{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":229,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":229,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"95051c0e07aa","filters":{"topic":"Big Data and Digital Economy"}},"results":[{"id":"W3118820303","doi":"10.1007/s10462-020-09948-w","title":"Machine learning towards intelligent systems: applications, challenges, and opportunities","year":2021,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":132,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Government of Ontario","keywords":"Process (computing); The Internet; Mechanism (biology); Work (physics); Field (mathematics); Cognition","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.257928733914214,"gpt":0.3262040223463608,"spread":0.06827528843214675,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005724401,0.000575413,0.001142684,0.00242012,0.0005228671,0.004162244,0.001273555,0.002465674,0.002713451],"category_scores_gemma":[0.007598519,0.0003622812,0.0004736653,0.003856444,0.003378333,0.007538345,0.001457041,0.005051501,0.001185146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002090911,"about_ca_system_score_gemma":0.002738904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001265824,"about_ca_topic_score_gemma":0.002115831,"domain_scores_codex":[0.9977682,0.00095994,0.0001210652,0.0001557191,0.0008626715,0.0001324705],"domain_scores_gemma":[0.9853276,0.01115106,0.000494312,0.0003495564,0.002337064,0.0003404468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005176031,0.0001188388,0.001104604,0.005285035,0.00007998047,0.00008374922,0.0002294174,0.002452764,0.0006680003,0.2640148,0.05090259,0.6750085],"study_design_scores_gemma":[0.00002099157,0.0001087219,0.001601677,0.004517058,0.0000494625,0.0003550509,0.0004724205,0.005123286,0.0005537934,0.246034,0.7411237,0.00003975114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007408062,0.9582618,0.006118433,0.02831171,0.0009256668,0.000008346164,0.00001767714,0.00003083556,0.005584642],"genre_scores_gemma":[0.01189113,0.9763049,0.004198754,0.003442866,0.002893105,0.00001741802,0.00002536597,0.00001280835,0.001213568],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005724401,"threshold_uncertainty_score":0.03027385,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2117278106","doi":"10.1016/j.jcss.2012.11.002","title":"Security-aware optimization for ubiquitous computing systems with SEAT graph approach","year":2012,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":106,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Correctness; Graph; Computer security model; Theoretical computer science; Cryptography; Integer programming; Distributed computing; Computer security; Algorithm","authors":[{"name":"Meikang Qiu","is_ca":false},{"name":"Lei Zhang","is_ca":false},{"name":"Zhong Ming","is_ca":false},{"name":"Zhi Chen","is_ca":false},{"name":"Xiao Qin","is_ca":false},{"name":"Laurence T. Yang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02633655907656768,"gpt":0.2342976843090428,"spread":0.2079611252324751,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007300329,0.001083885,0.001334897,0.00094668,0.000600845,0.001040152,0.001279067,0.0008938403,0.005648986],"category_scores_gemma":[0.00249832,0.0004748982,0.0008408958,0.0008531083,0.0005284091,0.001687447,0.001008811,0.0009644015,0.0003335458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093608,"about_ca_system_score_gemma":0.00176492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00892455,"about_ca_topic_score_gemma":0.009123244,"domain_scores_codex":[0.9995283,0.0001662902,0.00001433752,0.00007339574,0.00009939937,0.0001183911],"domain_scores_gemma":[0.999204,0.0004887792,0.00006790105,0.00005850144,0.0001151471,0.00006567998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006673535,0.00006198756,0.0003080108,0.00004291366,0.00003534091,0.00003037694,0.00002180195,0.9623145,0.0008017271,0.01460973,0.001735911,0.0199709],"study_design_scores_gemma":[0.000004727294,0.00001363653,0.0000620014,0.000002237345,0.00000753581,0.00000492318,0.000009215843,0.9925908,0.0001127565,0.007004859,0.0001849275,0.000002494775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04641764,0.0003742795,0.9444575,0.0005719705,0.00008484416,0.000103028,0.0002095638,0.0005123081,0.007268892],"genre_scores_gemma":[0.8705921,0.0002847165,0.123391,0.0001522406,0.00005127433,0.0001017124,0.0002125311,0.0002033381,0.005011112],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00892455,"threshold_uncertainty_score":0.01889777,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008164459","doi":"10.1109/tetc.2015.2398824","title":"Data Allocation for Hybrid Memory With Genetic Algorithm","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Emerging Topics in Computing","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"St. Francis Xavier University","funders":"Division of Computer and Network Systems; National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Cache-only memory architecture; Parallel computing; Interleaved memory; Bottleneck; Uniform memory access; Flat memory model; Memory architecture; Static random-access memory; Memory management; Registered memory; Semiconductor memory; Latency (audio); Non-uniform memory access; Embedded system; Computer architecture; Computer hardware","authors":[{"name":"Meikang Qiu","is_ca":false},{"name":"Zhi Chen","is_ca":false},{"name":"Jianwei Niu","is_ca":false},{"name":"Ziliang Zong","is_ca":false},{"name":"Gang Quan","is_ca":false},{"name":"Xiao Qin","is_ca":false},{"name":"Laurence T. Yang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08209833086676656,"gpt":0.2968735042650074,"spread":0.2147751733982408,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003329361,0.0005256197,0.0006212246,0.000689373,0.0004138265,0.0007625954,0.001263755,0.0008780248,0.001805654],"category_scores_gemma":[0.0009127567,0.0002266501,0.0004425175,0.0007471082,0.0003790896,0.0006414014,0.0006021983,0.0003664383,0.0002219099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006439632,"about_ca_system_score_gemma":0.0008769117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006915258,"about_ca_topic_score_gemma":0.00505366,"domain_scores_codex":[0.9998108,0.00004142533,0.00001040229,0.00005037701,0.00004602654,0.00004108731],"domain_scores_gemma":[0.9997484,0.0001242476,0.00002413487,0.00002109316,0.00006835353,0.00001369619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001161319,0.00008963765,0.0009786279,0.00005332617,0.00005482503,0.00008090521,0.00006061676,0.8851178,0.004242801,0.005938515,0.001194821,0.1020721],"study_design_scores_gemma":[0.00001471819,0.00001838918,0.00005622047,0.000002041622,0.000006807399,0.00001201965,0.000006642505,0.9981883,0.0005179371,0.000921118,0.0002531609,0.000002696874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1223355,0.0006875256,0.8686375,0.0002957503,0.00007831485,0.00009293221,0.0000658245,0.00115557,0.006650991],"genre_scores_gemma":[0.7399202,0.0002306323,0.2548471,0.0002042732,0.00002965654,0.0002767669,0.0001326282,0.000062705,0.004296052],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006915258,"threshold_uncertainty_score":0.01375002,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2541757429","doi":"10.1109/bdcloud-socialcom-sustaincom.2016.14","title":"Dew Computing: The Complementary Piece of Cloud Computing","year":2016,"lang":"en","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Dew; Cloud computing; Computer science; Dew point; Computational science; Operating system; Meteorology; Physics","authors":[{"name":"Andy Rindos","is_ca":false},{"name":"Yingwei Wang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04051164631384358,"gpt":0.2568589844397109,"spread":0.2163473381258674,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001168923,0.000522743,0.000705214,0.001408517,0.001910774,0.007344363,0.0017006,0.001981774,0.006459265],"category_scores_gemma":[0.002987799,0.0003028873,0.000475633,0.004358064,0.002742261,0.01441574,0.005493061,0.003232878,0.00197247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001627332,"about_ca_system_score_gemma":0.002406385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001889835,"about_ca_topic_score_gemma":0.001293653,"domain_scores_codex":[0.99826,0.0003377166,0.00006651023,0.0003034075,0.0006824535,0.0003499771],"domain_scores_gemma":[0.9978994,0.0005159083,0.0001426721,0.0006542982,0.0004082987,0.0003794708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009102665,0.00006017883,0.001323298,0.0005186822,0.00003395953,0.0002093356,0.0003691012,0.001455622,0.002750186,0.7437646,0.02857313,0.2208509],"study_design_scores_gemma":[0.00001843694,0.00006210889,0.00145754,0.0003854335,0.00002364065,0.000771006,0.0006784956,0.01168586,0.003009905,0.3049251,0.6769213,0.00006116488],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03673381,0.06052158,0.4699968,0.06937665,0.007413811,0.0004740098,0.0007011049,0.001624581,0.3531578],"genre_scores_gemma":[0.6013295,0.07440741,0.2382177,0.01378927,0.009165009,0.0003560997,0.00102134,0.0008335946,0.06088008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007344363,"threshold_uncertainty_score":0.02160841,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2345186664","doi":"10.1109/tia.2016.2533599","title":"A Novel Technique for &lt;italic&gt;In Situ&lt;/italic&gt; Efficiency Estimation of Three-Phase IM Operating With Unbalanced Voltages","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Hydro-Québec; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Hydro-Québec","keywords":"Voltage; Induction motor; Power (physics); Engineering; Control theory (sociology); Electronic engineering; Electrical engineering; Computer science; Physics","authors":[{"name":"Maher Al-Badri","is_ca":true},{"name":"Pragasen Pillay","is_ca":true},{"name":"Pierre Angers","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0274401014456051,"gpt":0.2785586656552849,"spread":0.2511185642096798,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002807664,0.0006454745,0.0005250636,0.000900926,0.0003077859,0.0004950598,0.000781362,0.0006327737,0.001081958],"category_scores_gemma":[0.0009955965,0.000270115,0.0003142312,0.0006279045,0.0002738551,0.0006260128,0.0003619401,0.0005862335,0.0005917114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003791732,"about_ca_system_score_gemma":0.0004337287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264473,"about_ca_topic_score_gemma":0.002126446,"domain_scores_codex":[0.9996518,0.00004691179,0.00001859398,0.00009295854,0.0001653635,0.00002432311],"domain_scores_gemma":[0.9995558,0.0001020706,0.0001196324,0.00007013114,0.000138927,0.0000134663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001859577,0.0002326973,0.003599413,0.0001165539,0.00007521241,0.0001103308,0.0001729756,0.05844198,0.1634934,0.003959351,0.001981837,0.7676303],"study_design_scores_gemma":[0.00003901998,0.000223536,0.004466001,0.00001628184,0.00003528296,0.0004382624,0.0000459584,0.8732285,0.1151817,0.001948567,0.004340438,0.00003644492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01577966,0.00003401751,0.982347,0.00003735174,0.00002349274,0.0000317202,0.00002606139,0.0007554968,0.000965055],"genre_scores_gemma":[0.2870708,0.00005754337,0.7099699,0.00005890095,0.00002261741,0.00008071916,0.000127207,0.000117164,0.002495202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001264473,"threshold_uncertainty_score":0.003619432,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2482943584","doi":"10.1007/978-3-540-68825-9","title":"Advances in Artificial Intelligence","year":2008,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor; University of Regina; Concordia University; University of Alberta","funders":"","keywords":"Windsor; Computer science; Artificial intelligence; Operations research; Data science; Engineering","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03096667502955157,"gpt":0.2630952357029157,"spread":0.2321285606733641,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001052192,0.001141615,0.00138157,0.001791905,0.0006211539,0.00370015,0.001119315,0.001269707,0.04506485],"category_scores_gemma":[0.002217648,0.0004701837,0.0004287133,0.002560028,0.001661304,0.004684107,0.002097829,0.002805079,0.02743106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009103396,"about_ca_system_score_gemma":0.00115317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004746312,"about_ca_topic_score_gemma":0.0009446169,"domain_scores_codex":[0.9992577,0.0001281243,0.00003741695,0.00008924749,0.000441436,0.00004600064],"domain_scores_gemma":[0.9989618,0.0004546597,0.00004600149,0.00024471,0.0002036949,0.00008922259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002457864,0.00006105818,0.0001658009,0.0007031263,0.00003171743,0.00005701341,0.0001966234,0.0007762095,0.0006774401,0.2007407,0.3170941,0.4794716],"study_design_scores_gemma":[0.00000641453,0.00001950662,0.0002444031,0.0002707564,0.00001206635,0.0001089721,0.00006032364,0.0009929406,0.0002534487,0.09482634,0.9031987,0.000006094988],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001798993,0.2233989,0.05359568,0.01285212,0.01314023,0.00007517459,0.0003232215,0.0008441324,0.6939716],"genre_scores_gemma":[0.0317575,0.1909409,0.03390516,0.004158911,0.008688519,0.0001663014,0.000757064,0.0005014497,0.7291242],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04506485,"threshold_uncertainty_score":0.1507569,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1881217392","doi":"10.1108/ajim-02-2015-0027","title":"Computer