreement":null},{"id":"W2899567128","doi":"10.1109/tcomm.2018.2879088","title":"Systematic Fountain Codes for Massive Storage Using the Truncated Poisson Distribution","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Bombardier (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Decoding methods; Fountain code; List decoding; Computer science; Overhead (engineering); Redundancy (engineering); Algorithm; Poisson distribution; Luby transform code; Erasure; Theoretical computer science; Hamming code; Mathematics; Concatenated error correction code; Block code; Statistics","score_opus":0.05223495903565117,"score_gpt":0.3216712573283314,"score_spread":0.26943629829268023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899567128","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":[0.00083411677,0.00013775156,0.9937155,0.0029832395,0.00028676272,0.0010892351,0.00033360854,0.00058162236,0.000038133574],"genre_scores_gemma":[0.89652914,0.00005249025,0.102707386,0.000092561946,0.000015271773,0.0004909822,0.000035445966,0.000014788561,0.000061959996],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870217,0.00022758401,0.0003558821,0.00027582134,0.00018341419,0.00025515156],"domain_scores_gemma":[0.99456525,0.00096754136,0.00022347874,0.003889182,0.0003144205,0.000040154144],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00039767948,0.00017138419,0.0002138297,0.00011303114,0.0017703315,0.00015233879,0.0029622924,0.00009389525,0.0000034797158],"category_scores_gemma":[0.000096671174,0.00013385543,0.00010194034,0.0007599069,0.00049294985,0.0005627219,0.00003301734,0.00026809168,0.00002749461],"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":[0.00020111568,0.0027391957,0.000009480022,0.002458486,0.0013653808,0.000007563671,0.009413762,0.056570847,0.04753528,0.83729327,0.0037847832,0.038620852],"study_design_scores_gemma":[0.00043826853,0.0002388557,0.000014101798,0.0005788355,0.00014047665,0.000026659784,0.0010377882,0.9605531,0.02401295,0.011250008,0.001369231,0.00033971763],"about_ca_topic_score_codex":0.00004963812,"about_ca_topic_score_gemma":0.00016122882,"teacher_disagreement_score":0.9039823,"about_ca_system_score_codex":0.00032721012,"about_ca_system_score_gemma":0.00007507411,"threshold_uncertainty_score":0.99952924},"labels":[],"label_agreement":null},{"id":"W2901817239","doi":"","title":"{RAID} to {ML}: A Big Data Evolution","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"RAID; Computer science; Operating system","score_opus":0.08636695483199959,"score_gpt":0.3058816529706371,"score_spread":0.2195146981386375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901817239","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00094777165,0.00002875816,0.9906708,0.0022421458,0.0005253426,0.00009668977,0.000015930975,0.0013136959,0.004158894],"genre_scores_gemma":[0.37364906,0.0000018145421,0.625125,0.0005219529,0.00014764468,0.00000544064,0.0000073661836,0.000004434071,0.0005372871],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989787,0.000010211,0.000103807244,0.0005185603,0.00016161418,0.00022712245],"domain_scores_gemma":[0.99651176,0.000026275067,0.000027046153,0.0033226334,0.000060990904,0.00005129907],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001461155,0.00007938253,0.000072395174,0.00011970192,0.00008691278,0.000067480825,0.0036666014,0.000040081344,0.000014741409],"category_scores_gemma":[0.00031923846,0.00006720991,0.0000081261405,0.0006455571,0.00008365952,0.0009845777,0.0045142723,0.00005838482,0.0013423952],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030603035,0.000024571713,0.00010285639,0.0000021150738,0.0000050627104,0.000007136901,0.00007488492,0.000004251449,0.0032819798,0.30846578,0.10096007,0.5870682],"study_design_scores_gemma":[0.0003179083,0.00048391268,0.0028819973,0.000023472414,0.000004974354,0.00004152095,0.00013092438,0.052127082,0.015099712,0.10470047,0.8235834,0.00060457754],"about_ca_topic_score_codex":0.000050643644,"about_ca_topic_score_gemma":0.00016476342,"teacher_disagreement_score":0.72262335,"about_ca_system_score_codex":0.00005267681,"about_ca_system_score_gemma":0.000037825033,"threshold_uncertainty_score":0.9994352},"labels":[],"label_agreement":null},{"id":"W2903566129","doi":"","title":"{AMD} x86 Memory Encryption Technologies","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Encryption; Computer science; x86; Memory protection; Computer security; Semiconductor memory; Operating system; Memory management; Virtual memory; Software","score_opus":0.014328068524788403,"score_gpt":0.2366149128837393,"score_spread":0.22228684435895088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903566129","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":[0.0026520742,0.00017125653,0.9759956,0.006601944,0.00018180445,0.000098485056,0.0000025808977,0.009585416,0.0047108447],"genre_scores_gemma":[0.5603855,0.00018376631,0.43787912,0.00010047873,0.000012410239,0.000033844222,5.4616805e-7,0.000007152264,0.0013971598],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989822,0.000011334626,0.0001442243,0.00040916895,0.00017508234,0.00027802773],"domain_scores_gemma":[0.99844515,0.00009876337,0.000060495186,0.0013329921,0.000043235268,0.000019390276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011208897,0.00012223421,0.000109515175,0.00017807444,0.00007020518,0.0000415361,0.0017280824,0.00011526753,0.000029207444],"category_scores_gemma":[0.00034146555,0.000070789,0.000030423598,0.00035944805,0.00019518111,0.0013827106,0.0010794426,0.000076977376,0.00057256874],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.79603e-7,0.000008590104,0.00004465394,0.0000014164012,0.0000024734043,0.000008929314,0.000009490082,9.182701e-7,0.021793207,0.29011565,0.0023492689,0.6856646],"study_design_scores_gemma":[0.00038298228,0.00011492257,0.00026618515,0.00003171319,0.0000023131877,0.000040760176,0.00025042376,0.00043060436,0.5163773,0.4373988,0.04430366,0.00040036382],"about_ca_topic_score_codex":0.0000034653676,"about_ca_topic_score_gemma":0.0000040711507,"teacher_disagreement_score":0.6852642,"about_ca_system_score_codex":0.000069960995,"about_ca_system_score_gemma":0.00001923117,"threshold_uncertainty_score":0.7359404},"labels":[],"label_agreement":null},{"id":"W2903878491","doi":"","title":"Accomplishing Data Level Security in MongoDB","year":2014,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Computer security","score_opus":0.06971315032719558,"score_gpt":0.2823994046771038,"score_spread":0.2126862543499082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903878491","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":[0.017984116,0.0010802632,0.967305,0.0012308562,0.0017593226,0.00040737036,0.00045823058,0.0006344967,0.009140348],"genre_scores_gemma":[0.8830145,0.00016082198,0.115556486,0.00041033654,0.00013917773,0.00003028448,0.0005672567,0.000017412905,0.00010371966],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99708945,0.00017668243,0.0010446232,0.0004778273,0.00046653431,0.0007448775],"domain_scores_gemma":[0.99609053,0.00028140465,0.0005722143,0.00270625,0.0002449172,0.00010469905],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0017706276,0.00034869835,0.00040331026,0.00048385453,0.00029037957,0.0013164511,0.0038409436,0.00034518362,0.000020619746],"category_scores_gemma":[0.0034722907,0.00039819063,0.000044840457,0.0012206227,0.00046596644,0.04530038,0.0036079267,0.0006162591,0.0003849112],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000912421,0.000041454154,0.0009993379,0.00047694187,0.000014150839,0.000008684889,0.007907129,0.0014699769,0.000014879035,0.19761755,0.0045016515,0.78693914],"study_design_scores_gemma":[0.00060394156,0.00008770708,0.007907224,0.00075132767,0.000012213453,0.00012100315,0.0011374995,0.652709,0.00034226096,0.18358918,0.15209858,0.0006400632],"about_ca_topic_score_codex":0.0010106523,"about_ca_topic_score_gemma":0.00047608613,"teacher_disagreement_score":0.8650304,"about_ca_system_score_codex":0.00057955756,"about_ca_system_score_gemma":0.00015118784,"threshold_uncertainty_score":0.999847},"labels":[],"label_agreement":null},{"id":"W2910682868","doi":"10.32604/cmc.2019.03585","title":"GFCache: A Greedy Failure Cache Considering Failure Recency and Failure Frequency for an Erasure-coded Storage System","year":2019,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cascades (Canada)","funders":"","keywords":"Computer science; Erasure; Cache; Parallel computing; Operating system; Programming language","score_opus":0.015434073613706138,"score_gpt":0.23083397374992357,"score_spread":0.21539990013621743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910682868","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":[0.59715253,0.00041080292,0.3807016,0.001377404,0.009518369,0.005317914,0.00087666657,0.0045656664,0.00007904777],"genre_scores_gemma":[0.6347322,0.000037397698,0.36238125,0.00041981478,0.0011144073,0.00045686596,0.00043776055,0.00028024692,0.00014006151],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9864103,0.0012982313,0.0034517448,0.004720846,0.0011760694,0.0029428124],"domain_scores_gemma":[0.9893707,0.00095206074,0.002582853,0.005319101,0.0010541135,0.0007211793],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0031398225,0.0025558043,0.0042019715,0.001020823,0.00077138474,0.0051502213,0.006230924,0.0013992765,0.00017950336],"category_scores_gemma":[0.00032863792,0.0026049297,0.00042290564,0.0008470352,0.0006272867,0.0053116395,0.004673781,0.00079832,0.00044308073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002965748,0.00025600157,0.0004985227,0.0020353664,0.0005413279,0.00035245426,0.002304866,0.00012575068,0.9276482,0.041783523,0.015750663,0.008406764],"study_design_scores_gemma":[0.024241747,0.004584724,0.0046857204,0.007908893,0.0008193041,0.0036872549,0.003324938,0.010012874,0.8187525,0.011392862,0.096028574,0.014560605],"about_ca_topic_score_codex":0.0004270169,"about_ca_topic_score_gemma":0.00030924316,"teacher_disagreement_score":0.10889568,"about_ca_system_score_codex":0.0006580332,"about_ca_system_score_gemma":0.00036598966,"threshold_uncertainty_score":0.9998971},"labels":[],"label_agreement":null},{"id":"W2911938026","doi":"10.1007/s10766-019-00631-4","title":"Efficient Methods for Trace Analysis Parallelization","year":2019,"lang":"en","type":"article","venue":"International Journal of Parallel Programming","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Speedup; Scalability; Parallel computing; TRACE (psycholinguistics); Parallelizable manifold; Tracing; Synchronization (alternating current); Thread (computing); Distributed computing; Algorithm; Channel (broadcasting); Database; Programming language","score_opus":0.023685949324013,"score_gpt":0.37335821320108536,"score_spread":0.34967226387707234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911938026","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067411736,0.0004988263,0.99057376,0.0009879917,0.00082840596,0.00022985546,0.000002319427,0.000088626075,0.000049021033],"genre_scores_gemma":[0.23568243,0.000017004306,0.76412255,0.000044241413,0.000055669017,0.000011804789,0.000004906861,0.0000063955413,0.000054986776],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853605,0.000059433514,0.0005349635,0.0002421282,0.00041986676,0.00020753889],"domain_scores_gemma":[0.9979923,0.00027910882,0.00066334364,0.0003110935,0.0007011133,0.000053059528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008987595,0.00012472927,0.00027479112,0.0006074382,0.000040012732,0.00019216504,0.0017900157,0.00006423655,0.000011306473],"category_scores_gemma":[0.00034644766,0.000107611704,0.00029337488,0.00057445705,0.000033340955,0.0004242966,0.00020368131,0.00014890854,0.00000831743],"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":[0.00005338053,0.000115773524,0.00090080703,0.000007667116,0.000740934,0.000015048703,0.00025271092,0.3672475,0.0007462803,0.044550695,0.00004873523,0.5853205],"study_design_scores_gemma":[0.0012856643,0.00027923248,0.00068011065,0.00003420004,0.00013747606,0.000089377296,0.00014872673,0.9232045,0.0009908361,0.009239056,0.06364477,0.00026608093],"about_ca_topic_score_codex":0.000002791465,"about_ca_topic_score_gemma":0.000001385607,"teacher_disagreement_score":0.5850544,"about_ca_system_score_codex":0.00012045758,"about_ca_system_score_gemma":0.000052713323,"threshold_uncertainty_score":0.4388278},"labels":[],"label_agreement":null},{"id":"W2912682446","doi":"10.1007/978-981-13-2721-6_4","title":"Semantic-Aware Metadata Organization for Exact-Matching Queries","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Metadata; Scalability; Information retrieval; Directory; Metadata repository; Metadata management; Database; World Wide Web","score_opus":0.021834644584808775,"score_gpt":0.24244189149113068,"score_spread":0.2206072469063219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912682446","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000026272498,0.00017056809,0.9704325,0.0005703535,0.0004603239,0.0005481864,0.00016339305,0.0017434885,0.02590852],"genre_scores_gemma":[0.0013403399,0.00018638419,0.3674961,0.00035522692,0.00008267125,0.000009683194,0.0008922102,0.00013132999,0.62950605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99833745,0.000005663941,0.00032256593,0.0007956234,0.00027692216,0.00026178596],"domain_scores_gemma":[0.99712676,0.00018278215,0.0002981173,0.0021118454,0.00024385618,0.000036656118],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000119231976,0.0003767865,0.00045095777,0.00020839262,0.00014891283,0.0003844007,0.002250284,0.0003412358,0.00010056518],"category_scores_gemma":[0.00013892331,0.00033829937,0.00007182417,0.00008918454,0.000071690374,0.0026164635,0.0017826788,0.00024724615,0.00023296612],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010878626,0.0000034223624,0.0000010726856,0.00007186611,0.00003742889,0.0000053975928,0.000038529746,0.000026124375,0.00007591738,0.98704004,0.004090103,0.008608979],"study_design_scores_gemma":[0.000255597,0.00009934487,0.0000036212653,0.00017502473,0.00006467886,0.00003962102,0.00006400483,0.0014403921,0.0043335776,0.48378035,0.5086762,0.001067634],"about_ca_topic_score_codex":0.000009464149,"about_ca_topic_score_gemma":0.000026711174,"teacher_disagreement_score":0.6035975,"about_ca_system_score_codex":0.000090582456,"about_ca_system_score_gemma":0.00012142844,"threshold_uncertainty_score":0.9999069},"labels":[],"label_agreement":null},{"id":"W2913989356","doi":"10.3389/fncir.2019.00005","title":"DVID: Distributed Versioned Image-Oriented Dataservice","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neural Circuits","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Dalhousie University; Howard Hughes Medical Institute","keywords":"Connectomics; Computer science; Software versioning; Workflow; Software; Snapshot (computer storage); Software deployment; Server; Data type; Distributed computing; World Wide Web; Operating system; Database; Connectome","score_opus":0.008965437116082465,"score_gpt":0.2263082597028328,"score_spread":0.21734282258675033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913989356","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":[0.06997418,0.00042690797,0.92343646,0.00087065645,0.0031607635,0.000490772,0.00042307028,0.0009314497,0.00028573532],"genre_scores_gemma":[0.9259778,0.0000331293,0.07253413,0.0005135389,0.000028331844,0.000024709003,0.0007758741,0.000023001207,0.00008943401],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980741,0.00006094445,0.00027690124,0.00073500676,0.000335121,0.0005179147],"domain_scores_gemma":[0.9980813,0.00005717048,0.00012397624,0.001590906,0.00006309375,0.00008350544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014023171,0.00022151877,0.00029331914,0.00025895904,0.00007722159,0.00008347884,0.0021954423,0.000111313915,0.000016267191],"category_scores_gemma":[0.0001639694,0.00022488272,0.000046514695,0.0013056068,0.00008159855,0.0021653313,0.0009199015,0.00035126595,0.00016980238],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016081223,0.00071574096,0.12049733,0.00041662325,0.00015639089,0.0018478794,0.0011486161,0.0033966757,0.0373059,0.032225642,0.42827412,0.37385425],"study_design_scores_gemma":[0.013305357,0.0009543446,0.07067593,0.0003647325,0.00006489656,0.00022187397,0.0031275887,0.61479956,0.037097838,0.033589292,0.22118986,0.004608729],"about_ca_topic_score_codex":0.000018146578,"about_ca_topic_score_gemma":0.000003750467,"teacher_disagreement_score":0.8560037,"about_ca_system_score_codex":0.00017560074,"about_ca_system_score_gemma":0.00003368064,"threshold_uncertainty_score":0.9170451},"labels":[],"label_agreement":null},{"id":"W2914522519","doi":"10.1007/s11390-019-1899-7","title":"ROCO: Using a Solid State Drive Cache to Improve the Performance of a Host-Aware Shingled Magnetic Recording Drive","year":2019,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Cache; Operating system; Parallel computing; Host (biology)","score_opus":0.008948873919923585,"score_gpt":0.24744274182685375,"score_spread":0.23849386790693017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914522519","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":[0.63990414,0.00010753233,0.35769522,0.0016177022,0.0004250752,0.00018510116,0.0000012626039,0.000059747126,0.000004220919],"genre_scores_gemma":[0.8227348,0.00004604643,0.17704177,0.00013812313,0.00002421737,0.0000027706656,3.715756e-8,0.00000609278,0.000006152753],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980315,0.000027473276,0.00051496114,0.00043120407,0.00052752474,0.00046731628],"domain_scores_gemma":[0.9975301,0.00011026118,0.0005903641,0.0008495099,0.0008385944,0.00008117625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097453175,0.00018292322,0.00039931815,0.0010698386,0.00022171794,0.00015346776,0.0033771077,0.00009458943,0.0000012396654],"category_scores_gemma":[0.00014431636,0.00012551754,0.000043736734,0.0024993946,0.0007333689,0.001571375,0.0023088597,0.00048422944,0.0000046629043],"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":[0.000029264682,0.000066868975,0.007579821,0.000045936962,0.00003413814,0.00006196382,0.0013270605,0.0023574557,0.2892858,0.0044457586,0.00006959021,0.69469637],"study_design_scores_gemma":[0.0009791153,0.006156898,0.0024478757,0.00039251224,0.000024153256,0.0013865068,0.00068599597,0.7416484,0.23732542,0.007695121,0.00074291375,0.0005151411],"about_ca_topic_score_codex":0.0000051537177,"about_ca_topic_score_gemma":0.0000024365897,"teacher_disagreement_score":0.7392909,"about_ca_system_score_codex":0.0001265539,"about_ca_system_score_gemma":0.00034880775,"threshold_uncertainty_score":0.62755626},"labels":[],"label_agreement":null},{"id":"W2914831260","doi":"","title":"Proceedings of the 7th USENIX Conference on Hot Topics in Storage and File Systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; File system; Operating system","score_opus":0.049016086767015535,"score_gpt":0.25344281221239207,"score_spread":0.20442672544537654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914831260","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":[0.869838,0.00025152502,0.087094285,0.003255473,0.0007822666,0.0011311406,0.00011020793,0.00086850167,0.036668625],"genre_scores_gemma":[0.98653936,0.000005730908,0.012527735,0.000046156394,0.000009258228,0.000013885616,6.11205e-7,0.0000028958327,0.00085437676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939656,0.0000066313924,0.000118736236,0.00019444,0.00016894897,0.00011465571],"domain_scores_gemma":[0.9995044,0.000031507156,0.00007254548,0.00028675355,0.00007811913,0.0000266908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011473588,0.000071459435,0.000111501395,0.000054070853,0.00001867612,0.00005583559,0.00071104267,0.00004685383,0.0000034967334],"category_scores_gemma":[0.00018136713,0.000045490408,0.000008045087,0.00024345516,0.000081499995,0.00035207547,0.00048230574,0.00010703332,0.0000029002508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000062420468,0.00003887748,0.00202296,0.000035964847,0.0000031545817,0.000004428172,0.0008337787,0.000109010456,0.00053092954,0.973199,0.019042782,0.0041728667],"study_design_scores_gemma":[0.0051105525,0.002783315,0.07349211,0.0016947391,0.000021597265,0.00023836331,0.020211954,0.53011876,0.0688402,0.15167989,0.14319772,0.0026107708],"about_ca_topic_score_codex":0.00005574087,"about_ca_topic_score_gemma":0.000017249924,"teacher_disagreement_score":0.82151914,"about_ca_system_score_codex":0.000036534824,"about_ca_system_score_gemma":0.000033043365,"threshold_uncertainty_score":0.1855045},"labels":[],"label_agreement":null},{"id":"W2916926104","doi":"10.18429/jacow-ipac2015-mopwi050","title":"Open XAL Status Report 2015","year":2015,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TRIUMF","funders":"","keywords":"Oak Ridge National Laboratory; Spallation Neutron Source; Open source; National laboratory; Computer science; Operating system; Port (circuit theory); Architecture; Open architecture; Particle accelerator; Neutron source; Engineering; Software; Physics; Nuclear physics; Neutron; Engineering physics; Geography; Electrical engineering; Civil engineering","score_opus":0.031904417121804196,"score_gpt":0.28170713975942735,"score_spread":0.24980272263762315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916926104","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005165894,0.0004720618,0.8992932,0.013908587,0.00021745644,0.00030322635,0.00002106983,0.0008440028,0.079774514],"genre_scores_gemma":[0.23429194,0.00008757328,0.75282925,0.00016289447,0.000010699403,0.000054209846,0.00015809186,0.000024462943,0.012380863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966205,0.0013146068,0.00039787724,0.00075092795,0.0004692864,0.00044681047],"domain_scores_gemma":[0.9931384,0.00049027166,0.00035090063,0.0040615853,0.0016755365,0.00028332078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051239985,0.000194419,0.00023499267,0.00014013961,0.00023089025,0.00076132343,0.0050254995,0.00010717074,0.000024255902],"category_scores_gemma":[0.0046830946,0.00019557965,0.00005219973,0.00076273514,0.00022369732,0.001563034,0.0054504843,0.00026656088,0.00015027323],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008633164,0.00038266217,0.0023585847,0.000011361405,0.00002856166,0.00017417001,0.004339385,0.00004088494,0.0010599121,0.7851022,0.04501005,0.16148362],"study_design_scores_gemma":[0.0016228774,0.0000021083338,0.0022824628,0.0002806978,0.0000145681515,0.00035568245,0.00047913028,0.019415375,0.069322005,0.09747984,0.8078807,0.00086455693],"about_ca_topic_score_codex":0.0010791412,"about_ca_topic_score_gemma":0.00072100444,"teacher_disagreement_score":0.76287067,"about_ca_system_score_codex":0.00017056052,"about_ca_system_score_gemma":0.00043840706,"threshold_uncertainty_score":0.9338712},"labels":[],"label_agreement":null},{"id":"W2919259445","doi":"","title":"Persistent memory storage of cold regions in the OpenJ9 Java virtual machine.","year":2018,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Operating system; Java; Embedded system","score_opus":0.1334885456957214,"score_gpt":0.3954844135383679,"score_spread":0.2619958678426465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919259445","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":[0.4590837,0.02696271,0.21514732,0.22009027,0.007433594,0.042000953,0.0051076515,0.00079475634,0.023379035],"genre_scores_gemma":[0.9916626,0.0004984607,0.0063514053,0.0000761035,0.00002665744,0.00020684245,0.0000027656392,0.000012361533,0.0011627853],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9968403,0.0006623321,0.0004492564,0.000579791,0.00091150735,0.00055682176],"domain_scores_gemma":[0.992241,0.0020728288,0.0003358289,0.0016901382,0.0036147088,0.00004547703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015907702,0.00023252894,0.00046858678,0.00025352152,0.0005952805,0.00005623021,0.0038108416,0.000073188836,0.00000381033],"category_scores_gemma":[0.0051143896,0.00013767171,0.000110876,0.0025816811,0.0026057109,0.0004312105,0.001662242,0.00044606873,0.0000056539734],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047442637,0.00044254024,0.00009349395,0.00011349112,0.00019841739,0.000010051035,0.024463067,0.0016018398,0.009572773,0.94004714,0.011842508,0.011140232],"study_design_scores_gemma":[0.005855505,0.009483298,0.00043691648,0.0018793148,0.000055367553,0.0000062035137,0.45723456,0.013389924,0.38927272,0.052301798,0.06903934,0.0010450615],"about_ca_topic_score_codex":0.000010981008,"about_ca_topic_score_gemma":0.0005003611,"teacher_disagreement_score":0.8877454,"about_ca_system_score_codex":0.00026990724,"about_ca_system_score_gemma":0.00042257353,"threshold_uncertainty_score":0.96008503},"labels":[],"label_agreement":null},{"id":"W2923701711","doi":"10.1109/bdcloud.2018.00102","title":"DataFall: A Policy-Driven Algorithm for Decentralized Placement and Reorganization of Replicated Data","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Ericsson (Canada)","funders":"","keywords":"Computer science; Distributed computing; Hash function; Upgrade; Variety (cybernetics); Object (grammar); Set (abstract data type); Data structure; State (computer science); Simple (philosophy); Algorithm; Computer security","score_opus":0.04063099782842776,"score_gpt":0.3262534276605167,"score_spread":0.2856224298320889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2923701711","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040118367,0.00003299784,0.99767023,0.0008372061,0.00004257723,0.0003355663,0.00025384637,0.00036762538,0.000058765687],"genre_scores_gemma":[0.014321688,0.00009387765,0.9850195,0.00012476153,0.000025486062,0.000009261694,0.0003437775,0.000008556161,0.0000530801],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989888,0.0000126722,0.00019990039,0.000501943,0.000115414754,0.00018129034],"domain_scores_gemma":[0.99746746,0.000057050453,0.00011714077,0.0021840676,0.00013739127,0.00003688647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015195285,0.000087659035,0.00012772641,0.00009876077,0.00006520067,0.000040801962,0.0016223982,0.000045091376,0.0000065579793],"category_scores_gemma":[0.00040265848,0.00007680468,0.000006460254,0.00046938914,0.00014568125,0.0007548553,0.0021926034,0.000029659248,0.0000042921492],"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":[0.000035294514,0.00017062662,0.00031172868,0.000044103243,0.00008718282,0.0000027765168,0.00041368813,0.0000149090665,0.024176015,0.26970187,0.034299973,0.67074186],"study_design_scores_gemma":[0.0014942082,0.00038321558,0.00023390968,0.000022319151,0.000016720322,0.000019609673,0.0001007594,0.8351463,0.10518534,0.009611963,0.047500532,0.00028514478],"about_ca_topic_score_codex":0.000039325125,"about_ca_topic_score_gemma":0.000016640133,"teacher_disagreement_score":0.83513135,"about_ca_system_score_codex":0.000028796705,"about_ca_system_score_gemma":0.000057585283,"threshold_uncertainty_score":0.3132004},"labels":[],"label_agreement":null},{"id":"W2945891467","doi":"10.5281/zenodo.2578277","title":"Building an open source software ecosystem for cross-disciplinary plasma research and education","year":2019,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Cross disciplinary; Open source; Open source software; Discipline; Ecosystem; Software; Computer science; Data science; Sociology; Ecology; Operating system; Biology; Social science","score_opus":0.11661743950196209,"score_gpt":0.3806224084474298,"score_spread":0.2640049689454677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945891467","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016930422,0.0011899648,0.91171557,0.0009882522,0.0017977272,0.008451267,0.0027700607,0.00685501,0.04930172],"genre_scores_gemma":[0.15595874,0.0030304207,0.70124775,0.00020571028,0.003161134,0.000021215881,0.030713165,0.018456163,0.0872057],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9952361,0.0003900145,0.00056000345,0.001784284,0.0012159253,0.00081370305],"domain_scores_gemma":[0.99260145,0.00021509822,0.00043694972,0.0026244035,0.0038603186,0.00026175502],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.00441234,0.00035692978,0.00045739923,0.00091852155,0.0044500986,0.0070846924,0.0097087575,0.00037491502,0.00027925998],"category_scores_gemma":[0.004027357,0.00038155488,0.000053246004,0.0010375865,0.00033082,0.0025644887,0.024113482,0.0009587536,0.0008025258],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008183861,0.00030108602,0.000013182183,0.0011726124,0.000060940365,0.000014873227,0.0006373655,0.00016326705,0.00049205933,0.014371961,0.319637,0.6630538],"study_design_scores_gemma":[0.0003810511,0.0008893457,0.00008649057,0.0003956421,0.0000094571915,0.00043491033,0.00031039186,0.0019014946,0.00019914031,0.0048118266,0.9901439,0.0004363778],"about_ca_topic_score_codex":0.000032549,"about_ca_topic_score_gemma":0.0000022251868,"teacher_disagreement_score":0.67050683,"about_ca_system_score_codex":0.0010449679,"about_ca_system_score_gemma":0.0002017869,"threshold_uncertainty_score":0.99997544},"labels":[],"label_agreement":null},{"id":"W2949266513","doi":"10.1515/res-2019-0002","title":"Suitability of Flash Media for the Long-Term Storage of Information","year":2019,"lang":"en","type":"article","venue":"Restaurator International Journal for the Preservation of Library and Archival Material","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Heritage","funders":"","keywords":"USB; Flash (photography); Flash memory; Flash memory emulator; Computer science; Ageing; Relative humidity; Flash file system; Embedded system; Computer hardware; Operating system; Semiconductor memory; Computer memory; Art; Medicine; Physics","score_opus":0.017619296766525818,"score_gpt":0.26292782407201204,"score_spread":0.24530852730548622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949266513","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":[0.76320386,0.000037798894,0.23216209,0.0020864634,0.0014452843,0.00045059546,0.00055922265,0.000021884127,0.000032816806],"genre_scores_gemma":[0.983787,0.00011861472,0.015807506,0.00004048435,0.00013071545,0.000019711046,0.000066330154,0.000005322241,0.000024339797],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990172,0.000041724354,0.00047622828,0.00008649106,0.00028351202,0.00009484989],"domain_scores_gemma":[0.9977691,0.0012356787,0.000550437,0.0002864691,0.00013699847,0.000021277549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000308589,0.00007833119,0.00013728726,0.00009857687,0.000069853246,0.00011843968,0.0014814871,0.000028104554,0.000014874568],"category_scores_gemma":[0.00029761397,0.00004678845,0.0000726645,0.00007470705,0.00012356655,0.0049850014,0.00039854224,0.00007796722,2.938665e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003114911,0.000104572624,0.019248305,0.0004418829,0.00027766227,8.9966085e-7,0.001617426,0.0019044087,0.04806308,0.86041355,0.0006843096,0.064129],"study_design_scores_gemma":[0.0032264201,0.0007776877,0.4003471,0.0002955798,0.000049740363,0.000043650216,0.00045214331,0.037409764,0.33072588,0.21849573,0.007874461,0.00030182666],"about_ca_topic_score_codex":0.0000013411219,"about_ca_topic_score_gemma":2.8500205e-7,"teacher_disagreement_score":0.6419178,"about_ca_system_score_codex":0.00000616609,"about_ca_system_score_gemma":0.000058992115,"threshold_uncertainty_score":0.36140054},"labels":[],"label_agreement":null},{"id":"W2949440309","doi":"10.1109/mce.2019.2905541","title":"Giving Your Home an Edge [The Art of Storage]","year":2019,"lang":"en","type":"article","venue":"IEEE Consumer Electronics Magazine","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Edge computing; Cloud computing; Enhanced Data Rates for GSM Evolution; Computer network; Edge device; Gateway (web page); Residential gateway; Telecommunications; The Internet; Internet of Things; Default gateway; Computer security; World Wide Web; Operating system","score_opus":0.014792911202648928,"score_gpt":0.25476357737455535,"score_spread":0.23997066617190643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949440309","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":[0.44985887,0.0059989314,0.5380563,0.001408092,0.0012983414,0.00073620374,0.00003398656,0.001118039,0.0014912339],"genre_scores_gemma":[0.979694,0.00030237404,0.017229214,0.00019497598,0.000039164624,0.000024139516,0.000010983039,0.00003455411,0.0024705706],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99801505,0.00007589656,0.0003374488,0.00056738727,0.00035609675,0.0006481401],"domain_scores_gemma":[0.9971132,0.00015958757,0.00024332738,0.0022668927,0.00015090668,0.000066070985],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00043123827,0.0002465093,0.0003284867,0.00017524067,0.00009001845,0.000079882724,0.0024133644,0.000107966465,0.000045954996],"category_scores_gemma":[0.00007711904,0.00020044448,0.00007333477,0.0006778575,0.00017927738,0.0009808766,0.00038021957,0.0005084119,0.00085471076],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008511011,0.000552558,0.005200298,0.00019027578,0.00029156668,0.00007872651,0.0007770289,0.0024706323,0.4829727,0.22724539,0.031182472,0.24895322],"study_design_scores_gemma":[0.0021931976,0.0015509803,0.0046629147,0.00009357142,0.000070492235,0.00026304292,0.00009123425,0.05795843,0.088744536,0.036754187,0.8059211,0.0016963118],"about_ca_topic_score_codex":0.0000035158064,"about_ca_topic_score_gemma":0.000038043643,"teacher_disagreement_score":0.7747386,"about_ca_system_score_codex":0.00012541832,"about_ca_system_score_gemma":0.00020898238,"threshold_uncertainty_score":0.9999232},"labels":[],"label_agreement":null},{"id":"W2949443561","doi":"","title":"Evaluating File System Reliability on Solid State Drives.","year":2019,"lang":"en","type":"article","venue":"USENIX Annual Technical Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Reliability (semiconductor); Reliability engineering; Computer science; Engineering","score_opus":0.03700856751728223,"score_gpt":0.33016894527046337,"score_spread":0.29316037775318116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949443561","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":[0.20747356,0.000040752504,0.76634157,0.0011338997,0.00074935635,0.001829705,0.0014324861,0.010078454,0.010920224],"genre_scores_gemma":[0.86611944,0.0000056537424,0.13315718,0.00011963466,0.000018143091,0.000082404404,0.000025716956,0.000017847511,0.0004540049],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99674207,0.00014854126,0.00054564985,0.00120716,0.00073991384,0.0006166581],"domain_scores_gemma":[0.9957469,0.00072586053,0.00024931453,0.0027503758,0.0003933229,0.00013421781],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006817701,0.0003278191,0.0004578562,0.00014520502,0.00013719304,0.00016103957,0.002731212,0.0002113478,0.00019203531],"category_scores_gemma":[0.0014017483,0.00028439466,0.00009625806,0.00055199413,0.00022604274,0.0009820438,0.0016766426,0.0007135748,0.0011599967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016380315,0.0005479037,0.00087984366,0.00039759235,0.0000477629,0.00018983537,0.0010517495,0.0067582373,0.034364067,0.66316265,0.02035843,0.27207813],"study_design_scores_gemma":[0.0039845947,0.010492753,0.022417067,0.002721698,0.000056232628,0.0003002407,0.0019741212,0.67684484,0.078877315,0.13666102,0.05992357,0.0057465276],"about_ca_topic_score_codex":0.00002060939,"about_ca_topic_score_gemma":0.000007119401,"teacher_disagreement_score":0.6700866,"about_ca_system_score_codex":0.00025647183,"about_ca_system_score_gemma":0.0001806048,"threshold_uncertainty_score":0.99996084},"labels":[],"label_agreement":null},{"id":"W2949469701","doi":"10.48550/arxiv.1701.06687","title":"On the Average Locality of Locally Repairable Codes","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Locality; Upper and lower bounds; Distributed data store; Combinatorics; Code (set theory); Mathematics; Discrete mathematics; Dimension (graph theory); Minimum distance; Computer science; Algorithm; Distributed computing","score_opus":0.08068098796490022,"score_gpt":0.20624315531429632,"score_spread":0.1255621673493961,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949469701","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":[0.05919197,0.0000496682,0.9341519,0.0003112605,0.00029256268,0.00029951934,0.00006402014,0.0005456421,0.005093476],"genre_scores_gemma":[0.99484086,0.00015950108,0.0039604614,0.00009624098,0.000014394533,0.0000012229524,0.000007923476,0.0000120452005,0.0009073714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998113,0.00013869542,0.00021634442,0.0010671478,0.00014775734,0.00031706062],"domain_scores_gemma":[0.9929573,0.00038042598,0.00059905613,0.0058232597,0.00017757625,0.000062409075],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005135317,0.00030142695,0.00039630156,0.00014792236,0.00030741637,0.00010277986,0.0066151423,0.00030762205,0.000018562794],"category_scores_gemma":[0.00051899673,0.00025536545,0.00019093438,0.00025684948,0.0006792508,0.00041718967,0.00595234,0.00082163577,0.000059666476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024830115,0.00006933032,0.00022042728,0.0000512323,0.00005546739,0.00023345099,0.000045511777,0.15103471,0.00002178392,0.8462538,0.0010539271,0.00093551277],"study_design_scores_gemma":[0.0002299043,0.00009516099,0.00027400663,0.00020112243,0.000025428222,0.0000029758844,0.000045416393,0.27554348,0.0019053323,0.7203289,0.00096457364,0.00038365848],"about_ca_topic_score_codex":0.00019802399,"about_ca_topic_score_gemma":0.00005107162,"teacher_disagreement_score":0.93564886,"about_ca_system_score_codex":0.00018518002,"about_ca_system_score_gemma":0.00019171121,"threshold_uncertainty_score":0.99998987},"labels":[],"label_agreement":null},{"id":"W2949519087","doi":"10.1017/9781009283403.008","title":"Locally Repairable Codes","year":2024,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Computer network","score_opus":0.020364341603938903,"score_gpt":0.20469275853682778,"score_spread":0.18432841693288887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949519087","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000020439861,0.0005214381,0.15844488,0.000050796873,0.00037301815,0.00025089332,0.00024373074,0.0027865851,0.83732665],"genre_scores_gemma":[0.000092810704,0.00019321211,0.016371911,0.0000654502,0.000053610507,9.726388e-7,0.000029659914,0.00004618746,0.9831462],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980018,0.000013830211,0.00020497036,0.0010612775,0.00034335098,0.0003747843],"domain_scores_gemma":[0.99748534,0.000079112324,0.00017232909,0.0020049477,0.00013720771,0.00012104179],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010293601,0.0004445287,0.00042433525,0.00033186903,0.00017003354,0.00015801915,0.0027211776,0.00046255082,0.0000018843042],"category_scores_gemma":[0.000017660315,0.00050701434,0.00020551549,0.000025670068,0.0003910843,0.00038863093,0.003389995,0.00078640395,0.00014985297],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000087580365,0.0000035941162,7.093167e-8,0.00007708315,0.00008157477,0.0017877745,0.000013869789,0.000009301501,0.000028119939,0.9275259,0.066450864,0.004013122],"study_design_scores_gemma":[0.00014897448,0.000060529113,2.8675564e-7,0.00024691774,0.00007142983,0.000052651074,0.00001206644,0.0014832239,0.0005407034,0.0019736944,0.99487066,0.00053886545],"about_ca_topic_score_codex":0.00004600615,"about_ca_topic_score_gemma":0.0000026394832,"teacher_disagreement_score":0.92841977,"about_ca_system_score_codex":0.0003402602,"about_ca_system_score_gemma":0.00014369978,"threshold_uncertainty_score":0.99973816},"labels":[],"label_agreement":null},{"id":"W2950739896","doi":"10.48550/arxiv.1301.2497","title":"Update-Efficient Regenerating Codes with Minimum Per-Node Storage","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Node (physics); Overhead (engineering); Decoding methods; Generator matrix; Encoding (memory); Code (set theory); Algorithm; Diagonal; Scheme (mathematics); Distributed data store; Error detection and correction; Matrix (chemical analysis); Parity-check matrix; Mathematics; Distributed computing; Low-density parity-check code; Set (abstract data type); Engineering","score_opus":0.04407147171279695,"score_gpt":0.18580449497232285,"score_spread":0.14173302325952591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950739896","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":[0.34203175,0.00017846748,0.6555142,0.0001581117,0.00026318413,0.0003208176,0.0000431833,0.0010175372,0.00047276198],"genre_scores_gemma":[0.9019088,0.000110001456,0.09717662,0.00010548805,0.000046189543,0.0000053159033,0.00004787383,0.000035158875,0.0005645174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969001,0.00011610874,0.00025811032,0.0019043718,0.00019363985,0.0006276885],"domain_scores_gemma":[0.9958461,0.000102062346,0.00044789267,0.0031831267,0.00025389888,0.00016694146],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020191986,0.0005574536,0.00049950095,0.0003830846,0.00031912036,0.00029084377,0.0038653158,0.00037502436,0.00003570055],"category_scores_gemma":[0.00006279875,0.0005422509,0.00012359234,0.0006592241,0.0003676345,0.0006326156,0.00550811,0.0009257942,0.00024782598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000115282355,0.00007298147,0.00020986506,0.000044353375,0.000051863222,0.00034513624,0.00012562763,0.78522456,0.00013506608,0.2122473,0.0006850803,0.00084661983],"study_design_scores_gemma":[0.0004788165,0.00009356196,0.00014202073,0.0001614675,0.00005380306,0.00002182558,0.0002981278,0.9870877,0.0014134515,0.008205163,0.0010401687,0.0010038642],"about_ca_topic_score_codex":0.00010785365,"about_ca_topic_score_gemma":0.000039766164,"teacher_disagreement_score":0.5598771,"about_ca_system_score_codex":0.00039497373,"about_ca_system_score_gemma":0.00022156007,"threshold_uncertainty_score":0.99970293},"labels":[],"label_agreement":null},{"id":"W2950916997","doi":"10.48550/arxiv.1301.4620","title":"Update-Efficient Error-Correcting Product-Matrix Codes","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Science Council; McMaster University; Syracuse University; National Science Foundation","keywords":"Generator matrix; Computer science; Decoding methods; Overhead (engineering); Encoding (memory); Node (physics); Algorithm; Error detection and correction; Code (set theory); Parity-check matrix; List decoding; Matrix (chemical analysis); Concatenated error correction code; Theoretical computer science; Block code; Low-density parity-check code; Engineering","score_opus":0.05702923737308562,"score_gpt":0.21315728869472514,"score_spread":0.1561280513216395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950916997","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":[0.26971108,0.00023086382,0.72557175,0.00022229116,0.0012255731,0.00052054616,0.000029127214,0.0019647805,0.00052397395],"genre_scores_gemma":[0.96272224,0.00009904378,0.035942268,0.00004943079,0.000073602896,0.000004771168,0.000032801014,0.000031377032,0.0010444588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99653596,0.00011632373,0.0003132098,0.0021828995,0.00016898185,0.00068264146],"domain_scores_gemma":[0.99539727,0.00013054798,0.00051143725,0.003532947,0.00028036832,0.00014740358],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0003093816,0.0005292939,0.0005095493,0.0004971135,0.00029455064,0.0002449104,0.004849061,0.00033320556,0.000036987196],"category_scores_gemma":[0.0002740461,0.0005837016,0.00018215895,0.0010621247,0.0002871956,0.00072004367,0.009070998,0.0011716556,0.00065755093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011730922,0.0001437326,0.00065365847,0.00010958097,0.000078323,0.00038132104,0.0002266121,0.78552616,0.0001259759,0.20353407,0.002156213,0.007052629],"study_design_scores_gemma":[0.0003671705,0.00004897622,0.00023109521,0.00016274159,0.0000620336,0.000034616154,0.0003659041,0.92282206,0.003074055,0.06908422,0.0025059765,0.0012411603],"about_ca_topic_score_codex":0.00016693627,"about_ca_topic_score_gemma":0.00002229435,"teacher_disagreement_score":0.69301116,"about_ca_system_score_codex":0.00043838908,"about_ca_system_score_gemma":0.00020143158,"threshold_uncertainty_score":0.99966145},"labels":[],"label_agreement":null},{"id":"W2952935273","doi":"10.1109/cwit.2017.7994819","title":"On minimum distance of locally repairable codes","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Minimum distance; Mathematics; Statistics","score_opus":0.02643302035600622,"score_gpt":0.2844963611637052,"score_spread":0.258063340807699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952935273","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010352575,0.00031174519,0.9751989,0.0005938333,0.00053481007,0.00023643326,0.00007283683,0.0011248115,0.020891361],"genre_scores_gemma":[0.4597964,0.00015592152,0.53691286,0.000098006625,0.000020542762,0.00003892436,0.000017141285,0.000016413494,0.002943773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99807334,0.000025173757,0.0003500446,0.00090249215,0.00036995145,0.00027897],"domain_scores_gemma":[0.9930488,0.00016732841,0.0005720594,0.0060336315,0.00013474374,0.000043434462],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00024338797,0.0002756965,0.00046563262,0.00012501163,0.000102009704,0.00013877272,0.0056928205,0.00027827188,0.000011068247],"category_scores_gemma":[0.0006599135,0.00023722902,0.00010858364,0.000079879144,0.0003288396,0.00033389876,0.0054467623,0.000492973,0.00003844171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020348252,0.00011128786,0.00006158213,0.00019911336,0.000039004703,0.00007058516,0.0000671686,0.0024421727,0.000191617,0.94390327,0.017129341,0.035764504],"study_design_scores_gemma":[0.0002645255,0.00022219468,0.00015424949,0.00068604294,0.000010259737,0.0000056347712,0.000025013227,0.04463602,0.019689491,0.9228398,0.010786655,0.0006800882],"about_ca_topic_score_codex":0.0000559282,"about_ca_topic_score_gemma":0.000049889724,"teacher_disagreement_score":0.45876116,"about_ca_system_score_codex":0.00008298813,"about_ca_system_score_gemma":0.00014897683,"threshold_uncertainty_score":0.99968684},"labels":[],"label_agreement":null},{"id":"W2953243231","doi":"10.1109/tit.2019.2924888","title":"Universal and Dynamic Locally Repairable Codes With Maximal Recoverability via Sum-Rank Codes","year":2019,"lang":"en","type":"preprint","venue":"IEEE Transactions on Information Theory","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natur og Univers, Det Frie Forskningsråd","keywords":"Locality; Erasure code; Erasure; Mathematics; Discrete mathematics; Code (set theory); Disjoint sets; Bounded function; Computer science; Combinatorics; Algorithm; Decoding methods","score_opus":0.007122627266543371,"score_gpt":0.21609901505059081,"score_spread":0.20897638778404745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953243231","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":[0.007620523,0.000040536204,0.98843074,0.00022345118,0.0005685908,0.0006968538,0.000409018,0.0012517828,0.0007584975],"genre_scores_gemma":[0.9047162,0.00022533949,0.09450909,0.00021441207,0.000005215856,0.00007810996,0.000071528324,0.000018950665,0.00016117211],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99814594,0.00014697784,0.0004958783,0.00051820464,0.0003746032,0.00031840685],"domain_scores_gemma":[0.9973179,0.00034806816,0.0003766966,0.0016636469,0.00021820911,0.000075473225],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006621834,0.0003950515,0.0004011319,0.00046160445,0.00026731694,0.0002627137,0.0010033157,0.00037664862,0.000029356393],"category_scores_gemma":[0.00002434219,0.00036078945,0.00009713053,0.00030057377,0.00038474164,0.0037147426,0.000058418045,0.0010080966,0.00009004786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009528701,0.00017188274,0.00003339536,0.0007161085,0.00026616143,0.000010480062,0.0019005113,0.6405558,0.00007219115,0.024087556,0.000095557276,0.3311375],"study_design_scores_gemma":[0.002177958,0.00087962387,0.00048354012,0.0006317421,0.00014794974,0.00016206923,0.0015091401,0.8363764,0.006159401,0.14810553,0.0015596683,0.0018069491],"about_ca_topic_score_codex":0.00004460203,"about_ca_topic_score_gemma":0.000042827283,"teacher_disagreement_score":0.8970957,"about_ca_system_score_codex":0.00041673184,"about_ca_system_score_gemma":0.0002575408,"threshold_uncertainty_score":0.9998844},"labels":[],"label_agreement":null},{"id":"W2960945709","doi":"10.48550/arxiv.1708.03402","title":"Product Matrix MSR Codes with Bandwidth Adaptive Exact Repair","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Distributed data store; Coding (social sciences); Robustness (evolution); Distributed computing; Linear network coding; Computer network; Redundancy (engineering); Mathematics; Operating system","score_opus":0.06691934547296206,"score_gpt":0.21247178254983887,"score_spread":0.14555243707687682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2960945709","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":[0.04224779,0.000315607,0.95008236,0.0001835544,0.00041962508,0.0006959139,0.000092709,0.0031820943,0.0027803313],"genre_scores_gemma":[0.9178389,0.00027624972,0.0788705,0.000020843478,0.00006497992,0.0000037283173,0.000023439548,0.000031629435,0.002869746],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967203,0.000098736724,0.0001982999,0.0022614344,0.00017452826,0.0005466631],"domain_scores_gemma":[0.9931082,0.00010551429,0.0006286286,0.005755374,0.0002662323,0.00013601745],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027182116,0.00054586394,0.0005728333,0.0003517996,0.00041849923,0.00020641957,0.0051757423,0.00029335837,0.000010417409],"category_scores_gemma":[0.00016538982,0.0005228573,0.00019064202,0.0004210134,0.0005901036,0.0014230658,0.005876012,0.000982628,0.000087903965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046401063,0.00036458328,0.008055121,0.00032342089,0.0008319487,0.008207108,0.00047249845,0.20403673,0.0000918631,0.7646687,0.005588029,0.0068959626],"study_design_scores_gemma":[0.0032490566,0.0014265351,0.0075675193,0.0014512908,0.0006101982,0.00021564492,0.00062770024,0.5557969,0.0045769606,0.39973754,0.018959893,0.0057807523],"about_ca_topic_score_codex":0.00019214243,"about_ca_topic_score_gemma":0.00011627203,"teacher_disagreement_score":0.8755911,"about_ca_system_score_codex":0.0003507988,"about_ca_system_score_gemma":0.00036639636,"threshold_uncertainty_score":0.9997223},"labels":[],"label_agreement":null},{"id":"W2966040088","doi":"10.48550/arxiv.1908.01860","title":"Toward Efficient In-memory Data Analytics on NUMA Systems","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Analytics; Data analysis; Data science; Data mining","score_opus":0.16986908773715376,"score_gpt":0.22244913603065208,"score_spread":0.05258004829349833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966040088","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":[0.075136974,0.00017773989,0.9188643,0.0001026242,0.0016914881,0.00059260376,0.0002098952,0.00072320417,0.0025011739],"genre_scores_gemma":[0.9965813,0.00015146924,0.002490832,0.000045381876,0.000038,9.018363e-7,0.0001052938,0.00002145914,0.0005653469],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967598,0.00010695128,0.00029266762,0.0021632484,0.00019375952,0.0004836127],"domain_scores_gemma":[0.99141556,0.00020448072,0.00034987097,0.007844489,0.000092473296,0.00009310352],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.00038799914,0.00040368445,0.000524259,0.00070079346,0.000064665335,0.00015577427,0.009558593,0.00040702624,0.000004541484],"category_scores_gemma":[0.00015829377,0.00044959126,0.0000865048,0.0009813493,0.00014637996,0.0004467992,0.015011047,0.0010402747,0.00034620534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012254548,0.000087800196,0.0003194466,0.00010299053,0.000031266827,0.0007134221,0.00005462346,0.89499974,0.0000033783524,0.102691986,0.0005055164,0.00047756347],"study_design_scores_gemma":[0.00037274839,0.000050113256,0.00022465983,0.00023321094,0.0000241841,0.000005835727,0.00022383308,0.99327964,0.000033444063,0.004275432,0.0007844438,0.0004924492],"about_ca_topic_score_codex":0.00015457341,"about_ca_topic_score_gemma":0.000018445422,"teacher_disagreement_score":0.92144436,"about_ca_system_score_codex":0.00062138273,"about_ca_system_score_gemma":0.00023452907,"threshold_uncertainty_score":0.99979556},"labels":[],"label_agreement":null},{"id":"W2967739628","doi":"10.1145/3343737.3343751","title":"RocketStreams","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Server; Scalability; Computer science; Encryption; The Internet; Video on demand; Multimedia; Content delivery; Video streaming; Content distribution; Internet traffic; Computer network; World Wide Web; Database","score_opus":0.008580620748366605,"score_gpt":0.22792459311809496,"score_spread":0.21934397236972836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967739628","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":[0.017085217,0.0000213604,0.93971103,0.0005425206,0.00014560718,0.00005492716,4.3296254e-7,0.0012410434,0.04119784],"genre_scores_gemma":[0.7018215,0.000003432026,0.29522964,0.00019482721,0.000004290269,0.0000023323785,6.4666466e-7,0.0000021608937,0.0027411485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999589,0.000002889355,0.00004710906,0.0001742429,0.00007553204,0.00011118046],"domain_scores_gemma":[0.99921954,0.000019936848,0.000014885534,0.0007202821,0.000010843898,0.000014540318],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000025721682,0.000042913205,0.000046971272,0.000034430584,0.000013192648,0.000027352638,0.0008062226,0.000022776394,0.0000706979],"category_scores_gemma":[0.0000143428215,0.00003374842,0.000012138661,0.00015532102,0.000010118252,0.00051719695,0.0004089887,0.00004404799,0.0021074964],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.6109892e-7,0.00001236739,0.0013849015,0.0000023137572,0.0000026568962,0.0000064165365,0.000024828349,0.00003934277,0.002026435,0.72944367,0.0038396332,0.26321697],"study_design_scores_gemma":[0.000894879,0.00033769233,0.0043882616,0.000019231666,0.0000024414096,0.000082014696,0.00025365173,0.06323049,0.1990534,0.35875565,0.3720349,0.00094736106],"about_ca_topic_score_codex":0.000003147339,"about_ca_topic_score_gemma":0.0000010841352,"teacher_disagreement_score":0.6847363,"about_ca_system_score_codex":0.000011880508,"about_ca_system_score_gemma":0.000007326868,"threshold_uncertainty_score":0.9986695},"labels":[],"label_agreement":null},{"id":"W2970881973","doi":"","title":"ROADM Subsystems & Technologies","year":2005,"lang":"en","type":"article","venue":"Optical Fiber Communication Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"JDSU (Canada)","funders":"","keywords":"Key (lock); Variety (cybernetics); Computer science; Systems engineering; Computer architecture; Embedded system; Engineering; Computer security","score_opus":0.03274564048209333,"score_gpt":0.27519337029384633,"score_spread":0.242447729811753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970881973","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":[0.0026889725,0.001547626,0.9111382,0.03201543,0.00006355334,0.00031043324,0.0000062923295,0.0048653996,0.047364112],"genre_scores_gemma":[0.5952266,0.00020536553,0.40398905,0.00005790704,0.0000069358452,0.00005247749,0.0000071418785,0.0000062889767,0.0004482383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985902,0.00006449993,0.00034281943,0.00040819647,0.00026295416,0.00033134664],"domain_scores_gemma":[0.9955757,0.00027966013,0.00012257922,0.0037681896,0.00020083104,0.000053039716],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00024790686,0.00018484484,0.00021570644,0.00012381503,0.00019988406,0.00024953534,0.00482193,0.00018029334,0.00006019773],"category_scores_gemma":[0.00039519096,0.00017093089,0.000044252218,0.00046600617,0.0003969711,0.0012694887,0.0022010321,0.00043453605,0.0011062605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013157955,0.00003246232,0.000025058742,0.000003377965,0.000005111478,0.0000011921551,0.00006051099,0.000027391407,0.00055024197,0.6288412,0.00046153154,0.3699906],"study_design_scores_gemma":[0.00082136056,0.000172572,0.00081048894,0.00020453439,0.00001911217,0.00011765999,0.00074191764,0.08361133,0.06977554,0.1309722,0.7114012,0.0013520842],"about_ca_topic_score_codex":0.000007542449,"about_ca_topic_score_gemma":0.000021723816,"teacher_disagreement_score":0.71093965,"about_ca_system_score_codex":0.000090997404,"about_ca_system_score_gemma":0.000060045437,"threshold_uncertainty_score":0.9996715},"labels":[],"label_agreement":null},{"id":"W2973236520","doi":"10.1051/epjconf/201921407021","title":"Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm","year":2019,"lang":"en","type":"article","venue":"EPJ Web of Conferences","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Cloud computing; Computer science; Atlas (anatomy); Provisioning; ATLAS experiment; Resource (disambiguation); Large Hadron Collider; Database; Operating system; Telecommunications; Computer network","score_opus":0.052493913626878316,"score_gpt":0.2971274705535999,"score_spread":0.24463355692672156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973236520","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":[0.4638952,0.0002632513,0.5282501,0.0017637748,0.000398255,0.00058421394,0.000021108332,0.00028898794,0.0045350753],"genre_scores_gemma":[0.9306003,0.000012188063,0.06906579,0.00013180594,0.00003902516,0.00001630541,0.0000032042844,0.000007952738,0.00012345913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879795,0.000028853961,0.00025998813,0.00036849492,0.00027901572,0.00026568555],"domain_scores_gemma":[0.99848354,0.00036922592,0.0002678349,0.000684614,0.00016921386,0.000025601612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029785262,0.00016573719,0.0002463156,0.00009312877,0.000112045556,0.00010993395,0.0015283793,0.00008119861,0.00002975254],"category_scores_gemma":[0.00022523732,0.0001066956,0.00005659494,0.00029538415,0.00017683094,0.00033760545,0.0003055461,0.00015712703,0.000018649393],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000297447,0.00006523899,0.0010042771,0.000076418546,0.000024401068,0.0000014973383,0.0002069106,0.00067278085,0.01624161,0.879327,0.0001964405,0.1021537],"study_design_scores_gemma":[0.0010303804,0.000789113,0.0007117782,0.0004781212,0.000027111884,0.000008896926,0.001030648,0.6600528,0.15524295,0.12491812,0.055001568,0.00070853846],"about_ca_topic_score_codex":0.000012630514,"about_ca_topic_score_gemma":0.000013303708,"teacher_disagreement_score":0.75440884,"about_ca_system_score_codex":0.000021410995,"about_ca_system_score_gemma":0.00048035508,"threshold_uncertainty_score":0.43509203},"labels":[],"label_agreement":null},{"id":"W2973453427","doi":"10.1109/tit.2019.2940975","title":"Locally Repairable Codes: Joint Sequential–Parallel Repair for Multiple Node Failures","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Hamming code; Hamming distance; Combinatorics; Discrete mathematics; Disjoint sets; Mathematics; Locality; Node (physics); Computer science; Linear code; Set (abstract data type); Algorithm; Block code; Decoding methods; Physics","score_opus":0.01562384479844742,"score_gpt":0.2370479118258966,"score_spread":0.22142406702744918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973453427","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":[0.00077026134,0.000016949303,0.9936296,0.00031135016,0.0007451927,0.00088609045,0.00012388207,0.0026692858,0.00084743],"genre_scores_gemma":[0.5442155,0.000026967246,0.45368153,0.00096288463,0.000014589748,0.00034494203,0.000033557066,0.000018472932,0.0007015329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849397,0.000058137157,0.00053568144,0.0002944396,0.0002822226,0.0003355561],"domain_scores_gemma":[0.9980207,0.00030851926,0.00022343696,0.0012008839,0.00018473675,0.00006172176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061109057,0.00021602731,0.0002270159,0.0003564381,0.00027101918,0.00013343449,0.00068619265,0.0001536839,0.00006499614],"category_scores_gemma":[0.0000705413,0.00020498072,0.00021324329,0.00031984292,0.000094249284,0.0043556252,0.000012237331,0.00025667678,0.0006574588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041719768,0.00018244749,0.000007765487,0.00027768046,0.00016864792,0.0000025436482,0.0021036633,0.6407745,0.0018658488,0.2745237,0.0040267166,0.0756493],"study_design_scores_gemma":[0.0030032124,0.0005906578,0.000023308196,0.00013337964,0.000037217247,0.000040274987,0.0014524746,0.80058575,0.07404513,0.047753554,0.07148048,0.0008545666],"about_ca_topic_score_codex":0.000018224368,"about_ca_topic_score_gemma":0.00001174571,"teacher_disagreement_score":0.5434452,"about_ca_system_score_codex":0.00015722169,"about_ca_system_score_gemma":0.00009233701,"threshold_uncertainty_score":0.8450522},"labels":[],"label_agreement":null},{"id":"W2975679388","doi":"10.1109/isit.2019.8849528","title":"Private Information Retrieval from Locally Repairable Databases with Colluding Servers","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Server; Code (set theory); Dimension (graph theory); Code rate; Field size; Private information retrieval; Computer science; Discrete mathematics; Locality; Combinatorics; Algorithm; Database; Theoretical computer science; Physics; Mathematics; Computer network; Decoding methods; Set (abstract data type); Computer security","score_opus":0.015094356989182848,"score_gpt":0.22702127899786614,"score_spread":0.2119269220086833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975679388","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16832232,0.000013869922,0.82814425,0.00021714896,0.000109720946,0.0002096568,0.000029618288,0.0012646007,0.0016888166],"genre_scores_gemma":[0.33695748,0.0000127322455,0.6623438,0.0003877519,0.0000072484754,0.0000034511042,0.00008720893,0.000005747991,0.0001945639],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990055,0.000012700394,0.00018789498,0.00027760217,0.0002981938,0.00021810246],"domain_scores_gemma":[0.99846077,0.00008714695,0.00012603101,0.0012201905,0.00006924622,0.00003663789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013742351,0.00011888233,0.00013170106,0.00009664917,0.0000675199,0.00012959991,0.0008744646,0.00003894287,0.000046049518],"category_scores_gemma":[0.00012073256,0.00009243008,0.000016188096,0.0005652903,0.000041140134,0.007247593,0.00070754124,0.00011958006,0.0003742164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005287814,0.00012297455,0.04022052,0.00015996234,0.0001900308,0.00010467006,0.0009401325,0.014003181,0.015374678,0.87431026,0.015233784,0.03881104],"study_design_scores_gemma":[0.0046857474,0.0012028727,0.0074498514,0.00047172207,0.00003236225,0.000059218997,0.0019587588,0.45681027,0.28571242,0.013146937,0.2263664,0.0021034605],"about_ca_topic_score_codex":0.00009490629,"about_ca_topic_score_gemma":0.00002034639,"teacher_disagreement_score":0.8611633,"about_ca_system_score_codex":0.00008010195,"about_ca_system_score_gemma":0.000060276496,"threshold_uncertainty_score":0.52543294},"labels":[],"label_agreement":null},{"id":"W2976619897","doi":"10.1109/isit.2019.8849609","title":"Locally Repairable Convolutional Codes with Sliding Window Repair","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Node (physics); Algorithm; Code (set theory); Artificial intelligence; Physics; Programming language","score_opus":0.010318898229181734,"score_gpt":0.21817692637140337,"score_spread":0.20785802814222165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976619897","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02037987,0.00010839526,0.9622181,0.00046516495,0.00012819418,0.00021700455,0.0000039582137,0.004331919,0.0121474005],"genre_scores_gemma":[0.47288972,0.00000531703,0.5244246,0.00025522968,0.000010546986,0.000010256027,0.0000038385556,0.0000074368127,0.0023930517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866074,0.000019461808,0.00016265604,0.000536405,0.0003055584,0.0003151785],"domain_scores_gemma":[0.9985257,0.000112358895,0.000073450276,0.0011432127,0.000099129735,0.000046168327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002064008,0.00014003809,0.00016717259,0.00009221034,0.00009360649,0.000060370596,0.0008534374,0.00006480746,0.000065010005],"category_scores_gemma":[0.00006683813,0.00010641679,0.000042917683,0.0003966195,0.00007902658,0.001195672,0.00048511164,0.00015107536,0.0003512456],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018167048,0.000038782728,0.011702518,0.000017611073,0.000031728134,0.000046933917,0.000040698527,0.0014897778,0.00195756,0.97851056,0.004185179,0.0019604703],"study_design_scores_gemma":[0.004497052,0.0027519644,0.020238217,0.00041830895,0.00003416926,0.0009354854,0.0011935722,0.67164254,0.060683228,0.08144943,0.15315051,0.0030055102],"about_ca_topic_score_codex":0.000023673854,"about_ca_topic_score_gemma":0.000017717628,"teacher_disagreement_score":0.89706117,"about_ca_system_score_codex":0.00008690897,"about_ca_system_score_gemma":0.00010237973,"threshold_uncertainty_score":0.45146686},"labels":[],"label_agreement":null},{"id":"W2980862352","doi":"10.1137/1.9781611976007.14","title":"RecSplit: Minimal Perfect Hashing via Recursive Splitting","year":2019,"lang":"en","type":"preprint","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec","funders":"","keywords":"Perfect hash function; Hash function; Computer science; Hash table; Key (lock); Data structure; Theoretical computer science; Dynamic perfect hashing; Function (biology); Algorithm; Discrete mathematics; Double hashing; Mathematics","score_opus":0.06309495751379852,"score_gpt":0.27191379418527634,"score_spread":0.20881883667147783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980862352","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01407605,0.00012844299,0.97603995,0.00029078065,0.00086085236,0.0031599752,0.0001697584,0.0009365023,0.00433771],"genre_scores_gemma":[0.025981974,0.000019703322,0.97209173,0.00012219591,0.00052531104,0.00054460845,0.000062138366,0.00007485058,0.00057748874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971645,0.0000134483735,0.00069385447,0.0011330001,0.0003713448,0.00062383496],"domain_scores_gemma":[0.99687165,0.00076685235,0.00081954594,0.0013491897,0.00009197354,0.00010080078],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010093487,0.00058065937,0.0008750846,0.00007202031,0.00037088402,0.00044465085,0.0016083256,0.0012737177,0.0000016705261],"category_scores_gemma":[0.00020506287,0.0005472758,0.00050199725,0.000089960704,0.00025541024,0.00012691239,0.0039088265,0.0015675826,0.000008105062],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050006955,0.00012813813,0.000003859286,0.0022357458,0.00059301854,0.0000036098534,0.013385924,0.00034841336,0.0047298,0.6769741,0.008056503,0.2934909],"study_design_scores_gemma":[0.002121843,0.0001982912,6.1609654e-7,0.0007936588,0.00022668231,0.00002030468,0.003092869,0.029555101,0.015067116,0.94102204,0.006434541,0.001466959],"about_ca_topic_score_codex":0.00000437049,"about_ca_topic_score_gemma":5.60305e-7,"teacher_disagreement_score":0.29202393,"about_ca_system_score_codex":0.00016838356,"about_ca_system_score_gemma":0.00021374307,"threshold_uncertainty_score":0.99969786},"labels":[],"label_agreement":null},{"id":"W2981413263","doi":"10.1145/3341301.3359640","title":"An analysis of performance evolution of Linux's core operations","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Linux kernel; Scalability; Operating system; Overhead (engineering); Multi-core processor; System call; Workload; Kernel (algebra); Context switch; Latency (audio); Simple (philosophy); Context (archaeology); Distributed computing; Telecommunications","score_opus":0.015136356101310373,"score_gpt":0.2684862619965635,"score_spread":0.25334990589525314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981413263","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":[0.46557382,0.000011812262,0.53406364,0.000013690242,0.000021875148,0.00003917567,0.0000060956136,0.00007436754,0.00019550738],"genre_scores_gemma":[0.81354076,0.0000069357266,0.18637241,0.000006698461,0.0000015943436,0.000001966553,0.000012477992,0.000001366957,0.000055769884],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944174,0.0000072322878,0.00016759783,0.00017401752,0.000130679,0.000078740995],"domain_scores_gemma":[0.9988316,0.0000181066,0.000056069508,0.00096352433,0.00011668648,0.0000140049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074081516,0.00004937386,0.00014997093,0.0002962835,0.000021812346,0.000008405076,0.0007050472,0.000035461842,0.000047254493],"category_scores_gemma":[0.00002047759,0.000041606752,0.00003393253,0.0012221884,0.000047191257,0.0009085985,0.00014176717,0.000040932617,0.000020653268],"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":[0.0000035437665,0.00008841726,0.08846876,0.000015205607,0.00008833719,2.7279415e-7,0.00019582528,0.28238517,0.053722892,0.56409216,0.000022324675,0.01091711],"study_design_scores_gemma":[0.00005819975,0.00012351756,0.028596357,0.0000034561388,0.000023303073,3.4358928e-7,0.000098531375,0.94877553,0.0219711,0.0002548679,0.000040363833,0.000054412987],"about_ca_topic_score_codex":0.000054512377,"about_ca_topic_score_gemma":0.00006848927,"teacher_disagreement_score":0.6663904,"about_ca_system_score_codex":0.000034120832,"about_ca_system_score_gemma":0.000030810803,"threshold_uncertainty_score":0.16966741},"labels":[],"label_agreement":null},{"id":"W2984179089","doi":"10.1145/3357526.3357548","title":"A unifying abstraction for data structure splicing","year":2019,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Memory Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Locality; Abstraction; Cache; Data structure; RNA splicing; Data space; Parallel computing; Space (punctuation); Cache coherence; Distributed computing; Theoretical computer science; CPU cache; Programming language; Cache algorithms; Operating system; Artificial intelligence","score_opus":0.02552026042809518,"score_gpt":0.2690551292417009,"score_spread":0.2435348688136057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984179089","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":[0.94530404,0.00008759192,0.028287565,0.0055196094,0.010064473,0.0020432945,0.0002841058,0.00053677545,0.007872554],"genre_scores_gemma":[0.99136543,0.0000047565354,0.007767236,0.00007432743,0.00014728137,0.000018846578,0.00001297369,0.000013118944,0.0005960461],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998584,0.0000032004978,0.0002989966,0.0004653985,0.00049382634,0.00015461128],"domain_scores_gemma":[0.99848664,0.00010423963,0.0004932143,0.0006228692,0.00027261628,0.000020403992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003302798,0.0001320426,0.00015960878,0.000091179165,0.000076195625,0.00018379767,0.0047118976,0.000075154094,0.0000025024144],"category_scores_gemma":[0.00016787219,0.00009722659,0.00004447203,0.00016339413,0.000029263121,0.0013438358,0.0010375183,0.00016593497,0.000008272305],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004626244,0.000036414473,0.0015544826,0.00028417257,0.00008088297,3.752711e-7,0.00018734414,0.0046870573,0.8579943,0.12990232,0.0027736188,0.0024527472],"study_design_scores_gemma":[0.0012029157,0.00022147427,0.0007679458,0.0010142598,0.000030439882,0.00015413095,0.0011441915,0.46241236,0.49690452,0.0077849887,0.027782882,0.0005798657],"about_ca_topic_score_codex":0.000041744985,"about_ca_topic_score_gemma":0.0000016713926,"teacher_disagreement_score":0.45772532,"about_ca_system_score_codex":0.00014203071,"about_ca_system_score_gemma":0.000020987294,"threshold_uncertainty_score":0.8755957},"labels":[],"label_agreement":null},{"id":"W2991477359","doi":"10.1016/j.sysarc.2019.101685","title":"Leveraging partial-refresh for performance and lifetime improvement of 3D NAND flash memory in cyber-physical systems","year":2019,"lang":"en","type":"article","venue":"Journal of Systems Architecture","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; National Science Foundation","keywords":"Computer science; Flash (photography); Cyber-physical system; NAND gate; Embedded system; Flash memory; Computer hardware; Operating system; Logic gate; Algorithm","score_opus":0.008455566641710318,"score_gpt":0.22637100011009353,"score_spread":0.2179154334683832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991477359","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":[0.89235216,0.0010699134,0.10505284,0.00012298854,0.0007194246,0.0005862272,0.000008886509,0.000032377266,0.00005517764],"genre_scores_gemma":[0.9910956,0.0000290127,0.008542115,0.000014904933,0.00016985208,0.000019293673,6.103849e-7,0.000014055715,0.000114567265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982968,0.000049750313,0.0006738985,0.0002718427,0.0004073119,0.00030038643],"domain_scores_gemma":[0.99836034,0.00020215451,0.000744578,0.0004883739,0.00013608196,0.00006847871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006588253,0.0001913754,0.00060662604,0.00030723927,0.00004587663,0.00007942888,0.00072828523,0.00008408,3.183432e-7],"category_scores_gemma":[0.000069466805,0.00014133788,0.000070709604,0.00022382408,0.00006222782,0.00044857978,0.0002676639,0.0003630968,0.0000017278562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004500527,0.00040477735,0.012613175,0.006173594,0.000392285,0.00011947704,0.011489084,0.4668753,0.28262156,0.0039913002,0.0013773611,0.213492],"study_design_scores_gemma":[0.01422225,0.009785167,0.008970157,0.010069202,0.00014528616,0.002747183,0.0037655346,0.83716536,0.0777867,0.0027014385,0.030403446,0.00223829],"about_ca_topic_score_codex":0.000021620044,"about_ca_topic_score_gemma":0.0000014979461,"teacher_disagreement_score":0.37029,"about_ca_system_score_codex":0.0000879,"about_ca_system_score_gemma":0.00007586858,"threshold_uncertainty_score":0.57635915},"labels":[],"label_agreement":null},{"id":"W2995733890","doi":"10.1109/iemcon.2019.8936243","title":"HMM Optimized Modeling of SSD Storage for I/O MapReduce Workloads","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Workload; Provisioning; Big data; Controller (irrigation); Distributed computing; Real-time computing; Operating system; Embedded