{"meta":{"query_hash":"e23fe9768780","filters":{"venue":"Communications in computer and information science"},"cohort_total":653,"direct_labels_cover":0,"predictions_cover":653,"exported":653,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/e23fe9768780","api":"https://metacan.xera.ac/api/v1/cohort?venue=Communications+in+computer+and+information+science"},"results":[{"id":"W100954132","doi":"10.1007/978-3-642-54092-9_13","title":"Investigating the Applicability of the Laws of Software Evolution: A Metrics Based Study","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Software evolution; Metric (unit); Computer science; Software; Java; Software metric; Quality (philosophy); Empirical research; Open source software; Object (grammar); Software quality; Software development; Software engineering; Data science; Software construction; Programming language; Artificial intelligence; Mathematics; Engineering; Operations management; Statistics","score_opus":0.051741168538568034,"score_gpt":0.29699221642596985,"score_spread":0.24525104788740182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W100954132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002719989,0.00031670547,0.9887132,0.00072132784,0.00019469071,0.001626279,0.00001164467,0.00007727084,0.0056188945],"genre_scores_gemma":[0.8556048,0.000023200015,0.14407524,0.0001255664,0.000009540098,0.000071454495,0.0000025217043,0.0000052638443,0.0000823677],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980505,0.00008315919,0.0006899842,0.0001874798,0.0008382565,0.00015061648],"domain_scores_gemma":[0.9930145,0.00198815,0.00042325992,0.0037086848,0.0008142043,0.0000511874],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0024136927,0.00013639702,0.00020718918,0.0005086127,0.00034930187,0.00017942388,0.006251236,0.00006555215,0.000003236868],"category_scores_gemma":[0.0010644483,0.000090871355,0.000051409697,0.0015189411,0.0013195509,0.0016825689,0.0037856943,0.00045034956,0.0000053050417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016294163,0.00018341643,0.051963862,0.00030530835,0.000028221286,6.912856e-8,0.009063784,0.012134495,0.000010182543,0.5814082,0.00031939868,0.34458143],"study_design_scores_gemma":[0.00031707948,0.00009928864,0.15630786,0.00023585162,0.000008784762,0.0000030477813,0.00008232335,0.8307705,0.000032192034,0.0072953976,0.004618125,0.00022955769],"about_ca_topic_score_codex":0.00005056186,"about_ca_topic_score_gemma":0.000007821648,"teacher_disagreement_score":0.8528848,"about_ca_system_score_codex":0.00013867802,"about_ca_system_score_gemma":0.0005074369,"threshold_uncertainty_score":0.9991254},"labels":[],"label_agreement":null},{"id":"W1022149868","doi":"10.1007/978-3-319-21380-4_55","title":"Family Channel: Accessible Social Media for Older Adults","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sheridan College","funders":"","keywords":"Isolation (microbiology); Social media; Social isolation; Channel (broadcasting); Internet privacy; Psychology; Computer science; Sociology; Telecommunications; World Wide Web; Psychiatry","score_opus":0.08405783867173962,"score_gpt":0.3533359285716015,"score_spread":0.2692780898998619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1022149868","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00092015637,0.002097133,0.032536805,0.011899101,0.001982837,0.0030444996,0.00022140508,0.0006855115,0.94661254],"genre_scores_gemma":[0.9052431,0.010799912,0.070795104,0.0034346431,0.001039546,0.0006833058,0.00071555044,0.000080013386,0.007208855],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99831957,0.000032552067,0.0005284734,0.00023738964,0.000557927,0.00032406455],"domain_scores_gemma":[0.99743307,0.0003265441,0.00034017436,0.00078588485,0.0009960145,0.0001183306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017965626,0.00017883354,0.00025186717,0.0008696289,0.0012725479,0.00032440436,0.0026579944,0.0003359532,0.000009189361],"category_scores_gemma":[0.00025908384,0.00019090199,0.000047503192,0.00040920993,0.002567635,0.004156791,0.0010338263,0.0003648259,0.000035756144],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007426624,0.000016557786,0.000012718231,0.000026181213,0.0000046210816,9.4658986e-8,0.054243293,0.0000047097237,1.9887679e-7,0.5997054,0.0054300507,0.34054875],"study_design_scores_gemma":[0.0013204328,0.0000365944,0.003162423,0.00041851745,0.000016444925,0.0000022883562,0.0034932122,0.010238376,0.0000021141766,0.05170496,0.92902195,0.00058265746],"about_ca_topic_score_codex":0.000083252664,"about_ca_topic_score_gemma":0.00040185722,"teacher_disagreement_score":0.9394037,"about_ca_system_score_codex":0.00024092398,"about_ca_system_score_gemma":0.00076311233,"threshold_uncertainty_score":0.9787538},"labels":[],"label_agreement":null},{"id":"W1032648216","doi":"10.1007/978-3-642-27503-6_20","title":"Application