science in Eastern Europe 1989-2014: a bibliometric study","year":2015,"lang":"en","type":"article","venue":"Aslib Journal of Information Management","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Czech; Originality; Library science; Web of science; Citation; Bibliometrics; Regional science; Subject (documents); Period (music); Political science; Social science; Geography; Sociology; Computer science; Law; MEDLINE","authors":[{"name":"Dalibor Fiala","is_ca":false},{"name":"Peter Willett","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04404927582855164,"gpt":0.270503925167112,"spread":0.2264546493385604,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00367785,0.000233881,0.0007150719,0.03950352,0.0009286962,0.003541874,0.000353444,0.0004870521,0.001989779],"category_scores_gemma":[0.01024169,0.0001582398,0.0004424211,0.0817899,0.0005618567,0.002392675,0.001729428,0.0002563633,0.0005305793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001910745,"about_ca_system_score_gemma":0.002133136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007331799,"about_ca_topic_score_gemma":0.007758073,"domain_scores_codex":[0.9970132,0.0005102654,0.0008365356,0.0002834068,0.001128732,0.0002279019],"domain_scores_gemma":[0.9892804,0.003492643,0.004305891,0.0003999145,0.002095532,0.0004256456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001753163,0.0001156779,0.906423,0.001439826,0.0003454506,0.0005182243,0.002789337,0.000584348,0.0002532256,0.002398812,0.003430915,0.08152585],"study_design_scores_gemma":[0.000005573861,0.00004272464,0.9835666,0.0002738269,0.0001051237,0.0002869066,0.001975353,0.0002272984,0.000202603,0.0001528752,0.01315369,0.000007437661],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9644578,0.01482523,0.0002922657,0.0005631204,0.00003728514,0.00006930178,0.006254142,0.00002765643,0.01347325],"genre_scores_gemma":[0.9801301,0.01097008,0.0006282051,0.0001114699,0.000106288,0.00004938641,0.006417583,0.00001042905,0.001576386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9604965,"threshold_uncertainty_score":0.01945055,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4246953298","doi":"10.1007/11538356","title":"Advances in Intelligent Computing","year":2005,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science","authors":[{"name":"De-Shuang Huang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01811664335471653,"gpt":0.2608122872404336,"spread":0.2426956438857171,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008340894,0.001058039,0.001271558,0.001514472,0.0007047954,0.003535376,0.001097694,0.001219981,0.04174859],"category_scores_gemma":[0.002010655,0.0004218396,0.0004118555,0.002206322,0.001513175,0.005306197,0.001913362,0.002249637,0.02202725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008293759,"about_ca_system_score_gemma":0.000882207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004480407,"about_ca_topic_score_gemma":0.0008504182,"domain_scores_codex":[0.9993672,0.00009208645,0.0000311385,0.00008212482,0.0003804632,0.00004707791],"domain_scores_gemma":[0.9991799,0.0003239022,0.00003180989,0.000199848,0.0001930552,0.00007149496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002482095,0.00005812624,0.0001532214,0.0005510547,0.00002337374,0.00004922714,0.0001989092,0.0008622475,0.0009737915,0.2407054,0.2587338,0.4976659],"study_design_scores_gemma":[0.000005865811,0.00002142067,0.0002669498,0.000194661,0.00001394793,0.0001192804,0.00006370342,0.001927247,0.0004906992,0.1087836,0.8881045,0.000008091184],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002755194,0.2311762,0.09529696,0.01367469,0.01364747,0.00009040777,0.0003028015,0.001402793,0.6416536],"genre_scores_gemma":[0.04717261,0.1854773,0.0512386,0.003875815,0.008882357,0.0001530689,0.0008129501,0.0006169465,0.7017704],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04174859,"threshold_uncertainty_score":0.1396629,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4226393414","doi":"10.1007/978-981-16-8862-1","title":"Proceedings of Third International Conference on Communication, Computing and Electronics Systems","year":2022,"lang":"en","type":"book","venue":"Lecture notes in electrical engineering","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Electronics; Computer science; Engineering; Engineering ethics; Telecommunications; Systems engineering; Electrical engineering","authors":[{"name":"V. Bindhu","is_ca":false},{"name":"João Manuel R. S. Tavares","is_ca":false},{"name":"Ke-Lin Du","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0125615222946614,"gpt":0.2179797628683086,"spread":0.2054182405736472,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000701751,0.0006931125,0.0007202424,0.0006818291,0.0007190929,0.00286307,0.0007678183,0.000837605,0.1033703],"category_scores_gemma":[0.0006629349,0.0001675826,0.0004693926,0.0008853303,0.0003613869,0.001062194,0.0008263899,0.001036748,0.03938932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005047007,"about_ca_system_score_gemma":0.001608853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003586128,"about_ca_topic_score_gemma":0.006700794,"domain_scores_codex":[0.9996339,0.00004780467,0.0000178193,0.00005426286,0.0001825662,0.00006361333],"domain_scores_gemma":[0.9993147,0.0000604585,0.00001456458,0.0000740181,0.0003810505,0.0001552014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002281089,0.000206607,0.001017047,0.0002729779,0.0000399179,0.0002533203,0.0001333657,0.0009333146,0.008376452,0.007060276,0.5913476,0.390131],"study_design_scores_gemma":[0.00001543446,0.00009452364,0.002206575,0.00009768544,0.0000519464,0.0002691105,0.0002423625,0.004253442,0.004926645,0.003138404,0.9846853,0.00001859249],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03330586,0.04245043,0.1042099,0.01077992,0.08385025,0.0003809356,0.002261057,0.005439335,0.7173223],"genre_scores_gemma":[0.05356046,0.0127485,0.0180066,0.000983083,0.002775816,0.0001095066,0.003890869,0.000497542,0.9074275],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1033703,"threshold_uncertainty_score":0.3458082,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403650534","doi":"10.1007/s10676-024-09808-z","title":"Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies","year":2024,"lang":"en","type":"article","venue":"Ethics and Information Technology","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Content (measure theory); Ecosystem; Computer science; Data science; Information retrieval; World Wide Web; Internet privacy; Business; Ecology; Mathematics; Biology","authors":[{"name":"Alistair Knott","is_ca":false},{"name":"Dino Pedreschi","is_ca":false},{"name":"Toshiya Jitsuzumi","is_ca":false},{"name":"Susan Leavy","is_ca":false},{"name":"David Eyers","is_ca":false},{"name":"Tapabrata Chakraborti","is_ca":false},{"name":"Andrew Trotman","is_ca":false},{"name":"Sundar Sundareswaran","is_ca":false},{"name":"Ricardo Baeza‐Yates","is_ca":false},{"name":"Przemysław Biecek","is_ca":false},{"name":"Adrian Weller","is_ca":false},{"name":"Paul D. Teal","is_ca":false},{"name":"Subhadip Basu","is_ca":false},{"name":"Mehmet Haklıdır","is_ca":false},{"name":"Virginia Morini","is_ca":false},{"name":"Stuart Russell","is_ca":false},{"name":"Yoshua Bengio","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04298933103889412,"gpt":0.2701211972685472,"spread":0.227131866229653,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006421698,0.001823627,0.00164974,0.004778773,0.005608384,0.008931254,0.004517489,0.01840784,0.04934741],"category_scores_gemma":[0.167392,0.00119516,0.001280517,0.003892208,0.006275936,0.005553819,0.003545785,0.02267644,0.03248097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00722436,"about_ca_system_score_gemma":0.0110162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03525426,"about_ca_topic_score_gemma":0.03157793,"domain_scores_codex":[0.9889048,0.002185107,0.001624093,0.001554543,0.00490367,0.0008278342],"domain_scores_gemma":[0.8451731,0.036367,0.006772235,0.01092397,0.09603011,0.004733559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001746147,0.000002917838,0.00006610827,0.00009151147,0.000009023816,0.0001257222,0.0001211204,0.00003110927,0.00004050868,0.001962468,0.9946579,0.002874141],"study_design_scores_gemma":[0.00003188085,0.0000100275,0.0006242327,0.0004057283,0.00003459,0.0003196983,0.0003335079,0.0004237352,0.000444944,0.003877529,0.9934366,0.00005761985],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0003116737,0.0008499479,0.001435466,0.2137094,0.7742593,0.00003836583,0.001406947,0.0006798775,0.007309111],"genre_scores_gemma":[0.03775049,0.004690547,0.008152256,0.2558804,0.3875184,0.0003334647,0.001618711,0.002241253,0.3018144],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.04934741,"threshold_uncertainty_score":0.1650835,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388678284","doi":"10.29327/268346.7.15-15","title":"TEORIA CRÍTICA DA TECNOLOGIA EM ANDREW FEENBERG contribuições ao ensino de história em tempos de pós-pandemia","year":2023,"lang":"pt","type":"article","venue":"Revista Communitas","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Philosophy; Humanities","authors":[{"name":"Francisco Amarildo Freires dos Santos","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05593864718378017,"gpt":0.2975035287155712,"spread":0.241564881531791,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01293937,0.0005224588,0.0004894923,0.004633251,0.01255268,0.01791093,0.001380509,0.004245766,0.008181569],"category_scores_gemma":[0.03123706,0.0004313952,0.0003940625,0.007177273,0.03181891,0.01814348,0.005267129,0.006732255,0.001433727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01577603,"about_ca_system_score_gemma":0.01067086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04705913,"about_ca_topic_score_gemma":0.05027109,"domain_scores_codex":[0.9898088,0.00528125,0.0004147622,0.001188453,0.002665038,0.0006417243],"domain_scores_gemma":[0.9751474,0.01592826,0.001508992,0.002274245,0.004005746,0.00113533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003245799,0.00001531868,0.001381434,0.0001341567,0.000008092967,0.0001976881,0.0426357,0.0002186899,0.0001693659,0.8375959,0.08822979,0.02938145],"study_design_scores_gemma":[0.000005205286,0.000009060432,0.001163943,0.0004466368,0.000008719209,0.0002058765,0.0165468,0.0002310367,0.0002696769,0.09456088,0.886521,0.00003115033],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0299993,0.0496689,0.009235859,0.6314175,0.007890877,0.00004902939,0.0002133955,0.0001790157,0.2713461],"genre_scores_gemma":[0.7294951,0.06141055,0.006240359,0.04243593,0.007016177,0.0001514101,0.0001488524,0.0006975223,0.1524041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9874473,"threshold_uncertainty_score":0.1144636,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4226420445","doi":"10.1016/j.ipm.2022.102941","title":"Predictive intelligence in secure data processing, management, and forecasting","year":2022,"lang":"en","type":"article","venue":"Information Processing & Management","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Data science; Artificial intelligence","authors":[{"name":"Marek R. Ogiela","is_ca":false},{"name":"Wenny Rahayu","is_ca":false},{"name":"Isaac Woungang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04390366159766859,"gpt":0.2548047777355908,"spread":0.2109011161379223,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003181389,0.0006465532,0.0008833627,0.00166938,0.000885948,0.004797653,0.001123741,0.001850767,0.002174618],"category_scores_gemma":[0.009834256,0.0004850086,0.0005121524,0.002573607,0.004215804,0.006539922,0.001975179,0.00273242,0.0005037414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001756934,"about_ca_system_score_gemma":0.001302393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004208914,"about_ca_topic_score_gemma":0.002315544,"domain_scores_codex":[0.997862,0.0007848922,0.0001320919,0.0002858476,0.0007778129,0.0001573799],"domain_scores_gemma":[0.9946821,0.003706015,0.0003397877,0.0007475615,0.0004107486,0.0001137603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000667757,0.00007092946,0.00158497,0.0002077235,0.00005695056,0.0001785612,0.0002109621,0.07088427,0.0005327158,0.8268458,0.00684573,0.09251452],"study_design_scores_gemma":[0.000009049299,0.0000232007,0.0003709188,0.0000895961,0.00002022601,0.00007623644,0.0001005285,0.2546346,0.000619371,0.734796,0.009242115,0.00001820162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02560928,0.03828171,0.8618013,0.02130592,0.0016466,0.0001096124,0.0002103925,0.0006028395,0.05043232],"genre_scores_gemma":[0.8728087,0.022348,0.09356204,0.001004517,0.001969286,0.0001323247,0.0002139316,0.00008170996,0.007879482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004797653,"threshold_uncertainty_score":0.01682496,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2905549479","doi":"10.1017/9781108557122.012","title":"ABS: Big Data, Data Sovereignty and Digitization","year":2018,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Digitization; Data science; Indigenous; Big data; Sophistication; Computer science; Telecommunications; Sociology; Social science; Data mining","authors":[{"name":"Chidi Oguamanam","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1082802384379621,"gpt":0.2185100494068268,"spread":0.1102298109688647,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001937962,0.0006255175,0.000425805,0.002938269,0.002453899,0.009401876,0.001036938,0.002040916,0.02207268],"category_scores_gemma":[0.003916583,0.0004061402,0.0003171025,0.005883737,0.007910254,0.01197975,0.004438862,0.00495451,0.006382778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003810772,"about_ca_system_score_gemma":0.003910027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004301222,"about_ca_topic_score_gemma":0.004655864,"domain_scores_codex":[0.9981394,0.0004347662,0.00008098501,0.0001864041,0.001056427,0.0001020672],"domain_scores_gemma":[0.9974779,0.001681658,0.00007812615,0.0003209903,0.0003199435,0.0001213262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000554745,0.0000105297,0.00005914261,0.0002624469,0.000003446889,0.00006886819,0.001986669,0.0001703908,0.0001411024,0.7877111,0.1373235,0.07225741],"study_design_scores_gemma":[0.000001157538,0.000002046783,0.00008635828,0.0002729655,0.000001072125,0.00009105599,0.0003664419,0.00008266637,0.00007577187,0.08894194,0.9100739,0.000004545888],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001642814,0.1142393,0.02208848,0.04034784,0.007340823,0.0001229154,0.0004921569,0.000407503,0.8133181],"genre_scores_gemma":[0.05351813,0.1644532,0.0264813,0.02374006,0.01072523,0.0003516913,0.001217245,0.0010135,0.7184997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02207268,"threshold_uncertainty_score":0.07384044,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6986614003","doi":"","title":"A Profile of the Greenhouse Industry in British Columbia and Clues to Climate Change","year":2022,"lang":"en","type":"report","venue":"York University Digital Library (York University)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Climate change; Greenhouse; Greenhouse gas; Political economy of climate change; Global warming; Greenhouse effect","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02987576731286,"gpt":0.1800274498232162,"spread":0.1501516825103562,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002675448,0.0001419649,0.0001313653,0.003082062,0.005076905,0.002619583,0.0004243477,0.0005498902,0.004638267],"category_scores_gemma":[0.0006511044,0.0001770732,0.00007271414,0.008906344,0.0006701123,0.0008096888,0.0008310601,0.0006014053,0.0006536038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01318131,"about_ca_system_score_gemma":0.01868512,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9675764,"about_ca_topic_score_gemma":0.9914521,"domain_scores_codex":[0.9995233,0.00002734299,0.00001741407,0.00003332336,0.0001948992,0.0002036796],"domain_scores_gemma":[0.998763,0.00009865838,0.00009672451,0.00002202078,0.0006043979,0.0004153079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001265395,0.0001572288,0.6783204,0.0005668203,0.00002394262,0.003622258,0.09088649,0.0009220929,0.01063094,0.005778822,0.0735297,0.1354348],"study_design_scores_gemma":[0.000002192534,0.00002148166,0.7908738,0.000115671,0.000004550291,0.0003245332,0.1178017,0.0003161884,0.0004398239,0.0002520499,0.0898151,0.00003285171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8867372,0.001927378,0.0003656952,0.006564893,0.0000359057,0.0001073275,0.006891454,0.0000756536,0.09729446],"genre_scores_gemma":[0.9318028,0.003458414,0.0006030114,0.001113541,0.000009906702,0.00005263656,0.003773452,0.00004290579,0.05914337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03242356,"threshold_uncertainty_score":0.0956375,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7034200649","doi":"","title":"Spatial variation in soil organic carbon and stable carbon isotope signature in a pasture and a primary forest in central Panamá","year":2004,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Smithsonian Tropical Research Institute; Smithsonian Institution","keywords":"Pasture; Soil carbon; Spatial variability; Litter; Soil water; Soil test; Soil horizon; Carbon flux; Soil organic matter","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.007361693149792194,"gpt":0.1890789746459628,"spread":0.1817172814961706,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001687113,0.000103523,0.0001411728,0.0004843246,0.000464348,0.0005279143,0.0001895328,0.0002361867,0.001620417],"category_scores_gemma":[0.0003171799,0.000128683,0.0001134764,0.0006540371,0.0002484704,0.0002956624,0.0003953839,0.0001455236,0.0001795896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004322226,"about_ca_system_score_gemma":0.0001552143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05207596,"about_ca_topic_score_gemma":0.08835085,"domain_scores_codex":[0.9999226,0.00001214013,0.000005836132,0.00003095259,0.00001362486,0.00001487259],"domain_scores_gemma":[0.9998208,0.0000336083,0.00005786672,0.00001047754,0.0000409172,0.00003639858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002447056,0.0000505218,0.9865369,0.000016959,0.0000573986,0.0002324681,0.0009157071,0.00009520095,0.006038497,0.00004597554,0.0002191127,0.005546563],"study_design_scores_gemma":[0.000001495636,0.0000107181,0.9994312,0.000001461581,0.000004439033,0.00002518484,0.0002645143,0.00006826677,0.00004708159,0.000004453306,0.0001402573,9.049459e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994158,0.00006728302,0.00002349805,0.00002622882,0.000001979502,0.000001851917,0.0001220983,0.000003394658,0.0003378747],"genre_scores_gemma":[0.9993259,0.0000501273,0.00007333779,0.000007911618,0.000003322811,0.00000455985,0.0001729752,0.00000128812,0.0003606399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05207596,"threshold_uncertainty_score":0.1035457,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400882740","doi":"10.1109/icce59016.2024.10605106","title":"Intelligent Data Exchange [iDX] for 5Gbps Consumer Data Switch Shows Energy Savings Over 95%","year":2024,"lang":"en","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Energy exchange; Data exchange; Database; Geology","authors":[{"name":"Christopher Whittington","is_ca":false},{"name":"Hemant Arora","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1506638394345086,"gpt":0.3204036517161906,"spread":0.1697398122816819,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001867925,0.0004781744,0.0002052929,0.0002701073,0.0002576913,0.0003883035,0.0004101203,0.0002935485,0.010084],"category_scores_gemma":[0.0002090485,0.00009284176,0.0001263028,0.0003628861,0.0001663771,0.0007249494,0.0002216648,0.0002912173,0.001378001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003225072,"about_ca_system_score_gemma":0.0001990698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005350574,"about_ca_topic_score_gemma":0.001111912,"domain_scores_codex":[0.9998342,0.00001813969,0.000007213923,0.00003178382,0.000062799,0.00004575443],"domain_scores_gemma":[0.9998957,0.00002636338,0.0000142689,0.00002224115,0.00002412443,0.00001729992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002791418,0.0005085393,0.004500882,0.0003793147,0.00008918245,0.0006572767,0.000202153,0.004910345,0.7450764,0.008413631,0.03681815,0.1956527],"study_design_scores_gemma":[0.0001619089,0.001657444,0.009679428,0.00002496336,0.00005786656,0.0008852173,0.0001290708,0.0483007,0.8920221,0.001299002,0.04572909,0.00005323926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8734874,0.0009742549,0.05826871,0.0006977992,0.0003793054,0.0001172091,0.000799993,0.01029772,0.05497762],"genre_scores_gemma":[0.9681374,0.0002047343,0.01469466,0.0001612649,0.00002980172,0.00003202174,0.0009737058,0.0001673731,0.01559908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.010084,"threshold_uncertainty_score":0.03373438,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6966995111","doi":"10.5061/dryad.s4r94b0","title":"Data from: Effects of stand age, richness and density on productivity in subtropical forests in China","year":2019,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Productivity; Biodiversity; Species richness; Subtropics; Forest structure; Tropical and subtropical moist broadleaf forests; Forest ecology","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.030102573791063,"gpt":0.2634203488086063,"spread":0.2333177750175433,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113969,0.001310412,0.0008012387,0.003303148,0.0005747119,0.0008779951,0.001507103,0.0008132189,0.01087601],"category_scores_gemma":[0.003680113,0.0003196168,0.0008004679,0.005949214,0.0003444148,0.0006584646,0.001190387,0.0005665195,0.007482029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001523507,"about_ca_system_score_gemma":0.002367361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08639093,"about_ca_topic_score_gemma":0.1399807,"domain_scores_codex":[0.9992442,0.00008580898,0.0001216005,0.0002002205,0.000177752,0.0001704058],"domain_scores_gemma":[0.9982193,0.000298775,0.0002653472,0.0003209364,0.0006780242,0.0002175023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004628146,0.0001874881,0.1085548,0.002281202,0.0002592332,0.0002411673,0.0002994697,0.002342459,0.0009257231,0.0008282842,0.8615226,0.02209487],"study_design_scores_gemma":[0.0005463961,0.00008267145,0.6364506,0.0004873682,0.000169992,0.000187138,0.0005189356,0.003646615,0.001257734,0.001072804,0.3554629,0.0001167194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008621586,0.0001196739,0.0000868713,0.000114248,0.00002867994,0.00002343751,0.9902725,0.0001931937,0.0005398199],"genre_scores_gemma":[0.008736838,0.00007744931,0.0002834867,0.00003241727,0.000009999557,0.0001114236,0.990149,0.00001928136,0.0005800221],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08639093,"threshold_uncertainty_score":0.1717762,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415970235","doi":"10.1109/pci66488.2025.11219856","title":"Research Trends and Thematic Insights from the Most Cited Cybernetics Studies in the Last Ten Years Using Text Mining and Bibliometric Analysis","year":2025,"lang":"","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Cybernetics; Bibliometrics; Subject (documents); Field (mathematics); Thematic map; Publishing; China; Citation analysis; Web of science","authors":[{"name":"Muhammet Damar","is_ca":false},{"name":"Muhammet Ali Aydin","is_ca":false},{"name":"Melih Takyaci","is_ca":false},{"name":"Samet Özkök","is_ca":false},{"name":"Efendi Nasıbov","is_ca":false},{"name":"Ömer Aydın","is_ca":false},{"name":"Fatih Safa Erenay","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1967380786803535,"gpt":0.3886421581164499,"spread":0.1919040794360964,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003683787,0.0004059174,0.0007336113,0.07650745,0.0008288386,0.004347095,0.000567087,0.0004348379,0.001478255],"category_scores_gemma":[0.01358005,0.0001399533,0.00096847,0.0915383,0.0005276763,0.002599281,0.001260959,0.0005551859,0.0005865138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097781,"about_ca_system_score_gemma":0.001735581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00361969,"about_ca_topic_score_gemma":0.007243235,"domain_scores_codex":[0.9967757,0.0004360996,0.0007196564,0.0004141875,0.001465435,0.0001889997],"domain_scores_gemma":[0.9806263,0.007586394,0.005999014,0.000488743,0.004503609,0.0007959242],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002995099,0.0001855533,0.6802217,0.01026099,0.00113242,0.001501572,0.01144988,0.001740254,0.007753238,0.005460121,0.01035079,0.2696439],"study_design_scores_gemma":[0.00001746598,0.0001968038,0.9031352,0.002888787,0.0008296099,0.002154346,0.01411712,0.003097785,0.003907211,0.002184433,0.06739792,0.00007338376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8944475,0.0573743,0.002985718,0.001720757,0.0002938575,0.0001573808,0.0183194,0.0001806664,0.02452048],"genre_scores_gemma":[0.9308749,0.04124029,0.008707548,0.000221781,0.0004872615,0.0002735737,0.01572635,0.00005831824,0.002409954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9963162,"threshold_uncertainty_score":0.01948196,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6891597415","doi":"10.4224/12340981","title":"Design