system","score_opus":0.02389799030716712,"score_gpt":0.2630725343230122,"score_spread":0.2391745440158451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995733890","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015735304,0.0001601126,0.98096764,0.0002866262,0.0002647394,0.00040410497,0.000008606162,0.0006051356,0.0015677408],"genre_scores_gemma":[0.39762855,0.00001056738,0.6017493,0.00004398196,0.0000079050305,0.00002082928,0.0000025474908,0.000007444718,0.00052890566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989067,0.000011200713,0.00024386901,0.00040047773,0.00017046367,0.00026732593],"domain_scores_gemma":[0.99849564,0.00011624116,0.00009592393,0.0011624318,0.00009679058,0.00003298197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019252,0.00012918079,0.0002447377,0.0001215437,0.00003525589,0.000036168545,0.0014097561,0.00008309723,0.000022600081],"category_scores_gemma":[0.00008418357,0.000113293434,0.00007181543,0.00027539814,0.000033917215,0.0007584746,0.00056682125,0.000095867275,0.000034548324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046910394,0.000081715145,0.00002811314,0.000068232075,0.000033530603,0.0000028665688,0.00022124925,0.71823126,0.01271904,0.22695565,0.0008557433,0.040755667],"study_design_scores_gemma":[0.00055367337,0.000069399095,0.0000023797304,0.000021416854,0.0000030357944,0.0000019622714,0.000100990874,0.9756981,0.009586326,0.013400718,0.0004081834,0.0001537913],"about_ca_topic_score_codex":0.000008361843,"about_ca_topic_score_gemma":7.046054e-7,"teacher_disagreement_score":0.38189325,"about_ca_system_score_codex":0.0000378085,"about_ca_system_score_gemma":0.000039694234,"threshold_uncertainty_score":0.4619972},"labels":[],"label_agreement":null},{"id":"W3003540023","doi":"10.1007/978-3-030-39951-1_18","title":"Strongly Minimal MapReduce Algorithms: A TeraSort Case Study","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Load balancing (electrical power); Algorithm; Skew; Partition (number theory); Sorting algorithm; Parallel computing; Big data; Sorting; Multiplicative function; Parallel algorithm; Theoretical computer science; Mathematics; Data mining","score_opus":0.026719733449256978,"score_gpt":0.27465729748188533,"score_spread":0.24793756403262834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003540023","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00087143655,0.00032006946,0.9940054,0.0007100196,0.0014074616,0.0010372378,0.00002951672,0.0010158379,0.00060305104],"genre_scores_gemma":[0.2954292,0.0000095629675,0.70355505,0.00044521826,0.0003648235,0.00003246267,0.0000054675147,0.000051683382,0.00010652738],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9937756,0.000048646263,0.0007721748,0.003166146,0.0013172255,0.0009202035],"domain_scores_gemma":[0.99557143,0.0004373504,0.00040262475,0.0030903367,0.00022988945,0.00026838732],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00058371923,0.0009078509,0.00086276967,0.000974897,0.00036586192,0.00076379615,0.0068955054,0.00035990597,0.000015010382],"category_scores_gemma":[0.00022588689,0.00085936155,0.00014299076,0.0011113385,0.0010538157,0.0014327948,0.006172935,0.0016162527,0.0000751158],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008851709,0.00014438994,0.00009665542,0.00003291523,0.000037659083,0.037165675,0.0021816306,0.0075155688,0.00006213494,0.007376457,0.0000626652,0.9453154],"study_design_scores_gemma":[0.0018560486,0.0038695028,0.00012177751,0.00040870032,0.00007477043,0.0166381,0.00004938879,0.8038832,0.0017068643,0.16318817,0.0039706356,0.0042328546],"about_ca_topic_score_codex":0.000050360693,"about_ca_topic_score_gemma":0.00012214966,"teacher_disagreement_score":0.94108254,"about_ca_system_score_codex":0.00046159836,"about_ca_system_score_gemma":0.0006235447,"threshold_uncertainty_score":0.9993857},"labels":[],"label_agreement":null},{"id":"W3005884080","doi":"","title":"A Study of SSD Reliability in Large Scale Enterprise Storage Deployments.","year":2020,"lang":"en","type":"article","venue":"File and Storage Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Reliability (semiconductor); Computer science; Scale (ratio); Reliability engineering; Engineering","score_opus":0.0167311071800953,"score_gpt":0.2511494272811771,"score_spread":0.23441832010108182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005884080","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":[0.92573947,0.0006088299,0.06807437,0.0010052102,0.00007204073,0.0007493764,0.0002699699,0.0033729295,0.0001077876],"genre_scores_gemma":[0.97547585,0.000093860755,0.024175618,0.0000667503,0.000005307509,0.00013987336,0.000010564822,0.000015123328,0.000017033419],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9978436,0.00006465827,0.00047336027,0.0008741438,0.00030859877,0.00043562136],"domain_scores_gemma":[0.998177,0.0001437173,0.00020648513,0.0013671338,0.00005449237,0.00005115879],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002333392,0.00027532515,0.00050986116,0.00029411155,0.000096388605,0.000051206916,0.0017969463,0.0002064225,0.000024163215],"category_scores_gemma":[0.0009103766,0.00025170136,0.00004702737,0.001158327,0.00022631501,0.0007973265,0.0029190148,0.00049773045,0.000011935498],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057726644,0.013163387,0.39700973,0.0011135123,0.0002893894,0.0043711285,0.08222598,0.0022392233,0.008286596,0.014867605,0.048797116,0.42705905],"study_design_scores_gemma":[0.025224669,0.024625964,0.22838016,0.00097335037,0.00018090244,0.00015726908,0.40843686,0.13015465,0.05320827,0.057223238,0.06365854,0.007776109],"about_ca_topic_score_codex":0.00003467402,"about_ca_topic_score_gemma":0.000071961076,"teacher_disagreement_score":0.41928294,"about_ca_system_score_codex":0.000072425966,"about_ca_system_score_gemma":0.000029842417,"threshold_uncertainty_score":0.9999935},"labels":[],"label_agreement":null},{"id":"W3008714254","doi":"10.1109/bigdata47090.2019.9006560","title":"An Empirical Study of Rabin Fingerprinting Parameters","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Hash function; Byte; Hash table; Bloom filter; Search engine indexing; Theoretical computer science; Algorithm; Information retrieval","score_opus":0.03120561479000703,"score_gpt":0.3197460884567064,"score_spread":0.2885404736666993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008714254","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":[0.67574155,0.0000030088097,0.32335022,0.000057732796,0.00006271591,0.00013886404,2.2760322e-7,0.00034058758,0.00030508207],"genre_scores_gemma":[0.7641181,3.1986988e-7,0.2357954,0.000049447517,0.0000017553886,0.0000038996086,2.6649667e-7,0.0000031862287,0.000027640428],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991177,0.000034996516,0.00017377538,0.00034181937,0.00017484376,0.00015686781],"domain_scores_gemma":[0.9985395,0.00010036229,0.000073171774,0.0012320868,0.00002937106,0.000025483872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000171977,0.00007776264,0.00014579225,0.00009442967,0.0000227477,0.000033509747,0.0012291756,0.000034248063,0.000011105985],"category_scores_gemma":[0.00007440654,0.00006404839,0.00001858705,0.0003127338,0.00002686756,0.0006194117,0.0005283905,0.000099908495,0.00004495711],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017169286,0.0019281097,0.6881778,0.000026970112,0.000049415507,0.000036373516,0.005157086,0.0071463916,0.017249882,0.019773873,0.0004378419,0.25999907],"study_design_scores_gemma":[0.0046131876,0.010906838,0.2760317,0.00006659453,0.00002718453,0.00003874289,0.024489796,0.51477873,0.13460702,0.030837798,0.0015716804,0.002030732],"about_ca_topic_score_codex":0.0000299371,"about_ca_topic_score_gemma":0.000008503893,"teacher_disagreement_score":0.5076324,"about_ca_system_score_codex":0.000016264383,"about_ca_system_score_gemma":0.000012057705,"threshold_uncertainty_score":0.26118174},"labels":[],"label_agreement":null},{"id":"W3010697107","doi":"10.1145/1071690.1064230","title":"Empirical evaluation of multi-level buffer cache collaboration for storage systems","year":2005,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Cache; False sharing; Transparency (behavior); Distributed computing; Server; Hierarchy; Interface (matter); Software; Operating system; Memory hierarchy; IBM; File server; Cache algorithms; CPU cache; Database","score_opus":0.29996966189274565,"score_gpt":0.4431986743173009,"score_spread":0.14322901242455527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010697107","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":[0.027297914,0.15338525,0.81008166,0.0020303095,0.0006955364,0.006096478,0.00007529087,0.0002530503,0.00008452906],"genre_scores_gemma":[0.6652062,0.023597306,0.3081642,0.00047853318,0.00012399405,0.0021023457,0.00022773475,0.000029777679,0.00006993979],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952191,0.00045345628,0.0010449106,0.00061834,0.0023392073,0.00032494898],"domain_scores_gemma":[0.9918033,0.0005712194,0.0008825729,0.0019726027,0.004702859,0.00006747531],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.012592414,0.00026555374,0.0005257289,0.0006001907,0.00017593871,0.00008712284,0.0015849199,0.00016298881,0.000030822153],"category_scores_gemma":[0.018624207,0.00023877292,0.00009591107,0.0040501193,0.000061508326,0.0022015637,0.000330925,0.00017819187,0.000056890218],"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":[0.0000054853485,0.00013434926,0.00035945376,0.000998018,0.000029271738,1.1338745e-7,0.00016301335,0.041589182,0.00015815055,0.0005736613,0.006575663,0.94941366],"study_design_scores_gemma":[0.0012153316,0.00015723777,0.0026213098,0.00058484974,0.00023805934,0.000004845602,0.000042260577,0.9763716,0.0009918787,0.00014079327,0.017340483,0.00029136965],"about_ca_topic_score_codex":0.0000019521103,"about_ca_topic_score_gemma":0.0000047535295,"teacher_disagreement_score":0.94912225,"about_ca_system_score_codex":0.0008759154,"about_ca_system_score_gemma":0.0007121305,"threshold_uncertainty_score":0.9896423},"labels":[],"label_agreement":null},{"id":"W3011013547","doi":"10.1109/ccwc47524.2020.9031232","title":"AIOPS Prediction for Hard Drive Failures Based on Stacking Ensemble Model","year":2020,"lang":"en","type":"article","venue":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kensington Health","funders":"","keywords":"Computer science; Stacking; Feature extraction; Artificial intelligence; Process (computing); Ensemble forecasting; Ensemble learning; Data mining; Machine learning; Raw data; Filter (signal processing); Feature (linguistics); Pattern recognition (psychology); Computer vision","score_opus":0.04081647050436263,"score_gpt":0.2763858449968022,"score_spread":0.23556937449243956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011013547","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":[0.010022564,0.00033890572,0.97440946,0.013990262,0.00004074884,0.00030330513,0.00006710529,0.00059723883,0.00023038039],"genre_scores_gemma":[0.80899805,0.0001583136,0.1894603,0.0012425829,0.000028087257,0.000022955732,0.000056800192,0.000011116638,0.000021758357],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855083,0.00009531485,0.00029739083,0.0005757451,0.00019537154,0.00028536178],"domain_scores_gemma":[0.99819565,0.00045797153,0.0001864884,0.00079292804,0.00022825226,0.00013869628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002198223,0.00022678528,0.0002557898,0.00007028859,0.00056478643,0.0003285408,0.0009912065,0.00012671319,0.0000016074412],"category_scores_gemma":[0.00030095276,0.00022515451,0.000042116324,0.00028855665,0.0001515156,0.0005252764,0.0007505841,0.00039197662,0.0000026782413],"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":[0.00018004431,0.000116158255,0.0006562785,0.00012589704,0.000049847593,0.000004235624,0.009103418,0.093068615,0.0006792133,0.21243633,0.0063815857,0.6771984],"study_design_scores_gemma":[0.0004913519,0.00018721397,0.0001704082,0.00012313611,0.000011634664,0.0000023083771,0.0020439303,0.9885515,0.00022551624,0.006096951,0.0018683062,0.00022776534],"about_ca_topic_score_codex":0.000008105432,"about_ca_topic_score_gemma":0.000009938811,"teacher_disagreement_score":0.89548284,"about_ca_system_score_codex":0.000023414997,"about_ca_system_score_gemma":0.00007965844,"threshold_uncertainty_score":0.9181534},"labels":[],"label_agreement":null},{"id":"W3012520832","doi":"10.1109/aiccsa47632.2019.9035253","title":"SSD: Cache or Tier an Evaluation of SSD Cost and Efficiency using MapReduce","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Cache; Workload; Workflow; Software deployment; Latency (audio); Operating system; Task (project management); Parallel computing; Process (computing); Distributed computing; Database","score_opus":0.09253385277820253,"score_gpt":0.35247090112575974,"score_spread":0.2599370483475572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012520832","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":[0.60104245,0.00006646308,0.39777192,0.00004257711,0.000097102515,0.00027437898,0.0000025367015,0.00012657508,0.00057597714],"genre_scores_gemma":[0.8546969,0.0000036276854,0.14515795,0.000028308707,0.0000056838753,0.0000045431375,0.0000019760225,0.0000043072514,0.000096692376],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989632,0.000045661793,0.00014600436,0.00032654073,0.00035824298,0.00016034716],"domain_scores_gemma":[0.9989354,0.000048457234,0.00008428662,0.00076431746,0.00013711094,0.000030403355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000555191,0.00008555722,0.00011564264,0.000102858736,0.000041058902,0.000039610124,0.00054518145,0.0000546693,0.00006499925],"category_scores_gemma":[0.00014455098,0.00006434127,0.000010509345,0.0003261747,0.00007352325,0.0009840054,0.0003509417,0.0000658409,0.000013276997],"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":[0.000028199443,0.00023069803,0.0030985812,0.000057808236,0.000019633299,0.0000052151518,0.0012836955,0.01542592,0.101135984,0.05947287,0.00016547723,0.81907594],"study_design_scores_gemma":[0.00048553027,0.0001750571,0.0014472671,0.000019497907,0.00001347171,0.000022388453,0.00043215838,0.9600962,0.033018302,0.003958753,0.00015113837,0.00018025661],"about_ca_topic_score_codex":0.000032465192,"about_ca_topic_score_gemma":0.000009786204,"teacher_disagreement_score":0.94467026,"about_ca_system_score_codex":0.000063542844,"about_ca_system_score_gemma":0.00010471381,"threshold_uncertainty_score":0.2623761},"labels":[],"label_agreement":null},{"id":"W3012550338","doi":"10.14778/3389133.3389134","title":"Dash","year":2020,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":135,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Hash function; Scalability; Emulation; Hash table; Factor (programming language); Double hashing; Table (database)","score_opus":0.021384455536146138,"score_gpt":0.22421011762339768,"score_spread":0.20282566208725156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012550338","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":[0.25722143,0.001645049,0.3888936,0.26322767,0.0016848856,0.0034011577,0.000055809964,0.006458937,0.07741145],"genre_scores_gemma":[0.92402464,0.000021269649,0.07505194,0.0007989347,0.000027453438,0.000019137018,1.6031734e-7,0.000005905706,0.0000505319],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99916226,0.0000015138392,0.00015379219,0.00025300193,0.00026258788,0.00016682479],"domain_scores_gemma":[0.99952847,0.000014356758,0.0001436229,0.00020397823,0.00006704888,0.000042511725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007203795,0.0000934175,0.00011556132,0.000026441305,0.000056751618,0.000041245286,0.0023199013,0.000027529288,0.000004226365],"category_scores_gemma":[0.00020508877,0.00006256819,0.0000497191,0.00042252173,0.00007289151,0.00043965803,0.0017972084,0.00011530189,0.000018790372],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009833822,0.00005757588,0.0015006555,0.00009057555,0.00002969021,0.0000015097414,0.0012782875,0.00003327442,0.17655663,0.7617239,0.022596227,0.036121838],"study_design_scores_gemma":[0.0003344827,0.00013594607,0.00051428966,0.00003400526,0.000008792299,0.000008631237,0.00023818138,0.0024467586,0.91997427,0.042872075,0.03324641,0.00018616366],"about_ca_topic_score_codex":0.0000026108858,"about_ca_topic_score_gemma":1.1646844e-7,"teacher_disagreement_score":0.7434176,"about_ca_system_score_codex":0.000030033836,"about_ca_system_score_gemma":0.00001177812,"threshold_uncertainty_score":0.43109924},"labels":[],"label_agreement":null},{"id":"W3017302221","doi":"10.1109/hpca47549.2020.00055","title":"Griffin: Hardware-Software Support for Efficient Page Migration in Multi-GPU Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; CUDA; Parallel computing; Scalability; General-purpose computing on graphics processing units; Demand paging; Programmer; Cache; GPU cluster; Operating system; Memory management; Graphics; Virtual memory; Overlay","score_opus":0.04441728940581071,"score_gpt":0.2718763423651543,"score_spread":0.22745905295934357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017302221","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041506602,0.00010055251,0.99173045,0.0015943123,0.0002590438,0.00069697015,0.000047549995,0.0013868571,0.000033574273],"genre_scores_gemma":[0.44478312,0.000008571826,0.55430377,0.00045568048,0.000025395413,0.00018278894,0.00004575973,0.000013893008,0.00018104071],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986288,0.000020961463,0.00030918792,0.0005445143,0.00019550713,0.00030104382],"domain_scores_gemma":[0.99910325,0.000111449284,0.000092946,0.000548941,0.00007242565,0.00007100032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015361836,0.00015474469,0.00020770486,0.00010398738,0.00006087284,0.00011306227,0.0009740482,0.00009000797,0.000005190651],"category_scores_gemma":[0.00052178366,0.00013590623,0.000046471036,0.00047279676,0.00003215012,0.00041574502,0.0003807253,0.0001200088,0.00006295224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019042409,0.0014622628,0.018928338,0.0017685507,0.00010870221,0.00074269355,0.0114580095,0.35515898,0.028616386,0.29994,0.12179073,0.1598349],"study_design_scores_gemma":[0.0008510867,0.00021373929,0.00054921105,0.000024184741,0.0000032331766,0.000007297365,0.0003631224,0.96620405,0.0055578146,0.00012233794,0.025774486,0.00032946712],"about_ca_topic_score_codex":0.000035432437,"about_ca_topic_score_gemma":0.000054931686,"teacher_disagreement_score":0.611045,"about_ca_system_score_codex":0.00007528337,"about_ca_system_score_gemma":0.00004661814,"threshold_uncertainty_score":0.55420953},"labels":[],"label_agreement":null},{"id":"W3021440659","doi":"10.1109/tcad.2020.2990896","title":"SmartHeating: On the Performance and Lifetime Improvement of Self-Healing SSDs","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Hubei Province; National Natural Science Foundation of China","keywords":"Flash memory; Flash (photography); Computer science; Reliability (semiconductor); Overhead (engineering); Flash file system; Embedded system; Computer hardware; NAND gate; Dwell time; Reliability engineering; Logic gate; Computer memory; Operating system; Semiconductor memory; Algorithm; Engineering; Power (physics)","score_opus":0.033827821453744855,"score_gpt":0.2232374552513742,"score_spread":0.18940963379762935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021440659","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":[0.06750853,0.00012082507,0.9308894,0.00028799247,0.0002876785,0.0005808065,0.000026038837,0.00027200286,0.000026679554],"genre_scores_gemma":[0.98740023,0.000149167,0.012202479,0.00016326268,0.00002300767,0.00003926982,9.2876877e-7,0.000014462291,0.0000072133485],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99831766,0.00013256258,0.0005671511,0.0004552859,0.00029876077,0.00022858843],"domain_scores_gemma":[0.99846494,0.00049504166,0.0002781503,0.00050970237,0.00016285614,0.000089302586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041537127,0.00025246196,0.00040810867,0.00015595123,0.00019044819,0.00009426153,0.0005824332,0.000105630155,0.0000017722708],"category_scores_gemma":[0.000014185664,0.00017361912,0.000049758375,0.00049135706,0.000115628136,0.0002587263,0.000011364408,0.00033553687,0.0000026333694],"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":[0.00008939232,0.00043598018,0.000048568105,0.00075772766,0.00042327153,0.000016349424,0.004334572,0.3051485,0.1025187,0.010100818,0.00038419696,0.5757419],"study_design_scores_gemma":[0.000390892,0.0024222934,0.00001690372,0.00033661368,0.000018764462,0.000019821095,0.00026504407,0.90881765,0.0873766,0.000054829346,0.00009210862,0.00018844985],"about_ca_topic_score_codex":0.000043499644,"about_ca_topic_score_gemma":6.028458e-7,"teacher_disagreement_score":0.91989166,"about_ca_system_score_codex":0.00004338133,"about_ca_system_score_gemma":0.00007271244,"threshold_uncertainty_score":0.7079982},"labels":[],"label_agreement":null},{"id":"W3024552950","doi":"10.1002/er.5355","title":"A novel method for a new electromagnetic‐induced ammonia synthesizer","year":2020,"lang":"en","type":"article","venue":"International Journal of Energy Research","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ammonia; Electronic engineering; Electrical engineering; Nuclear engineering; Materials science; Physics; Chemistry; Computer science; Engineering; Process engineering","score_opus":0.12712130384011258,"score_gpt":0.4190865650869689,"score_spread":0.2919652612468563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3024552950","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012390172,0.00017323242,0.9632707,0.034744255,0.00022281826,0.00005533863,0.0000056369427,0.000048884376,0.0002400677],"genre_scores_gemma":[0.09604525,0.000055036176,0.9025356,0.0005603606,0.000564264,0.000010048284,0.0000013489758,0.0000142273075,0.0002138374],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.997865,0.000081203565,0.00036004686,0.00026427762,0.0011112817,0.00031819692],"domain_scores_gemma":[0.997177,0.0009358787,0.00019383249,0.00025230108,0.0012555397,0.0001854152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078270276,0.00010369222,0.00018965201,0.0003928873,0.000056791534,0.00019875003,0.0036197177,0.0000717826,0.000015810489],"category_scores_gemma":[0.0029913282,0.00008926428,0.00011153877,0.00045892497,0.000043520722,0.00060916273,0.00059802586,0.00038457592,0.0000059770955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000200846,0.00006916485,0.0000034617233,0.0000030234407,0.00011937615,0.00010066939,0.000117625874,0.00020141879,0.5609768,0.20553552,0.0074808816,0.22519122],"study_design_scores_gemma":[0.0032203714,0.0032526697,0.00015253875,0.00009822283,0.000014798229,0.0010845735,0.00011391058,0.07807544,0.531982,0.12977897,0.2518228,0.00040366646],"about_ca_topic_score_codex":0.00006775814,"about_ca_topic_score_gemma":0.00001350589,"teacher_disagreement_score":0.24434192,"about_ca_system_score_codex":0.0001346298,"about_ca_system_score_gemma":0.00046185753,"threshold_uncertainty_score":0.6726396},"labels":[],"label_agreement":null},{"id":"W3029537863","doi":"","title":"A new key management scheme for distributed encrypted storage systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Encryption; Computer science; Key management; Scheme (mathematics); Computer security; Mathematics","score_opus":0.027138661840310788,"score_gpt":0.2780650280407431,"score_spread":0.25092636620043235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029537863","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025450593,0.00010837123,0.9933475,0.0010489164,0.00054409204,0.00062784995,0.00005038763,0.0012860884,0.0027322588],"genre_scores_gemma":[0.10791762,0.000018309904,0.888231,0.00004446239,0.000049661103,0.000114563365,0.00003052382,0.000011985102,0.0035819227],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987127,0.000008669356,0.00019854898,0.00050172786,0.00021377215,0.00036457303],"domain_scores_gemma":[0.99685365,0.000041123483,0.00019586101,0.0027556936,0.0000635827,0.00009010298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015608867,0.00016803687,0.00019248763,0.00008173351,0.00041483867,0.0006505732,0.003460097,0.00007486642,0.0000072697744],"category_scores_gemma":[0.00015510755,0.00014629468,0.000050917904,0.00011601596,0.00005560662,0.0011864566,0.0015167383,0.00008329693,0.00006255626],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000062580675,0.000019501635,0.000055361194,0.000043032134,0.00003767522,0.000038304195,0.000019970754,0.00011604341,0.00023857963,0.9258548,0.04431278,0.02925769],"study_design_scores_gemma":[0.0031070604,0.00023978318,0.0024195644,0.0001392789,0.000030083625,0.000027923537,0.0002866335,0.26616934,0.0034706837,0.05289844,0.6700979,0.001113297],"about_ca_topic_score_codex":0.00006192092,"about_ca_topic_score_gemma":0.000007933863,"teacher_disagreement_score":0.8729564,"about_ca_system_score_codex":0.00009354962,"about_ca_system_score_gemma":0.00002832576,"threshold_uncertainty_score":0.64297783},"labels":[],"label_agreement":null},{"id":"W3033256959","doi":"10.1145/3375553","title":"The Reliability of Modern File Systems in the face of SSD Errors","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Journaling file system; Computer science; File system; Reliability (semiconductor); Flash file system; Versioning file system; Device file; Self-certifying File System; Metadata; Computer file; File system fragmentation; Operating system; Unix file types; File Control Block; Database; Embedded system; Stub file","score_opus":0.031133439748733786,"score_gpt":0.26110855191712073,"score_spread":0.22997511216838695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033256959","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":[0.01763183,0.00025536196,0.97760427,0.0035913486,0.00012406426,0.00032279256,0.0002587154,0.00014018704,0.0000714051],"genre_scores_gemma":[0.98999304,0.00004111993,0.009802985,0.000068347974,0.000004726361,0.000059969414,0.0000025270022,0.0000062630497,0.00002104133],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879813,0.00012562826,0.0003149427,0.0002810153,0.00031342008,0.00016688232],"domain_scores_gemma":[0.99707484,0.0008566463,0.00013969018,0.0018517154,0.00005217462,0.000024911627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030964022,0.00011183859,0.00018293473,0.000051932904,0.00012200612,0.000024913415,0.002595556,0.000065257474,0.0000083017],"category_scores_gemma":[0.00032179203,0.000069506576,0.00006701848,0.00069800654,0.00019782019,0.00032183813,0.000048215752,0.00032454467,0.0000072546936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012901887,0.0005421211,0.00006609289,0.00024924663,0.000058697435,0.000031759566,0.020692468,0.7592319,0.004095293,0.008655036,0.0036667727,0.20258155],"study_design_scores_gemma":[0.0019199292,0.0018425249,0.0034202384,0.0002758421,0.00006871937,0.00003948601,0.024724754,0.8573473,0.02443558,0.037394922,0.047403373,0.0011273228],"about_ca_topic_score_codex":0.00007919383,"about_ca_topic_score_gemma":0.000027878163,"teacher_disagreement_score":0.9723612,"about_ca_system_score_codex":0.00004032087,"about_ca_system_score_gemma":0.000038426046,"threshold_uncertainty_score":0.4823232},"labels":[],"label_agreement":null},{"id":"W3035487791","doi":"10.1109/fccm48280.2020.00043","title":"SHIP: Storage for Hybrid Interconnected Processors","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Field-programmable gate array; Storage management; Protocol (science); Operating system; Computer data storage; Embedded system; Database","score_opus":0.03414571864543435,"score_gpt":0.26244705834101334,"score_spread":0.22830133969557898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035487791","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":[0.0052238246,0.000059494694,0.9835698,0.007710168,0.0000983484,0.0002810177,0.000016717067,0.0025751174,0.00046549144],"genre_scores_gemma":[0.64907146,0.00000293388,0.34920385,0.0015198857,0.00002911225,0.00005222936,0.000007813832,0.000009480683,0.0001032548],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990422,0.000009080425,0.00015062389,0.00044698032,0.000112981084,0.00023813307],"domain_scores_gemma":[0.999249,0.00009746722,0.00005810383,0.00044921003,0.00007229943,0.000073933115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060121503,0.000121582285,0.0001409934,0.00005040935,0.000060707203,0.000083151,0.0015320111,0.000032894193,0.000016467178],"category_scores_gemma":[0.0006594527,0.000105016064,0.000038863465,0.00032973304,0.000043583845,0.000862017,0.00054512784,0.00010688428,0.000062274834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005436639,0.00010971977,0.000077959834,0.00022810553,0.00005705492,0.000112669346,0.0017005836,0.0005251871,0.015102837,0.62196,0.07754078,0.28253075],"study_design_scores_gemma":[0.0013119162,0.00090770173,0.00007272951,0.000028699438,0.000011424672,0.00002884324,0.0005254762,0.45746452,0.29187605,0.07778483,0.1690385,0.0009493098],"about_ca_topic_score_codex":0.0000015853412,"about_ca_topic_score_gemma":0.0000023317498,"teacher_disagreement_score":0.6438476,"about_ca_system_score_codex":0.000026456437,"about_ca_system_score_gemma":0.000030424146,"threshold_uncertainty_score":0.4282431},"labels":[],"label_agreement":null},{"id":"W3042208251","doi":"10.1145/3386368","title":"Spiffy","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Versioning file system; Unix file types; File Control Block; File system; Computer file; Operating system; Self-certifying File System; File system fragmentation; Stub file; Virtual file system; Metadata; SSH File Transfer Protocol; Journaling file system; Torrent file; Fork (system call); Database; Flash file system","score_opus":0.03673170540678989,"score_gpt":0.2621306478916758,"score_spread":0.2253989424848859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042208251","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":[0.0014581494,0.000055773235,0.98425376,0.011624991,0.00022738344,0.00011411723,0.0000228214,0.0017714764,0.0004715322],"genre_scores_gemma":[0.7321707,0.000026685871,0.26567054,0.0019653316,0.00002759554,0.0000230063,0.0000018388266,0.000013014472,0.000101323014],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989506,0.000021216965,0.00014544623,0.00043960483,0.00021709822,0.00022600725],"domain_scores_gemma":[0.9984015,0.00008634018,0.000043544263,0.0013329939,0.000027360567,0.00010826718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046945574,0.00014528066,0.00013962762,0.0000893978,0.00015429468,0.000062674386,0.0018960041,0.00007285597,0.000070736845],"category_scores_gemma":[0.00008937163,0.00014254158,0.00006629315,0.0006290929,0.00006106048,0.0006901608,0.000050650568,0.00032201564,0.0005563362],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003325911,0.00019111154,0.000010080185,0.000027214395,0.00005314304,0.00026161122,0.0011808572,0.014574802,0.006478287,0.027859965,0.004257599,0.94507205],"study_design_scores_gemma":[0.003188369,0.0024733734,0.0006263898,0.000075610165,0.00007192524,0.0001023145,0.0008765767,0.08837394,0.17148188,0.057835046,0.67216307,0.002731498],"about_ca_topic_score_codex":0.0000040363534,"about_ca_topic_score_gemma":0.0000020927648,"teacher_disagreement_score":0.94234055,"about_ca_system_score_codex":0.00004658907,"about_ca_system_score_gemma":0.000026297112,"threshold_uncertainty_score":0.71507615},"labels":[],"label_agreement":null},{"id":"W3043880614","doi":"","title":"Rethinking WOM Codes to Enhance the Lifetime in New SSD Generations.","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Internet privacy","score_opus":0.032116100148666255,"score_gpt":0.2845377090479084,"score_spread":0.25242160889924214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043880614","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003946814,0.00013410734,0.90082693,0.09364262,0.000057932943,0.00014300509,0.0000013683334,0.00057491794,0.00067227497],"genre_scores_gemma":[0.26344445,0.000019493682,0.7238595,0.012056363,0.000063625004,0.000012188799,0.0000011618438,0.0000053489066,0.0005378675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991264,0.000025677757,0.00015866537,0.00034350794,0.00016144906,0.0001843079],"domain_scores_gemma":[0.99917024,0.000098424796,0.000034078832,0.0006137193,0.000021151476,0.00006236797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012933927,0.000088024935,0.00009687061,0.00004391591,0.000084388164,0.00013205658,0.0015525289,0.000039372197,0.000022583747],"category_scores_gemma":[0.0004219497,0.000062655716,0.000015421814,0.00075657637,0.00003458958,0.0004854544,0.00081252394,0.00017925979,0.00018660039],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008123683,0.000021379568,0.00024266705,0.000007755275,0.000008977835,0.000039409,0.011791296,0.009965389,0.023566183,0.60639966,0.07634778,0.2716014],"study_design_scores_gemma":[0.0003159243,0.0002640476,0.0006722251,0.000054180764,0.0000039573906,0.000012349601,0.00049043226,0.21320438,0.35353434,0.20775843,0.22284901,0.00084072066],"about_ca_topic_score_codex":0.000053956515,"about_ca_topic_score_gemma":0.00020462913,"teacher_disagreement_score":0.3986412,"about_ca_system_score_codex":0.00003173033,"about_ca_system_score_gemma":0.00007736202,"threshold_uncertainty_score":0.28850108},"labels":[],"label_agreement":null},{"id":"W3047079659","doi":"10.1140/epjc/s10052-023-11885-1","title":"Data preservation in high energy physics","year":2023,"lang":"en","type":"article","venue":"The European Physical Journal C","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"U.S. Department of Energy","keywords":"Perspective (graphical); Data science; Term (time); Computer science; Plan (archaeology); Risk analysis (engineering); Management science; Engineering; Physics; Business; Artificial intelligence","score_opus":0.06640664933670494,"score_gpt":0.28893419342608606,"score_spread":0.22252754408938114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047079659","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":[0.02073965,0.000039427574,0.96820813,0.0038273092,0.00030599118,0.000057606674,0.000027105298,0.00071315095,0.0060816524],"genre_scores_gemma":[0.9938885,0.00008652715,0.004819301,0.00013114938,0.0008826471,0.0000013163445,0.000030383366,0.000020822605,0.00013933664],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987964,0.00028138157,0.0001566174,0.00024579532,0.00028122723,0.00023858233],"domain_scores_gemma":[0.99838847,0.00014581729,0.00010939041,0.0012902383,0.000031484222,0.00003460109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006124424,0.00009761393,0.00010532521,0.00005543446,0.00013313587,0.00015202779,0.0042960094,0.000010011475,2.5217562e-7],"category_scores_gemma":[0.0001516464,0.000064135544,0.000025206564,0.0009530408,0.000068177156,0.0017136479,0.0031255214,0.00035163286,0.00014711908],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048247966,0.00007220176,0.0000145373115,0.0000027175774,0.000012655179,0.0002780932,0.00024933866,0.0030738767,0.0021054111,0.23880412,0.042027153,0.71335506],"study_design_scores_gemma":[0.00020885718,0.00004062656,0.0020548112,0.000019241046,0.0000032695013,0.000020398813,0.000027235594,0.036305744,0.00034931817,0.95391047,0.0069323317,0.00012767068],"about_ca_topic_score_codex":0.000006406673,"about_ca_topic_score_gemma":0.0000022201543,"teacher_disagreement_score":0.9731489,"about_ca_system_score_codex":0.00002427733,"about_ca_system_score_gemma":0.00001677006,"threshold_uncertainty_score":0.7983126},"labels":[],"label_agreement":null},{"id":"W3080469496","doi":"10.1109/lcomm.2020.3018937","title":"Codes With Minimum Bandwidth Cooperative Local Regeneration","year":2020,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bandwidth (computing); Computer science; Locality; Distributed data store; Block code; Computer network; Distributed computing; Algorithm; Decoding methods","score_opus":0.03726197317733011,"score_gpt":0.26376556011861674,"score_spread":0.22650358694128664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080469496","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":[0.0038614285,0.00015626218,0.87607855,0.11888471,0.000039620205,0.00017184735,0.000012835619,0.0005547183,0.00024000481],"genre_scores_gemma":[0.6687472,0.00008140312,0.32334694,0.0076987497,0.000018813193,0.00005558515,0.00003258374,0.000009551265,0.000009196241],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904954,0.00011284804,0.00018324515,0.00031222522,0.00016505555,0.00017709733],"domain_scores_gemma":[0.99730104,0.00014690775,0.00009429323,0.0023018536,0.00009139038,0.000064536216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074226635,0.0001425392,0.00014760757,0.00006073036,0.0003018086,0.00012099935,0.002866073,0.000042556974,0.000002697612],"category_scores_gemma":[0.000053111347,0.00012440038,0.000023267436,0.00059700344,0.0004913255,0.00080684945,0.00050591526,0.0002608952,0.000058739093],"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":[0.00007139992,0.0002964184,0.00048135576,0.000042250886,0.00022361598,0.00006205763,0.008356971,0.068931065,0.3945413,0.29839855,0.11892939,0.10966562],"study_design_scores_gemma":[0.0017957885,0.0006438928,0.0002348024,0.000092764814,0.000045707533,0.00006653467,0.0012384048,0.6368342,0.2400772,0.0009877556,0.11662317,0.0013597803],"about_ca_topic_score_codex":0.00001068036,"about_ca_topic_score_gemma":0.0000447643,"teacher_disagreement_score":0.66488576,"about_ca_system_score_codex":0.00006230888,"about_ca_system_score_gemma":0.000047498652,"threshold_uncertainty_score":0.5325924},"labels":[],"label_agreement":null},{"id":"W3083878797","doi":"10.1002/spe.2889","title":"Performance analysis of distributed storage clusters based on kernel and userspace traces","year":2020,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Tracing; Distributed computing; Scalability; Debugging; Replication (statistics); Queue; Parallel computing; Operating system; Computer network","score_opus":0.018964038167925034,"score_gpt":0.2719575905685418,"score_spread":0.2529935524006168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083878797","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":[0.36010262,0.00019312584,0.6364654,0.0028477467,0.000027885862,0.000082308594,0.000035402856,0.00022791709,0.000017613247],"genre_scores_gemma":[0.9014912,0.00015731674,0.09736506,0.0009473647,0.0000053025847,0.000015055069,0.000010697724,0.0000052798937,0.000002674398],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876004,0.00005054501,0.00018597046,0.0005196882,0.0002818809,0.00020187342],"domain_scores_gemma":[0.9984627,0.0006157667,0.00023243205,0.00049982534,0.00008025216,0.000109019405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014503958,0.000158372,0.00025510174,0.00012712841,0.00020154609,0.000075791475,0.00052172615,0.000061996674,0.0000037240734],"category_scores_gemma":[0.001965017,0.00014436168,0.000033910444,0.0012827327,0.00023511892,0.002130505,0.00041797798,0.00017091833,0.0000014276022],"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":[0.0027399547,0.0012542177,0.1726817,0.0010098832,0.0014739537,0.0007147251,0.25891122,0.1716925,0.005846048,0.007996458,0.0019544745,0.37372488],"study_design_scores_gemma":[0.00056696456,0.0007461,0.010394838,0.000044531007,0.00021496539,0.000012680806,0.00949694,0.96811324,0.0034373892,0.000029272911,0.0064482177,0.0004948699],"about_ca_topic_score_codex":0.000023286613,"about_ca_topic_score_gemma":0.0000027199255,"teacher_disagreement_score":0.79642075,"about_ca_system_score_codex":0.000022844133,"about_ca_system_score_gemma":0.00003092694,"threshold_uncertainty_score":0.58868986},"labels":[],"label_agreement":null},{"id":"W3086093300","doi":"10.14778/3415478.3415483","title":"PiBench online","year":2020,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Benchmarking; Upload; Emulation; Key (lock); Implementation; Operating system; Dram; Interface (matter); Spec#; Embedded system; Software engineering; Computer hardware","score_opus":0.025558968550096615,"score_gpt":0.23712624469475133,"score_spread":0.2115672761446547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086093300","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":[0.5202621,0.00166486,0.20393234,0.24619077,0.0013277765,0.0027534822,0.00013636572,0.0047536925,0.01897858],"genre_scores_gemma":[0.8768339,0.000035615765,0.12206458,0.0009534634,0.00004026387,0.0000139013655,6.363261e-7,0.0000069534917,0.0000506738],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990522,0.0000017522218,0.00018717637,0.00028253096,0.00029148403,0.00018485749],"domain_scores_gemma":[0.9994633,0.000016545067,0.00016493481,0.00021961608,0.000087567365,0.000048036938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006560101,0.00010884063,0.00013564374,0.000032660195,0.00005706886,0.000036187426,0.002339904,0.000032193584,0.000004927004],"category_scores_gemma":[0.00021558066,0.00007284462,0.00005491452,0.00049446686,0.00007687367,0.0004233381,0.0017614434,0.00014597557,0.000010899602],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002019426,0.00025342006,0.0025885024,0.00018199135,0.000058332782,0.0000033712042,0.002060109,0.00009722237,0.2538564,0.646611,0.025146415,0.06912308],"study_design_scores_gemma":[0.00067317113,0.00032310895,0.0017880033,0.0000754947,0.000018376068,0.000017799926,0.0005933079,0.00822041,0.89762735,0.057648245,0.032658506,0.0003561975],"about_ca_topic_score_codex":0.0000044254275,"about_ca_topic_score_gemma":3.7419542e-7,"teacher_disagreement_score":0.643771,"about_ca_system_score_codex":0.00003545845,"about_ca_system_score_gemma":0.00001536423,"threshold_uncertainty_score":0.4348163},"labels":[],"label_agreement":null},{"id":"W3091603075","doi":"10.1561/9781638280255","title":"Codes for Distributed Storage","year":2022,"lang":"en","type":"book","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"NetApp; Silicon Valley Community Foundation","keywords":"Distributed data store; Computer science; Redundancy (engineering); Computer data storage; Overhead (engineering); Distributed computing; Operating system","score_opus":0.02210601484482585,"score_gpt":0.26101853142410225,"score_spread":0.2389125165792764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091603075","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.8516354e-7,0.00034437948,0.9217128,0.00038208478,0.0004496561,0.00049339223,0.0024959978,0.002350577,0.071770884],"genre_scores_gemma":[0.000017607857,0.000033199554,0.27586615,0.00020760746,0.000056744677,0.00027766934,0.002388565,0.000034270033,0.7211182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984193,0.000013681929,0.00023548362,0.0007039186,0.0003018994,0.0003257261],"domain_scores_gemma":[0.9976948,0.00030251138,0.00019484849,0.0016967546,0.00006644606,0.00004462821],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015312272,0.00028054486,0.0003557001,0.00016033431,0.00020557614,0.0000970873,0.0032647213,0.0001943146,0.00020525484],"category_scores_gemma":[0.00015272228,0.00027055398,0.0001234827,0.00015882897,0.00009384865,0.00035984858,0.0023207709,0.00038651313,0.00003865561],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017649961,0.000008467455,1.1696077e-7,0.000019635341,0.000015141557,0.000019754196,0.00000710039,0.00004950144,0.000003877414,0.5128113,0.47867623,0.008387082],"study_design_scores_gemma":[0.00012492786,0.00008634998,5.503583e-7,0.0000073151537,0.0000074074246,0.000007853719,0.000008606889,0.0021262597,0.000055229182,0.17482437,0.822463,0.00028813042],"about_ca_topic_score_codex":0.0000019487848,"about_ca_topic_score_gemma":0.000005798905,"teacher_disagreement_score":0.6493473,"about_ca_system_score_codex":0.0005409203,"about_ca_system_score_gemma":0.00029217394,"threshold_uncertainty_score":0.99997467},"labels":[],"label_agreement":null},{"id":"W3112014538","doi":"","title":"Making the most of a meteorite collection - an application of Multi MIMSY 2000, a collections database management system.","year":2000,"lang":"en","type":"article","venue":"Journal of the Royal Astronomical Society of Canada","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Database; Meteorite; Computer science; World Wide Web; Astrobiology; Biology","score_opus":0.01073839899568029,"score_gpt":0.227603423665307,"score_spread":0.2168650246696267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112014538","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":[0.18152411,0.00022739363,0.81596196,0.0012048995,0.00027428035,0.00048828006,0.00012836854,0.000024445482,0.0001662914],"genre_scores_gemma":[0.8109248,0.0000040982263,0.18878262,0.000022490809,0.000025710204,0.000007463456,0.000001194079,0.000005334238,0.00022628377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987689,0.0000708401,0.0005288101,0.00013581569,0.00034229786,0.00015330318],"domain_scores_gemma":[0.99852514,0.000074288924,0.0007078281,0.00053619844,0.00011673995,0.00003980467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036919524,0.0000960278,0.00023449195,0.000033529144,0.00022326606,0.000017625045,0.0011740172,0.000036566624,0.000006901818],"category_scores_gemma":[0.000016801376,0.00006495562,0.00014009436,0.00052430655,0.0001317874,0.00017971295,0.00019464357,0.00019421897,1.0693948e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017927271,0.00040090657,0.0010530076,0.00025592788,0.0007149405,0.0000016060815,0.0005934144,0.88066596,0.0022441298,0.0028690356,0.05386817,0.057153642],"study_design_scores_gemma":[0.00096136256,0.00018058032,0.006028704,0.0001721207,0.00011812235,0.000012510239,0.002374618,0.9745307,0.0043718596,0.000094683615,0.010997921,0.000156809],"about_ca_topic_score_codex":0.019408487,"about_ca_topic_score_gemma":0.00906507,"teacher_disagreement_score":0.6294007,"about_ca_system_score_codex":0.0006239959,"about_ca_system_score_gemma":0.00039279324,"threshold_uncertainty_score":0.98712134},"labels":[],"label_agreement":null},{"id":"W3118571333","doi":"10.1145/3423088","title":"Reliability of SSDs in Enterprise Storage Systems","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; RAID; Firmware; Vendor; Reliability (semiconductor); Computer data storage; NAND gate; Flash (photography); Embedded system; Operating system; Database; Reliability engineering; Algorithm; Logic gate","score_opus":0.017288366207710217,"score_gpt":0.26139127746051505,"score_spread":0.24410291125280484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118571333","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":[0.091192976,0.00033622395,0.90660775,0.00031404782,0.0006982227,0.00019919843,0.00007419867,0.00037736888,0.00020002155],"genre_scores_gemma":[0.9394339,0.00009615617,0.06010097,0.00004701831,0.000009485695,0.00005507178,0.000005163175,0.0000145686645,0.00023771575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980626,0.00014912151,0.0004658167,0.0006494868,0.0003634931,0.00030947968],"domain_scores_gemma":[0.9961647,0.00032520675,0.00013206221,0.003168753,0.00014442221,0.00006485784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031969725,0.00020205631,0.0003603911,0.00029561174,0.00008535073,0.000052809126,0.0014615527,0.00014980983,0.00002914528],"category_scores_gemma":[0.0002929103,0.00020746014,0.00010736521,0.0011762275,0.000119376586,0.0008455638,0.0000928879,0.0004498745,0.000029950073],"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":[0.00026683309,0.0063699735,0.0019513676,0.0010308889,0.00020704606,0.0031916127,0.006183001,0.64257926,0.059649024,0.02892305,0.0013322483,0.24831572],"study_design_scores_gemma":[0.015218858,0.0035774235,0.04806265,0.0029893578,0.00027317606,0.00117464,0.011351877,0.2846126,0.44512787,0.07707441,0.102799825,0.0077373055],"about_ca_topic_score_codex":0.00008126371,"about_ca_topic_score_gemma":0.000045707246,"teacher_disagreement_score":0.84824085,"about_ca_system_score_codex":0.00025611246,"about_ca_system_score_gemma":0.00012331684,"threshold_uncertainty_score":0.84599787},"labels":[],"label_agreement":null},{"id":"W3118848851","doi":"10.1109/lcomm.2021.3049188","title":"Lower Bounds on Bandwidth Requirements of Regenerating Code Parameter Scaling in Distributed Storage Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Bandwidth (computing); Distributed computing; Scaling; Fault tolerance; Distributed data store; Upper and lower bounds; Reliability (semiconductor); Code (set theory); Variety (cybernetics); Set (abstract data type); Computer network; Mathematics","score_opus":0.06078671273120112,"score_gpt":0.3076918176642665,"score_spread":0.2469051049330654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118848851","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":[0.1607575,0.00085129775,0.83316797,0.004247782,0.00039505074,0.0001749856,0.00011051547,0.00020639959,0.00008847917],"genre_scores_gemma":[0.8905613,0.00006393812,0.10875788,0.00044211515,0.000010830033,0.00005190938,0.000093515824,0.0000111636455,0.000007390696],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984644,0.00025155387,0.00046878643,0.00034399098,0.00022235408,0.00024893606],"domain_scores_gemma":[0.99491805,0.00041970005,0.00022986061,0.004300198,0.0000994821,0.000032718614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033660608,0.00014376771,0.00023231738,0.0001616155,0.00017494455,0.00013274937,0.002383479,0.00006721774,0.0000011398445],"category_scores_gemma":[0.0003411024,0.00015426062,0.00004880796,0.0007962248,0.00018538444,0.00047814404,0.00073045027,0.0003146309,0.000006142989],"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":[0.000027725378,0.0014032,0.006932288,0.00017504861,0.00020459609,0.00017329787,0.0015096582,0.24376689,0.38524193,0.3266026,0.009245983,0.024716776],"study_design_scores_gemma":[0.00293752,0.00023533625,0.0025455533,0.0022009886,0.000051347215,0.00005742427,0.00068119407,0.77451485,0.1923859,0.0035703676,0.018988563,0.0018309695],"about_ca_topic_score_codex":0.00002986727,"about_ca_topic_score_gemma":0.00003713692,"teacher_disagreement_score":0.72980374,"about_ca_system_score_codex":0.00021790268,"about_ca_system_score_gemma":0.000045844805,"threshold_uncertainty_score":0.6290565},"labels":[],"label_agreement":null},{"id":"W3119951918","doi":"10.1145/3423137","title":"SSD-based Workload Characteristics and Their Performance Implications","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Workload; File system; Locality; Block (permutation group theory); Cover (algebra); Block size; Sensitivity (control systems); Computer data storage; Operating system; Embedded system","score_opus":0.02264682567126836,"score_gpt":0.24520644273065748,"score_spread":0.22255961705938912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119951918","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":[0.055856448,0.00017975147,0.93976754,0.0031422246,0.00018686424,0.00009943034,0.00009140246,0.0005768008,0.00009951927],"genre_scores_gemma":[0.8898857,0.00026431112,0.10916882,0.0004631166,0.000013879276,0.000060367693,0.000012093687,0.000012716899,0.000118994605],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998985,0.000030083951,0.00018284317,0.00045396943,0.000106384774,0.00024171291],"domain_scores_gemma":[0.9976725,0.00020817193,0.000067225286,0.0018886745,0.00009319737,0.000070244634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000078149795,0.00017473262,0.00016899561,0.00012699008,0.0003523115,0.000107503634,0.00080148695,0.00008796303,0.00002215143],"category_scores_gemma":[0.00006224948,0.00016446976,0.00004765468,0.0006036648,0.0001068815,0.00051570986,0.000049096154,0.00029848705,0.000035198344],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007671298,0.00015850361,0.00019997403,0.000022324672,0.000021088714,0.000017408105,0.00016636806,0.00063434226,0.0044407807,0.0017804585,0.00007060581,0.99248046],"study_design_scores_gemma":[0.0044298107,0.0012984558,0.1648554,0.00078225625,0.00015006687,0.00082870515,0.0011757526,0.13883172,0.48851728,0.03385752,0.160748,0.0045250216],"about_ca_topic_score_codex":0.0000016778781,"about_ca_topic_score_gemma":0.000005343452,"teacher_disagreement_score":0.98795545,"about_ca_system_score_codex":0.00006749136,"about_ca_system_score_gemma":0.0000895747,"threshold_uncertainty_score":0.6706882},"labels":[],"label_agreement":null},{"id":"W3120354622","doi":"10.1007/s42803-020-00029-6","title":"From archive to analysis: accessing web archives at scale through a cloud-based interface","year":2021,"lang":"en","type":"article","venue":"International Journal of Digital Humanities","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; York University","funders":"University of Waterloo; York University; Compute Canada; Andrew W. Mellon Foundation","keywords":"Cloud computing; World Wide Web; Computer science; Interface (matter); Scope (computer science); Mashup; Scale (ratio); Web development; Web service; Web page","score_opus":0.031190827745018183,"score_gpt":0.3008049511167233,"score_spread":0.2696141233717051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120354622","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":[0.27019587,0.00031652878,0.72405404,0.0011529587,0.0006532406,0.000028784489,0.00031507155,0.000081007005,0.003202492],"genre_scores_gemma":[0.9070174,0.000015201469,0.09197813,0.00036203794,0.00025631086,0.0000024839508,0.000043650012,0.000009892761,0.00031490132],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99840415,0.00003577526,0.0004825914,0.00028630038,0.0006062338,0.00018493188],"domain_scores_gemma":[0.9985079,0.0003890079,0.00035826824,0.00037026274,0.0003188589,0.00005567684],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000048804024,0.00016553604,0.00028568396,0.0004522005,0.00008658868,0.0012188018,0.0022209089,0.000029146198,0.00004981038],"category_scores_gemma":[0.00019480185,0.00015317343,0.00024141413,0.00028869338,0.00017732741,0.002532289,0.0013621621,0.00019914813,0.000024244979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023252433,0.0036806713,0.03982329,0.00011471294,0.019551931,0.013326568,0.11213687,0.11539669,0.113814615,0.22061624,0.026915729,0.33229744],"study_design_scores_gemma":[0.0026761736,0.00062849483,0.0044137044,0.0011544533,0.0003645369,0.00052494736,0.012175487,0.021869592,0.24184573,0.647766,0.065138556,0.0014423543],"about_ca_topic_score_codex":0.000007161641,"about_ca_topic_score_gemma":0.00006651474,"teacher_disagreement_score":0.6368215,"about_ca_system_score_codex":0.00014416935,"about_ca_system_score_gemma":0.00013195879,"threshold_uncertainty_score":0.999818},"labels":[],"label_agreement":null},{"id":"W3121619739","doi":"10.1109/icde55515.2023.00097","title":"Real-Time LSM-Trees for HTAP Workloads","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Online analytical processing; Online transaction processing; Merge (version control); Workload; Analytics; Parallel computing; Data structure; Database; Operating system; Real-time computing; Distributed computing; Data warehouse; Transaction processing","score_opus":0.024695670900532492,"score_gpt":0.28387603741109957,"score_spread":0.2591803665105671,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121619739","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0054663736,0.00002268921,0.9766652,0.0028639857,0.00021919308,0.00025118692,0.000014288506,0.008515307,0.005981769],"genre_scores_gemma":[0.032882232,0.000117697076,0.9491262,0.00015413263,0.000062321466,0.00013733136,0.000026881755,0.000021195254,0.01747203],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99900365,0.000008563539,0.00013358297,0.00037328384,0.00014069628,0.0003402106],"domain_scores_gemma":[0.9987049,0.00024360149,0.000040577557,0.00093387545,0.000039279923,0.000037770194],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00016778507,0.00010727375,0.00012734046,0.00015283354,0.0000966781,0.00007562294,0.001314332,0.00006533664,0.00002287317],"category_scores_gemma":[0.0001709605,0.00009111231,0.000044737953,0.00082634337,0.000053588727,0.0005417113,0.0007512077,0.00005670181,0.0010594631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066378393,0.00002691867,0.00012477477,0.000012137242,0.000018253531,0.000032899738,0.00013576022,0.00032578365,0.017663458,0.4850606,0.2452601,0.25133267],"study_design_scores_gemma":[0.0010568813,0.0004240278,0.0034646138,0.000057792142,0.000012050586,0.000018693552,0.00031946172,0.2625761,0.05784382,0.46815884,0.20488392,0.0011838133],"about_ca_topic_score_codex":0.00001070457,"about_ca_topic_score_gemma":0.000009411481,"teacher_disagreement_score":0.2622503,"about_ca_system_score_codex":0.00003283842,"about_ca_system_score_gemma":0.000024303472,"threshold_uncertainty_score":0.9997183},"labels":[],"label_agreement":null},{"id":"W3135280567","doi":"","title":"On List Recovery of High-Rate Tensor Codes.","year":2019,"lang":"en","type":"article","venue":"CWI's Institutional Repository (Centrum Wiskunde & Informatica)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Decoding methods; Probabilistic logic; List decoding; Mathematics; Tensor product; Linear code; Discrete mathematics; Algorithm; Block code; Computer science; Concatenated error correction code; Statistics","score_opus":0.00755733341339793,"score_gpt":0.2084363799384936,"score_spread":0.20087904652509567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135280567","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":[0.55812985,0.00013889359,0.3658452,0.0007320239,0.004292037,0.00087717647,0.00014703198,0.0010742912,0.06876348],"genre_scores_gemma":[0.96733874,0.000031167616,0.03154326,0.0004130127,0.000056678906,0.000022494916,0.000047377336,0.000012157119,0.0005350926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99747854,0.00005031134,0.0008358814,0.00042294915,0.0007429158,0.0004694027],"domain_scores_gemma":[0.9972218,0.00032633476,0.00052728684,0.0015831363,0.00021449693,0.00012690114],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028092164,0.00031190412,0.00042707825,0.00029276032,0.00033706127,0.00017474077,0.0016520638,0.00019527799,0.00003684618],"category_scores_gemma":[0.00045641608,0.0002807275,0.00013788337,0.000478206,0.00053650304,0.002922815,0.0006948857,0.00039428347,0.00046256927],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008227931,0.00013616413,0.00029279315,0.00010254992,0.000062169755,0.000048662856,0.000096638825,0.015511516,0.0011396667,0.9761984,0.0013943019,0.0049348986],"study_design_scores_gemma":[0.008611619,0.004432304,0.02968242,0.002336665,0.00013630909,0.0020718148,0.0007494325,0.16866784,0.21824077,0.35279235,0.20761958,0.004658905],"about_ca_topic_score_codex":0.000029674991,"about_ca_topic_score_gemma":0.0000024562414,"teacher_disagreement_score":0.623406,"about_ca_system_score_codex":0.00043429047,"about_ca_system_score_gemma":0.0004016088,"threshold_uncertainty_score":0.9999645},"labels":[],"label_agreement":null},{"id":"W3140278220","doi":"10.1109/clustr.2003.1253343","title":"\"Plug-and-play\" cluster computing using Mac OS X","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kruger (Canada)","funders":"","keywords":"Unix; Computer science; Mac OS; OS X; Scalability; Operating system; Supercomputer; Usability; Cluster analysis; Computer cluster; Parallel I/O; Software","score_opus":0.027408320497796318,"score_gpt":0.27747249598053136,"score_spread":0.2500641754827351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3140278220","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028069075,0.0001057004,0.9673405,0.00020242178,0.00016388332,0.00008924831,7.367322e-7,0.00064879964,0.0033796036],"genre_scores_gemma":[0.41395342,0.0000036200595,0.5855652,0.00036104277,0.000007959454,6.6877703e-7,3.2869002e-7,0.0000051561656,0.00010256605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904734,0.000033338434,0.00015505606,0.0003593623,0.00012595185,0.00027896077],"domain_scores_gemma":[0.99921143,0.00009348512,0.00005702367,0.00056693656,0.000027919143,0.0000432182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017870509,0.000120322744,0.00012509058,0.00009024175,0.00014321307,0.00010696569,0.0005056134,0.000059530437,0.000011318064],"category_scores_gemma":[0.000117907846,0.000104984916,0.000019773532,0.000271113,0.00007383838,0.000560906,0.0005990277,0.00012584773,0.000027720213],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022614488,0.000041288473,0.002057349,0.00002150497,0.000020583446,0.00006178073,0.00035148076,0.003115968,0.003668336,0.89407784,0.0018716421,0.09470994],"study_design_scores_gemma":[0.0009718292,0.00008632566,0.00052649685,0.000049015638,0.000011247808,0.0005792927,0.0002733948,0.8805322,0.029580701,0.055990744,0.03051613,0.00088259485],"about_ca_topic_score_codex":0.000011251001,"about_ca_topic_score_gemma":0.0000025043598,"teacher_disagreement_score":0.87741625,"about_ca_system_score_codex":0.000038504688,"about_ca_system_score_gemma":0.000024846533,"threshold_uncertainty_score":0.42811605},"labels":[],"label_agreement":null},{"id":"W3141865943","doi":"","title":"SHIP: A Storage System for Hybrid Interconnected Processors","year":2020,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Computer science; Embedded system; Parallel computing","score_opus":0.023329831794279082,"score_gpt":0.30892593056574086,"score_spread":0.28559609877146175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3141865943","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":[0.010510885,0.00083944906,0.9774594,0.0007666975,0.001586468,0.0012831652,0.00006467359,0.005077683,0.0024116298],"genre_scores_gemma":[0.792191,0.000034232547,0.19521195,0.0001338238,0.00021945414,0.0011107309,0.0017228074,0.00016352769,0.009212423],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980335,0.000030648127,0.0003076029,0.0009413415,0.00029447634,0.0003923831],"domain_scores_gemma":[0.99811494,0.00014484308,0.0004217121,0.001007368,0.00021974524,0.00009140736],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011392268,0.00040048783,0.0005077949,0.00021901872,0.00013017509,0.00018703472,0.002383103,0.00021977506,0.0000047222798],"category_scores_gemma":[0.00064695603,0.00040069604,0.0001191412,0.0005001211,0.00002896865,0.00045618822,0.00025114728,0.00042288602,0.00008117441],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011402611,0.00034456485,0.000012898658,0.029641489,0.00084904756,0.0015646121,0.07178825,0.00043960288,0.02818521,0.57576334,0.093888566,0.19638218],"study_design_scores_gemma":[0.0036720585,0.0019348814,0.000083493695,0.0047441996,0.00036491637,0.0002149019,0.08155565,0.14527822,0.52154833,0.015485195,0.21911608,0.006002068],"about_ca_topic_score_codex":0.000014362539,"about_ca_topic_score_gemma":0.00003833905,"teacher_disagreement_score":0.7822474,"about_ca_system_score_codex":0.00023828162,"about_ca_system_score_gemma":0.0001843129,"threshold_uncertainty_score":0.9998445},"labels":[],"label_agreement":null},{"id":"W3146266057","doi":"10.5488/cmp.11.4.761","title":"nformation and data protection within a RDBMS","year":2008,"lang":"en","type":"article","venue":"Condensed Matter Physics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan College","funders":"","keywords":"Computer science; Encryption; Relational database management system; Computer security; SQL; Database; Oracle; Relational database; Programming language","score_opus":0.06319973063614848,"score_gpt":0.26354191138546634,"score_spread":0.20034218074931787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3146266057","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":[0.046283204,0.000024871952,0.95220685,0.00054001046,0.00011281442,0.00019724641,0.000013827554,0.00040395124,0.00021724848],"genre_scores_gemma":[0.90297776,0.000008870552,0.09607996,0.00069288595,0.00004218928,0.000024928553,0.000041661002,0.0000100678135,0.00012169792],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992762,0.000014859393,0.00013427317,0.00030466227,0.00013923354,0.00013073657],"domain_scores_gemma":[0.9985475,0.000017449685,0.00010458101,0.0012687471,0.000037130747,0.00002462324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007291363,0.000099413046,0.00009635217,0.000037050027,0.00013780649,0.000062559964,0.00075244054,0.00004082615,0.0000029131384],"category_scores_gemma":[0.000024083445,0.000094307994,0.000008921751,0.00018855372,0.00011423447,0.002432717,0.00085017685,0.00013546944,0.00015544795],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085946034,0.0004641439,0.004248051,0.0006282252,0.00019681665,0.00028950887,0.01924336,0.0013037354,0.12287083,0.17430536,0.11306068,0.56330335],"study_design_scores_gemma":[0.0023131587,0.00027286535,0.008100742,0.0001147895,0.000029758028,0.0011788199,0.00032712033,0.5351605,0.12209049,0.31658688,0.012187136,0.0016377439],"about_ca_topic_score_codex":0.000008261611,"about_ca_topic_score_gemma":0.000001164171,"teacher_disagreement_score":0.8566945,"about_ca_system_score_codex":0.00001927626,"about_ca_system_score_gemma":0.00002502219,"threshold_uncertainty_score":0.38457686},"labels":[],"label_agreement":null},{"id":"W3146736181","doi":"10.1109/isca.2012.6237001","title":"RAIDR: Retention-aware intelligent DRAM refresh","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":176,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada; Samsung; National Science Foundation","keywords":"Dram; Memory controller; Computer science; Dynamic random-access memory; CAS latency; Universal memory; Row; Embedded system; Memory refresh; Static random-access memory; Data retention; Computer hardware; Overhead (engineering); Controller (irrigation); Semiconductor memory; Computer memory; Operating system","score_opus":0.037511675481464266,"score_gpt":0.2803923666801232,"score_spread":0.2428806911986589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3146736181","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":[0.0017932757,0.0002918409,0.99043685,0.0007379704,0.0005646279,0.000105403065,0.0000033695349,0.0015309899,0.004535668],"genre_scores_gemma":[0.6788573,0.00004683942,0.31834322,0.00026845926,0.000058400663,0.00001848194,0.000007798894,0.000008337354,0.002391165],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989739,0.00001927026,0.00017070927,0.00026142818,0.000200278,0.00037440038],"domain_scores_gemma":[0.9986629,0.00004743161,0.00005674711,0.0011027775,0.0000472956,0.00008285949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018289962,0.00011303855,0.000102296035,0.00009854095,0.000086442065,0.00006210159,0.0011238633,0.000070462585,0.000078274716],"category_scores_gemma":[0.0000879166,0.00009302401,0.000043318923,0.0003410486,0.00006389421,0.0015753509,0.0008710917,0.00013573216,0.0006836647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019910003,0.00008263437,0.0012924558,0.000009093665,0.000012431335,0.000007886589,0.00022180678,0.000016555337,0.0006512394,0.7447512,0.034527224,0.21842545],"study_design_scores_gemma":[0.0004216937,0.0002183937,0.0027657307,0.000052355048,0.000014323709,0.00011883614,0.000844144,0.01182081,0.124050364,0.124965824,0.73353976,0.0011877536],"about_ca_topic_score_codex":0.000008708224,"about_ca_topic_score_gemma":0.0000038086393,"teacher_disagreement_score":0.6990125,"about_ca_system_score_codex":0.00006621291,"about_ca_system_score_gemma":0.000013278044,"threshold_uncertainty_score":0.8787355},"labels":[],"label_agreement":null},{"id":"W3150385764","doi":"10.1109/pacrim.2017.8121878","title":"Program committee members","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"China; Library science; Geography; Archaeology","score_opus":0.0321892005348379,"score_gpt":0.31696230843268897,"score_spread":0.28477310789785104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150385764","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024325799,0.000028648841,0.90232384,0.005293212,0.00029895108,0.00020755873,0.0000013308135,0.0036420687,0.08577179],"genre_scores_gemma":[0.28237778,0.0000055911237,0.7166095,0.00011100583,0.000010601265,0.000023742325,5.8038853e-7,0.0000032111514,0.00085801614],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999408,0.000004976402,0.00006958675,0.0002214017,0.00011428249,0.00018177506],"domain_scores_gemma":[0.99741274,0.000017956878,0.00006957812,0.0024447015,0.000023797174,0.000031244646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007366316,0.000069677626,0.000073161296,0.00002986682,0.00031872734,0.0003661923,0.0033087188,0.00003790165,0.000016591945],"category_scores_gemma":[0.0001366708,0.000056123496,0.000021643405,0.00004519265,0.00015981706,0.0012000569,0.0014221261,0.0000872508,0.00011797572],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.251881e-7,0.000021969356,0.00043045933,0.0000015248268,0.0000031300006,0.00001679374,0.000015490947,0.000002389441,0.000042586427,0.23768134,0.0060973563,0.75568664],"study_design_scores_gemma":[0.0005273527,0.00021339658,0.009455138,0.000014360099,0.000003891291,0.000032716096,0.000074088675,0.022404945,0.012952135,0.19137388,0.76240635,0.000541766],"about_ca_topic_score_codex":0.000032286825,"about_ca_topic_score_gemma":0.000034639736,"teacher_disagreement_score":0.756309,"about_ca_system_score_codex":0.0000149834705,"about_ca_system_score_gemma":0.000010131194,"threshold_uncertainty_score":0.6148478},"labels":[],"label_agreement":null},{"id":"W3152852792","doi":"10.5539/cis.v14n2p75","title":"A Nonuniform Reference Voltage Optimization Based on Relative-Precision-Loss Ratios in MLC NAND Flash Memory","year":2021,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Foundation","keywords":"Computer science; NAND gate; Flash memory; Flash (photography); Reliability (semiconductor); Low-density parity-check code; Voltage; Decoding methods; Computer data storage; Noise (video); Error detection and correction; Bit error rate; Electronic engineering; Algorithm; Computer hardware; Logic gate; Electrical engineering; Physics","score_opus":0.016007794002939803,"score_gpt":0.25286876790122104,"score_spread":0.23686097389828123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152852792","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043019243,0.000020239997,0.9886511,0.0004104474,0.00024632172,0.00017258278,0.00000596881,0.0001858704,0.0060055736],"genre_scores_gemma":[0.3994327,0.0000659896,0.59912795,0.001287514,0.000013453295,0.000017011324,0.000023835866,0.0000033690076,0.00002815104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983399,0.000029912131,0.00040428378,0.00038989028,0.0005666078,0.00026941707],"domain_scores_gemma":[0.9984474,0.0001894342,0.00016790957,0.0007408596,0.0003720419,0.00008233744],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00063502765,0.00015202005,0.00015833991,0.0005884561,0.00029413067,0.0005682291,0.0009564246,0.00007374798,0.00000902951],"category_scores_gemma":[0.00040546767,0.0001369199,0.000019128847,0.002098218,0.000280479,0.018566944,0.00071635016,0.0002153424,0.000039460585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014905233,0.000053884472,0.00047585208,0.000027418957,0.0000020350346,0.000022613991,0.001313452,0.5151246,0.00016638395,0.08776921,0.0003065763,0.39472303],"study_design_scores_gemma":[0.00047518976,0.00008304902,0.0024807744,0.00006626857,7.6046206e-7,0.000016577269,0.000043624215,0.9907839,0.0017782451,0.0015157099,0.0025758408,0.00018007608],"about_ca_topic_score_codex":0.0000027105825,"about_ca_topic_score_gemma":0.000002218045,"teacher_disagreement_score":0.47565925,"about_ca_system_score_codex":0.00011824445,"about_ca_system_score_gemma":0.00028648163,"threshold_uncertainty_score":0.99515986},"labels":[],"label_agreement":null},{"id":"W3167131451","doi":"10.1145/3458336.3465285","title":"The Aurora operating system","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ephemeral key; Computer science; Granularity; Operating system; State (computer science); Consistency (knowledge bases); Persistent data structure; Embedded system; Computer hardware; Database; Programming language; Computer security","score_opus":0.015536089863529664,"score_gpt":0.24472540170049184,"score_spread":0.22918931183696217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167131451","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008818478,0.00033005045,0.982185,0.0020964162,0.00024336412,0.000035301302,5.675445e-7,0.0010920708,0.0131353745],"genre_scores_gemma":[0.4574715,0.000013787636,0.54075295,0.00017767599,0.000020087158,0.000011626043,7.455796e-7,0.0000038711223,0.0015477502],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944735,0.00002346722,0.00009279338,0.00018835539,0.00010468786,0.00014334988],"domain_scores_gemma":[0.99891895,0.00010867944,0.0000219103,0.00087706704,0.00005799911,0.000015371075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011567098,0.000048191163,0.000049803963,0.000009904095,0.0002725439,0.00025820168,0.0008744206,0.00002016064,0.0000022046413],"category_scores_gemma":[0.00016843587,0.000029012986,0.000014886751,0.00025360877,0.000029106017,0.00032373433,0.00083791884,0.00007230023,0.0000766527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.1212368e-8,0.0000017865141,0.000012557715,0.0000023681655,0.0000020766422,0.000049892285,0.000020250027,0.00003807695,0.0009391086,0.9458277,0.000901964,0.052204173],"study_design_scores_gemma":[0.00043164432,0.000072224444,0.0003490909,0.00008579429,0.0000058923256,0.0007339383,0.009006829,0.3631359,0.2927705,0.018523607,0.31419724,0.0006872963],"about_ca_topic_score_codex":0.000003150241,"about_ca_topic_score_gemma":0.0000092127475,"teacher_disagreement_score":0.9273041,"about_ca_system_score_codex":0.000032823486,"about_ca_system_score_gemma":0.00003735712,"threshold_uncertainty_score":0.24898447},"labels":[],"label_agreement":null},{"id":"W3177419060","doi":"10.1145/3409964.3461819","title":"A Scalable Recoverable Skip List for Persistent Memory","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Concurrent data structure; Scalability; Parallel computing; Lock (firearm); Data structure; Blocking (statistics); Linked list; Benchmark (surveying); Concurrency; Node (physics); Persistent data structure; B-tree; Algorithm; Distributed computing; Database; Operating system; Computer