of Atmosphere-Environment Quality Assessment Based on Fuzzy Comprehensive Evaluation","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Environmental Quality and Pollution","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences North","funders":"","keywords":"Atmosphere (unit); Subordination (linguistics); Fuzzy logic; Computer science; Quality (philosophy); Environmental quality; Quality assessment; Risk analysis (engineering); Operations research; Data mining; Evaluation methods; Reliability engineering; Artificial intelligence; Engineering; Business; Meteorology; Geography","score_opus":0.08554305729720157,"score_gpt":0.339071934439066,"score_spread":0.25352887714186445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1032648216","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022599762,0.00010214251,0.14824009,0.0005250045,0.000134747,0.001721736,0.00006457508,0.0000364006,0.8469153],"genre_scores_gemma":[0.95947546,0.0007662458,0.03799676,0.0011162149,0.000013690943,0.00010876989,0.00026775076,0.00001252571,0.00024258568],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975506,0.00013834008,0.00083251734,0.00030933548,0.0010044334,0.000164775],"domain_scores_gemma":[0.99734485,0.00022395662,0.00067388645,0.0016259196,0.000046528985,0.00008482778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018877202,0.00022066264,0.00025258664,0.00010995101,0.0002841637,0.000042877382,0.00089901884,0.00014204007,0.0003937645],"category_scores_gemma":[0.000017715212,0.00022716602,0.000057681493,0.0001601207,0.0017270027,0.0014312107,0.0007891163,0.00030816873,0.00023120102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032967855,0.00024521016,0.005177439,0.000067193716,0.000010808781,7.6569364e-8,0.0012344588,0.072072215,0.000115715404,0.26869172,0.00015386412,0.6521983],"study_design_scores_gemma":[0.0007917554,0.00022186375,0.24656422,0.00013062105,0.000032913016,0.0000016930695,0.00005062221,0.6627339,0.000057119054,0.021149244,0.06776981,0.00049625244],"about_ca_topic_score_codex":0.00013674873,"about_ca_topic_score_gemma":0.000016921234,"teacher_disagreement_score":0.9572155,"about_ca_system_score_codex":0.00072832225,"about_ca_system_score_gemma":0.00006896298,"threshold_uncertainty_score":0.92635614},"labels":[],"label_agreement":null},{"id":"W10973028","doi":"10.1007/978-3-642-27192-2_1","title":"Wireless Multimedia Sensor Networks Testbeds and State-of-the-Art Hardware: A Survey","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Process (computing); Domain (mathematical analysis); Wireless; State (computer science); Wireless sensor network; Software; Embedded system; Computer network; Telecommunications; Operating system","score_opus":0.03245127060500179,"score_gpt":0.24721574449533565,"score_spread":0.21476447389033387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W10973028","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009273062,0.00074009935,0.94887924,0.00033999025,0.00096021546,0.00068038946,0.000029757726,0.00012219357,0.04732081],"genre_scores_gemma":[0.6003754,0.014989467,0.3753733,0.0019175602,0.00009948617,0.000067357854,0.00017289918,0.00006831664,0.0069361944],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978747,0.00012071589,0.0008448039,0.0003541477,0.00048847334,0.00031716865],"domain_scores_gemma":[0.9952812,0.0006517698,0.0006185082,0.0027115736,0.00060351763,0.00013342703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015875283,0.0002844297,0.00035391306,0.0004341382,0.00042440862,0.0003460663,0.0038969542,0.00015381875,0.000002691104],"category_scores_gemma":[0.000067465364,0.0002443196,0.000052396623,0.000698491,0.0019179294,0.002595978,0.004068673,0.00058804674,0.000011839811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011045486,0.00006484673,0.0029335404,0.000057838137,0.000025342977,9.602962e-7,0.004046913,0.027412856,0.000004671228,0.19421248,0.00080840214,0.7704211],"study_design_scores_gemma":[0.00022235708,0.000034064546,0.015154388,0.00024561674,0.000004815723,0.000018913266,0.0000027880035,0.970457,0.0000145747545,0.00063920283,0.01290511,0.0003011496],"about_ca_topic_score_codex":0.000054585093,"about_ca_topic_score_gemma":0.00010203001,"teacher_disagreement_score":0.9430442,"about_ca_system_score_codex":0.000073084884,"about_ca_system_score_gemma":0.00021396654,"threshold_uncertainty_score":0.9963064},"labels":[],"label_agreement":null},{"id":"W113041619","doi":"10.1007/978-3-642-23147-6_21","title":"Threaded