ice pressure-area relationships: Molikpaq data","year":2005,"lang":"en","type":"report","venue":"NPARC","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Sea ice; Data collection; Feature (linguistics); Data processing","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.3065564853571567,"gpt":0.3222951556578262,"spread":0.01573867030066955,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001007753,0.0004198582,0.0002610394,0.000732251,0.0005158163,0.001594925,0.001338143,0.0004225057,0.02781169],"category_scores_gemma":[0.006165073,0.0003733663,0.000415601,0.001645269,0.0002890098,0.002047013,0.0005929216,0.0007466943,0.007767112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007794248,"about_ca_system_score_gemma":0.001385758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01221269,"about_ca_topic_score_gemma":0.01685842,"domain_scores_codex":[0.9994142,0.0001436614,0.00003073921,0.0001294778,0.0002144993,0.00006753009],"domain_scores_gemma":[0.9986315,0.0002709047,0.0000741102,0.0002539377,0.0006996627,0.00006977676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0009240533,0.0003223468,0.03186285,0.0006540448,0.0001757294,0.0001576682,0.0004549707,0.1553999,0.008777489,0.04583687,0.5312324,0.2242017],"study_design_scores_gemma":[0.0004717282,0.0002153849,0.01305286,0.00007383696,0.00009091511,0.00008408874,0.0006025371,0.5371964,0.02118239,0.02051991,0.4064401,0.00006981355],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09540617,0.0003829023,0.5711669,0.00396554,0.00105281,0.002229487,0.1587245,0.03120132,0.1358703],"genre_scores_gemma":[0.5607299,0.0004749707,0.2926548,0.0008241432,0.000246259,0.00148271,0.105575,0.005780021,0.03223205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02781169,"threshold_uncertainty_score":0.09303945,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2913478607","doi":"","title":"Proceedings of the First international conference on High Performance Computing and Communications","year":2005,"lang":"en","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Telecommunications; Political science; Data science","authors":[{"name":"Laurence T. Yang","is_ca":true},{"name":"Omer Rana","is_ca":false},{"name":"Beniamino Di Martino","is_ca":false},{"name":"Jack Dongarra","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04317538632867216,"gpt":0.2508997846460475,"spread":0.2077243983173754,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001376494,0.0008500476,0.001163437,0.0008657521,0.001418454,0.004586596,0.0007927929,0.001322369,0.07642086],"category_scores_gemma":[0.001892685,0.0002320096,0.0005349834,0.0009499477,0.0007643386,0.001994172,0.001082897,0.002040251,0.02906714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007412367,"about_ca_system_score_gemma":0.001628305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003669645,"about_ca_topic_score_gemma":0.009703824,"domain_scores_codex":[0.9993368,0.0001129452,0.00002754192,0.00009184965,0.0002980501,0.0001327667],"domain_scores_gemma":[0.9975024,0.0003788818,0.00005852269,0.0002480834,0.001138686,0.0006734614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006283035,0.0003127939,0.001855587,0.0002220185,0.00006296729,0.0002831494,0.0001797336,0.0006726235,0.005225729,0.009733476,0.7525851,0.2282386],"study_design_scores_gemma":[0.00005216493,0.000138027,0.00276673,0.000102876,0.00007881838,0.0002631344,0.0002987157,0.006149797,0.005156063,0.004685509,0.9802787,0.00002944211],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04192526,0.04079194,0.1177781,0.04422449,0.1841534,0.0005979131,0.001853652,0.003929196,0.5647461],"genre_scores_gemma":[0.1071922,0.02149048,0.02341395,0.003755079,0.02027758,0.0001975973,0.003946255,0.0009348128,0.818792],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07642086,"threshold_uncertainty_score":0.2556533,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3173483327","doi":"10.4000/ere.7428","title":"La foire aux sciences, une expérience d’éducation scientifique et environnementale dans la formation des éducatrices et éducateurs en petite enfance","year":2021,"lang":"fr","type":"article","venue":"Éducation relative à l environnement","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","authors":[{"name":"Genina Calafell","is_ca":false},{"name":"Neus Banqué","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07420955227350473,"gpt":0.343168920871637,"spread":0.2689593685981323,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01263571,0.0004197898,0.0005112832,0.001476594,0.01023021,0.009157924,0.0009920265,0.002791,0.007868282],"category_scores_gemma":[0.01317699,0.0004301579,0.0005664647,0.001479314,0.02457066,0.008373878,0.01046852,0.006087358,0.001280076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004393771,"about_ca_system_score_gemma":0.008202533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006189293,"about_ca_topic_score_gemma":0.01169399,"domain_scores_codex":[0.9915646,0.0053494,0.0002290497,0.0007309054,0.001455604,0.0006704729],"domain_scores_gemma":[0.9822693,0.0109741,0.001196351,0.001097331,0.002004363,0.002458667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006102577,0.0001296843,0.006036449,0.0004825057,0.00002581026,0.001048222,0.6476848,0.0002473706,0.003566617,0.2824417,0.006652485,0.05162342],"study_design_scores_gemma":[0.00001343334,0.0001964751,0.007441156,0.0007154284,0.00001950247,0.00133546,0.259799,0.0001941027,0.002342184,0.04956796,0.6783002,0.00007505048],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4774512,0.01935043,0.0589343,0.1135946,0.002375256,0.000157707,0.0002294874,0.0002556666,0.3276513],"genre_scores_gemma":[0.9434434,0.006374127,0.0100853,0.005010498,0.0003515841,0.0001263344,0.00006961278,0.00009620032,0.03444294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01263571,"threshold_uncertainty_score":0.06682479,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410349087","doi":"10.37256/cnc.3120256490","title":"Dynamic Real Time Framework for Abnormal Detection of IMS Core in Kubernetes Cloud","year":2025,"lang":"en","type":"article","venue":"Computer Networks and Communications","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure","funders":"","keywords":"Cloud computing; Computer science; Core (optical fiber); Operating system; Telecommunications","authors":[{"name":"Rasel Chowdhury","is_ca":true},{"name":"Saad Inshi","is_ca":true},{"name":"Hakima Ould‐Slimane","is_ca":true},{"name":"Chamseddine Talhi","is_ca":true},{"name":"Azzam Mourad","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01850859804395306,"gpt":0.2699859643178218,"spread":0.2514773662738688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006018144,0.0006023427,0.000448409,0.0007456494,0.000384534,0.0009977521,0.001089002,0.0004795285,0.0006310591],"category_scores_gemma":[0.001781031,0.0001865594,0.0003943968,0.0004678284,0.0004467768,0.0009543838,0.0009220884,0.0006829379,0.0002256135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050116,"about_ca_system_score_gemma":0.0009455699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01259291,"about_ca_topic_score_gemma":0.01463046,"domain_scores_codex":[0.9996166,0.00005948439,0.00002254117,0.0001402221,0.00009344021,0.00006769344],"domain_scores_gemma":[0.9995516,0.0001118357,0.00008415838,0.00005727255,0.0001536646,0.00004145929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003891459,0.0001885257,0.01959967,0.0001016808,0.00009650896,0.0006318445,0.0003054973,0.7417108,0.01797267,0.01429973,0.003637868,0.2010662],"study_design_scores_gemma":[0.000001511683,0.00000932762,0.0004245845,0.000001536052,0.000003498185,0.00002358523,0.00001972346,0.9968013,0.0009683733,0.001533093,0.0002094759,0.000004000787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0658263,0.0001751291,0.9289629,0.0001968496,0.00004935698,0.00004483841,0.0001616965,0.003418448,0.001164408],"genre_scores_gemma":[0.902758,0.00009380699,0.09578388,0.00007355437,0.00002957643,0.00004641728,0.0001948358,0.00008557987,0.0009343324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01259291,"threshold_uncertainty_score":0.0250392,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7106845579","doi":"10.1080/21598282.2025.2579900","title":"DeepSeek Upends Silicon Valley’s Sci-Fin-Fi Business Model","year":2025,"lang":"en","type":"article","venue":"International Critical Thought","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Business model; Silicon valley; Process (computing); Production (economics); Work (physics)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03090565157694173,"gpt":0.3144980483041405,"spread":0.2835923967271987,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008136672,0.0006499345,0.0005417934,0.0009791595,0.007693303,0.01322814,0.002098788,0.02340473,0.005589758],"category_scores_gemma":[0.02070397,0.0004316895,0.0009883665,0.001063543,0.02000425,0.00782217,0.00363767,0.03306863,0.001579772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01361941,"about_ca_system_score_gemma":0.01418772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04235494,"about_ca_topic_score_gemma":0.05295153,"domain_scores_codex":[0.9935392,0.001520798,0.0002275576,0.001201916,0.00238831,0.001122265],"domain_scores_gemma":[0.9842741,0.01237249,0.0004363395,0.0005100177,0.001833376,0.0005736001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002751243,0.000009088423,0.0001459477,0.00005924198,0.000007007781,0.0001306808,0.001939635,0.0001496018,0.0001197053,0.5788693,0.4145566,0.003985566],"study_design_scores_gemma":[0.00004228818,0.00002285588,0.0003994507,0.0002270289,0.000006811767,0.00005653794,0.001191805,0.0003766048,0.000369709,0.07575965,0.9215025,0.00004485351],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002896537,0.002470328,0.001003269,0.9279558,0.005552638,0.00001196631,0.000105889,0.0000570602,0.0599465],"genre_scores_gemma":[0.1280485,0.002191189,0.001107324,0.8109191,0.00683908,0.00008132578,0.00009934147,0.0001367192,0.05057743],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04235494,"threshold_uncertainty_score":0.09881622,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2625551154","doi":"10.1002/cpe.4215","title":"Special issue on Big Data Security and Intelligent Data in Clouds (<scp>BDS‐IDC</scp>)","year":2017,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Big data; Cloud computing; Computer science; Cloud computing security; Computer security; Implementation; Data security; Data science; Encryption; Data mining; Software engineering; Operating system","authors":[{"name":"Houcine Hassan","is_ca":false},{"name":"Laurence T. Yang","is_ca":true},{"name":"Meikang Qiu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1400249338473722,"gpt":0.3732381384231027,"spread":0.2332132045757304,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002556569,0.002538912,0.003137826,0.004380303,0.003233466,0.01121437,0.003145522,0.005582357,0.09157542],"category_scores_gemma":[0.006890659,0.0009647999,0.001672346,0.003038628,0.001414241,0.005806357,0.003046829,0.005458464,0.05163288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002618167,"about_ca_system_score_gemma":0.003323217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002078701,"about_ca_topic_score_gemma":0.004296619,"domain_scores_codex":[0.9964442,0.0003090214,0.0003460585,0.0006175584,0.00183964,0.0004435608],"domain_scores_gemma":[0.9859836,0.0026658,0.001145364,0.0008115593,0.005879634,0.00351403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003864115,0.00003031744,0.0001134472,0.0002405466,0.00001247601,0.00006775876,0.00001076129,0.00005923482,0.000312656,0.0004493351,0.9807034,0.01796147],"study_design_scores_gemma":[0.00001149246,0.00004245936,0.0004962995,0.000186563,0.0000117562,0.0001508491,0.00001868664,0.0002396534,0.0002252963,0.0004816751,0.9981213,0.00001389439],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0004884111,0.01195343,0.001325232,0.02258261,0.9249796,0.0002386845,0.001075757,0.0006934112,0.03666293],"genre_scores_gemma":[0.002010707,0.01477383,0.0007225449,0.01284913,0.872411,0.000193271,0.001575696,0.0006670879,0.09479674],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.09157542,"threshold_uncertainty_score":0.3063503,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409882804","doi":"10.1109/jiot.2025.3564766","title":"Fault-Tolerant Differential Privacy Routing of Human–Cyber–Physical Fusion Systems for Large Language Models Security","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Fok Ying Tung Education Foundation; Natural Science Foundation of Fujian Province; National Natural Science Foundation of China","keywords":"Computer science; Differential privacy; Computer security; Cyber-physical system; Routing (electronic design automation); Computer network; Distributed computing; Data mining","authors":[{"name":"Limei