network","score_opus":0.025973551701608442,"score_gpt":0.2535948008980298,"score_spread":0.22762124919642138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177419060","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00071482494,0.00049399585,0.9742215,0.003187849,0.0003347079,0.0001429405,0.000012320813,0.00067872106,0.020213086],"genre_scores_gemma":[0.021587214,0.000049304854,0.9374632,0.00096635276,0.000032708536,0.000046345605,0.000014942744,0.0000102031945,0.039829712],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999006,0.00001273943,0.00013101133,0.000438245,0.00013012144,0.00028191585],"domain_scores_gemma":[0.9987217,0.000110326306,0.00003821701,0.00095658074,0.00012864021,0.000044536104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012397443,0.00009704599,0.00013427883,0.000046829184,0.00012354826,0.00014271974,0.00073386997,0.000057044195,0.00009255055],"category_scores_gemma":[0.00028574126,0.00009015081,0.00009948567,0.00031859337,0.000037065794,0.0006937219,0.00055975426,0.00007828254,0.00006883114],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017460543,0.0003044718,0.00010521097,0.00012073748,0.00010049584,0.00014606312,0.000297757,0.0020908026,0.011062871,0.5012958,0.23610896,0.24834934],"study_design_scores_gemma":[0.0011525714,0.00028697692,0.000034377827,0.000046658926,0.000020712141,0.00016020994,0.0010903039,0.12228545,0.2259614,0.08594925,0.5622935,0.000718531],"about_ca_topic_score_codex":0.00001542113,"about_ca_topic_score_gemma":0.000030066267,"teacher_disagreement_score":0.41534656,"about_ca_system_score_codex":0.00008319132,"about_ca_system_score_gemma":0.000088609064,"threshold_uncertainty_score":0.36762434},"labels":[],"label_agreement":null},{"id":"W3194069769","doi":"10.1145/3476886.3477514","title":"C2J","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Workload; Journaling file system; Latency (audio); Thread (computing); Operating system; Database transaction; Transaction processing; Database; Computer file","score_opus":0.017820169583175297,"score_gpt":0.2539632364647433,"score_spread":0.236143066881568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194069769","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005033936,0.000108308355,0.9728612,0.0020402048,0.00009573042,0.000010029987,4.2996507e-7,0.0008308161,0.023549901],"genre_scores_gemma":[0.09824271,0.000013620563,0.89878637,0.00054905505,0.0000072460475,0.000002137425,0.0000010630063,0.0000016528454,0.0023961258],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996507,0.0000045918937,0.00004075774,0.00015500358,0.000062164065,0.00008674726],"domain_scores_gemma":[0.9993241,0.000019405536,0.000008529791,0.0006080486,0.000026428595,0.000013518041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002092342,0.00003007669,0.000035443274,0.000016729464,0.000023267374,0.000036441495,0.00045326634,0.00001727194,0.00004483297],"category_scores_gemma":[0.000073246025,0.000026169091,0.000010792668,0.00023151046,0.000015405765,0.0003337264,0.0005364926,0.000038769267,0.00019735008],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.1367035e-8,0.000006759775,0.000031796357,6.588242e-7,0.0000011778686,0.00008213694,0.0000095235855,0.0000055891423,0.001921699,0.8868156,0.0046032355,0.10652174],"study_design_scores_gemma":[0.0001481069,0.000019518371,0.0006004709,0.000004035656,9.405624e-7,0.00012011709,0.00008896979,0.0053029214,0.3788862,0.29607695,0.31854096,0.00021081135],"about_ca_topic_score_codex":9.768848e-7,"about_ca_topic_score_gemma":0.0000032655855,"teacher_disagreement_score":0.5907387,"about_ca_system_score_codex":0.000009032508,"about_ca_system_score_gemma":0.000020094529,"threshold_uncertainty_score":0.25366017},"labels":[],"label_agreement":null},{"id":"W3197491921","doi":"10.1109/isit45174.2021.9518214","title":"An Information Bottleneck Problem with Rényi's Entropy","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Information bottleneck method; Bottleneck; Information theory; Mutual information; Entropy (arrow of time); Computer science; Rényi entropy; Mathematics; Decoding methods; Joint entropy; Multiplicative function; Mathematical optimization; Theoretical computer science; Algorithm; Principle of maximum entropy; Artificial intelligence; Statistics","score_opus":0.006464594729021653,"score_gpt":0.22035812878648955,"score_spread":0.21389353405746792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197491921","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034057433,0.000018417828,0.9910442,0.0010237207,0.00003668116,0.00007509308,0.0000028378824,0.0010192706,0.0033740131],"genre_scores_gemma":[0.14919338,0.00001056231,0.85026056,0.00039612266,0.0000068558606,0.000012639475,0.000023981302,0.0000028084698,0.000093092676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993534,0.000011892853,0.00011478534,0.00017873386,0.00017478141,0.00016637333],"domain_scores_gemma":[0.9989683,0.000013144061,0.00005058849,0.0008196489,0.00011038009,0.000037915157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048525515,0.000078805286,0.00007376588,0.00005417731,0.000057946945,0.0001928218,0.0005865138,0.00003564954,0.00002415268],"category_scores_gemma":[0.00002301615,0.00005930133,0.000010170469,0.00037336725,0.000031493524,0.004934943,0.00022851,0.00007694753,0.00009142151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035238133,0.00003962219,0.00033678097,0.000010514732,0.0000070942474,0.00003162726,0.00023383544,0.00062497763,0.0017378258,0.86523944,0.0012920075,0.13044272],"study_design_scores_gemma":[0.0021836513,0.001241478,0.0036601948,0.00007398018,0.000015873096,0.00054276804,0.001896222,0.116391666,0.41821355,0.15152289,0.3028035,0.0014542545],"about_ca_topic_score_codex":0.0000067519077,"about_ca_topic_score_gemma":0.000015669904,"teacher_disagreement_score":0.71371657,"about_ca_system_score_codex":0.0000308788,"about_ca_system_score_gemma":0.000069131514,"threshold_uncertainty_score":0.35777143},"labels":[],"label_agreement":null},{"id":"W3197594919","doi":"10.23967/eccomas.2022.215","title":"Parallel Finite Volume Code for Plasma with Unstructured Adaptive Mesh Refinement","year":2022,"lang":"en","type":"article","venue":"8th European Congress on Computational Methods in Applied Sciences and Engineering","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Adaptive mesh refinement; Computer science; Parallel computing; Finite volume method; Poisson's equation; Solver; Computational science; Partial differential equation; Compiler; Code (set theory); Algorithm; Mechanics; Mathematics; Physics; Programming language","score_opus":0.040365516066315214,"score_gpt":0.30014067157411656,"score_spread":0.25977515550780134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197594919","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017699276,0.0000386492,0.9964497,0.00021302607,0.00028585893,0.00030129432,0.000044653232,0.00020550487,0.0006913695],"genre_scores_gemma":[0.18910636,0.0000030795527,0.81063557,0.00010428949,0.000013041291,0.000096507574,0.000006754907,0.00001235698,0.00002204092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984312,0.00009411184,0.0002385582,0.00061574066,0.00033304945,0.00028734276],"domain_scores_gemma":[0.9988032,0.0007845705,0.00011738166,0.00021642016,0.000028535887,0.000049871258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011626885,0.00018269438,0.0001911566,0.00027374263,0.00034740733,0.000113164126,0.0008658567,0.000016041606,0.0000040339223],"category_scores_gemma":[0.00008297234,0.00016322335,0.000019822286,0.00059638656,0.00015112481,0.00013892527,0.00054826523,0.00022510295,9.89876e-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":[0.000024964087,0.000009739478,0.000011139195,0.000006399567,0.0000065071877,0.000008661706,0.000090302914,0.7522355,0.00007439782,0.19710612,0.0000379324,0.050388366],"study_design_scores_gemma":[0.0006151245,0.00030748587,0.00033792152,0.000015399351,0.0000026222228,0.000013539812,0.0001364847,0.985021,0.0001056329,0.006240041,0.0069733853,0.00023139663],"about_ca_topic_score_codex":9.0337613e-7,"about_ca_topic_score_gemma":0.0000012642867,"teacher_disagreement_score":0.23278551,"about_ca_system_score_codex":0.0000617177,"about_ca_system_score_gemma":0.000038050952,"threshold_uncertainty_score":0.66560555},"labels":[],"label_agreement":null},{"id":"W3206320699","doi":"10.3390/electronics10202486","title":"Performance Evaluation of NVMe-over-TCP Using Journaling File Systems in International WAN","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Dell Technologies; Canarie; Northwestern University; National Science Foundation","keywords":"Computer science; Operating system; Journaling file system; Computer network; File system; Copying; Database; Computer file","score_opus":0.033193644055028275,"score_gpt":0.3041688607041492,"score_spread":0.27097521664912094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206320699","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":[0.7875571,0.007366955,0.20395689,0.00010640159,0.00050359993,0.000112378606,0.000019373894,0.00008266087,0.00029459922],"genre_scores_gemma":[0.97193617,0.00025033733,0.027712217,0.000013602583,0.000030015857,0.000007823821,0.000022998413,0.0000059280324,0.000020900208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987649,0.00005988023,0.0002499658,0.00020427338,0.00051045546,0.00021057834],"domain_scores_gemma":[0.99917376,0.000049778828,0.0001693308,0.0003256398,0.00026706522,0.000014402125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005909532,0.00007344445,0.000116353796,0.00013570269,0.000042145544,0.000053498676,0.0005517231,0.000049132374,0.00005662739],"category_scores_gemma":[0.0002798494,0.00007893767,0.000022642818,0.00045505926,0.000018128203,0.000680191,0.00021757437,0.0002096464,0.0000027081228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012285184,0.00014212889,0.003265465,0.00005086968,0.000068405614,0.000031960462,0.00048730144,0.5203845,0.049604863,0.03388712,0.0005069741,0.3915581],"study_design_scores_gemma":[0.00024457483,0.000023456021,0.000594365,0.00007839511,0.0000047269314,0.000045001398,0.000053753618,0.9816352,0.013859738,0.00070542115,0.0026719398,0.00008340257],"about_ca_topic_score_codex":0.0000071548357,"about_ca_topic_score_gemma":0.000024668308,"teacher_disagreement_score":0.46125072,"about_ca_system_score_codex":0.00055920606,"about_ca_system_score_gemma":0.00041496824,"threshold_uncertainty_score":0.3218985},"labels":[],"label_agreement":null},{"id":"W3207452942","doi":"10.1145/3483840","title":"RocksDB: Evolution of Development Priorities in a Key-value Store Serving Large-scale Applications","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":186,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Key (lock); Replication (statistics); Scale (ratio); Associative array; Resource (disambiguation); Computer security; Distributed computing; Computer network","score_opus":0.012742153370747394,"score_gpt":0.25059256805151653,"score_spread":0.23785041468076915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207452942","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":[0.021256568,0.00045894217,0.9770057,0.0003671948,0.00013656492,0.00024065976,0.00004535655,0.00036346607,0.00012551136],"genre_scores_gemma":[0.58882725,0.000039575105,0.41073778,0.000037062146,0.000008631281,0.00016915986,0.000008266215,0.00001152341,0.00016070499],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984807,0.00005899937,0.00036000615,0.00049085304,0.00030888463,0.0003005896],"domain_scores_gemma":[0.998112,0.000119904595,0.00010405346,0.0014887014,0.00012730513,0.000047988047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019758743,0.00016717054,0.0002261641,0.00031791927,0.00023025941,0.0000349019,0.0010297121,0.00011780346,0.000015578617],"category_scores_gemma":[0.000046463683,0.00019169423,0.000059287006,0.0012315967,0.00005324894,0.0006470005,0.000111771085,0.00030826812,0.000021758817],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008235233,0.0042570406,0.0027201255,0.0008436777,0.00021404814,0.00025683324,0.023866136,0.13358118,0.034430742,0.1374655,0.00029562594,0.66198677],"study_design_scores_gemma":[0.006719433,0.00056017505,0.03900817,0.0013932851,0.00013585729,0.00032450695,0.029958298,0.07662113,0.48497832,0.114606395,0.24154182,0.0041526123],"about_ca_topic_score_codex":0.000025818701,"about_ca_topic_score_gemma":0.0005274045,"teacher_disagreement_score":0.6578341,"about_ca_system_score_codex":0.0005124796,"about_ca_system_score_gemma":0.00033857417,"threshold_uncertainty_score":0.78170633},"labels":[],"label_agreement":null},{"id":"W3208409304","doi":"10.5281/zenodo.3547649","title":"SSHOC D7.1 System Specification - SSH Open Marketplace","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Humber Polytechnic","funders":"European Commission","keywords":"Computer science; Business","score_opus":0.03608584984145421,"score_gpt":0.2502948924100565,"score_spread":0.21420904256860226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208409304","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":[0.004384533,0.000092600596,0.62583125,0.00126423,0.00034686344,0.0014032271,0.00012983757,0.0054734084,0.36107406],"genre_scores_gemma":[0.9606511,0.00007217002,0.032974236,0.0001497371,0.0000904312,2.1519995e-7,0.0008028288,0.0011305043,0.004128781],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980594,0.00024230739,0.0002563123,0.00069582835,0.00038059638,0.00036555083],"domain_scores_gemma":[0.9975742,0.000036542348,0.00016495507,0.0017752327,0.0003465715,0.00010251414],"candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008599933,0.00014905508,0.00016969036,0.00022067955,0.0010569348,0.0019501152,0.0067066574,0.00007241843,0.0020137483],"category_scores_gemma":[0.0003296829,0.00015554976,0.00003140194,0.00087691983,0.00009086932,0.0016219321,0.0074604186,0.00025106233,0.026945226],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057726942,0.00010306361,0.000008201886,0.00011644929,0.000031062715,0.000026913298,0.00044115988,0.00015436104,0.00749708,0.5750844,0.18288332,0.23359628],"study_design_scores_gemma":[0.0004082226,0.00013628104,0.0002783218,0.00004427298,0.0000031591032,0.0001255777,0.00040447694,0.0051911715,0.0012153229,0.00080742926,0.99116504,0.0002207084],"about_ca_topic_score_codex":0.000009814814,"about_ca_topic_score_gemma":1.2144791e-7,"teacher_disagreement_score":0.9562666,"about_ca_system_score_codex":0.00034366816,"about_ca_system_score_gemma":0.0000053394174,"threshold_uncertainty_score":0.99908596},"labels":[],"label_agreement":null},{"id":"W3209834326","doi":"10.5281/zenodo.3525336","title":"Benchmarking data and outputs for CLASSIC v. 1.0","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Benchmarking; Computer science; Data science; Business","score_opus":0.11458922207363959,"score_gpt":0.32358127145370236,"score_spread":0.20899204938006277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209834326","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.6558765e-8,0.001064617,0.005702215,0.000104791354,0.00029815928,0.0005270352,0.99206257,0.00022672348,0.000013875286],"genre_scores_gemma":[7.4193395e-7,0.0000398028,0.022369152,0.00020067014,0.00016215906,0.00015956654,0.97700286,0.000015588095,0.0000494578],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980379,0.000015212142,0.00021022219,0.0011563569,0.00022331518,0.0003570117],"domain_scores_gemma":[0.9942327,0.000424325,0.00027208278,0.004952778,0.00006489079,0.000053209576],"candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.000072864255,0.00029844986,0.00032534674,0.0001602339,0.00010065306,0.00029277915,0.006513179,0.00035132634,0.002195865],"category_scores_gemma":[0.0018549099,0.0002863796,0.000034098815,0.00018155217,0.000013964645,0.0010086396,0.009975455,0.00036852842,0.0009382537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.348406e-7,0.0000065802674,1.2072788e-7,0.000402708,0.000011673194,0.000013276711,0.0000022802994,0.0000011020772,3.5275414e-7,0.000024784207,0.9788226,0.020713607],"study_design_scores_gemma":[0.0001308155,0.000051476603,0.000004737162,0.00092681026,0.000008877377,0.000012911424,0.0000023305909,0.003084115,0.0000074066497,0.00022819077,0.9951989,0.00034342217],"about_ca_topic_score_codex":0.0000021312371,"about_ca_topic_score_gemma":0.00001600082,"teacher_disagreement_score":0.020370185,"about_ca_system_score_codex":0.00004247648,"about_ca_system_score_gemma":0.00011483774,"threshold_uncertainty_score":0.9999588},"labels":[],"label_agreement":null},{"id":"W39307351","doi":"10.5220/0004317301170122","title":"TStore: A Trace-Base Management System - Using Finite-state Transducer Approach for Trace Transformation","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"TRACE (psycholinguistics); Transformation (genetics); Exploit; Computer science; State (computer science); Base (topology); Model transformation; Transducer; Engineering; Algorithm; Electrical engineering; Artificial intelligence; Mathematics; Computer security","score_opus":0.04742773314001825,"score_gpt":0.26648100438984124,"score_spread":0.219053271249823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W39307351","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018559314,0.00044167764,0.9880243,0.0003041707,0.00053728657,0.0045620785,0.00022398775,0.0026825045,0.0013680676],"genre_scores_gemma":[0.14174673,0.00007019621,0.85616416,0.00004019652,0.00003711579,0.0014740529,0.00013944016,0.00005256073,0.00027553638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965346,0.00007666671,0.00085712195,0.001333274,0.0005180925,0.0006802309],"domain_scores_gemma":[0.99718744,0.00010962844,0.00038337824,0.0020536082,0.00015112355,0.00011483159],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005481287,0.00064455107,0.00064411236,0.00052827544,0.00022153335,0.00047412794,0.002636034,0.00040470224,0.0000066933285],"category_scores_gemma":[0.000017518008,0.00058929727,0.00030079042,0.00040969436,0.0000979137,0.0015038638,0.00055462006,0.00057594915,0.000019353865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052873147,0.0002718807,7.95611e-7,0.008539406,0.00026281108,0.00004823899,0.0035341436,0.5691133,0.00025355173,0.14523804,0.0005698662,0.27211505],"study_design_scores_gemma":[0.0008231351,0.000051564337,0.0000028418774,0.00020939013,0.00008573655,0.000025565309,0.0008882755,0.98689604,0.002420943,0.0052430485,0.0026022804,0.0007511818],"about_ca_topic_score_codex":0.000064511296,"about_ca_topic_score_gemma":0.000004689513,"teacher_disagreement_score":0.4177827,"about_ca_system_score_codex":0.0005860034,"about_ca_system_score_gemma":0.000088050445,"threshold_uncertainty_score":0.99965584},"labels":[],"label_agreement":null},{"id":"W4200534353","doi":"10.32920/17190185.v1","title":"Transfer Learning Based Performance Modeling And Effective Storage Management In Big Data Ecosystems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Workload; Computer science; Big data; Cache; Distributed computing; Data management; Database; Transfer (computing); Data modeling; Information repository; Component (thermodynamics); Computer data storage; Operating system","score_opus":0.04617086414538442,"score_gpt":0.2607581010266625,"score_spread":0.21458723688127812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200534353","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":[0.15786792,0.0006030941,0.8393997,0.00010764751,0.00042401758,0.0007203908,0.00001646661,0.0005991419,0.00026163226],"genre_scores_gemma":[0.88934475,0.00051180634,0.10966599,0.00004824722,0.000025806088,0.00016312943,0.00018438647,0.00002250361,0.000033395518],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970601,0.00015549871,0.00038019638,0.0016894673,0.0003332445,0.00038145646],"domain_scores_gemma":[0.9968773,0.00010425645,0.00006348377,0.002854529,0.00005006962,0.00005036131],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00078384357,0.00036943937,0.00047022346,0.00044049651,0.00010321172,0.00034335887,0.0027463685,0.00023258053,0.0000032190385],"category_scores_gemma":[0.00004963194,0.0003655429,0.000036854923,0.00040029804,0.000040197985,0.0011462305,0.0083416905,0.0011228174,0.000003903044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006710786,0.000033982906,0.00014491663,0.00074318354,0.000039931692,0.00014709082,0.00015951369,0.7707188,0.000043846598,0.000671801,0.000007866877,0.22728236],"study_design_scores_gemma":[0.00039523072,0.00003213858,0.00008372013,0.00051314925,0.000013587702,0.0000056394574,0.00027745392,0.99746716,0.00034261204,0.0001568361,0.00030796896,0.0004045198],"about_ca_topic_score_codex":0.00011009143,"about_ca_topic_score_gemma":0.00017530393,"teacher_disagreement_score":0.7314768,"about_ca_system_score_codex":0.0001871063,"about_ca_system_score_gemma":0.00006915469,"threshold_uncertainty_score":0.99987966},"labels":[],"label_agreement":null},{"id":"W4200549627","doi":"10.32920/17190185","title":"Transfer Learning Based Performance Modeling And Effective Storage Management In Big Data Ecosystems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Workload; Computer science; Big data; Cache; Distributed computing; Transfer (computing); Data management; Database; Component (thermodynamics); Information repository; Computer data storage; Data modeling; Operating system","score_opus":0.04617086414538442,"score_gpt":0.2607581010266625,"score_spread":0.21458723688127812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200549627","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":[0.15786792,0.0006030941,0.8393997,0.00010764751,0.00042401758,0.0007203908,0.00001646661,0.0005991419,0.00026163226],"genre_scores_gemma":[0.88934475,0.00051180634,0.10966599,0.00004824722,0.000025806088,0.00016312943,0.00018438647,0.00002250361,0.000033395518],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970601,0.00015549871,0.00038019638,0.0016894673,0.0003332445,0.00038145646],"domain_scores_gemma":[0.9968773,0.00010425645,0.00006348377,0.002854529,0.00005006962,0.00005036131],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00078384357,0.00036943937,0.00047022346,0.00044049651,0.00010321172,0.00034335887,0.0027463685,0.00023258053,0.0000032190385],"category_scores_gemma":[0.00004963194,0.0003655429,0.000036854923,0.00040029804,0.000040197985,0.0011462305,0.0083416905,0.0011228174,0.000003903044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006710786,0.000033982906,0.00014491663,0.00074318354,0.000039931692,0.00014709082,0.00015951369,0.7707188,0.000043846598,0.000671801,0.000007866877,0.22728236],"study_design_scores_gemma":[0.00039523072,0.00003213858,0.00008372013,0.00051314925,0.000013587702,0.0000056394574,0.00027745392,0.99746716,0.00034261204,0.0001568361,0.00030796896,0.0004045198],"about_ca_topic_score_codex":0.00011009143,"about_ca_topic_score_gemma":0.00017530393,"teacher_disagreement_score":0.7314768,"about_ca_system_score_codex":0.0001871063,"about_ca_system_score_gemma":0.00006915469,"threshold_uncertainty_score":0.99987966},"labels":[],"label_agreement":null},{"id":"W4205197572","doi":"10.3390/electronics11020240","title":"Exploiting Data Compression for Adaptive Block Placement in Hybrid Caches","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; National Research Foundation","keywords":"Static random-access memory; Computer science; Cache; Block (permutation group theory); Latency (audio); Metadata; Embedded system; Parallel computing; Non-volatile memory; Computer hardware; Operating system","score_opus":0.058174122804709155,"score_gpt":0.2891994388777034,"score_spread":0.23102531607299423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205197572","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":[0.01626975,0.0038583328,0.977821,0.0007534738,0.00013932491,0.00050782895,0.00014692207,0.00042190615,0.00008148214],"genre_scores_gemma":[0.8480277,0.00011751267,0.15103315,0.00019116205,0.000024652078,0.00031247668,0.00019918458,0.000018432964,0.00007569997],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855053,0.00004711027,0.00018181985,0.00053902273,0.0002335966,0.000447908],"domain_scores_gemma":[0.9985021,0.00016050611,0.000105700805,0.001192684,0.000017773125,0.000021284486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037951473,0.00011428777,0.00013625373,0.00010553,0.00024858603,0.000032247422,0.0025158233,0.000016816017,0.0000042391753],"category_scores_gemma":[0.000095380885,0.0001239158,0.000017758159,0.00026850204,0.000022517415,0.0005098168,0.003861767,0.00033815065,0.000001921007],"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":[0.00038008727,0.00096425996,0.00022302732,0.00006793887,0.00011484961,0.00019687618,0.0017965862,0.17937054,0.016917363,0.2577066,0.0789724,0.46328947],"study_design_scores_gemma":[0.00090245093,0.0006458522,0.000013952141,0.000016004144,0.0000056193753,0.00003873691,0.00073279074,0.7438002,0.014729442,0.018076256,0.22068755,0.00035110587],"about_ca_topic_score_codex":0.000005113795,"about_ca_topic_score_gemma":0.000029464538,"teacher_disagreement_score":0.83175796,"about_ca_system_score_codex":0.00040336195,"about_ca_system_score_gemma":0.0001328325,"threshold_uncertainty_score":0.50531393},"labels":[],"label_agreement":null},{"id":"W4206104491","doi":"10.1109/access.2021.3138832","title":"IBU: An In-Block Update Address Mapping Scheme for Solid-State Drives","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Flash file system; Garbage collection; Firmware; Block (permutation group theory); Flash memory; Physical address; Table (database); Scheme (mathematics); Benchmark (surveying); Computer hardware; Parallel computing; Embedded system; Database; Computer memory; Garbage; Programming language; Semiconductor memory","score_opus":0.05397526347559226,"score_gpt":0.349166108731582,"score_spread":0.2951908452559897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206104491","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":[0.23076238,0.00020436154,0.7666851,0.00083673594,0.00054722326,0.00023870375,0.00004391617,0.00058097544,0.00010056585],"genre_scores_gemma":[0.75487894,0.000101710335,0.24406463,0.0006258508,0.00007115949,0.00012503701,0.00002827494,0.000024313616,0.00008008567],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982471,0.000037746766,0.00029801737,0.00072885776,0.0001942362,0.0004940587],"domain_scores_gemma":[0.99826604,0.00009943674,0.00012758063,0.0012806697,0.00015592195,0.0000703787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001713645,0.00018715215,0.00025565462,0.00020159909,0.00012540027,0.00044897807,0.0027774633,0.00008279933,0.000004914156],"category_scores_gemma":[0.00015318689,0.00019550911,0.0000462804,0.0007922728,0.00007823813,0.0033908924,0.0010240759,0.00019730294,0.00001682381],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000103074985,0.001206075,0.016224828,0.0007148074,0.00025311086,0.0029581687,0.0047584176,0.027398637,0.36816475,0.07361755,0.017959636,0.48664096],"study_design_scores_gemma":[0.0015549083,0.00008749991,0.003637506,0.00018329619,0.0000073626884,0.00006299838,0.00029370407,0.08070913,0.7782371,0.103609845,0.030500237,0.001116434],"about_ca_topic_score_codex":0.000012547541,"about_ca_topic_score_gemma":0.00016253587,"teacher_disagreement_score":0.5241166,"about_ca_system_score_codex":0.000059353028,"about_ca_system_score_gemma":0.00009681032,"threshold_uncertainty_score":0.797263},"labels":[],"label_agreement":null},{"id":"W4206667627","doi":"10.1109/access.2022.3143899","title":"Locally Repairable Codes Based on Permutation Cubes and Latin Squares","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Agencia Estatal de Investigación","keywords":"Circulant matrix; Notation; Permutation (music); Combinatorics; Discrete mathematics; Computer science; Mathematics; Algorithm; Arithmetic","score_opus":0.028554811832966726,"score_gpt":0.2925592658240619,"score_spread":0.2640044539910952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206667627","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":[0.19597471,0.00009923,0.8007305,0.0010982812,0.0002621761,0.00019459121,0.0000326287,0.00097095635,0.0006368809],"genre_scores_gemma":[0.97696364,0.0000056564536,0.022219792,0.0006402726,0.000012534503,0.0000765829,0.000009133226,0.000007976991,0.00006443499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898946,0.00005776373,0.00012928166,0.0003769776,0.00028042088,0.00016609837],"domain_scores_gemma":[0.99911153,0.00018070429,0.000077222016,0.00057018193,0.00003419853,0.00002614274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017935275,0.000098239114,0.000104691826,0.00019517046,0.00030635236,0.00018671987,0.00089481083,0.000025930576,0.000020040326],"category_scores_gemma":[0.000099211014,0.000096177304,0.000018226205,0.0005131685,0.00006167094,0.00085551996,0.00047484876,0.00015739881,0.0000050125245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097354074,0.00028300102,0.009653407,0.000086522574,0.00002017659,0.00033510945,0.00068855507,0.75467384,0.0029003113,0.052542236,0.012646402,0.16607311],"study_design_scores_gemma":[0.00039362555,0.00032029077,0.002897046,0.000017722828,0.000004104849,0.000011197612,0.00012955711,0.9640067,0.011291493,0.016286725,0.0043826564,0.00025887528],"about_ca_topic_score_codex":0.00004414416,"about_ca_topic_score_gemma":0.000015195084,"teacher_disagreement_score":0.78098893,"about_ca_system_score_codex":0.00006171693,"about_ca_system_score_gemma":0.000041172956,"threshold_uncertainty_score":0.39219967},"labels":[],"label_agreement":null},{"id":"W4221144283","doi":"10.1007/s41781-022-00086-2","title":"Constraints on Future Analysis Metadata Systems in High Energy Physics","year":2022,"lang":"en","type":"article","venue":"Computing and Software for Big Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Division of Physics; Science and Technology Facilities Council; European Commission; CERN; High Energy Physics; U.S. Department of Energy; H2020 European Research Council; Office of Science; National Science Foundation","keywords":"Metadata; Computer science; Scope (computer science); Reinterpretation; Meta Data Services; Data element; Data science; World Wide Web; Metadata modeling; Information retrieval","score_opus":0.022744865202540876,"score_gpt":0.26073315954809634,"score_spread":0.23798829434555546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221144283","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":[0.01955426,0.00032505917,0.9783975,0.00012489747,0.0010430422,0.0001093884,0.00009084572,0.00034420108,0.000010830959],"genre_scores_gemma":[0.91631645,0.000007630388,0.08340623,0.000135574,0.0000719467,0.000020285392,0.000020685387,0.00000513284,0.000016046912],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802554,0.00004941134,0.00021935465,0.00083039777,0.000464973,0.0004103312],"domain_scores_gemma":[0.9985634,0.00030446606,0.00015424458,0.000822416,0.000090935566,0.00006450457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008070763,0.00014981817,0.00027917087,0.00047141802,0.0008515213,0.00031195866,0.0019668557,0.000030426296,4.801005e-7],"category_scores_gemma":[0.00024949078,0.00014203705,0.000043421653,0.004443988,0.0004410639,0.00047908557,0.0016016321,0.00017816956,3.2907647e-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":[0.0000036894228,0.0000455906,0.0006997318,0.000011445583,0.000023579618,0.000015372365,0.00018922126,0.059287425,0.00004934962,0.4065612,0.000096605094,0.5330168],"study_design_scores_gemma":[0.001254874,0.00068592234,0.006610215,0.00006390342,0.0000867971,0.00007129292,0.0015202104,0.92308426,0.000903123,0.055554993,0.00892035,0.0012440674],"about_ca_topic_score_codex":0.00007762425,"about_ca_topic_score_gemma":0.000009031916,"teacher_disagreement_score":0.8967622,"about_ca_system_score_codex":0.00012429312,"about_ca_system_score_gemma":0.00013722524,"threshold_uncertainty_score":0.65492994},"labels":[],"label_agreement":null},{"id":"W4225291709","doi":"10.1145/3529538.3529992","title":"SYCLops: A SYCL Specific LLVM to MLIR Converter","year":2022,"lang":"en","type":"article","venue":"International Workshop on OpenCL","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Exploit; Computer science; Computer security","score_opus":0.029261833443367354,"score_gpt":0.2936517919966401,"score_spread":0.26438995855327274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225291709","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":[0.0037052615,0.00010897732,0.9266546,0.034901172,0.0045071044,0.0004702254,0.000091004804,0.0007441057,0.028817581],"genre_scores_gemma":[0.8823634,0.00004509804,0.096451856,0.011055019,0.00018196042,0.0004371525,0.000056424287,0.00003498361,0.009374105],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979703,0.00004590236,0.00026377186,0.0006655559,0.00076802395,0.00028648804],"domain_scores_gemma":[0.9985827,0.00017692732,0.00009316807,0.000985239,0.00008040941,0.00008155593],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00023203173,0.00017612465,0.00015267184,0.0003395493,0.0002310051,0.00023298664,0.0045599123,0.00004091781,0.0012394807],"category_scores_gemma":[0.00013204546,0.00018044277,0.00006242917,0.0006262277,0.000044867815,0.0005838214,0.003318797,0.00041588114,0.0010751919],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000867028,0.00023128737,0.00012357738,0.0000019298725,0.00004909011,0.00031010094,0.0006953892,0.004712046,0.0008975031,0.50488466,0.22765806,0.26034966],"study_design_scores_gemma":[0.00032567815,0.000106606785,0.0005329105,0.00002779631,0.0000011921042,0.000058387297,0.00031212976,0.008003465,0.0005125393,0.008670332,0.98113704,0.00031190377],"about_ca_topic_score_codex":0.000008072661,"about_ca_topic_score_gemma":0.000003933128,"teacher_disagreement_score":0.8786581,"about_ca_system_score_codex":0.00041506623,"about_ca_system_score_gemma":0.000037213464,"threshold_uncertainty_score":0.9997026},"labels":[],"label_agreement":null},{"id":"W4230890328","doi":"10.1145/1272998.1273018","title":"Secure file system versioning at the block level","year":2007,"lang":"en","type":"article","venue":"ACM SIGOPS Operating Systems Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Operating system; File system; Virtual file system; Stub file; Unix file types; Versioning file system; Self-certifying File System; Software versioning; File Control Block; SSH File Transfer Protocol; Kernel (algebra); sysfs; Computer file; Database; Linux kernel; Computer security; Software","score_opus":0.03936023523260051,"score_gpt":0.2875078219079759,"score_spread":0.2481475866753754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230890328","genre_codex":"review","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":[0.0032716205,0.59832084,0.37595254,0.0036143085,0.0033478984,0.0048122676,0.00043887532,0.004199378,0.006042292],"genre_scores_gemma":[0.69382125,0.00944597,0.28264016,0.0035475227,0.00087667257,0.0009291253,0.00027680947,0.00018385965,0.008278599],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997319,0.00020607574,0.00077249727,0.0006394998,0.00052711304,0.0005358022],"domain_scores_gemma":[0.99519384,0.0009999165,0.00038829917,0.0031431392,0.00019053984,0.00008426179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002242306,0.0003017466,0.00052872015,0.00006241348,0.00083098724,0.00023020261,0.0034641442,0.00011673349,0.000035518853],"category_scores_gemma":[0.002377817,0.00019390021,0.000105375126,0.00080690923,0.000075239914,0.0005591424,0.002488664,0.00034681035,0.0005024203],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005625576,0.000068018286,0.00043556746,0.020184401,0.00022047499,0.00081115676,0.0013732738,0.002204565,0.0048958003,0.090400666,0.76151556,0.11788487],"study_design_scores_gemma":[0.00056239526,0.0001850202,0.00018130227,0.049130943,0.00009589691,0.0032004945,0.0022877133,0.011400499,0.0025370477,0.00004357228,0.9288688,0.0015063363],"about_ca_topic_score_codex":0.000080471065,"about_ca_topic_score_gemma":0.000022544327,"teacher_disagreement_score":0.6905497,"about_ca_system_score_codex":0.0003806387,"about_ca_system_score_gemma":0.00006383325,"threshold_uncertainty_score":0.7907021},"labels":[],"label_agreement":null},{"id":"W4233220155","doi":"10.1109/iemcon.2015.7344509","title":"Device-independent on demand synchronization in the Unico file system","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Metadata; Synchronization (alternating current); File system; Distributed File System; Self-certifying File System; Torrent file; State (computer science); Computer file; Operating system; Database; Journaling file system; Computer network","score_opus":0.030690598143817374,"score_gpt":0.2612243551789642,"score_spread":0.23053375703514684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233220155","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":[0.0025871228,0.00009489139,0.9854043,0.00069658906,0.00014958967,0.00023053632,0.000009876974,0.0005882626,0.010238817],"genre_scores_gemma":[0.9754157,0.0000027362025,0.024171289,0.00023008669,0.000016080625,0.000033386594,0.0000132446585,0.000004074596,0.00011336988],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991145,0.00006740996,0.00013287738,0.00023397375,0.00029339944,0.00015780506],"domain_scores_gemma":[0.99895513,0.00012421147,0.000051365656,0.0008009224,0.000042146155,0.000026220338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003389954,0.00008319821,0.000080962374,0.00008878265,0.000044981152,0.0000871873,0.0012683676,0.000053266558,0.000009742733],"category_scores_gemma":[0.00015250253,0.000052321135,0.000011241093,0.00045561136,0.000022262257,0.00042177286,0.00028020737,0.00011272523,0.00021749515],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007170389,0.00010845551,0.0005423417,0.000032219188,0.000007489549,0.00017991831,0.0011184996,0.011044774,0.00001730276,0.897314,0.052221723,0.037406113],"study_design_scores_gemma":[0.0020650362,0.00065776694,0.0028685266,0.00032625592,0.000011072627,0.0002951555,0.013592282,0.8990235,0.003479396,0.021040276,0.05571223,0.00092855527],"about_ca_topic_score_codex":0.000037822792,"about_ca_topic_score_gemma":0.00011470737,"teacher_disagreement_score":0.9728286,"about_ca_system_score_codex":0.00019543193,"about_ca_system_score_gemma":0.000045967714,"threshold_uncertainty_score":0.27955326},"labels":[],"label_agreement":null},{"id":"W4233695695","doi":"10.1109/iwqos.2012.6245967","title":"On the impact of virtualization on Dropbox-like cloud file storage/synchronization services","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Cloud storage; Cloud computing; Synchronization (alternating current); Bottleneck; Server; Operating system; Retrievability; File sharing; Computer network; Virtualization; Object storage; Provisioning; Distributed computing; The Internet; Computer data storage; Embedded system; World Wide Web","score_opus":0.01318872587603248,"score_gpt":0.2652229362341421,"score_spread":0.25203421035810963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233695695","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":[0.05631229,0.000065493885,0.94043255,0.00017878617,0.00031590683,0.00022840554,0.00007779713,0.0005370156,0.0018517488],"genre_scores_gemma":[0.99215376,0.000014412731,0.007276465,0.0002585706,0.000050535524,0.000014765252,0.00007112562,0.000011742508,0.00014859923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990232,0.00006458736,0.00017470894,0.00021592647,0.00027488876,0.0002466836],"domain_scores_gemma":[0.9983997,0.00030676092,0.00017700157,0.0010055875,0.000070944516,0.000040037427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018614683,0.00015020843,0.00012273728,0.000114475544,0.00011209249,0.00004954902,0.00094305445,0.000074943455,0.0004573062],"category_scores_gemma":[0.00012998536,0.00008934723,0.000050182916,0.0005810427,0.000056060464,0.000938468,0.00020862381,0.000107747306,0.00016813078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020632317,0.0003298029,0.0005795931,0.000022889064,0.00004074163,0.0000015491906,0.0012090731,0.015978925,0.0012989904,0.905836,0.052717365,0.021964457],"study_design_scores_gemma":[0.0012853405,0.003507769,0.026590677,0.0003694666,0.000032764798,0.000026674246,0.0013871817,0.8331577,0.0460992,0.07414587,0.01171268,0.0016846524],"about_ca_topic_score_codex":0.00006323097,"about_ca_topic_score_gemma":0.0000055370856,"teacher_disagreement_score":0.9358415,"about_ca_system_score_codex":0.0001309294,"about_ca_system_score_gemma":0.000025899782,"threshold_uncertainty_score":0.50071824},"labels":[],"label_agreement":null},{"id":"W4233993544","doi":"10.1007/978-1-4939-7131-2_100254","title":"Data Storage for Networked Data","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science","score_opus":0.14906528555904244,"score_gpt":0.3216913810429016,"score_spread":0.17262609548385918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233993544","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.82718e-8,0.0007319147,0.8510807,0.000401899,0.0008957623,0.0005183884,0.0057809595,0.0015799539,0.1390104],"genre_scores_gemma":[0.000005232521,0.00021744292,0.6795657,0.00032505186,0.0005517339,0.000010252671,0.008617684,0.00006033555,0.31064656],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99657017,0.000007501773,0.00039553604,0.0022344338,0.0003469368,0.00044544568],"domain_scores_gemma":[0.9748611,0.00025934417,0.00032256093,0.02437178,0.00010804536,0.0000772104],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.00050980144,0.00044630063,0.0004587482,0.00015503974,0.0001474907,0.00021597648,0.029271001,0.00042895647,0.00024850297],"category_scores_gemma":[0.0001695087,0.00039717098,0.000043270786,0.000066082095,0.00029008705,0.0023631973,0.032726172,0.00034676993,0.00049408403],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002697398,0.000004733344,4.3495152e-8,0.000014233612,0.000037006757,0.000014818175,0.0000036287438,0.0000032702367,0.0000014496026,0.30252394,0.6048431,0.09255111],"study_design_scores_gemma":[0.00012361392,0.000058126556,1.0816045e-7,0.00004243626,0.000022033493,0.000009383696,0.0000022789186,0.062812135,0.000005030945,0.13270575,0.803814,0.00040509383],"about_ca_topic_score_codex":0.000003917993,"about_ca_topic_score_gemma":0.0000978179,"teacher_disagreement_score":0.19897093,"about_ca_system_score_codex":0.00006160227,"about_ca_system_score_gemma":0.00014116411,"threshold_uncertainty_score":0.999848},"labels":[],"label_agreement":null},{"id":"W4234459897","doi":"10.22215/etd/2007-07899","title":"A parallel external memory system","year":2007,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage","funders":"","keywords":"Computer science; Humanities; Art","score_opus":0.015872080379191227,"score_gpt":0.290707446289043,"score_spread":0.27483536590985175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234459897","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072334544,0.00085145433,0.9180619,0.000017423867,0.0013013756,0.00020450792,0.000003744478,0.0026960033,0.076140255],"genre_scores_gemma":[0.018662697,0.000041572464,0.9398846,0.00007848088,0.00010766448,0.000058971935,0.00011660965,0.00003384747,0.04101557],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983067,0.0000146411385,0.00032264288,0.00059456646,0.00042303724,0.0003384266],"domain_scores_gemma":[0.9982633,0.00005291092,0.00023250439,0.0013035694,0.00009020911,0.00005750445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017873448,0.00027101772,0.00028313717,0.00031033397,0.000084252366,0.00011583926,0.0023798626,0.00034230636,0.000016378595],"category_scores_gemma":[0.000040539733,0.00023966854,0.000081797385,0.00030011972,0.000024167148,0.00049983384,0.00022070645,0.000364459,0.00033641164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031762705,0.000033389715,0.0000051235643,0.00034078333,0.000031677388,0.0006019363,0.00027155175,0.00007560774,0.00063295016,0.7036827,0.003888452,0.29040405],"study_design_scores_gemma":[0.010017597,0.0027143578,0.009578975,0.012982695,0.0005148809,0.0036197114,0.075278066,0.1664172,0.3314316,0.22813158,0.13439693,0.024916431],"about_ca_topic_score_codex":0.000042245945,"about_ca_topic_score_gemma":0.000091270136,"teacher_disagreement_score":0.47555113,"about_ca_system_score_codex":0.00015546358,"about_ca_system_score_gemma":0.00007451584,"threshold_uncertainty_score":0.97734},"labels":[],"label_agreement":null},{"id":"W4235392844","doi":"10.1007/978-1-4899-7993-3_689-2","title":"Database Middleware","year":2016,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Database; Computer science; Middleware (distributed applications)","score_opus":0.02228997584661638,"score_gpt":0.24154453570176176,"score_spread":0.2192545598551454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235392844","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000028940642,0.007359209,0.41260615,0.0001115616,0.0027740654,0.00081209216,0.016235774,0.00097496883,0.5591233],"genre_scores_gemma":[0.00041904816,0.015804453,0.11131223,0.00008454173,0.0013957298,0.00019353339,0.0035793425,0.00030116815,0.86691],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956317,0.000053740412,0.0011565541,0.0015009746,0.0010548467,0.0006022062],"domain_scores_gemma":[0.99115914,0.0004146236,0.0011733852,0.006772049,0.0002648231,0.00021600373],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00047927647,0.00079728325,0.0010739515,0.00061429065,0.00011077307,0.000067904555,0.004431432,0.00045135652,0.00011475481],"category_scores_gemma":[0.00034747116,0.00065058557,0.00018781367,0.00014840833,0.0003460127,0.0019357768,0.0035150605,0.00058903306,0.0009980808],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000082306715,0.000026859127,0.00000992473,0.00059234345,0.000087967055,0.00038957488,0.000038714872,0.0000028140398,0.00017480923,0.93046063,0.05196432,0.016243784],"study_design_scores_gemma":[0.00036720838,0.00007936604,0.0000014298145,0.002355418,0.00004550408,0.000088418725,0.000020373194,0.00010341235,0.00017125528,0.0057034884,0.9901752,0.00088893675],"about_ca_topic_score_codex":0.000043381442,"about_ca_topic_score_gemma":0.000018705365,"teacher_disagreement_score":0.93821084,"about_ca_system_score_codex":0.0001685923,"about_ca_system_score_gemma":0.00031224804,"threshold_uncertainty_score":0.99977976},"labels":[],"label_agreement":null},{"id":"W4235459437","doi":"10.1145/2491899.2465563","title":"FTL <sup>2</sup>","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cache; NAND gate; Operating system; Power consumption; Garbage collection; Flash (photography); Parallel computing; Power (physics); Garbage; Logic gate; Programming language; Algorithm","score_opus":0.014082851279558911,"score_gpt":0.2326239375034731,"score_spread":0.2185410862239142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235459437","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008342519,0.000047939982,0.97267646,0.0024792417,0.000051412422,0.00012268873,8.389575e-7,0.0019622503,0.014316661],"genre_scores_gemma":[0.36936146,0.00000877911,0.6276795,0.00068569125,0.00001720986,0.00003397747,0.0000013363962,0.000005447692,0.0022065502],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992446,0.000008677291,0.00010430967,0.00027547378,0.00013212259,0.00023487366],"domain_scores_gemma":[0.99884623,0.00004608187,0.000025335827,0.0009974529,0.00004207957,0.00004280697],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004479916,0.00008751414,0.00008171835,0.000068903304,0.00005337122,0.00011483148,0.0013850424,0.00004807689,0.00023709533],"category_scores_gemma":[0.00007834994,0.00006835441,0.0000216502,0.0002689638,0.00005672834,0.0014517915,0.0007609814,0.00009381681,0.00327361],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.707053e-7,0.000027554543,0.00022013877,0.000003647751,0.000006347919,0.000012040074,0.00013556701,0.00040753084,0.000578514,0.5567481,0.0772304,0.36462986],"study_design_scores_gemma":[0.0004295474,0.0001483575,0.0014255571,0.00001242741,0.0000028229529,0.00005893877,0.00045175623,0.3950238,0.018140266,0.4164569,0.16712752,0.0007221166],"about_ca_topic_score_codex":0.000045809476,"about_ca_topic_score_gemma":0.000001277284,"teacher_disagreement_score":0.39461625,"about_ca_system_score_codex":0.00002247232,"about_ca_system_score_gemma":0.000012188954,"threshold_uncertainty_score":0.99750245},"labels":[],"label_agreement":null},{"id":"W4236224329","doi":"10.22215/etd/2009-08766","title":"Simulation analysis of multi-channel ARQ protocols","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Computer science; Channel (broadcasting); Computer network","score_opus":0.04385516902744891,"score_gpt":0.3684452318343295,"score_spread":0.3245900628068806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236224329","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034151977,0.000039624418,0.99372905,0.000014655965,0.00005518548,0.004631589,0.00001871774,0.0006025347,0.0005671272],"genre_scores_gemma":[0.35252032,0.000017994731,0.6345592,0.00008448399,0.00002713784,0.004839301,0.002204648,0.00003711327,0.0057098204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985004,0.000021784848,0.0004385726,0.0005243937,0.0003333792,0.00018146477],"domain_scores_gemma":[0.9978532,0.00010963657,0.00051468343,0.0012349836,0.00025919772,0.000028254099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011224316,0.00022577988,0.000502106,0.0010629764,0.000045435176,0.00005049019,0.0012951542,0.0002841936,0.000011465292],"category_scores_gemma":[0.00026893415,0.00020578773,0.00017936336,0.0020667808,0.000019838413,0.000517334,0.00008854338,0.00017269004,0.000010142759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020349735,0.00021121804,0.000021817908,0.00008225507,0.00040335508,0.000007809038,0.00041475566,0.86421824,0.0003803887,0.00704284,0.00009493799,0.12710205],"study_design_scores_gemma":[0.000162636,0.000072471565,0.0026389281,0.000047838777,0.00014223429,8.44261e-8,0.00009908052,0.9882289,0.005208698,0.0028792133,0.00025699625,0.00026293122],"about_ca_topic_score_codex":0.000027149661,"about_ca_topic_score_gemma":0.00032321637,"teacher_disagreement_score":0.35916987,"about_ca_system_score_codex":0.000049747257,"about_ca_system_score_gemma":0.000048450274,"threshold_uncertainty_score":0.83917797},"labels":[],"label_agreement":null},{"id":"W4238631751","doi":"10.1145/2820615","title":"RAIDShield","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"RAID; Computer science; Reliability (semiconductor); Reliability engineering; Operating system","score_opus":0.05061019071836591,"score_gpt":0.2835157450749115,"score_spread":0.23290555435654559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238631751","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":[0.0017827227,0.00008936052,0.9921748,0.0023355852,0.0006178429,0.000107150205,0.000013380067,0.0013983664,0.001480762],"genre_scores_gemma":[0.64823985,0.000015645683,0.35045925,0.00041469446,0.000022385268,0.00003527665,0.0000019914553,0.00001264913,0.0007982454],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989184,0.000032114276,0.00014530034,0.00037084403,0.00028725664,0.00024606887],"domain_scores_gemma":[0.99762744,0.000118505784,0.00004466872,0.0020302262,0.000058024925,0.00012115039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016671093,0.00014282974,0.00013544112,0.00020259709,0.00011523575,0.00006998049,0.0018018379,0.00009071783,0.000023636268],"category_scores_gemma":[0.00015445586,0.00013559661,0.000053806587,0.0005845734,0.00007196923,0.00091679645,0.000048719594,0.00029100443,0.00042019342],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038510985,0.00035833823,0.000018038441,0.0000100527295,0.000052074516,0.00021124513,0.0011744379,0.00960164,0.0008362129,0.040500466,0.010474251,0.9367247],"study_design_scores_gemma":[0.0038658702,0.0020227523,0.00026543278,0.00007492263,0.000054795913,0.0003284398,0.001731258,0.015456443,0.07346743,0.32632643,0.57421565,0.0021905748],"about_ca_topic_score_codex":0.000014537109,"about_ca_topic_score_gemma":0.000011429181,"teacher_disagreement_score":0.93453413,"about_ca_system_score_codex":0.0001083005,"about_ca_system_score_gemma":0.000057536723,"threshold_uncertainty_score":0.5529469},"labels":[],"label_agreement":null},{"id":"W4240191654","doi":"10.1145/2675113","title":"Checking the Integrity of Transactional Mechanisms","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Journaling file system; Commit; File system; Versioning file system; Operating system; Database transaction; Overhead (engineering); Database; Computer file","score_opus":0.027528368324329887,"score_gpt":0.2631868135703679,"score_spread":0.235658445246038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240191654","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":[0.0019485606,0.000022848266,0.99446577,0.0022378769,0.00044603331,0.00013807091,0.000022210455,0.00044262744,0.00027599986],"genre_scores_gemma":[0.7758621,0.000013075299,0.22382332,0.00017970621,0.000012574876,0.00002922702,0.0000013232889,0.000009638766,0.00006905149],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987317,0.00008499852,0.00024330591,0.0003518686,0.00036527147,0.00022290999],"domain_scores_gemma":[0.9976214,0.00042011595,0.00010859239,0.0017367869,0.00007238689,0.000040692004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042001394,0.0001644135,0.0001862652,0.00015493835,0.00027453023,0.000040032402,0.0020484289,0.000108916225,0.000048009057],"category_scores_gemma":[0.00010710686,0.00012235784,0.00011975498,0.0005090169,0.00015379439,0.0005278703,0.000026382604,0.0005869482,0.000029613966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030266508,0.0002670187,0.000003836905,0.000026625665,0.00006928285,0.000005504598,0.0006445121,0.008866537,0.014352631,0.32468024,0.00011884788,0.6509347],"study_design_scores_gemma":[0.0012139197,0.00075213006,0.000742709,0.000099526485,0.000068802896,0.00010437683,0.0006251669,0.052926786,0.3486441,0.5755824,0.018421885,0.00081820897],"about_ca_topic_score_codex":0.000026707889,"about_ca_topic_score_gemma":0.00002174621,"teacher_disagreement_score":0.7739135,"about_ca_system_score_codex":0.000064200234,"about_ca_system_score_gemma":0.000036173235,"threshold_uncertainty_score":0.49896082},"labels":[],"label_agreement":null},{"id":"W4240344883","doi":"10.2118/2009-190","title":"Partial SAGD Applications in the Jackfish SAGD Project","year":2009,"lang":"en","type":"article","venue":"Canadian International Petroleum Conference","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Devon Energy (Canada)","funders":"","keywords":"Petroleum engineering; Computer science; Environmental science; Engineering","score_opus":0.026958581891589704,"score_gpt":0.27407399619274025,"score_spread":0.24711541430115055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240344883","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":[0.047683626,0.00014659936,0.79476976,0.05938462,0.0006553927,0.00086003746,0.00028677762,0.00052001973,0.09569318],"genre_scores_gemma":[0.992765,0.000020943004,0.0052489936,0.0014950611,0.000071793445,0.00012812259,0.000056622357,0.000004167902,0.00020931495],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986948,0.00003733317,0.0002164912,0.0003971167,0.00029729295,0.0003569843],"domain_scores_gemma":[0.99894124,0.00007560271,0.000076676435,0.0007154666,0.00010529348,0.000085725325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017668647,0.00014252143,0.00011130161,0.0003854505,0.00012217983,0.00031098461,0.0032845614,0.000069680325,0.000030691495],"category_scores_gemma":[0.00013285459,0.00012053694,0.00003723487,0.00041783426,0.00008978191,0.0006017458,0.00008878772,0.00028257846,0.00005732126],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002297766,0.00003313346,0.0013778845,0.0000013046189,0.0000067443325,0.00004799152,0.00033141297,0.00024882797,0.00006521096,0.97462535,0.004477323,0.01878249],"study_design_scores_gemma":[0.0005561249,0.00014260519,0.046999197,0.00004254942,0.0000065355134,0.00008388921,0.0007714994,0.04787062,0.00040866307,0.09449249,0.8080097,0.0006161658],"about_ca_topic_score_codex":0.007922796,"about_ca_topic_score_gemma":0.056273736,"teacher_disagreement_score":0.94508135,"about_ca_system_score_codex":0.0002884755,"about_ca_system_score_gemma":0.00056847674,"threshold_uncertainty_score":0.9986835},"labels":[],"label_agreement":null},{"id":"W4242270633","doi":"10.1109/hoti.2007.4296815","title":"Assessing the Ability of Computation/Communication Overlap and Communication Progress in Modern Interconnects","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Ontario Innovation Trust","keywords":"Myrinet; InfiniBand; Computer science; Ethernet; Computation; Latency (audio); Implementation; Computer network; Benchmark (surveying); Computer architecture; Distributed computing; Telecommunications; Message passing","score_opus":0.03324145928726949,"score_gpt":0.35115443437687877,"score_spread":0.31791297508960925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242270633","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":[0.37972656,0.0007054222,0.6182032,0.0007954603,0.0000098272785,0.00012967351,3.0220653e-7,0.00010597848,0.00032355147],"genre_scores_gemma":[0.69851804,0.000024872132,0.30141336,0.000031415704,8.3176474e-7,0.000005635283,0.0000028346954,0.0000022856964,7.3119804e-7],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999187,0.0001119527,0.0002843764,0.00017364684,0.00012508013,0.000117928044],"domain_scores_gemma":[0.9978598,0.00070146204,0.00016383413,0.0011747696,0.00008622448,0.000013916138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011875373,0.00007106204,0.000105520354,0.000092234324,0.000093209834,0.0000994362,0.0010678387,0.000047711153,4.3727005e-7],"category_scores_gemma":[0.00015097244,0.000053395324,0.000012948065,0.0003420778,0.00035369082,0.0014183131,0.000981004,0.00017022119,4.1623198e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036715535,0.00008718084,0.028283982,0.000020284328,0.000004746898,6.8964306e-7,0.0020053452,0.00026126078,0.0007173658,0.11722507,0.000010541396,0.8513799],"study_design_scores_gemma":[0.00033959048,0.000034621087,0.41447082,0.000091206784,0.0000027950507,0.000008940942,0.003324393,0.34558475,0.0039000462,0.23206012,0.000029926478,0.00015277394],"about_ca_topic_score_codex":0.00004003035,"about_ca_topic_score_gemma":0.00011941816,"teacher_disagreement_score":0.8512271,"about_ca_system_score_codex":0.00005530414,"about_ca_system_score_gemma":0.000017142162,"threshold_uncertainty_score":0.2177398},"labels":[],"label_agreement":null},{"id":"W4242345272","doi":"10.1007/978-0-387-39940-9_2791","title":"I/O cache","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cache; Computer science; Parallel computing","score_opus":0.018923295430605974,"score_gpt":0.2410258519749446,"score_spread":0.22210255654433864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242345272","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000018633275,0.0075421818,0.18867518,0.00009363904,0.0014068029,0.00057949836,0.0013781679,0.0008212356,0.7995014],"genre_scores_gemma":[0.00044024436,0.009397545,0.123120345,0.00008950273,0.0007637286,0.00005656625,0.0013731346,0.00013054309,0.8646284],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970716,0.00003107406,0.00083168474,0.0009415861,0.0007346045,0.00038943518],"domain_scores_gemma":[0.99475586,0.00016792254,0.00080796407,0.0039978554,0.00014997847,0.00012041136],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003389542,0.00054070895,0.0008282332,0.00042206928,0.00006812611,0.00005412805,0.0030527897,0.00040253988,0.000030343786],"category_scores_gemma":[0.00015941815,0.0005114346,0.00014066925,0.00012667954,0.0001607266,0.0009220557,0.0011843351,0.0006021601,0.00033253472],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031964194,0.000022663473,0.00000273072,0.00020052718,0.00004722579,0.00024061801,0.00004713256,0.000025261907,0.00003914215,0.8912645,0.048570987,0.059536],"study_design_scores_gemma":[0.00016275462,0.00009174534,0.0000027995777,0.00052628206,0.000029163824,0.000063455926,0.000012398458,0.00024870684,0.000056869532,0.008372604,0.9898789,0.00055433466],"about_ca_topic_score_codex":0.00005269548,"about_ca_topic_score_gemma":0.000011318216,"teacher_disagreement_score":0.9413079,"about_ca_system_score_codex":0.00011608046,"about_ca_system_score_gemma":0.00018906928,"threshold_uncertainty_score":0.99973375},"labels":[],"label_agreement":null},{"id":"W4242582993","doi":"10.22215/etd/2006-07640","title":"CASH2 - a multiple categorization file management tool for UNIX/LINUX file systems","year":2006,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage","funders":"","keywords":"Unix; Operating system; Computer science; Software","score_opus":0.011234144255587324,"score_gpt":0.24414435500275494,"score_spread":0.2329102107471676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242582993","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007811504,0.00016321,0.98104745,0.0000228547,0.001331106,0.0019974906,0.005663858,0.0017459434,0.007949968],"genre_scores_gemma":[0.0063085505,0.000047371486,0.5687147,0.00004985128,0.00016768363,0.0051811985,0.16652405,0.000100893434,0.25290573],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99790263,0.000021016625,0.0004807336,0.00084451283,0.00034251867,0.0004085948],"domain_scores_gemma":[0.99778146,0.0003326952,0.00037612292,0.0012681251,0.00020871604,0.00003286372],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009750995,0.00037216864,0.00034868717,0.00034548048,0.00020118698,0.0002969713,0.0014609217,0.00033798433,0.0002811696],"category_scores_gemma":[0.00021823171,0.00036026607,0.00009605858,0.00051270373,0.000020590242,0.00067660905,0.00021634025,0.0001648665,0.00010911924],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012315269,0.000066899804,0.000003994656,0.0006197094,0.000048791135,0.000028696331,0.00007795866,0.0022752243,0.0000596859,0.08863409,0.87700695,0.031165687],"study_design_scores_gemma":[0.000954274,0.00020911568,0.0005534194,0.0005345526,0.00008517888,0.000013249239,0.0015922334,0.2820165,0.002375151,0.007956228,0.70183456,0.0018755783],"about_ca_topic_score_codex":0.00031192758,"about_ca_topic_score_gemma":0.00039974632,"teacher_disagreement_score":0.41233277,"about_ca_system_score_codex":0.00021185138,"about_ca_system_score_gemma":0.00006414815,"threshold_uncertainty_score":0.9998849},"labels":[],"label_agreement":null},{"id":"W4243637967","doi":"10.22215/etd/2005-08016","title":"Compressing data cube in parallel OLAP systems","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Library and Archives Canada","funders":"","keywords":"Online analytical processing; Cube (algebra); Computer science; Data cube; Database; Information retrieval; Data mining; Data warehouse; Mathematics; Combinatorics","score_opus":0.054154249135968516,"score_gpt":0.3265790195086865,"score_spread":0.272424770372718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243637967","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008619103,0.0069251615,0.9626837,0.00017031663,0.0018112358,0.0005787118,0.00008355137,0.0019699738,0.024915475],"genre_scores_gemma":[0.112613045,0.00059321715,0.8632413,0.00012120923,0.0002190271,0.00010892115,0.009668934,0.00007413449,0.01336021],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99783343,0.000039479066,0.00044930025,0.0009756954,0.00034919076,0.00035290935],"domain_scores_gemma":[0.99583566,0.00012152071,0.00025414894,0.0037032797,0.000047206366,0.000038153565],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00020183077,0.000287228,0.00039544815,0.00032754918,0.00007101084,0.00033175974,0.0064441734,0.0003136896,0.000008286279],"category_scores_gemma":[0.00013689481,0.00026846482,0.000023788332,0.00040491947,0.000029554729,0.0020493574,0.0011514176,0.0004911852,0.00009218771],"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":[0.000038652644,0.00031039058,0.00027013718,0.0007384929,0.00008421929,0.00042732476,0.0010778847,0.01849889,0.00058140705,0.45559624,0.04190445,0.48047194],"study_design_scores_gemma":[0.0008128651,0.00004455457,0.0012141588,0.0011104239,0.000020033387,0.000031088282,0.0026135298,0.88243604,0.00035676893,0.0040636905,0.105662316,0.0016345187],"about_ca_topic_score_codex":0.00019820278,"about_ca_topic_score_gemma":0.0011958677,"teacher_disagreement_score":0.86393714,"about_ca_system_score_codex":0.00010377913,"about_ca_system_score_gemma":0.00010180684,"threshold_uncertainty_score":0.99997675},"labels":[],"label_agreement":null},{"id":"W4244409740","doi":"10.1145/782848.782851","title":"miNI","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cache; Virtual memory; Embedded system; Distributed computing; Memory management; Operating system; Semiconductor memory","score_opus":0.018976531421435378,"score_gpt":0.2514246500003594,"score_spread":0.23244811857892403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244409740","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00055392645,0.00004423183,0.93242884,0.00029871028,0.00008681826,0.000022572127,1.8369606e-7,0.00071311154,0.06585163],"genre_scores_gemma":[0.20664598,0.0000036898161,0.7920199,0.00021790442,0.000001880112,0.000002982353,1.3134502e-7,0.0000014853157,0.0011060428],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99965614,0.000006444089,0.000043864413,0.00013446853,0.000057097397,0.00010200226],"domain_scores_gemma":[0.9994194,0.000021113216,0.000011299324,0.0005229585,0.000009960333,0.000015272652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000044924192,0.000035773966,0.000034236615,0.000029801233,0.000024179775,0.000022668402,0.0004927864,0.000018461677,0.000030464227],"category_scores_gemma":[0.00010971846,0.000028949002,0.000009042101,0.0001733994,0.000020971604,0.00032735168,0.00010791227,0.000033070897,0.00021188229],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.5370682e-8,0.0000042395736,0.00004010472,2.760394e-7,5.3703843e-7,0.000004849983,0.000007560363,0.000002365114,0.00020408162,0.97932863,0.0029888717,0.017418457],"study_design_scores_gemma":[0.00014175333,0.000036463814,0.00014720463,0.0000016426777,5.7809393e-7,0.000038036764,0.000056590685,0.000893712,0.08647491,0.3153545,0.5966721,0.00018248706],"about_ca_topic_score_codex":8.47474e-7,"about_ca_topic_score_gemma":9.702064e-7,"teacher_disagreement_score":0.6639741,"about_ca_system_score_codex":0.000008649119,"about_ca_system_score_gemma":0.00000953146,"threshold_uncertainty_score":0.27233887},"labels":[],"label_agreement":null},{"id":"W4245247914","doi":"10.1145/1357010.1352598","title":"Parallax","year":2008,"lang":"en","type":"article","venue":"ACM SIGOPS Operating Systems Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Converged storage; Snapshot (computer storage); Computer data storage; Virtualization; Storage virtualization; Architecture; Cache; Object storage; Temporal isolation among virtual machines; Operating system; Embedded system; Overhead (engineering); Information repository; Distributed computing; Computer hardware; Cloud computing","score_opus":0.053344197366860364,"score_gpt":0.2971492869363381,"score_spread":0.24380508956947772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245247914","genre_codex":"review","genre_gemma":"methods","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":[0.0021237128,0.59701884,0.39025357,0.00299541,0.0009543137,0.0016308508,0.000009760869,0.00267147,0.0023420793],"genre_scores_gemma":[0.28118974,0.1467851,0.56538963,0.0036409658,0.0002608126,0.00071929174,0.000027309488,0.00006584721,0.0019213285],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99807715,0.00014934635,0.00056696526,0.0005330131,0.00032960894,0.00034391382],"domain_scores_gemma":[0.9966029,0.00017682688,0.00019371667,0.0028309054,0.00012617784,0.00006950774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048256497,0.0002237423,0.0005187705,0.000052902084,0.00030802572,0.0000992696,0.0030051225,0.000068067566,0.000008585326],"category_scores_gemma":[0.0020639205,0.00017702507,0.00007106518,0.0005892343,0.00007166652,0.0008950852,0.0010341841,0.00020717262,0.00044217927],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020575321,0.00021604316,0.004420281,0.013876587,0.00019967415,0.0022343071,0.0011151496,0.0018435769,0.004565812,0.32316232,0.37237796,0.27598622],"study_design_scores_gemma":[0.0007517304,0.00035006215,0.0004646382,0.019716658,0.0000447156,0.0063650208,0.000107034524,0.012338471,0.0013722392,0.0010784011,0.95513695,0.0022740534],"about_ca_topic_score_codex":0.000039639493,"about_ca_topic_score_gemma":0.0000011795581,"teacher_disagreement_score":0.582759,"about_ca_system_score_codex":0.00006502719,"about_ca_system_score_gemma":0.00007707498,"threshold_uncertainty_score":0.72188723},"labels":[],"label_agreement":null},{"id":"W4245280155","doi":"10.1007/978-1-4614-6170-8_100985","title":"Network Representation and File","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Representation (politics); Programming language; Political science","score_opus":0.025233311845452862,"score_gpt":0.2465138834170412,"score_spread":0.22128057157158834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245280155","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.935389e-8,0.000164928,0.6107635,0.00019960447,0.00011347304,0.0000678905,0.000015480266,0.0005263391,0.38814873],"genre_scores_gemma":[0.000051078125,0.00010531196,0.3813139,0.00034564993,0.0001158922,0.000008756558,0.000087819106,0.000014889398,0.6179567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99916047,0.000004464182,0.00013266684,0.00044201568,0.00012741044,0.00013294895],"domain_scores_gemma":[0.99870753,0.00014716109,0.00011478323,0.00097442575,0.000028319537,0.000027781949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005240587,0.00014518893,0.000168435,0.000057218822,0.000055008626,0.00006705316,0.00057498564,0.00016575564,0.00040309806],"category_scores_gemma":[0.000045473935,0.00013140215,0.000023202128,0.00002898843,0.00007933926,0.0001944522,0.0008637811,0.00016021742,0.00019304208],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.927512e-7,2.7291318e-7,5.4712814e-7,0.0000023946675,0.0000031181366,0.000006458378,0.0000030356236,0.000015090277,5.2504186e-7,0.7075305,0.2041168,0.08832095],"study_design_scores_gemma":[0.000029761426,0.000019913641,0.000007314919,0.000021603943,0.0000023851824,0.0000133624835,6.719151e-7,0.001214345,0.000008082944,0.48450541,0.5140442,0.00013293797],"about_ca_topic_score_codex":0.0000035263768,"about_ca_topic_score_gemma":0.0000063277703,"teacher_disagreement_score":0.3099274,"about_ca_system_score_codex":0.00001639926,"about_ca_system_score_gemma":0.000009743548,"threshold_uncertainty_score":0.53584236},"labels":[],"label_agreement":null},{"id":"W4246281707","doi":"10.1145/3187009.3164147","title":"Bztree","year":2018,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Throughput; Block (permutation group theory); Non-volatile memory; Embedded system; Computer hardware; Tree (set theory); Code (set theory); Parallel computing; Operating system; Programming language","score_opus":0.01413647543843038,"score_gpt":0.23617268233670108,"score_spread":0.2220362068982707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246281707","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":[0.5111469,0.000836374,0.25280896,0.031061577,0.0038424272,0.0025387446,0.00003087176,0.004373182,0.19336092],"genre_scores_gemma":[0.90750587,0.000011869613,0.0919593,0.00016950653,0.00005144404,0.000020318696,9.228312e-8,0.000005695705,0.00027590196],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99911964,0.0000015838795,0.00015454313,0.00024831083,0.00026775664,0.00020817833],"domain_scores_gemma":[0.9992897,0.000015487916,0.00015651788,0.00035755814,0.00015541441,0.000025338439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013682774,0.000097531825,0.0001038119,0.00006071629,0.00010299351,0.000042465606,0.0023589425,0.000033509958,0.0000070833507],"category_scores_gemma":[0.00014873414,0.00006302792,0.000044542052,0.00041112877,0.00023184763,0.0004679766,0.0016546318,0.000085013606,0.000034863453],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007385755,0.00006998602,0.001388867,0.00002693118,0.000022797749,5.0601227e-7,0.0005411999,0.0000014072349,0.104651086,0.8233912,0.016877748,0.053020913],"study_design_scores_gemma":[0.00019337347,0.00013603958,0.0009159349,0.000035268913,0.0000052787805,0.000012605525,0.00009483996,0.0004750034,0.8715439,0.10502451,0.021443095,0.00012015496],"about_ca_topic_score_codex":0.0000076012657,"about_ca_topic_score_gemma":0.0000014090231,"teacher_disagreement_score":0.7668928,"about_ca_system_score_codex":0.000049853174,"about_ca_system_score_gemma":0.000012908025,"threshold_uncertainty_score":0.43835413},"labels":[],"label_agreement":null},{"id":"W4247063686","doi":"10.1145/2499369.2465563","title":"FTL <sup>2</sup>","year":2013,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Flash file system; Cache; Garbage collection; Operating system; Overhead (engineering); Flash memory; NAND gate; Parallel computing; Flash (photography); Flash memory emulator; Embedded system; Garbage; Computer memory; Programming language; Algorithm; Logic gate","score_opus":0.02028831787280234,"score_gpt":0.24756213025185214,"score_spread":0.2272738123790498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247063686","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":[0.5376275,0.0010896745,0.4277309,0.014688354,0.00068250025,0.0009192795,0.000039334824,0.0063559357,0.010866516],"genre_scores_gemma":[0.7227668,0.000015727235,0.27627504,0.0005488323,0.000057079873,0.00003698692,0.000009110759,0.000011226176,0.00027919209],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986353,0.000029434585,0.00019840675,0.0004686979,0.0002586447,0.00040952524],"domain_scores_gemma":[0.9972178,0.00040353002,0.000103728526,0.0021309527,0.000063553736,0.00008048138],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010365686,0.00017997989,0.00017402624,0.00012553377,0.00012499504,0.00026917638,0.003944657,0.00009751092,0.00012252406],"category_scores_gemma":[0.00074196263,0.00015226862,0.00003606659,0.0003522214,0.000113746195,0.002200316,0.0015460651,0.00019715323,0.0025461307],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008868863,0.00020017414,0.007965834,0.00009216561,0.000098095545,0.0002152428,0.002778883,0.006118585,0.0031046392,0.15636626,0.1138471,0.70920414],"study_design_scores_gemma":[0.001774581,0.00080717134,0.019900823,0.00016275412,0.000053526892,0.00015221798,0.0025569894,0.2792619,0.027501825,0.41150096,0.25324795,0.003079299],"about_ca_topic_score_codex":0.00010195261,"about_ca_topic_score_gemma":0.000007213397,"teacher_disagreement_score":0.70612484,"about_ca_system_score_codex":0.000029439565,"about_ca_system_score_gemma":0.000022974953,"threshold_uncertainty_score":0.9982305},"labels":[],"label_agreement":null},{"id":"W4249042938","doi":"10.2172/1044233","title":"What Scientific Applications can Benefit from Hardware Transactional Memory?","year":2012,"lang":"en","type":"report","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Programmer; Parallel