C and Freezer OS","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Semaphore; Computer science; Thread (computing); Robotics; Markup language; Artificial intelligence; Operating system; Embedded system; Programming language; Robot; XML","score_opus":0.038586834745803045,"score_gpt":0.27055791185877087,"score_spread":0.23197107711296783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W113041619","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000122051715,0.0003382773,0.64560163,0.0004501851,0.00013918952,0.00026281975,0.0000042796596,0.00017716213,0.35301423],"genre_scores_gemma":[0.12191183,0.021362612,0.83964914,0.00737345,0.00010972069,0.00012612504,0.000038199854,0.000034303095,0.009394623],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99886185,0.000019028721,0.0004448214,0.0002444762,0.00025410694,0.00017569156],"domain_scores_gemma":[0.9975978,0.00008093616,0.00021427106,0.0017603855,0.0002632234,0.00008337232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069142855,0.0001796186,0.00018654358,0.0009140811,0.00038840412,0.0005296088,0.0022282477,0.0001224925,0.00001045034],"category_scores_gemma":[0.000021157706,0.00017397868,0.000028732517,0.00027055675,0.00084787834,0.007106569,0.0024228687,0.0003590913,0.000040768857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.385737e-7,0.0000051282755,0.0000068857257,0.000010613801,0.0000021909589,2.7878937e-7,0.0011760098,5.6799456e-7,0.0000033179342,0.4430838,0.00032103487,0.55538946],"study_design_scores_gemma":[0.00064155227,0.0003442724,0.0028730438,0.00044782716,0.000015281752,0.00021564029,0.000027803575,0.08990775,0.001656804,0.2813096,0.62132823,0.0012321805],"about_ca_topic_score_codex":0.000039631483,"about_ca_topic_score_gemma":0.0000114914465,"teacher_disagreement_score":0.6210072,"about_ca_system_score_codex":0.00006301444,"about_ca_system_score_gemma":0.00013013552,"threshold_uncertainty_score":0.7094645},"labels":[],"label_agreement":null},{"id":"W1146584004","doi":"10.1007/978-3-319-17509-6_6","title":"A Performance Improvement and Management Model for Small and Medium Sized Enterprises","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Accounting and Organizational Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Business; Industrial organization; Process management","score_opus":0.0431614636143096,"score_gpt":0.25110137959431367,"score_spread":0.20793991598000405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1146584004","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009995661,0.0016768737,0.3267577,0.009442375,0.0010148057,0.006173091,0.00005993991,0.0004162462,0.6444633],"genre_scores_gemma":[0.802853,0.018433614,0.15229967,0.01303495,0.00052607286,0.0004213845,0.000602379,0.00008774463,0.011741163],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889505,0.0000019139532,0.0004311139,0.00022853016,0.00027283613,0.00017058208],"domain_scores_gemma":[0.99872184,0.000041732786,0.00028960776,0.00050723687,0.0004152975,0.00002426759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089102366,0.00019252641,0.00018359702,0.0006816899,0.00041750335,0.0006538599,0.0006444364,0.000056802648,0.0000034709308],"category_scores_gemma":[0.000028018914,0.00018624325,0.00001680506,0.00016217517,0.00036955831,0.0035320115,0.002246676,0.00011279584,0.000010184784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040993138,0.000047461388,0.001651818,0.0017102793,0.00004303287,2.6175118e-7,0.00080866035,0.0018945113,0.0000031024406,0.6569558,0.0032818366,0.33356228],"study_design_scores_gemma":[0.00062870944,0.000016456512,0.0024733306,0.00020017313,0.000040855466,0.0000012658929,0.000046595505,0.86354566,4.5049396e-7,0.007165881,0.1256391,0.00024151281],"about_ca_topic_score_codex":0.000009231016,"about_ca_topic_score_gemma":0.000014358883,"teacher_disagreement_score":0.8616512,"about_ca_system_score_codex":0.000061862695,"about_ca_system_score_gemma":0.00005520762,"threshold_uncertainty_score":0.759478},"labels":[],"label_agreement":null},{"id":"W117435862","doi":"10.1007/978-3-642-03986-7_12","title":"An Exploratory Investigation into the Effects of Adaptation in Child-Robot