Lin","is_ca":false},{"name":"Yanze Huang","is_ca":false},{"name":"Xiaoding Wang","is_ca":false},{"name":"Sahil Garg","is_ca":true},{"name":"Sherif Moussa","is_ca":false},{"name":"Mubarak Alrashoud","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02140999359477254,"gpt":0.2831859857595689,"spread":0.2617759921647964,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001771638,0.0005644041,0.0008257783,0.0005160202,0.001211592,0.001699936,0.001426256,0.001247854,0.002540743],"category_scores_gemma":[0.006211206,0.0003886727,0.001194533,0.0005403133,0.001760471,0.002645392,0.003404783,0.00162694,0.0003718579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002488464,"about_ca_system_score_gemma":0.001493287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003243351,"about_ca_topic_score_gemma":0.002318562,"domain_scores_codex":[0.9983493,0.0005093617,0.00008072951,0.0004326436,0.000404679,0.0002233878],"domain_scores_gemma":[0.9975086,0.001345477,0.00031795,0.000477397,0.0002376746,0.0001127717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001365596,0.00004214899,0.0006548856,0.00006566295,0.00005083392,0.0002403851,0.0002862471,0.6808394,0.003753494,0.2832814,0.002184247,0.02846477],"study_design_scores_gemma":[0.000005970466,0.0000120583,0.00004979287,0.000002771159,0.00000483079,0.0000240934,0.00001295005,0.942517,0.0005199144,0.05624964,0.0005943968,0.000006599294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02724794,0.0002040486,0.9680769,0.0007448004,0.00005853773,0.00005232592,0.0000793744,0.0003249014,0.003211067],"genre_scores_gemma":[0.9246704,0.0002263765,0.07020921,0.0002676125,0.00005827091,0.0001286311,0.0001578753,0.00007266102,0.004208929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003243351,"threshold_uncertainty_score":0.01805514,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6926675834","doi":"10.25384/sage.c.5811214.v1","title":"Associations Between Video Game Engagement and ADHD Symptoms in Early Adolescence","year":2022,"lang":"en","type":"other","venue":"Sage Journals Data","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Video game; Association (psychology); Causality (physics); Longitudinal study; Cohort; Sample (material); Attention deficit hyperactivity disorder","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.092571741104987,"gpt":0.3083392892195198,"spread":0.2157675481145328,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006000526,0.0002442859,0.0002658242,0.001361226,0.0005344595,0.0009972217,0.0006905839,0.0003793466,0.002206935],"category_scores_gemma":[0.003319824,0.0002005375,0.0003798831,0.00129219,0.0003212148,0.0002614921,0.0005385549,0.0007432161,0.0001685913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002088875,"about_ca_system_score_gemma":0.00283206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5472897,"about_ca_topic_score_gemma":0.6996917,"domain_scores_codex":[0.9995959,0.00004959786,0.00002369502,0.00007044701,0.0001392469,0.0001210225],"domain_scores_gemma":[0.9975298,0.0003169907,0.001042499,0.00007280995,0.0005443546,0.0004935128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001948385,0.00002877767,0.9982409,0.000009135539,0.00001740648,0.00001692663,0.00008149953,0.00002158997,0.00005075539,0.00002049798,0.00009739603,0.001395543],"study_design_scores_gemma":[7.683543e-7,0.00000786101,0.9997111,0.000007982558,0.000006882287,0.00001387124,0.00008134943,0.00004507249,0.00001704754,0.000006680135,0.0001004648,8.909904e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963786,0.0003642804,0.00007393173,0.0001038323,0.00000575936,0.00001950064,0.00171474,0.00000760221,0.001331865],"genre_scores_gemma":[0.9971305,0.0003591369,0.0002063745,0.00002753195,0.000004707431,0.00001885839,0.001650856,0.000003335608,0.0005987148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5472897,"threshold_uncertainty_score":0.9107529,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6957912628","doi":"10.6068/dp14ba878325623","title":"Trend 1999 - 2003. Statistics Canada. CANSIM: Culture and Leisure - Performing and Visual Arts | Country: Canada | Table: Canadian summary characteristics of performing arts, by discipline and company size | Variable: Tour performances in other countries, Music, Total, all company sizes | Units: #, 1999-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-050.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Census; The arts; Performing arts; Statistics education; Descriptive statistics; Official statistics; Population; Economic statistics","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02151788067403323,"gpt":0.2322544598384556,"spread":0.2107365791644224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001654335,0.002898737,0.002908254,0.009446342,0.003819139,0.006000978,0.005706643,0.001521222,0.0965118],"category_scores_gemma":[0.01557443,0.001589784,0.002166729,0.04351285,0.0007668008,0.00292525,0.002458241,0.00319628,0.06609188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04257328,"about_ca_system_score_gemma":0.114885,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993705,"about_ca_topic_score_gemma":0.9925461,"domain_scores_codex":[0.995836,0.0002279198,0.0004105217,0.0006347539,0.001798205,0.001092531],"domain_scores_gemma":[0.9699377,0.001028169,0.001003558,0.0009203616,0.02563599,0.001474211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002459713,0.000005538216,0.001036888,0.0002028439,0.00001802919,0.000007101221,0.0000193732,0.00008730674,0.000009459742,0.0003087875,0.9970307,0.001249322],"study_design_scores_gemma":[0.000140701,0.00001085659,0.02239639,0.0007650375,0.0000647647,0.00002845053,0.0005683542,0.0004629899,0.0001957361,0.0006000947,0.9746787,0.00008798025],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004816487,0.00004049312,0.0000184448,0.00009909699,0.00002369193,0.000008917896,0.9989653,0.00005054886,0.0007453071],"genre_scores_gemma":[0.0006253751,0.0001887012,0.0002133673,0.0001107038,0.0000159554,0.00007241465,0.9956001,0.00008773972,0.003085572],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0965118,"threshold_uncertainty_score":0.3228642,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6889785898","doi":"10.26092/elib/2897","title":"Climate - cryosphere interactions for past, present and future climates with the comprehensive Earth system model AWI-ESM","year":2023,"lang":"en","type":"article","venue":"Media (https://www.suub.uni-bremen.de/)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Ice-sheet model; Ice sheet; Cryosphere; Climate model; Transient climate simulation; Glacial period; Forcing (mathematics); Lead (geology); Earth system science; Climate change","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03273593381980093,"gpt":0.25199798140757,"spread":0.2192620475877691,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000535101,0.0009163129,0.0007601966,0.0007093452,0.0005904712,0.0009077183,0.001425365,0.001027599,0.006455707],"category_scores_gemma":[0.001112112,0.0004154365,0.001238679,0.001270791,0.0003176605,0.0007620197,0.0007243835,0.0009946171,0.0006756062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166877,"about_ca_system_score_gemma":0.001735875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07719305,"about_ca_topic_score_gemma":0.0543597,"domain_scores_codex":[0.9998617,0.00005142823,0.000008720045,0.00003337218,0.00002032634,0.00002442753],"domain_scores_gemma":[0.9997229,0.0001013831,0.00003369603,0.00003765687,0.00006376467,0.000040535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006683209,0.00006989877,0.005020839,0.00005386317,0.0001327317,0.00006437399,0.00003316307,0.9852477,0.0008149933,0.002204706,0.003354147,0.002936681],"study_design_scores_gemma":[0.00008125514,0.00002889967,0.003048414,0.000007345283,0.00003839319,0.000009918625,0.00001937444,0.9934819,0.0002203904,0.0008952676,0.002151861,0.00001690513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8609463,0.0007060252,0.03904811,0.00119728,0.0003172632,0.0003019272,0.05937711,0.004635431,0.03347054],"genre_scores_gemma":[0.9478697,0.0003651328,0.02465898,0.0001803273,0.00009011667,0.000580677,0.02135679,0.0007526493,0.004145588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07719305,"threshold_uncertainty_score":0.1534875,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6929373690","doi":"10.4224/23000573","title":"MeerKAT : first light","year":2016,"lang":"en","type":"article","venue":"NPARC","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"Herzberg Institute of Astrophysics","funders":"","keywords":"","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01613839543973972,"gpt":0.1997934523661859,"spread":0.1836550569264462,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00394506,0.001383168,0.002002459,0.004257727,0.005037925,0.0133562,0.003034126,0.005662995,0.8333119],"category_scores_gemma":[0.03022919,0.001272161,0.001468715,0.001468327,0.002131494,0.004323588,0.006616897,0.004761274,0.7999891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002122405,"about_ca_system_score_gemma":0.006068982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001306017,"about_ca_topic_score_gemma":0.00361158,"domain_scores_codex":[0.9936107,0.0008480782,0.0002839227,0.0009293772,0.003409469,0.0009183687],"domain_scores_gemma":[0.9676833,0.002186654,0.0009380922,0.005686025,0.01554746,0.007958525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009207719,0.00004466043,0.0001582391,0.0001790492,0.00001217927,0.0001351622,0.00004830271,0.00004685576,0.0004884395,0.002581889,0.9529278,0.04328545],"study_design_scores_gemma":[0.00003046149,0.00002202207,0.0003630111,0.0001198274,0.000006578493,0.0001482716,0.00006593664,0.0001777834,0.0007002065,0.002742469,0.9956006,0.00002266691],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002114009,0.0023345,0.004107911,0.03665016,0.1054322,0.0008076015,0.007303726,0.01051197,0.8307379],"genre_scores_gemma":[0.005028284,0.0004298846,0.0008133159,0.001487141,0.003801424,0.0001201415,0.001377262,0.00216678,0.9847758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8333119,"threshold_uncertainty_score":0.2377602,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6925178019","doi":"10.17605/osf.io/5dmau","title":"Neural representations of stimulus category membership across modalities: A systematic review","year":2021,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Stimulus (psychology); Systematic review; Categorization; Academic institution; Grey literature","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.0395379774392162,"gpt":0.3034277272627914,"spread":0.2638897498235752,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1090143,0.002232775,0.007777893,0.01660495,0.002427784,0.005573087,0.004581304,0.004341531,0.07180059],"category_scores_gemma":[0.3139237,0.002943879,0.009070051,0.0174765,0.002679776,0.008359846,0.005392922,0.003637644,0.009967695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008481658,"about_ca_system_score_gemma":0.05190725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005293643,"about_ca_topic_score_gemma":0.02112862,"domain_scores_codex":[0.9034239,0.04318509,0.03389004,0.004404393,0.01360041,0.001496075],"domain_scores_gemma":[0.798418,0.1259583,0.02690239,0.01598229,0.03101769,0.001721326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0006082901,0.000031092,0.000506523,0.9251894,0.002083412,0.00009233945,0.0007289857,0.0001590187,0.0002873165,0.002562581,0.04235488,0.02539605],"study_design_scores_gemma":[0.003048868,0.000347089,0.002949967,0.8493721,0.01280895,0.0002236161,0.0009215534,0.000357806,0.0004829909,0.00529271,0.1239699,0.0002243507],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"protocol","genre_gemma":"review","genre_scores_codex":[0.004134234,0.113227,0.02182128,0.01222928,0.00474652,0.7205095,0.1123983,0.001165773,0.009768114],"genre_scores_gemma":[0.01013265,0.0483418,0.03147965,0.00284004,0.0003240636,0.8879923,0.01559715,0.0001885177,0.003103754],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.1090143,"threshold_uncertainty_score":0.5765296,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6926521394","doi":"10.25384/sage.21767020.v1","title":"sj-pdf-1-cph-10.1177_17151635221140412 – Supplemental material for “It’s a lonely battle”: A qualitative study of older adult Canadians’ experiences with chronic obstructive pulmonary disease medication adherence and support","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Qualitative research; Pulmonary disease; Medication adherence; Chronic disease; Loneliness; Social support; COPD; Qualitative