computing; Thread (computing); Transactional memory; Speedup; Instruction set; POSIX Threads; Benchmark (surveying); Embedded system; Operating system; Programming language","score_opus":0.05673943882019541,"score_gpt":0.29046355161485704,"score_spread":0.23372411279466163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249042938","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022115766,0.0062887887,0.9750004,0.001006039,0.00632615,0.0005895038,0.0010723532,0.0017992106,0.007895439],"genre_scores_gemma":[0.014993369,0.0061046737,0.7778154,0.00038531324,0.0020910534,0.0018644698,0.008903741,0.00019445804,0.1876475],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99620134,0.000014568035,0.00045371146,0.0013492428,0.0014525012,0.0005286207],"domain_scores_gemma":[0.9955637,0.00012405962,0.0003192126,0.00325876,0.0005688288,0.00016545376],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003473698,0.00040409595,0.00042160755,0.0004013461,0.00040915297,0.0011935679,0.0032296947,0.0004401472,0.0005483929],"category_scores_gemma":[0.00004165904,0.0003782176,0.00017115759,0.00073652994,0.00030550326,0.0028544224,0.000584143,0.00058043463,0.00042291582],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013403975,0.00012389402,0.000023265029,0.000060470524,0.00011152251,0.000013911435,0.0001931196,0.00012600477,0.00025351153,0.014697214,0.039611064,0.9447847],"study_design_scores_gemma":[0.00008715655,0.000008692515,0.00012845414,0.00007448925,0.00004207181,0.00004533589,0.00016200088,0.00019748253,0.0027010979,0.019676922,0.97630715,0.0005691576],"about_ca_topic_score_codex":0.00042605278,"about_ca_topic_score_gemma":0.0009773348,"teacher_disagreement_score":0.94421554,"about_ca_system_score_codex":0.00060080626,"about_ca_system_score_gemma":0.00091062667,"threshold_uncertainty_score":0.99986696},"labels":[],"label_agreement":null},{"id":"W4249607976","doi":"10.1007/978-0-387-39940-9_3547","title":"Secure Datawarehouses","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science","score_opus":0.018382018296869706,"score_gpt":0.24198894023187384,"score_spread":0.22360692193500414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249607976","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000028638945,0.011697443,0.27323383,0.00012526927,0.0021197072,0.00092993845,0.007114179,0.0016897345,0.70308703],"genre_scores_gemma":[0.00073494384,0.02636395,0.2173795,0.00020657925,0.0016027074,0.000106200634,0.0067198966,0.0003268318,0.7465594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99649453,0.000036980364,0.0009550191,0.0011836345,0.000877492,0.00045237105],"domain_scores_gemma":[0.99326235,0.00020648478,0.0009682106,0.005246839,0.00017544597,0.00014064144],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032460282,0.00066777813,0.0009740981,0.00049046444,0.0000914086,0.000083498984,0.0041234493,0.00044734715,0.00003729179],"category_scores_gemma":[0.00019630203,0.00063204503,0.00014334712,0.0001560193,0.00019625662,0.0015090258,0.0018046523,0.0006978203,0.00031059177],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004772925,0.000032670374,0.000004695793,0.0003427845,0.00006758434,0.00034308914,0.00006634851,0.000035589877,0.000026319496,0.8462385,0.11936149,0.033476163],"study_design_scores_gemma":[0.00018077838,0.00010660816,0.000002754226,0.00077230955,0.0000365633,0.00007973094,0.000019053346,0.0001849457,0.000049757127,0.006810982,0.9910997,0.0006567867],"about_ca_topic_score_codex":0.000053056683,"about_ca_topic_score_gemma":0.000021826907,"teacher_disagreement_score":0.87173826,"about_ca_system_score_codex":0.00010659226,"about_ca_system_score_gemma":0.00024093207,"threshold_uncertainty_score":0.9996131},"labels":[],"label_agreement":null},{"id":"W4250183506","doi":"10.1007/978-1-4939-7131-2_100382","title":"File Representation of Network Data","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Representation (politics); Political science","score_opus":0.07780121000553387,"score_gpt":0.30287524175216657,"score_spread":0.2250740317466327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250183506","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.285859e-8,0.00012858017,0.5952451,0.00007133772,0.0002006997,0.00009925822,0.0005458559,0.00038829524,0.40332076],"genre_scores_gemma":[0.000012964385,0.00011978405,0.66017807,0.00006449861,0.00017146341,0.0000031916431,0.0015337701,0.000016342194,0.33789995],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987045,0.000005468607,0.00026340023,0.00064142304,0.00023902483,0.00014617687],"domain_scores_gemma":[0.9941672,0.00015554801,0.00030605154,0.0052642985,0.000085309504,0.000021579835],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009132488,0.00015433338,0.00024415166,0.000076285476,0.000034622462,0.000029145109,0.004002743,0.00018238393,0.0033928691],"category_scores_gemma":[0.00012158524,0.00014040207,0.000031548952,0.00007912658,0.00017782758,0.0006748175,0.0050521432,0.000144056,0.00034351868],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.1270224e-7,0.000001624,4.595042e-7,0.000004505357,0.000012155424,0.000005025813,0.0000060710895,0.000008921202,0.0000017850399,0.35078147,0.62143165,0.027745485],"study_design_scores_gemma":[0.000038959948,0.000038568414,0.0000032771284,0.00005906383,0.000006928683,0.000005527165,0.000003175449,0.0031761213,0.00010172137,0.40024784,0.5961549,0.000163868],"about_ca_topic_score_codex":0.000009479348,"about_ca_topic_score_gemma":0.000023527324,"teacher_disagreement_score":0.06542082,"about_ca_system_score_codex":0.000018167066,"about_ca_system_score_gemma":0.00003906799,"threshold_uncertainty_score":0.9975182},"labels":[],"label_agreement":null},{"id":"W4250683494","doi":"10.1109/isca.1988.5233","title":"Scrambled storage for parallel memory systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Scrambling; Scheme (mathematics); Computer science; Interconnection; Row; Parallel computing; Electronic circuit; Word (group theory); Computer data storage; Computer hardware; Arithmetic; Computer network; Algorithm; Mathematics; Engineering; Electrical engineering; Programming language","score_opus":0.026775747071079124,"score_gpt":0.26141035750042907,"score_spread":0.23463461042934994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250683494","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035803518,0.00045508274,0.9888228,0.00019014101,0.0005524215,0.00046734718,0.0000048993397,0.0013088313,0.0078404425],"genre_scores_gemma":[0.18922734,0.000012746615,0.8063598,0.00016721548,0.000019345474,0.00018914304,0.000003112838,0.00001284616,0.0040084124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989305,0.000030435924,0.000179196,0.00038991257,0.00015160034,0.00031836424],"domain_scores_gemma":[0.99864477,0.00012549662,0.00007022177,0.0010433128,0.00006553761,0.00005064392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026520013,0.00013098434,0.0001695218,0.00008862273,0.00010988093,0.00011451969,0.00096486,0.00007611035,0.000007382569],"category_scores_gemma":[0.00023877827,0.00011031357,0.00004300195,0.00024374799,0.000043364897,0.0006584121,0.00015356032,0.00007946021,0.00006588474],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001475944,0.00002173717,0.0000062403874,0.000016633348,0.0000080269165,0.000009144398,0.00002849906,0.002261261,0.0004798348,0.98511505,0.008389493,0.0036625743],"study_design_scores_gemma":[0.0029961802,0.00046310193,0.00006136282,0.000048252794,0.000018183613,0.00013643627,0.0010859189,0.22793081,0.017312301,0.15757614,0.59088176,0.0014895414],"about_ca_topic_score_codex":0.000008477465,"about_ca_topic_score_gemma":0.000003203708,"teacher_disagreement_score":0.82753897,"about_ca_system_score_codex":0.00005643992,"about_ca_system_score_gemma":0.00004289095,"threshold_uncertainty_score":0.4498457},"labels":[],"label_agreement":null},{"id":"W4251633315","doi":"10.2139/ssrn.3956388","title":"Price discovery between forward-looking SOFR and LIBOR","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Price discovery; Libor; Forward rate; Forward contract; Financial economics; Economics; Econometrics; Futures contract; Monetary economics; Interest rate","score_opus":0.008055123022538354,"score_gpt":0.24039205354916002,"score_spread":0.23233693052662166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251633315","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":[0.05639708,0.0065483414,0.9346025,0.0018530525,0.00012289848,0.000049006132,0.0000035261658,0.00018290745,0.00024068811],"genre_scores_gemma":[0.9588292,0.004652736,0.035158575,0.00012900081,0.00020419534,0.00000381399,0.000004078739,0.00001959683,0.0009988031],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99743867,0.000050030747,0.00022727995,0.00036356336,0.0002610206,0.001659431],"domain_scores_gemma":[0.9991234,0.000119377866,0.00014873882,0.00047535324,0.00006774737,0.00006537345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006433189,0.00015291669,0.000202386,0.000108013126,0.00026182068,0.00036547473,0.0008498299,0.00007774922,0.0000021275978],"category_scores_gemma":[0.0002314037,0.00013851128,0.000060018592,0.00039574495,0.0000636349,0.002170793,0.0006987641,0.0014983186,0.000008225075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036557287,0.000022645318,0.0029879445,0.000007884777,0.000109071625,0.00007252474,0.00010581027,0.000018130466,0.001080036,0.7232245,0.000082446015,0.2722853],"study_design_scores_gemma":[0.00045623767,0.00017435622,0.0015872247,0.00003515758,0.000023323893,0.0015705125,0.0006471747,0.0002500901,0.005324135,0.98365045,0.005967225,0.00031413772],"about_ca_topic_score_codex":0.0000044856397,"about_ca_topic_score_gemma":0.000044374192,"teacher_disagreement_score":0.90243214,"about_ca_system_score_codex":0.000444414,"about_ca_system_score_gemma":0.0012934554,"threshold_uncertainty_score":0.65095323},"labels":[],"label_agreement":null},{"id":"W4252495035","doi":"10.1109/bigdatacongress.2018.00031","title":"XRT: Programming-Language Independent MapReduce on Shared-Memory Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Shared memory; Parallel computing; Overhead (engineering); Speedup; Distributed shared memory; Programming paradigm; Memory management; Distributed computing; Multi-core processor; Computer architecture; Uniform memory access; Operating system; Programming language","score_opus":0.01658725222377375,"score_gpt":0.2712571560523049,"score_spread":0.2546699038285311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252495035","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":[0.027649833,0.00035537034,0.9469414,0.00053599634,0.0015326316,0.000744541,0.000022145881,0.0047942814,0.01742385],"genre_scores_gemma":[0.8917498,0.0000030055244,0.104356684,0.00022497876,0.00017650527,0.00008656343,0.000008045631,0.000017314707,0.0033770865],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982055,0.000031342297,0.00022600377,0.0006595329,0.00042790183,0.00044974775],"domain_scores_gemma":[0.99794835,0.00005201366,0.00010490258,0.0017237286,0.00008524316,0.00008577525],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021291355,0.00020293653,0.00017565434,0.00018518229,0.00013955195,0.0003089417,0.002088578,0.00011738061,0.00004308877],"category_scores_gemma":[0.00011964125,0.00016611032,0.000039178398,0.00041425147,0.0001554565,0.0007465845,0.00092673127,0.00021277928,0.001065025],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023545856,0.00032717013,0.00018402742,0.00007307614,0.00005163791,0.00039933578,0.002640319,0.00008975997,0.0057740016,0.25373086,0.022814982,0.71389127],"study_design_scores_gemma":[0.005524386,0.00909725,0.004248121,0.0010170637,0.00006449214,0.0014007601,0.020928483,0.11762322,0.4742534,0.012741817,0.34573063,0.007370414],"about_ca_topic_score_codex":0.000064889486,"about_ca_topic_score_gemma":0.000016510103,"teacher_disagreement_score":0.8641,"about_ca_system_score_codex":0.00011191049,"about_ca_system_score_gemma":0.000040271352,"threshold_uncertainty_score":0.99971277},"labels":[],"label_agreement":null},{"id":"W4253248299","doi":"10.1016/j.ins.2005.09.005","title":"Attribute value reordering for efficient hybrid OLAP☆","year":2005,"lang":"en","type":"article","venue":"Information Sciences","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; University of New Brunswick","funders":"","keywords":"Online analytical processing; Normalization (sociology); Heuristics; Computer science; Data cube; Algorithm; Cube (algebra); Dimension (graph theory); Data warehouse; Multidimensional data; Data mining; Mathematics; Combinatorics","score_opus":0.02665205060919379,"score_gpt":0.2877847271022613,"score_spread":0.2611326764930675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253248299","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":[0.014150398,0.000048284623,0.9809315,0.002515796,0.0002703761,0.00023180284,0.000020787611,0.0005833154,0.0012477228],"genre_scores_gemma":[0.5881914,0.0000060010548,0.41115674,0.0005558975,0.000027175269,0.000036193946,0.0000073624597,0.0000015929222,0.000017645227],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880594,0.00000860418,0.00030609343,0.00018962011,0.0003799858,0.00030974264],"domain_scores_gemma":[0.9991791,0.00012108118,0.00017252768,0.0003774058,0.00010831648,0.000041550345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073942053,0.00009736374,0.00009528585,0.00024396254,0.0004247335,0.00038328965,0.0014694261,0.000026793054,0.0000035018602],"category_scores_gemma":[0.00041230826,0.000082264174,0.000035988254,0.0006141654,0.00017719608,0.005524227,0.00035715965,0.0000636344,0.00013297386],"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":[0.0000025398933,0.00001654166,0.00004552165,0.000014535442,0.0000032806358,4.304952e-7,0.00070488383,0.23084414,0.00015712505,0.28945482,0.0029618063,0.47579437],"study_design_scores_gemma":[0.00019697582,0.000063899606,0.00011474104,0.000010989685,0.0000011595943,0.000016797143,0.0001646167,0.8066275,0.0144964885,0.0035403934,0.1745998,0.00016665223],"about_ca_topic_score_codex":0.0000047071767,"about_ca_topic_score_gemma":0.0000013224151,"teacher_disagreement_score":0.5757834,"about_ca_system_score_codex":0.00007109516,"about_ca_system_score_gemma":0.00007577173,"threshold_uncertainty_score":0.40049312},"labels":[],"label_agreement":null},{"id":"W4253472758","doi":"10.1007/978-1-4939-7131-2_100745","title":"Network Representation and File","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Representation (politics); Political science","score_opus":0.031270945036401335,"score_gpt":0.25894874600663315,"score_spread":0.22767780097023183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253472758","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.616852e-7,0.000229123,0.4953694,0.00017080878,0.00018382164,0.00009455889,0.000035036544,0.00067834073,0.50323856],"genre_scores_gemma":[0.0000143722855,0.000103650025,0.41347885,0.00022803746,0.00016094456,0.0000071250483,0.00007523228,0.000013113518,0.58591866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991403,0.0000032978216,0.00012823704,0.0004624042,0.00012807394,0.00013765095],"domain_scores_gemma":[0.99875057,0.00009505848,0.00010836941,0.00097650825,0.000042648233,0.000026873198],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000044034277,0.00014329466,0.00014607499,0.00005826618,0.00006297075,0.000071643146,0.0005955846,0.0001690407,0.0017885898],"category_scores_gemma":[0.00003912115,0.00012924799,0.000021221002,0.000036075464,0.00014118958,0.00034628218,0.0010492967,0.00013217781,0.0003987673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.809071e-7,4.9712827e-7,4.8157244e-7,0.0000019527708,0.000004448018,0.000011179867,0.000009689673,0.0000023061518,6.8409815e-7,0.5203079,0.44838935,0.031271018],"study_design_scores_gemma":[0.00002591618,0.000028721908,0.000005773711,0.000022150158,0.0000023221667,0.000015093689,0.0000017872169,0.00048097654,0.00001538021,0.56882644,0.43044952,0.00012590512],"about_ca_topic_score_codex":0.000002942524,"about_ca_topic_score_gemma":0.000008383103,"teacher_disagreement_score":0.08268012,"about_ca_system_score_codex":0.000019251771,"about_ca_system_score_gemma":0.000013556071,"threshold_uncertainty_score":0.99912393},"labels":[],"label_agreement":null},{"id":"W4256158913","doi":"10.1145/500164.500165","title":"Server-based smoothing of variable bit-rate streams","year":2001,"lang":"en","type":"article","venue":"Proceedings of the ninth ACM international conference on Multimedia - MULTIMEDIA '01","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Smoothing; Variable bitrate; Variable (mathematics); Data stream mining; Bandwidth (computing); Data striping; Throughput; Real-time computing; Algorithm; Parallel computing; Computer network; Operating system; Bit rate; Data mining; Mathematics; Wireless","score_opus":0.04273152011895426,"score_gpt":0.2882270185165469,"score_spread":0.24549549839759266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256158913","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":[0.8849275,0.00016341884,0.061032504,0.02028906,0.006413727,0.0025509996,0.0005072325,0.0019493881,0.022166168],"genre_scores_gemma":[0.70427513,0.000088639936,0.29492286,0.00021992673,0.000096148055,0.0000678893,0.000023468048,0.000028952303,0.00027700444],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966953,0.000028506218,0.00080038654,0.000805957,0.0011512525,0.00051862287],"domain_scores_gemma":[0.99596244,0.00064548827,0.0010792474,0.0009850961,0.0011824637,0.00014524936],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00068590546,0.00043590885,0.00050119363,0.00046714666,0.00012941277,0.00015043428,0.0074514975,0.00024008138,0.00024455323],"category_scores_gemma":[0.006024686,0.0003461669,0.00017738191,0.0008640932,0.0005347252,0.0012832488,0.0017943988,0.00062637444,0.000041500203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089061266,0.0020256273,0.049792126,0.0003566971,0.0005168414,0.000027972525,0.0031757322,0.0021592625,0.4614275,0.18585268,0.0038947384,0.28988022],"study_design_scores_gemma":[0.0021631557,0.0002615754,0.004451979,0.00071292784,0.000036145593,0.000013485314,0.00044715006,0.6707714,0.29577857,0.023087785,0.0016799675,0.000595836],"about_ca_topic_score_codex":0.0002408663,"about_ca_topic_score_gemma":0.000017569635,"teacher_disagreement_score":0.6686121,"about_ca_system_score_codex":0.00018624401,"about_ca_system_score_gemma":0.0002218828,"threshold_uncertainty_score":0.999899},"labels":[],"label_agreement":null},{"id":"W4285137472","doi":"10.1109/tpds.2022.3170574","title":"The State of the Art of Metadata Managements in Large-Scale Distributed File Systems — Scalability, Performance and Availability","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; National Natural Science Foundation of China","keywords":"Metadata; Computer science; File system; Distributed File System; Database; Scalability; Metadata management; Meta Data Services; Namespace; Distributed database; Distributed data store; Operating system; Metadata repository","score_opus":0.01313245041459584,"score_gpt":0.22281705968027216,"score_spread":0.2096846092656763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285137472","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":[0.09092842,0.00039337992,0.8879254,0.00015364612,0.00038043232,0.0007985655,0.019328019,0.00007408963,0.000018043722],"genre_scores_gemma":[0.9988895,0.00012730986,0.00026797183,0.0000052865776,0.0000020967516,0.00032673503,0.000117102354,0.0000062606305,0.000257735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978654,0.00031476442,0.0006323136,0.0004395669,0.00044351423,0.00030448227],"domain_scores_gemma":[0.99799126,0.0003057436,0.00029438097,0.0012885926,0.00007348357,0.000046528057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090712635,0.00017895811,0.0003454819,0.000075054806,0.00052744645,0.00009867589,0.0010211444,0.000042534448,0.0000065440377],"category_scores_gemma":[0.000028537903,0.000121276906,0.000056253644,0.0008236634,0.0002989828,0.00048141036,0.00013367063,0.00031184772,0.0000013768432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017220246,0.00068414304,0.004331925,0.0005975748,0.00013881033,0.000005336198,0.00032077625,0.98458254,0.0001592566,0.0011516407,0.0035629135,0.0042928704],"study_design_scores_gemma":[0.0018622822,0.0003909942,0.030919524,0.00016744118,0.000057503286,0.00004970433,0.0026539448,0.94240683,0.00037958875,0.0006762718,0.019961942,0.00047394188],"about_ca_topic_score_codex":0.00015510208,"about_ca_topic_score_gemma":0.000110347166,"teacher_disagreement_score":0.9079611,"about_ca_system_score_codex":0.00011327486,"about_ca_system_score_gemma":0.000038891074,"threshold_uncertainty_score":0.49455288},"labels":[],"label_agreement":null},{"id":"W4287666556","doi":"10.5281/zenodo.4031745","title":"SSD-Based Workload Characteristics and Their Performance Implications","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Workload; Computer science; Operating system","score_opus":0.043451308013627725,"score_gpt":0.23226599927582814,"score_spread":0.1888146912622004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287666556","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":[0.025617542,0.00010032141,0.9550534,0.010502566,0.00003974141,0.00030204223,0.00019361726,0.0031871581,0.00500364],"genre_scores_gemma":[0.9894989,0.00011608395,0.009179246,0.0006446404,0.00004031324,6.8201736e-8,0.00023073492,0.0002696455,0.000020365824],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99905616,0.000060641094,0.00015173676,0.00038381788,0.000116683776,0.00023094901],"domain_scores_gemma":[0.99899113,0.000025154699,0.00008108013,0.0005802551,0.0001985881,0.0001237779],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015278655,0.00011014476,0.00010461655,0.00008901239,0.0011273528,0.0005354292,0.0016331464,0.000040043396,0.00021103583],"category_scores_gemma":[0.00042044782,0.00010554886,0.000017557322,0.0006004746,0.00015408231,0.00048086702,0.0017766157,0.0002028258,0.0010166642],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000140286365,0.000039863608,0.00003050118,0.000043730193,0.000010391679,0.0000036143865,0.0006755237,0.000045123154,0.0062277415,0.013359405,0.01256057,0.9669895],"study_design_scores_gemma":[0.00028922068,0.0002445394,0.0042699995,0.000025099362,0.000003289859,0.00003832079,0.00009455089,0.028318271,0.0025225682,0.00047200837,0.96349025,0.00023186042],"about_ca_topic_score_codex":5.186054e-7,"about_ca_topic_score_gemma":1.6073455e-8,"teacher_disagreement_score":0.96675766,"about_ca_system_score_codex":0.000044040637,"about_ca_system_score_gemma":0.0000035767825,"threshold_uncertainty_score":0.99976116},"labels":[],"label_agreement":null},{"id":"W4288375488","doi":"10.1145/3297858.3304031","title":"StreamBox-HBM","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Purdue University; National Science Foundation","keywords":"Computer science; Dram; Scalability; Bandwidth (computing); Parallel computing; Distributed computing; Database; Computer network; Computer hardware","score_opus":0.02426010288352239,"score_gpt":0.27228360513656363,"score_spread":0.24802350225304123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288375488","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072936184,0.00022836436,0.96015257,0.00097070757,0.0011249238,0.0002494794,0.000022355687,0.002899172,0.03362307],"genre_scores_gemma":[0.22858664,0.0001029186,0.76579857,0.00024831336,0.00005029324,0.000038081496,0.0000368385,0.000018767836,0.0051195817],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984637,0.000016222872,0.00018859374,0.0008183208,0.00024122387,0.0002719439],"domain_scores_gemma":[0.99600255,0.000060657443,0.00013131363,0.0037156641,0.0000533524,0.00003645324],"candidate_categories":["open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008867817,0.00023973231,0.0002659163,0.00015219928,0.000028999031,0.00017627249,0.004242016,0.0003036092,0.000034794102],"category_scores_gemma":[0.00006887104,0.00020732955,0.000075637945,0.00015064476,0.00005976027,0.00034998136,0.012569366,0.0006055537,0.0009152476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001448558,0.00006047481,0.00016386522,0.00009395956,0.00003822916,0.000051556435,0.00006522819,0.003961286,0.00009836823,0.6771634,0.028726675,0.28957552],"study_design_scores_gemma":[0.0004085919,0.00020159346,0.0004815107,0.00017061496,0.00001592312,0.000027827678,0.00009149954,0.0984598,0.011954331,0.8196396,0.066804975,0.0017437357],"about_ca_topic_score_codex":0.00003098515,"about_ca_topic_score_gemma":0.0000056955837,"teacher_disagreement_score":0.28783178,"about_ca_system_score_codex":0.000080684345,"about_ca_system_score_gemma":0.000109697874,"threshold_uncertainty_score":0.9998627},"labels":[],"label_agreement":null},{"id":"W4292722031","doi":"10.1145/3530876","title":"Rethinking the Interactivity of OS and Device Layers in Memory Management","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Academia Sinica","keywords":"Computer science; Embedded system; Dram; Registered memory; Semiconductor memory; Phase-change memory; Interleaved memory; Non-volatile memory; Memory management; Non-volatile random-access memory; Computer hardware; Overhead (engineering); Memory refresh; Cache; Computer memory; Operating system; Layer (electronics)","score_opus":0.02734896087964162,"score_gpt":0.2705067879880743,"score_spread":0.2431578271084327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292722031","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":[0.11755185,0.00016469482,0.8800959,0.00051509956,0.00066222204,0.00043309812,0.000006546662,0.00028613638,0.0002844839],"genre_scores_gemma":[0.9687669,0.000010653531,0.031027552,0.000089980786,0.000007390058,0.000054811448,8.3208704e-7,0.000009948805,0.000031891806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99836206,0.00029587746,0.00034520525,0.0004203205,0.00035101103,0.00022550512],"domain_scores_gemma":[0.99781215,0.00065125804,0.00020811842,0.0012806599,0.00002634639,0.000021461075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009061999,0.00014166835,0.00021436215,0.00028653632,0.0004147634,0.000063864296,0.0016201687,0.000034772045,0.0000024166839],"category_scores_gemma":[0.000034479388,0.00012599483,0.00004252113,0.0007845482,0.0000682733,0.00027257114,0.00032184567,0.00055114116,0.000001614921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004000611,0.00023965992,0.00009388981,0.0002209077,0.00012965334,0.000085527485,0.01711397,0.672947,0.0007196479,0.014590501,0.00007472872,0.2937445],"study_design_scores_gemma":[0.0017646272,0.00042875978,0.00087830896,0.00055428635,0.00005164622,0.00037426312,0.039204113,0.93702185,0.0034685058,0.013822153,0.0016484547,0.0007829981],"about_ca_topic_score_codex":0.00013325817,"about_ca_topic_score_gemma":0.00001726692,"teacher_disagreement_score":0.85121506,"about_ca_system_score_codex":0.00017819331,"about_ca_system_score_gemma":0.000018798288,"threshold_uncertainty_score":0.51379204},"labels":[],"label_agreement":null},{"id":"W4294733115","doi":"10.1145/3561651","title":"Lock-Free High-performance Hashing for Persistent Memory via PM-aware Holistic Optimization","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Architecture and Code Optimization","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Computer science; Bottleneck; Hash function; Parallel computing; Dynamic perfect hashing; Latency (audio); Hash table; CAS latency; Lock (firearm); Distributed computing; Embedded system; Operating system; Memory controller; Double hashing; Semiconductor memory","score_opus":0.018319145688222953,"score_gpt":0.23075004998246174,"score_spread":0.21243090429423878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294733115","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00061259134,0.00009391059,0.99472547,0.0028903943,0.00032509348,0.00054105924,0.00022206521,0.00056094944,0.000028496639],"genre_scores_gemma":[0.34428608,0.0000801429,0.65472597,0.0003350281,0.000021186885,0.00029822,0.00011599466,0.000026105829,0.000111271125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853826,0.00005895039,0.00024621026,0.00056792947,0.00030220972,0.00028643192],"domain_scores_gemma":[0.99840325,0.00016120153,0.00012925254,0.0011664716,0.000078690726,0.00006113932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015044637,0.00022503355,0.00018800878,0.0003353136,0.0012147005,0.00010710232,0.0011951596,0.00007593191,0.000039391467],"category_scores_gemma":[0.00006625914,0.00023365344,0.000072686526,0.000561407,0.00007711359,0.00051645975,0.00015013394,0.00035920093,9.670149e-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":[0.00005228938,0.00005645342,9.668873e-7,0.000025936446,0.000022512742,0.0000016029618,0.0003055153,0.8952371,0.000037371003,0.00017197992,0.000041901025,0.104046404],"study_design_scores_gemma":[0.0007674973,0.00046574255,0.0000057998664,0.000016130864,0.00004377222,0.00005476674,0.00015903731,0.99525934,0.0006388278,0.0018922983,0.0004220464,0.00027472098],"about_ca_topic_score_codex":0.00000921954,"about_ca_topic_score_gemma":0.000012075298,"teacher_disagreement_score":0.3436735,"about_ca_system_score_codex":0.00014620004,"about_ca_system_score_gemma":0.000044139484,"threshold_uncertainty_score":0.95281106},"labels":[],"label_agreement":null},{"id":"W4295520929","doi":"10.4230/lipics.disc.2023.38","title":"Brief Announcement: On Implementing Wear Leveling in Persistent Synchronization Structures","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":144,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Registered memory; Interleaved memory; Operating system; Cache; Memory management; Memory map; Dram; Computer hardware; Embedded system; Scalability; Semiconductor memory","score_opus":0.11061154773561183,"score_gpt":0.2236952256091611,"score_spread":0.11308367787354928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295520929","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":[0.12593412,0.00006091802,0.8714995,0.00018490691,0.000548095,0.0003937634,0.00007033097,0.0010140503,0.0002943545],"genre_scores_gemma":[0.99226654,0.00018140061,0.00706496,0.000057071695,0.000038912083,0.0000020417606,0.000099598445,0.000025061143,0.0002644001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99757713,0.00007389079,0.00027353154,0.0013637588,0.00016513308,0.00054654485],"domain_scores_gemma":[0.99807113,0.00008814322,0.00029729411,0.001393088,0.000092476446,0.000057885976],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029795896,0.00032469712,0.00028749512,0.0006504974,0.00020714344,0.00015296381,0.0020984665,0.000235788,0.000012375943],"category_scores_gemma":[0.00012840542,0.00039428455,0.00012872284,0.001009472,0.00008557406,0.00049756916,0.004570604,0.00065721065,0.000043042393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010562044,0.000031791362,0.0017641265,0.000076087155,0.000054693846,0.00032077567,0.0003214629,0.8028541,0.00005579037,0.19135384,0.00015540118,0.0030013581],"study_design_scores_gemma":[0.00066993164,0.00013372653,0.0015572642,0.0003059858,0.00003560742,0.0000034972213,0.0010156541,0.8857776,0.00024159097,0.108540624,0.000962688,0.00075582886],"about_ca_topic_score_codex":0.00019672087,"about_ca_topic_score_gemma":0.00016344969,"teacher_disagreement_score":0.8663324,"about_ca_system_score_codex":0.0007938345,"about_ca_system_score_gemma":0.0001330198,"threshold_uncertainty_score":0.9998509},"labels":[],"label_agreement":null},{"id":"W4296452968","doi":"","title":"Measurement of Lifetime and Decay-Width Difference in B0s -&gt; J/psi phi Decays","year":2007,"lang":"en","type":"article","venue":"University of North Texas Digital Library (University of North Texas)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fermilab; Science and Technology Facilities Council; Istituto Nazionale di Fisica Nucleare; National Science Foundation; Comisión Interministerial de Ciencia y Tecnología; Centre National de la Recherche Scientifique; Bundesministerium für Bildung und Forschung; Natural Sciences and Engineering Research Council of Canada; National Science Council; Alfred P. Sloan Foundation; U.S. Department of Energy; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Russian Foundation for Basic Research; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Physics; Nuclear physics; Particle physics","score_opus":0.013074464266719026,"score_gpt":0.1767774345575648,"score_spread":0.1637029702908458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296452968","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":[0.9153256,0.00019485642,0.08128672,0.00017652908,0.000037535887,0.0002734968,0.00025127197,0.00024229234,0.002211701],"genre_scores_gemma":[0.9805673,0.00019851766,0.01878717,0.000018698693,0.000006128215,1.4665049e-8,0.0000505341,0.0000127111625,0.0003589533],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978348,0.000042678796,0.00031901733,0.0006669248,0.0006736189,0.00046293653],"domain_scores_gemma":[0.99806744,0.00016406373,0.00050605764,0.0008724502,0.00017532284,0.00021465935],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016269014,0.00030564377,0.0005832147,0.0008160266,0.00013403471,0.000035198053,0.002546004,0.00013159035,0.000024606705],"category_scores_gemma":[0.000048642225,0.00039646012,0.00014717,0.0013580645,0.0008934698,0.004550103,0.0025651231,0.00027291212,0.000016790022],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014046449,0.0002618828,0.93920535,0.00008642178,0.000053719355,0.00021480744,0.00009508775,0.000066902234,0.0000041306444,0.0019821317,0.00020058075,0.0576885],"study_design_scores_gemma":[0.0009793859,0.0002798325,0.9937151,0.000119704564,0.000023357414,0.000008427965,0.00007343306,0.00028662008,0.00024513953,0.00048260932,0.0034290047,0.00035738558],"about_ca_topic_score_codex":0.00016205398,"about_ca_topic_score_gemma":0.0018459788,"teacher_disagreement_score":0.06524167,"about_ca_system_score_codex":0.000098589684,"about_ca_system_score_gemma":0.0001914502,"threshold_uncertainty_score":0.9998487},"labels":[],"label_agreement":null},{"id":"W4301331999","doi":"10.48550/arxiv.1708.06012","title":"Product Matrix Minimum Storage Regenerating Codes with Flexible Number\\n of Helpers","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Distributed data store; Computer science; Coding (social sciences); Computer data storage; Distributed computing; Code (set theory); Computer network; Mathematics; Computer hardware; Set (abstract data type)","score_opus":0.064492864889483,"score_gpt":0.23356926900392896,"score_spread":0.16907640411444597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301331999","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":[0.33068743,0.00028121177,0.66551876,0.00012973086,0.00034977094,0.00040005925,0.00008006131,0.0008195363,0.0017334159],"genre_scores_gemma":[0.9081293,0.00017097573,0.08964039,0.000010746185,0.000050408016,0.0000021974759,0.0000241392,0.000027394992,0.0019444986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99752027,0.00008178272,0.0002484681,0.001540512,0.00017282093,0.0004361316],"domain_scores_gemma":[0.99444777,0.00007794005,0.0008690055,0.0042309095,0.0002778831,0.00009647454],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027136767,0.00042849148,0.00057253614,0.000251149,0.00031135243,0.00015693647,0.0044511845,0.00024725686,0.00000959106],"category_scores_gemma":[0.00016347884,0.0004366433,0.0001245965,0.00043686957,0.0005316703,0.000978714,0.004202243,0.0006431525,0.00003090656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011547436,0.00019311794,0.009098295,0.0005408914,0.0002808619,0.0009579138,0.0005046579,0.50019807,0.0011440561,0.4825961,0.00082750345,0.0035430945],"study_design_scores_gemma":[0.0044055176,0.00083450665,0.002176885,0.0031465404,0.0006185393,0.00029607167,0.0019970452,0.66004056,0.121202014,0.1949926,0.0036962014,0.006593529],"about_ca_topic_score_codex":0.0001744042,"about_ca_topic_score_gemma":0.000043322238,"teacher_disagreement_score":0.5774418,"about_ca_system_score_codex":0.00020563917,"about_ca_system_score_gemma":0.00033842312,"threshold_uncertainty_score":0.99980855},"labels":[],"label_agreement":null},{"id":"W4303415524","doi":"10.2218/ijdc.v17i1.782","title":"OpenStack Swift: An Ideal Bit-Level Object Storage System for Digital Preservation","year":2022,"lang":"en","type":"article","venue":"International Journal of Digital Curation","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Library; University of Alberta","funders":"","keywords":"Computer science; Digital preservation; Swift; Object storage; Obsolescence; Scalability; Cloud computing; Object (grammar); Cloud storage; Computer data storage; Software; Database; Software engineering; Operating system","score_opus":0.05292288886082759,"score_gpt":0.3047834880594124,"score_spread":0.25186059919858483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4303415524","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":[0.047470216,0.000044502092,0.9482679,0.00095386006,0.001570425,0.00024854546,0.0008368053,0.00015080364,0.00045698602],"genre_scores_gemma":[0.9839847,0.000002112149,0.015280981,0.000050297225,0.00021992734,0.000026926191,0.00031389398,0.000015283727,0.0001058444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99791276,0.000030348128,0.0006202726,0.0002587674,0.001008553,0.00016930523],"domain_scores_gemma":[0.9979344,0.00013748875,0.0007780249,0.00030642725,0.0007798836,0.000063762214],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00031414593,0.00014441794,0.00017530311,0.0003590714,0.00016490054,0.0013378481,0.0021383618,0.000039416445,0.000004801557],"category_scores_gemma":[0.00043141053,0.00014127979,0.00011143617,0.0002501351,0.000033467277,0.027119188,0.00060468016,0.00020626595,0.000004241674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076603703,0.0007717328,0.0010136104,0.000047496207,0.00034698076,0.00038384678,0.0014546043,0.097660005,0.0040730936,0.6461819,0.0043529198,0.24294777],"study_design_scores_gemma":[0.009355438,0.007910163,0.0033045083,0.00030584564,0.00006930917,0.0048068627,0.006769148,0.6732277,0.010438215,0.20068918,0.0809722,0.0021513796],"about_ca_topic_score_codex":0.000004112859,"about_ca_topic_score_gemma":0.0000034537131,"teacher_disagreement_score":0.9365145,"about_ca_system_score_codex":0.0005718675,"about_ca_system_score_gemma":0.0001773862,"threshold_uncertainty_score":0.9996989},"labels":[],"label_agreement":null},{"id":"W4308215377","doi":"10.1109/emsoft55006.2022.00009","title":"Work-in-Progress: Boot Sequence Integrity Verification with Power Analysis","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Power integrity; Computer science; Sequence (biology); Power analysis; Reliability engineering; Data integrity; Signal integrity; Embedded system; Operating system; Engineering; Computer security; Cryptography; Printed circuit board","score_opus":0.02780744951465898,"score_gpt":0.2798616810865943,"score_spread":0.25205423157193535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308215377","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":[0.057453506,0.00014507573,0.9388661,0.0019826787,0.00005690955,0.00014612371,0.000007938149,0.0007782473,0.00056344917],"genre_scores_gemma":[0.7626958,0.0000031880675,0.23703086,0.00009308022,0.0000012812089,0.00007759995,0.000009687939,0.0000032250862,0.000085258216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988025,0.000050422354,0.00014927526,0.0004797151,0.00031032143,0.00020775541],"domain_scores_gemma":[0.9986552,0.00003779171,0.00008288256,0.001159897,0.000038358146,0.00002587682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024450992,0.0000998935,0.00014297605,0.00034539565,0.00011487017,0.000062912026,0.0011785169,0.000026326985,0.00009492122],"category_scores_gemma":[0.000031323467,0.000082558545,0.000032362193,0.004380961,0.000105688574,0.0005842399,0.00070654193,0.0003448084,0.000011658083],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015045948,0.00058249355,0.22195604,0.0000107793185,0.0003267291,0.0006847676,0.0019840926,0.019119183,0.00058468926,0.60585946,0.0021690726,0.14657225],"study_design_scores_gemma":[0.0033943667,0.0027842703,0.51617956,0.00008040624,0.00036352832,0.00029065102,0.011247821,0.28272688,0.013508574,0.06888661,0.095264554,0.005272767],"about_ca_topic_score_codex":0.00004075341,"about_ca_topic_score_gemma":0.000044463046,"teacher_disagreement_score":0.70524234,"about_ca_system_score_codex":0.00019478911,"about_ca_system_score_gemma":0.00004371839,"threshold_uncertainty_score":0.336664},"labels":[],"label_agreement":null},{"id":"W4308477749","doi":"10.1109/tcad.2022.3197487","title":"Resolving the Reliability Issues of Open Blocks for 3-D NAND Flash: Observations and Strategies","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Research Grants Council, University Grants Committee","keywords":"Computer science; Block (permutation group theory); Reliability (semiconductor); NAND gate; Flash (photography); Workload; Reduction (mathematics); Degradation (telecommunications); Reliability engineering; Embedded system; Computer hardware; Operating system; Algorithm; Logic gate; Telecommunications; Mathematics; Engineering","score_opus":0.07707273089317593,"score_gpt":0.2889758330256165,"score_spread":0.2119031021324406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308477749","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":[0.01162654,0.0006146991,0.9850841,0.000310944,0.00051824027,0.0014324217,0.0002458921,0.0001454451,0.000021706666],"genre_scores_gemma":[0.9472619,0.000101743826,0.052065782,0.000032947795,0.000012734778,0.00039527178,0.0000043761115,0.000015002202,0.00011023565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979836,0.00032689524,0.000626209,0.0005167469,0.0003282567,0.00021829896],"domain_scores_gemma":[0.9973253,0.0010580925,0.00032497966,0.0008357742,0.0004122432,0.000043616456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001312123,0.00021648432,0.00045548152,0.00019864908,0.0006579325,0.00034908592,0.0014421805,0.0000767403,0.0000028300553],"category_scores_gemma":[0.00004163848,0.00016290057,0.00005862552,0.00063581334,0.00023040031,0.00075517985,0.00005350304,0.00030036242,1.2627697e-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":[0.00011456193,0.00043084405,0.000037631755,0.00030839778,0.00024090768,0.000007593506,0.0032403606,0.81478184,0.022857605,0.059220318,0.0031931854,0.09556675],"study_design_scores_gemma":[0.0011203889,0.0020886993,0.00009077048,0.00028104676,0.000055707107,0.00008595036,0.004304485,0.9647413,0.012648229,0.01022744,0.0039428696,0.00041313324],"about_ca_topic_score_codex":0.00051680434,"about_ca_topic_score_gemma":0.000016845897,"teacher_disagreement_score":0.9356354,"about_ca_system_score_codex":0.0000867782,"about_ca_system_score_gemma":0.00022770312,"threshold_uncertainty_score":0.6642893},"labels":[],"label_agreement":null},{"id":"W4308627351","doi":"10.1145/3558489.3559071","title":"LOGI: an empirical model of heat-induced disk drive data loss and its implications for data recovery","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Software; Empirical research; Data recovery; Software bug; Computer data storage; Measure (data warehouse); Data modeling; Data mining; Reliability engineering; Software engineering; Computer hardware; Operating system; Engineering","score_opus":0.26027176786098766,"score_gpt":0.3969880880787033,"score_spread":0.13671632021771563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308627351","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019101812,0.00008687612,0.9694012,0.004591118,0.000053060114,0.00035348482,0.0060702437,0.0002910304,0.000051173167],"genre_scores_gemma":[0.48874563,0.000041449362,0.5092268,0.00032024452,0.000010417703,0.00007574091,0.0015381447,0.000010477105,0.00003108945],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843097,0.00003182561,0.0002311598,0.0009468267,0.00014332905,0.00021591669],"domain_scores_gemma":[0.99416965,0.00020068334,0.00007726067,0.005443199,0.0000537018,0.000055476277],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.00030834743,0.00011206063,0.00017530007,0.000088336645,0.0002294372,0.00004234316,0.0063347854,0.000042859196,0.00000418005],"category_scores_gemma":[0.00028034602,0.00010513681,0.000013478178,0.00030693406,0.000055959412,0.0025277194,0.01186496,0.00013985607,8.852505e-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":[0.000085515785,0.0010061229,0.0016273056,0.000068254856,0.00011178426,0.000007939698,0.00046470363,0.021560458,0.032244295,0.5621582,0.0383619,0.34230348],"study_design_scores_gemma":[0.00017705986,0.0001619306,0.00020437804,0.000001414746,0.00000854056,0.000012868572,0.00009188545,0.9442275,0.00063603773,0.053399738,0.0009348206,0.00014383337],"about_ca_topic_score_codex":0.00001762467,"about_ca_topic_score_gemma":0.00003883757,"teacher_disagreement_score":0.922667,"about_ca_system_score_codex":0.000039546936,"about_ca_system_score_gemma":0.00011951692,"threshold_uncertainty_score":0.99904144},"labels":[],"label_agreement":null},{"id":"W4308731338","doi":"10.1145/3565026","title":"ctFS: Replacing File Indexing with Hardware Memory Translation through Contiguous File Allocation for Persistent Memory","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; VMware","keywords":"Computer science; Operating system; File Control Block; File system fragmentation; Stub file; File system; Computer file; Unix file types; Versioning file system; Virtual memory; Offset (computer science); Parallel computing; Memory management; Computer hardware; Semiconductor memory","score_opus":0.036841194622613246,"score_gpt":0.25707262058948455,"score_spread":0.22023142596687129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308731338","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001082224,0.00020840397,0.99197614,0.0011584412,0.00036361927,0.00088965707,0.0028598225,0.0010360947,0.00042560566],"genre_scores_gemma":[0.44428575,0.000019784455,0.54976296,0.00053030986,0.00004510036,0.0026629502,0.00097408285,0.00006920204,0.0016498362],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979595,0.0000847629,0.00031316976,0.0007777112,0.0004905269,0.0003743499],"domain_scores_gemma":[0.99752367,0.0004957996,0.00019498091,0.0016270594,0.000104685605,0.000053828197],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022846487,0.00026037233,0.00026133776,0.00023420878,0.0012100617,0.000090644426,0.0011947415,0.00008711564,0.0011215165],"category_scores_gemma":[0.000081057406,0.00027202207,0.0001690613,0.0006608728,0.00008714782,0.0013143374,0.000049238897,0.00046507636,0.000012884027],"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":[0.00039451531,0.00048580926,0.0000018263676,0.00013088227,0.0002782091,0.000075743046,0.011465519,0.5213134,0.0021830997,0.0008659923,0.019678256,0.44312668],"study_design_scores_gemma":[0.012208528,0.009424713,0.00015818217,0.00058908184,0.00062154053,0.0010236244,0.06162675,0.32463276,0.060791414,0.012293248,0.51134807,0.0052820835],"about_ca_topic_score_codex":0.000059713184,"about_ca_topic_score_gemma":0.000047576785,"teacher_disagreement_score":0.49166983,"about_ca_system_score_codex":0.0004118168,"about_ca_system_score_gemma":0.00012372933,"threshold_uncertainty_score":0.9999732},"labels":[],"label_agreement":null},{"id":"W4309000239","doi":"10.1145/3565027","title":"Improving the Endurance of Next Generation SSD’s using WOM-v Codes","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Garbage collection; Computer science; Context (archaeology); Garbage; Database; Programming language","score_opus":0.06998583098756729,"score_gpt":0.2732459015908353,"score_spread":0.203260070603268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309000239","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":[0.08510016,0.00021055658,0.9131765,0.00051317015,0.0004804831,0.00018423863,0.00006537333,0.0002537112,0.000015854392],"genre_scores_gemma":[0.84677863,0.000017248796,0.15289396,0.00014483418,0.00002069471,0.00006647493,0.0000032077946,0.0000112795815,0.000063695385],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987687,0.00010053494,0.00022846664,0.0003478897,0.00034563654,0.00020878603],"domain_scores_gemma":[0.9980377,0.00014675452,0.00016537502,0.0015815949,0.00004510328,0.00002350472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025951935,0.00013122724,0.00014303552,0.00015536055,0.000826367,0.00006297434,0.0016853305,0.00003675327,0.00004578539],"category_scores_gemma":[0.000055879435,0.00011480009,0.00006769675,0.00067643373,0.00010358122,0.00079165836,0.000118480624,0.00038261147,0.0000035348885],"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":[0.0000152197845,0.00012801787,0.000006949819,0.000015402687,0.000028156976,0.000017180002,0.0008482489,0.26357806,0.4795546,0.0051686433,0.000103601524,0.25053594],"study_design_scores_gemma":[0.00063990854,0.00033627218,0.000107063286,0.00001691853,0.00003933257,0.00017362308,0.0019616156,0.8160723,0.1693679,0.003440351,0.0072806934,0.0005640656],"about_ca_topic_score_codex":0.000091146154,"about_ca_topic_score_gemma":0.0000185606,"teacher_disagreement_score":0.76167846,"about_ca_system_score_codex":0.00018890377,"about_ca_system_score_gemma":0.00006916725,"threshold_uncertainty_score":0.63558304},"labels":[],"label_agreement":null},{"id":"W4309505072","doi":"10.1145/3572751.3572765","title":"Characterizing I/O in Machine Learning with MLPerf Storage","year":2022,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Focus (optics); Inference; Software; Machine learning; Computer data storage; Training set; Training (meteorology); Data access; Database; Artificial intelligence; Computer engineering; Operating system","score_opus":0.017438022209979483,"score_gpt":0.23393867511933225,"score_spread":0.21650065290935278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309505072","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":[0.7306154,0.0003285848,0.26400766,0.0024360039,0.00044861776,0.00030324011,0.000014591221,0.0014146034,0.00043135398],"genre_scores_gemma":[0.89224565,0.000031161788,0.10703437,0.00022930442,0.000020257301,0.00010304464,0.000019135961,0.000022110187,0.0002949711],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985131,0.00010651261,0.00019496222,0.0005379151,0.00028060187,0.00036689918],"domain_scores_gemma":[0.99847585,0.00014920799,0.00014165643,0.0011778341,0.000017303722,0.000038175873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030349803,0.00016614515,0.00020883132,0.00027403398,0.00027691392,0.000060865896,0.0022606004,0.00003545777,0.00006351681],"category_scores_gemma":[0.0002332974,0.00015567825,0.000026552652,0.0008548382,0.00004315693,0.0007629736,0.0029241608,0.0008144728,0.000016924247],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011837346,0.0002057347,0.048766684,0.000028324395,0.000030589166,0.0012870504,0.002273113,0.0064571984,0.019591514,0.005648853,0.0002984343,0.9152941],"study_design_scores_gemma":[0.004925001,0.0052123833,0.025834262,0.0001641588,0.000025114428,0.0009254786,0.002896303,0.31936437,0.010594159,0.021403003,0.6050707,0.0035850515],"about_ca_topic_score_codex":0.000115312774,"about_ca_topic_score_gemma":0.00006550504,"teacher_disagreement_score":0.9117091,"about_ca_system_score_codex":0.00018558095,"about_ca_system_score_gemma":0.000042431268,"threshold_uncertainty_score":0.63483745},"labels":[],"label_agreement":null},{"id":"W4311787046","doi":"10.1109/icfpt56656.2022.9974258","title":"ZHW: A Numerical CODEC for Big Data Scientific Computation","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"U.S. Department of Energy","keywords":"Codec; Bottleneck; Computer science; Field-programmable gate array; Computation; Implementation; Big data; Data compression; Parallel computing; Computer architecture; Computer hardware; Embedded system; Operating system; Algorithm; Software engineering","score_opus":0.12165633783088406,"score_gpt":0.32425218677054124,"score_spread":0.20259584893965718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311787046","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00047856968,0.00005513396,0.9949308,0.0015387622,0.0015124639,0.00024959832,0.00020394521,0.00087879185,0.0001519285],"genre_scores_gemma":[0.27491307,7.146317e-7,0.72373724,0.000256239,0.00003981915,0.00009111246,0.00046119056,0.000008316436,0.0004922561],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860847,0.000027456197,0.00015096524,0.00067891314,0.00031055315,0.00022366221],"domain_scores_gemma":[0.9981199,0.00015406692,0.00006902802,0.0015784659,0.000047304435,0.000031237658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040950283,0.00007835755,0.000098521436,0.0001415207,0.0005926972,0.00020499463,0.0033111377,0.000016468382,0.000009959054],"category_scores_gemma":[0.00016021795,0.000076019875,0.000020181906,0.000847873,0.000087012675,0.00065181777,0.0053370204,0.00010479753,0.000022641367],"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":[0.000009589442,0.00013349096,0.000037332848,0.000009452734,0.000010574433,0.000012374394,0.00013801828,0.0056984816,0.00091695966,0.118100286,0.19265194,0.6822815],"study_design_scores_gemma":[0.00021023824,0.00007898807,0.000024418792,8.3767975e-7,0.0000021634412,0.00001589318,0.00010034526,0.68701845,0.0003813225,0.029388467,0.28265107,0.0001277905],"about_ca_topic_score_codex":0.000009108263,"about_ca_topic_score_gemma":0.0000056515346,"teacher_disagreement_score":0.6821537,"about_ca_system_score_codex":0.000067648805,"about_ca_system_score_gemma":0.000086408865,"threshold_uncertainty_score":0.66522145},"labels":[],"label_agreement":null},{"id":"W4312621027","doi":"10.14778/3561261.3561270","title":"TreeLine","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Merge (version control); Associative array; Workload; Key (lock); Point (geometry); Parallel computing; Operating system; Artificial intelligence","score_opus":0.012707166413659191,"score_gpt":0.22132474582873737,"score_spread":0.2086175794150782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312621027","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":[0.63402855,0.0037781864,0.16330159,0.10949912,0.005870527,0.005213883,0.00023423834,0.006622392,0.07145149],"genre_scores_gemma":[0.9547662,0.000013051824,0.044367928,0.0002532956,0.000015936932,0.00011700463,5.140949e-7,0.000006635584,0.00045944637],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99901867,0.000003504854,0.0001670489,0.00023459502,0.0003992679,0.00017689755],"domain_scores_gemma":[0.9994396,0.000017833447,0.000175697,0.00029668905,0.000051051502,0.000019148018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020482029,0.000085163156,0.000104460836,0.00007288146,0.0001990535,0.000023811172,0.0026517485,0.000012684304,0.000017928862],"category_scores_gemma":[0.000078726676,0.000061476334,0.000054565422,0.0005296486,0.000056459292,0.00027529226,0.0040010866,0.00016528319,0.0000034321868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014112118,0.00019948688,0.0009912945,0.000029992223,0.00002819435,0.00000204191,0.00063003146,0.00032450896,0.08813933,0.83184135,0.023780683,0.054018956],"study_design_scores_gemma":[0.0009324502,0.00043375287,0.0008431661,0.00002384356,0.000018913088,0.00010020887,0.0012989898,0.005709714,0.5899306,0.20204169,0.19826096,0.0004057033],"about_ca_topic_score_codex":0.000008282491,"about_ca_topic_score_gemma":3.6612022e-7,"teacher_disagreement_score":0.62979966,"about_ca_system_score_codex":0.00010768436,"about_ca_system_score_gemma":0.000015911528,"threshold_uncertainty_score":0.4987068},"labels":[],"label_agreement":null},{"id":"W4312815529","doi":"10.53766/cei/2021.43.02.09","title":"Proposal to Improve the Management System of Storage in a Virtual Learning Environment","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Collège Montmorency","funders":"","keywords":"Computer science; Scalability; Big data; Computer data storage; Deep learning; Storage management; File system; Virtual learning environment; Data management; Database; Distributed computing; Data science; Operating system; Multimedia; World Wide Web; Artificial intelligence","score_opus":0.006811535024128148,"score_gpt":0.2109898524642549,"score_spread":0.20417831744012674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312815529","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":[0.012819251,0.000047000394,0.9844416,0.00076999253,0.00010013283,0.00029814543,0.0000016414937,0.00020001578,0.0013222563],"genre_scores_gemma":[0.77580166,0.000009390255,0.22308722,0.000048863014,0.000006299795,0.000057743517,9.765403e-7,0.000005377944,0.0009824762],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989686,0.000055059274,0.00019333132,0.00034872105,0.00024413802,0.00019014347],"domain_scores_gemma":[0.9990692,0.000036534995,0.000057642887,0.00080042536,0.000012666221,0.000023508253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024147703,0.000090138004,0.00012161446,0.00007568052,0.000045657514,0.00003414203,0.0008038908,0.000028378545,0.0000068288614],"category_scores_gemma":[0.000024572597,0.000063842235,0.00002302756,0.0003246924,0.000037281763,0.00018388637,0.0018790677,0.00013768594,0.00004714341],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006094968,0.00007231594,0.00009497472,0.00006275757,0.000024300409,0.00029053053,0.0006275365,0.02707947,0.008541499,0.7858036,0.00010458354,0.17729235],"study_design_scores_gemma":[0.0036984538,0.0024889228,0.0070621977,0.00067023904,0.00006179493,0.00017939888,0.08243434,0.40252572,0.39374593,0.008754296,0.09617739,0.0022013213],"about_ca_topic_score_codex":0.000008903596,"about_ca_topic_score_gemma":0.000007951848,"teacher_disagreement_score":0.7770493,"about_ca_system_score_codex":0.00014851254,"about_ca_system_score_gemma":0.000021459518,"threshold_uncertainty_score":0.26034108},"labels":[],"label_agreement":null},{"id":"W4312884722","doi":"10.1109/access.2022.3227384","title":"CephArmor: A Lightweight Cryptographic Interface for Secure High-Performance Ceph Storage Systems","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"PROTO Manufacturing (Canada); University of New Brunswick","funders":"Australian Research Council; Chinese Academy of Sciences; Natural Sciences and Engineering Research Council of Canada; Mitacs; Lockheed Martin","keywords":"Computer science; Object storage; File server; Cryptography; Server; Storage area network; Distributed data store; Cryptographic primitive; Computer network; File system; Computer data storage; Throughput; Computer security; Overhead (engineering); Operating system; Cryptographic protocol; Wireless","score_opus":0.024133373798498284,"score_gpt":0.2827220807969248,"score_spread":0.2585887069984265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312884722","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":[0.22294329,0.0009841641,0.76990855,0.0004087987,0.0035240254,0.00074513466,0.00015613476,0.0012497434,0.000080179656],"genre_scores_gemma":[0.9841217,0.00007196688,0.014125496,0.00019563368,0.00013000083,0.0011389516,0.000017345119,0.000038902348,0.00016000931],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975863,0.00007922427,0.00038746468,0.0008372926,0.00050975685,0.000599949],"domain_scores_gemma":[0.99782205,0.00014556471,0.0003055328,0.0015271854,0.000115854324,0.00008380684],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0003481948,0.00030684719,0.0003507896,0.0004336526,0.0006669315,0.00043789187,0.0060371817,0.00008588521,0.000025918938],"category_scores_gemma":[0.000031267016,0.00029662534,0.00008228149,0.0014095772,0.00009863673,0.0026049593,0.0019959637,0.00047874387,0.000019847554],"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":[0.00044734703,0.0011433016,0.0025575352,0.0016600824,0.000538951,0.00041374212,0.0030976338,0.4463526,0.03764768,0.24620427,0.20109963,0.05883723],"study_design_scores_gemma":[0.0036188005,0.001676268,0.001046212,0.0001789935,0.000079326106,0.000278372,0.00052584865,0.40896395,0.12676151,0.018477803,0.43557188,0.0028210552],"about_ca_topic_score_codex":0.0000339027,"about_ca_topic_score_gemma":0.000004135047,"teacher_disagreement_score":0.7611784,"about_ca_system_score_codex":0.00020127604,"about_ca_system_score_gemma":0.00006958765,"threshold_uncertainty_score":0.99994856},"labels":[],"label_agreement":null},{"id":"W4313065965","doi":"10.14778/3551793.3551853","title":"Spooky","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Merge (version control); Computer science; Granularity; Associative array; Data structure; Parallel computing; Operating system; Programming language","score_opus":0.01181195605712601,"score_gpt":0.21574701719651604,"score_spread":0.20393506113939003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313065965","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":[0.6994852,0.004030131,0.07107375,0.07065836,0.006296491,0.005331377,0.00017595115,0.006597687,0.13635105],"genre_scores_gemma":[0.9700024,0.000015046574,0.02909995,0.00020416013,0.000011425601,0.000113893526,2.3624067e-7,0.000006437783,0.0005464444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990152,0.0000032939115,0.0001488963,0.00023612546,0.0004123539,0.0001841278],"domain_scores_gemma":[0.99944913,0.000017046601,0.00017015259,0.00030167444,0.000042721225,0.000019259778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017359323,0.00008467878,0.000099378194,0.000070830865,0.00021389812,0.000027999122,0.0027647177,0.000012949984,0.0000314626],"category_scores_gemma":[0.00006500297,0.000062693776,0.00005383142,0.00048773727,0.00006093732,0.0002997795,0.0042267833,0.00017067014,0.0000065009945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006709241,0.00015118167,0.0010438033,0.000029224695,0.00002361626,0.000002089613,0.0007865943,0.00014891243,0.044917148,0.8988926,0.021766154,0.03223196],"study_design_scores_gemma":[0.000829141,0.00040808856,0.0010242441,0.00002966553,0.000019595755,0.00013536982,0.001463115,0.005643093,0.53638,0.23221758,0.22136521,0.0004848736],"about_ca_topic_score_codex":0.0000061712303,"about_ca_topic_score_gemma":1.2999537e-7,"teacher_disagreement_score":0.66667503,"about_ca_system_score_codex":0.00011521271,"about_ca_system_score_gemma":0.000009302494,"threshold_uncertainty_score":0.5268383},"labels":[],"label_agreement":null},{"id":"W4313152108","doi":"10.14778/3561261.3561263","title":"The case for distributed shared-memory databases with RDMA-enabled memory disaggregation","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Remote direct memory access; Scalability; Computer science; Shared memory; Database; Distributed memory; Scaling; Memory management; Operating system; Semiconductor memory","score_opus":0.01966093503013673,"score_gpt":0.2441219501968502,"score_spread":0.22446101516671346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313152108","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":[0.44393736,0.0030101857,0.49184886,0.035985302,0.0021170175,0.012583489,0.0059748497,0.0029098177,0.0016331221],"genre_scores_gemma":[0.9633692,0.000026984822,0.034480687,0.00013235652,0.000037059093,0.0015931432,0.00005164679,0.000022356915,0.00028658423],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985098,0.000012434827,0.00027187905,0.00043289948,0.00042629652,0.00034667877],"domain_scores_gemma":[0.99850005,0.00022685688,0.000443779,0.0006142683,0.00017619932,0.00003883311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052005285,0.00017990745,0.00016413853,0.000060779887,0.0012232185,0.0001271685,0.002133181,0.000017896755,0.0000058622563],"category_scores_gemma":[0.00039415184,0.000103260354,0.00006668813,0.0005869945,0.00018262248,0.00081211136,0.0025694193,0.00020169471,8.5037124e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010588729,0.0011409628,0.0011634274,0.00078671495,0.00056232716,0.0002371455,0.0043870853,0.006580694,0.039469805,0.5475175,0.13644047,0.26065502],"study_design_scores_gemma":[0.00695868,0.0020047366,0.00045574343,0.000324373,0.0002966239,0.004265939,0.0326381,0.053821802,0.7006986,0.067339376,0.12943706,0.0017589364],"about_ca_topic_score_codex":0.000051306233,"about_ca_topic_score_gemma":0.00001879571,"teacher_disagreement_score":0.66122884,"about_ca_system_score_codex":0.00023568427,"about_ca_system_score_gemma":0.000054375327,"threshold_uncertainty_score":0.9408132},"labels":[],"label_agreement":null},{"id":"W4313591100","doi":"10.1109/access.2022.3233829","title":"Design and Implementation of Burst Buffer Over-Subscription Scheme for HPC Storage Systems","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office of Science; Korea Institute of Science and Technology; Advanced Scientific Computing Research; National Research Foundation; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Korea Institute of Science and Technology Information; National Energy Research Scientific Computing Center; National Research Foundation of Korea; U.S. Department of Energy","keywords":"Computer science; Buffer (optical fiber); Overhead (engineering); Supercomputer; Computer network; Write buffer; Operating system; Telecommunications","score_opus":0.0703756033261591,"score_gpt":0.36371669642724386,"score_spread":0.29334109310108475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313591100","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":[0.19337696,0.000101225785,0.80500144,0.000086263026,0.00047582705,0.0005395771,0.000029024728,0.0003857975,0.000003868745],"genre_scores_gemma":[0.9571056,0.000059223115,0.04249322,0.00002581134,0.00003739814,0.00021393552,0.000019600886,0.000012379207,0.00003285505],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907273,0.000028055532,0.00021031224,0.00030499708,0.00017820901,0.00020571284],"domain_scores_gemma":[0.9991708,0.00012923697,0.0001594311,0.00043376003,0.00008066881,0.00002614179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028218777,0.00010244061,0.00014780053,0.00018933674,0.00008253817,0.00016459577,0.00076127786,0.000055439494,0.0000015447235],"category_scores_gemma":[0.00003471735,0.00009932249,0.000019464998,0.0004926579,0.000041518117,0.0017464509,0.0002452403,0.000050409177,0.0000040046993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012525519,0.00014151089,0.010719585,0.0016474508,0.00022008005,0.000064046406,0.0023018408,0.028934306,0.5906749,0.15705591,0.058217946,0.1498972],"study_design_scores_gemma":[0.0028972146,0.00057826063,0.02115348,0.00015286819,0.000040865867,0.000018444298,0.0012441251,0.5792822,0.36305428,0.025504349,0.0051776245,0.00089628756],"about_ca_topic_score_codex":0.000075916454,"about_ca_topic_score_gemma":0.0000071285926,"teacher_disagreement_score":0.7637286,"about_ca_system_score_codex":0.000053358915,"about_ca_system_score_gemma":0.000020987954,"threshold_uncertainty_score":0.40502533},"labels":[],"label_agreement":null},{"id":"W4317767825","doi":"10.14778/3570690.3570704","title":"FILM","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Search engine indexing; Overhead (engineering); Data structure; Range query (database); Parallel computing; Auxiliary memory; Database; Distributed computing; Information retrieval; Operating system; Sargable; Search engine; Web search query","score_opus":0.012163401002412973,"score_gpt":0.2179784930603923,"score_spread":0.20581509205797932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317767825","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":[0.63223785,0.003234373,0.13496497,0.073210925,0.006766968,0.005646385,0.0002496625,0.006957941,0.13673091],"genre_scores_gemma":[0.96520203,0.000010008324,0.033901475,0.00024243878,0.000010977215,0.0001339222,3.8832226e-7,0.000006235781,0.0004924933],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99903953,0.0000034048435,0.00014605986,0.00023215373,0.0003977351,0.0001811219],"domain_scores_gemma":[0.999455,0.000018532537,0.00016703608,0.0002957349,0.000045142784,0.000018553807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018542437,0.00008196872,0.00009648458,0.00006665917,0.00022133946,0.00002768872,0.002763104,0.000012912773,0.0000238791],"category_scores_gemma":[0.00007652559,0.000060306535,0.000052393607,0.00049475266,0.000059069625,0.00029643142,0.0044433954,0.0001688296,0.000004578487],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008838451,0.00013614068,0.0009539518,0.00003029165,0.000024211593,0.000001758685,0.00083542103,0.00039929518,0.04982453,0.8955407,0.030757895,0.021486973],"study_design_scores_gemma":[0.0006821784,0.00034953374,0.0010128969,0.000024868954,0.000015116037,0.00009711571,0.0017548862,0.005205652,0.58286905,0.23057239,0.17702448,0.00039184687],"about_ca_topic_score_codex":0.0000075525036,"about_ca_topic_score_gemma":1.9224208e-7,"teacher_disagreement_score":0.6649683,"about_ca_system_score_codex":0.000109420565,"about_ca_system_score_gemma":0.000016630496,"threshold_uncertainty_score":0.5538375},"labels":[],"label_agreement":null},{"id":"W4318148204","doi":"10.1109/bigdata55660.2022.10020871","title":"Predicting Deduplication Performance: An Analytical Model and Empirical Evaluation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Big Data (Big Data)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Data deduplication; Computer science; Data mining; Software versioning; Kernel (algebra); Database; Software; Operating system","score_opus":0.5054255254777182,"score_gpt":0.4297697773039301,"score_spread":0.07565574817378812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318148204","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":[0.24896824,0.00006396672,0.72909385,0.005338928,0.0026421214,0.0006339412,0.010835878,0.0005967025,0.0018263969],"genre_scores_gemma":[0.96884954,0.00017616013,0.012245461,0.00055204425,0.00026542763,0.00012134182,0.01771075,0.000016501006,0.00006279691],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995834,0.00015650516,0.00041901224,0.0015907701,0.0017003266,0.00029936503],"domain_scores_gemma":[0.99493235,0.00010995109,0.00024667042,0.0043664086,0.00023142423,0.00011318423],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0017016429,0.00022605431,0.00019270628,0.00033541836,0.00043928888,0.00033484265,0.00850097,0.00007319442,0.00006331935],"category_scores_gemma":[0.0005306479,0.00023752115,0.000016287426,0.00043120343,0.00014120068,0.0033156315,0.008200962,0.0006094473,0.000020772382],"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":[0.000074305804,0.00027975783,0.002411202,0.000010400522,0.000055404715,0.0000110699875,0.00017126526,0.009577411,0.0008338721,0.022914516,0.009909265,0.9537515],"study_design_scores_gemma":[0.00039169603,0.00015345062,0.0012999998,0.000012834838,0.00002237058,0.00004157196,0.0001525655,0.98863214,0.000080946054,0.0040922537,0.0048703877,0.00024980376],"about_ca_topic_score_codex":0.00002880252,"about_ca_topic_score_gemma":0.00006522831,"teacher_disagreement_score":0.9790547,"about_ca_system_score_codex":0.00026415335,"about_ca_system_score_gemma":0.00044230168,"threshold_uncertainty_score":0.99982053},"labels":[],"label_agreement":null},{"id":"W4321121383","doi":"10.2139/ssrn.4360939","title":"Partn: A Plugin Implementation of the Activation Relaxation Technique Nouveau Hijacking a Minimisation Algorithm","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Regroupement Québécois sur les Matériaux de Pointe","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interfacing; Computer science; Plug-in; Interoperability; Software; Interface (matter); Algorithm; Minification; Energy minimization; Reverse engineering; Distributed computing; Computer engineering; Operating system; Programming language; Computer hardware","score_opus":0.022325141522060703,"score_gpt":0.3019174197587023,"score_spread":0.27959227823664157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321121383","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":[0.008591102,0.00011664175,0.9861482,0.003447466,0.0005002266,0.0007933657,0.000014548313,0.00037557434,0.000012875006],"genre_scores_gemma":[0.86437446,0.0016066193,0.1332323,0.00005064149,0.00020641607,0.00029157853,0.000073623436,0.000053907203,0.00011046799],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969743,0.00018553837,0.0006583916,0.00047759592,0.000624225,0.0010799513],"domain_scores_gemma":[0.9969474,0.00009946271,0.00175457,0.00093309296,0.00023944971,0.000026021578],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0020393839,0.00026037777,0.00025913448,0.00039425583,0.00025690455,0.00012501035,0.0018293058,0.00028795848,0.0000023043328],"category_scores_gemma":[0.00024651847,0.00021784924,0.00015951536,0.0006942426,0.0000664714,0.0007709828,0.0012749438,0.003075602,0.000004158233],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010189793,0.000051501193,0.00047013286,0.000059610138,0.00019728445,0.000002453903,0.0012759711,0.0022889164,0.0076222713,0.17264724,0.00028890124,0.81508553],"study_design_scores_gemma":[0.00033434966,0.00013598977,0.0015349847,0.00022009808,0.00003343305,0.000084607695,0.0019382361,0.0071047815,0.045928996,0.94210654,0.00027727103,0.00030071367],"about_ca_topic_score_codex":0.00020415489,"about_ca_topic_score_gemma":0.00036024698,"teacher_disagreement_score":0.85578334,"about_ca_system_score_codex":0.0025467288,"about_ca_system_score_gemma":0.0029116636,"threshold_uncertainty_score":0.99922436},"labels":[],"label_agreement":null},{"id":"W4360832450","doi":"10.1109/hpca56546.2023.10070924","title":"D-Shield: Enabling Processor-side Encryption and Integrity Verification for Secure NVMe Drives","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"National Science Foundation","keywords":"Computer science; Encryption; Operating system; Embedded system; Software; Data integrity; Metadata; Computer network; Computer hardware; Computer