analysis","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03675628107739412,"gpt":0.2880303967722196,"spread":0.2512741156948255,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001783034,0.0002443057,0.0003171878,0.001119911,0.006031381,0.002510755,0.001140527,0.001233877,0.6123122],"category_scores_gemma":[0.00960476,0.0002944177,0.0002064585,0.00278986,0.001167327,0.001705965,0.00185329,0.0012925,0.105265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008437808,"about_ca_system_score_gemma":0.01403001,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5564019,"about_ca_topic_score_gemma":0.7576004,"domain_scores_codex":[0.9992435,0.000157423,0.00002605663,0.00005215868,0.0003330538,0.0001877991],"domain_scores_gemma":[0.9888681,0.00531845,0.0001635613,0.0002937324,0.003374772,0.001981415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002412847,0.00005951913,0.0006771634,0.0001917285,0.000001054612,0.00009358825,0.008491014,0.00001693429,0.0001709274,0.0007465033,0.9762772,0.01325027],"study_design_scores_gemma":[0.00005270783,0.00004011521,0.01060128,0.0003797965,0.000003998845,0.00008551099,0.03683021,0.00006913449,0.0002128144,0.0005393242,0.9511427,0.00004237787],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.03458844,0.0007585711,0.002377129,0.02529558,0.002379003,0.003124576,0.2464153,0.002130086,0.6829312],"genre_scores_gemma":[0.1267327,0.001545732,0.007547635,0.01046618,0.0004439756,0.006551632,0.0438172,0.001803329,0.8010917],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.6123122,"threshold_uncertainty_score":0.8924211,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6927610353","doi":"10.34943/73facd42-5037-46f9-8132-8f65e20fb1b3","title":"Baynes Sound Oxygen Sensor Deployed 2024-04-09","year":2024,"lang":"en","type":"dataset","venue":"Ocean Networks Canada Society","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Measure (data warehouse); Oxygen; Oxygen sensor; Sound (geography); Software deployment; Wireless sensor network","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01159292324143765,"gpt":0.2054964858616877,"spread":0.19390356262025,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005570764,0.001427452,0.0007150154,0.001441477,0.0006293575,0.0008323086,0.001642601,0.0009231591,0.008543689],"category_scores_gemma":[0.001657573,0.0002958347,0.0003812067,0.002051304,0.00033339,0.000908558,0.0008893793,0.00102757,0.01907294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053341,"about_ca_system_score_gemma":0.001692394,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07926493,"about_ca_topic_score_gemma":0.1414093,"domain_scores_codex":[0.9994147,0.00004152122,0.0000484316,0.0001563982,0.0002429957,0.00009582546],"domain_scores_gemma":[0.9992589,0.00004621052,0.00003488376,0.0001391077,0.0004191154,0.0001018031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001212591,0.00006262019,0.002927838,0.0001595454,0.00001772132,0.00006893952,0.00003364734,0.0008351852,0.0008307779,0.0004983111,0.9881425,0.006301531],"study_design_scores_gemma":[0.0002487143,0.00006957291,0.02262098,0.0001350763,0.00002302399,0.0001393728,0.000271018,0.004887076,0.002907434,0.001448167,0.9671965,0.00005320516],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00456334,0.00008384934,0.0004355968,0.0002496848,0.0001362373,0.00006849636,0.9877278,0.00163039,0.005104731],"genre_scores_gemma":[0.002851454,0.00003197982,0.0006069813,0.00005368642,0.000009953139,0.00005347946,0.9949957,0.00005224918,0.001344539],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9207351,"threshold_uncertainty_score":0.1576071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6949600847","doi":"10.5281/zenodo.14710229","title":"INSTAR Rollup #1 - AIOTI Days 2024","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"European Commission","keywords":"Key (lock); Instar; Emerging technologies; Information technology","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03179318165978392,"gpt":0.2384113101170477,"spread":0.2066181284572638,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003127792,0.001492327,0.0007142583,0.001682989,0.002320997,0.006072538,0.001599599,0.003249806,0.1844776],"category_scores_gemma":[0.003959657,0.0005448259,0.0008971705,0.0008975386,0.0005801879,0.002644699,0.003806054,0.003357287,0.1387184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001808366,"about_ca_system_score_gemma":0.004982688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006751206,"about_ca_topic_score_gemma":0.01224042,"domain_scores_codex":[0.9977745,0.0002228644,0.00005022678,0.0002459071,0.001212735,0.0004937681],"domain_scores_gemma":[0.9965746,0.0003060055,0.0001817721,0.0005019579,0.001281847,0.001153796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008690948,0.0002056954,0.0006733221,0.0001993885,0.00002611246,0.0002484565,0.00007060726,0.0003772174,0.003243673,0.01670764,0.937368,0.04001087],"study_design_scores_gemma":[0.0000543326,0.0001415497,0.001025903,0.00003206477,0.00000612924,0.00004875636,0.00004441722,0.0003473135,0.001825053,0.001640459,0.9948196,0.0000144192],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01545354,0.003684444,0.0148928,0.01917722,0.02810691,0.001376148,0.0641499,0.01756739,0.8355916],"genre_scores_gemma":[0.04083166,0.0007218028,0.009088868,0.005836588,0.001552369,0.0009991998,0.04834164,0.003955234,0.8886726],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1844776,"threshold_uncertainty_score":0.617139,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6977988345","doi":"10.7488/ds/5002","title":"Tower Blocks UK: Hammersmith and Fulham London Dieppe Street Redevelopment Area, l18-18.jpg","year":2023,"lang":"en","type":"other","venue":"University of Edinburgh","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Redevelopment; Borough; Block (permutation group theory); Tower; Metropolitan area; Object (grammar); Quarter (Canadian coin); Identification (biology)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02261441027771735,"gpt":0.1930206517265398,"spread":0.1704062414488225,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005552057,0.001616372,0.0009296656,0.00124269,0.002686871,0.007581671,0.001163544,0.003300077,0.9275532],"category_scores_gemma":[0.00166734,0.001023311,0.0005122095,0.003037652,0.0009402614,0.005347891,0.00280274,0.001960509,0.8130214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002192158,"about_ca_system_score_gemma":0.002429876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02001975,"about_ca_topic_score_gemma":0.07902968,"domain_scores_codex":[0.99925,0.00006819011,0.00005088243,0.000259006,0.0002460712,0.0001258137],"domain_scores_gemma":[0.9989409,0.0001455103,0.0000735728,0.0001364786,0.0003208656,0.0003827578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009269084,0.00002059835,0.0002936511,0.0003353243,0.000003717969,0.0003417355,0.0002965481,0.00008340572,0.0006045813,0.002458113,0.9121692,0.0833004],"study_design_scores_gemma":[0.000009663249,0.00001576203,0.001085621,0.0001415175,0.000001644452,0.00008144566,0.0002556685,0.00001858087,0.00009292981,0.0001314826,0.9981589,0.000006706956],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001326861,0.0030731,0.0005135474,0.001682684,0.00117314,0.0001598847,0.007346346,0.0009364384,0.983788],"genre_scores_gemma":[0.001398008,0.0009543991,0.0001524773,0.0001227388,0.0000481832,0.00002786689,0.0007796668,0.0002488991,0.9962677],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9275532,"threshold_uncertainty_score":0.1033365,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205763488","doi":"10.1109/mc.2013.182","title":"Software Experts Summit Advertisement","year":2013,"lang":"en","type":"article","venue":"Computer","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Summit; Computer science; Software; World Wide Web; Software engineering; Computer security; Multimedia; Operating system","authors":[{"name":"James A. Whittaker","is_ca":false},{"name":"Wolfram Schulte","is_ca":false},{"name":"Ayşe Bener","is_ca":true},{"name":"Forrest Shull","is_ca":false},{"name":"Paul Zikopoulos","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01613177319856155,"gpt":0.2023045842031551,"spread":0.1861728110045936,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002748376,0.001390389,0.0006404498,0.002408714,0.003208108,0.006827572,0.001100758,0.004655547,0.3517301],"category_scores_gemma":[0.006287578,0.0004931476,0.0008788485,0.001441074,0.0006627587,0.003331407,0.00292886,0.004716243,0.3581612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124647,"about_ca_system_score_gemma":0.002599183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006911813,"about_ca_topic_score_gemma":0.0206822,"domain_scores_codex":[0.9981008,0.0001414634,0.00005760169,0.0001765977,0.001216139,0.0003074486],"domain_scores_gemma":[0.9935858,0.0006941556,0.0001352564,0.0002525838,0.003131148,0.002201037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001043901,0.00001240846,0.00003497833,0.0000123354,7.462357e-7,0.0000174779,0.000009946802,0.000006895108,0.0000592549,0.000260561,0.9945879,0.004987089],"study_design_scores_gemma":[0.000009675038,0.00001821284,0.000328519,0.00002052374,0.000001801009,0.0000110201,0.00006397039,0.00004352777,0.00006523627,0.0002445328,0.9991879,0.0000051431],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002727135,0.002520242,0.001856785,0.116245,0.156238,0.0003152989,0.005348045,0.003657599,0.7110919],"genre_scores_gemma":[0.003705696,0.0006795506,0.0003159978,0.01356088,0.009744401,0.0001084286,0.002852945,0.0006810146,0.968351],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6482699,"threshold_uncertainty_score":0.9246783,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405522446","doi":"10.1109/cipae64326.2024.00005","title":"Message from General Chair: CIPAE 2024","year":2024,"lang":"en","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Computer science","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02235932717628762,"gpt":0.240303051857009,"spread":0.2179437246807214,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001466494,0.0009726565,0.0008385209,0.0008428564,0.002298125,0.004073328,0.001601318,0.01100362,0.3310458],"category_scores_gemma":[0.00515872,0.0004266758,0.0006106529,0.000944963,0.0005781176,0.002290225,0.001592304,0.007567208,0.2920463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771039,"about_ca_system_score_gemma":0.00346154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004554442,"about_ca_topic_score_gemma":0.006100155,"domain_scores_codex":[0.998988,0.0000842642,0.00005858448,0.0002062473,0.0004776001,0.0001853566],"domain_scores_gemma":[0.9966822,0.0002759515,0.0001053587,0.0001380723,0.00198182,0.0008165796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001863833,0.000006032708,0.00004266405,0.00002370322,7.071313e-7,0.00002229544,0.000004646155,0.000006670261,0.00005936725,0.0001585184,0.9967465,0.002910325],"study_design_scores_gemma":[0.000009699068,0.00001163869,0.0003795375,0.00003970073,0.000001624309,0.00002373225,0.00003466021,0.00003371399,0.00009970622,0.0001374431,0.9992223,0.000006269844],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.001078786,0.003237634,0.001370393,0.3379138,0.3851151,0.00114944,0.004211366,0.001746126,0.2641773],"genre_scores_gemma":[0.004107893,0.001110955,0.0004173954,0.08186301,0.03917632,0.0003723607,0.001323199,0.0004229981,0.8712059],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.3310458,"threshold_uncertainty_score":0.954182,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6893430549","doi":"10.5281/zenodo.16570729","title":"Burnsius communis subsp. tenebrunis Zhang & Cong & Shen & Song & Grishin 2025, new subspecies","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Subspecies; GenBank; Clade; Genome; White (mutation); Type locality","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.05058364493485031,"gpt":0.2493167529359945,"spread":0.1987331080011442,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001634388,0.0003563885,0.0001951831,0.00197964,0.001014413,0.0002569976,0.0003942914,0.0002130252,0.00573807],"category_scores_gemma":[0.0001646637,0.0001151364,0.000155535,0.00165492,0.0004333763,0.0005040856,0.0006909282,0.0004339933,0.001022865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005560507,"about_ca_system_score_gemma":0.0004187506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02906796,"about_ca_topic_score_gemma":0.0978343,"domain_scores_codex":[0.9998814,0.000005940334,0.000009367443,0.00004662864,0.0000403888,0.00001619339],"domain_scores_gemma":[0.9999206,0.000005836354,0.00002197971,0.000009284579,0.00002141162,0.0000209348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006532664,0.0001664415,0.2708381,0.0007484734,0.0002260146,0.003334877,0.006286564,0.0008628027,0.1561188,0.003189329,0.00776798,0.5498074],"study_design_scores_gemma":[0.0000288125,0.00009082276,0.9115235,0.0001133475,0.00006497499,0.004069556,0.001945663,0.0005292784,0.00156564,0.0006307026,0.07940893,0.00002878995],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9205176,0.00320607,0.003223253,0.0003073698,0.0001242617,0.0001931816,0.003566762,0.0002550235,0.06860648],"genre_scores_gemma":[0.9732165,0.001101081,0.005412966,0.0002004212,0.00005712242,0.0001366632,0.008190611,0.00002570477,0.01165891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02906796,"threshold_uncertainty_score":0.05779755,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7011811289","doi":"","title":"Neurolaw:Revisiting