security","score_opus":0.03817006626588674,"score_gpt":0.29999438618806895,"score_spread":0.2618243199221822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360832450","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":[0.04474514,0.00007645525,0.9507662,0.0021573044,0.00009678684,0.00025292498,0.000006477573,0.0017375543,0.0001611645],"genre_scores_gemma":[0.70465505,0.00016665153,0.2947022,0.00008474499,0.000029597919,0.000112699636,0.000028091341,0.0000071525665,0.00021378831],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99918455,0.000010534499,0.00012955819,0.00037753745,0.0001082412,0.0001895526],"domain_scores_gemma":[0.99932617,0.00013269494,0.00006106216,0.00038375382,0.00006874024,0.00002755332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002177497,0.00009153988,0.000091905895,0.0001514209,0.00012778607,0.000105164734,0.00046001974,0.00008940811,0.0000014739853],"category_scores_gemma":[0.0004517352,0.00007944769,0.000017780561,0.0005299849,0.00005310878,0.0010292456,0.000253692,0.00013096463,0.000018237777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009979705,0.000024434248,0.0003059238,0.00012287236,0.000010542124,0.0000039873153,0.0015221591,0.00009372853,0.0279094,0.66733587,0.0017126026,0.30094847],"study_design_scores_gemma":[0.0006702047,0.00024238096,0.003981583,0.00007765748,0.0000114383165,0.000017321056,0.0031479807,0.21957834,0.12114276,0.6266974,0.023807792,0.00062512676],"about_ca_topic_score_codex":0.000006745525,"about_ca_topic_score_gemma":0.0000135573155,"teacher_disagreement_score":0.6599099,"about_ca_system_score_codex":0.000024820813,"about_ca_system_score_gemma":0.000024658531,"threshold_uncertainty_score":0.32397825},"labels":[],"label_agreement":null},{"id":"W4360989123","doi":"10.18280/ria.370129","title":"Tree-Based Approach’s to Mitigate the Heterogeneity Concerns among Different file Systems: A Possible Solution","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Advanced Data Storage Technologies","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":"Tree (set theory); Computer science; Mathematics; Combinatorics","score_opus":0.0698189326096353,"score_gpt":0.2829226095177284,"score_spread":0.21310367690809312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360989123","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":[0.028111,0.00013754285,0.96722776,0.0008062172,0.0003626449,0.0007964767,0.000116639225,0.0013798049,0.0010619321],"genre_scores_gemma":[0.9923402,0.000012944464,0.0052604494,0.00008324605,0.00006526502,0.00057092094,0.00007980901,0.000023406466,0.0015637814],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976522,0.00012397605,0.00045459135,0.000792705,0.00032859016,0.0006479453],"domain_scores_gemma":[0.997352,0.00043352856,0.00016834406,0.0018138351,0.00009771173,0.00013458633],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004003891,0.00026873965,0.00027980452,0.00021676708,0.00042429153,0.00029741327,0.0021586353,0.000110235924,0.000041446663],"category_scores_gemma":[0.00034938942,0.000200917,0.00012569547,0.0015759198,0.0002491275,0.00036204903,0.000754185,0.00025029355,0.0011877413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019153478,0.00022606937,0.0004247579,0.0001408783,0.0000378695,0.00004948492,0.0011861288,0.87648153,0.003944722,0.025330663,0.01933129,0.072827466],"study_design_scores_gemma":[0.00003068202,0.00010270484,0.00023675576,0.00008895097,0.0000058911246,0.0000055690384,0.0005131138,0.9504376,0.04401,0.0005702593,0.0037449885,0.00025345496],"about_ca_topic_score_codex":0.00007214748,"about_ca_topic_score_gemma":0.00006479775,"teacher_disagreement_score":0.96422917,"about_ca_system_score_codex":0.00012376899,"about_ca_system_score_gemma":0.000042536274,"threshold_uncertainty_score":0.9995899},"labels":[],"label_agreement":null},{"id":"W4360996114","doi":"10.1109/isaiee57420.2022.00022","title":"Performance Analysis of Utilizing Reed Solomon Code in Redundant Array of Independent Disk","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"RAID; Computer science; Disk array; Coding (social sciences); Parallel computing; Code (set theory); Computer hardware; Mathematics; Programming language","score_opus":0.02396913508030309,"score_gpt":0.26419651266359656,"score_spread":0.24022737758329346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360996114","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":[0.7519012,0.000074139745,0.24591199,0.0001147477,0.000055742184,0.00010490573,0.000031797936,0.00013795137,0.001667533],"genre_scores_gemma":[0.9548242,0.000031933738,0.04503902,0.000017035467,9.820287e-7,0.000017548771,0.000008454877,0.000003892939,0.00005693205],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986183,0.00004602065,0.00040244768,0.00033230125,0.00040359347,0.00019732858],"domain_scores_gemma":[0.99869424,0.00006260712,0.00024235704,0.000948528,0.000033526787,0.000018714662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041993058,0.000092841845,0.00031765533,0.0007170612,0.000063025305,0.000008246374,0.001390306,0.000029725881,0.000031314095],"category_scores_gemma":[0.00005538665,0.000087210894,0.000068157526,0.002696196,0.00008579461,0.0003732806,0.0011137234,0.00019734784,7.3165137e-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":[0.00012936666,0.000808169,0.32464492,0.000107136504,0.000635879,0.000060420127,0.0050257193,0.21276268,0.23784465,0.12502931,0.00011201996,0.09283973],"study_design_scores_gemma":[0.0007346267,0.00053517194,0.10344934,0.00002915276,0.0001230604,0.00001063321,0.0049931547,0.6372688,0.24921703,0.002707038,0.0004492916,0.00048270126],"about_ca_topic_score_codex":0.00014741615,"about_ca_topic_score_gemma":0.00025541006,"teacher_disagreement_score":0.42450613,"about_ca_system_score_codex":0.000120445075,"about_ca_system_score_gemma":0.000043078595,"threshold_uncertainty_score":0.3556357},"labels":[],"label_agreement":null},{"id":"W4366158728","doi":"10.1007/978-3-031-20002-1_8","title":"Constant Amortized Complexity Algorithm","year":2023,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on distributed computing theory","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Amortized analysis; Swap (finance); Computer science; Constant (computer programming); Algorithm; Set (abstract data type); Mathematics; Data structure; Combinatorics; Theoretical computer science; Programming language","score_opus":0.03270902441127518,"score_gpt":0.2575149012246038,"score_spread":0.22480587681332861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366158728","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007691881,0.00038877898,0.94266504,0.0005212375,0.00093974674,0.0005736755,0.002571193,0.007636225,0.044696383],"genre_scores_gemma":[0.114700474,0.0010436765,0.788525,0.004263485,0.0023336858,0.00033272503,0.0056846463,0.00212501,0.080991305],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948629,0.00028470292,0.0009429926,0.0018952452,0.00096586096,0.0010482699],"domain_scores_gemma":[0.98983145,0.0055050706,0.00093159685,0.0033050359,0.00022195543,0.00020491488],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012210845,0.0011820561,0.0013881706,0.0006169524,0.00062706845,0.00033084152,0.004424606,0.0008217917,0.00011819849],"category_scores_gemma":[0.0020583402,0.0010978995,0.0004947307,0.00037869526,0.0011583443,0.00016355907,0.002312376,0.001634805,0.0007012943],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003094309,0.000027419948,2.5320796e-7,0.000027699525,0.00021822998,0.0002833528,0.000025250092,0.00031300756,0.00001530372,0.7314507,0.0037273255,0.26388055],"study_design_scores_gemma":[0.0002683823,0.00011223002,0.00001579457,0.00063267426,0.00008785103,0.00006102673,0.000017773664,0.009958175,0.0014452433,0.9675218,0.018620674,0.0012583626],"about_ca_topic_score_codex":0.0000055764967,"about_ca_topic_score_gemma":0.000004840914,"teacher_disagreement_score":0.26262218,"about_ca_system_score_codex":0.00048725627,"about_ca_system_score_gemma":0.00020816056,"threshold_uncertainty_score":0.9991471},"labels":[],"label_agreement":null},{"id":"W4366283405","doi":"10.1038/d41586-023-01275-8","title":"Stat checkers: make reproducible computer code mandatory","year":2023,"lang":"en","type":"letter","venue":"Nature","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Code (set theory); Programming language; Computational biology; Biology; Set (abstract data type)","score_opus":0.022792286367368242,"score_gpt":0.28091825643539275,"score_spread":0.2581259700680245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366283405","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001895441,0.002093554,0.17979513,0.8028511,0.0068308357,0.00048906833,0.0006306692,0.0068291523,0.00046156373],"genre_scores_gemma":[0.000023938153,0.0002182383,0.26604608,0.71811193,0.004549577,0.00006313215,0.0010660489,0.0001392936,0.009781728],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99558544,0.0000717583,0.00036247866,0.002286402,0.00089609006,0.00079782837],"domain_scores_gemma":[0.99386597,0.00018723146,0.0002985384,0.005423239,0.00017291402,0.000052093634],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0003820409,0.0005508727,0.0005483501,0.00048983964,0.00015038578,0.0002951397,0.0048689535,0.0066509056,0.000016125012],"category_scores_gemma":[0.00023313175,0.0005081127,0.00015512925,0.0010161337,0.00017470165,0.0005385158,0.0028083306,0.018098582,0.00077966915],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018342245,0.000008399451,0.000006669711,0.00011071206,0.00004288488,0.0021748466,0.00004385267,0.000021360614,0.000011725835,0.0010176016,0.97887695,0.017683148],"study_design_scores_gemma":[0.00016349845,0.000049287202,0.000041199255,0.00010758952,0.000012016785,0.00006495543,0.00000561233,0.0007011177,0.00036717043,0.0065190154,0.99139756,0.00057095033],"about_ca_topic_score_codex":0.0000055056903,"about_ca_topic_score_gemma":0.00001136767,"teacher_disagreement_score":0.08625095,"about_ca_system_score_codex":0.00021930966,"about_ca_system_score_gemma":0.00013898549,"threshold_uncertainty_score":0.99999833},"labels":[],"label_agreement":null},{"id":"W4367309807","doi":"10.1016/j.memori.2023.100051","title":"A review on computational storage devices and near memory computing for high performance applications","year":2023,"lang":"en","type":"review","venue":"Memories - Materials Devices Circuits and Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Computer data storage; Bottleneck; Scalability; Computation; Data processing; Distributed computing; Big data; Embedded system; Parallel computing; Computer engineering; Computer hardware; Database; Operating system","score_opus":0.06621883828946713,"score_gpt":0.3217407566733221,"score_spread":0.25552191838385496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367309807","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018667437,0.9543639,0.038694102,0.000049649956,0.0010982112,0.004099052,0.0007217041,0.00076562626,0.000021069993],"genre_scores_gemma":[0.0013427646,0.992874,0.0030544256,0.0001782187,0.00033890695,0.0015219407,0.0005473857,0.00008288479,0.000059463255],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964527,0.00022095747,0.00130773,0.0011729329,0.00036234257,0.0004833734],"domain_scores_gemma":[0.996496,0.00094816607,0.001314387,0.00095638906,0.0001821036,0.00010295285],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012044726,0.0006756382,0.0024212715,0.00023026313,0.0007145585,0.0011332642,0.0012531402,0.00027190673,0.0000023708878],"category_scores_gemma":[0.000097121265,0.00054479437,0.00008646183,0.00059631193,0.00021461005,0.0006097367,0.0006719809,0.00020034725,0.00004970662],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012578956,0.00001859256,0.000002050836,0.33357155,0.00014154344,0.0000079514375,0.00009534286,0.00012855223,0.0000013195345,0.013395017,0.00042886645,0.652208],"study_design_scores_gemma":[0.00026528272,0.00017496005,0.000029342076,0.087486476,0.00036419783,0.0002081507,0.00007875685,0.002301669,0.000005384268,0.00039100792,0.9076146,0.0010801965],"about_ca_topic_score_codex":0.000021502394,"about_ca_topic_score_gemma":0.0000035804617,"teacher_disagreement_score":0.90718573,"about_ca_system_score_codex":0.00009872014,"about_ca_system_score_gemma":0.00015467657,"threshold_uncertainty_score":0.9999037},"labels":[],"label_agreement":null},{"id":"W4368408252","doi":"10.1145/3578353.3589544","title":"Is Bare-metal I/O Performance with User-defined Storage Drives Inside VMs Possible?: Benchmarking libvfio-user vs. Common Storage Virtualization Configurations","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Operating system; Computer science; Virtualization; Virtual machine; Cloud computing; Embedded system; Process (computing); Booting; PCI Express; Hardware virtualization; Full virtualization; Field-programmable gate array","score_opus":0.018103289700117896,"score_gpt":0.25310438329375434,"score_spread":0.23500109359363644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368408252","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":[0.3941912,0.000045838988,0.59837306,0.0010998169,0.00032575647,0.00042739513,0.000046079902,0.0033463473,0.002144494],"genre_scores_gemma":[0.94958884,0.00015660732,0.047553018,0.0006273954,0.000058663074,0.000095079646,0.00022410984,0.000052757805,0.0016435485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99709356,0.00009064793,0.00052314834,0.0009286601,0.00070337916,0.00066061236],"domain_scores_gemma":[0.9974733,0.000236618,0.00022200057,0.0017323667,0.00020396936,0.00013172188],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002967343,0.00044689453,0.0004379305,0.0007113676,0.00068660214,0.00045957664,0.0016421326,0.00018878814,0.00010700421],"category_scores_gemma":[0.00010952181,0.00038378898,0.000074513126,0.0029153198,0.00026189914,0.00432203,0.0009129931,0.00039096718,0.0002491281],"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":[0.00022232314,0.0005697883,0.046232656,0.00035452459,0.00045955068,0.00070808316,0.01341302,0.07724601,0.02516536,0.6993506,0.050267044,0.086011015],"study_design_scores_gemma":[0.0029188967,0.0021906309,0.16176501,0.0004632115,0.00009912982,0.00016225853,0.0025033704,0.70459014,0.057714168,0.002492036,0.06197412,0.0031270038],"about_ca_topic_score_codex":0.00008674043,"about_ca_topic_score_gemma":0.00024288215,"teacher_disagreement_score":0.6968586,"about_ca_system_score_codex":0.00015275985,"about_ca_system_score_gemma":0.0001529944,"threshold_uncertainty_score":0.9998614},"labels":[],"label_agreement":null},{"id":"W4376311824","doi":"10.48550/arxiv.2305.06365","title":"Lifting topological codes: Three-dimensional subsystem codes from two-dimensional anyon models","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Perimeter Institute","funders":"Ministry of Colleges and Universities; Institut Périmètre de physique théorique; Industry Canada; Vlaamse regering; Fonds De La Recherche Scientifique - FNRS; Fonds Wetenschappelijk Onderzoek; Government of Canada","keywords":"Toric code; Anyon; Abelian group; Topology (electrical circuits); Computer science; Code (set theory); Class (philosophy); Physics; Quantum; Theoretical physics; Mathematics; Topological quantum computer; Pure mathematics; Quantum mechanics; Quantum computer; Combinatorics; Artificial intelligence","score_opus":0.13602286702962257,"score_gpt":0.22519009281624985,"score_spread":0.08916722578662728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376311824","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":[0.3935863,0.00020552265,0.6017526,0.00021257486,0.00085634546,0.00033745103,0.00034981713,0.0025616009,0.00013781415],"genre_scores_gemma":[0.9475807,0.00003724204,0.051529896,0.00011261699,0.00012776085,0.0000042465804,0.00024434607,0.000045156365,0.0003180573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954887,0.00021114566,0.0004973651,0.0026641458,0.00036931035,0.00076930167],"domain_scores_gemma":[0.9954094,0.0009263479,0.0005331405,0.0026227073,0.0002837701,0.0002245859],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00045546473,0.00068091706,0.0008514643,0.00043472208,0.0004111733,0.00017295443,0.0040333485,0.0007167524,0.00003137544],"category_scores_gemma":[0.0001799003,0.00071069127,0.00030814324,0.00086800853,0.00045837968,0.0009440969,0.011456422,0.0013482596,0.00030900683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003561323,0.00005138267,0.0009680706,0.000026847596,0.00011158794,0.0013209885,0.00004510024,0.8158584,0.00012750963,0.18087146,0.00031935464,0.00026367212],"study_design_scores_gemma":[0.00036233137,0.00003827131,0.00023429279,0.00018006189,0.000037743885,0.000009011822,0.000046577294,0.6377069,0.0001976728,0.36063987,0.000028598399,0.00051869854],"about_ca_topic_score_codex":0.0011479838,"about_ca_topic_score_gemma":0.0006226381,"teacher_disagreement_score":0.55399436,"about_ca_system_score_codex":0.00046437257,"about_ca_system_score_gemma":0.00026920796,"threshold_uncertainty_score":0.9995344},"labels":[],"label_agreement":null},{"id":"W4377093063","doi":"10.1038/s41597-023-02174-3","title":"M100 ExaData: a data collection campaign on the CINECA’s Marconi100 Tier-0 supercomputer","year":2023,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Supercomputer; Computer science; Workload; Software; Data science; Operating system","score_opus":0.15939045995022397,"score_gpt":0.31590441355818877,"score_spread":0.1565139536079648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377093063","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005880384,0.00020918717,0.9320571,0.02411447,0.011873379,0.0014045639,0.017225709,0.005376137,0.0018590789],"genre_scores_gemma":[0.18524434,0.0005768078,0.54632723,0.0053664735,0.0016331597,0.00037028294,0.17430028,0.00032000506,0.0858614],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9954464,0.00014775908,0.00033979357,0.0024983073,0.0008930971,0.0006746711],"domain_scores_gemma":[0.9760736,0.00050638703,0.00011079656,0.023129512,0.000088855,0.00009080119],"candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.0034058094,0.0002569326,0.00021343316,0.00048599514,0.0011055378,0.0017145339,0.025556305,0.00008824133,0.00007747033],"category_scores_gemma":[0.0011397288,0.0001825119,0.000028177465,0.004464674,0.0005510214,0.0044338536,0.026898306,0.00037424767,0.002351698],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035566018,0.00003565397,0.000021442174,0.0000072246594,0.000014324251,0.000039965995,0.00010949307,0.000032534805,0.00038411305,0.010978709,0.9600029,0.028370082],"study_design_scores_gemma":[0.00018948143,0.000044857876,0.0003291205,0.00003630315,0.000009113205,0.000027484453,0.0002215569,0.251601,0.00062613003,0.0058036917,0.74081296,0.00029829552],"about_ca_topic_score_codex":0.000055845067,"about_ca_topic_score_gemma":0.00012768076,"teacher_disagreement_score":0.38572985,"about_ca_system_score_codex":0.00008442181,"about_ca_system_score_gemma":0.00023847868,"threshold_uncertainty_score":0.99932176},"labels":[],"label_agreement":null},{"id":"W4380669379","doi":"10.1145/3578338.3593533","title":"Architectural Support for Efficient Data Movement in Fully Disaggregated Systems","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Server; Data center; Bandwidth (computing); Scaling; Distributed computing; Elasticity (physics); Computer network","score_opus":0.04955384594743171,"score_gpt":0.3034721709201585,"score_spread":0.25391832497272676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380669379","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":[0.025645863,0.000042829062,0.969644,0.0011136734,0.0004825846,0.00075356185,0.00018595131,0.0019307061,0.00020083463],"genre_scores_gemma":[0.88298184,0.00001127833,0.11424975,0.00022883258,0.000039678438,0.00029501063,0.0006891512,0.000024137587,0.001480347],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837637,0.00001812412,0.00027868015,0.0006341982,0.00024622987,0.00044639778],"domain_scores_gemma":[0.99768627,0.00015249339,0.000067780726,0.0020229886,0.000028553155,0.000041945692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043949793,0.000133307,0.00016794834,0.0002620974,0.000057036308,0.000103980434,0.0028220334,0.000043413747,0.000003332866],"category_scores_gemma":[0.00020539353,0.00010660236,0.000020793781,0.0009297683,0.000050276147,0.0002913674,0.0026081775,0.00009121243,0.00007978048],"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":[0.000054445198,0.00027754798,0.001060067,0.0002935853,0.00006635915,0.00035663028,0.00085115584,0.2411587,0.004879231,0.40584522,0.043193266,0.30196378],"study_design_scores_gemma":[0.00041233312,0.00008604038,0.0006020672,0.000022487347,0.0000017232938,0.000007809566,0.00019229845,0.988989,0.00092180684,0.0024144903,0.0061541107,0.00019583864],"about_ca_topic_score_codex":0.00006596287,"about_ca_topic_score_gemma":0.00005984463,"teacher_disagreement_score":0.8573359,"about_ca_system_score_codex":0.00007027152,"about_ca_system_score_gemma":0.000043359996,"threshold_uncertainty_score":0.5244087},"labels":[],"label_agreement":null},{"id":"W4382198979","doi":"10.1145/3606376.3593533","title":"Architectural Support for Efficient Data Movement in Fully Disaggregated Systems","year":2023,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cache; Dram; Interleaved memory; Cache-only memory architecture; Registered memory; Overlay; Data center; Memory map; Server; Semiconductor memory; Embedded system; Operating system; Memory management; Computer hardware","score_opus":0.14846856336504663,"score_gpt":0.3828089313179465,"score_spread":0.2343403679528999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382198979","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":[0.116940886,0.1186746,0.7318565,0.007225177,0.0036077942,0.018007858,0.00049309235,0.0029032764,0.00029080245],"genre_scores_gemma":[0.7240189,0.13025306,0.13094212,0.0023247255,0.00019441074,0.005665691,0.0061161625,0.00010739197,0.0003775866],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99657845,0.00012166638,0.0007942723,0.0008174304,0.0011796077,0.0005085591],"domain_scores_gemma":[0.99479413,0.00056190445,0.000374227,0.0038812372,0.00032845006,0.000060033773],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006991586,0.00022908028,0.0004141363,0.0009204262,0.00012750228,0.000103377686,0.004338193,0.00006535573,0.000012932977],"category_scores_gemma":[0.0088920975,0.00019528413,0.000050074166,0.0073955683,0.00004624836,0.0007664122,0.0022891306,0.00018705026,0.00018043096],"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":[0.0000043708533,0.000043600365,0.00055020844,0.0015987917,0.000014056922,0.0000035461214,0.000045167122,0.034649387,0.000031476495,0.001066882,0.0057334006,0.95625913],"study_design_scores_gemma":[0.0005325565,0.00013446057,0.0028399583,0.0009776604,0.000031895717,0.0000065901695,0.000017039614,0.9808156,0.00009026946,0.00035005194,0.013930325,0.00027360054],"about_ca_topic_score_codex":0.000005941583,"about_ca_topic_score_gemma":0.0000026645498,"teacher_disagreement_score":0.9559855,"about_ca_system_score_codex":0.00027984002,"about_ca_system_score_gemma":0.00021015936,"threshold_uncertainty_score":0.9994564},"labels":[],"label_agreement":null},{"id":"W4383176085","doi":"10.5281/zenodo.8107729","title":"Creating a DH workflow in the SSH Open Marketplace","year":2023,"lang":"en","type":"paratext","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canarie","funders":"","keywords":"Workflow; Computer science; Open source; Operating system; World Wide Web; Database; Software","score_opus":0.05801779100125045,"score_gpt":0.29732935455218745,"score_spread":0.239311563550937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383176085","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000071531496,0.00036439023,0.17785762,0.002881025,0.0005942155,0.0017432455,0.00055308593,0.002433375,0.8135015],"genre_scores_gemma":[0.04899058,0.0099659655,0.18132496,0.0053918464,0.0026879231,0.00001094977,0.04249136,0.027549224,0.6815872],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964999,0.00082833046,0.00040692245,0.0009990204,0.00061623985,0.0006495743],"domain_scores_gemma":[0.9969338,0.00022822658,0.0002661495,0.0022169822,0.00027405465,0.00008077244],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.0021350884,0.0003003303,0.00032489756,0.00051609904,0.0021129195,0.0047877366,0.016963892,0.0002038129,0.0049527055],"category_scores_gemma":[0.0020992763,0.00026282444,0.00005705474,0.0026496053,0.0002054393,0.0009879494,0.018400893,0.0010836531,0.08125595],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015262862,0.00004538528,1.3513043e-7,0.000047464575,0.000017171658,0.00006714585,0.0007612129,0.00019547617,0.000036094734,0.006691641,0.8593327,0.13279034],"study_design_scores_gemma":[0.00029308046,0.00010826535,0.000036142283,0.00017809813,0.0000047278745,0.00008401792,0.0003965834,0.0015717653,0.000028441082,0.0015920798,0.99540704,0.0002997288],"about_ca_topic_score_codex":0.0000631506,"about_ca_topic_score_gemma":0.0000025644376,"teacher_disagreement_score":0.13607441,"about_ca_system_score_codex":0.00029922527,"about_ca_system_score_gemma":0.000015088021,"threshold_uncertainty_score":0.9999824},"labels":[],"label_agreement":null},{"id":"W4383468758","doi":"10.48550/arxiv.2307.01343","title":"HPC-driven computational reproducibility in numerical relativity codes: A use case study with IllinoisGRMHD","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Dementia Research Alliance","funders":"Office of Advanced Cyberinfrastructure; U.S. Department of Energy; High Energy Physics; Office of Science; National Science Foundation","keywords":"Computer science; Compiler; Code (set theory); Software; Source code; Cornerstone; Reproducibility; Computational science; Programming language; Mathematics","score_opus":0.1578610961721065,"score_gpt":0.24535473862911675,"score_spread":0.08749364245701025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383468758","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":[0.5038607,0.000004236547,0.49446464,0.000070006354,0.000104904844,0.0006167215,0.000048385515,0.00081837457,0.000012037627],"genre_scores_gemma":[0.95614266,0.00000999952,0.043557078,0.000019825644,0.000015295884,0.0000078881985,0.000034392993,0.000028586352,0.00018430062],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99416167,0.00043869126,0.00038940774,0.0043439968,0.00022222415,0.00044403897],"domain_scores_gemma":[0.9929976,0.0007401915,0.000392104,0.0054987115,0.00024785858,0.00012354046],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00090431666,0.0004496473,0.00062113476,0.0005291064,0.00019424317,0.00014462047,0.0018982937,0.00027673345,0.000003327281],"category_scores_gemma":[0.00077231444,0.00047146907,0.00010533744,0.0020728093,0.0003316724,0.0012015979,0.005542418,0.0013783848,0.000044298602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056043908,0.0005201677,0.16344056,0.000027081926,0.00007197461,0.037935227,0.00072187034,0.78427994,6.567344e-7,0.012641479,0.000039564267,0.00026547018],"study_design_scores_gemma":[0.0010997026,0.00037526884,0.041609272,0.000095007905,0.000058583948,0.00028665803,0.0014809543,0.9012626,0.0000061159294,0.05288388,0.000033503435,0.0008084772],"about_ca_topic_score_codex":0.002515826,"about_ca_topic_score_gemma":0.002056992,"teacher_disagreement_score":0.45228195,"about_ca_system_score_codex":0.00063120754,"about_ca_system_score_gemma":0.00030869016,"threshold_uncertainty_score":0.9997737},"labels":[],"label_agreement":null},{"id":"W4384080299","doi":"10.1109/access.2023.3294544","title":"On the Design of SSRS and RS Codes for Enhancing the Integrity of Information Storage in NAND Flash Memories","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Technology Karnataka, Surathkal; Visvesvaraya Technological University; McMaster University; Ministry of Education, India; Institution of Engineers (India); Department of Science and Technology, Ministry of Science and Technology, India; Indian Institute of Science","keywords":"Computer science; NAND gate; Flash memory; Computer data storage; Error detection and correction; BCH code; Flash (photography); Computer hardware; Bit error rate; Encoding (memory); Decoding methods; Algorithm; Logic gate","score_opus":0.0526912553273308,"score_gpt":0.3145653850546312,"score_spread":0.2618741297273004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384080299","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":[0.33735123,0.000017819335,0.6618378,0.00033605233,0.00010380331,0.0002656907,0.00001081031,0.000059938367,0.000016846157],"genre_scores_gemma":[0.99311423,0.00004158308,0.0067187827,0.000056124634,0.000004839462,0.00005497141,0.0000013678396,0.0000025596287,0.00000553957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993884,0.00004398611,0.00021148221,0.00009939918,0.00013900302,0.00011774112],"domain_scores_gemma":[0.9978694,0.0015150993,0.00015905558,0.00038413776,0.00006505891,0.000007287407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082230254,0.000068972106,0.00011989027,0.00012597487,0.000074596166,0.000073316376,0.0010779185,0.000039575993,3.8349356e-7],"category_scores_gemma":[0.00091957586,0.000039065388,0.000014443393,0.00055384025,0.00014750607,0.001337667,0.0002709402,0.00012382325,0.0000010616202],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035306314,0.00012057619,0.0025987749,0.00092757924,0.000107304826,0.000009318999,0.031341683,0.12688766,0.039154116,0.4721654,0.01686086,0.30947363],"study_design_scores_gemma":[0.0004321342,0.00018690721,0.0042213523,0.00016602718,0.0000068134523,0.000001928602,0.0020225397,0.087949045,0.72621816,0.17833467,0.00028206632,0.00017834743],"about_ca_topic_score_codex":0.000028120017,"about_ca_topic_score_gemma":0.000085626045,"teacher_disagreement_score":0.68706405,"about_ca_system_score_codex":0.000019902727,"about_ca_system_score_gemma":0.000033650627,"threshold_uncertainty_score":0.20030585},"labels":[],"label_agreement":null},{"id":"W4385249512","doi":"10.1016/j.jpdc.2023.104746","title":"Mixed precision support in HPC applications: What about reliability?","year":2023,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Intel Corporation","keywords":"Computer science; Leverage (statistics); Reliability (semiconductor); Supercomputer; Double-precision floating-point format; Exascale computing; Single-precision floating-point format; Floating point; Computer engineering; Parallel computing; Operating system; Machine learning","score_opus":0.02413579568500913,"score_gpt":0.28514081126150914,"score_spread":0.2610050155765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385249512","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":[0.08895513,0.0006884092,0.90872085,0.0011082971,0.00019710073,0.0001404581,0.000008369398,0.00016633247,0.0000150858705],"genre_scores_gemma":[0.8715416,0.001006662,0.127287,0.000053720254,0.00005820543,0.000006654092,0.000029558052,0.0000067232445,0.0000098662695],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984525,0.000055998884,0.000646881,0.00027913155,0.0002794518,0.00028605768],"domain_scores_gemma":[0.9985804,0.00037449235,0.0004028774,0.0004091602,0.00015096065,0.00008211504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009519918,0.00012846572,0.00027881545,0.00025790388,0.000111443966,0.00022800156,0.0008324738,0.00008369361,0.000001487151],"category_scores_gemma":[0.00033045374,0.000110427405,0.000057682966,0.0010736784,0.0000689125,0.0013540329,0.0006429369,0.00030331945,0.000013796161],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050074537,0.00018732499,0.008561038,0.000080186386,0.000024539837,0.00031685177,0.0005552919,0.09979893,0.00037063527,0.01806971,0.004788557,0.86719686],"study_design_scores_gemma":[0.004296354,0.0007640109,0.13018452,0.0009023106,0.00003136165,0.0008695432,0.0041999253,0.5282002,0.0006687999,0.26864144,0.060165796,0.0010756875],"about_ca_topic_score_codex":0.0000022495308,"about_ca_topic_score_gemma":0.0000015722923,"teacher_disagreement_score":0.8661212,"about_ca_system_score_codex":0.00007268965,"about_ca_system_score_gemma":0.00005837633,"threshold_uncertainty_score":0.45030987},"labels":[],"label_agreement":null},{"id":"W4386124507","doi":"10.1109/tcomm.2023.3308153","title":"Efficient Constrained Codes That Enable Page Separation in Modern Flash Memories","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, San Diego; University of Oxford; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; University of Warwick; California Institute of Technology; York University; Massachusetts Institute of Technology; Princeton University; National Science Foundation","keywords":"Computer science; Decoding methods; Coding (social sciences); Flash memory; Variable-length code; Flash file system; Theoretical computer science; Algorithm; Computer engineering; Computer hardware; Mathematics; Computer memory","score_opus":0.055586202226156456,"score_gpt":0.31395266680229666,"score_spread":0.2583664645761402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386124507","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":[0.008849537,0.000095025585,0.9838514,0.0030864663,0.00021575594,0.0003612494,0.000095575684,0.001772325,0.0016727104],"genre_scores_gemma":[0.94236255,0.00034869628,0.056470662,0.00006937102,0.0000039013894,0.0002838963,0.000026938247,0.000014186651,0.0004198214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866563,0.00012764269,0.00028617468,0.00035444958,0.00024775253,0.00031837836],"domain_scores_gemma":[0.99627256,0.0005568976,0.00008658958,0.0029666112,0.000067713954,0.000049642764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003045741,0.0001734949,0.00019068294,0.0005193763,0.0005366023,0.00011239821,0.002055223,0.000103601546,0.000008510987],"category_scores_gemma":[0.000027768034,0.00018430423,0.000063903484,0.001617729,0.0003306137,0.00041295405,0.000049335933,0.00040913487,0.00021059923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001771016,0.00064677256,0.000031335465,0.000025611118,0.00005179515,0.000017804123,0.0041034217,0.8343007,0.012964163,0.039736237,0.0008197568,0.10728469],"study_design_scores_gemma":[0.00038017123,0.000045643712,0.00007559693,0.000040383275,0.00000883671,0.000008903702,0.00071754685,0.9587722,0.024825923,0.013590904,0.0012834725,0.00025045223],"about_ca_topic_score_codex":0.00002928616,"about_ca_topic_score_gemma":0.00055321306,"teacher_disagreement_score":0.933513,"about_ca_system_score_codex":0.00014523978,"about_ca_system_score_gemma":0.00008664644,"threshold_uncertainty_score":0.7515708},"labels":[],"label_agreement":null},{"id":"W4387414063","doi":"10.2139/ssrn.4594417","title":"Construction of Locally Repairable Codes Using Rate H-1/H Reed-Solomon Codes for Distributed Storage Systems","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Reed–Solomon error correction; Computer science; Distributed data store; Block code; Concatenated error correction code; Algorithm; Decoding methods; Distributed computing","score_opus":0.0284884631786,"score_gpt":0.28000266494153736,"score_spread":0.2515142017629374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387414063","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":[0.022557685,0.003301183,0.9700021,0.00020269249,0.0017966881,0.000737495,0.0005051418,0.0008898529,0.000007121083],"genre_scores_gemma":[0.82578444,0.005568774,0.16751622,0.000012828959,0.00034808632,0.000107392734,0.00031541573,0.00012183147,0.00022497794],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950388,0.00025468864,0.0010793684,0.0008712944,0.00046922077,0.0022866363],"domain_scores_gemma":[0.99579215,0.00030879764,0.0018493101,0.0013192191,0.0006457913,0.000084723055],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0039317613,0.00045125818,0.0009096065,0.00046984025,0.00037431536,0.00029659815,0.0023016287,0.000511468,5.763097e-7],"category_scores_gemma":[0.0007510797,0.00046037795,0.00028114198,0.00058325985,0.00030529505,0.000644637,0.0013254838,0.0031351347,0.0000033062977],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020718353,0.00010647396,0.000309091,0.0006807827,0.0010702483,0.000059744307,0.00012956827,0.32677028,0.0057299566,0.65465385,0.00034432532,0.009938489],"study_design_scores_gemma":[0.0007342174,0.0004694151,0.000024011755,0.0006947174,0.00012529247,0.00088370574,0.0015082436,0.36228818,0.0018730446,0.63055474,0.00022023288,0.00062419416],"about_ca_topic_score_codex":0.00028126957,"about_ca_topic_score_gemma":0.00026827794,"teacher_disagreement_score":0.80322677,"about_ca_system_score_codex":0.002799373,"about_ca_system_score_gemma":0.003960621,"threshold_uncertainty_score":0.99978477},"labels":[],"label_agreement":null},{"id":"W4388264823","doi":"10.1145/3630614.3630616","title":"The Dirty Secret of SSDs: Embodied Carbon","year":2023,"lang":"en","type":"article","venue":"ACM SIGEnergy Energy Informatics Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Scalability; Computer science; Sustainability; Reuse; Greenhouse gas; Process engineering; Nanotechnology; Engineering; Waste management; Operating system; Materials science","score_opus":0.023497509337612854,"score_gpt":0.2706835783539496,"score_spread":0.24718606901633677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388264823","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002301978,0.30416498,0.5945863,0.012119338,0.0027967328,0.0012604572,0.00010403777,0.007901438,0.074764706],"genre_scores_gemma":[0.025747316,0.9005314,0.06943872,0.002808714,0.00007070835,0.0003350661,0.00016280905,0.000048011527,0.00085725024],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976791,0.00007100254,0.0010482596,0.00018667828,0.00052974507,0.0004851913],"domain_scores_gemma":[0.99527746,0.0005198559,0.0006192811,0.0033603094,0.00014899706,0.00007411702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007127997,0.00025478165,0.0004721433,0.0001482957,0.00018980987,0.00006104603,0.0046357773,0.00010073954,0.0000035781904],"category_scores_gemma":[0.0011370332,0.00016702239,0.00013429386,0.001877127,0.00017891332,0.00055845035,0.0026418678,0.00014883331,0.00002826888],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014630414,0.000011035124,0.000009480328,0.00062911614,0.0000611077,0.000007975096,0.00015441739,0.0009897518,0.000065359294,0.48481026,0.008705049,0.504555],"study_design_scores_gemma":[0.0001538854,0.00007440903,0.000014953553,0.000826996,0.000027166141,0.000017828504,0.000116944524,0.02594808,0.00515576,0.03273819,0.9345349,0.00039086325],"about_ca_topic_score_codex":0.000052097013,"about_ca_topic_score_gemma":0.000040410352,"teacher_disagreement_score":0.9258299,"about_ca_system_score_codex":0.0000533571,"about_ca_system_score_gemma":0.00010565722,"threshold_uncertainty_score":0.8614505},"labels":[],"label_agreement":null},{"id":"W4389162168","doi":"10.1145/3611643.3613871","title":"Dead Code Removal at Meta: Automatically Deleting Millions of Lines of Code and Petabytes of Deprecated Data","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Codebase; Code (set theory); Database; Consistency (knowledge bases); Petabyte; Source lines of code; Software; Asset (computer security); Reliability (semiconductor); Software engineering; Operating system; Programming language; Computer security; Set (abstract data type)","score_opus":0.10631005133543875,"score_gpt":0.3262006704612547,"score_spread":0.21989061912581598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389162168","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37623566,0.0009064754,0.6200647,0.000812098,0.000052720367,0.00019107977,0.00059402856,0.00095081754,0.00019243901],"genre_scores_gemma":[0.3137098,0.00020423779,0.68592113,0.00001298978,0.0000033152226,0.0000043538416,0.000055885932,0.000008524857,0.00007978804],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985757,0.000042607764,0.00051734183,0.00040448032,0.00025848034,0.00020139138],"domain_scores_gemma":[0.9971113,0.00075985515,0.00026688387,0.0016734839,0.00015359673,0.00003483266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046405982,0.00012930715,0.00044403397,0.00019943011,0.000049766113,0.0000114021595,0.0017635074,0.00006587752,0.00001018132],"category_scores_gemma":[0.0015697305,0.00010064666,0.000041957206,0.0009071834,0.0003058521,0.00041691377,0.004172224,0.00007109223,0.000004842223],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052276602,0.0003206035,0.0055620656,0.0011594229,0.0016481281,0.00014109234,0.00092254265,0.0030811317,0.7556703,0.12443787,0.009596447,0.09740811],"study_design_scores_gemma":[0.0003986365,0.000104318715,0.0026796598,0.00008670749,0.00023158386,0.00006545633,0.00020990512,0.6455715,0.34198666,0.007010793,0.0013822586,0.00027253685],"about_ca_topic_score_codex":0.00004975595,"about_ca_topic_score_gemma":0.00019840476,"teacher_disagreement_score":0.6424903,"about_ca_system_score_codex":0.000008976369,"about_ca_system_score_gemma":0.000037204754,"threshold_uncertainty_score":0.5200379},"labels":[],"label_agreement":null},{"id":"W4389392180","doi":"10.1088/1742-6596/2649/1/012056","title":"Analysis of Verilog-based improvements to the memory transfer","year":2023,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Verilog; Computer architecture; Power consumption; Variety (cybernetics); Acceleration; Embedded system; Power (physics); Field-programmable gate array; Artificial intelligence","score_opus":0.030404685324925657,"score_gpt":0.2721708525004474,"score_spread":0.24176616717552177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389392180","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":[0.108130515,0.000016289143,0.8893399,0.00207845,0.00020112559,0.000080927224,0.00003350119,0.000068238296,0.000051030594],"genre_scores_gemma":[0.99181587,0.000024658884,0.007930475,0.00014988052,0.000029928819,0.000005136122,0.0000036826596,0.0000053811405,0.000034976438],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884975,0.00003859465,0.00035355164,0.00015423946,0.00041690262,0.00018698885],"domain_scores_gemma":[0.9986865,0.00009573634,0.0001916654,0.0006095387,0.00037178007,0.000044807653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003000055,0.00011839528,0.00033839975,0.00029744106,0.00007087534,0.000066775116,0.0015340393,0.00003240886,0.000008353118],"category_scores_gemma":[0.000085667016,0.00008077182,0.00016448183,0.0024579177,0.000121315745,0.0008098307,0.00019567403,0.00016080316,0.000008106189],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013345412,0.00015660984,0.0008515946,0.000057399717,0.0013495843,0.000057368485,0.0042600636,0.06451432,0.10978816,0.14635602,0.0010169252,0.67145854],"study_design_scores_gemma":[0.0005209712,0.0009591765,0.008795414,0.00006791576,0.00038209482,0.0000033278097,0.0017037112,0.01933039,0.9392844,0.026596239,0.002018226,0.0003381352],"about_ca_topic_score_codex":0.000008170397,"about_ca_topic_score_gemma":0.00002263378,"teacher_disagreement_score":0.88368535,"about_ca_system_score_codex":0.000026591639,"about_ca_system_score_gemma":0.00017208324,"threshold_uncertainty_score":0.32937792},"labels":[],"label_agreement":null},{"id":"W4389476308","doi":"10.1145/3613424.3623789","title":"Utopia: Fast and Efficient Address Translation via Hybrid Restrictive &amp; Flexible Virtual-to-Physical Address Mappings","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"VMware; Semiconductor Research Corporation","keywords":"Computer science; Physical address; Flexibility (engineering); Virtual memory; Translation (biology); Distributed computing; Swap (finance); Latency (audio); Virtual machine; Memory management; Embedded system; Overlay; Operating system","score_opus":0.03379198074303926,"score_gpt":0.28855484773656614,"score_spread":0.2547628669935269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389476308","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":[0.15040217,0.000018718216,0.84475887,0.0010078931,0.00016865028,0.0003771531,0.00003857289,0.0023969924,0.0008309978],"genre_scores_gemma":[0.94308776,0.000018812269,0.055349752,0.00016247561,0.000063468164,0.000101716694,0.000042950967,0.000023932364,0.001149135],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981157,0.000037708425,0.00021509545,0.00077413867,0.0004052269,0.00045213796],"domain_scores_gemma":[0.99865746,0.00025647925,0.00006756279,0.00082095986,0.00007569309,0.000121842895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001556264,0.00022351662,0.00024262449,0.00041720996,0.00019218167,0.0001365247,0.00085333013,0.00006377491,0.0000052637965],"category_scores_gemma":[0.00010366282,0.00020482227,0.00004722484,0.0015681529,0.00012453926,0.0005151923,0.00078719825,0.00021881588,0.00034477486],"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":[0.000055193763,0.00022066706,0.000075668744,0.000046336158,0.00005226939,0.00010127613,0.0038947691,0.044314496,0.029687548,0.17742202,0.0052982788,0.73883146],"study_design_scores_gemma":[0.0016839308,0.0007092573,0.005104995,0.0001413915,0.000031330623,0.00007737212,0.00067225896,0.8214531,0.10888059,0.02660162,0.032988135,0.0016560131],"about_ca_topic_score_codex":0.00003649921,"about_ca_topic_score_gemma":0.000010827631,"teacher_disagreement_score":0.79268557,"about_ca_system_score_codex":0.000057552134,"about_ca_system_score_gemma":0.000025931244,"threshold_uncertainty_score":0.83524096},"labels":[],"label_agreement":null},{"id":"W4389783994","doi":"10.1007/s10623-023-01341-2","title":"Optimal binary and ternary locally repairable codes with minimum distance 6","year":2023,"lang":"en","type":"article","venue":"Designs Codes and Cryptography","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linear subspace; Combinatorics; Mathematics; Ternary operation; Binary number; Intersection (aeronautics); Code (set theory); Code word; Discrete mathematics; Upper and lower bounds; Disjoint sets; Computer science; Algorithm; Arithmetic; Decoding methods; Pure mathematics","score_opus":0.01800367410080721,"score_gpt":0.23779753718322075,"score_spread":0.21979386308241353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389783994","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":[0.14908095,0.0012964667,0.8474436,0.0003870977,0.00004208179,0.00018827841,0.000038627084,0.0013565947,0.00016632245],"genre_scores_gemma":[0.55722475,0.0012223471,0.44127208,0.00012191208,0.000014760007,0.000058453083,0.00001592549,0.000020660096,0.00004912159],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984606,0.000038941733,0.00018462347,0.0006681329,0.0002260146,0.00042172143],"domain_scores_gemma":[0.99894416,0.0001550389,0.000085463325,0.0006606449,0.0000493224,0.000105391846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002033273,0.00024167591,0.0002508398,0.00031973998,0.00027913664,0.00020074286,0.0005623699,0.00008254323,0.000001972278],"category_scores_gemma":[0.000019865787,0.00019511716,0.000042507567,0.0012835342,0.0005285859,0.0006874211,0.0004335555,0.00015397466,0.0000051702204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009451609,0.0005626373,0.09399788,0.000712104,0.0006491068,0.005384675,0.0031028811,0.0062251952,0.031169409,0.6318565,0.03538453,0.19000994],"study_design_scores_gemma":[0.0063758227,0.010695428,0.08372959,0.0013592227,0.00021621822,0.0012275788,0.0061935293,0.62406904,0.013075719,0.16932584,0.07776465,0.0059673386],"about_ca_topic_score_codex":0.000013664502,"about_ca_topic_score_gemma":0.000010653282,"teacher_disagreement_score":0.61784387,"about_ca_system_score_codex":0.000008973762,"about_ca_system_score_gemma":0.00002406395,"threshold_uncertainty_score":0.79566467},"labels":[],"label_agreement":null},{"id":"W4389880933","doi":"10.1007/s10470-023-02198-0","title":"Hard-disk drive read-channel design trade-offs for areal densities beyond 2 Tb/in2","year":2023,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Works and Government Services Canada","funders":"","keywords":"Computer science; Power consumption; Patterned media; Offset (computer science); Channel (broadcasting); Computer hardware; Area density; Electronic engineering; Real-time computing; Electrical engineering; Power (physics); Engineering; Telecommunications; Head (geology)","score_opus":0.04407113161924989,"score_gpt":0.2632933852471884,"score_spread":0.21922225362793854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389880933","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":[0.0039551617,0.001041623,0.9920601,0.00069613487,0.00011659572,0.00036916608,0.00007818199,0.0014202739,0.0002627146],"genre_scores_gemma":[0.9809289,0.00015880943,0.017784646,0.00047005448,0.00007960548,0.00011115807,0.00011850288,0.00004141295,0.00030693912],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99768794,0.0000665273,0.00040492072,0.0008463442,0.00030219887,0.00069205137],"domain_scores_gemma":[0.9987129,0.00034916055,0.00020820522,0.0003658838,0.00023592793,0.00012793507],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000489989,0.00037115166,0.0004295801,0.0004502488,0.0006476315,0.00049962767,0.00081695634,0.00022623691,0.000004488329],"category_scores_gemma":[0.00017474317,0.0003128573,0.00008202595,0.0012738899,0.0002863991,0.0013290055,0.00016370942,0.00037223406,0.000010744211],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027537013,0.000054118518,0.00006691275,0.00016032493,0.000092412454,0.0001951314,0.0030738292,0.0021283936,0.01392189,0.019409958,0.0063437037,0.95452577],"study_design_scores_gemma":[0.00088713155,0.00064603955,0.0005865198,0.0004275989,0.00007822794,0.0001452017,0.005505845,0.71788424,0.01533473,0.25589883,0.0015453537,0.0010602829],"about_ca_topic_score_codex":0.000031677493,"about_ca_topic_score_gemma":0.000014970149,"teacher_disagreement_score":0.9769737,"about_ca_system_score_codex":0.00007859265,"about_ca_system_score_gemma":0.0002167973,"threshold_uncertainty_score":0.99993235},"labels":[],"label_agreement":null},{"id":"W4390097354","doi":"10.1109/tnsm.2023.3346202","title":"LMPT: A Novel Authenticated Data Structure to Eliminate Storage Bottlenecks for High Performance Blockchains","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Database transaction; Throughput; Latency (audio); Data structure; Parallel computing; Transaction processing; Computer network; Distributed computing; Operating system; Database","score_opus":0.02984141835768819,"score_gpt":0.25417483543368186,"score_spread":0.22433341707599366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390097354","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":[0.032075133,0.000017004415,0.9609888,0.003978422,0.0007520946,0.00081377797,0.00033823063,0.0010010332,0.000035494304],"genre_scores_gemma":[0.874174,0.00024810666,0.1234659,0.0013838287,0.000053854914,0.00017093396,0.00009021264,0.000030992545,0.00038216996],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981136,0.000014945322,0.00023868534,0.00084122753,0.00025195978,0.0005395963],"domain_scores_gemma":[0.99787825,0.00007845419,0.00006675476,0.0018238763,0.00005740607,0.000095243224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023017799,0.00025265972,0.00020851537,0.00026548744,0.00046180826,0.00012715138,0.0017983651,0.000085095,0.0000059281315],"category_scores_gemma":[0.0000023107687,0.0002450109,0.000023860755,0.0016637556,0.000028953003,0.00039309773,0.00015805733,0.00018103118,0.00003144748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007295497,0.00009429868,0.0000021388803,0.00027109927,0.00015829942,0.000016617638,0.00041339942,0.68441343,0.00026936777,0.0065236785,0.0026565697,0.30510813],"study_design_scores_gemma":[0.0008173766,0.00021265434,0.00062233076,0.0001047394,0.00008553211,0.0000054361367,0.00018557553,0.9797212,0.0006685502,0.0015126661,0.015620816,0.00044314933],"about_ca_topic_score_codex":0.000015283615,"about_ca_topic_score_gemma":0.00011680646,"teacher_disagreement_score":0.8420989,"about_ca_system_score_codex":0.000048434376,"about_ca_system_score_gemma":0.00001304607,"threshold_uncertainty_score":0.9991254},"labels":[],"label_agreement":null},{"id":"W4391054874","doi":"10.14778/3632093.3632117","title":"The Art of Latency Hiding in Modern Database Engines","year":2023,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Latency (audio); Interleaving; CAS latency; Speedup; Parallel computing; Operating system; Scheduling (production processes); CPU cache; Cache; Semiconductor memory; Memory controller","score_opus":0.020143839000601394,"score_gpt":0.24488364605150129,"score_spread":0.22473980705089988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391054874","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":[0.93004435,0.0017724753,0.037924226,0.019495033,0.0013246335,0.0020962395,0.00007981983,0.0018097282,0.0054534655],"genre_scores_gemma":[0.98673147,0.00036418714,0.012618212,0.000019622961,0.000011346477,0.00005690151,0.0000011803279,0.000008565634,0.00018854225],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99889606,0.000004035076,0.00027837578,0.00023804817,0.00032227358,0.00026117795],"domain_scores_gemma":[0.99920374,0.000106319065,0.00019787707,0.00039704374,0.00007712138,0.00001792129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046303013,0.00010763096,0.00014147208,0.00013696241,0.00008557847,0.00003231624,0.0020610986,0.000029112292,5.833058e-7],"category_scores_gemma":[0.00039906593,0.000063217216,0.000044432654,0.0009782567,0.00010334879,0.00049702585,0.0018451336,0.00013404174,0.0000071071922],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002270061,0.000113728616,0.005219335,0.00022663346,0.000043075197,0.000005063343,0.0018611507,0.0009336697,0.3930581,0.51846606,0.008668086,0.071382426],"study_design_scores_gemma":[0.0005389416,0.000079295,0.0023379868,0.00032340092,0.000011222308,0.000010483164,0.0010241392,0.068669595,0.74875206,0.17372741,0.004260502,0.0002649728],"about_ca_topic_score_codex":0.000013170101,"about_ca_topic_score_gemma":0.0000047574204,"teacher_disagreement_score":0.35569397,"about_ca_system_score_codex":0.000044152388,"about_ca_system_score_gemma":0.000018578558,"threshold_uncertainty_score":0.38300684},"labels":[],"label_agreement":null},{"id":"W4391055211","doi":"10.1145/3641832.3641842","title":"Future Database Engine Development: You Will Only Need One Programming Language","year":2023,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; SPARK (programming language); Database; Java; Programming language; Productivity; Operating system","score_opus":0.021180013553948315,"score_gpt":0.2615194378698532,"score_spread":0.24033942431590488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391055211","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21565905,0.00074116717,0.7665132,0.005044687,0.0015301536,0.0006813864,0.000056850786,0.009617753,0.00015571003],"genre_scores_gemma":[0.03962586,0.00013050849,0.9585849,0.00016096204,0.00025256645,0.00008067561,0.0003060551,0.000038811548,0.0008196422],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980576,0.000027921487,0.0002844687,0.00067395426,0.00034499232,0.000611079],"domain_scores_gemma":[0.997389,0.00013272127,0.00011766725,0.0022089847,0.00005317558,0.000098406636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002874254,0.00024701963,0.00024130073,0.00034026257,0.0001819508,0.00011622516,0.002787605,0.00012278394,0.000018231925],"category_scores_gemma":[0.0005698354,0.0002365464,0.000043750148,0.001721666,0.000054419743,0.0013508042,0.0026581446,0.00034626474,0.00029827893],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000053823983,0.00004051284,0.00027162812,0.000029055833,0.00002302106,0.00014103192,0.00075637037,0.000008172776,0.0025358265,0.0019502185,0.0017516476,0.99248713],"study_design_scores_gemma":[0.0012281878,0.00023864012,0.0022828253,0.0002019724,0.000023794639,0.00006580218,0.0026949926,0.0044172565,0.03103282,0.004003331,0.95227253,0.0015378429],"about_ca_topic_score_codex":0.000024328248,"about_ca_topic_score_gemma":0.00007424275,"teacher_disagreement_score":0.9909493,"about_ca_system_score_codex":0.00008308006,"about_ca_system_score_gemma":0.00010863181,"threshold_uncertainty_score":0.9646082},"labels":[],"label_agreement":null},{"id":"W4391308691","doi":"10.2514/6.2024-0043","title":"Leveraging High Performance Computing AMD EPYC CPU’s For CFD Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science; Computational fluid dynamics; Supercomputer; Computer architecture; Parallel computing; Operating system; Computational science; Engineering; Aerospace engineering","score_opus":0.022722947789132815,"score_gpt":0.2741544801546458,"score_spread":0.25143153236551297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391308691","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":[0.004269154,0.00031575508,0.98928714,0.0013853802,0.00028241027,0.00034296053,0.000006854838,0.003266935,0.00084343035],"genre_scores_gemma":[0.5465754,0.000016619158,0.45279044,0.0001262761,0.000054956414,0.00007770211,0.0000077122895,0.000008701727,0.0003421457],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989109,0.0000056035246,0.00017908288,0.0004847312,0.00012661613,0.0002930521],"domain_scores_gemma":[0.9990129,0.00019253776,0.000034186793,0.0006799286,0.00004755985,0.000032870517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016831346,0.0001233834,0.000111025576,0.00013819321,0.00022366477,0.00022781461,0.0010468328,0.000048999653,0.0000057802226],"category_scores_gemma":[0.000024071573,0.00011030028,0.00003470049,0.00051954965,0.000052216918,0.00079382333,0.0005438072,0.00015019598,0.00011263411],"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":[5.20095e-7,0.000009034018,0.000028982256,0.00006712247,0.000008380876,0.0000022567579,0.00010668334,0.0010956136,0.00041193096,0.42444,0.0018745343,0.57195497],"study_design_scores_gemma":[0.00011720666,0.000039122904,0.00018471574,0.00004834651,0.000005203113,0.000022325645,0.00007129964,0.8524632,0.009276121,0.03027864,0.10723236,0.0002614822],"about_ca_topic_score_codex":0.0000075510707,"about_ca_topic_score_gemma":0.0000010071468,"teacher_disagreement_score":0.85136753,"about_ca_system_score_codex":0.00007413348,"about_ca_system_score_gemma":0.00004032271,"threshold_uncertainty_score":0.4497915},"labels":[],"label_agreement":null},{"id":"W4391400210","doi":"10.20944/preprints202401.2084.v1","title":"Parallel Computation of Shallow Water Flows Using Hybrid MPI/OpenACC","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computation; Parallel computing; Computer science; Waves and shallow water; Computational science; Geology; Programming language","score_opus":0.13458321960823436,"score_gpt":0.35595996941221514,"score_spread":0.22137674980398078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391400210","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":[0.5692448,0.00027202212,0.42664438,0.00039558116,0.00109523,0.0005686366,0.000043560674,0.0011121618,0.0006235978],"genre_scores_gemma":[0.8545821,0.000057082274,0.1449512,0.000047112044,0.00006681402,0.00007088453,0.00007182075,0.000048416307,0.00010458329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960753,0.000114363174,0.0008636393,0.001815288,0.00057795766,0.00055347855],"domain_scores_gemma":[0.9963493,0.00006198964,0.00035702545,0.002919008,0.00022090175,0.000091770664],"candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006770343,0.0005265375,0.0006960503,0.0004496989,0.000097903336,0.00011081209,0.0035139571,0.00031107376,0.00006819899],"category_scores_gemma":[0.00015561075,0.00046132345,0.0002556255,0.00025489298,0.00016662967,0.0004873803,0.026360815,0.0012616452,0.0012028031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098696146,0.00057259784,0.016244745,0.0034611716,0.00092787296,0.0009925823,0.0052033565,0.7545511,0.17081022,0.017927501,0.00036343152,0.028846707],"study_design_scores_gemma":[0.00038179473,0.00003286934,0.002302183,0.00078676816,0.00008997401,0.00008724694,0.00006132114,0.4854179,0.2436083,0.2651,0.0010610006,0.0010706467],"about_ca_topic_score_codex":0.00014984436,"about_ca_topic_score_gemma":0.000011099251,"teacher_disagreement_score":0.28533727,"about_ca_system_score_codex":0.00027791623,"about_ca_system_score_gemma":0.0001720081,"threshold_uncertainty_score":0.9997839},"labels":[],"label_agreement":null},{"id":"W4391577197","doi":"10.36227/techrxiv.170723137.75506234/v1","title":"Parallel Computation of Shallow Water Flows Using Hybrid MPI/OpenACC","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Parallel computing; Computation; Computer science; Waves and shallow water; Computational science; Geology; Programming language; Oceanography","score_opus":0.043188674069405644,"score_gpt":0.2994061825078627,"score_spread":0.2562175084384571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391577197","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04258704,0.00041513395,0.9527994,0.0005013997,0.0010835067,0.00039246533,0.000040894178,0.0013702525,0.0008099436],"genre_scores_gemma":[0.42715764,0.00002199219,0.57255447,0.00004742794,0.000031525724,0.000016604203,0.00005754553,0.000020685304,0.00009213335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770164,0.000040660154,0.0005362746,0.0009783952,0.00038282762,0.00036017338],"domain_scores_gemma":[0.9982181,0.00003924894,0.00015823563,0.0014057175,0.00013302776,0.000045644247],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0002498381,0.00034873668,0.00046976717,0.0003508028,0.0000544019,0.00024109258,0.0022302903,0.00019471809,0.00002204581],"category_scores_gemma":[0.00003315164,0.0002579525,0.0001462728,0.00017366016,0.000089256886,0.0003924449,0.01368003,0.0006550582,0.00014562113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015929061,0.00010002385,0.0000272071,0.001217883,0.00023786246,0.0004335578,0.00073412847,0.8526918,0.011777557,0.051755603,0.002887393,0.07812103],"study_design_scores_gemma":[0.0000898223,0.000021241709,0.000005548658,0.00016422359,0.000017376176,0.000027241596,0.000017682472,0.7345111,0.01631307,0.248209,0.00032373445,0.0002999661],"about_ca_topic_score_codex":0.0001401318,"about_ca_topic_score_gemma":0.000019545172,"teacher_disagreement_score":0.3845706,"about_ca_system_score_codex":0.00019606206,"about_ca_system_score_gemma":0.00013776534,"threshold_uncertainty_score":0.99998724},"labels":[],"label_agreement":null},{"id":"W4391740537","doi":"10.2316/j.2024.201-0425","title":"TIMESTAMP HASH LOOKUP METHOD FOR LARGE-CAPACITY IMAGE STORAGE, 110-120.","year":2024,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Advanced Data Storage Technologies","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":"Timestamp; Computer science; Hash function; Image (mathematics); Lookup table; Hash table; Real-time computing; Artificial intelligence; Operating system; Computer security","score_opus":0.013103772834354672,"score_gpt":0.26854536578572974,"score_spread":0.2554415929513751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391740537","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":[0.0002677583,0.01290701,0.9820092,0.0008103032,0.0011925334,0.001032338,0.00025294628,0.0013727302,0.00015522182],"genre_scores_gemma":[0.7658334,0.000088580346,0.23168945,0.00016818033,0.00027303965,0.0007022742,0.000012955274,0.000051562198,0.001180576],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997728,0.00012684627,0.00037346836,0.0008458581,0.000261916,0.0006639402],"domain_scores_gemma":[0.9982966,0.00044515298,0.000113463044,0.0009493331,0.000094178475,0.00010128313],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013610707,0.00029921776,0.0004981878,0.0001800551,0.00021575614,0.0006432935,0.00082216144,0.00017198037,0.000007683279],"category_scores_gemma":[0.000137464,0.00025022935,0.00013438919,0.00026724505,0.00004868106,0.0009776554,0.00026549018,0.0002639942,0.00004482415],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014274898,0.00003574598,0.000005813457,0.00033616828,0.00014059502,0.000046224308,0.0001969854,0.00010123706,0.004975012,0.94527584,0.003961733,0.044910353],"study_design_scores_gemma":[0.001485725,0.00021359806,0.000009371156,0.00013214732,0.000057686662,0.000112615635,0.00020265716,0.8170289,0.0006140085,0.026857354,0.15289217,0.0003937906],"about_ca_topic_score_codex":0.000054134533,"about_ca_topic_score_gemma":0.000014792429,"teacher_disagreement_score":0.9184185,"about_ca_system_score_codex":0.00015586415,"about_ca_system_score_gemma":0.00011111921,"threshold_uncertainty_score":0.999995},"labels":[],"label_agreement":null},{"id":"W4392399504","doi":"10.5220/0012306600003648","title":"UPSS: A Global, Least-Privileged Storage System with Stronger Security and Better Performance","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Reliability (semiconductor); Cryptography; Confidentiality; Computer security; Access control; Immutability","score_opus":0.009837660508733383,"score_gpt":0.22603833768641393,"score_spread":0.21620067717768054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392399504","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":[0.28181008,0.0015549763,0.70532674,0.0011119178,0.000877618,0.00072600896,0.00027350592,0.0050631054,0.0032560593],"genre_scores_gemma":[0.8930838,0.000049507064,0.10643044,0.000093719995,0.0000787611,0.00012287855,0.000019638861,0.00002765627,0.00009359204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99692786,0.000050311777,0.0003517639,0.0015881938,0.0005368962,0.0005449557],"domain_scores_gemma":[0.9970687,0.00003551023,0.00019321477,0.002477943,0.00010583459,0.000118788725],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0002349069,0.00059467484,0.0005571832,0.00016899433,0.00012537869,0.0006427792,0.002175954,0.00037090448,0.0000073659103],"category_scores_gemma":[0.000016520995,0.0004484334,0.00006686642,0.00041341636,0.00025661147,0.0006403627,0.011576812,0.0012731522,0.000085369524],"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":[0.0001595201,0.00031193663,0.014947321,0.020510634,0.0013240007,0.0031371904,0.002899182,0.009594444,0.00007550044,0.7349538,0.025448231,0.18663824],"study_design_scores_gemma":[0.001364229,0.0007739356,0.0050794384,0.0052842367,0.0002463445,0.0013346227,0.0017204125,0.9360139,0.0008477683,0.033486012,0.009527957,0.004321151],"about_ca_topic_score_codex":0.00006146034,"about_ca_topic_score_gemma":0.00009272087,"teacher_disagreement_score":0.92641944,"about_ca_system_score_codex":0.00047840877,"about_ca_system_score_gemma":0.0001827911,"threshold_uncertainty_score":0.99979675},"labels":[],"label_agreement":null},{"id":"W4392667226","doi":"10.1109/tcsii.2024.3375640","title":"A Low-Cost Fault-Tolerant Racetrack Cache Based on Data Compression","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits & Systems II Express Briefs","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Cache; Computer science; Parallel computing; Fault tolerance; Embedded system; Operating system","score_opus":0.04705085190707002,"score_gpt":0.28875956929044905,"score_spread":0.241708717383379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392667226","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":[0.000936286,0.0006935379,0.9862466,0.00054436346,0.0046699517,0.0012238077,0.001634554,0.0035971592,0.00045373788],"genre_scores_gemma":[0.99562114,0.00005443565,0.0027652842,0.0002518086,0.00014160563,0.00038507013,0.00008727092,0.00008722492,0.0006061584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9950985,0.0002575573,0.00075537944,0.0020096393,0.0011180579,0.00076088595],"domain_scores_gemma":[0.99329054,0.00068625546,0.00017631726,0.005499096,0.000120803925,0.00022696948],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005570237,0.0006007295,0.00059848634,0.0006428078,0.00073601183,0.0007782028,0.004248684,0.00036148267,0.000030236155],"category_scores_gemma":[0.00004060828,0.00054602226,0.00016122192,0.0011540367,0.00018168449,0.0022917103,0.00007044309,0.0011550906,0.0003056198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053685002,0.0011593519,0.0000022319546,0.0008234193,0.00016242197,0.00070557144,0.001194308,0.5744102,0.03157368,0.0026590102,0.017963136,0.36929297],"study_design_scores_gemma":[0.0008439871,0.0002125176,0.000009724747,0.0025200518,0.000046213692,0.00011623828,0.00012699416,0.8636563,0.03864674,0.00006805273,0.092941724,0.00081146247],"about_ca_topic_score_codex":0.00017092514,"about_ca_topic_score_gemma":0.000022103493,"teacher_disagreement_score":0.9946849,"about_ca_system_score_codex":0.00029788612,"about_ca_system_score_gemma":0.00024900903,"threshold_uncertainty_score":0.9996991},"labels":[],"label_agreement":null},{"id":"W4393179173","doi":"10.1017/9781009283403.007","title":"Coding for Distributed Storage","year":2024,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Coding (social sciences); Distributed data store; Computer network; Database; Sociology","score_opus":0.028017266637344315,"score_gpt":0.2203751342357354,"score_spread":0.19235786759839107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393179173","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000012319573,0.00018126625,0.52685654,0.000041088173,0.0003792064,0.00036686292,0.0021150834,0.0012255694,0.46883312],"genre_scores_gemma":[0.00030923478,0.00005701442,0.010812989,0.000029786232,0.000077122466,0.0000032765192,0.000236996,0.000048654645,0.9884249],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99828917,0.00000845029,0.00018452958,0.0009122313,0.00023360636,0.00037200187],"domain_scores_gemma":[0.9980917,0.00014387976,0.00018842625,0.0013244207,0.00014379004,0.000107795146],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008969459,0.00041299462,0.00040230117,0.00027354993,0.0002131224,0.00015553643,0.002210583,0.00040206488,6.6245764e-7],"category_scores_gemma":[0.000028425078,0.00048436123,0.00022918372,0.000022298791,0.00023421482,0.00032130306,0.0021788639,0.0005312863,0.00002416255],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012819442,0.0000029742992,2.6836467e-8,0.00011876157,0.00007740879,0.00044955648,0.000012474644,0.000008307919,0.000042474912,0.93916523,0.05794379,0.0021661618],"study_design_scores_gemma":[0.0002741888,0.00005580034,2.8139266e-7,0.00018383429,0.00009548238,0.000019792236,0.000013478701,0.0029637795,0.0005282509,0.0014399209,0.993906,0.0005191879],"about_ca_topic_score_codex":0.000009413788,"about_ca_topic_score_gemma":7.593612e-7,"teacher_disagreement_score":0.9377253,"about_ca_system_score_codex":0.00044559428,"about_ca_system_score_gemma":0.00009048046,"threshold_uncertainty_score":0.9997608},"labels":[],"label_agreement":null},{"id":"W4393407022","doi":"10.1109/hpca57654.2024.00072","title":"FlipBit: Approximate Flash Memory for IoT Devices","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Flash (photography); Flash memory; Internet of Things; Non-volatile memory; Embedded system; Computer hardware","score_opus":0.023330361676849272,"score_gpt":0.28297563237537765,"score_spread":0.2596452706985284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393407022","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000657021,0.00095657783,0.9864958,0.001977042,0.0005470089,0.00023357628,0.0000140722705,0.0041322084,0.0049867234],"genre_scores_gemma":[0.040827405,0.000014928615,0.95524836,0.0003378907,0.00006314923,0.00010476977,0.0000058677415,0.000015514439,0.0033821322],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898237,0.000006913958,0.00014310116,0.00046555945,0.00013258193,0.00026950167],"domain_scores_gemma":[0.9990741,0.0001618575,0.00002340463,0.00067618245,0.000031287655,0.000033139142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016119472,0.00012386685,0.00011667186,0.00012669072,0.00007356356,0.0002449904,0.0011571884,0.00006133435,0.000016902959],"category_scores_gemma":[0.0000635041,0.000096641255,0.000051322826,0.00035759527,0.0000534226,0.00064582017,0.00055175915,0.00009571256,0.00023840091],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012542138,0.000010282182,0.0000033262575,0.00010922571,0.000013700724,0.000019501938,0.00009092137,0.000058285597,0.0011351968,0.61365235,0.017450167,0.36745575],"study_design_scores_gemma":[0.00017319267,0.000093213705,0.000017433262,0.00006258027,0.000009518876,0.00003519373,0.00012234325,0.4170982,0.052498706,0.19456218,0.33492944,0.00039800917],"about_ca_topic_score_codex":0.0000029057337,"about_ca_topic_score_gemma":0.00001538071,"teacher_disagreement_score":0.41909018,"about_ca_system_score_codex":0.000036269972,"about_ca_system_score_gemma":0.000046752462,"threshold_uncertainty_score":0.3940916},"labels":[],"label_agreement":null},{"id":"W4393591641","doi":"10.1109/hpca57654.2024.00036","title":"DockerSSD: Containerized In-Storage Processing and Hardware Acceleration for Computational SSDs","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Hardware acceleration; Computer science; Acceleration; Embedded system; Computer hardware; Parallel computing; Operating system; Field-programmable gate array","score_opus":0.025329658349062516,"score_gpt":0.29614245636510905,"score_spread":0.2708127980160465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393591641","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":[0.005385714,0.0005829012,0.99081725,0.0018600594,0.00010615972,0.00025823983,0.000009454062,0.0007970138,0.00018322542],"genre_scores_gemma":[0.6172608,0.000006066233,0.38240802,0.00012184858,0.000016133225,0.00005393202,0.000022347656,0.000005924428,0.00010489527],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992359,0.000009265688,0.00015394454,0.00034655552,0.00010600777,0.00014830827],"domain_scores_gemma":[0.9996415,0.000120497374,0.000025551455,0.00014068105,0.000050064722,0.000021724549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013180258,0.00009406863,0.00010648258,0.00016613094,0.00007368215,0.0003695942,0.00024691614,0.000047491736,0.0000035750431],"category_scores_gemma":[0.00006024512,0.00008248192,0.000016256046,0.0003037846,0.000042199554,0.0014710323,0.0001586744,0.00008355018,0.0000035798041],"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":[0.000017463035,0.000026545678,0.00012319592,0.00021611294,0.000010708436,0.000050991912,0.00066494825,0.0052304254,0.001779504,0.5081602,0.00210385,0.48161608],"study_design_scores_gemma":[0.00038515506,0.00004527255,0.00029801615,0.00004800244,0.0000020265593,0.000016925405,0.000105523584,0.9370652,0.000529585,0.055097807,0.00626394,0.00014254307],"about_ca_topic_score_codex":0.000004226453,"about_ca_topic_score_gemma":0.000012913733,"teacher_disagreement_score":0.93183476,"about_ca_system_score_codex":0.000060802966,"about_ca_system_score_gemma":0.0000686177,"threshold_uncertainty_score":0.35640055},"labels":[],"label_agreement":null},{"id":"W4394575921","doi":"10.1016/j.sysarc.2024.103140","title":"A survey on Persistent Memory indexes: Recent advances, challenges and opportunities","year":2024,"lang":"en","type":"article","venue":"Journal of Systems Architecture","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Gujarat Council on Science and Technology","keywords":"Computer science; Dram; Persistent data structure; Non-volatile random-access memory; Non-volatile memory; Computer data storage; Class (philosophy); Data science; Database; Operating system; Computer memory; Semiconductor memory; Memory refresh; Computer hardware; Artificial intelligence","score_opus":0.07325814639705903,"score_gpt":0.27406861233725205,"score_spread":0.20081046594019303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394575921","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069251265,0.8871402,0.094555676,0.0073402836,0.0026173783,0.00024544503,0.000054345208,0.00030436247,0.0008172001],"genre_scores_gemma":[0.7848848,0.20684439,0.00720393,0.00021070728,0.00044580185,0.000013918841,0.0000047525973,0.000043554104,0.00034814584],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99842066,0.00019210018,0.00040462852,0.00028674447,0.00047272939,0.0002231188],"domain_scores_gemma":[0.998706,0.00036380306,0.00024303456,0.00043338691,0.00014165205,0.00011214523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000948799,0.00019850567,0.00034946215,0.00047037803,0.00006625459,0.00017878521,0.0007247618,0.000095055904,0.0000015955607],"category_scores_gemma":[0.0001785362,0.00013592461,0.00008432341,0.00016453222,0.00010243708,0.00052073365,0.00022480759,0.00058195397,0.0000027104054],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024748037,0.000024740251,0.000007769689,0.0003036976,0.00009513898,0.0005185243,0.0020059713,0.0023799066,0.000049165996,0.0076306574,0.0009781257,0.9859816],"study_design_scores_gemma":[0.00071990176,0.0026755363,0.0015246322,0.0041884356,0.000049718732,0.006260393,0.0051807635,0.0032658342,0.00020423348,0.008316228,0.966818,0.00079635985],"about_ca_topic_score_codex":0.0000046314854,"about_ca_topic_score_gemma":0.00001737799,"teacher_disagreement_score":0.9851852,"about_ca_system_score_codex":0.000103596656,"about_ca_system_score_gemma":0.00010940507,"threshold_uncertainty_score":0.5542845},"labels":[],"label_agreement":null},{"id":"W4395106468","doi":"10.1145/3620666.3651334","title":"MemSnap μCheckpoints: A Data Single Level Store for Fearless Persistence","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Persistence (discontinuity); Computer science; Granularity; Persistent data structure; File system; Operating system; Database; Engineering","score_opus":0.274814097985871,"score_gpt":0.33639481252896397,"score_spread":0.061580714543092996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395106468","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026357954,0.0011761184,0.9913669,0.003109756,0.00055910787,0.00023573221,0.0003296121,0.0019816398,0.0009775055],"genre_scores_gemma":[0.112787224,0.00002634133,0.88462245,0.00020316304,0.000061192346,0.00003662332,0.00007927034,0.000019409694,0.0021643215],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99835306,0.0000109974535,0.00017652956,0.0009075774,0.00022077162,0.00033106637],"domain_scores_gemma":[0.99723095,0.00020356524,0.000034368328,0.0024166298,0.000063463296,0.000051046263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027788596,0.00015779749,0.0001501575,0.00012851528,0.00011170851,0.00037489855,0.0040727626,0.00007706637,0.000016100212],"category_scores_gemma":[0.00035092447,0.00013237332,0.00004798979,0.0004728972,0.000119326956,0.0032381634,0.0024181588,0.00014332205,0.00009081375],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000071206578,0.00009623154,0.000010064348,0.00018680039,0.000063163934,0.00008691463,0.00055275956,0.000035635283,0.007829452,0.42464596,0.092989914,0.473496],"study_design_scores_gemma":[0.00039582048,0.00027472345,0.000045749657,0.00019700505,0.00003269798,0.0001317017,0.0013398211,0.3860162,0.019337686,0.049621843,0.54174954,0.00085722556],"about_ca_topic_score_codex":0.000014914954,"about_ca_topic_score_gemma":0.000044745208,"teacher_disagreement_score":0.4726388,"about_ca_system_score_codex":0.00010615004,"about_ca_system_score_gemma":0.000092177215,"threshold_uncertainty_score":0.7568274},"labels":[],"label_agreement":null},{"id":"W4395479396","doi":"10.18280/isi.290231","title":"Minimizing the Cache Memory Miss Ratio Using Modified Replacement Algorithm (M-CAR)","year":2024,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Data Storage Technologies","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":"Mustansiriyah University","keywords":"Cache; Parallel computing; Computer science; Algorithm; Cache algorithms; CPU cache","score_opus":0.02947152943155775,"score_gpt":0.26319068828459824,"score_spread":0.23371915885304048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395479396","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":[0.0060703484,0.0007018286,0.9885607,0.0002837332,0.000826396,0.00039506136,0.000019212186,0.0012052798,0.0019374477],"genre_scores_gemma":[0.66592944,0.00004548112,0.33333784,0.00031248108,0.000098809825,0.00010169535,0.000054425644,0.000017581782,0.00010226772],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843293,0.000059851478,0.0005482382,0.00024437346,0.0003780905,0.0003365342],"domain_scores_gemma":[0.9986521,0.00013906993,0.00019109999,0.00084606005,0.0001282765,0.000043388478],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00065218477,0.00020710441,0.00016610308,0.00027057575,0.00044037707,0.0010435395,0.00090198586,0.00010611126,0.0000075762173],"category_scores_gemma":[0.00023469534,0.00015718427,0.00006504153,0.0007651512,0.00016452628,0.0071128984,0.00047216946,0.00024129279,0.00006356461],"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":[0.000008617856,0.000010542779,0.0000051594498,0.00022584581,0.00006524678,0.000019190707,0.011608529,0.015763937,0.00091676594,0.043264486,0.0018226716,0.926289],"study_design_scores_gemma":[0.00014235562,0.000041164007,0.00001763164,0.0001513288,0.000014188635,0.000116359,0.0020455378,0.9761328,0.007098721,0.008972067,0.0050393613,0.00022849205],"about_ca_topic_score_codex":0.000060025126,"about_ca_topic_score_gemma":0.0000024786555,"teacher_disagreement_score":0.9603689,"about_ca_system_score_codex":0.00043818456,"about_ca_system_score_gemma":0.00014941403,"threshold_uncertainty_score":0.99999344},"labels":[],"label_agreement":null},{"id":"W4396661858","doi":"10.1051/epjconf/202429507034","title":"NOTED: An intelligent network controller to improve the throughput of large data transfers in File Transfer Services by handling dynamic circuits","year":2024,"lang":"en","type":"article","venue":"EPJ Web of Conferences","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Throughput; Transfer (computing); Computer science; File transfer; Electronic circuit; Controller (irrigation); Engineering; Operating system; Electrical engineering","score_opus":0.022977778564623498,"score_gpt":0.2903845819574177,"score_spread":0.26740680339279416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396661858","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":[0.047613997,0.0032503677,0.9429652,0.0012484253,0.00045344557,0.00062446366,0.003288158,0.00025430848,0.00030160396],"genre_scores_gemma":[0.99640244,0.0003229294,0.002872144,0.00014152321,0.000022303851,0.0000376623,0.00017085594,0.000011492221,0.00001862814],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802834,0.00008393084,0.00050415547,0.00066522823,0.00032735296,0.00039101925],"domain_scores_gemma":[0.998239,0.0004508127,0.000051163395,0.0011369628,0.00007211055,0.000049958257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061616296,0.00021367604,0.00040195792,0.0001318938,0.00006313665,0.00013680912,0.0035531996,0.00010892332,0.00009698905],"category_scores_gemma":[0.000043941003,0.00015051407,0.000050745675,0.0007190503,0.00014555511,0.0009883823,0.0003584116,0.00026685794,0.000007312613],"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":[0.00008344004,0.00033582712,0.00035812936,0.0005587676,0.0002899546,0.000029264424,0.008391313,0.0039394065,0.03290512,0.16368826,0.0029210793,0.78649944],"study_design_scores_gemma":[0.00074469036,0.0007314587,0.00042553898,0.0008281094,0.000047359827,0.0000037786156,0.0026759517,0.93345267,0.013565243,0.014208328,0.032772657,0.0005442266],"about_ca_topic_score_codex":0.00023904377,"about_ca_topic_score_gemma":0.002377524,"teacher_disagreement_score":0.94878846,"about_ca_system_score_codex":0.00002191417,"about_ca_system_score_gemma":0.00030308924,"threshold_uncertainty_score":0.6602788},"labels":[],"label_agreement":null},{"id":"W4396681647","doi":"10.1051/epjconf/202429501046","title":"Scale tests of the new DUNE data pipeline","year":2024,"lang":"en","type":"article","venue":"EPJ Web of Conferences","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"High Energy Physics; Institut National de Physique Nucléaire et de Physique des Particules; Horizon 2020 Framework Programme; Science and Technology Facilities Council; Natural Sciences and Engineering Research Council of Canada; Office of Science; European Commission; Ministerio de Ciencia e Innovación; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Centre National de la Recherche Scientifique; European Regional Development Fund; Ministerstvo Školství, Mládeže a Tělovýchovy; U.S. Department of Energy; Junta de Andalucía; Fundação para a Ciência e a Tecnologia; Fundação de Amparo à Pesquisa do Estado de Goiás; Fermilab; UK Research and Innovation; National Science Foundation; Royal Society; National Energy Research Scientific Computing Center; Xunta de Galicia; CERN; Fundação de Amparo à Pesquisa do Estado de São Paulo; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Daemon; Large Hadron Collider; Pipeline (software); Petabyte; Metadata; Data acquisition; Computer science; Detector; Operating system; Physics; Particle physics; Big data; Telecommunications","score_opus":0.0451835308187973,"score_gpt":0.30192842598973224,"score_spread":0.25674489517093496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396681647","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":[0.016601076,0.006128282,0.9354405,0.023958791,0.0020256264,0.00037022517,0.00033255288,0.0010068191,0.014136128],"genre_scores_gemma":[0.955172,0.00011820074,0.04383407,0.000029195488,0.0000369187,0.000001495233,0.000007929546,0.0000038157586,0.0007963859],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99897593,0.000022644,0.000249269,0.00033611426,0.00027975964,0.00013629507],"domain_scores_gemma":[0.99778295,0.00019562144,0.00010282277,0.0018326124,0.000059032118,0.000026993395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019723356,0.000098194774,0.0001751091,0.000081900434,0.000028034872,0.00006023208,0.004269112,0.000048170383,0.00004916158],"category_scores_gemma":[0.0002818429,0.00005483489,0.000031441436,0.00057491974,0.00026877577,0.0006267562,0.0019981642,0.00013265006,0.000013727664],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034294305,0.000043424545,0.0017275016,0.00008433173,0.00002513745,0.0000075641437,0.00020247493,0.000022762339,0.01107578,0.25653672,0.05743986,0.672831],"study_design_scores_gemma":[0.0003543616,0.000168796,0.0070895483,0.00075623865,0.000041493447,0.000027416741,0.00026726542,0.119309716,0.1256517,0.19540934,0.55049735,0.0004268054],"about_ca_topic_score_codex":0.00009832932,"about_ca_topic_score_gemma":0.00027306814,"teacher_disagreement_score":0.9385709,"about_ca_system_score_codex":0.0000060253064,"about_ca_system_score_gemma":0.0009447548,"threshold_uncertainty_score":0.79331434},"labels":[],"label_agreement":null},{"id":"W4396796787","doi":"10.3390/jcp4020015","title":"A Usable Encryption Solution for File-Based Geospatial Data within a Database File System","year":2024,"lang":"en","type":"article","venue":"Journal of Cybersecurity and Privacy","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Island University","funders":"","keywords":"USable; Computer science; Database; File system; Geospatial analysis; Computer file; Encryption; Data file; Operating system; World Wide Web; Geography","score_opus":0.04167397227471563,"score_gpt":0.2894056364614945,"score_spread":0.24773166418677883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396796787","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002272676,0.0010148039,0.9893054,0.0008667434,0.00065081444,0.00020565405,0.005453071,0.0002053308,0.000025549636],"genre_scores_gemma":[0.22811379,0.00005919211,0.7705051,0.00008455242,0.00028556804,0.000019700357,0.00089910877,0.000013693504,0.000019337072],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868786,0.000054454176,0.00041887205,0.00034273014,0.00028974103,0.00020633143],"domain_scores_gemma":[0.99812096,0.0005036393,0.00029933878,0.00088280434,0.00011631564,0.00007692948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008257254,0.00013689711,0.00022082632,0.00019733961,0.00015281195,0.0002906378,0.0013624011,0.00008910536,0.00006614597],"category_scores_gemma":[0.0007423768,0.00011565566,0.00005717245,0.0002718413,0.00006996373,0.003236226,0.0007169111,0.00031550202,0.000008422446],"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":[0.00033686683,0.0002589838,0.000031017014,0.0022498772,0.00020060274,0.00069816585,0.002775139,0.000416782,0.0033451603,0.126288,0.7196718,0.14372762],"study_design_scores_gemma":[0.0006452948,0.00031211082,0.000036398716,0.00097013975,0.000049523187,0.0003709299,0.00017538872,0.85995543,0.000947449,0.007222139,0.129091,0.00022418457],"about_ca_topic_score_codex":0.00003914273,"about_ca_topic_score_gemma":0.000023588706,"teacher_disagreement_score":0.8595387,"about_ca_system_score_codex":0.00008969534,"about_ca_system_score_gemma":0.00025826634,"threshold_uncertainty_score":0.4716301},"labels":[],"label_agreement":null},{"id":"W4396986985","doi":"10.48550/arxiv.2405.09165","title":"An Empirical Study of Token-based Micro Commits","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada","keywords":"Security token; Computer science; Business; Empirical research; Computer security; Mathematics; Statistics","score_opus":0.09150203788213532,"score_gpt":0.24925604787805675,"score_spread":0.15775400999592143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396986985","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":[0.63220537,0.000057465328,0.36592788,0.00007941759,0.00030969517,0.00032222003,0.000044442317,0.0008582141,0.00019533082],"genre_scores_gemma":[0.98920953,0.000011116243,0.010557813,0.0000579549,0.000019846146,0.0000016654109,0.00001685705,0.000020980584,0.00010423321],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977659,0.0001589977,0.00025746739,0.0013840392,0.00013169732,0.0003018727],"domain_scores_gemma":[0.9961616,0.0001283979,0.00022290969,0.0032352225,0.00014550351,0.00010639152],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019567941,0.00034036557,0.00043806963,0.00053054973,0.000084837084,0.00008986467,0.004378924,0.00029760753,0.000008309182],"category_scores_gemma":[0.00004018406,0.00037287624,0.00012625978,0.0010246151,0.0001901007,0.00029364554,0.005568951,0.0009394681,0.000051033054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001581459,0.0053449646,0.04756122,0.00065696624,0.0004986435,0.0063953893,0.0025583338,0.84981513,0.0011045261,0.075199306,0.0034923952,0.00721499],"study_design_scores_gemma":[0.0015206464,0.0013998229,0.003843607,0.00022194078,0.00023520218,0.0000070186234,0.0015422511,0.8600106,0.0039272667,0.12516375,0.00079185853,0.0013360237],"about_ca_topic_score_codex":0.00011300128,"about_ca_topic_score_gemma":0.00010677932,"teacher_disagreement_score":0.3570042,"about_ca_system_score_codex":0.00020131166,"about_ca_system_score_gemma":0.00021575791,"threshold_uncertainty_score":0.9998723},"labels":[],"label_agreement":null},{"id":"W4398234136","doi":"10.1145/3626246.3653393","title":"Native Cloud Object Storage in Db2 Warehouse: Implementing a Fast and Cost-Efficient Cloud Storage Architecture","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Cloud computing; Computer science; Cloud storage; Architecture; Object (grammar); Warehouse; Database; Object storage; Computer data storage; Operating system; Business; Artificial intelligence","score_opus":0.016124544814984203,"score_gpt":0.2814643871324747,"score_spread":0.26533984231749047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398234136","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":[0.06940646,0.00160529,0.92342424,0.0009441786,0.0007352703,0.0007509851,0.00007710155,0.0020964597,0.0009600347],"genre_scores_gemma":[0.93998885,0.00004944446,0.059199374,0.00017776126,0.0001094847,0.00010453407,0.00001211669,0.000038484355,0.00031997444],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971869,0.00010719253,0.0003994932,0.0010846311,0.00042959067,0.00079220923],"domain_scores_gemma":[0.9985276,0.000372598,0.00009019257,0.0008622707,0.000049030776,0.000098325814],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006806329,0.0003600432,0.00032652993,0.00060632074,0.00019449968,0.00041828392,0.0011190912,0.00012028389,0.00002863959],"category_scores_gemma":[0.00020158311,0.00030457944,0.000064722284,0.0014271585,0.00018057435,0.0004829222,0.0021560048,0.0007328879,0.000029577504],"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":[0.00003125485,0.00020090227,0.00024321173,0.00028318146,0.00010360652,0.0020100174,0.017599603,0.039665066,0.0023625458,0.31240028,0.00570322,0.6193971],"study_design_scores_gemma":[0.002086119,0.0006187488,0.0010226127,0.0006142121,0.000035654244,0.00047459174,0.006903079,0.7931692,0.009392589,0.031412307,0.15191092,0.002359946],"about_ca_topic_score_codex":0.00008791062,"about_ca_topic_score_gemma":0.0003189668,"teacher_disagreement_score":0.87058234,"about_ca_system_score_codex":0.00032005977,"about_ca_system_score_gemma":0.00011065676,"threshold_uncertainty_score":0.99994063},"labels":[],"label_agreement":null},{"id":"W4399021598","doi":"10.1145/3663676","title":"PUF-based Digital Money with Propagation-of-Provenance and Offline Transfers between Two Parties","year":2024,"lang":"en","type":"article","venue":"ACM Journal on Emerging Technologies in Computing Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Computer science; Provenance; Biology","score_opus":0.02118398281606011,"score_gpt":0.2792540533757343,"score_spread":0.2580700705596742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399021598","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":[0.28752342,0.0026497713,0.7040591,0.0028107315,0.0003756023,0.00027065183,0.000012793946,0.0022579401,0.000039971357],"genre_scores_gemma":[0.9500392,0.000078955985,0.049787868,0.000008594168,0.000041935848,0.0000118476255,0.0000022400288,0.000023881139,0.000005462476],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99780434,0.000047821508,0.00071040227,0.0005421658,0.00045460538,0.00044067352],"domain_scores_gemma":[0.99798405,0.0006331826,0.0002829848,0.00096887554,0.00009533153,0.000035558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062563457,0.0002922391,0.00046527945,0.0008350848,0.00016312464,0.0004915433,0.0020077848,0.00013231926,1.3231478e-7],"category_scores_gemma":[0.0007161856,0.00021922812,0.000052071096,0.0012889772,0.0003726358,0.0009440636,0.0005131909,0.0008369882,0.0000017940057],"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":[0.000039074555,0.00008123011,0.02165305,0.000657419,0.00014668619,0.0005720522,0.0006264698,0.094523534,0.00077347417,0.09544086,0.00023625355,0.7852499],"study_design_scores_gemma":[0.0023062534,0.0028576378,0.00089485355,0.013538157,0.000049333335,0.00075212016,0.0035082505,0.8841862,0.028627034,0.05823784,0.0034898464,0.0015524523],"about_ca_topic_score_codex":0.000008354312,"about_ca_topic_score_gemma":0.0000011325859,"teacher_disagreement_score":0.78966266,"about_ca_system_score_codex":0.00014935218,"about_ca_system_score_gemma":0.00009824843,"threshold_uncertainty_score":0.89398634},"labels":[],"label_agreement":null},{"id":"W4399531343","doi":"10.1145/3644815.3644963","title":"An Exploratory Study of Dataset and Model Management in Open Source Machine Learning Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Computer science; TRACE (psycholinguistics); Key (lock); Focus (optics); Open source; Data modeling; Data science; Data mining; Predictive modelling; Database; Machine learning; Software; Operating system","score_opus":0.04372501606269334,"score_gpt":0.33044733656707886,"score_spread":0.2867223205043855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399531343","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":[0.0076120715,0.00014999243,0.9911323,0.000066197244,0.0000062231643,0.000511404,0.000051136216,0.00029605217,0.0001746199],"genre_scores_gemma":[0.7999632,0.000043806052,0.19953331,0.00003174438,0.0000017398197,0.00023244353,0.00009951436,0.000006988924,0.000087280125],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992847,0.00002641423,0.00012981331,0.0003810165,0.00009134243,0.0000867191],"domain_scores_gemma":[0.9991762,0.000022931665,0.000022505035,0.0007517442,0.000006476748,0.000020151401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023556156,0.00006690097,0.00008544981,0.00016029346,0.00004315266,0.00013902076,0.00129782,0.000014622632,0.0000018219305],"category_scores_gemma":[0.0000039646566,0.000059360453,0.0000031802451,0.00036800926,0.000025371284,0.0012409043,0.0025906262,0.000107094434,0.0000048940465],"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":[0.0000072202456,0.00079608295,0.00076078356,0.000092313945,0.000044619563,0.000054270604,0.0043579484,0.12935919,0.0003931379,0.22953929,0.001330879,0.63326424],"study_design_scores_gemma":[0.00017121957,0.0000858813,0.00003403804,0.000007112483,0.000003980172,0.0000011480736,0.0029641355,0.9840876,0.00006265926,0.0058599925,0.0066355206,0.0000867486],"about_ca_topic_score_codex":0.000041534517,"about_ca_topic_score_gemma":0.0001965374,"teacher_disagreement_score":0.8547284,"about_ca_system_score_codex":0.000015727634,"about_ca_system_score_gemma":0.000007679364,"threshold_uncertainty_score":0.322903},"labels":[],"label_agreement":null},{"id":"W4399551865","doi":"10.32614/cran.package.domino","title":"domino: R Console Bindings for the 'Domino Command-Line Client'","year":2014,"lang":"en","type":"dataset","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Domtar (Canada)","funders":"","keywords":"Domino; Domino effect; Line (geometry); Operating system; Computer science; Programming language; Embedded system; Chemistry; Physics; Mathematics; Nuclear physics","score_opus":0.028890217582915854,"score_gpt":0.2921973803892516,"score_spread":0.2633071628063357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399551865","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016058693,0.00016090822,0.45471844,0.0012139162,0.0007969368,0.0006062988,0.54209965,0.0003567935,0.000045462726],"genre_scores_gemma":[0.000035151836,0.00038992887,0.11559876,0.0022153102,0.00024324977,0.0003810434,0.8801604,0.000026737267,0.00094941497],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99758226,0.000044920787,0.0005020475,0.0008880778,0.00037190996,0.0006108025],"domain_scores_gemma":[0.9932177,0.0020212207,0.0004541531,0.004107398,0.000121955694,0.000077564924],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0006555913,0.00047583316,0.0005838062,0.00023620455,0.00042580935,0.0003262156,0.0073553966,0.00040621107,0.00005360514],"category_scores_gemma":[0.0005896988,0.00030062936,0.0001785782,0.0003376095,0.00044726438,0.0003860294,0.002934765,0.00058935035,0.000398761],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013855249,0.00003216459,5.794919e-7,0.000043684773,0.00003725014,0.000005374667,0.0000057506163,0.000009929234,0.000006941683,0.010812334,0.97867435,0.01035781],"study_design_scores_gemma":[0.00074829673,0.00015763467,0.0000011867322,0.000032218843,0.00004757269,0.000021797212,0.000019547902,0.002218659,0.0005212216,0.0031706996,0.9926454,0.00041580622],"about_ca_topic_score_codex":0.00009826081,"about_ca_topic_score_gemma":0.00016155164,"teacher_disagreement_score":0.33911967,"about_ca_system_score_codex":0.00008211028,"about_ca_system_score_gemma":0.00008213295,"threshold_uncertainty_score":0.99994457},"labels":[],"label_agreement":null},{"id":"W4399723139","doi":"10.1145/3665283.3665287","title":"Learned Index Acceleration with FPGAs: A SMART Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Acceleration; Field-programmable gate array; Computer science; Index (typography); Embedded system; Computer architecture; World Wide Web; Physics","score_opus":0.031056256576477446,"score_gpt":0.2645840712107043,"score_spread":0.23352781463422687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399723139","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":[0.0013498293,0.00012796461,0.98527414,0.0010302827,0.00007522598,0.00012009558,8.8173505e-7,0.0029038258,0.009117748],"genre_scores_gemma":[0.61552775,0.000008637667,0.38303125,0.00011305269,0.000015059791,0.0000306931,0.0000053227277,0.000007345636,0.0012609109],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912554,0.000011402322,0.00009005692,0.00041761706,0.00018446248,0.0001709259],"domain_scores_gemma":[0.99931467,0.000030140496,0.000016542186,0.00058777427,0.000025417143,0.000025466885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094885014,0.00010048419,0.00007980033,0.00013301763,0.000056637316,0.0003677767,0.00064245146,0.0000527821,0.000012223948],"category_scores_gemma":[0.000020730819,0.000068802176,0.000015939026,0.00065053406,0.000050449198,0.0011043969,0.00028983006,0.0001674436,0.00008461604],"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":[0.0000040396303,0.000026552976,0.00020124209,0.000029093495,0.00002010715,0.000047064317,0.00023310816,0.0011524357,0.00041186294,0.63151973,0.0032460047,0.36310875],"study_design_scores_gemma":[0.00024345898,0.00016705887,0.00040641715,0.00003212401,0.00000561455,0.00011961869,0.00021876724,0.92609704,0.0051553613,0.028488217,0.038678512,0.0003878181],"about_ca_topic_score_codex":0.000013111961,"about_ca_topic_score_gemma":0.000008653277,"teacher_disagreement_score":0.9249446,"about_ca_system_score_codex":0.000039375773,"about_ca_system_score_gemma":0.00004859147,"threshold_uncertainty_score":0.3546479},"labels":[],"label_agreement":null},{"id":"W4399969878","doi":"10.1145/3663351.3663880","title":"Wayfinder: Speeding up Key-Value Separation by Avoiding I/O Based Indirection","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Indirection; Key (lock); Value (mathematics); Computer science; Separation (statistics); Programming language; Computer security; Machine learning","score_opus":0.020950383534807698,"score_gpt":0.2961778317761612,"score_spread":0.2752274482413535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399969878","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":[0.0050009578,0.0003835556,0.9843703,0.0013362726,0.0012389129,0.00011734971,0.0000053062945,0.0039387415,0.003608623],"genre_scores_gemma":[0.8676523,0.000024585173,0.13060908,0.00018866724,0.000057503876,0.000017576496,0.00002060947,0.000014457095,0.001415189],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988149,0.000033803008,0.00017363353,0.00049104326,0.00024942457,0.00023720301],"domain_scores_gemma":[0.9993337,0.00015945337,0.00003834613,0.00040505498,0.000027496935,0.00003598358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033853255,0.00013750988,0.00010308919,0.00025138576,0.00019058737,0.0004053032,0.0005058358,0.00009789415,0.000025797672],"category_scores_gemma":[0.00013282399,0.00012625597,0.000039437677,0.00079214544,0.000032534444,0.0018160255,0.0001914207,0.00027090512,0.0001797182],"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":[0.000004953678,0.000032036754,0.00009546202,0.000059679147,0.000027641574,0.000035834088,0.00061989704,0.0017041683,0.13319871,0.565654,0.11054324,0.18802437],"study_design_scores_gemma":[0.00009986017,0.00004627363,0.000016520702,0.00004150471,0.0000046596633,0.000013644102,0.00008832273,0.63942,0.29483154,0.010645155,0.054571643,0.00022090346],"about_ca_topic_score_codex":0.000020433423,"about_ca_topic_score_gemma":0.000004342788,"teacher_disagreement_score":0.86265135,"about_ca_system_score_codex":0.00018066021,"about_ca_system_score_gemma":0.000044762444,"threshold_uncertainty_score":0.5148569},"labels":[],"label_agreement":null},{"id":"W4400919119","doi":"10.1007/s00493-024-00114-2","title":"Storage Codes on Coset Graphs with Asymptotically Unit Rate","year":2024,"lang":"en","type":"article","venue":"COMBINATORICA","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Combinatorics; Coset; Unit (ring theory); Discrete mathematics","score_opus":0.015269433132303528,"score_gpt":0.25138211051095577,"score_spread":0.23611267737865224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400919119","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":[0.03476163,0.0015138848,0.932654,0.006015321,0.0018869464,0.0005576915,0.000058416488,0.008637853,0.013914228],"genre_scores_gemma":[0.986734,0.00006929888,0.012356284,0.000246002,0.0000114145905,0.00003780109,0.000011111771,0.000028011389,0.00050610374],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998392,0.000069357724,0.00017330202,0.0006462517,0.0003298505,0.000389277],"domain_scores_gemma":[0.9981587,0.00039775783,0.00004583798,0.0012102359,0.00008282092,0.000104661005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002254321,0.00024503632,0.00022446578,0.0002652457,0.00015091768,0.00031174644,0.00148119,0.00009621045,0.000012794698],"category_scores_gemma":[0.00012442944,0.00018838281,0.000045616223,0.0014010671,0.00018405801,0.0004719301,0.00043482648,0.00044357395,0.00031157065],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009281928,0.00007643701,0.000058399033,0.000023886123,0.000027189633,0.00048567203,0.000051204373,0.00007115149,0.00012640083,0.98303163,0.007331534,0.008707201],"study_design_scores_gemma":[0.00074181805,0.0018865819,0.0014762939,0.0002784194,0.000028623128,0.00008093848,0.000051977793,0.015061689,0.0043379487,0.7807628,0.19440559,0.0008873461],"about_ca_topic_score_codex":0.0000038650796,"about_ca_topic_score_gemma":0.0000017426805,"teacher_disagreement_score":0.95197237,"about_ca_system_score_codex":0.000110050925,"about_ca_system_score_gemma":0.00009087583,"threshold_uncertainty_score":0.7682028},"labels":[],"label_agreement":null},{"id":"W4401164625","doi":"10.1109/csp62567.2024.00013","title":"An Application Evaluation for Differentially Private Database Release Methods","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Database","score_opus":0.05221623195628605,"score_gpt":0.41475260444611267,"score_spread":0.3625363724898266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401164625","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001492501,0.00020993699,0.99469775,0.00059199135,0.00021313882,0.00076357025,0.000023228764,0.0019295757,0.00007833095],"genre_scores_gemma":[0.1418141,0.000010457292,0.8573754,0.00006057603,0.00003074212,0.0004702157,0.00019671283,0.000009875008,0.0000319193],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882203,0.000076537806,0.00016041443,0.00056515535,0.00019822964,0.0001776207],"domain_scores_gemma":[0.998365,0.00015887544,0.000037653233,0.0013028563,0.00009312721,0.00004250941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093945034,0.0001022989,0.000083882296,0.00012685343,0.00008610872,0.00019399318,0.0008921717,0.000048059275,0.000011194856],"category_scores_gemma":[0.00024144302,0.00008536719,0.000029263563,0.00041560616,0.000027897175,0.0014840454,0.00028193492,0.00007697806,0.000027192982],"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":[0.000002502522,0.000016791217,0.0000018859039,0.000016179478,0.000004287802,4.831133e-7,0.000028780054,0.00007500288,0.033327684,0.29736748,0.0002954567,0.6688635],"study_design_scores_gemma":[0.000104753504,0.000045156354,0.00005092568,0.000008510196,0.000015704294,0.0000016661587,0.000010738577,0.8420863,0.051033236,0.092717364,0.013803556,0.0001220633],"about_ca_topic_score_codex":0.0000064793467,"about_ca_topic_score_gemma":0.000006411506,"teacher_disagreement_score":0.84201133,"about_ca_system_score_codex":0.000073306765,"about_ca_system_score_gemma":0.00005251664,"threshold_uncertainty_score":0.3481173},"labels":[],"label_agreement":null},{"id":"W4401247357","doi":"10.1109/jssc.2024.3419808","title":"A 28-nm 28.8-TOPS/W Attention-Based NN Processor With Correlative CIM Ring Architecture and Dataflow-Reshaped Digital-Assisted CIM Array","year":2024,"lang":"en","type":"article","venue":"IEEE Journal of Solid-State Circuits","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"National Key Research and Development Program of China; National Science and Technology Major Project; Beijing National Research Center For Information Science And Technology; National Natural Science Foundation of China","keywords":"Dataflow; TOPS; Correlative; Ring (chemistry); Computer science; Dig; Architecture; Computer architecture; Computer hardware; Embedded system; Parallel computing; Engineering; Chemistry; Art; World Wide Web","score_opus":0.018077957817261653,"score_gpt":0.2631377239688243,"score_spread":0.24505976615156264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401247357","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":[0.13252984,0.0009234722,0.8641344,0.00078889827,0.0005278289,0.00027890762,0.00025111224,0.0003975178,0.00016806398],"genre_scores_gemma":[0.9894121,0.00005302001,0.010043315,0.0001280572,0.00011067785,0.000014383528,0.00001706616,0.000051224204,0.00017015215],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972645,0.00005769371,0.0007091748,0.00067526486,0.0007389463,0.0005543905],"domain_scores_gemma":[0.99775136,0.0004119949,0.00058814965,0.0006317949,0.00039103965,0.00022568471],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034832917,0.00042152818,0.0005377869,0.00064495404,0.00020489981,0.00079912145,0.0012649344,0.000122053185,0.000005100849],"category_scores_gemma":[0.00025044667,0.00032121871,0.00011848515,0.0011222656,0.00032193837,0.0029361325,0.00014977038,0.0009993475,0.00001822439],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036033013,0.00068131083,0.0033032773,0.0017874591,0.0013842009,0.009399767,0.007010843,0.04075869,0.15403557,0.0013213819,0.002307784,0.7776494],"study_design_scores_gemma":[0.03382339,0.014407331,0.057329964,0.042212546,0.0019608776,0.042863157,0.005719856,0.33024696,0.25403932,0.14889307,0.053855743,0.014647779],"about_ca_topic_score_codex":0.0000028343188,"about_ca_topic_score_gemma":0.000013958101,"teacher_disagreement_score":0.8568823,"about_ca_system_score_codex":0.00017283994,"about_ca_system_score_gemma":0.00042051414,"threshold_uncertainty_score":0.999924},"labels":[],"label_agreement":null},{"id":"W4401328698","doi":"10.1109/tse.2024.3438119","title":"AddressWatcher: Sanitizer-Based Localization of Memory Leak Fixes","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Hand sanitizer; Leak; Memory leak; Embedded system; Leak detection; Programming language; Memory management; Overlay; Engineering","score_opus":0.0139245237817579,"score_gpt":0.23100124283280993,"score_spread":0.21707671905105203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401328698","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":[0.00053956016,0.00037668302,0.9944922,0.00005305737,0.0008322036,0.000112653266,0.000046400408,0.003536072,0.000011169261],"genre_scores_gemma":[0.8055951,0.000026306281,0.19420826,0.000030227053,0.000016947608,0.000040834086,0.0000037992163,0.000029361105,0.000049167396],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990532,0.000011030016,0.00020935641,0.00031398368,0.00021786704,0.00019459357],"domain_scores_gemma":[0.9991263,0.00024636625,0.000026985861,0.00051598693,0.000045250046,0.000039076323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000796122,0.00016681668,0.00015374584,0.00034472274,0.00005630489,0.000057241916,0.00043673336,0.00009731905,0.000023187355],"category_scores_gemma":[0.000038193106,0.0001732092,0.00008214099,0.00072879845,0.000042338106,0.000521636,0.0000043912764,0.0002499887,0.000025033884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025637319,0.00002744724,0.0000015349256,0.00015304776,0.000021731365,0.000019664756,0.00009946757,0.94497925,0.0012902439,0.0005037773,0.00013304746,0.05276823],"study_design_scores_gemma":[0.0001441032,0.00007522472,0.0000063140897,0.00028424332,0.000015890084,0.000009086682,0.000021697735,0.6966931,0.30027285,0.00014650167,0.0020940374,0.00023689297],"about_ca_topic_score_codex":0.000008700923,"about_ca_topic_score_gemma":0.000005165594,"teacher_disagreement_score":0.80505556,"about_ca_system_score_codex":0.000086401335,"about_ca_system_score_gemma":0.00005097267,"threshold_uncertainty_score":0.7063266},"labels":[],"label_agreement":null},{"id":"W4401560365","doi":"10.1145/3689051.3689059","title":"Is Bare-metal I/O Performance with User-defined Storage Drives Inside VMs Possible? Benchmarking libvfio-user vs. Common Storage Virtualization Configurations","year":2024,"lang":"en","type":"article","venue":"ACM SIGOPS Operating Systems Review","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Benchmarking; Virtualization; Storage virtualization; Computer science; Operating system; Business; Cloud computing","score_opus":0.021912740136627373,"score_gpt":0.2800678232548425,"score_spread":0.2581550831182151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401560365","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":[0.087361716,0.17697297,0.7207839,0.0030343686,0.0021759586,0.0040085334,0.00015809904,0.0043260315,0.0011784101],"genre_scores_gemma":[0.9434888,0.014297615,0.03933102,0.0010600121,0.00021177277,0.00057091867,0.0002206245,0.000111977126,0.0007072742],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99585754,0.00038515942,0.0011874436,0.0012042635,0.0007783731,0.00058720884],"domain_scores_gemma":[0.99601126,0.00046913518,0.00032385776,0.00274262,0.00031851206,0.00013462918],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00097265444,0.00062604493,0.0009931992,0.0003247658,0.0007289546,0.0014844879,0.0023108893,0.00018380744,0.00004251817],"category_scores_gemma":[0.00062905764,0.0004921554,0.00012612423,0.0020584106,0.00015606298,0.0043938947,0.0008908613,0.00060940767,0.00014571648],"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":[0.00004772007,0.000570937,0.013218176,0.070323154,0.0016794018,0.0019277328,0.0161631,0.0629099,0.024065778,0.5071568,0.07334262,0.2285947],"study_design_scores_gemma":[0.001332227,0.002065193,0.0025794606,0.10770997,0.0005249861,0.0016122388,0.0010692725,0.53158534,0.0049419156,0.00016422574,0.3419751,0.004440089],"about_ca_topic_score_codex":0.0001288045,"about_ca_topic_score_gemma":0.000048057147,"teacher_disagreement_score":0.8561271,"about_ca_system_score_codex":0.000260758,"about_ca_system_score_gemma":0.00029404613,"threshold_uncertainty_score":0.999753},"labels":[],"label_agreement":null},{"id":"W4401568809","doi":"10.23919/date58400.2024.10546818","title":"Shared Data Kills Real-Time Cache Analysis. How to Resurrect It?","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Cache; Computer science; Operating system","score_opus":0.04908469635405117,"score_gpt":0.3197532534574466,"score_spread":0.27066855710339544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401568809","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023672996,0.00016918639,0.9685548,0.021670895,0.00023554159,0.00017170866,0.0003601072,0.0035935084,0.005007541],"genre_scores_gemma":[0.09987917,0.00009209859,0.88634247,0.00063967705,0.0000777504,0.000027937811,0.0005627937,0.000025208928,0.012352896],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99777406,0.000045188208,0.00019992587,0.001271357,0.00035058433,0.00035887834],"domain_scores_gemma":[0.99451876,0.000283502,0.000036469915,0.0050047254,0.000051516377,0.00010503028],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00052158785,0.00019006857,0.00028281257,0.00058691803,0.000070965434,0.0007690994,0.005236205,0.00008221791,0.000117309086],"category_scores_gemma":[0.000618821,0.0001530396,0.00006847449,0.004008121,0.000044770335,0.002214525,0.0047348323,0.00017155947,0.0009588919],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003571993,0.000027057162,0.000048704045,0.000017205266,0.00037751085,0.00026502225,0.00019402496,0.00036835644,0.0069050253,0.020973274,0.8921543,0.078665994],"study_design_scores_gemma":[0.00015065541,0.00013372116,0.00081003923,0.000080812235,0.0002429002,0.000026210335,0.00015212643,0.6026417,0.0073592924,0.0055618198,0.38185632,0.0009844209],"about_ca_topic_score_codex":0.000116565,"about_ca_topic_score_gemma":0.00014604608,"teacher_disagreement_score":0.60227334,"about_ca_system_score_codex":0.00008387384,"about_ca_system_score_gemma":0.00006893858,"threshold_uncertainty_score":0.999819},"labels":[],"label_agreement":null},{"id":"W4401598533","doi":"10.1007/978-3-031-68400-5_12","title":"CDS Composition of Multi-round Protocols","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Composition (language)","score_opus":0.03271625657244092,"score_gpt":0.3067580909927956,"score_spread":0.2740418344203547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401598533","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014554197,0.00042481313,0.9929778,0.00037446112,0.00077518314,0.003751449,0.000027423455,0.0006016011,0.0010527377],"genre_scores_gemma":[0.022745537,0.000019449206,0.9760861,0.00023871927,0.00013559042,0.00038095305,0.000010303206,0.000042368367,0.0003410181],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99635094,0.000016512,0.0006311812,0.0015748767,0.00090538815,0.00052111637],"domain_scores_gemma":[0.9968811,0.0002643285,0.00035802487,0.0021733462,0.00023941552,0.000083745595],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005217114,0.000515404,0.00060341135,0.0011091073,0.0001289498,0.0003857983,0.004783558,0.00037865288,0.000008195635],"category_scores_gemma":[0.00006711818,0.00046098063,0.00013024849,0.000872172,0.0013270137,0.0009442002,0.0031583088,0.0009491204,0.000065756176],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008595967,0.00008322707,0.000016643407,0.00035323363,0.000023057566,0.00026050524,0.0004612077,0.019942353,0.0030796607,0.24886066,0.000034295903,0.72687656],"study_design_scores_gemma":[0.00032414717,0.00035427487,0.000028427534,0.0018508793,0.000010646762,0.00012021183,2.2625092e-7,0.41650364,0.019973474,0.55729455,0.0027290778,0.0008104491],"about_ca_topic_score_codex":0.00000961654,"about_ca_topic_score_gemma":0.00002276726,"teacher_disagreement_score":0.7260661,"about_ca_system_score_codex":0.00037142396,"about_ca_system_score_gemma":0.0003212385,"threshold_uncertainty_score":0.9997842},"labels":[],"label_agreement":null},{"id":"W4401693310","doi":"10.1109/isit57864.2024.10619149","title":"Secure Storage Using Maximally Recoverable Locally Repairable Codes","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Database","score_opus":0.02221787307759944,"score_gpt":0.2653729086902514,"score_spread":0.24315503561265195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401693310","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030816856,0.0013386536,0.98087037,0.00067865895,0.000586235,0.00014724559,0.000015165537,0.005066653,0.008215331],"genre_scores_gemma":[0.124631345,0.00012346532,0.8721434,0.00032568842,0.00004946301,0.000011038648,0.0000061860496,0.000027560129,0.002681875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829954,0.000031222076,0.0002438737,0.00072058203,0.0002786026,0.00042616218],"domain_scores_gemma":[0.9985982,0.00010845864,0.00004326555,0.0011222826,0.00006506102,0.000062684645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032540815,0.00020303711,0.00019658613,0.0002277783,0.00014588596,0.0005094652,0.0012093555,0.00012370246,0.000088734574],"category_scores_gemma":[0.000104696606,0.00017682427,0.00007115978,0.0009390091,0.00007936684,0.0023158211,0.000766767,0.0003057741,0.0002027796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010897305,0.00006681743,0.000052163112,0.0001811903,0.000077655895,0.0013767838,0.00028949545,0.014607822,0.010306806,0.8536995,0.028441235,0.09088963],"study_design_scores_gemma":[0.00011082524,0.00010736458,0.000009882382,0.00013226473,0.000009009716,0.00018973758,0.000076317796,0.8157546,0.0068709333,0.058887966,0.11743952,0.00041158815],"about_ca_topic_score_codex":0.00008559186,"about_ca_topic_score_gemma":0.000039286067,"teacher_disagreement_score":0.80114675,"about_ca_system_score_codex":0.0002100342,"about_ca_system_score_gemma":0.00018439493,"threshold_uncertainty_score":0.72106844},"labels":[],"label_agreement":null},{"id":"W4402192962","doi":"10.1109/fccm60383.2024.00036","title":"Learned Index Acceleration with FPGAs: A SMART Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Acceleration; Field-programmable gate array; Computer science; Index (typography); Embedded system; World Wide Web; Physics","score_opus":0.031056256576477446,"score_gpt":0.2645840712107043,"score_spread":0.23352781463422687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402192962","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":[0.0013498293,0.00012796461,0.98527414,0.0010302827,0.00007522598,0.00012009558,8.8173505e-7,0.0029038258,0.009117748],"genre_scores_gemma":[0.61552775,0.000008637667,0.38303125,0.00011305269,0.000015059791,0.0000306931,0.0000053227277,0.000007345636,0.0012609109],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912554,0.000011402322,0.00009005692,0.00041761706,0.00018446248,0.0001709259],"domain_scores_gemma":[0.99931467,0.000030140496,0.000016542186,0.00058777427,0.000025417143,0.000025466885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094885014,0.00010048419,0.00007980033,0.00013301763,0.000056637316,0.0003677767,0.00064245146,0.0000527821,0.000012223948],"category_scores_gemma":[0.000020730819,0.000068802176,0.000015939026,0.00065053406,0.000050449198,0.0011043969,0.00028983006,0.0001674436,0.00008461604],"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":[0.0000040396303,0.000026552976,0.00020124209,0.000029093495,0.00002010715,0.000047064317,0.00023310816,0.0011524357,0.00041186294,0.63151973,0.0032460047,0.36310875],"study_design_scores_gemma":[0.00024345898,0.00016705887,0.00040641715,0.00003212401,0.00000561455,0.00011961869,0.00021876724,0.92609704,0.0051553613,0.028488217,0.038678512,0.0003878181],"about_ca_topic_score_codex":0.000013111961,"about_ca_topic_score_gemma":0.000008653277,"teacher_disagreement_score":0.9249446,"about_ca_system_score_codex":0.000039375773,"about_ca_system_score_gemma":0.00004859147,"threshold_uncertainty_score":0.3546479},"labels":[],"label_agreement":null},{"id":"W4402572146","doi":"10.1109/newcas58973.2024.10666340","title":"A 580-nA Quiescent Current Low-Dropout Regulator with Zero-Tracking for Wide Load Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Regulator; Low-dropout regulator; Zero (linguistics); Control theory (sociology); Dropout (neural networks); Tracking (education); Dropout voltage; Current (fluid); Computer science; Voltage regulator; Engineering; Control (management); Chemistry; Electrical engineering; Voltage; Artificial intelligence; Psychology; Machine learning","score_opus":0.018334123899766464,"score_gpt":0.2899688326371607,"score_spread":0.27163470873739426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402572146","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":[0.00025811527,0.0015354601,0.9916262,0.002649464,0.00025262902,0.00079815346,0.000025225378,0.00268065,0.00017411192],"genre_scores_gemma":[0.5331239,0.00007138432,0.4650427,0.00014039541,0.000095359246,0.00089447876,0.000019801146,0.000036717807,0.00057523925],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983999,0.000008033016,0.00022413631,0.000703042,0.00030560163,0.00035928877],"domain_scores_gemma":[0.99843127,0.00016229005,0.000057164238,0.0011552316,0.00012547438,0.00006857962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001370784,0.0001960455,0.00016185481,0.00012619438,0.00014549095,0.00031115857,0.0010734551,0.000054069453,0.000005674226],"category_scores_gemma":[0.000061588435,0.00013287576,0.000058961385,0.00060781604,0.00012485086,0.0008780774,0.00041240305,0.0001799099,0.00009188865],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048171696,0.000039823826,0.00006437634,0.00013943386,0.00001739546,0.0000058187206,0.00009317429,0.00009025785,0.00050169125,0.35187402,0.0052138628,0.6419553],"study_design_scores_gemma":[0.00044255191,0.00017982496,0.00012521351,0.0004554806,0.000031917334,0.00004262662,0.00009435165,0.079587564,0.02836671,0.08165801,0.8082825,0.0007332715],"about_ca_topic_score_codex":0.000006034836,"about_ca_topic_score_gemma":0.000018034207,"teacher_disagreement_score":0.80306864,"about_ca_system_score_codex":0.00024051218,"about_ca_system_score_gemma":0.00018905311,"threshold_uncertainty_score":0.54185164},"labels":[],"label_agreement":null},{"id":"W4403277132","doi":"10.1109/fpl64840.2024.00038","title":"IMAGine: An In-Memory Accelerated GEMV Engine Overlay","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"National Science Foundation","keywords":"Overlay; Computer science; Random access memory; Operating system; Computer hardware","score_opus":0.020245732850251424,"score_gpt":0.2840457953245237,"score_spread":0.26380006247427223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403277132","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":[0.020853844,0.0009213586,0.9653507,0.0017078368,0.0005575141,0.00014294505,0.0000065992494,0.0055029895,0.0049562315],"genre_scores_gemma":[0.7696856,0.00004482608,0.2291533,0.00028981903,0.000039977225,0.000018441173,0.000011642275,0.000015448932,0.00074089895],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989384,0.00001420085,0.0001556763,0.00048187547,0.00014285039,0.00026702558],"domain_scores_gemma":[0.99903387,0.000053873806,0.000013559223,0.00082947203,0.000025817784,0.000043386583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012984994,0.00013258017,0.00011458826,0.0002860773,0.000024863602,0.00024652644,0.0010929871,0.000055842433,0.000081008344],"category_scores_gemma":[0.000048177226,0.00011177599,0.000020333913,0.0010339762,0.000045398858,0.0025118992,0.00046310097,0.00023294956,0.00019644653],"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":[0.0000030396266,0.00007759649,0.0001100519,0.0000355578,0.00001247458,0.00094157207,0.00027294832,0.0011513497,0.021266004,0.18593276,0.010772522,0.77942413],"study_design_scores_gemma":[0.0004546243,0.0001596764,0.0019725834,0.000067946785,0.00000463661,0.00012027477,0.0001743245,0.85101086,0.071663804,0.037790325,0.035803616,0.00077732437],"about_ca_topic_score_codex":0.000039935,"about_ca_topic_score_gemma":0.000029530345,"teacher_disagreement_score":0.84985954,"about_ca_system_score_codex":0.00007046446,"about_ca_system_score_gemma":0.000048765993,"threshold_uncertainty_score":0.45580924},"labels":[],"label_agreement":null},{"id":"W4403278692","doi":"10.1109/fpl64840.2024.00051","title":"FORC: A High-Throughput Streaming FPGA Accelerator for Optimized Row Columnar File Decoders in Big Data Engines","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada); Simon Fraser University","funders":"","keywords":"Throughput; Computer science; Field-programmable gate array; Big data; Parallel computing; Computer hardware; Streaming data; Operating system; Wireless","score_opus":0.06754967657033036,"score_gpt":0.2990600390113527,"score_spread":0.23151036244102235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403278692","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007156199,0.0005121486,0.99250346,0.0014926735,0.00077826297,0.0005353196,0.0013883347,0.0019434601,0.00013073588],"genre_scores_gemma":[0.040988572,0.000094916,0.9571959,0.00019402886,0.000105676925,0.0002810913,0.0006133194,0.000033347947,0.0004931812],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979047,0.000018817771,0.00033614656,0.0010504327,0.00019171252,0.0004981429],"domain_scores_gemma":[0.9971403,0.00070821773,0.00005412371,0.0019959265,0.000046569898,0.000054863405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024256893,0.00023909102,0.00029898065,0.0002870274,0.00009316666,0.00034766458,0.002940244,0.00012600364,0.000086571265],"category_scores_gemma":[0.00047961692,0.00021805005,0.000046519137,0.00088680594,0.00006907318,0.0024926846,0.0020382032,0.00018833969,0.000030693278],"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":[0.000030515834,0.00010472548,0.000016352535,0.00018779685,0.00008395191,0.00017164678,0.00024527937,0.004938802,0.00068759243,0.037318993,0.29662868,0.65958565],"study_design_scores_gemma":[0.0009000192,0.00010352601,0.000026078287,0.000120153774,0.000011698051,0.000014178634,0.00025036206,0.8702203,0.004793997,0.009739645,0.113336876,0.00048317848],"about_ca_topic_score_codex":0.00014247192,"about_ca_topic_score_gemma":0.00041758968,"teacher_disagreement_score":0.86528146,"about_ca_system_score_codex":0.00011285799,"about_ca_system_score_gemma":0.00015507873,"threshold_uncertainty_score":0.88918227},"labels":[],"label_agreement":null},{"id":"W4403310488","doi":"10.22331/q-2024-10-10-1498","title":"Decoding algorithms for surface codes","year":2024,"lang":"en","type":"article","venue":"Quantum","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Photon Etc (Canada)","funders":"Ministerio de Ciencia e Innovación; Ministerio de Economía y Competitividad; European Commission","keywords":"Decoding methods; Computer science; Algorithm; List decoding; Sequential decoding; Concatenated error correction code; Block code","score_opus":0.049339016999500135,"score_gpt":0.32596670949151874,"score_spread":0.2766276924920186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403310488","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030680783,0.0024642653,0.9900669,0.0011558847,0.0008915483,0.00013469154,0.000033483415,0.0020612862,0.0001238875],"genre_scores_gemma":[0.22264965,0.00009547635,0.77684116,0.00006951445,0.00004934016,0.000021808819,0.000007413536,0.000014952218,0.00025068663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914825,0.000008340999,0.000120479286,0.00036416837,0.00010924363,0.00024951537],"domain_scores_gemma":[0.9991807,0.00027140934,0.000021507161,0.00046979173,0.000027917999,0.000028689408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018123194,0.0000985766,0.000106662716,0.000064385385,0.00007877211,0.00016766222,0.0007653626,0.000050543957,0.0000035032406],"category_scores_gemma":[0.00008968094,0.000086935135,0.00004435235,0.00030093262,0.000045884037,0.00064715446,0.0002570716,0.000096759606,0.000086507054],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010348732,0.0000071829436,0.00000661737,0.000035206245,0.000009685327,0.000029551295,0.00008596766,0.000098148266,0.0020065946,0.82839125,0.0057253833,0.16360337],"study_design_scores_gemma":[0.000059349197,0.000056067867,0.000010258926,0.000034162782,0.0000030704207,0.000014640223,0.00004013819,0.77869403,0.01018535,0.15409367,0.056664873,0.00014435698],"about_ca_topic_score_codex":0.0000051508096,"about_ca_topic_score_gemma":0.0000021509377,"teacher_disagreement_score":0.7785959,"about_ca_system_score_codex":0.00004413624,"about_ca_system_score_gemma":0.00003345011,"threshold_uncertainty_score":0.3545112},"labels":[],"label_agreement":null},{"id":"W4403448754","doi":"10.1007/s43678-024-00773-6","title":"Tech the pressure off: streamlining ED discharges with digital solutions","year":2024,"lang":"en","type":"editorial","venue":"Canadian Journal of Emergency Medicine","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital","funders":"","keywords":"Medicine; Aeronautics; Engineering","score_opus":0.03425918049664772,"score_gpt":0.2994101486583109,"score_spread":0.26515096816166317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403448754","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008860996,0.055662815,0.045479737,0.011006652,0.88607,0.00018721912,0.0005308103,0.000105985506,0.00094787957],"genre_scores_gemma":[0.007292942,0.005479987,0.002892639,0.000041357827,0.9774938,0.000028429658,0.00017904992,0.00012653433,0.0064652455],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99711525,0.000039365117,0.00081820245,0.00041713144,0.0009830103,0.0006270196],"domain_scores_gemma":[0.99676186,0.0003291968,0.00066289486,0.001047184,0.00073755265,0.0004612899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060123735,0.00039266958,0.0005506689,0.0005753425,0.00034229626,0.00010487597,0.0033749384,0.00034367375,0.00019284178],"category_scores_gemma":[0.0037007674,0.00021471307,0.0001249402,0.0009160738,0.00042846365,0.00089600723,0.00020457077,0.002148958,0.000019746049],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036749227,0.000005142326,0.000017445527,0.000046879584,0.00020473717,0.00025714003,0.0003633977,0.00004884899,0.0000030135857,0.0022829995,0.99137354,0.0053931647],"study_design_scores_gemma":[0.000172932,0.00042980272,0.0000073285464,0.0008410892,0.00020373265,0.000037906335,0.000390407,0.0001470382,0.0000022863724,0.003682702,0.9938413,0.00024349664],"about_ca_topic_score_codex":0.00083408307,"about_ca_topic_score_gemma":0.007054246,"teacher_disagreement_score":0.09142377,"about_ca_system_score_codex":0.00016005817,"about_ca_system_score_gemma":0.0031172433,"threshold_uncertainty_score":0.93362725},"labels":[],"label_agreement":null},{"id":"W4403579187","doi":"10.48550/arxiv.2410.13123","title":"Improved Kernelization and Fixed-parameter Algorithms for Bicluster Editing","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kernelization; Algorithm; Computer science; Mathematical optimization; Mathematics; Parameterized complexity","score_opus":0.06158120445733221,"score_gpt":0.2159942082774401,"score_spread":0.1544130038201079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403579187","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":[0.018000336,0.00019858022,0.97880197,0.00023636359,0.001058608,0.0005168852,0.000097261305,0.0009851069,0.00010489003],"genre_scores_gemma":[0.8449864,0.00012829722,0.15356265,0.00010776721,0.0001761858,0.0000093537155,0.000059381717,0.000036952184,0.0009330186],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980815,0.000028057064,0.00018407001,0.0013185492,0.000057448502,0.00033037225],"domain_scores_gemma":[0.9984042,0.00019026599,0.00018534884,0.0010191792,0.00012857617,0.000072428484],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016870069,0.00029913464,0.00026754002,0.0003136008,0.00012259286,0.00025060773,0.0011912351,0.00033899595,0.000002590281],"category_scores_gemma":[0.0001760257,0.00032629832,0.00010796944,0.000400347,0.00013607004,0.000503391,0.0057608876,0.00049134623,0.000013753657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008862381,0.00017540327,0.0006508691,0.0022082694,0.0005923678,0.000706436,0.0011877507,0.08675866,0.0013332776,0.7429034,0.00646116,0.15693377],"study_design_scores_gemma":[0.00021872635,0.000046043027,0.000015109906,0.000079211226,0.00004490804,0.000004998206,0.000059174607,0.7961626,0.00061642297,0.20170905,0.0007508195,0.0002929201],"about_ca_topic_score_codex":0.000025083456,"about_ca_topic_score_gemma":0.000014413094,"teacher_disagreement_score":0.8269861,"about_ca_system_score_codex":0.00015712816,"about_ca_system_score_gemma":0.00006539263,"threshold_uncertainty_score":0.9999189},"labels":[],"label_agreement":null},{"id":"W4403681459","doi":"10.1016/j.future.2024.107571","title":"Efficient security interface for high-performance Ceph storage systems","year":2024,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Research Canada; University of New Brunswick","funders":"Mitacs; Lockheed Martin","keywords":"Computer science; Interface (matter); Embedded system; Distributed computing; Operating system","score_opus":0.013741165547944521,"score_gpt":0.24070109676054857,"score_spread":0.22695993121260405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403681459","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":[0.017326724,0.008496158,0.829254,0.00044013927,0.14144228,0.0009520083,0.0000833264,0.0019847811,0.00002058792],"genre_scores_gemma":[0.8987735,0.00003754916,0.062313564,0.000061494386,0.03808128,0.00038126516,0.00009317081,0.000042467946,0.00021570221],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99744844,0.000112259884,0.00056795054,0.0009951349,0.00043139086,0.0004448166],"domain_scores_gemma":[0.9982377,0.00009556803,0.00016041551,0.0011929793,0.00022627655,0.000087018794],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005289798,0.00036130592,0.00037830215,0.00029085396,0.00028206265,0.0013850775,0.0012381506,0.00022239648,0.0000014296213],"category_scores_gemma":[0.000010902655,0.00031104137,0.00007417939,0.0006022206,0.00004246546,0.00063284335,0.00043185902,0.00027653595,0.00008882888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041948583,0.000033075077,0.000002866174,0.0005555283,0.00005147014,0.000018168254,0.00066705275,0.6484747,0.0009658742,0.15810904,0.18357155,0.0075465166],"study_design_scores_gemma":[0.00017459225,0.00015365526,0.000006490405,0.0001361572,0.000007704206,0.00007160524,0.000049855378,0.8308308,0.0012950436,0.000017905524,0.16694948,0.00030669192],"about_ca_topic_score_codex":0.00001613946,"about_ca_topic_score_gemma":0.0000030301846,"teacher_disagreement_score":0.8814468,"about_ca_system_score_codex":0.00028839536,"about_ca_system_score_gemma":0.000088485955,"threshold_uncertainty_score":0.9999342},"labels":[],"label_agreement":null},{"id":"W4403986936","doi":"10.1016/j.disc.2024.114298","title":"On finding the largest minimum distance of locally recoverable codes: A graph theory approach","year":2024,"lang":"en","type":"article","venue":"Discrete Mathematics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Combinatorics; Discrete mathematics; Graph theory; Graph","score_opus":0.019490960527396996,"score_gpt":0.2627805352785573,"score_spread":0.24328957475116034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403986936","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":[0.0017937098,0.00067921646,0.98942095,0.0002641295,0.00015232114,0.00025141568,0.000069822345,0.00044046348,0.0069279787],"genre_scores_gemma":[0.644406,0.000101694684,0.35452706,0.00009689378,0.000020052752,0.000069789065,0.000014817076,0.00003427605,0.00072940503],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99865854,0.00005160889,0.0003168914,0.0003647549,0.00033490043,0.00027331582],"domain_scores_gemma":[0.9975044,0.0010262312,0.0001282316,0.0012805095,0.000032046075,0.0000285901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006949413,0.00019146649,0.00024340676,0.00011402568,0.00012012828,0.00017671096,0.0015404263,0.00007258062,0.000007102892],"category_scores_gemma":[0.00038191737,0.000117762684,0.00009987012,0.0006583258,0.00022518107,0.00035498585,0.00036750652,0.00026815233,0.000026962274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004177635,0.00004720452,0.0000021851483,0.000267991,0.00003062061,0.000010213511,0.0012741216,0.00043338933,0.00013298822,0.9943071,0.00076419907,0.0027258224],"study_design_scores_gemma":[0.00007957519,0.00007043573,0.0000029583466,0.00035512962,0.000015669446,0.000014462801,0.00078022457,0.14272012,0.0014461044,0.8534906,0.0008467886,0.00017791268],"about_ca_topic_score_codex":0.0000012106535,"about_ca_topic_score_gemma":0.0000013375162,"teacher_disagreement_score":0.64261234,"about_ca_system_score_codex":0.000041510742,"about_ca_system_score_gemma":0.00003744166,"threshold_uncertainty_score":0.48022228},"labels":[],"label_agreement":null},{"id":"W4404001584","doi":"10.1088/1361-6668/ad8e03","title":"Manufacturing the current flow diverter architecture in REBCO tapes using silver inkjet printing","year":2024,"lang":"en","type":"article","venue":"Superconductor Science and Technology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Clinical Research Institute; Collège Boréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Inkjet printing; Materials science; Current (fluid); Flow (mathematics); Flow diverter; Composite material; Inkwell; Electrical engineering","score_opus":0.021631156875421845,"score_gpt":0.275020298955686,"score_spread":0.2533891420802642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404001584","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":[0.9501208,0.0028862383,0.03896712,0.0060502198,0.00076304417,0.00023530268,0.0000046356254,0.00093682494,0.00003579602],"genre_scores_gemma":[0.9515655,0.000103382816,0.04819209,0.000074955016,0.000029838193,0.0000184154,4.903321e-7,0.000009319849,0.0000059976715],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99785656,0.000022808785,0.00022879057,0.000918859,0.00035948958,0.00061352056],"domain_scores_gemma":[0.9988671,0.00008502314,0.00003095601,0.0009108149,0.00006301654,0.000043089127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059734454,0.00021040122,0.00018255987,0.0011899124,0.00037111746,0.00037155478,0.0023372886,0.000112551825,0.0000034402376],"category_scores_gemma":[0.00031755734,0.00013859256,0.00002578091,0.0025346274,0.0016934985,0.0019242812,0.0026150418,0.0008913914,0.000011434216],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.835842e-7,0.000011929494,0.0010337254,0.00003176771,0.000004524924,0.000059414786,0.0006342233,0.000036824553,0.04924902,0.038289424,0.000023424547,0.91062516],"study_design_scores_gemma":[0.00052303873,0.00019815954,0.003217861,0.00074089604,0.00002769917,0.0010615345,0.0021208308,0.18368404,0.34999672,0.37287667,0.083947,0.001605566],"about_ca_topic_score_codex":0.000016076761,"about_ca_topic_score_gemma":0.000035152036,"teacher_disagreement_score":0.9090196,"about_ca_system_score_codex":0.00014634055,"about_ca_system_score_gemma":0.00019426784,"threshold_uncertainty_score":0.6239766},"labels":[],"label_agreement":null},{"id":"W4404707156","doi":"10.2139/ssrn.5025403","title":"The Next Phase of the Data Economy: Economic &amp;amp; Technological Perspectives","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Economics; Phase (matter); Chemistry","score_opus":0.05420795687323905,"score_gpt":0.32738967937595764,"score_spread":0.2731817225027186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404707156","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":[0.022095373,0.102827735,0.8354837,0.034007113,0.002263906,0.00086202135,0.00024735683,0.0009973795,0.0012154585],"genre_scores_gemma":[0.9462597,0.037407417,0.014599718,0.000057353067,0.00041804177,0.000054872573,0.000031088384,0.00006345976,0.0011083634],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99594766,0.0001584169,0.00067181996,0.0010982263,0.00024013793,0.0018837638],"domain_scores_gemma":[0.9927212,0.00030827094,0.0007736314,0.0060616387,0.00008569708,0.000049557275],"candidate_categories":["open_science","research_integrity"],"consensus_categories":["open_science"],"category_scores_codex":[0.0029148334,0.00042520527,0.00045547617,0.00021865554,0.00049949164,0.0007359021,0.018232582,0.00038031774,0.000010945857],"category_scores_gemma":[0.0006552929,0.00024395909,0.00027383794,0.00028402853,0.0010301998,0.0006294104,0.023134783,0.009702496,0.0001397458],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001116424,0.000051047606,0.0000059999775,0.000011513377,0.00027129523,0.0000026100074,0.00011459201,0.00016118101,0.00006311465,0.88808405,0.0014984976,0.109724954],"study_design_scores_gemma":[0.0002110288,0.000052721338,0.0000021523197,0.000055176715,0.000045344623,0.0004425687,0.001137972,0.0023782405,0.00009345166,0.9236848,0.07163427,0.00026228486],"about_ca_topic_score_codex":0.000028691858,"about_ca_topic_score_gemma":0.0009833297,"teacher_disagreement_score":0.9241643,"about_ca_system_score_codex":0.002613822,"about_ca_system_score_gemma":0.0057769055,"threshold_uncertainty_score":0.9998594},"labels":[],"label_agreement":null},{"id":"W4405647145","doi":"10.1145/3708993","title":"Holographic Storage for the Cloud: advances and challenges","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Cloud computing; Holography; Cloud storage; Operating system; Optics; Physics","score_opus":0.04280044925094979,"score_gpt":0.28636050813317016,"score_spread":0.24356005888222038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405647145","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":[0.0004003239,0.09397366,0.8912433,0.011222944,0.001344732,0.00035950597,0.000070760536,0.0013097803,0.000074989606],"genre_scores_gemma":[0.8264505,0.07303712,0.099231444,0.00029070317,0.00013089516,0.00055713276,0.000003624616,0.000045483834,0.0002530889],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99864393,0.00003626561,0.00017009386,0.00064462377,0.00019549501,0.00030959872],"domain_scores_gemma":[0.9971555,0.0012381168,0.00003983844,0.0014792247,0.00003580704,0.000051524046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028896952,0.00021961892,0.00017340225,0.0002673702,0.00042130775,0.00017635337,0.0013802106,0.00010969483,0.000006942554],"category_scores_gemma":[0.00006822546,0.00015680304,0.00010508292,0.0005148642,0.00025673606,0.0010113261,0.000054192158,0.0003626091,0.00001717296],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009665169,0.000036696423,5.2444585e-7,0.00011055689,0.000053051917,0.000029770403,0.00041597238,0.00088874786,0.00011085645,0.037933093,0.00017962194,0.9602314],"study_design_scores_gemma":[0.00034631882,0.0004691697,0.00011746862,0.00008410957,0.000060927527,0.00009215583,0.0007353699,0.012814811,0.0009813551,0.07798523,0.90586936,0.00044372858],"about_ca_topic_score_codex":0.0000037677244,"about_ca_topic_score_gemma":0.00002957304,"teacher_disagreement_score":0.9597877,"about_ca_system_score_codex":0.000041177605,"about_ca_system_score_gemma":0.000027038408,"threshold_uncertainty_score":0.63942426},"labels":[],"label_agreement":null},{"id":"W4405936761","doi":"10.1109/icm63406.2024.10815775","title":"Machine Learning based Memory Load Value Predictor for Multimedia Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Multimedia; Value (mathematics); Machine learning","score_opus":0.014756229459902192,"score_gpt":0.2683446567429991,"score_spread":0.25358842728309694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405936761","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021145202,0.0010617878,0.9915037,0.0012783309,0.00018709472,0.00050771487,0.000048674865,0.004429148,0.0009623954],"genre_scores_gemma":[0.048794564,0.000017639886,0.9484188,0.00017358392,0.0000705184,0.0006502909,0.000049988445,0.000018259125,0.0018063657],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898595,0.000013678574,0.00014609557,0.0004542743,0.00018699608,0.00021301102],"domain_scores_gemma":[0.9988437,0.00042682566,0.000028603756,0.0005992188,0.00005413193,0.000047501115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019900769,0.00011742664,0.000100902216,0.000114703296,0.000111268666,0.00011139363,0.00082973076,0.00006312175,0.0000238016],"category_scores_gemma":[0.00021495034,0.00009914112,0.000052452702,0.0003820865,0.000060830695,0.00043813785,0.00025439268,0.0001851937,0.00011712887],"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":[0.0000066250377,0.00007082166,0.000052264717,0.00017332958,0.00003542778,0.000015632728,0.00019453131,0.011507845,0.0033728285,0.24200611,0.0064966055,0.736068],"study_design_scores_gemma":[0.00013655309,0.00003681439,0.000008537752,0.000010906814,0.00000503764,0.0000023634016,0.0000113856,0.81926835,0.003965893,0.0069518853,0.1694976,0.00010468534],"about_ca_topic_score_codex":0.000013083556,"about_ca_topic_score_gemma":0.000005375036,"teacher_disagreement_score":0.8077605,"about_ca_system_score_codex":0.0000943712,"about_ca_system_score_gemma":0.00011653187,"threshold_uncertainty_score":0.40428576},"labels":[],"label_agreement":null},{"id":"W4406261209","doi":"10.1109/qce60285.2024.00037","title":"A Quantum Vault Scheme for Digital Currency","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; University of Ottawa","funders":"","keywords":"Vault (architecture); Scheme (mathematics); Computer science; Digital signature; Digital currency; Currency; Computer security; World Wide Web; Mathematics; Engineering; Payment; Hash function; Monetary economics; Structural engineering; Economics","score_opus":0.026721658006044306,"score_gpt":0.29656536179048626,"score_spread":0.26984370378444195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406261209","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005174314,0.00069127284,0.99175936,0.0013259085,0.00049888296,0.00013717041,0.000038671285,0.0031230461,0.0019082436],"genre_scores_gemma":[0.38761005,0.000023777395,0.6105927,0.00008353285,0.000060415812,0.00008377566,0.000019191384,0.000014137354,0.0015124283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99919915,0.0000017025598,0.000113790484,0.00036356674,0.00010860081,0.00021316197],"domain_scores_gemma":[0.9993071,0.000107717075,0.000013830345,0.0005113493,0.00003127983,0.000028718916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004948842,0.00009382796,0.00007845877,0.00009387777,0.00004221305,0.00041517965,0.0008520567,0.00004118728,0.000007649462],"category_scores_gemma":[0.00015438374,0.00007372459,0.000049163904,0.00034166736,0.000040147133,0.0018608663,0.0004165388,0.00008724199,0.00021619315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.66559e-7,0.000009729427,0.0000071353415,0.000018821622,0.000004400916,0.000008275863,0.000023016148,0.0000011522691,0.00015713884,0.82233083,0.014222545,0.16321646],"study_design_scores_gemma":[0.000088233915,0.00008656482,0.000006070967,0.000030494772,0.0000015452595,0.000017619606,0.00003468145,0.25516513,0.001699258,0.408573,0.3340985,0.00019889713],"about_ca_topic_score_codex":0.000001106954,"about_ca_topic_score_gemma":6.7487554e-7,"teacher_disagreement_score":0.41375783,"about_ca_system_score_codex":0.000026509522,"about_ca_system_score_gemma":0.000044661072,"threshold_uncertainty_score":0.40035868},"labels":[],"label_agreement":null},{"id":"W4406308322","doi":"10.1177/10591478251313785","title":"Design and Analysis of Efficient Sequencing Policies for Linear Cold Storage Devices","year":2025,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital","funders":"","keywords":"Computer science; FIFO (computing and electronics); Scalability; Time complexity; Mathematical optimization; Dynamic programming; Operations research; Algorithm; Database; Computer