Huberty v. McDonald’s through the Lens of Nutritional Criminology and Food Crime","year":2024,"lang":"en","type":"article","venue":"UWA Profiles and Research Repository (University of Western Australia)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Humber Polytechnic","funders":"","keywords":"Relevance (law); Criminal justice; Intervention (counseling); Economic Justice; Microbiome; Salient; Notice; Legitimacy","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.1959314233321045,"gpt":0.3209267988993318,"spread":0.1249953755672273,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01395821,0.0005938726,0.001093061,0.003084471,0.01462371,0.01059199,0.003187975,0.0178719,0.002259061],"category_scores_gemma":[0.02285623,0.0006010145,0.0005941059,0.001393939,0.05466762,0.01545314,0.007217054,0.02947465,0.0005209722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01337648,"about_ca_system_score_gemma":0.02364907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1101616,"about_ca_topic_score_gemma":0.1760628,"domain_scores_codex":[0.9924706,0.003492277,0.0003672948,0.0009864718,0.001759116,0.0009243451],"domain_scores_gemma":[0.9831268,0.0130547,0.0007248948,0.0005198687,0.001588607,0.0009851835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001212672,0.00002058572,0.0005329986,0.0001678412,0.00001150497,0.0006118739,0.04175838,0.00009574951,0.00008929909,0.7282225,0.2095801,0.01889708],"study_design_scores_gemma":[0.00001368341,0.00002714656,0.001497848,0.002002633,0.00002020105,0.000514988,0.02105815,0.0002772287,0.0001938909,0.3234423,0.6508969,0.00005504789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.005623569,0.02751462,0.001660292,0.9284117,0.00690182,0.00003806064,0.00003790943,0.0000331953,0.02977878],"genre_scores_gemma":[0.2293329,0.05045072,0.004271691,0.6690715,0.01182733,0.0001985541,0.00003740005,0.0001563641,0.03465366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1101616,"threshold_uncertainty_score":0.2190408,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7071783666","doi":"","title":"Tencent buys 12 percent stake in Snap","year":2017,"lang":"en","type":"other","venue":"Internet Archive (Internet Archive)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"China; Payment; Quarter (Canadian coin); The Internet; Social media; Launched","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03052659728913166,"gpt":0.2471109951556352,"spread":0.2165843978665035,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00106486,0.0007126664,0.0003711754,0.002215286,0.004281071,0.007044197,0.0006757536,0.00147338,0.3163096],"category_scores_gemma":[0.002485636,0.0003470393,0.0005596405,0.0015174,0.0009315716,0.004226636,0.003360377,0.001978286,0.1152597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002052957,"about_ca_system_score_gemma":0.003301222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02091054,"about_ca_topic_score_gemma":0.06698807,"domain_scores_codex":[0.9989767,0.00005080762,0.00002354251,0.0001118641,0.0006242121,0.0002128519],"domain_scores_gemma":[0.9978065,0.00009072454,0.00005195008,0.0001681735,0.0008452849,0.001037413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008307715,0.00009963204,0.001567703,0.00005396646,0.000007677085,0.0002992172,0.0002393237,0.0000329214,0.000711849,0.01278213,0.9389426,0.04517983],"study_design_scores_gemma":[0.00001171638,0.00003442906,0.002849815,0.00004204303,0.000005021477,0.0001464252,0.0004020689,0.0000988302,0.0003819884,0.0009315342,0.9950776,0.00001871457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008349019,0.00061001,0.0006301645,0.006463203,0.001714957,0.0000923336,0.00297909,0.002339579,0.9768216],"genre_scores_gemma":[0.02066671,0.0004553159,0.0004708173,0.002763233,0.0002578887,0.00004494621,0.003607251,0.0004778981,0.9712559],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3163096,"threshold_uncertainty_score":0.9752014,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6949077855","doi":"10.5281/zenodo.12566933","title":"Quasars/orange-spectroscopy: Release 0.6.14","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Canadian Light Source (Canada)","funders":"","keywords":"Action (physics); Process (computing); Yield (engineering); Work (physics)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03666548649748762,"gpt":0.2473790200629515,"spread":0.2107135335654638,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003679851,0.003363395,0.001575729,0.003693067,0.001067906,0.004259517,0.003860451,0.002608349,0.2710893],"category_scores_gemma":[0.006436925,0.002555319,0.001705906,0.002351536,0.0006436292,0.004443103,0.005139238,0.002748252,0.4714454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006982809,"about_ca_system_score_gemma":0.0008197168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002577006,"about_ca_topic_score_gemma":0.002841499,"domain_scores_codex":[0.9985105,0.0001549322,0.00007625138,0.0002710327,0.0006501419,0.000337004],"domain_scores_gemma":[0.9967218,0.0005107968,0.0002710595,0.001292381,0.0007152076,0.0004887995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002187606,0.00002452348,0.0005090883,0.0002611774,0.00005261034,0.00005119961,0.00004595351,0.0001109362,0.001196828,0.001606902,0.9796931,0.01622911],"study_design_scores_gemma":[0.0001789169,0.00003737178,0.002159602,0.0001604301,0.00003133892,0.0001586586,0.00003261515,0.0006057294,0.006451251,0.005348121,0.984698,0.0001379236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.001624645,0.00107583,0.02604408,0.001128222,0.0007210771,0.0002261448,0.2779055,0.6180369,0.07323773],"genre_scores_gemma":[0.01629745,0.0008918296,0.03029609,0.002154034,0.0007359089,0.0007172464,0.4482445,0.4306699,0.06999305],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.2710893,"threshold_uncertainty_score":0.9068841,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6923241379","doi":"10.1371/journal.pone.0092797.t004","title":"Summary of analysis of variance (ANOVA) of the relationship between NN distances at COI and larval food plant categories for 1196 species of Canadian noctuoids.","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Set (abstract data type); Sample (material); Data set; Variance (accounting); Sample size determination; Variance components","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.1412783848595793,"gpt":0.2578479813284423,"spread":0.116569596468863,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00192423,0.001515055,0.001303609,0.004118305,0.001191535,0.001104575,0.002684083,0.0007932761,0.0233347],"category_scores_gemma":[0.00854389,0.0004976853,0.001557603,0.005535826,0.0004950702,0.0005665148,0.0009282173,0.001092822,0.007598696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004226226,"about_ca_system_score_gemma":0.00845462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6824489,"about_ca_topic_score_gemma":0.8254989,"domain_scores_codex":[0.9989659,0.00007571993,0.00009164873,0.0003242633,0.0003538059,0.0001886704],"domain_scores_gemma":[0.9936619,0.001779451,0.0004853891,0.0008348289,0.002879994,0.0003583965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003119586,0.00008565519,0.04154174,0.001868053,0.0004633069,0.0000674277,0.0001709012,0.001568109,0.001128831,0.0006997988,0.9340338,0.01806029],"study_design_scores_gemma":[0.0004192144,0.0001142342,0.4573855,0.0008517801,0.0006500002,0.0001713398,0.000671768,0.002895888,0.001480182,0.001435019,0.5337683,0.0001567117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00180581,0.00009598045,0.0001575454,0.00004071947,0.00002020797,0.0000168656,0.997215,0.000230059,0.0004178487],"genre_scores_gemma":[0.008522447,0.0001035605,0.0009844855,0.00003494977,0.000007467482,0.0001139032,0.9894022,0.0001028019,0.0007281363],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3175511,"threshold_uncertainty_score":0.6388425,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409474076","doi":"10.2139/ssrn.5218480","title":"Enhancing Data Anomaly Prediction and Real-Time Physical Problem Detection with Digital Twins and Cognitive Super Digital Twins","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Anomaly detection; Anomaly (physics); Cognition; Computer science; Artificial intelligence; Psychology; Data mining; Physics; Neuroscience","authors":[{"name":"Meriem Smati","is_ca":false},{"name":"Jannik Laval","is_ca":false},{"name":"Christophe Danjou","is_ca":true},{"name":"Vincent Cheutet","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01120299285133659,"gpt":0.2277792928633812,"spread":0.2165763000120446,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001164003,0.0006453143,0.0008680616,0.001398704,0.0005692993,0.001374637,0.001258044,0.0007724293,0.002789514],"category_scores_gemma":[0.007691606,0.0003191229,0.0006250791,0.001219923,0.0005898608,0.003381112,0.002599616,0.001259715,0.0004706752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004822886,"about_ca_system_score_gemma":0.001022337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004280868,"about_ca_topic_score_gemma":0.005800384,"domain_scores_codex":[0.9992091,0.0001664693,0.00004399214,0.0002173904,0.0002696822,0.00009348552],"domain_scores_gemma":[0.9974961,0.001001199,0.0001851984,0.0004524095,0.0006672197,0.0001979064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001563136,0.001474423,0.03578032,0.0002253676,0.0003346055,0.0005039049,0.0004928534,0.1113893,0.03066592,0.03527977,0.005517439,0.7767729],"study_design_scores_gemma":[0.00002026761,0.0001399971,0.002586546,0.000008013842,0.0000484911,0.0001153206,0.0001160562,0.970202,0.006527357,0.01883132,0.001387157,0.00001742661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2704066,0.0003711563,0.7203708,0.0005752486,0.0002520785,0.0001328676,0.000259846,0.001600719,0.006030661],"genre_scores_gemma":[0.793174,0.0001708936,0.2031668,0.0001491744,0.00007265251,0.0000666353,0.0002676303,0.00007256919,0.002859594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004280868,"threshold_uncertainty_score":0.009331882,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2060356914","doi":"10.1109/mahc.2001.948911","title":"The complete story of codebreaking in World War II [Reviews]","year":2001,"lang":"en","type":"article","venue":"IEEE Annals of the History of Computing","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Annals; History of computing; First world war; World War II; Computer science; Library science; History; Political science; Classics; Law; Algorithm","authors":[{"name":"K. W. Smillie","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1471400096183261,"gpt":0.2928362860290996,"spread":0.1456962764107734,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003497402,0.001014817,0.001152414,0.00294042,0.001647876,0.006228504,0.0008107249,0.002980394,0.01160502],"category_scores_gemma":[0.02394909,0.0005483162,0.000778403,0.005264569,0.001455519,0.005005998,0.001553745,0.006176905,0.01009084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001981131,"about_ca_system_score_gemma":0.004341054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006221039,"about_ca_topic_score_gemma":0.01302131,"domain_scores_codex":[0.9963588,0.0009500799,0.00034822,0.0002669625,0.001837935,0.0002380093],"domain_scores_gemma":[0.9848343,0.005290026,0.001748567,0.0006677975,0.005870036,0.001589206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002543873,0.000004468198,0.00006736636,0.00130218,0.00002370512,0.00007968217,0.0002419403,0.00002481931,0.0001288334,0.001232257,0.9213021,0.07556712],"study_design_scores_gemma":[0.000003110064,0.00002386581,0.0003842015,0.001677606,0.00001191351,0.0001220574,0.0001805062,0.000004988472,0.00005591123,0.0005567628,0.9969689,0.00001007176],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004146053,0.8478312,0.0003028633,0.07517172,0.05652194,0.00005138105,0.0005108214,0.0001810924,0.01901434],"genre_scores_gemma":[0.007085028,0.8400579,0.000859973,0.07320879,0.03700377,0.0001780588,0.0007459006,0.0002534977,0.04060708],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9983521,"threshold_uncertainty_score":0.03882265,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6969612503","doi":"10.5683/sp3/dyene2","title":"Sierra Crest EDS Point Spectra Data","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Crest; Point (geometry); Spectral line; Identification (biology)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.07064397719674667,"gpt":0.2883944461778532,"spread":0.2177504689811065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004839828,0.001761526,0.0009785682,0.003237462,0.0008590029,0.001341889,0.00198399,0.00136565,0.01906308],"category_scores_gemma":[0.001571331,0.0005111514,0.001041709,0.004558811,0.0004594222,0.0006857171,0.001119904,0.001089652,0.02503783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009384021,"about_ca_system_score_gemma":0.001875358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06883515,"about_ca_topic_score_gemma":0.1359062,"domain_scores_codex":[0.9993767,0.0000394793,0.00004114981,0.0001603943,0.0002719062,0.0001105034],"domain_scores_gemma":[0.9990826,0.0001113023,0.00007299175,0.0001854855,0.0004343998,0.0001132543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001481362,0.0001309594,0.004410488,0.0006600631,0.00007111525,0.000126636,0.00009600866,0.001423761,0.00178478,0.000656358,0.9821773,0.008314459],"study_design_scores_gemma":[0.0002345544,0.00003419866,0.03140144,0.0001442317,0.00005599225,0.0001329175,0.000248377,0.00166901,0.001967067,0.000942675,0.9631071,0.00006239075],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001517713,0.00006109016,0.0001202409,0.00004222465,0.00002655041,0.0000177395,0.9962977,0.0007266965,0.001190153],"genre_scores_gemma":[0.001738531,0.00003910955,0.0004806235,0.00002110007,0.000005920921,0.00003600873,0.9970093,0.00007256094,0.0005968674],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06883515,"threshold_uncertainty_score":0.136869,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6977325383","doi":"10.6084/m9.figshare.23982576.v1","title":"Marketing","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Course (navigation); Information system; Information science; Data collection; Focus (optics)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.0690951896067731,"gpt":0.2634246775212288,"spread":0.1943294879144557,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000711902,0.001322612,0.0008259254,0.003751518,0.0007821576,0.002192201,0.001620898,0.001376696,0.09309457],"category_scores_gemma":[0.004962132,0.0003804067,0.0009170569,0.006914256,0.0002564877,0.001210548,0.001269941,0.001302957,0.1214846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001703239,"about_ca_system_score_gemma":0.002391536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04666912,"about_ca_topic_score_gemma":0.09971748,"domain_scores_codex":[0.9989626,0.0001319983,0.0001062354,0.0002711176,0.0003497375,0.0001783037],"domain_scores_gemma":[0.997311,0.0006578213,0.0002166725,0.0005188179,0.0009886841,0.0003070551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005266686,0.00003641352,0.001988448,0.0003604217,0.00001614394,0.00002148631,0.00003423684,0.0001929783,0.0001055393,0.0006998961,0.9910871,0.005404591],"study_design_scores_gemma":[0.00005547102,0.00001276723,0.00762795,0.0001438134,0.00001071461,0.00003707475,0.0001240205,0.0003508989,0.0002021343,0.0007141662,0.9907055,0.00001547566],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003407376,0.00005573773,0.00004364183,0.00006232972,0.00002141634,0.00001080242,0.9973124,0.0001559747,0.001996903],"genre_scores_gemma":[0.000602159,0.00005151689,0.0001959807,0.00004667609,0.000007528894,0.00003282445,0.9973163,0.00003730468,0.001709669],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9069054,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7008027260","doi":"","title":"Ansia dentale: aspetti emotivi ed interpersonali.","year":2013,"lang":"it","type":"article","venue":"Florence Research (University of Florence)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Alexithymia; Anxiety; Psychological stress; Dental care","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.06970652045243772,"gpt":0.2817707920684725,"spread":0.2120642716160348,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009985551,0.0006250729,0.0005747963,0.0009680958,0.0008555386,0.001312836,0.0002790249,0.0006307585,0.004756369],"category_scores_gemma":[0.003752489,0.0002786031,0.0007418017,0.0008112932,0.0004970545,0.0006579894,0.001470659,0.001435218,0.0005402206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067041,"about_ca_system_score_gemma":0.0007729745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005170424,"about_ca_topic_score_gemma":0.009901438,"domain_scores_codex":[0.998731,0.0003463314,0.0001138542,0.0001319177,0.0005108527,0.0001661066],"domain_scores_gemma":[0.9987079,0.0003632436,0.0004377245,0.0000537745,0.0001897109,0.0002476762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006824708,0.001107641,0.6380011,0.001942568,0.000782134,0.002998786,0.010302,0.0003363797,0.006461577,0.004077163,0.0128158,0.3204923],"study_design_scores_gemma":[0.00001642058,0.0001875645,0.9836687,0.0001855221,0.0001660454,0.002288407,0.001300668,0.0001660036,0.0002443805,0.001133944,0.01061695,0.0000253956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8323635,0.05684557,0.002120754,0.006245709,0.0008207552,0.0005417576,0.002185692,0.0001109715,0.09876513],"genre_scores_gemma":[0.9769793,0.01444973,0.001238418,0.0009776255,0.0002594955,0.0002072292,0.0005117552,0.00001088098,0.005365632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005170424,"threshold_uncertainty_score":0.01591164,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6977560740","doi":"10.6084/m9.figshare.27329545","title":"Additional file 7 of Medications for community pharmacists to dose adjust or avoid to enhance prescribing safety in individuals with advanced chronic kidney disease: a scoping review and modified Delphi","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Horizon Health Network; University of Toronto; University of British Columbia; University Health Network; Dalhousie University","funders":"","keywords":"Delphi method; Delphi; Kidney disease; MEDLINE; Patient safety; Medication adherence; Medical prescription","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.07084440180845501,"gpt":0.3453797766599134,"spread":0.2745353748514584,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004398672,0.0009500704,0.001259871,0.004878907,0.0007887952,0.001639939,0.001231164,0.001515806,0.8765513],"category_scores_gemma":[0.04369335,0.000564749,0.001525305,0.00612178,0.0002462408,0.002814483,0.001661663,0.0008639403,0.1499495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002129879,"about_ca_system_score_gemma":0.00365591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007218975,"about_ca_topic_score_gemma":0.01665294,"domain_scores_codex":[0.9977842,0.0006189597,0.0006684099,0.0001794558,0.0005452266,0.000203807],"domain_scores_gemma":[0.9463569,0.03858984,0.003327513,0.0008787576,0.01002975,0.0008172756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002771776,0.00004906732,0.0005377955,0.009892969,0.00002805004,0.0000342485,0.0001215565,0.0001197065,0.00006453296,0.0005959524,0.9737417,0.01453736],"study_design_scores_gemma":[0.004287487,0.000241711,0.01358695,0.02218188,0.0001773868,0.0001478629,0.0009672982,0.0005595397,0.0004998615,0.00462936,0.9526197,0.0001009708],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"review","genre_scores_codex":[0.000370474,0.0001079346,0.0003507573,0.001080087,0.00009434384,0.001517954,0.9876823,0.0003646504,0.008431477],"genre_scores_gemma":[0.01531686,0.00132976,0.0131306,0.00470896,0.0005161571,0.04008505,0.8456445,0.001242014,0.07802613],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.8765513,"threshold_uncertainty_score":0.1760846,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7034487016","doi":"","title":"Three Dimensional Laser Scanning Technology","year":2010,"lang":"en","type":"other","venue":"NPARC","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01530174213797262,"gpt":0.2235068092196595,"spread":0.2082050670816869,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003633238,0.0006476766,0.001007401,0.003162102,0.002925345,0.004731067,0.001918443,0.002625846,0.4432599],"category_scores_gemma":[0.01237716,0.0005833872,0.0008774591,0.002074228,0.00124158,0.002141561,0.002778819,0.001777438,0.2903459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00134972,"about_ca_system_score_gemma":0.004720049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001922549,"about_ca_topic_score_gemma":0.005734385,"domain_scores_codex":[0.9946568,0.0007363977,0.0002391105,0.0004696797,0.00352898,0.0003690638],"domain_scores_gemma":[0.9783876,0.001463911,0.0004915948,0.003390519,0.01494233,0.001324052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008878412,0.00006384175,0.0006813905,0.0004499747,0.00001716986,0.0002300593,0.0001157953,0.0001989973,0.006779233,0.005726971,0.8074157,0.1782321],"study_design_scores_gemma":[0.00002294625,0.00003659726,0.001932207,0.00009996232,0.00001320383,0.0003172194,0.0001032462,0.001033406,0.005653336,0.002383152,0.9883789,0.00002590659],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.007931811,0.001813182,0.01374675,0.009519935,0.02375793,0.0009726218,0.003562833,0.003260337,0.9354346],"genre_scores_gemma":[0.02240672,0.001225872,0.008441776,0.0009037834,0.001784966,0.0003085181,0.00254738,0.000792308,0.9615887],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4432599,"threshold_uncertainty_score":0.7941222,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7037062389","doi":"","title":"Disciplining preschool children, parent interaction","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Dyad; Socialization; Context (archaeology); Content analysis; Sample (material); Qualitative research; Social relation; Field (mathematics); Child discipline","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.005089453670755341,"gpt":0.155933237720874,"spread":0.1508437840501187,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002681436,0.0002150097,0.0003784948,0.0007344265,0.005615763,0.002420101,0.0007902161,0.0007490227,0.002588966],"category_scores_gemma":[0.006164506,0.0003119552,0.0001309251,0.001111675,0.002799959,0.001645742,0.002215353,0.001169299,0.0002553278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003593174,"about_ca_system_score_gemma":0.00346408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02452566,"about_ca_topic_score_gemma":0.04583945,"domain_scores_codex":[0.9977595,0.001492974,0.00008513607,0.0001783213,0.0002712281,0.0002128208],"domain_scores_gemma":[0.9965969,0.002329723,0.0004346136,0.0001574814,0.0002127253,0.0002685497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002403436,0.00002979667,0.01125932,0.0000917264,0.000004880776,0.00195838,0.9686882,0.00002745195,0.0007462736,0.002374236,0.001351285,0.01344428],"study_design_scores_gemma":[0.000006916341,0.00004686795,0.01414015,0.000169828,0.00001200119,0.001858294,0.9418509,0.0000409917,0.0005641003,0.0007026866,0.0405951,0.00001222276],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9718046,0.00364861,0.003186453,0.001893329,0.00007697745,0.00007536757,0.0002187578,0.00006157625,0.01903432],"genre_scores_gemma":[0.9895574,0.001815445,0.001843915,0.0003468411,0.00001233371,0.0001056557,0.00007279856,0.00001975213,0.006225761],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02452566,"threshold_uncertainty_score":0.04876584,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6949673988","doi":"10.5281/zenodo.15062094","title":"O FUTURO DA IA: Além dos LLMs e Rumo a Arquiteturas Preditivas (JEPA) e Modelos Baseados em Energia","year":2025,"lang":"pt","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"WSP (Canada)","funders":"","keywords":"Balance (ability); Work (physics); Term (time)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.04176905240469243,"gpt":0.2616519098192175,"spread":0.2198828574145251,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001962811,0.0008241962,0.0005647401,0.0006757639,0.0008005149,0.004685955,0.001291702,0.0015593,0.006249161],"category_scores_gemma":[0.009643812,0.0005996044,0.0008360167,0.0007719035,0.002133469,0.006094159,0.003269668,0.002380442,0.0009090058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001445931,"about_ca_system_score_gemma":0.001535252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007015495,"about_ca_topic_score_gemma":0.005737145,"domain_scores_codex":[0.9992742,0.0002814312,0.00003908331,0.0001802827,0.0001549113,0.00007012075],"domain_scores_gemma":[0.9968207,0.001852797,0.0002783078,0.0004652895,0.0004303198,0.000152609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006128688,0.0001480624,0.01402987,0.0004634166,0.0001531173,0.0004651632,0.004616799,0.5024334,0.007988469,0.3289655,0.002965661,0.1371577],"study_design_scores_gemma":[0.00002391618,0.0001268671,0.001929236,0.0001442926,0.00008072974,0.0001225852,0.0008838382,0.833873,0.003140129,0.148093,0.01153084,0.00005158442],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.202717,0.001753279,0.7524069,0.003597243,0.0003062013,0.00008651002,0.000250264,0.001261651,0.03762094],"genre_scores_gemma":[0.9316878,0.0008582172,0.0571142,0.0002060197,0.00006276029,0.0000834061,0.0001650765,0.0001869064,0.009635572],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.007015495,"threshold_uncertainty_score":0.02090549,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}