hardware","score_opus":0.027970618929971325,"score_gpt":0.2915664071999586,"score_spread":0.26359578826998725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406308322","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017016688,0.00031401863,0.9801651,0.0017211266,0.000089051224,0.0005335905,0.0000037532864,0.00009922088,0.000057408874],"genre_scores_gemma":[0.4252228,0.00012701494,0.57398593,0.00009687526,0.0000058688343,0.000098160024,0.0000045881748,0.0000019933623,0.00045675552],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993922,0.000020508858,0.00014902018,0.00028658443,0.00006858775,0.000083098486],"domain_scores_gemma":[0.99951816,0.000026792037,0.000035636658,0.00031787786,0.00008992114,0.000011600001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026267604,0.00006656096,0.00011485783,0.0005287842,0.00020993337,0.000075812175,0.00015081078,0.000016761349,5.4441534e-7],"category_scores_gemma":[0.000053862273,0.00006107841,0.000016300433,0.000990627,0.0000625627,0.00022444908,0.00019520293,0.00002637976,2.1328593e-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":[0.000003241303,0.000027012624,0.00006888243,0.00007045913,0.00020122714,2.960016e-7,0.00032096886,0.60109574,0.0016925641,0.38862538,0.00013716359,0.0077571003],"study_design_scores_gemma":[0.000115644456,0.000036980447,0.0009008981,0.000024638766,0.0002505463,4.524428e-7,0.00056328735,0.9825029,0.011710275,0.00041749084,0.0033783324,0.00009857182],"about_ca_topic_score_codex":0.000010925794,"about_ca_topic_score_gemma":0.000019679997,"teacher_disagreement_score":0.40820614,"about_ca_system_score_codex":0.000041926694,"about_ca_system_score_gemma":0.000013326886,"threshold_uncertainty_score":0.24907054},"labels":[],"label_agreement":null},{"id":"W4406421002","doi":"10.1016/0967-0653(93)93649-c","title":"10.1016/0967-0653(93)93649-c","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Bathythermograph; Test (biology); Computer science; Geology; Oceanography; Paleontology","score_opus":0.007742980846380411,"score_gpt":0.18574282526143246,"score_spread":0.17799984441505204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406421002","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003007718,0.000113098824,0.007060394,0.0007171286,0.0000035847634,0.0001752358,0.000017519573,0.0018877329,0.98999524],"genre_scores_gemma":[0.000045500685,5.357773e-7,0.039435208,0.000071971546,0.00004155198,0.000025077137,0.000008697446,0.000015392205,0.96035606],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986702,0.000024525996,0.00018188536,0.00048217556,0.0002434223,0.00039778225],"domain_scores_gemma":[0.99840796,0.000059784245,0.000038493694,0.0013470671,0.00003902518,0.000107665524],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000119228935,0.00017703757,0.00017755882,0.00012264842,0.00010424086,0.000104000705,0.0019182385,0.00008184874,0.9575945],"category_scores_gemma":[0.000085366366,0.00017141199,0.000045417477,0.000588399,0.000067501,0.0006873789,0.0004936181,0.00016250358,0.99630904],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007855702,0.000021001953,1.0217526e-8,0.0000017180639,0.0000046574646,0.000022657043,0.0000109410485,0.00013102475,0.000025426283,0.00008429263,0.13672051,0.86296993],"study_design_scores_gemma":[0.00011662186,0.000110326466,0.0000040721898,0.000010967122,0.0000028402626,0.000022921095,7.2447534e-7,0.0015613155,0.0005183755,0.0004997831,0.9969227,0.0002293832],"about_ca_topic_score_codex":0.000008105996,"about_ca_topic_score_gemma":1.5779825e-7,"teacher_disagreement_score":0.8627405,"about_ca_system_score_codex":0.000059362425,"about_ca_system_score_gemma":0.000026513495,"threshold_uncertainty_score":0.6989978},"labels":[],"label_agreement":null},{"id":"W4406458249","doi":"10.1109/bigdata62323.2024.10825314","title":"Common Pitfalls with Data Deduplication Parameters and Metrics","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Data deduplication; Computer science; Data mining; Database","score_opus":0.0493737158693585,"score_gpt":0.2980830176485887,"score_spread":0.24870930177923017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406458249","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062208907,0.0010277453,0.9895214,0.0015534704,0.000049022798,0.00009579209,0.0000132419855,0.001139489,0.00037895062],"genre_scores_gemma":[0.37700912,0.00010206399,0.62266827,0.00014364164,0.000003262269,0.0000059756903,0.000018883295,0.000004627729,0.000044159955],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992335,0.000008242843,0.00007997454,0.00043915992,0.00012503298,0.000114123286],"domain_scores_gemma":[0.99821526,0.00017697147,0.000019030462,0.0015477366,0.000013495308,0.000027525275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012971157,0.000073866715,0.00007289545,0.00014765968,0.00003620437,0.00025071096,0.001260365,0.000030472233,0.0000011155831],"category_scores_gemma":[0.000056933895,0.000051826137,0.0000044077715,0.0008053476,0.00007097069,0.0014156697,0.0011337418,0.00009356773,0.000020467609],"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":[0.0000014676216,0.00001343588,0.00040528298,0.000022334785,0.00001808019,0.000029324698,0.000045298253,0.00003692784,0.00016014292,0.34759137,0.005278851,0.6463975],"study_design_scores_gemma":[0.00020090859,0.00024016235,0.0012036145,0.000060718266,0.00002783765,0.00017095501,0.00012183378,0.86768293,0.0064334436,0.057905074,0.0654396,0.0005129473],"about_ca_topic_score_codex":0.000027904312,"about_ca_topic_score_gemma":0.000019881534,"teacher_disagreement_score":0.867646,"about_ca_system_score_codex":0.00001999242,"about_ca_system_score_gemma":0.000017996263,"threshold_uncertainty_score":0.24176116},"labels":[],"label_agreement":null},{"id":"W4406659679","doi":"10.1016/b978-0-434-98607-1.50042-x","title":"10.1016/b978-0-434-98607-1.50042-x","year":2000,"lang":"en","type":"book-chapter","venue":"Time to knit","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.011419845601079535,"score_gpt":0.18912394998179818,"score_spread":0.17770410438071865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406659679","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.116841e-8,0.0005046087,0.0032985003,0.00039068641,0.000010763947,0.00041816352,0.0001489127,0.002521667,0.99270666],"genre_scores_gemma":[2.5513998e-7,0.0000026979274,0.020318607,0.000082798695,0.0001480663,0.000032158532,0.00007794507,0.000094569485,0.9792429],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972019,0.000015218841,0.0004542304,0.0011772929,0.00056302367,0.00058831717],"domain_scores_gemma":[0.99637944,0.00011466638,0.00021536944,0.0029636503,0.00013057551,0.00019629765],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014129466,0.000650433,0.00061941205,0.00050085643,0.00013932845,0.00018184916,0.003849448,0.0005269237,0.9580909],"category_scores_gemma":[0.00008603808,0.0006740287,0.0001550325,0.00021703851,0.00017711462,0.00059889053,0.0017251853,0.0006777139,0.9954552],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000132291925,0.000010854729,5.6189775e-10,0.000008158609,0.000027761203,0.000121325495,0.0000058110986,0.00003331498,0.000004409679,0.0035746016,0.1800394,0.81616116],"study_design_scores_gemma":[0.00012801375,0.00018530531,1.5999785e-7,0.00010500727,0.000019979785,0.000056768393,1.5836257e-7,0.00017582986,0.00004954843,0.01130773,0.9872078,0.00076372846],"about_ca_topic_score_codex":0.0000060102934,"about_ca_topic_score_gemma":3.269676e-7,"teacher_disagreement_score":0.8153974,"about_ca_system_score_codex":0.00020059866,"about_ca_system_score_gemma":0.00012026616,"threshold_uncertainty_score":0.9995711},"labels":[],"label_agreement":null},{"id":"W4407554117","doi":"10.1007/978-3-031-81375-7_19","title":"Optimizing B-Trees for Memory-Constrained Flash Embedded Devices","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Computer science; Flash memory; Flash file system; Flash (photography); Parallel computing; Embedded system; Computer hardware; Computer memory; Semiconductor memory; Visual arts","score_opus":0.01789434609431879,"score_gpt":0.2667276773376951,"score_spread":0.2488333312433763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407554117","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011378664,0.00091035716,0.99041945,0.0010638637,0.0017393864,0.0008744155,0.0000444001,0.0009494485,0.003987304],"genre_scores_gemma":[0.0076973997,0.000039142433,0.9899054,0.0011823832,0.00019961843,0.000050422295,0.00001745066,0.000032498607,0.000875686],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99539685,0.000020889554,0.00066626107,0.002247869,0.0007284981,0.00093963864],"domain_scores_gemma":[0.99534464,0.0013084386,0.00042284123,0.0024522932,0.00034982897,0.00012196224],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007056971,0.00074460154,0.00080407533,0.0013923644,0.00040717545,0.00067711715,0.007158524,0.00050067226,0.000009435397],"category_scores_gemma":[0.00050010474,0.00070300745,0.00020175938,0.00087589514,0.001265854,0.0012487948,0.0032266746,0.00080446986,0.000018999906],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000069035145,0.000016794867,0.0000030958884,0.00008428999,0.000021439448,0.000054939228,0.00034519186,0.032967128,0.00023386256,0.057659045,0.00014307348,0.90846425],"study_design_scores_gemma":[0.00060986745,0.00022406159,0.000006856979,0.0009091891,0.000023695744,0.000050021587,0.0000017005449,0.6423836,0.008734115,0.33875343,0.007046033,0.0012574359],"about_ca_topic_score_codex":0.0000056187596,"about_ca_topic_score_gemma":0.00016126911,"teacher_disagreement_score":0.9072068,"about_ca_system_score_codex":0.00036266132,"about_ca_system_score_gemma":0.0008033752,"threshold_uncertainty_score":0.9995421},"labels":[],"label_agreement":null},{"id":"W4407691016","doi":"10.1109/sds64317.2024.10883912","title":"Integrating AEAD Ciphers into Software-Defined-Storage Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Mitacs","keywords":"Computer science; Software; Software engineering; Operating system; Computer security","score_opus":0.014710042276960277,"score_gpt":0.2600876066962813,"score_spread":0.24537756441932101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407691016","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00073205354,0.0027534475,0.9823411,0.0006474998,0.0016445374,0.0001593683,0.0000047148656,0.008714948,0.0030023153],"genre_scores_gemma":[0.37434167,0.00002666892,0.6241156,0.00012521207,0.00006832572,0.00005583977,0.0000065298036,0.00002616742,0.001233987],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998422,0.000031499825,0.00028368135,0.00064021384,0.00028334066,0.00033924045],"domain_scores_gemma":[0.99852675,0.0002654572,0.000048165435,0.0010450379,0.00005210694,0.00006246006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026287846,0.00021554278,0.00020005385,0.0002274738,0.0001204234,0.00065702363,0.0015160685,0.00010788953,0.000017211558],"category_scores_gemma":[0.0003937912,0.00016831512,0.00006131406,0.00088909664,0.000093981755,0.0015311502,0.00084622134,0.00032551895,0.0004545668],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010877222,0.000010768189,0.000031131054,0.00009940638,0.000019977724,0.00017960435,0.00046116867,0.0006963686,0.00077719725,0.8683633,0.011535673,0.117824286],"study_design_scores_gemma":[0.0002477085,0.00034447896,0.00002995093,0.0006314897,0.0000185451,0.00023591016,0.0025979036,0.6278778,0.0030414644,0.11737695,0.2462961,0.0013017392],"about_ca_topic_score_codex":0.00017785127,"about_ca_topic_score_gemma":0.000030025272,"teacher_disagreement_score":0.7509864,"about_ca_system_score_codex":0.0002046935,"about_ca_system_score_gemma":0.00007857275,"threshold_uncertainty_score":0.6863692},"labels":[],"label_agreement":null},{"id":"W4407784031","doi":"10.1109/ispa63168.2024.00068","title":"On-the-Fly Data Layout Conversion for GEMM on AI Accelerators","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Huawei Technologies (Canada)","funders":"","keywords":"Computer science; On the fly; Parallel computing; Computer architecture; Programming language; Computational science; Theoretical computer science; Computer graphics (images); Operating system","score_opus":0.07530892368876543,"score_gpt":0.3249007994447046,"score_spread":0.2495918757559392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407784031","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":[0.0015200047,0.000087392385,0.9774999,0.016681526,0.00075624674,0.000305187,0.00012884015,0.0016473269,0.001373601],"genre_scores_gemma":[0.84954196,0.000055771263,0.13296176,0.013731717,0.00015104382,0.00008624745,0.00015501864,0.000044518783,0.003271938],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99884385,0.000013341928,0.00011500033,0.00061211985,0.000196665,0.00021899589],"domain_scores_gemma":[0.9970791,0.00060183683,0.00002234047,0.0022402245,0.000026732563,0.000029773782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022258557,0.00012754675,0.00009244499,0.0001041348,0.0001293346,0.0002949548,0.0031908061,0.000060417107,0.000046338027],"category_scores_gemma":[0.00023821738,0.000079210964,0.000029180716,0.0003198615,0.00006249819,0.001001646,0.0014264846,0.00019355757,0.00051268126],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003902645,0.0000112997,0.0000017187612,0.000009355923,0.000007762448,0.000010854027,0.000018969953,0.00002785888,0.00007967404,0.622821,0.35584205,0.02116557],"study_design_scores_gemma":[0.00019490528,0.0002846052,0.000008103427,0.00006200951,0.0000067517612,0.000005795674,0.000074371965,0.30043367,0.019520704,0.063816644,0.6153143,0.000278169],"about_ca_topic_score_codex":0.0000051073994,"about_ca_topic_score_gemma":0.0000028719453,"teacher_disagreement_score":0.848022,"about_ca_system_score_codex":0.000047161782,"about_ca_system_score_gemma":0.000046121982,"threshold_uncertainty_score":0.6589652},"labels":[],"label_agreement":null},{"id":"W4408215992","doi":"10.56553/popets-2025-0083","title":"Wave Hello to Privacy: Efficient Mixed-Mode MPC using Wavelet Transforms","year":2025,"lang":"en","type":"article","venue":"Proceedings on Privacy Enhancing Technologies","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mode (computer interface); Wavelet; Computer science; Artificial intelligence; Human–computer interaction","score_opus":0.020004945578862076,"score_gpt":0.2829707917422202,"score_spread":0.2629658461633581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408215992","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":[0.38800243,0.00015999954,0.5944663,0.0056455233,0.00038549164,0.00082037726,0.000009571588,0.009852681,0.00065760984],"genre_scores_gemma":[0.64230424,0.000059479273,0.35708386,0.0002746968,0.000014951568,0.00015003559,0.0000018480254,0.000034094148,0.00007676941],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99527323,0.000010252047,0.00082068733,0.0017989171,0.00069502555,0.0014018954],"domain_scores_gemma":[0.9972838,0.00017858396,0.00029105594,0.0018043603,0.00034176823,0.00010040713],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005496339,0.00073330617,0.0007249973,0.0018835653,0.00054837245,0.00045584355,0.005409378,0.0005297264,0.0000022823801],"category_scores_gemma":[0.0035999685,0.00065339,0.00016971846,0.0038206663,0.00031871602,0.00097290054,0.004673906,0.00096569577,0.000056413977],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007009985,0.0002991008,0.0001365631,0.00031976803,0.00009172895,0.00004101276,0.0014883018,0.00091642776,0.2974426,0.3369276,0.0021039443,0.36016288],"study_design_scores_gemma":[0.0003952912,0.00026846817,0.000050336635,0.00059519627,0.00002089774,0.000028925751,0.0014458968,0.031480983,0.8887467,0.069705024,0.006526513,0.0007357703],"about_ca_topic_score_codex":0.000019072113,"about_ca_topic_score_gemma":0.0000042064175,"teacher_disagreement_score":0.5913041,"about_ca_system_score_codex":0.0008161906,"about_ca_system_score_gemma":0.00015706978,"threshold_uncertainty_score":0.9999718},"labels":[],"label_agreement":null},{"id":"W4408271059","doi":"10.1007/s11227-025-07078-0","title":"A survey of SSD simulators and emulators","year":2025,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Springboard (Canada)","funders":"","keywords":"Computer science; Data science","score_opus":0.020345641292385357,"score_gpt":0.2800162098649732,"score_spread":0.25967056857258786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408271059","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":[0.6344187,0.0010389565,0.36411,0.00018891883,0.0001512487,0.00003391142,0.000001154726,0.00002766681,0.000029400697],"genre_scores_gemma":[0.9789257,0.000049636514,0.020942058,0.0000618177,0.000011872658,6.18108e-8,1.5893941e-7,0.0000037827967,0.000004884471],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99897385,0.00014383478,0.00044065362,0.00009993082,0.00018694793,0.00015481235],"domain_scores_gemma":[0.9980727,0.001078864,0.00022379255,0.0003880431,0.00020952948,0.000027087219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017601545,0.000095154326,0.0002483834,0.00020842519,0.00010498839,0.000031106487,0.0011537964,0.000043865417,6.948944e-7],"category_scores_gemma":[0.0006892936,0.00006230967,0.00003555562,0.0006585353,0.00014573199,0.00040998912,0.00071865646,0.0002535614,4.6504132e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010022016,0.00018625302,0.29713094,0.00017357909,0.00039192144,0.000056419438,0.005654733,0.061924275,0.009054384,0.04550901,0.0012568495,0.5785614],"study_design_scores_gemma":[0.0017573241,0.00046759567,0.58151895,0.00075609493,0.00008656273,0.00028381436,0.0016995219,0.36510512,0.018827092,0.028411884,0.0005913166,0.00049471937],"about_ca_topic_score_codex":0.00007070588,"about_ca_topic_score_gemma":0.000008363682,"teacher_disagreement_score":0.5780667,"about_ca_system_score_codex":0.000028008202,"about_ca_system_score_gemma":0.00006587365,"threshold_uncertainty_score":0.25409144},"labels":[],"label_agreement":null},{"id":"W4408712562","doi":"10.1007/978-3-031-85634-1_13","title":"Storage Benchmarks","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science","score_opus":0.012947991216128671,"score_gpt":0.2348564545197409,"score_spread":0.22190846330361225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408712562","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.8875549e-8,0.000508672,0.45671389,0.00034690494,0.00030222163,0.00009699283,0.000018360264,0.0008166612,0.5411963],"genre_scores_gemma":[0.00003625929,0.00018060522,0.19733483,0.00036304293,0.00003102599,0.0000073887422,0.000052325126,0.000012366345,0.80198216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985196,0.0000043625023,0.00024430663,0.0007215012,0.00026668445,0.00024353266],"domain_scores_gemma":[0.99738115,0.000102039325,0.00013234124,0.0022715714,0.000068303176,0.000044567838],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007903675,0.00033276362,0.00032462308,0.00033199263,0.00007524146,0.00009344725,0.002755111,0.00041880328,0.00059128995],"category_scores_gemma":[0.000053750395,0.00030755662,0.000102968566,0.00007191575,0.00011003103,0.00040912686,0.002329227,0.000525646,0.00024917565],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.8892185e-7,0.0000023098899,1.323573e-7,0.00001030871,0.000013538759,0.000057474266,0.0000042022552,0.0000034105678,0.000002384812,0.7907382,0.11418401,0.094983645],"study_design_scores_gemma":[0.000044908094,0.000020452866,6.624566e-7,0.000049623843,0.0000056009417,0.0000056288386,0.000001429757,0.000483784,0.00003979432,0.31887826,0.6802073,0.00026250846],"about_ca_topic_score_codex":0.000005995315,"about_ca_topic_score_gemma":0.000017791252,"teacher_disagreement_score":0.56602335,"about_ca_system_score_codex":0.00012908455,"about_ca_system_score_gemma":0.000119441946,"threshold_uncertainty_score":0.99993765},"labels":[],"label_agreement":null},{"id":"W4408794007","doi":"10.3390/computers14040118","title":"Enhancing CuFP Library with Self-Alignment Technique","year":2025,"lang":"en","type":"article","venue":"Computers","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science","score_opus":0.0050622158758464025,"score_gpt":0.2157861283041501,"score_spread":0.21072391242830368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408794007","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008424924,0.0001359687,0.9908278,0.0015477758,0.00028142973,0.00031930974,0.0000016249851,0.0040549324,0.001988679],"genre_scores_gemma":[0.08154512,0.000022933522,0.9172533,0.0009332377,0.000017003566,0.00007097871,0.0000034415953,0.000010771421,0.00014320832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99886024,0.000028257296,0.00017809488,0.0004905349,0.0001553239,0.00028757224],"domain_scores_gemma":[0.9986974,0.00009969306,0.000068716414,0.001070691,0.000019863077,0.000043658154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008020435,0.00017611275,0.00017240412,0.00024049239,0.00011031646,0.00015185258,0.0017091824,0.00006837577,0.0000022541103],"category_scores_gemma":[0.000008817769,0.000150901,0.000031735268,0.0007969851,0.0000625049,0.0010150106,0.001444811,0.00017381493,0.000016793389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020301015,0.00024741158,0.0010524999,0.0001932158,0.00016328396,0.00040529278,0.0005771728,0.0010351831,0.009445241,0.77209306,0.03848201,0.1762853],"study_design_scores_gemma":[0.0009029219,0.00040402706,0.0006900662,0.0007202469,0.000021710532,0.00009568863,0.000109148124,0.020531999,0.76190454,0.05195403,0.16168769,0.0009779292],"about_ca_topic_score_codex":0.0000018678123,"about_ca_topic_score_gemma":7.7018586e-7,"teacher_disagreement_score":0.7524593,"about_ca_system_score_codex":0.000081982005,"about_ca_system_score_gemma":0.00010370002,"threshold_uncertainty_score":0.61535645},"labels":[],"label_agreement":null},{"id":"W4409103355","doi":"10.1109/iccc62609.2024.10941747","title":"Investigations on Disk Performance Indices and Their Statistical Learning for Storage Cluster Disk Fail-Slow Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Cluster (spacecraft); Hard disk drive performance characteristics; Storage management; Disk array; Operating system","score_opus":0.015760286840048772,"score_gpt":0.2518743567673784,"score_spread":0.23611406992732964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409103355","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":[0.10540266,0.0000945088,0.89232224,0.0006460093,0.00018617367,0.00020779023,0.000025428119,0.0009810281,0.00013414038],"genre_scores_gemma":[0.92468023,0.000034998986,0.07481523,0.00010078198,0.000031540072,0.000078952726,0.000015900412,0.000012029555,0.00023032875],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990735,0.000029275041,0.00014363982,0.00042715986,0.00011348403,0.00021291654],"domain_scores_gemma":[0.9990124,0.0005967389,0.000036814236,0.00027772156,0.000022165632,0.00005412147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017832742,0.00014335079,0.00010908162,0.0001646027,0.00027659044,0.00030434618,0.00030023436,0.000066979694,0.0000040564223],"category_scores_gemma":[0.00025508716,0.00010392637,0.000020217298,0.0002747909,0.00015393591,0.0011300297,0.00024535693,0.00027547686,0.000021036469],"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":[0.000014018702,0.000019458004,0.0005176333,0.0001656712,0.000027451639,0.0000050792696,0.0015758256,0.0036135376,0.00097187393,0.116736054,0.000736291,0.8756171],"study_design_scores_gemma":[0.00013737066,0.00037886275,0.0012159119,0.000053863998,0.0000059624595,0.000008373902,0.00039539326,0.9630623,0.0058265375,0.017464632,0.011248983,0.00020180849],"about_ca_topic_score_codex":0.00000582956,"about_ca_topic_score_gemma":0.000031599404,"teacher_disagreement_score":0.95944875,"about_ca_system_score_codex":0.0000540944,"about_ca_system_score_gemma":0.000023950053,"threshold_uncertainty_score":0.42379946},"labels":[],"label_agreement":null},{"id":"W4409327205","doi":"10.1109/tpwrd.2025.3559001","title":"Comparative Analysis of Negative Sequence Behavior in Grid-Following and Grid-Forming Inverters: Modeling, Control, and Protection","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Grid; Sequence (biology); Control (management); Power grid; Computer science; Engineering; Electronic engineering; Control theory (sociology); Power (physics); Mathematics; Physics; Artificial intelligence; Chemistry","score_opus":0.03217131268629107,"score_gpt":0.28609457686866063,"score_spread":0.25392326418236955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409327205","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":[0.36709788,0.000084530235,0.6321333,0.000059267866,0.0002050677,0.0002731218,0.00004393264,0.00008587014,0.000017032853],"genre_scores_gemma":[0.9904576,0.000059657545,0.009277757,0.00007427765,0.0000021931323,0.00011380255,0.0000013937558,0.0000038314606,0.000009494585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998788,0.0000643018,0.0003282143,0.00046298135,0.00016659482,0.00018990743],"domain_scores_gemma":[0.9992919,0.00013896814,0.00009393573,0.0003599323,0.00007985097,0.000035408913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015753078,0.00017989629,0.0004177196,0.0011694576,0.00014528267,0.00005020671,0.0002656176,0.00009942766,0.0000015216765],"category_scores_gemma":[0.00001273366,0.00018139835,0.00009418395,0.001557045,0.0001395791,0.0012065074,0.0000125000715,0.0002893299,6.4337934e-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":[0.0006824618,0.0010686772,0.0020097024,0.00013659381,0.0035639263,0.00016741577,0.0147205,0.7421979,0.10407494,0.002329267,0.00004835531,0.12900028],"study_design_scores_gemma":[0.0008327077,0.00017173437,0.0009222205,0.000098100936,0.00035039123,0.000003783844,0.0009178621,0.98366547,0.012405248,0.00040556546,0.000008125695,0.00021876956],"about_ca_topic_score_codex":0.0004658958,"about_ca_topic_score_gemma":0.00043642483,"teacher_disagreement_score":0.6233597,"about_ca_system_score_codex":0.00012671015,"about_ca_system_score_gemma":0.000048254034,"threshold_uncertainty_score":0.739721},"labels":[],"label_agreement":null},{"id":"W4409601530","doi":"10.1007/s00521-025-11164-y","title":"Self-evaluation of LLMs on challenging LLM-generated STEM MCQs","year":2025,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computational Science and Engineering; Computer science; Mathematics education; Psychology; Machine learning","score_opus":0.039044504548228706,"score_gpt":0.31347785788458293,"score_spread":0.2744333533363542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409601530","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":[0.102974206,0.0005305927,0.89264965,0.001112759,0.00007969496,0.00042898313,0.0000040187338,0.0007965673,0.0014235443],"genre_scores_gemma":[0.9772828,0.000021082784,0.022529945,0.00007803909,0.000017861228,0.000039886996,0.0000047119697,0.0000035791877,0.000022054968],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917346,0.000044277207,0.00017743032,0.00031339872,0.00016747262,0.00012397031],"domain_scores_gemma":[0.9991445,0.00012619157,0.00009474398,0.0004830467,0.00013295258,0.00001855918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025104923,0.00009028115,0.00011055132,0.00012901193,0.00021912901,0.000039349397,0.0003961862,0.000041882347,2.4597733e-7],"category_scores_gemma":[0.000020468147,0.00008683679,0.000018383433,0.0005512979,0.00003712614,0.00009996772,0.0002472427,0.0001153241,0.0000024561298],"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":[0.0000010383698,0.000077703946,0.00006519693,0.000033316308,0.000012900282,2.593556e-7,0.000113342416,0.018316654,0.0013950508,0.3167767,0.0001280783,0.66307974],"study_design_scores_gemma":[0.00020991357,0.0000354884,0.00042099194,0.000027355763,0.000013577387,0.0000022909132,0.00006779569,0.984292,0.0073976703,0.0056724646,0.0017683551,0.000092107664],"about_ca_topic_score_codex":0.000001944405,"about_ca_topic_score_gemma":6.965178e-7,"teacher_disagreement_score":0.96597534,"about_ca_system_score_codex":0.000035234432,"about_ca_system_score_gemma":0.000025459047,"threshold_uncertainty_score":0.35411018},"labels":[],"label_agreement":null},{"id":"W4409659987","doi":"10.1109/lascas64004.2025.10966299","title":"Toward Full GPU Acceleration of Agile Homomorphic Encryption Frameworks","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Homomorphic encryption; Computer science; Agile software development; Acceleration; Encryption; Embedded system; Operating system; Software engineering; Physics","score_opus":0.02329352143083399,"score_gpt":0.27265034797017673,"score_spread":0.24935682653934274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409659987","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":[0.007865643,0.00013445114,0.98627985,0.001989862,0.00025903076,0.00012778454,0.0000022524553,0.0009112287,0.0024299219],"genre_scores_gemma":[0.69892615,0.00004207764,0.3006545,0.00020850799,0.000008222714,0.000014133386,0.000003646633,0.0000030881688,0.00013966224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992166,0.00001820314,0.00020683231,0.00027168525,0.00014309112,0.0001435562],"domain_scores_gemma":[0.9990052,0.000077041004,0.000080450525,0.0007208982,0.00010044561,0.000015953816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010746543,0.000090384536,0.00013043398,0.0001824732,0.000050562223,0.00005823416,0.00086897827,0.00019683962,0.000034067707],"category_scores_gemma":[0.00016719852,0.00008262122,0.000032254375,0.0006550225,0.00006912226,0.0007628837,0.0004614021,0.0002470035,0.00003491481],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005186797,0.0000414691,0.00009556856,0.000021719343,0.000009223947,0.000003658512,0.000094092626,0.00033045394,0.016294619,0.8423625,0.0032212038,0.13752027],"study_design_scores_gemma":[0.0005579098,0.00024396834,0.0020382744,0.00013188939,0.0000140773645,0.0000115857765,0.0002825762,0.08957591,0.26801407,0.62945074,0.009258321,0.0004207008],"about_ca_topic_score_codex":0.000012586292,"about_ca_topic_score_gemma":0.000007299975,"teacher_disagreement_score":0.69106054,"about_ca_system_score_codex":0.000043261476,"about_ca_system_score_gemma":0.000041598312,"threshold_uncertainty_score":0.33691955},"labels":[],"label_agreement":null},{"id":"W4411374363","doi":"10.1145/3722212.3725097","title":"Demonstrating CatDB: LLM-based Generation of Data-centric ML Pipelines","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Pipeline transport; Engineering; Mechanical engineering","score_opus":0.07181776484659808,"score_gpt":0.32112082897441263,"score_spread":0.24930306412781456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411374363","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030009649,0.0002533514,0.9942184,0.0009936283,0.0001595191,0.000109420565,0.00001781623,0.00045974518,0.00078711606],"genre_scores_gemma":[0.39661592,0.000008783666,0.6030495,0.00017394156,0.000015002217,0.000003968627,0.000048265094,0.000002167921,0.00008242132],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990388,0.000023161148,0.00026641355,0.00038239802,0.00014148722,0.00014769998],"domain_scores_gemma":[0.99817353,0.00010841339,0.0000986655,0.001516261,0.00008736479,0.000015745567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018842085,0.000090948655,0.0001236371,0.00018539431,0.000071606395,0.000050528164,0.0016708515,0.000052168416,0.000005140256],"category_scores_gemma":[0.00033704165,0.00007915505,0.000016463067,0.000815113,0.000059244354,0.0008670642,0.0006923967,0.00007572322,0.0000059397676],"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":[0.0000029769933,0.00015651788,0.0014319059,0.000050749004,0.000016665963,0.000009392814,0.000020399877,0.0034580668,0.033284847,0.23842697,0.015598758,0.7075428],"study_design_scores_gemma":[0.00020010034,0.000021842281,0.00010262609,0.000015675083,0.0000059867953,0.0000011748986,0.000024865809,0.8813522,0.11432926,0.0019284937,0.0019173229,0.00010043922],"about_ca_topic_score_codex":0.000034996687,"about_ca_topic_score_gemma":0.00005790888,"teacher_disagreement_score":0.87789416,"about_ca_system_score_codex":0.000024905838,"about_ca_system_score_gemma":0.0001424779,"threshold_uncertainty_score":0.3227849},"labels":[],"label_agreement":null},{"id":"W4411447237","doi":"10.1109/ids66066.2025.00011","title":"Enhancing Developer Productivity: Benchmarking LLM-Powered Tools like GitHub Copilot and TabNine in Real-Time Coding Environments","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Benchmarking; Coding (social sciences); Computer science; Productivity; Software engineering; Embedded system; Business","score_opus":0.01666522638890612,"score_gpt":0.24943462558733873,"score_spread":0.2327693991984326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411447237","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":[0.15273455,0.00021733962,0.8402329,0.00096145825,0.00030191793,0.00054146873,0.0000053858844,0.0006017413,0.0044032224],"genre_scores_gemma":[0.56095487,0.00029741414,0.43620095,0.00021191749,0.00002025229,0.000050307663,0.000010940995,0.0000132690375,0.0022401125],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998225,0.00004311939,0.00031940176,0.000810983,0.00019877126,0.0004027303],"domain_scores_gemma":[0.9988965,0.00018765758,0.00008613886,0.00077388843,0.00001641017,0.000039444865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004130981,0.00021326166,0.00028620622,0.0003006641,0.00013390977,0.00016345219,0.00065669086,0.00008300781,0.000021072281],"category_scores_gemma":[0.00029856633,0.00020452848,0.000016246162,0.0006775977,0.00011140391,0.0015704063,0.0016544713,0.00019385693,0.000020775069],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029834217,0.00023615792,0.00701515,0.00009382304,0.000052837655,0.00010218158,0.00072095875,0.00011921008,0.56179106,0.03610493,0.0011529503,0.39258093],"study_design_scores_gemma":[0.0031252103,0.0005103094,0.092706285,0.0011801198,0.00003386032,0.00007578411,0.00054506847,0.01958272,0.8151754,0.015094615,0.049476143,0.0024944434],"about_ca_topic_score_codex":0.000038322472,"about_ca_topic_score_gemma":0.000065282504,"teacher_disagreement_score":0.4082203,"about_ca_system_score_codex":0.00019066759,"about_ca_system_score_gemma":0.000067856796,"threshold_uncertainty_score":0.83404297},"labels":[],"label_agreement":null},{"id":"W4411552880","doi":"10.1109/icse55347.2025.00238","title":"Dockerfile Flakiness: Characterization and Repair","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Characterization (materials science); Computer science; Materials science; Nanotechnology","score_opus":0.007550024644114766,"score_gpt":0.24088453036582322,"score_spread":0.23333450572170844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411552880","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008570493,0.000041921503,0.9854962,0.0020753876,0.00014083483,0.000065827895,0.0000026434195,0.0017745724,0.0018320661],"genre_scores_gemma":[0.455815,0.00006930431,0.52930397,0.0014372282,0.000017621533,0.000037751586,0.00002305644,0.000005158318,0.013290947],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995614,0.000006693422,0.00008019307,0.00021855775,0.000047081783,0.000086027605],"domain_scores_gemma":[0.9994685,0.000023439903,0.000022115199,0.00044747483,0.00002804062,0.000010421749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045772216,0.000053129625,0.000060274902,0.00008763869,0.000052493768,0.000045879086,0.0002949285,0.000032346685,0.0000073087604],"category_scores_gemma":[0.000071360904,0.00004555841,0.0000097239445,0.00034899253,0.000033821667,0.0006017353,0.00047331624,0.000040115203,0.000010513805],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013507159,0.000010167086,0.0010194116,0.000015622501,0.0000057704433,0.000006227084,0.000025725247,0.0000017999937,0.010423255,0.7642397,0.0032430317,0.22100788],"study_design_scores_gemma":[0.00046808238,0.000062336105,0.061935205,0.000057136207,0.0000075028574,0.00001751656,0.000051245912,0.100699164,0.047584474,0.04925489,0.7394501,0.00041235995],"about_ca_topic_score_codex":0.000003068061,"about_ca_topic_score_gemma":0.0000024791327,"teacher_disagreement_score":0.73620707,"about_ca_system_score_codex":0.000012091971,"about_ca_system_score_gemma":0.0000130594535,"threshold_uncertainty_score":0.1857818},"labels":[],"label_agreement":null},{"id":"W4412554211","doi":"10.1145/3747846","title":"Ephemera: Accelerating I/O-Intensive Serverless Workloads with a Harvested In-memory File System","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Architecture and Code Optimization","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Computer science; Operating system; Ephemera; Parallel computing; File system; Embedded system","score_opus":0.011059805654790627,"score_gpt":0.2272247325624125,"score_spread":0.21616492690762187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412554211","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001695283,0.00008467907,0.99536765,0.0015288122,0.00007812707,0.000323061,0.00006415769,0.00050779304,0.0003504231],"genre_scores_gemma":[0.3299207,0.000035737048,0.6691214,0.000497608,0.0000065918966,0.00014821679,0.00003483338,0.000013833903,0.00022110937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892104,0.000052780604,0.00021196538,0.00046868643,0.0001325341,0.00021300954],"domain_scores_gemma":[0.9988381,0.00019959352,0.00007600174,0.00072793965,0.0001239019,0.000034420475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006264341,0.00019198873,0.0002014963,0.00036985887,0.00024253778,0.00013754399,0.0005381977,0.000099854784,0.000015008849],"category_scores_gemma":[0.00006232771,0.00016460282,0.00002686023,0.0010833509,0.00006947788,0.0004417076,0.00004418484,0.00034192894,0.0000017037567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041284133,0.000027196482,0.000020337922,0.000042412237,0.000021332142,0.000015642117,0.00032569325,0.8647129,0.000055364762,0.0007662147,0.000041187184,0.13393043],"study_design_scores_gemma":[0.0019538212,0.00030493902,0.00079756696,0.0014719282,0.000048494938,0.00011852365,0.0025034186,0.98547465,0.004789985,0.0014322492,0.00046809466,0.0006363592],"about_ca_topic_score_codex":0.000024441171,"about_ca_topic_score_gemma":0.00040512058,"teacher_disagreement_score":0.32822543,"about_ca_system_score_codex":0.000078345,"about_ca_system_score_gemma":0.00005689388,"threshold_uncertainty_score":0.67123085},"labels":[],"label_agreement":null},{"id":"W4412819474","doi":"10.1007/978-3-031-89033-8_31","title":"Profiling Serial and Shared-Memory Code","year":2025,"lang":"en","type":"book-chapter","venue":"CMS/CAIMS books in mathematics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Profiling (computer programming); Parallel computing; Programming language","score_opus":0.028355416838752288,"score_gpt":0.26427460522479734,"score_spread":0.23591918838604506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412819474","genre_codex":"other","genre_gemma":"methods","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":[0.0000774681,0.0017681567,0.39659038,0.00026687226,0.0008789577,0.0014091254,0.00027595804,0.0015532331,0.59717983],"genre_scores_gemma":[0.0000836975,0.00026473813,0.72470117,0.00013330283,0.00009277418,0.00006740632,0.000037950183,0.000070880706,0.2745481],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976665,0.000012468817,0.0007180404,0.00083424273,0.0003692881,0.00039950074],"domain_scores_gemma":[0.9972726,0.00031546288,0.00039022334,0.0018712268,0.00008470539,0.000065748594],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034261553,0.0005358291,0.0007511136,0.00044320239,0.00010614847,0.00021693022,0.0018711959,0.0005603243,0.000019996294],"category_scores_gemma":[0.00029676806,0.0005386275,0.00008528462,0.00008179094,0.00028149207,0.0004233503,0.0023484265,0.0008010288,0.000048490165],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035674632,0.000019543679,0.000001964993,0.0006139395,0.000027077847,0.00012580513,0.0003482686,0.000019079615,0.00009182626,0.9826692,0.0022446702,0.013835064],"study_design_scores_gemma":[0.000394181,0.0000540779,0.0000010299469,0.0015361093,0.000030714247,0.000051684554,0.000077951765,0.009358248,0.000993438,0.96725094,0.019540858,0.0007107847],"about_ca_topic_score_codex":0.0000013751112,"about_ca_topic_score_gemma":0.000016638967,"teacher_disagreement_score":0.32811075,"about_ca_system_score_codex":0.00017600245,"about_ca_system_score_gemma":0.00017263938,"threshold_uncertainty_score":0.9997065},"labels":[],"label_agreement":null},{"id":"W4413157092","doi":"10.1109/cvpr52734.2025.02503","title":"EventSplat: 3D Gaussian Splatting from Moving Event Cameras for Real-time Rendering","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Rendering (computer graphics); Computer graphics (images); Real-time rendering; Computer vision; Artificial intelligence; Gaussian","score_opus":0.012661944229186699,"score_gpt":0.2779449975726708,"score_spread":0.2652830533434841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413157092","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007914797,0.000097305936,0.98568463,0.0007984423,0.0003070291,0.00027229424,0.000021915686,0.0014207872,0.0034828018],"genre_scores_gemma":[0.12213194,0.000024150944,0.87525743,0.00018008424,0.000037358714,0.000054780678,0.000021133077,0.000014068474,0.0022790637],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983968,0.000020005677,0.00033505884,0.00065505406,0.00017220799,0.0004208847],"domain_scores_gemma":[0.998388,0.00033662232,0.00012448052,0.001065231,0.000039486687,0.000046162964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020692077,0.00019661033,0.0002398269,0.00018372442,0.00022902168,0.00012068132,0.0012534045,0.00010055052,0.000027806433],"category_scores_gemma":[0.00023621856,0.00018849211,0.000070535774,0.0003964175,0.000038651917,0.0007464066,0.0010794727,0.00014667008,0.000038351267],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002767659,0.0001007118,0.001283275,0.000086312415,0.00016934024,0.00005924837,0.0005371963,0.0025782608,0.0682338,0.15819281,0.0054250173,0.7633064],"study_design_scores_gemma":[0.0018110332,0.00015599727,0.0042362246,0.00070210674,0.000060493527,0.000014255893,0.0006189599,0.7225244,0.11468034,0.139049,0.0147650605,0.0013821259],"about_ca_topic_score_codex":0.00038323097,"about_ca_topic_score_gemma":0.00004974364,"teacher_disagreement_score":0.7619242,"about_ca_system_score_codex":0.00016081735,"about_ca_system_score_gemma":0.00006577271,"threshold_uncertainty_score":0.7686485},"labels":[],"label_agreement":null},{"id":"W4413325977","doi":"10.1016/j.ijpharm.2025.126087","title":"Grid-induced aerosol optimization in pMDIs: A multiscale design, simulation, and experimental study","year":2025,"lang":"en","type":"article","venue":"International Journal of Pharmaceutics","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aerosol; Computer science; Chemistry; Organic chemistry","score_opus":0.06918033424051352,"score_gpt":0.418507736154469,"score_spread":0.3493274019139555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413325977","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":[0.11256434,0.00028367038,0.88550264,0.00050599826,0.00089318375,0.00018986771,0.0000022757895,0.000037956783,0.00002005744],"genre_scores_gemma":[0.8825296,0.000030761865,0.1172298,0.0001512074,0.000039821138,0.0000052646146,7.6100673e-7,0.0000041298213,0.000008623598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989329,0.000074828415,0.00041025085,0.0001590106,0.00031982482,0.00010318575],"domain_scores_gemma":[0.9991582,0.00018772446,0.00021865743,0.00013414727,0.00026791164,0.00003334974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029644606,0.000100295496,0.00013130199,0.0003923295,0.000037487527,0.00010965398,0.00081352436,0.000038157294,0.00000489904],"category_scores_gemma":[0.00019568056,0.0000962729,0.000024227907,0.0002513308,0.00003081671,0.00092029554,0.00034787005,0.00019725229,8.5237104e-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":[0.00007184762,0.0005380585,0.0018652715,0.0000020486423,0.00006442491,0.00010752042,0.00073930045,0.98018694,0.007557866,0.0002600481,0.000033071028,0.008573611],"study_design_scores_gemma":[0.0021490073,0.00013194574,0.0002637607,0.000037855643,0.000008965849,0.000024273553,0.00048288974,0.9267776,0.06961922,0.00029713978,0.000117469484,0.0000898599],"about_ca_topic_score_codex":0.000003324762,"about_ca_topic_score_gemma":0.000001656955,"teacher_disagreement_score":0.7699653,"about_ca_system_score_codex":0.00017315509,"about_ca_system_score_gemma":0.000060068156,"threshold_uncertainty_score":0.3925895},"labels":[],"label_agreement":null},{"id":"W4413332477","doi":"10.1016/j.procs.2025.07.168","title":"Adaptive and Efficient Data Retrieval in Distributed File Systems: A Metadata-Driven Approach","year":2025,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Metadata; Information retrieval; Metadata repository; Data retrieval; Database; World Wide Web","score_opus":0.02986117336548021,"score_gpt":0.2653796244883331,"score_spread":0.23551845112285286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413332477","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020031235,0.0005762453,0.9950334,0.00021619395,0.0004222693,0.0005523416,0.00059942965,0.00047670415,0.0001203072],"genre_scores_gemma":[0.3754808,0.000018547218,0.62418693,0.00008680678,0.00002717819,0.000040958024,0.00013404762,0.000005964147,0.000018789004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965533,0.000051640454,0.00038578187,0.00180012,0.0005977928,0.00061134493],"domain_scores_gemma":[0.9968295,0.00027806783,0.00015132943,0.0024376868,0.00019327499,0.00011015894],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0009836634,0.0002495775,0.0003489322,0.0006030481,0.00025795482,0.0008397444,0.007034309,0.00007877903,8.3117374e-7],"category_scores_gemma":[0.000655978,0.00022128849,0.000017525492,0.004797503,0.00081197644,0.0031627577,0.010657577,0.00031123476,0.000005414456],"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":[0.00011047198,0.0011232181,0.0014427704,0.0006400964,0.00010224245,0.00022733453,0.0018215864,0.15711191,0.000872724,0.68829286,0.022671372,0.12558338],"study_design_scores_gemma":[0.00026997612,0.000049003986,0.0013935582,0.00008901095,0.000005326127,0.000030729007,0.00006831475,0.9960685,0.00015467883,0.00079989625,0.0008398449,0.00023120278],"about_ca_topic_score_codex":0.000026571366,"about_ca_topic_score_gemma":0.0000036574636,"teacher_disagreement_score":0.83895653,"about_ca_system_score_codex":0.00018966744,"about_ca_system_score_gemma":0.00050314737,"threshold_uncertainty_score":0.9983381},"labels":[],"label_agreement":null},{"id":"W4413948809","doi":"10.14778/3746405.3746414","title":"KEIGO: Co-Designing Log-Structured Merge Key-Value Stores with a Non-Volatile, Concurrency-Aware Storage Hierarchy","year":2025,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Merge (version control); Computer science; Concurrency; Hierarchy; Memory hierarchy; Database; Key (lock); Parallel computing; Distributed computing; Operating system","score_opus":0.007952278613537941,"score_gpt":0.24574192578378504,"score_spread":0.2377896471702471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413948809","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":[0.22307724,0.00139244,0.7554803,0.0029578505,0.0014169936,0.0034307593,0.00013697792,0.0017961223,0.010311316],"genre_scores_gemma":[0.92327076,0.000038607803,0.07605485,0.00015976105,0.00002768936,0.00014200478,0.000003791472,0.000021277574,0.000281237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976063,0.000016953514,0.00044272127,0.00074491533,0.0006511481,0.00053797587],"domain_scores_gemma":[0.99841887,0.00010190973,0.00047907347,0.00067536504,0.0002503927,0.00007438775],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030074976,0.00039413638,0.00045732426,0.00032100428,0.00032411583,0.00014002107,0.0031728817,0.00012328579,0.00000798549],"category_scores_gemma":[0.00017443494,0.00026619426,0.00010838229,0.001144941,0.00037865213,0.00085087353,0.0013918384,0.00046848325,0.000003627804],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030435048,0.00039567632,0.020591099,0.0011193365,0.00067883043,0.000028993167,0.0068934183,0.0016766558,0.27733722,0.6154674,0.037106663,0.038400307],"study_design_scores_gemma":[0.0026192742,0.0006225953,0.0054391404,0.0010457532,0.0001226952,0.00004148274,0.0014652747,0.016396925,0.91251945,0.0513282,0.007430007,0.00096917764],"about_ca_topic_score_codex":0.00003971156,"about_ca_topic_score_gemma":0.0000057066845,"teacher_disagreement_score":0.7001935,"about_ca_system_score_codex":0.00026585377,"about_ca_system_score_gemma":0.00018446006,"threshold_uncertainty_score":0.999979},"labels":[],"label_agreement":null},{"id":"W4413980865","doi":"10.14778/3749646.3749703","title":"Sphinx: A Succinct Perfect Hash Index for x86","year":2025,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Hash function; Sphinx; Index (typography); Computer science; x86; Computer security; History; World Wide Web; Programming language; Archaeology","score_opus":0.00943147209938856,"score_gpt":0.24889599828362524,"score_spread":0.2394645261842367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413980865","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":[0.115346074,0.0016192547,0.84424096,0.020316016,0.0015890016,0.0038830421,0.00004205764,0.0015642451,0.011399334],"genre_scores_gemma":[0.943225,0.000044467633,0.05570468,0.0002750294,0.000021305364,0.00022445942,5.613011e-7,0.000008758868,0.0004957422],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988083,0.0000027459523,0.00024905024,0.00039959766,0.00024059454,0.00029970007],"domain_scores_gemma":[0.9991348,0.000082786886,0.00018584654,0.00039746807,0.00017396908,0.000025158051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002793213,0.00016475917,0.00021352035,0.00015471765,0.00016403265,0.00008834212,0.0024010371,0.000065157445,0.0000022991144],"category_scores_gemma":[0.0002894661,0.0001150882,0.00011645189,0.0006127405,0.00010587995,0.00045568636,0.00158024,0.00014457945,0.0000028246727],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050538794,0.00015593051,0.005116499,0.00027982294,0.0000859753,5.953367e-7,0.00033007917,0.00005520607,0.0463079,0.8429737,0.027036887,0.07760687],"study_design_scores_gemma":[0.0015134983,0.0002197455,0.0029140145,0.00025841765,0.00003144387,0.000010043909,0.0002472492,0.0056827553,0.6688647,0.25731587,0.06261017,0.0003320718],"about_ca_topic_score_codex":0.00001304193,"about_ca_topic_score_gemma":0.0000021524904,"teacher_disagreement_score":0.8278789,"about_ca_system_score_codex":0.0001286948,"about_ca_system_score_gemma":0.00004140823,"threshold_uncertainty_score":0.46931607},"labels":[],"label_agreement":null},{"id":"W4414031888","doi":"10.1101/2025.09.05.674540","title":"Deep-mutational scanning libraries using tiled-region exchange mutagenesis","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Mutagenesis; Genetics; Biology; Mutation; Computer science; Computational biology; Gene","score_opus":0.027412833470459523,"score_gpt":0.24271040830628532,"score_spread":0.2152975748358258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414031888","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03681857,0.0042832685,0.9529816,0.0003655833,0.001798888,0.00061267527,0.00013853137,0.0029826316,0.000018241006],"genre_scores_gemma":[0.4866361,0.00017057222,0.51232,0.00029541412,0.0002741844,0.00021403344,9.748904e-7,0.00007576733,0.000012987338],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99610275,0.00014213476,0.0006327053,0.0017555549,0.000586844,0.0007800398],"domain_scores_gemma":[0.9957015,0.00018567988,0.00063710916,0.0028236068,0.00047278483,0.00017935382],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033650358,0.00075344305,0.0006771819,0.00094341795,0.00044478776,0.00081333093,0.0031846098,0.0007090986,0.000013721074],"category_scores_gemma":[0.00044707395,0.0008741254,0.00017805138,0.0015544577,0.00028908305,0.001629912,0.0052644294,0.0008288738,0.000026395272],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018934334,0.0012860949,0.01926319,0.009006737,0.002429697,0.0062329713,0.00073460623,0.08922919,0.34995696,0.5129656,0.0068291053,0.0018764432],"study_design_scores_gemma":[0.0017403794,0.00014438266,0.025650436,0.0036937257,0.00043267192,8.569799e-7,0.000040332056,0.45793906,0.4845694,0.0012975299,0.018166326,0.006324891],"about_ca_topic_score_codex":0.000039670784,"about_ca_topic_score_gemma":0.0000018912955,"teacher_disagreement_score":0.51166815,"about_ca_system_score_codex":0.0005345446,"about_ca_system_score_gemma":0.0011325338,"threshold_uncertainty_score":0.99937093},"labels":[],"label_agreement":null},{"id":"W4414688264","doi":"10.1145/3766882.3767172","title":"Bridging Natural Resilience and Cost-Effectiveness in SSDs for Containerized ML Applications","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Bridging (networking); Resilience (materials science); Quality of service; Set (abstract data type); Reliability (semiconductor); Latency (audio); Container (type theory); Key (lock)","score_opus":0.013640216556981949,"score_gpt":0.3165466773021112,"score_spread":0.3029064607451293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414688264","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":[0.005204111,0.00029408926,0.9919421,0.0007147751,0.000058267695,0.0011455086,0.000004061592,0.00033455755,0.0003025109],"genre_scores_gemma":[0.84843445,0.000013768336,0.15020674,0.00015661953,0.0000038148755,0.0010312847,0.0000051345214,0.0000024674325,0.00014574373],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992939,0.000020496753,0.00011243606,0.0003514692,0.00005055498,0.00017109505],"domain_scores_gemma":[0.9990992,0.0004060583,0.000028268136,0.00040779824,0.00004439246,0.0000142941235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020013314,0.00007817138,0.00012539144,0.00014589168,0.00008408306,0.000054807122,0.00053321663,0.000035147594,2.4842785e-7],"category_scores_gemma":[0.00020730247,0.0000709244,0.000013728163,0.0005282396,0.00008645099,0.00041740635,0.00037255746,0.00008881184,8.316045e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016374537,0.000015464757,0.0009046174,0.00003237263,0.0000032761873,0.0000016013825,0.000016038894,0.00009595336,0.010316605,0.6270509,0.000066211236,0.36148062],"study_design_scores_gemma":[0.0052926843,0.00012272515,0.05199456,0.00020658196,0.000011303075,0.000019627822,0.0002905718,0.60475343,0.07656492,0.22822586,0.03175818,0.0007595751],"about_ca_topic_score_codex":0.00002378614,"about_ca_topic_score_gemma":0.00004953536,"teacher_disagreement_score":0.8432303,"about_ca_system_score_codex":0.00006957318,"about_ca_system_score_gemma":0.000034640045,"threshold_uncertainty_score":0.28922132},"labels":[],"label_agreement":null},{"id":"W4415312682","doi":"10.48550/arxiv.2506.14630","title":"Keigo: Co-designing Log-Structured Merge Key-Value Stores with a Non-Volatile, Concurrency-aware Storage Hierarchy (Extended Version)","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"European Regional Development Fund; Fundação para a Ciência e a Tecnologia; European Commission; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Merge (version control); Leverage (statistics); Computer data storage; Distributed data store; Hierarchy; Storage area network; Storage management; Memory hierarchy","score_opus":0.02142723986779072,"score_gpt":0.2790511748346529,"score_spread":0.2576239349668622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415312682","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":[0.15891193,0.0009441398,0.832338,0.0004114233,0.0020990141,0.0012928346,0.00065243593,0.0024381143,0.0009121111],"genre_scores_gemma":[0.8663023,0.00016984253,0.13173835,0.0002624633,0.00014467225,0.00022378498,0.0004595544,0.000072049275,0.0006269728],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9943171,0.0002591824,0.00079513516,0.002569814,0.00096529064,0.001093437],"domain_scores_gemma":[0.99389184,0.0003990337,0.00083992846,0.0042727394,0.00034759365,0.000248858],"candidate_categories":["metaepi_narrow","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00039690558,0.0011614638,0.0012280041,0.00082039624,0.0005689571,0.00024961372,0.0057900255,0.0008344299,0.000065653556],"category_scores_gemma":[0.00033771934,0.0010503597,0.00026035125,0.001097085,0.000622289,0.0011157353,0.005880667,0.0026817347,0.00010064335],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002140467,0.0019944825,0.4399052,0.007543867,0.0062612947,0.010115479,0.024038723,0.1006089,0.025975259,0.09636381,0.14723615,0.13781638],"study_design_scores_gemma":[0.018455451,0.004400417,0.34833422,0.012236762,0.0016086493,0.00042478947,0.0038571178,0.2803041,0.15175162,0.08218413,0.074898966,0.021543767],"about_ca_topic_score_codex":0.0001418603,"about_ca_topic_score_gemma":0.000048638776,"teacher_disagreement_score":0.70739037,"about_ca_system_score_codex":0.00060476485,"about_ca_system_score_gemma":0.0012533271,"threshold_uncertainty_score":0.9996191},"labels":[],"label_agreement":null},{"id":"W4416146758","doi":"10.1145/3712285.3769442","title":"Reproducibility Report for SC25 Paper ThirstyFLOPS: Water Footprint Modeling and Analysis Toward Sustainable HPC Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Reproducibility; Artifact (error); Footprint; Work (physics); Ecological footprint","score_opus":0.02902723579671414,"score_gpt":0.29132705511748236,"score_spread":0.26229981932076823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416146758","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":[0.016790604,0.0030500425,0.96749395,0.0069851894,0.0007377155,0.00241139,0.000016767945,0.0010030785,0.0015112879],"genre_scores_gemma":[0.8747344,0.00021560388,0.11108007,0.00014190753,0.000053116313,0.0004039725,0.000052442352,0.000023701701,0.01329476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9891214,0.00015236551,0.0019886096,0.006639111,0.0005388119,0.0015597076],"domain_scores_gemma":[0.9851822,0.00022525518,0.0003193732,0.012419576,0.0016951093,0.00015848181],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008845357,0.0006616647,0.001399157,0.0010174531,0.0008219978,0.0012394422,0.001965404,0.00044547906,0.000014650533],"category_scores_gemma":[0.0044903103,0.0005041395,0.00041116917,0.0025183202,0.00036171154,0.0017588122,0.006229704,0.00047205453,0.0000040087716],"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":[0.00025857094,0.00049946347,0.0048970683,0.0048774187,0.0041012242,0.00083901105,0.0030840482,0.44971982,0.0020407818,0.48871252,0.00057263684,0.04039743],"study_design_scores_gemma":[0.0004311375,0.00011235197,0.0001035123,0.00007912948,0.00081126025,0.0000476988,0.004808238,0.91583025,0.0052644643,0.062521316,0.009299609,0.0006910578],"about_ca_topic_score_codex":0.0015878292,"about_ca_topic_score_gemma":0.000053243275,"teacher_disagreement_score":0.85794383,"about_ca_system_score_codex":0.000618926,"about_ca_system_score_gemma":0.00035380607,"threshold_uncertainty_score":0.99979734},"labels":[],"label_agreement":null},{"id":"W4416263579","doi":"10.36948/ijfmr.2025.v07i06.59624","title":"Valtora - Secure File Management System Using Blockchain, IPFS, and Smart Contracts","year":2025,"lang":"","type":"article","venue":"International Journal For Multidisciplinary Research","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Permission; Upload; File system; Public-key cryptography; Data integrity; Metadata; Database transaction; Encryption; Cryptography","score_opus":0.07967323351535338,"score_gpt":0.4312379659626478,"score_spread":0.3515647324472944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416263579","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":[0.046703167,0.008387262,0.90246075,0.015764654,0.01794656,0.0035152116,0.0027909297,0.00036930182,0.0020621459],"genre_scores_gemma":[0.7384426,0.0015871597,0.24824756,0.0001015714,0.0010713423,0.00023468675,0.00010817638,0.00008427085,0.010122607],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9939147,0.00041338778,0.0011150399,0.0011716639,0.0021232297,0.0012619627],"domain_scores_gemma":[0.9937828,0.0015917234,0.00045092293,0.00090841873,0.0029495775,0.00031651414],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0038345843,0.00046080846,0.0005170661,0.0022552211,0.002153928,0.0017651833,0.004282372,0.0003228452,0.000075381955],"category_scores_gemma":[0.0008507105,0.00044838272,0.00023220708,0.0010493661,0.00069838285,0.0011062063,0.007386322,0.0017563163,0.000029521641],"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":[0.0033659623,0.0019415168,0.0016940458,0.002481089,0.0048614624,0.011346925,0.0033644058,0.012593947,0.004672671,0.40791905,0.13804951,0.4077094],"study_design_scores_gemma":[0.003869702,0.0005329924,0.0010625086,0.0050470214,0.00008729968,0.0016664102,0.0073438827,0.8836558,0.0008370051,0.03234602,0.06289278,0.00065857073],"about_ca_topic_score_codex":0.00004899656,"about_ca_topic_score_gemma":0.000020968544,"teacher_disagreement_score":0.87106186,"about_ca_system_score_codex":0.0020268396,"about_ca_system_score_gemma":0.00056232885,"threshold_uncertainty_score":0.9997968},"labels":[],"label_agreement":null},{"id":"W4416962065","doi":"10.1109/pst65910.2025.11268846","title":"Comparing Client- &amp; Server-Side AEAD Encryption in Software-Defined Storage Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Mitacs","keywords":"Encryption; 56-bit encryption; On-the-fly encryption; 40-bit encryption; Client-side encryption; Block cipher; Filesystem-level encryption; Multiple encryption","score_opus":0.038592133836801656,"score_gpt":0.28215932907846325,"score_spread":0.2435671952416616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416962065","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":[0.14129114,0.0029433602,0.8466808,0.0005296428,0.003575418,0.00096628076,0.000016920421,0.0020747054,0.0019216795],"genre_scores_gemma":[0.8832652,0.0002497817,0.112913765,0.00019537802,0.00004613098,0.00011333394,0.00003832265,0.000030707393,0.003147396],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940331,0.0003205326,0.0016267591,0.0019337247,0.000762803,0.0013230578],"domain_scores_gemma":[0.99496627,0.00054649386,0.0005137132,0.003580438,0.0002483547,0.00014474316],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012019259,0.000741795,0.00112431,0.0014275537,0.0003939241,0.00083613343,0.0036553293,0.00051474554,0.000030658826],"category_scores_gemma":[0.0012191408,0.0007959338,0.00016704766,0.0037554603,0.00034533386,0.0026720944,0.0042015053,0.0010739821,0.00055500615],"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":[0.00013661252,0.0009123512,0.079553574,0.0014071255,0.0001573213,0.00026835743,0.0014378291,0.19837204,0.0018317691,0.62489027,0.0044766976,0.08655604],"study_design_scores_gemma":[0.0046527805,0.00030639512,0.037342034,0.0037170737,0.00009674364,0.00007133553,0.0014414631,0.8641242,0.001241755,0.0350731,0.049022436,0.0029107258],"about_ca_topic_score_codex":0.0014109961,"about_ca_topic_score_gemma":0.0021471214,"teacher_disagreement_score":0.74197406,"about_ca_system_score_codex":0.0013401475,"about_ca_system_score_gemma":0.0003529258,"threshold_uncertainty_score":0.99944913},"labels":[],"label_agreement":null},{"id":"W613165032","doi":"10.29173/cais145","title":"A New approach to Design and Implementation of IBM PC for Accessing Library CD-ROM Database via Campus Network","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Advanced Data Storage Technologies","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":"CD-ROM; Computer science; Workstation; Database; IBM; Operating system; IBM PC compatible; World Wide Web; Software","score_opus":0.031905075511895704,"score_gpt":0.27298083290542985,"score_spread":0.24107575739353415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W613165032","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":[0.3244675,0.00016668579,0.6718632,0.0014069101,0.0000848298,0.0014282791,0.00011744296,0.00013886072,0.00032626084],"genre_scores_gemma":[0.5960528,0.000026403803,0.40365005,0.00010618612,0.000031757416,0.00007316445,0.00000750523,0.0000130279905,0.00003908684],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99838316,0.000018561619,0.0004707608,0.00045376344,0.0002771056,0.00039666385],"domain_scores_gemma":[0.99300236,0.00021251655,0.00073830795,0.0003716079,0.0055496586,0.00012557922],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00036508977,0.00023128974,0.00039515007,0.00016106619,0.00011731598,0.0017729389,0.0027470856,0.00009599898,0.000007971738],"category_scores_gemma":[0.0022289352,0.000186198,0.000061941,0.0006083197,0.00018156078,0.023842674,0.0020357228,0.00014326439,8.509316e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002477174,0.00021802532,0.050578922,0.0012675847,0.00022177184,0.0000010424401,0.030361766,0.0002969371,0.15298605,0.12470969,0.06465525,0.57445526],"study_design_scores_gemma":[0.0035145672,0.0017919493,0.14585921,0.001165804,0.0002530648,0.00010119912,0.010288475,0.031062873,0.5133696,0.27177423,0.018922474,0.0018965156],"about_ca_topic_score_codex":0.00018405724,"about_ca_topic_score_gemma":0.000004214491,"teacher_disagreement_score":0.5725587,"about_ca_system_score_codex":0.000023126302,"about_ca_system_score_gemma":0.00021523178,"threshold_uncertainty_score":0.99926335},"labels":[],"label_agreement":null},{"id":"W6894015204","doi":"10.5281/zenodo.6552863","title":"D7.4.1: Applications and user requirements for Tier-0 systems","year":2011,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"European Commission","keywords":"Deliverable; Task (project management); Principal (computer security); Baseline (sea); Quarter (Canadian coin); Power (physics); Factor (programming language); User requirements document","score_opus":0.08060114831209207,"score_gpt":0.26639348178566397,"score_spread":0.18579233347357188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6894015204","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":[0.00043473303,0.00013157143,0.98105264,0.00015731655,0.00006764279,0.00081594376,0.00017264015,0.0016685924,0.015498931],"genre_scores_gemma":[0.782168,0.00034751883,0.21151032,0.0002933894,0.00018911512,0.0000049845994,0.0015643055,0.0016998826,0.0022225433],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99888605,0.000060540835,0.00017949533,0.00042874904,0.00017723216,0.00026790693],"domain_scores_gemma":[0.99871314,0.000018569925,0.00009690343,0.0007809918,0.00030265798,0.00008775255],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00033627407,0.00010247906,0.00010109558,0.00016144785,0.0011664451,0.0004516894,0.0016706192,0.000049789152,0.00016132732],"category_scores_gemma":[0.00020846045,0.00010555599,0.000019051044,0.00037105518,0.0001399953,0.00067784765,0.0018339665,0.0001028381,0.0009993679],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025876989,0.00015207526,0.000009308777,0.00012934834,0.000047511872,0.0000065781674,0.0009876934,0.000016374526,0.002950944,0.601138,0.13652219,0.25801408],"study_design_scores_gemma":[0.0002530485,0.00014276312,0.00008071226,0.000011257227,0.000005165652,0.000039411127,0.00015603383,0.0010260163,0.0005970029,0.0025049786,0.99504876,0.00013487649],"about_ca_topic_score_codex":0.0000056968015,"about_ca_topic_score_gemma":7.544241e-8,"teacher_disagreement_score":0.8585265,"about_ca_system_score_codex":0.00006894974,"about_ca_system_score_gemma":0.00000217546,"threshold_uncertainty_score":0.99977845},"labels":[],"label_agreement":null},{"id":"W6901747285","doi":"10.60692/sakw0-nw922","title":"Intelligent Distributed Data Storage for Wireless Communications in B5G Networks","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Wireless; Distributed data store; Key (lock); Software deployment; Intelligent Network; Computer data storage; Field (mathematics); Wireless network","score_opus":0.08887450426232427,"score_gpt":0.273742920891822,"score_spread":0.18486841662949774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901747285","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":[0.0034864382,0.000019270228,0.9924089,0.00024952984,0.0003491911,0.0006866154,0.0020746582,0.000658536,0.00006689846],"genre_scores_gemma":[0.9782344,8.0492407e-7,0.01954944,0.000091002985,0.000011541443,0.0005079198,0.0015885843,0.000006848443,0.00000944326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985289,0.00009514965,0.00060422573,0.0002529352,0.00024170117,0.00027710095],"domain_scores_gemma":[0.9954745,0.00004311639,0.0003444698,0.004016699,0.00008140004,0.000039794464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072976644,0.00014120011,0.00019843358,0.00027190524,0.00038166225,0.00019128884,0.0051706983,0.000055345758,0.0000024745198],"category_scores_gemma":[0.000042476673,0.00014157158,0.000030820673,0.00076163607,0.000047039706,0.0020935994,0.005298435,0.0002404953,0.000024200572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019160206,0.00009497483,0.035171684,0.0008407339,0.00021151715,0.00003911489,0.118224904,0.42673188,0.000004299247,0.283607,0.011153671,0.1237286],"study_design_scores_gemma":[0.000380117,0.000031680644,0.00069956516,0.0000251331,0.0000043572854,0.000019125782,0.008839181,0.9784534,0.000019541338,0.00002349519,0.011323683,0.00018072648],"about_ca_topic_score_codex":0.00000852546,"about_ca_topic_score_gemma":0.0000015539996,"teacher_disagreement_score":0.97474796,"about_ca_system_score_codex":0.00039726263,"about_ca_system_score_gemma":0.00004536665,"threshold_uncertainty_score":0.96085304},"labels":[],"label_agreement":null},{"id":"W6906077719","doi":"10.15468/dl.z75jmg","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); State (computer science)","score_opus":0.016427675173837874,"score_gpt":0.22508654086499424,"score_spread":0.20865886569115638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6906077719","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011990364,0.000034765937,0.002466752,0.0002786177,0.0008413403,0.00028613737,0.99532664,0.0007076528,0.000046111578],"genre_scores_gemma":[0.0000014947283,0.000082373685,0.00009989466,0.0005196161,4.5059923e-7,0.000011349332,0.99928474,9.322678e-9,6.0400765e-8],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980162,0.00006645574,0.00038288208,0.00041329834,0.0007464955,0.00037471324],"domain_scores_gemma":[0.99750507,0.00003100712,0.0004153009,0.0017935053,0.00014929814,0.0001058414],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00026977237,0.00031539783,0.00028426122,0.00017247513,0.0005172353,0.0002560964,0.003872869,0.00025863037,0.0065950686],"category_scores_gemma":[0.00027476694,0.0003449399,0.00012163639,0.00083742035,0.00020134043,0.0037108937,0.0047955853,0.0005501086,0.05926743],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008072774,0.000025272413,0.000045618486,0.00004983461,0.000013788083,0.000009009768,0.000022140177,0.000032562595,1.7594687e-8,0.000004494727,0.99280083,0.0069883857],"study_design_scores_gemma":[0.00018323572,0.00004815496,0.000007997056,6.987574e-7,0.000011546405,0.000013035665,0.00008164483,8.5835444e-7,0.0000027180022,0.00001792461,0.99928993,0.0003422793],"about_ca_topic_score_codex":0.00018052668,"about_ca_topic_score_gemma":0.000005205869,"teacher_disagreement_score":0.05267236,"about_ca_system_score_codex":0.0007007946,"about_ca_system_score_gemma":0.000183062,"threshold_uncertainty_score":0.9999003},"labels":[],"label_agreement":null},{"id":"W6930351394","doi":"10.5281/zenodo.12193721","title":"[PDF] Tremblez encore ! - 10 nouvelles histoire criminelles vraies et flippantes download","year":2024,"lang":"fr","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Period (music); Context (archaeology); First world war; Nova scotia","score_opus":0.048181573811171566,"score_gpt":0.26180040004772626,"score_spread":0.2136188262365547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930351394","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000105208164,0.0107759675,0.06377719,0.00653852,0.001132566,0.00089758344,0.001990769,0.0070800046,0.9077022],"genre_scores_gemma":[0.0058848676,0.0040250826,0.016047528,0.0004633364,0.00050682353,5.278474e-7,0.0044772695,0.007974482,0.9606201],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9952725,0.0004969694,0.00064694014,0.0018026876,0.00081035413,0.00097054284],"domain_scores_gemma":[0.9964356,0.00011241929,0.0003831965,0.0021128652,0.00068768085,0.00026825705],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.0006462158,0.0007537579,0.00060703076,0.0010230741,0.0021564867,0.002911331,0.005576258,0.00045380628,0.13988303],"category_scores_gemma":[0.0021116822,0.00076376484,0.00020465726,0.001387427,0.0014509641,0.00091542053,0.008719278,0.0011548868,0.27041903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023088796,0.00013416076,1.423103e-7,0.00040899808,0.0000974898,0.00020552875,0.0031847435,0.000045077963,0.0014424451,0.069510065,0.67792356,0.2470247],"study_design_scores_gemma":[0.000335689,0.0003987543,0.000008652848,0.000585844,0.00006730979,0.000369115,0.001381891,0.00096085685,0.0005575816,0.0023530596,0.99220556,0.0007757051],"about_ca_topic_score_codex":0.000052709907,"about_ca_topic_score_gemma":0.0000063506536,"teacher_disagreement_score":0.31428197,"about_ca_system_score_codex":0.00043507887,"about_ca_system_score_gemma":0.000035557052,"threshold_uncertainty_score":0.9998041},"labels":[],"label_agreement":null},{"id":"W6931406093","doi":"10.5281/zenodo.4254315","title":"RegardeR*]] Journal de Bolivie (2020) — Film Complet Streaming VF yld","year":2020,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Southeast asia; Expansive; Access to information","score_opus":0.057643350580137476,"score_gpt":0.2632158768501331,"score_spread":0.20557252626999561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931406093","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":[0.004382253,0.004059693,0.89904237,0.05868076,0.00053198176,0.00050768396,0.000586398,0.003132395,0.02907646],"genre_scores_gemma":[0.80139273,0.008687831,0.16236652,0.0074869515,0.0037635176,1.7390678e-7,0.002013979,0.0068600187,0.0074282642],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964314,0.00065475784,0.0004977281,0.00077976566,0.00065393007,0.0009823949],"domain_scores_gemma":[0.9974311,0.00007567575,0.00032201695,0.0008109415,0.0007783267,0.0005819252],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00086191006,0.00030658895,0.00031724077,0.00019219841,0.0033488756,0.0030381945,0.0042202454,0.00016251659,0.008147743],"category_scores_gemma":[0.0035381522,0.00035654608,0.000104729144,0.001328794,0.000537326,0.0015362832,0.006127436,0.0012820131,0.01011609],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031475814,0.00011243354,0.0000033187537,0.000112633,0.00005767709,0.0006065574,0.0025282346,0.0016505591,0.0015467417,0.016760575,0.5640679,0.41252187],"study_design_scores_gemma":[0.0005181581,0.0005360507,0.00014387346,0.00011220564,0.000022241109,0.0019588016,0.0007275209,0.035238236,0.0004798316,0.0020933591,0.9578212,0.0003485196],"about_ca_topic_score_codex":0.000019748912,"about_ca_topic_score_gemma":5.806023e-7,"teacher_disagreement_score":0.7970105,"about_ca_system_score_codex":0.00041654098,"about_ca_system_score_gemma":0.000029361327,"threshold_uncertainty_score":0.99988866},"labels":[],"label_agreement":null},{"id":"W6931673119","doi":"10.5281/zenodo.7525913","title":"tardis-sn/tardis: TARDIS v2023.01.11","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sequence (biology); Control theory (sociology); Action (physics); Component (thermodynamics)","score_opus":0.032929456319970005,"score_gpt":0.25240459813891925,"score_spread":0.21947514181894923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931673119","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011156827,0.0004384962,0.2538061,0.0013156093,0.00083302247,0.0009183958,0.0016741841,0.038949247,0.7020538],"genre_scores_gemma":[0.0035218666,0.0031362132,0.05651489,0.00074441714,0.0018527466,0.0000016524617,0.009005655,0.07899208,0.84623045],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963816,0.00025789277,0.0003882615,0.001322273,0.00084108557,0.000808919],"domain_scores_gemma":[0.99648005,0.00004605292,0.00031271952,0.0026932512,0.00024499322,0.00022294946],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00057594164,0.0004536846,0.00045822453,0.000927474,0.001233553,0.0011773504,0.006409972,0.00032612745,0.012483959],"category_scores_gemma":[0.0011206731,0.00047949507,0.00014822514,0.0017248857,0.0003694709,0.0006042239,0.009101143,0.000647756,0.04981957],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004936113,0.000041945845,6.9683597e-7,0.000062156956,0.00007377745,0.000111521,0.00017204248,0.000026357611,0.00006450892,0.01496153,0.8861714,0.09830911],"study_design_scores_gemma":[0.00029735954,0.00010508817,0.00003514483,0.00011989683,0.000017943912,0.00007043953,0.000114241346,0.00029237932,0.000085332285,0.0009932825,0.99735695,0.000511941],"about_ca_topic_score_codex":0.00010502213,"about_ca_topic_score_gemma":0.000014551132,"teacher_disagreement_score":0.19729123,"about_ca_system_score_codex":0.00031938558,"about_ca_system_score_gemma":0.000010161684,"threshold_uncertainty_score":0.9998595},"labels":[],"label_agreement":null},{"id":"W6931852759","doi":"10.5281/zenodo.6500751","title":"FIGURES 23–29 in Revision of the genus Charippus Thorell, 1895, with descriptions of eight new species (Araneae, Salticidae, Euophryini)","year":2022,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dorsum; Genus; Male genitalia; Taxonomy (biology); Morphology (biology)","score_opus":0.037354271110113184,"score_gpt":0.2384621477987092,"score_spread":0.201107876688596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931852759","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005695487,0.0046726153,0.12141594,0.0015441495,0.00046185974,0.0024232722,0.0015147383,0.0023071547,0.8650907],"genre_scores_gemma":[0.05397385,0.009346023,0.08567166,0.00045571587,0.00051703124,8.7827266e-7,0.004066814,0.014069138,0.83189887],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99784374,0.0002769241,0.00036072568,0.00055166194,0.0006569172,0.00031003903],"domain_scores_gemma":[0.9975993,0.000033751327,0.000443408,0.0016945897,0.0001625036,0.00006643158],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00031562665,0.00022747043,0.00032498367,0.0006033677,0.00046918256,0.00016615652,0.0042915936,0.000111330446,0.011431671],"category_scores_gemma":[0.0005057794,0.00017962808,0.000063331165,0.001718503,0.0003784774,0.00022671663,0.0039041967,0.0005264162,0.00038014105],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027893502,0.00011084874,0.000011558038,0.00018840116,0.000041386404,0.000023146906,0.00063980516,0.000118277356,0.00080636714,0.020696977,0.92326534,0.054069985],"study_design_scores_gemma":[0.00030063093,0.00019700489,0.00022419496,0.00022694936,0.000013632132,0.00003793514,0.00015126225,0.00010593704,0.0004928387,0.00026323888,0.9978005,0.00018585857],"about_ca_topic_score_codex":0.00008236974,"about_ca_topic_score_gemma":0.000007263701,"teacher_disagreement_score":0.07453517,"about_ca_system_score_codex":0.0001602778,"about_ca_system_score_gemma":0.000022730737,"threshold_uncertainty_score":0.98947203},"labels":[],"label_agreement":null},{"id":"W6931967666","doi":"10.5683/sp3/nobfew","title":"Systematic map of ecological restoration knowledge in Canada","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Disturbance (geology); Restoration ecology; Ecosystem; Intervention (counseling); Outcome (game theory); Ecosystem services; Novel ecosystem; Ecosystem management","score_opus":0.017902278967390356,"score_gpt":0.25387923026868886,"score_spread":0.2359769513012985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931967666","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000056410863,0.001154148,0.0009248681,0.00012857662,0.00033179557,0.00042739752,0.99693394,0.00006897829,0.000024645145],"genre_scores_gemma":[0.00010147555,0.00008029233,0.0014906728,0.00004486679,0.000012086362,0.00023614314,0.99801576,0.0000062998515,0.0000123981845],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99815404,0.00021929613,0.00059900415,0.000409296,0.00038437676,0.00023398262],"domain_scores_gemma":[0.99733686,0.0003364079,0.00046477062,0.0017734279,0.000052713505,0.000035830224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034207304,0.00019938877,0.0005712254,0.0002645964,0.000049308772,0.00002229545,0.0026866386,0.00013661086,0.00012345656],"category_scores_gemma":[0.00042228636,0.00018018187,0.000037415237,0.00039779634,0.000044280365,0.00018712647,0.0013287546,0.0003803353,0.000003211503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013856298,0.00003939932,0.000002558008,0.0033332747,0.000008592931,0.0001360621,0.000012815337,0.000071654234,5.1427304e-7,0.0018282747,0.9945176,0.00004782965],"study_design_scores_gemma":[0.00011910105,0.00007470201,0.00012506072,0.00053471467,0.00001534404,0.000011658266,0.00013369803,0.00040664032,0.000011602167,0.0008541767,0.9974551,0.00025820342],"about_ca_topic_score_codex":0.9332943,"about_ca_topic_score_gemma":0.9953623,"teacher_disagreement_score":0.062067997,"about_ca_system_score_codex":0.0016286289,"about_ca_system_score_gemma":0.0014708719,"threshold_uncertainty_score":0.73476034},"labels":[],"label_agreement":null},{"id":"W6944476466","doi":"10.18712/nsd-nsd1265-3-v1","title":"Travel and Holiday Survey, 3rd quarter 2009","year":2019,"lang":"en","type":"dataset","venue":"NSD – Norsk senter for forskningsdata","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Continuance; Travel behavior; Tourism; Travel survey; Survey data collection; Falling (accident)","score_opus":0.03698560325131598,"score_gpt":0.289822279696374,"score_spread":0.252836676445058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6944476466","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000053322718,0.00026613998,0.26339832,0.0003239105,0.0012373208,0.00088013033,0.73359925,0.0002299565,0.000011620551],"genre_scores_gemma":[0.00015577019,0.00022804395,0.029145142,0.00060382433,0.0001697553,0.00012229677,0.96900517,0.00006683457,0.0005031585],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99520457,0.000117042895,0.00079685345,0.0021469104,0.00059506594,0.001139577],"domain_scores_gemma":[0.9932102,0.00057655945,0.0006906305,0.0051351083,0.00018695014,0.00020057867],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.00094036583,0.00094359653,0.0010951463,0.0006208883,0.0002465208,0.0006296967,0.005879424,0.00076154206,0.000034033816],"category_scores_gemma":[0.00052129506,0.0008806107,0.00020198373,0.00047838603,0.00026633573,0.002407232,0.0033836835,0.0008705188,0.00038158044],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003745291,0.000071882256,0.00008587776,0.00021125792,0.00008312363,0.000025776226,0.000041600328,0.0000020560985,0.000016948643,0.00024690482,0.9969212,0.0022559352],"study_design_scores_gemma":[0.0010796061,0.00042974474,0.0004589653,0.00016717508,0.000067090186,0.00010509391,0.000043748954,0.0009714994,0.000108937056,0.0013067909,0.9941517,0.0011096568],"about_ca_topic_score_codex":0.0004519388,"about_ca_topic_score_gemma":0.0004818129,"teacher_disagreement_score":0.2354059,"about_ca_system_score_codex":0.00010538151,"about_ca_system_score_gemma":0.00011376999,"threshold_uncertainty_score":0.99949926},"labels":[],"label_agreement":null},{"id":"W6945381786","doi":"10.25316/ir-17493","title":"Contextualized social work education in Canada: Understanding educators’ perspectives","year":2021,"lang":"en","type":"article","venue":"VIUspace","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Contextualization; Social work; Social change; Colonialism; Social learning; Agency (philosophy); Work (physics); Social relation","score_opus":0.029481265762172384,"score_gpt":0.2796022427052037,"score_spread":0.2501209769430313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6945381786","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":[0.16514952,0.00641571,0.748863,0.064679064,0.0022035737,0.00037554238,0.000012872174,0.0006106722,0.011690038],"genre_scores_gemma":[0.9790726,0.000031731426,0.020046473,0.00021027228,0.000040930237,0.000013985524,0.0000034888888,0.0000075717508,0.0005729953],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9990487,0.000056604178,0.00011668434,0.0003546034,0.00017826892,0.00024510143],"domain_scores_gemma":[0.9993738,0.0000929769,0.00006593486,0.0003676678,0.00006099441,0.000038620947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006698722,0.000104899365,0.00014749232,0.000094366915,0.00014075599,0.00006848027,0.0004357487,0.000044044504,0.000021101549],"category_scores_gemma":[0.00021872859,0.00011495599,0.0000224623,0.0011788511,0.00004917748,0.00034997764,0.00024299472,0.00016853196,0.0000066892644],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055147534,0.00008047754,0.0017813388,0.000007862453,0.00001195082,0.000041905,0.006128158,0.000016351523,0.00026274766,0.9369298,0.03597811,0.018755749],"study_design_scores_gemma":[0.0014895011,0.000038091126,0.034119215,0.00020643885,0.000015047763,0.000062425046,0.77196115,0.00043503498,0.0061106733,0.117050305,0.067107596,0.0014045441],"about_ca_topic_score_codex":0.06587866,"about_ca_topic_score_gemma":0.7537534,"teacher_disagreement_score":0.81987953,"about_ca_system_score_codex":0.003129871,"about_ca_system_score_gemma":0.00554079,"threshold_uncertainty_score":0.98291236},"labels":[],"label_agreement":null},{"id":"W6945653927","doi":"10.25318/1810018701-eng","title":"Industry price indexes for electrical and communication products, nonmetallic mineral products, petroleum and coal products (1997=100)","year":2020,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Table (database); Coal; Petroleum; Petroleum product; Coal mining","score_opus":0.012532942393113656,"score_gpt":0.2579261470416306,"score_spread":0.24539320464851694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6945653927","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012446461,0.0012407126,0.039800122,0.005475947,0.0002737449,0.0011414476,0.9518224,0.00011960254,0.000001555154],"genre_scores_gemma":[0.0011711173,0.00053928833,0.12440757,0.00014608799,0.00012429999,0.00020451729,0.8732411,0.000030596988,0.00013540259],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997158,0.00009379413,0.0004984038,0.0011729569,0.0006201716,0.00045668855],"domain_scores_gemma":[0.99705505,0.00046898992,0.00057336094,0.0013122205,0.0004540962,0.00013629881],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002944017,0.0004552749,0.00047469654,0.00021511449,0.000297293,0.00026179868,0.0011844423,0.0004548194,0.0000013457654],"category_scores_gemma":[0.0049506747,0.00047957397,0.000010238083,0.0006026946,0.0002166833,0.0004976816,0.000706941,0.0012958201,0.0000011528996],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001516557,0.000045655794,0.000012239357,0.00058881,0.00003376681,0.000019628675,0.000028360091,0.000005537469,0.00016854942,0.0036136382,0.9897628,0.005705873],"study_design_scores_gemma":[0.00028831547,0.00024138628,0.0015299763,0.00010483975,0.00010522712,0.000057937294,0.00004804986,0.001969641,0.0011218584,0.0011081704,0.99268824,0.00073635887],"about_ca_topic_score_codex":0.0039239954,"about_ca_topic_score_gemma":0.01639807,"teacher_disagreement_score":0.084607445,"about_ca_system_score_codex":0.00035916714,"about_ca_system_score_gemma":0.0009996198,"threshold_uncertainty_score":0.9997656},"labels":[],"label_agreement":null},{"id":"W6945816046","doi":"10.25446/oxford.25923232.v1","title":"Jock's War","year":2024,"lang":"en","type":"other","venue":"Figshare","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Yard; Value (mathematics); World War II; Spanish Civil War; Front (military); Palestine","score_opus":0.03240861085212485,"score_gpt":0.27153676891340794,"score_spread":0.2391281580612831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6945816046","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[8.1170454e-10,0.011262591,0.001713356,0.00013673349,0.0002882046,0.00015090333,0.3048831,0.0073017892,0.6742633],"genre_scores_gemma":[0.0000020110735,0.00003477329,0.029694622,0.0001563675,0.00023897881,0.00018394207,0.041656002,0.00040213403,0.92763114],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989738,0.000006519811,0.000087271656,0.0005350783,0.00017848062,0.00021887165],"domain_scores_gemma":[0.998515,0.000019391702,0.00007816628,0.0013380256,0.000014084087,0.00003532229],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000009953153,0.00021103454,0.00016700856,0.00023690384,0.000013991605,0.000079143705,0.0020210186,0.000277193,0.16808668],"category_scores_gemma":[0.0002851855,0.0001887316,0.00005601835,0.00030848215,0.0000065188574,0.00013361697,0.0016621886,0.0003006606,0.14084946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.274189e-8,0.00000282561,9.754521e-9,0.00015451216,0.000009436392,0.00014044116,0.0000075305297,2.2979317e-7,5.8858933e-7,0.00083164737,0.9864823,0.012370398],"study_design_scores_gemma":[0.000020965306,0.000010011746,2.0113013e-7,0.0022565657,0.0000019326226,0.000010815045,0.0000022280087,0.00008778458,0.000054806183,0.002424319,0.9949072,0.00022319975],"about_ca_topic_score_codex":0.0000030278868,"about_ca_topic_score_gemma":0.000007939337,"teacher_disagreement_score":0.2632271,"about_ca_system_score_codex":0.000035168134,"about_ca_system_score_gemma":0.000036707093,"threshold_uncertainty_score":0.8598195},"labels":[],"label_agreement":null},{"id":"W6948046539","doi":"10.4224/12328809","title":"Laboratory experiments of ice scour processes: buoyant ice model","year":2002,"lang":"en","type":"report","venue":"NPARC","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"National Research Council Canada; Canadian Wood Council","funders":"","keywords":"Seabed; Block (permutation group theory); Hydraulics; Displacement (psychology); Sea ice; Vertical displacement","score_opus":0.055400679509277684,"score_gpt":0.3156687742581402,"score_spread":0.26026809474886253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6948046539","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043498568,0.0068284124,0.9073196,0.00020693168,0.00082317763,0.0006096366,0.00049968285,0.0014769277,0.08180065],"genre_scores_gemma":[0.10239063,0.007727876,0.88328743,0.00017924776,0.00021273387,0.00032135667,0.000065217304,0.00013835498,0.005677136],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99634784,0.000030236068,0.00063299434,0.0009881998,0.0015185594,0.00048214637],"domain_scores_gemma":[0.99519396,0.0000987782,0.00081514736,0.0024326018,0.001366848,0.0000926605],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034919893,0.00044868997,0.0006716508,0.00032703124,0.00009003908,0.00007427719,0.0033464534,0.00044216178,0.000040881256],"category_scores_gemma":[0.0011754938,0.0004316966,0.00007587579,0.0009944767,0.00020562278,0.0009315478,0.0013997923,0.00054258574,0.00004818946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050139493,0.002508865,0.00014610954,0.010973199,0.000758141,0.001211663,0.004774219,0.00848853,0.10426554,0.03128859,0.6928821,0.14265288],"study_design_scores_gemma":[0.0017395376,0.00067625666,0.000021229404,0.0038938392,0.00022547132,0.0001809909,0.0006831551,0.13832657,0.35916913,0.05227136,0.43767184,0.0051406426],"about_ca_topic_score_codex":0.000015044172,"about_ca_topic_score_gemma":0.0000046008468,"teacher_disagreement_score":0.25521028,"about_ca_system_score_codex":0.00033688272,"about_ca_system_score_gemma":0.0020299342,"threshold_uncertainty_score":0.9998135},"labels":[],"label_agreement":null},{"id":"W6958028838","doi":"10.60692/nz8mq-vjp50","title":"Intelligent Distributed Data Storage for Wireless Communications in B5G Networks","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Wireless; Distributed data store; Key (lock); Software deployment; Intelligent Network; Computer data storage; Field (mathematics); Wireless network","score_opus":0.08887450426232427,"score_gpt":0.273742920891822,"score_spread":0.18486841662949774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958028838","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":[0.0034864382,0.000019270228,0.9924089,0.00024952984,0.0003491911,0.0006866154,0.0020746582,0.000658536,0.00006689846],"genre_scores_gemma":[0.9782344,8.0492407e-7,0.01954944,0.000091002985,0.000011541443,0.0005079198,0.0015885843,0.000006848443,0.00000944326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985289,0.00009514965,0.00060422573,0.0002529352,0.00024170117,0.00027710095],"domain_scores_gemma":[0.9954745,0.00004311639,0.0003444698,0.004016699,0.00008140004,0.000039794464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072976644,0.00014120011,0.00019843358,0.00027190524,0.00038166225,0.00019128884,0.0051706983,0.000055345758,0.0000024745198],"category_scores_gemma":[0.000042476673,0.00014157158,0.000030820673,0.00076163607,0.000047039706,0.0020935994,0.005298435,0.0002404953,0.000024200572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019160206,0.00009497483,0.035171684,0.0008407339,0.00021151715,0.00003911489,0.118224904,0.42673188,0.000004299247,0.283607,0.011153671,0.1237286],"study_design_scores_gemma":[0.000380117,0.000031680644,0.00069956516,0.0000251331,0.0000043572854,0.000019125782,0.008839181,0.9784534,0.000019541338,0.00002349519,0.011323683,0.00018072648],"about_ca_topic_score_codex":0.00000852546,"about_ca_topic_score_gemma":0.0000015539996,"teacher_disagreement_score":0.97474796,"about_ca_system_score_codex":0.00039726263,"about_ca_system_score_gemma":0.00004536665,"threshold_uncertainty_score":0.96085304},"labels":[],"label_agreement":null},{"id":"W6989743952","doi":"","title":"CCBFC proposes relocating NBC and NFC requirements","year":2000,"lang":"en","type":"article","venue":"NPARC","topic":"Advanced Data Storage Technologies","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":"Identification (biology); Key (lock); Component (thermodynamics); Process (computing); Focus (optics)","score_opus":0.022039155167880943,"score_gpt":0.26599554386646146,"score_spread":0.24395638869858052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6989743952","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":[0.41790807,0.0005448974,0.494427,0.0050170277,0.00027526796,0.00062834256,0.0000101381465,0.0034183196,0.07777094],"genre_scores_gemma":[0.5771964,0.000079124264,0.42188135,0.00016214004,0.000016771168,0.000013502033,0.0000011661833,0.0000062549243,0.00064325036],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991521,0.000016177906,0.00012974536,0.00032195,0.0001648988,0.00021513226],"domain_scores_gemma":[0.9992795,0.00003353621,0.000040171,0.00058921904,0.000022060403,0.000035516474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000108532855,0.00009096197,0.00009159712,0.0000449933,0.00012163241,0.00007239804,0.0006171716,0.00004000658,0.00007307456],"category_scores_gemma":[0.00009419074,0.00008111925,0.000011067581,0.00021047397,0.00010431937,0.0007137379,0.00030598266,0.00009847915,0.000079327074],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030572128,0.000021394064,0.00019041996,0.000010657829,0.0000046665577,0.000020836382,0.00021322942,0.000008264552,0.014453446,0.03378743,0.0009849413,0.95030165],"study_design_scores_gemma":[0.0017596754,0.00067587604,0.0029877992,0.00027107933,0.000018645238,0.00021165457,0.00038546295,0.03321475,0.12352455,0.6941879,0.14138286,0.0013797379],"about_ca_topic_score_codex":0.000004204447,"about_ca_topic_score_gemma":0.0000019094794,"teacher_disagreement_score":0.9489219,"about_ca_system_score_codex":0.000027004675,"about_ca_system_score_gemma":0.000018277313,"threshold_uncertainty_score":0.33079472},"labels":[],"label_agreement":null},{"id":"W7008368251","doi":"","title":"Behrooz File System (BFS)","year":2015,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo","keywords":"Nucleofection; Fusible alloy; Gestational period; Proteogenomics; TSG101; Hyporeflexia; Pretext","score_opus":0.01241025252819145,"score_gpt":0.20885784984512568,"score_spread":0.19644759731693423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008368251","genre_codex":"empirical","genre_gemma":"other","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":[0.9096695,0.0021256278,0.039227765,0.0023835616,0.00611574,0.002398192,0.0048778728,0.010485601,0.022716094],"genre_scores_gemma":[0.027305951,0.00008429298,0.21463127,0.000014056628,0.00006509022,0.0000028634938,0.0040016733,0.000059605896,0.7538352],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.9985273,0.0000387611,0.00012663861,0.0005669264,0.00043370965,0.00030667064],"domain_scores_gemma":[0.99800915,0.000039332594,0.00036910127,0.0011964219,0.00028937188,0.00009663932],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011991494,0.00025913768,0.00044011828,0.00036250715,0.00016062548,0.000038924103,0.002465925,0.00038506277,0.000113740476],"category_scores_gemma":[0.000036810947,0.00030383564,0.00011380229,0.0003961235,0.000093847666,0.00082948286,0.0005004177,0.00028981882,0.00032100175],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019910907,0.00023440871,0.000053523596,0.0023301265,0.0003943615,0.0014677614,0.18257433,0.00026444596,0.0030131182,0.050981127,0.64806,0.11042764],"study_design_scores_gemma":[0.0021272046,0.00074953807,0.0011490231,0.0018740195,0.00027802913,0.000066293745,0.9098745,0.008996352,0.0070173773,0.006662788,0.05857958,0.0026253064],"about_ca_topic_score_codex":0.007310331,"about_ca_topic_score_gemma":0.010481646,"teacher_disagreement_score":0.8823636,"about_ca_system_score_codex":0.0002514423,"about_ca_system_score_gemma":0.00015525371,"threshold_uncertainty_score":0.99994135},"labels":[],"label_agreement":null},{"id":"W7024159799","doi":"","title":"Santé numérique. Transformations sociotechniques du soin et des pratiques de santé dans un monde connecté","year":2024,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Perspective (graphical); Context (archaeology); Narrative; Subject (documents); Field (mathematics); Natural (archaeology)","score_opus":0.01523721270645224,"score_gpt":0.2685009919674036,"score_spread":0.2532637792609514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7024159799","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":[0.018580839,0.012823337,0.8827028,0.05722398,0.00022938881,0.000533795,0.000284201,0.0031874918,0.024434118],"genre_scores_gemma":[0.563285,0.014283195,0.41931495,0.0002581851,0.00003322505,0.00013517753,0.00014993793,0.0000621574,0.0024781926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99112993,0.005870626,0.00077017175,0.00095276453,0.00046677297,0.0008097505],"domain_scores_gemma":[0.99293023,0.0031661927,0.00026615898,0.0020979831,0.0013180313,0.00022138139],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00707703,0.0005102398,0.00041409294,0.00034248215,0.0008399866,0.0016003065,0.0024471022,0.00048566872,0.00016165701],"category_scores_gemma":[0.0026240617,0.0005563532,0.0002588115,0.0013855794,0.0013076353,0.0031282133,0.0009189236,0.0010500128,0.00010678043],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033232195,0.00028332273,0.00014709841,0.00020707665,0.00006494814,0.000053723583,0.10311791,0.000055801076,0.0090644695,0.70895505,0.0028735031,0.17517377],"study_design_scores_gemma":[0.00033055196,0.000004785734,0.0010489125,0.0032387138,0.000049462884,0.00031531331,0.003290824,0.17152269,0.48036447,0.2756327,0.063368306,0.0008332466],"about_ca_topic_score_codex":0.0011749166,"about_ca_topic_score_gemma":0.003947452,"teacher_disagreement_score":0.54470414,"about_ca_system_score_codex":0.00061746733,"about_ca_system_score_gemma":0.00080179586,"threshold_uncertainty_score":0.9996888},"labels":[],"label_agreement":null},{"id":"W7034801400","doi":"","title":"Why do midwives stay? A Descriptive Study Investigating Retention amongst Currently Practicing Ontario Midwives","year":2010,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Autonomy; Flexibility (engineering); Descriptive research; Descriptive statistics; Exploratory research; Work (physics); Qualitative research","score_opus":0.1219348000309258,"score_gpt":0.31935931029801656,"score_spread":0.19742451026709076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034801400","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":[0.9502543,0.00004140257,0.046268564,0.00025111466,0.0011435745,0.0008331653,0.000018283585,0.0010831287,0.000106459236],"genre_scores_gemma":[0.9862296,0.000009379663,0.012414253,0.00018535146,0.00006040965,0.0000076877695,0.000017855968,0.000043714,0.0010317299],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959203,0.0004363508,0.00048943766,0.0015431944,0.00077871705,0.00083197013],"domain_scores_gemma":[0.99639416,0.00025479635,0.0007329558,0.0019117745,0.00036859728,0.00033772466],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00074160175,0.0005907723,0.0005045276,0.0009465402,0.00078996795,0.0012509143,0.003394437,0.0002992522,0.000016426213],"category_scores_gemma":[0.00053685036,0.0006615034,0.0001513903,0.001280185,0.00046281476,0.01413635,0.0026049744,0.0025112897,0.00008064788],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035610698,0.00032192396,0.9788603,0.000024504332,0.00009479538,0.00047157743,0.007871615,0.000019650079,0.009296887,0.0009463472,0.0000021960452,0.0020545535],"study_design_scores_gemma":[0.0014892673,0.0005952289,0.97940344,0.00024133093,0.000121539735,0.000077807934,0.007179358,0.000008239838,0.005075839,0.002115552,0.0027101175,0.0009822879],"about_ca_topic_score_codex":0.00043916103,"about_ca_topic_score_gemma":0.14043675,"teacher_disagreement_score":0.1399976,"about_ca_system_score_codex":0.00063871377,"about_ca_system_score_gemma":0.0002895062,"threshold_uncertainty_score":0.99978995},"labels":[],"label_agreement":null},{"id":"W7036920960","doi":"","title":"Cytokine ELISPOT assay development report","year":2009,"lang":"en","type":"report","venue":"NPARC","topic":"Advanced Data Storage Technologies","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":"","score_opus":0.035907740632392944,"score_gpt":0.29770267557139013,"score_spread":0.2617949349389972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7036920960","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003811635,0.00033314622,0.71898514,0.00086215726,0.0012752811,0.00029005023,0.000018946903,0.0021848972,0.27601224],"genre_scores_gemma":[0.004081478,0.0005492808,0.9707425,0.00018338441,0.0003215628,0.00008808078,0.00031976364,0.00005168058,0.02366227],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9952361,0.00003928585,0.000912872,0.0013108173,0.0018652101,0.0006357013],"domain_scores_gemma":[0.9951931,0.00008695499,0.000800035,0.0032642628,0.00053701515,0.00011860142],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015974938,0.00051300443,0.0006811076,0.00041131902,0.00016096403,0.00015609249,0.0030024466,0.0005556073,0.000060871615],"category_scores_gemma":[0.001635197,0.00047655692,0.00011868624,0.00060135376,0.00008953267,0.00049534574,0.0015653888,0.0008553527,0.00018210382],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001719186,0.00005870838,0.000026975738,0.000044347315,0.00003591408,0.00571236,0.00003634673,0.0000074382515,0.0007415339,0.0030566216,0.22954963,0.7607284],"study_design_scores_gemma":[0.00008560437,0.000034783512,0.00031160898,0.00012660351,0.000010768539,0.0020742891,0.0000035736841,0.000074492826,0.006210293,0.013440032,0.97704434,0.00058362645],"about_ca_topic_score_codex":0.000008155396,"about_ca_topic_score_gemma":0.000012743024,"teacher_disagreement_score":0.76014477,"about_ca_system_score_codex":0.0009788716,"about_ca_system_score_gemma":0.0025770783,"threshold_uncertainty_score":0.9997686},"labels":[],"label_agreement":null},{"id":"W7037662416","doi":"","title":"Facteurs associés à un usage approprié des médicaments contre l'asthme chez les 12 à 45 ans","year":2007,"lang":"fr","type":"other","venue":"Corpus Université Laval (Université Laval)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Validation test; Ile de france; Psychological intervention; Medical screening","score_opus":0.017724972458632617,"score_gpt":0.21182073543857144,"score_spread":0.19409576297993883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7037662416","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10085336,0.016905658,0.43278968,0.0042061578,0.0034400602,0.0030548715,0.0020357454,0.0057081566,0.4310063],"genre_scores_gemma":[0.053998582,0.016127177,0.046832066,0.0003692859,0.00037132305,0.0000062860818,0.00044248314,0.00065027765,0.8812025],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99204904,0.00048207145,0.0006877761,0.0028166347,0.0015470056,0.0024174482],"domain_scores_gemma":[0.9937037,0.0005174363,0.0014727245,0.0028207095,0.0005460186,0.00093937444],"candidate_categories":["metaepi_narrow","sts","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.00060696015,0.0018747817,0.0017298149,0.0022194881,0.0018471659,0.00034486852,0.006882943,0.0022491803,0.0017487938],"category_scores_gemma":[0.00022994938,0.0022351884,0.0007902512,0.0027512966,0.0026731342,0.0021302071,0.0049205045,0.0023029447,0.0005927528],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035939628,0.00089235033,0.033914175,0.00036338595,0.0016671474,0.012013937,0.021387858,0.00019809772,0.0121361185,0.12768146,0.006600851,0.78278524],"study_design_scores_gemma":[0.005377422,0.0009083974,0.016933585,0.0010112431,0.0009338674,0.00042258805,0.010109842,0.0009416739,0.015989117,0.0024328218,0.9413999,0.0035395606],"about_ca_topic_score_codex":0.011574317,"about_ca_topic_score_gemma":0.013003435,"teacher_disagreement_score":0.934799,"about_ca_system_score_codex":0.0042341477,"about_ca_system_score_gemma":0.00067961315,"threshold_uncertainty_score":0.9999988},"labels":[],"label_agreement":null},{"id":"W7038637006","doi":"","title":"Influence of Sexual Socialization, Gender Roles and Patriarchal Norms on Rape Myth Acceptance among South Asian Students in Canada","year":2021,"lang":"en","type":"dissertation","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mythology; Socialization; South asia; Perception; Narrative; Gender role; Patriarchy","score_opus":0.01241897157855471,"score_gpt":0.23334549950480632,"score_spread":0.22092652792625161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7038637006","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":[0.9982371,0.00025824076,0.000606614,0.000075017044,0.00013779619,0.0003319481,0.00016214116,0.00006324698,0.00012792826],"genre_scores_gemma":[0.9975128,0.00007763064,0.0017318442,0.000043136424,0.000013426398,0.0000014510697,0.00025548512,0.000024571056,0.00033961496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968339,0.00018324768,0.00039289225,0.000953525,0.0012105987,0.00042579608],"domain_scores_gemma":[0.9977036,0.000094233306,0.0008052565,0.00091864046,0.00035062994,0.00012765038],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035926042,0.0003819548,0.00065696496,0.0005545116,0.00028044957,0.00005838176,0.0024773148,0.00042877372,0.0000182985],"category_scores_gemma":[0.00026848007,0.00048705764,0.000065367145,0.0010764039,0.00020507429,0.001459418,0.0008750112,0.0007951541,0.0000026379792],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020367654,0.000117265205,0.96457255,0.00041934475,0.0001672832,0.00028401503,0.02201623,0.0017980607,0.0011779161,0.0009767826,0.000049878916,0.008217012],"study_design_scores_gemma":[0.00084538007,0.00007034768,0.9705009,0.00022251972,0.000040155166,0.0000021526296,0.026186274,0.000058718535,0.0010851012,0.0005436212,0.00002671563,0.00041811992],"about_ca_topic_score_codex":0.038889434,"about_ca_topic_score_gemma":0.73667246,"teacher_disagreement_score":0.69778305,"about_ca_system_score_codex":0.0006230928,"about_ca_system_score_gemma":0.0012058188,"threshold_uncertainty_score":0.9997581},"labels":[],"label_agreement":null},{"id":"W7039182235","doi":"","title":"Le concept de mutant dans l'oeuvre d'André Turpin (1937-2017), un pont avec les mouvements de la contre-culture au Québec","year":2025,"lang":"fr","type":"other","venue":"Archipelago (Université du Québec à Montréal)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Deterritorialization; Humanity; Subjectivity","score_opus":0.005550421661214258,"score_gpt":0.1881214817107778,"score_spread":0.18257106004956355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7039182235","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":[0.060454845,0.024647146,0.81826067,0.012008946,0.0006721721,0.0013733868,0.0010250892,0.0016364909,0.079921275],"genre_scores_gemma":[0.7772545,0.0025812378,0.039423946,0.000976699,0.00031516745,0.000060164926,0.00017293531,0.00029660028,0.17891875],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.99469537,0.0007589212,0.00060748024,0.0017340587,0.0005991748,0.0016049973],"domain_scores_gemma":[0.9954703,0.00083878206,0.00073793356,0.0022418238,0.0001993166,0.0005118673],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00039526116,0.0012367576,0.001198569,0.0006037834,0.0016592771,0.00023568123,0.004769473,0.0010941367,0.00054108584],"category_scores_gemma":[0.0005878975,0.0013250934,0.0005065727,0.00083422393,0.0022917325,0.00075564394,0.003002364,0.0016964426,0.00016804071],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00019310974,0.0006120022,0.0022728776,0.00017432417,0.0010661328,0.005388614,0.3624135,0.0019985943,0.0017765769,0.32938507,0.016699474,0.27801973],"study_design_scores_gemma":[0.0044299085,0.00041885805,0.006856491,0.0008702601,0.00047551765,0.0006159037,0.06048534,0.009437754,0.0012354224,0.007959282,0.90508884,0.0021264234],"about_ca_topic_score_codex":0.9171522,"about_ca_topic_score_gemma":0.9653535,"teacher_disagreement_score":0.88838935,"about_ca_system_score_codex":0.004866527,"about_ca_system_score_gemma":0.01093361,"threshold_uncertainty_score":0.9996404},"labels":[],"label_agreement":null},{"id":"W7039978759","doi":"","title":"\"No Nation More Tenacious of Its Past\" National Historical Memory in lnterwar Scotland, 1920-1934","year":2024,"lang":"en","type":"article","venue":"ScholarsArchive  (Brigham Young University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Derogation; Scapegoat; Pretext; Population; Liquation; Nucleofection","score_opus":0.016268622550935908,"score_gpt":0.22964937515473205,"score_spread":0.21338075260379613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7039978759","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":[0.111982785,0.003068392,0.79509586,0.0038574482,0.004503466,0.0013616971,0.0004420271,0.0032084605,0.07647985],"genre_scores_gemma":[0.9426805,0.00024634937,0.046304557,0.00006676958,0.00014154651,0.0000038879066,0.00006856072,0.00003102935,0.0104568275],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99813706,0.00010372359,0.00024175864,0.0006359161,0.00057559926,0.0003059345],"domain_scores_gemma":[0.9989783,0.00017979016,0.00010102199,0.00041811843,0.00024822247,0.000074514086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023151154,0.00019722337,0.00022955574,0.0016780077,0.00012058072,0.00009252742,0.0014018583,0.0001141321,0.000009646367],"category_scores_gemma":[0.0002719722,0.00020666294,0.000096819604,0.0015747133,0.00013386678,0.002538917,0.0007117272,0.00060954224,0.0000875864],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029125565,0.00059926935,0.009049899,0.0005358713,0.00025316727,0.0048941174,0.003325611,0.0021066247,0.04102006,0.8909052,0.010139135,0.036879763],"study_design_scores_gemma":[0.005613099,0.0010904543,0.030316167,0.001890392,0.00012203452,0.0005557793,0.0010010105,0.09959537,0.022298584,0.07427034,0.76002073,0.0032260409],"about_ca_topic_score_codex":0.0000658987,"about_ca_topic_score_gemma":0.00005866637,"teacher_disagreement_score":0.8306977,"about_ca_system_score_codex":0.0012644181,"about_ca_system_score_gemma":0.00022536832,"threshold_uncertainty_score":0.84274703},"labels":[],"label_agreement":null},{"id":"W7042800029","doi":"","title":"RAGGA NYC Mercer Union / Toronto","year":2018,"lang":"en","type":"other","venue":"Lund University Publications (Lund University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Exhibition; Queer; Trade union; Government (linguistics); Representation (politics); Context (archaeology)","score_opus":0.011685661338063058,"score_gpt":0.20805090307150878,"score_spread":0.19636524173344572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7042800029","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000018367982,0.0000988635,0.33689842,0.0008819553,0.00029380852,0.00027747496,0.00013396093,0.0025466366,0.65886706],"genre_scores_gemma":[0.0000060062716,0.0006172632,0.048458934,0.000052624244,0.000102890896,4.386188e-7,0.00022535986,0.00010149843,0.950435],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975304,0.00017154559,0.00015358829,0.0012110977,0.00037595083,0.0005574366],"domain_scores_gemma":[0.9960511,0.000080207115,0.00041369756,0.0029171992,0.0002831109,0.00025469443],"candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013473908,0.00045432203,0.00039359523,0.0017689526,0.00065051793,0.00016892537,0.0054300684,0.0006663395,0.0019893053],"category_scores_gemma":[0.000055972818,0.00058460137,0.00016959634,0.002442998,0.0005469695,0.0028078994,0.0024582548,0.00031809483,0.0006697146],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003379691,0.000058742782,0.0000116187775,0.000010016629,0.00007275751,0.000025126486,0.000051766976,0.000001481407,0.000005545905,0.6056117,0.3921997,0.0019481794],"study_design_scores_gemma":[0.0004912874,0.000057969595,0.000035733185,0.00004457819,0.00007866975,0.000008605357,0.00070018973,0.0001754278,0.000008663209,0.00045209916,0.99733484,0.00061191653],"about_ca_topic_score_codex":0.0016275349,"about_ca_topic_score_gemma":0.0062364857,"teacher_disagreement_score":0.6051596,"about_ca_system_score_codex":0.001565207,"about_ca_system_score_gemma":0.0003454016,"threshold_uncertainty_score":0.999951},"labels":[],"label_agreement":null},{"id":"W7087669997","doi":"10.5281/zenodo.17309009","title":"SuperDARN/pyDARNio: pyDARNio v2.0","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Serialization; Byte; Reading (process); File format; Field (mathematics)","score_opus":0.022690709769062584,"score_gpt":0.24656000596440594,"score_spread":0.22386929619534335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7087669997","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016865717,0.0004493402,0.32761422,0.0006957762,0.0002767938,0.00039537967,0.00049190904,0.008485488,0.6615894],"genre_scores_gemma":[0.0013764239,0.001302273,0.0529068,0.00058811606,0.00046191044,2.912212e-7,0.0047258865,0.01348703,0.9251513],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99722576,0.00025590806,0.0003046766,0.0010705158,0.00054803246,0.0005950891],"domain_scores_gemma":[0.99698526,0.000033834058,0.00021787369,0.0022985828,0.00032047508,0.00014395863],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004033551,0.00036017687,0.00034473132,0.0009504005,0.0011802709,0.0011641019,0.0065300683,0.00029629545,0.015740355],"category_scores_gemma":[0.0010197528,0.0003857073,0.00008770801,0.0012143684,0.00031348065,0.00041484335,0.007877862,0.0007060787,0.020327527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036663025,0.000043756416,1.9403898e-7,0.000058634814,0.000036257592,0.00003244354,0.000072487754,0.000005313001,0.000090564026,0.050621044,0.7628515,0.18618414],"study_design_scores_gemma":[0.00027343672,0.00010069007,0.000009228083,0.000116307834,0.0000107555325,0.000048661546,0.00005363169,0.00017417266,0.00013570255,0.0015107719,0.99719644,0.00037017761],"about_ca_topic_score_codex":0.0000450556,"about_ca_topic_score_gemma":0.0000013523309,"teacher_disagreement_score":0.2747074,"about_ca_system_score_codex":0.00023112881,"about_ca_system_score_gemma":0.000016699894,"threshold_uncertainty_score":0.9998728},"labels":[],"label_agreement":null},{"id":"W7092287796","doi":"10.5281/zenodo.17382307","title":"Iris: First-Class Multi-GPU Programming Experience in Triton","year":2025,"lang":"","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Simple (philosophy); Server; Data access; Control (management); Programming paradigm; Remote procedure call; Distributed memory","score_opus":0.0545556487976761,"score_gpt":0.2916561505302816,"score_spread":0.2371005017326055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7092287796","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021337152,0.0018219021,0.8123731,0.0020538503,0.00091486267,0.0035375569,0.0005220893,0.0067544933,0.17180876],"genre_scores_gemma":[0.14828141,0.014410831,0.48416287,0.0011628733,0.0012826002,0.000009355648,0.006170717,0.034850698,0.30966866],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.993986,0.00055286306,0.0009200481,0.00228331,0.00089142733,0.0013663177],"domain_scores_gemma":[0.99563706,0.00009471352,0.0005517708,0.0027927542,0.00066311704,0.00026057957],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00091207656,0.000705458,0.00067170995,0.0017785316,0.0026688837,0.002645332,0.009238514,0.0005428139,0.009303745],"category_scores_gemma":[0.0037245087,0.000812972,0.00013944319,0.0038012457,0.000972892,0.0011580563,0.012581789,0.0014410563,0.009906846],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006254962,0.0006993476,0.000008040075,0.0004173269,0.00006479012,0.00025956566,0.0040053804,0.00021709304,0.00030878067,0.012993255,0.10246538,0.8784985],"study_design_scores_gemma":[0.0011533827,0.00029048833,0.00009070462,0.0007405393,0.0000138915075,0.00006570372,0.0009610564,0.0061829183,0.00031621117,0.0002410065,0.98920166,0.00074242783],"about_ca_topic_score_codex":0.00012919703,"about_ca_topic_score_gemma":0.000011453034,"teacher_disagreement_score":0.8867363,"about_ca_system_score_codex":0.0009478193,"about_ca_system_score_gemma":0.00003178516,"threshold_uncertainty_score":0.9994321},"labels":[],"label_agreement":null},{"id":"W7092312891","doi":"10.5281/zenodo.17382306","title":"Iris: First-Class Multi-GPU Programming Experience in Triton","year":2025,"lang":"","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Simple (philosophy); Server; Data access; Control (management); Programming paradigm; Remote procedure call; Distributed memory","score_opus":0.0545556487976761,"score_gpt":0.2916561505302816,"score_spread":0.2371005017326055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7092312891","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021337152,0.0018219021,0.8123731,0.0020538503,0.00091486267,0.0035375569,0.0005220893,0.0067544933,0.17180876],"genre_scores_gemma":[0.14828141,0.014410831,0.48416287,0.0011628733,0.0012826002,0.000009355648,0.006170717,0.034850698,0.30966866],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.993986,0.00055286306,0.0009200481,0.00228331,0.00089142733,0.0013663177],"domain_scores_gemma":[0.99563706,0.00009471352,0.0005517708,0.0027927542,0.00066311704,0.00026057957],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00091207656,0.000705458,0.00067170995,0.0017785316,0.0026688837,0.002645332,0.009238514,0.0005428139,0.009303745],"category_scores_gemma":[0.0037245087,0.000812972,0.00013944319,0.0038012457,0.000972892,0.0011580563,0.012581789,0.0014410563,0.009906846],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006254962,0.0006993476,0.000008040075,0.0004173269,0.00006479012,0.00025956566,0.0040053804,0.00021709304,0.00030878067,0.012993255,0.10246538,0.8784985],"study_design_scores_gemma":[0.0011533827,0.00029048833,0.00009070462,0.0007405393,0.0000138915075,0.00006570372,0.0009610564,0.0061829183,0.00031621117,0.0002410065,0.98920166,0.00074242783],"about_ca_topic_score_codex":0.00012919703,"about_ca_topic_score_gemma":0.000011453034,"teacher_disagreement_score":0.8867363,"about_ca_system_score_codex":0.0009478193,"about_ca_system_score_gemma":0.00003178516,"threshold_uncertainty_score":0.9994321},"labels":[],"label_agreement":null},{"id":"W7098752761","doi":"","title":"Consumed with sex: The treatment of sex offender in risk society","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sex offender; Penology; Prison; Context (archaeology); Recidivism; Sex offense; Identity (music); Misdemeanor","score_opus":0.02766278033234756,"score_gpt":0.24367541963715905,"score_spread":0.2160126393048115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7098752761","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":[0.3796425,0.0003263407,0.61720216,0.0005102678,0.00003259588,0.00040056783,0.000010998806,0.00040310476,0.0014714587],"genre_scores_gemma":[0.79412127,0.0005030496,0.20474578,0.00006404943,0.0000039524684,0.000042666863,0.0000011362703,0.0000043337564,0.00051375467],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935174,0.000023278886,0.000114272385,0.0002186851,0.00013678978,0.0001552274],"domain_scores_gemma":[0.99901396,0.00013782326,0.00006524758,0.0007502957,0.000018042047,0.000014658303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057318877,0.000095905634,0.00013626416,0.000025096431,0.000072999654,0.0000073759643,0.000479191,0.000036850834,0.0000052870496],"category_scores_gemma":[0.000009177902,0.000048011978,0.000033705,0.00027253415,0.00028294278,0.00017160531,0.000100745914,0.000066330074,0.0000051826564],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000444808,0.0018103562,0.23764363,0.000021234213,0.0004140524,0.00024635703,0.036380373,0.0023818326,0.0011894464,0.03781566,0.009158279,0.6728943],"study_design_scores_gemma":[0.01993889,0.0073685576,0.19519731,0.00007244203,0.00011013308,0.0007866973,0.026066871,0.18311699,0.36152503,0.035642564,0.16737889,0.0027956148],"about_ca_topic_score_codex":0.00024828067,"about_ca_topic_score_gemma":0.00009133105,"teacher_disagreement_score":0.67009866,"about_ca_system_score_codex":0.000061011637,"about_ca_system_score_gemma":0.000043741722,"threshold_uncertainty_score":0.19578716},"labels":[],"label_agreement":null},{"id":"W7100664119","doi":"","title":"Printed in the USA 0730-7268/07 $12.00 +.00 RELEASE OF ELEMENTS TO NATURAL WATER FROM SEDIMENTS OF","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sediment; Slurry; Carbonate; Pore water pressure; Contamination; Water pollution; Adsorption; Groundwater","score_opus":0.017404715710564612,"score_gpt":0.27834094218912,"score_spread":0.26093622647855536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7100664119","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":[0.8035999,0.000024598181,0.19471037,0.00040882555,0.00016401244,0.00030000732,0.000015120125,0.00009196633,0.0006852049],"genre_scores_gemma":[0.87093174,0.000003235105,0.1284777,0.00041647002,0.000008864344,0.0000070185442,0.000012099935,0.0000050480353,0.00013781388],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983496,0.00003469118,0.000475472,0.00035210728,0.0004265694,0.00036155962],"domain_scores_gemma":[0.9986033,0.00011438581,0.0001064625,0.0010714141,0.000065991306,0.00003845395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045589116,0.00014228061,0.00019598442,0.00018807207,0.000028610872,0.000018473153,0.0019499722,0.00006062729,0.00007754014],"category_scores_gemma":[0.00012341642,0.00008250067,0.000037961934,0.00035210297,0.000072258474,0.0004114636,0.001016041,0.00018534604,0.00007159344],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004816742,0.001541307,0.11835276,0.000082903316,0.00021053517,0.00038386384,0.010221482,0.00042807317,0.6228714,0.040488467,0.0081500895,0.19678743],"study_design_scores_gemma":[0.00077407405,0.00018141477,0.044300877,0.000044889177,0.0000045299957,0.0000033014876,0.0004560193,0.0013307679,0.9428829,0.0040212106,0.005765088,0.00023494588],"about_ca_topic_score_codex":0.00047410055,"about_ca_topic_score_gemma":0.00038040648,"teacher_disagreement_score":0.32001147,"about_ca_system_score_codex":0.000059419846,"about_ca_system_score_gemma":0.000014575996,"threshold_uncertainty_score":0.3623566},"labels":[],"label_agreement":null},{"id":"W7113480626","doi":"","title":"Advancing File System Model Checking: Coverage, Framework, and Scalability","year":2025,"lang":"","type":"article","venue":"Academic Commons (Stony Brook University)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"File system; Scalability; Fork (system call); Correctness; File system fragmentation; Consistency (knowledge bases); Device file; Distributed File System; Container (type theory)","score_opus":0.013081808482924605,"score_gpt":0.24530113285299704,"score_spread":0.23221932437007242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7113480626","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":[0.019400854,0.0025287166,0.95570004,0.0020229474,0.00058402645,0.0008144717,0.00076969975,0.0015685469,0.016610708],"genre_scores_gemma":[0.9213799,0.0015791046,0.067197524,0.00036273763,0.000043908436,0.000007865418,0.00003181571,0.00004130788,0.009355812],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99507797,0.00031583122,0.0007730994,0.0020249856,0.00050477945,0.0013033575],"domain_scores_gemma":[0.99414825,0.0018074545,0.0005293712,0.0028968733,0.0002536805,0.00036434448],"candidate_categories":["metaepi_narrow","open_science","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0005911874,0.00078032457,0.0010124946,0.0013805691,0.0012185761,0.00016610086,0.004715595,0.001532437,0.000047162543],"category_scores_gemma":[0.0012499854,0.0009951241,0.00021285562,0.0036226744,0.0013058848,0.0027275258,0.009188643,0.004181587,0.000035335917],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014096654,0.00014321507,0.00471411,0.00085427216,0.00019186368,0.00025499891,0.0008733272,0.01511194,0.0005321973,0.83717227,0.015549505,0.12446136],"study_design_scores_gemma":[0.0014797066,0.00014479547,0.001365078,0.003931463,0.00031217476,0.00006895869,0.0022560433,0.8180099,0.0011558429,0.059624728,0.10996026,0.0016910171],"about_ca_topic_score_codex":0.00007493067,"about_ca_topic_score_gemma":0.00004386902,"teacher_disagreement_score":0.9019791,"about_ca_system_score_codex":0.0023328979,"about_ca_system_score_gemma":0.0007501958,"threshold_uncertainty_score":0.9997638},"labels":[],"label_agreement":null},{"id":"W7118205377","doi":"10.1145/3731599.3787540","title":"10.1145/3731599.3787540","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Key (lock); Component (thermodynamics); Term (time)","score_opus":0.007395886155651511,"score_gpt":0.1928147580154087,"score_spread":0.1854188718597572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7118205377","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017763923,0.00007731788,0.007482755,0.00095603074,0.000005181931,0.00016937059,0.000013090833,0.0020477427,0.9890709],"genre_scores_gemma":[0.00015586516,5.9988173e-7,0.047851525,0.00011406833,0.000029955057,0.000019517563,0.0000050967788,0.0000119921915,0.9518114],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988991,0.000017731956,0.00014757781,0.00040351375,0.00019987427,0.00033218053],"domain_scores_gemma":[0.99862033,0.000047121066,0.000028786326,0.0011834216,0.00003142366,0.00008891045],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00009257506,0.00014254858,0.00014411753,0.00010647252,0.00008485171,0.00008378929,0.0016528151,0.0000634235,0.86835563],"category_scores_gemma":[0.00006454143,0.00013844873,0.00003450022,0.00052485627,0.000053589803,0.00056956714,0.00041330716,0.00011459744,0.97402805],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068159898,0.000016823538,3.5301717e-8,0.0000012568986,0.000003414803,0.000021636002,0.000009046656,0.00012862064,0.000085154585,0.00014867402,0.09696052,0.902618],"study_design_scores_gemma":[0.00009764318,0.0000983046,0.000009972501,0.000006559976,0.0000019113597,0.000020455569,5.369544e-7,0.0022834442,0.0005065206,0.00047560877,0.9963133,0.00018576325],"about_ca_topic_score_codex":0.0000067387086,"about_ca_topic_score_gemma":9.875852e-8,"teacher_disagreement_score":0.90243226,"about_ca_system_score_codex":0.00004628762,"about_ca_system_score_gemma":0.000023727107,"threshold_uncertainty_score":0.5645775},"labels":[],"label_agreement":null},{"id":"W7118565579","doi":"10.1145/3725843.3786405","title":"10.1145/3725843.3786405","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Speculation; Key (lock); Information privacy; Session key","score_opus":0.007348184266763325,"score_gpt":0.19274182459250508,"score_spread":0.18539364032574177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7118565579","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018557436,0.00011973593,0.0092988135,0.0012034603,0.0000064671535,0.00018779303,0.000013909098,0.002296076,0.9866882],"genre_scores_gemma":[0.00025017056,6.461626e-7,0.041039262,0.00012046906,0.000031647178,0.000019967958,0.0000045080596,0.000012150688,0.9585212],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99890006,0.000017721413,0.00014772452,0.0004019166,0.0002000559,0.00033253743],"domain_scores_gemma":[0.9986246,0.000036680703,0.00002719129,0.0011905746,0.000031190146,0.000089742054],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00009408226,0.00014217192,0.00014384909,0.000106503474,0.00008459197,0.000082400766,0.0016611606,0.00006339378,0.83915037],"category_scores_gemma":[0.00006591885,0.00013852204,0.000034609322,0.0005230645,0.00005151836,0.00056379277,0.00041627648,0.00011477417,0.9745972],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068336994,0.000018381445,3.525633e-8,0.0000014379387,0.0000036196311,0.000021856975,0.000009474996,0.00014095346,0.000083756306,0.00015828667,0.075019926,0.92453545],"study_design_scores_gemma":[0.00009594866,0.00009949104,0.000010648919,0.000008337534,0.0000019190222,0.000019882855,4.858227e-7,0.0017132215,0.00048537637,0.00044650366,0.99693245,0.00018571355],"about_ca_topic_score_codex":0.0000059703457,"about_ca_topic_score_gemma":9.253831e-8,"teacher_disagreement_score":0.9243497,"about_ca_system_score_codex":0.000046650544,"about_ca_system_score_gemma":0.000021194684,"threshold_uncertainty_score":0.56487644},"labels":[],"label_agreement":null},{"id":"W7124136202","doi":"10.5281/zenodo.18239958","title":"Modern Storage for Modern HPC and AI Environments","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Xenon Pharmaceuticals (Canada)","funders":"","keywords":"RAID; Computer data storage; Workflow; Storage area network; Server; Flash (photography); Block (permutation group theory); NAND gate; Session (web analytics); Converged storage","score_opus":0.026700277592397344,"score_gpt":0.2558248959927594,"score_spread":0.22912461840036208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7124136202","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":[0.0014998914,0.001326244,0.9843869,0.002986132,0.00025172788,0.0012539298,0.00069627335,0.0012302095,0.006368668],"genre_scores_gemma":[0.96600634,0.0013924002,0.02184703,0.0010685939,0.000121317644,6.7346616e-7,0.0010246394,0.0020222245,0.006516802],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964155,0.00026847,0.00050329446,0.0014621741,0.0005043912,0.0008461747],"domain_scores_gemma":[0.99741197,0.00007656914,0.00021776369,0.0017847959,0.00029578767,0.00021312828],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007639337,0.0003954779,0.00036453558,0.0005546609,0.003878859,0.0020027324,0.0036309077,0.00022363127,0.0003953391],"category_scores_gemma":[0.0009991899,0.00046331208,0.00008511659,0.00081913325,0.00070523476,0.0014633143,0.009259356,0.0005864683,0.00070468883],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082760285,0.00023341697,0.0000016585968,0.00019006537,0.00010194126,0.000019843881,0.0014052087,0.0011821556,0.008361442,0.03688715,0.05194109,0.8995933],"study_design_scores_gemma":[0.0009959077,0.00032260251,0.00008974705,0.000083197345,0.0000343633,0.000034937715,0.00013488255,0.22682618,0.0012269064,0.024262693,0.74561054,0.00037805387],"about_ca_topic_score_codex":0.0000062990744,"about_ca_topic_score_gemma":3.1088672e-7,"teacher_disagreement_score":0.96450645,"about_ca_system_score_codex":0.00042464872,"about_ca_system_score_gemma":0.000013015379,"threshold_uncertainty_score":0.99978185},"labels":[],"label_agreement":null},{"id":"W7124159089","doi":"10.5281/zenodo.18239959","title":"Modern Storage for Modern HPC and AI Environments","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Xenon Pharmaceuticals (Canada)","funders":"","keywords":"RAID; Computer data storage; Workflow; Storage area network; Server; Flash (photography); Block (permutation group theory); NAND gate; Session (web analytics); Converged storage","score_opus":0.026700277592397344,"score_gpt":0.2558248959927594,"score_spread":0.22912461840036208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7124159089","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":[0.0014998914,0.001326244,0.9843869,0.002986132,0.00025172788,0.0012539298,0.00069627335,0.0012302095,0.006368668],"genre_scores_gemma":[0.96600634,0.0013924002,0.02184703,0.0010685939,0.000121317644,6.7346616e-7,0.0010246394,0.0020222245,0.006516802],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964155,0.00026847,0.00050329446,0.0014621741,0.0005043912,0.0008461747],"domain_scores_gemma":[0.99741197,0.00007656914,0.00021776369,0.0017847959,0.00029578767,0.00021312828],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007639337,0.0003954779,0.00036453558,0.0005546609,0.003878859,0.0020027324,0.0036309077,0.00022363127,0.0003953391],"category_scores_gemma":[0.0009991899,0.00046331208,0.00008511659,0.00081913325,0.00070523476,0.0014633143,0.009259356,0.0005864683,0.00070468883],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082760285,0.00023341697,0.0000016585968,0.00019006537,0.00010194126,0.000019843881,0.0014052087,0.0011821556,0.008361442,0.03688715,0.05194109,0.8995933],"study_design_scores_gemma":[0.0009959077,0.00032260251,0.00008974705,0.000083197345,0.0000343633,0.000034937715,0.00013488255,0.22682618,0.0012269064,0.024262693,0.74561054,0.00037805387],"about_ca_topic_score_codex":0.0000062990744,"about_ca_topic_score_gemma":3.1088672e-7,"teacher_disagreement_score":0.96450645,"about_ca_system_score_codex":0.00042464872,"about_ca_system_score_gemma":0.000013015379,"threshold_uncertainty_score":0.99978185},"labels":[],"label_agreement":null},{"id":"W7127357914","doi":"10.1109/ccece64018.2025.11364506","title":"Improving Locally Recoverable Codes Through Systematic Construction and Lee Metric Analysis","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; Kelowna General Hospital","funders":"","keywords":"Locality; Metric (unit); Upper and lower bounds; Hamming distance; Code (set theory); Event (particle physics); Limit (mathematics); Hamming code","score_opus":0.011738359708096786,"score_gpt":0.25261462267552126,"score_spread":0.24087626296742448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7127357914","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014563695,0.009267948,0.9842946,0.00038387466,0.00067014067,0.0007870011,0.000020069105,0.0006623166,0.0024576655],"genre_scores_gemma":[0.45987695,0.0007652262,0.53812224,0.0001698702,0.000008014724,0.000039715975,0.0000040611358,0.000008267142,0.0010056122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99639016,0.00021034459,0.0011001183,0.0013119716,0.00041644755,0.0005709821],"domain_scores_gemma":[0.99621034,0.00084806327,0.000604097,0.0019573574,0.00031631291,0.000063816646],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008008402,0.00043553306,0.0012788352,0.0017692213,0.0005332767,0.0009393111,0.0013033546,0.00029123743,0.000034230157],"category_scores_gemma":[0.0017946956,0.00039025323,0.00019484613,0.012383604,0.00052727276,0.002866326,0.001678137,0.0003742826,0.000019765062],"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":[0.000023534967,0.00014114192,0.0032738636,0.025416993,0.0044133756,0.000048027356,0.00036474166,0.009397445,0.0008377882,0.67464787,0.00027202014,0.28116322],"study_design_scores_gemma":[0.00064216874,0.00018436351,0.00018772282,0.0019378485,0.00291419,0.000039828654,0.0022183482,0.9427212,0.0066513373,0.04166493,0.00009694254,0.00074110803],"about_ca_topic_score_codex":0.0005908265,"about_ca_topic_score_gemma":0.00016844054,"teacher_disagreement_score":0.93332374,"about_ca_system_score_codex":0.0003509138,"about_ca_system_score_gemma":0.00021415917,"threshold_uncertainty_score":0.9998549},"labels":[],"label_agreement":null},{"id":"W7132886409","doi":"","title":"The Reliability and Error Mitigation of the Storage Stack","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Reliability (semiconductor); Process (computing); File system; Computer data storage; Data center; Stack (abstract data type); State (computer science); Electric power system; Fault (geology)","score_opus":0.023026816274623628,"score_gpt":0.3307437406917682,"score_spread":0.3077169244171446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132886409","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":[0.9661595,0.0015902488,0.020953761,0.0059717773,0.0030393528,0.0014446506,0.00006030443,0.00046805103,0.0003123515],"genre_scores_gemma":[0.97493094,0.0012637122,0.007288633,0.00003970543,0.000057056983,0.000117515796,0.000063641324,0.000065258675,0.016173506],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.99702555,0.00027412554,0.0005935444,0.00089508237,0.0007606791,0.0004510033],"domain_scores_gemma":[0.9942512,0.0010878067,0.0010431908,0.0031708623,0.00038799513,0.000058949212],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010236097,0.00039896765,0.0003927619,0.00009502431,0.0009226697,0.00019360815,0.00267032,0.0003607947,0.00000626209],"category_scores_gemma":[0.0031349647,0.00025176353,0.000136799,0.0013183705,0.001056391,0.00043419696,0.0012344201,0.0008080172,0.000026597701],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069050543,0.00052037375,0.0035184699,0.004424868,0.0005388394,0.00006159511,0.23785456,0.0190638,0.031951398,0.18605554,0.02428993,0.49103013],"study_design_scores_gemma":[0.0021014716,0.0011025293,0.23202176,0.0027037398,0.00046221216,0.000031422605,0.25611624,0.19288015,0.100235574,0.17400064,0.035008322,0.0033359102],"about_ca_topic_score_codex":0.00020244166,"about_ca_topic_score_gemma":0.0005713144,"teacher_disagreement_score":0.4876942,"about_ca_system_score_codex":0.00015581722,"about_ca_system_score_gemma":0.00028801462,"threshold_uncertainty_score":0.99999344},"labels":[],"label_agreement":null},{"id":"W7132886818","doi":"","title":"Examining Solid State Drives as Part of Modern Storage Stacks and Large-Scale Enterprise Storage Systems","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Reliability (semiconductor); Computer data storage; Key (lock); State (computer science); Stack (abstract data type); Field (mathematics); Solid-state; File system","score_opus":0.020987210583904427,"score_gpt":0.3136515915812499,"score_spread":0.2926643809973455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132886818","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":[0.4900998,0.023512091,0.48027828,0.00006042207,0.0030826365,0.0010333973,0.00042486424,0.00081618346,0.00069235545],"genre_scores_gemma":[0.9642293,0.003964199,0.008629586,0.00002870707,0.00013268893,0.00018768352,0.00036131984,0.00021663918,0.0222499],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99302495,0.00030581563,0.0014208782,0.0025959937,0.001299857,0.0013525211],"domain_scores_gemma":[0.9945605,0.0003920844,0.0014978731,0.0027766135,0.00042649606,0.00034647968],"candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0009069805,0.0012865919,0.0017400336,0.00093482755,0.00039435786,0.0008490265,0.0022563776,0.0007108947,0.00004493782],"category_scores_gemma":[0.00031725116,0.0013610568,0.0001922136,0.001007448,0.0004629342,0.0015777246,0.002056384,0.0015542652,0.00012441417],"study_design_candidate":"qualitative","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":[0.00065110804,0.0010091201,0.0006904187,0.013182561,0.0014985674,0.0029408152,0.7856849,0.05324878,0.033339545,0.006260768,0.0039417134,0.097551726],"study_design_scores_gemma":[0.0016378707,0.0019216791,0.00039267732,0.008694195,0.00049821124,0.00015882865,0.15885839,0.789726,0.011192681,0.0058976,0.017637072,0.0033847673],"about_ca_topic_score_codex":0.00015539082,"about_ca_topic_score_gemma":0.00016942086,"teacher_disagreement_score":0.73647726,"about_ca_system_score_codex":0.0003244837,"about_ca_system_score_gemma":0.00047231614,"threshold_uncertainty_score":0.9999886},"labels":[],"label_agreement":null},{"id":"W7287451","doi":"","title":"A Robust Storage System Architecture","year":2002,"lang":"en","type":"article","venue":"Head & Neck Surgery","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Data recovery; Robustness (evolution); Fault tolerance; Data loss; Computer data storage; Error detection and correction; Crash; Distributed data store; Mirroring; Computer hardware; Real-time computing; Distributed computing; Algorithm; Computer network; Operating system","score_opus":0.047499624182058886,"score_gpt":0.23008600371084412,"score_spread":0.18258637952878523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7287451","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":[0.061085638,0.0020333591,0.9270287,0.0016649908,0.0010984158,0.00022496091,0.000021552447,0.0045470027,0.0022953579],"genre_scores_gemma":[0.91300327,0.000058368412,0.08587821,0.00033019067,0.00013422988,0.00005387319,0.00000744259,0.000033591044,0.00050085573],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980465,0.000072622286,0.00032904986,0.00062150735,0.00035489985,0.0005754062],"domain_scores_gemma":[0.99765325,0.00038650114,0.00013827307,0.0016592594,0.00004824137,0.00011447015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023203845,0.0002466411,0.00039081668,0.0003194679,0.00017822061,0.0001226612,0.0009922658,0.0001318752,0.000035699646],"category_scores_gemma":[0.00020777587,0.00022533802,0.00013436326,0.0008297183,0.00008936629,0.0006155562,0.00047120443,0.00033891655,0.0004329282],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023450672,0.00037450233,0.0034986704,0.0007421114,0.000087248314,0.0054900595,0.0010017295,0.011427947,0.0008978157,0.06454788,0.23952045,0.67238814],"study_design_scores_gemma":[0.0013497211,0.00030116434,0.01088823,0.0021662575,0.000046736317,0.0047694673,0.0005322997,0.33343816,0.0041323258,0.005560129,0.63241607,0.0043994305],"about_ca_topic_score_codex":0.000015292837,"about_ca_topic_score_gemma":0.000010229595,"teacher_disagreement_score":0.8519176,"about_ca_system_score_codex":0.0001398517,"about_ca_system_score_gemma":0.0000273511,"threshold_uncertainty_score":0.91890174},"labels":[],"label_agreement":null},{"id":"W8439785","doi":"10.5555/2616448.2616472","title":"Bolt: data management for connected homes","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Overhead (engineering); Encryption; Computer data storage; Granularity; Data management; Cloud computing; Database; Class (philosophy); Computer network; Operating system; Artificial intelligence","score_opus":0.03584029722273756,"score_gpt":0.2842307635040174,"score_spread":0.2483904662812798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W8439785","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013033494,0.000036832582,0.9924332,0.0013915437,0.00015884795,0.00021329832,0.00002058899,0.0012963233,0.0043190503],"genre_scores_gemma":[0.061943956,0.000016817427,0.9367464,0.00039235555,0.000018911953,0.00002967708,0.00006687203,0.000005897575,0.00077907136],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913394,0.000008887078,0.00010434669,0.0004512951,0.000102653124,0.00019885073],"domain_scores_gemma":[0.99718124,0.00012009904,0.000037780705,0.0026121044,0.000024618232,0.00002414247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018175931,0.00008132662,0.0000954366,0.00006972349,0.000064775166,0.00007385793,0.0033033688,0.000028338292,0.00000785812],"category_scores_gemma":[0.0001494926,0.00006719645,0.000012603292,0.00018242397,0.00003587047,0.0007192131,0.0024525474,0.00003538175,0.000050877556],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010071027,0.00000998388,0.000009832559,0.000010414649,0.000007850674,0.0000012632245,0.0000047957124,0.0000072850735,0.00004498745,0.7433978,0.02631774,0.23018709],"study_design_scores_gemma":[0.0005594651,0.00008131105,0.00032467808,0.0000090617095,0.0000074826444,0.0000039995125,0.00006023932,0.1616501,0.0025431458,0.15633596,0.6781668,0.00025772798],"about_ca_topic_score_codex":0.0000026350197,"about_ca_topic_score_gemma":0.00000727094,"teacher_disagreement_score":0.6518491,"about_ca_system_score_codex":0.000012238233,"about_ca_system_score_gemma":0.0000043612135,"threshold_uncertainty_score":0.61385363},"labels":[],"label_agreement":null},{"id":"W84823787","doi":"","title":"Modular and efficient resource management in the exedra media server","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Modular design; Metadata; Server; SCSI; Variable bitrate; Structuring; Scheduling (production processes); Distributed computing; Variable (mathematics); Computer network; Operating system; Quality of service; Computer data storage","score_opus":0.015185764866937429,"score_gpt":0.23116957823990933,"score_spread":0.2159838133729719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W84823787","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":[0.18398567,0.00031022073,0.80220854,0.002711421,0.000050201586,0.00024319996,6.415372e-7,0.0003713108,0.010118788],"genre_scores_gemma":[0.9020821,0.00008258587,0.0969081,0.00071748445,0.000008655853,0.00002152705,0.0000013615237,0.0000041621447,0.00017403155],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918205,0.000028393675,0.00010088763,0.00027773518,0.00021955471,0.00019139178],"domain_scores_gemma":[0.9990487,0.0000658646,0.000021378855,0.0008391961,0.0000068563004,0.000017982531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002765122,0.00007947813,0.000065696106,0.00009617557,0.00004992789,0.000065945,0.0010823286,0.000027682767,0.0000048870625],"category_scores_gemma":[0.000018684794,0.000050756775,0.000010921889,0.00046702288,0.000059293976,0.00016263919,0.0007640568,0.00008955304,0.000017794244],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051987463,0.000105439496,0.0004003903,0.000012908518,0.000008762294,0.00079307327,0.0014847283,0.0076922383,0.000049725473,0.77170026,0.0015990096,0.21614824],"study_design_scores_gemma":[0.0020993997,0.0001403507,0.059238397,0.00006541793,0.00001676163,0.0003529072,0.008962087,0.45421886,0.0010097285,0.089166015,0.38371795,0.0010121034],"about_ca_topic_score_codex":0.000009824121,"about_ca_topic_score_gemma":0.000015020132,"teacher_disagreement_score":0.71809644,"about_ca_system_score_codex":0.000021204165,"about_ca_system_score_gemma":0.000002059601,"threshold_uncertainty_score":0.20698012},"labels":[],"label_agreement":null},{"id":"W8637698","doi":"10.1016/s0161-6420(96)30605-2","title":"Automated generic operating system installation and maintenance","year":2000,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"PQ Corporation (Canada)","funders":"","keywords":"Workstation; Operating system; Computer science; Microsoft Windows; Automation; Windows NT; Process (computing); System administrator; Software deployment; Software versioning; Software engineering; Embedded system; Software; Engineering","score_opus":0.01251523653731123,"score_gpt":0.22992017088438185,"score_spread":0.21740493434707062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W8637698","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":[0.13755459,0.000100852114,0.843692,0.000234627,0.000050831142,0.00011523722,0.0000017483011,0.007002264,0.011247885],"genre_scores_gemma":[0.6847739,0.000014223255,0.314855,0.00006516326,0.000005191512,0.000005481761,0.000001299109,0.000003039756,0.0002766667],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994039,0.000013285514,0.00011983449,0.00024045566,0.00007980684,0.00014274142],"domain_scores_gemma":[0.9995643,0.0000151008335,0.00002640884,0.00035007903,0.000021624455,0.00002246826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006789673,0.000072724535,0.00007726362,0.000039293114,0.00009595866,0.00009874195,0.00030890244,0.00003470743,0.000010064888],"category_scores_gemma":[0.000016963895,0.000058707235,0.000007077835,0.00025409384,0.00003123026,0.0007049354,0.00014447718,0.000044124536,0.000042346044],"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":[0.0000018727112,0.000012690695,0.0002577902,0.000036522895,0.000008424414,0.00005669957,0.00021415156,0.006618747,0.0051844753,0.27420506,0.0016277083,0.71177584],"study_design_scores_gemma":[0.00011157099,0.000019598032,0.0008433272,0.000018512352,6.702814e-7,0.00007049667,0.00006718714,0.99585557,0.0009541607,0.00019634231,0.001760981,0.00010156116],"about_ca_topic_score_codex":0.000016525246,"about_ca_topic_score_gemma":0.0000038219514,"teacher_disagreement_score":0.98923683,"about_ca_system_score_codex":0.000044771718,"about_ca_system_score_gemma":0.000010340542,"threshold_uncertainty_score":0.23940116},"labels":[],"label_agreement":null}]}