Interaction","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Adaptation (eye); Computer science; Robot; Exploratory research; Human–computer interaction; Psychology; Artificial intelligence; Neuroscience; Sociology; Social science","score_opus":0.06203880462817405,"score_gpt":0.3651082899474812,"score_spread":0.3030694853193071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W117435862","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0411242,0.0029282628,0.05990042,0.0072932723,0.007412367,0.0045223604,0.000013797474,0.00031211728,0.8764932],"genre_scores_gemma":[0.9925119,0.0012140183,0.0039964435,0.0015517882,0.00007344869,0.00007387513,0.00010196648,0.000010768687,0.00046577855],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998684,0.00013303135,0.0006528692,0.00017077957,0.00024250688,0.00011679985],"domain_scores_gemma":[0.9979524,0.00034457198,0.00047357424,0.00093509705,0.00024255687,0.00005182425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078264787,0.00014607138,0.00018322132,0.0008982895,0.00026901072,0.000122068086,0.00080906524,0.00013603336,0.00002143084],"category_scores_gemma":[0.00007358395,0.00013380426,0.000034296856,0.0003545069,0.0006199631,0.0036346763,0.00015745786,0.0005132436,0.000038489077],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018205099,0.000051604362,0.00010868227,0.000029713528,0.000007569153,2.9583632e-7,0.14575602,0.00065124896,0.000028698985,0.2447554,0.00010796825,0.60848457],"study_design_scores_gemma":[0.0054619345,0.0023483264,0.23658487,0.0060013677,0.00013079685,0.00012106268,0.035945933,0.40371633,0.00045182087,0.091650955,0.21497557,0.00261104],"about_ca_topic_score_codex":0.00015789403,"about_ca_topic_score_gemma":0.00031251454,"teacher_disagreement_score":0.9513877,"about_ca_system_score_codex":0.00015690463,"about_ca_system_score_gemma":0.00010500725,"threshold_uncertainty_score":0.54563797},"labels":[],"label_agreement":null},{"id":"W1229193984","doi":"10.1007/978-3-642-23141-4_9","title":"The Proactive and Reactive Digital Forensics Investigation Process: A Systematic Literature Review","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Digital forensics; Process (computing); Computer science; Digital evidence; Computer forensics; Automation; Data science; Computer security; Engineering","score_opus":0.026218134763513878,"score_gpt":0.248797007134284,"score_spread":0.22257887237077012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1229193984","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000052266456,0.06394983,0.099917345,0.003939998,0.000546863,0.004996579,0.00007016459,0.00028109123,0.82624584],"genre_scores_gemma":[0.13829817,0.7234958,0.10464834,0.017024938,0.00024311073,0.0016399993,0.0008033674,0.00012469414,0.013721586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984488,0.00002720527,0.0006552423,0.00025997683,0.0004239989,0.0001847651],"domain_scores_gemma":[0.99683124,0.0002500777,0.00053280924,0.00149303,0.00078952446,0.0001033385],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0008098993,0.00023446836,0.00029260546,0.00026895574,0.0005136153,0.0019639698,0.00204662,0.00008771038,1.9151743e-7],"category_scores_gemma":[0.00014671304,0.00016034127,0.000039826875,0.0005213773,0.0014101417,0.014242021,0.001457092,0.00038894985,0.000012777932],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011874416,0.0000045150496,0.000005103485,0.002697862,0.000011006746,3.683334e-7,0.0043840404,6.392872e-7,5.3993205e-8,0.86128074,0.00010985818,0.13150464],"study_design_scores_gemma":[0.0003892843,0.00023365638,0.0003869926,0.10122425,0.00006684188,0.00046063526,0.00017454372,0.052212235,0.000017824625,0.8174722,0.026240297,0.0011212438],"about_ca_topic_score_codex":9.968409e-7,"about_ca_topic_score_gemma":0.0000026562461,"teacher_disagreement_score":0.81252426,"about_ca_system_score_codex":0.00006981002,"about_ca_system_score_gemma":0.00023560826,"threshold_uncertainty_score":0.9995453},"labels":[],"label_agreement":null},{"id":"W124314188","doi":"10.1007/978-3-540-70600-7_14","title":"A Robust Class of Stable Proteins in the 2D HPC Model","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Conjecture; Inverse; Protein design; Sequence (biology); Protein folding; Folding (DSP implementation); Subclass; Protein structure prediction; Computer science; Protein structure; Stability (learning theory); Class (philosophy); Function (biology); Algorithm; Combinatorics; Mathematics; Chemistry; Geometry; Biology; Artificial intelligence","score_opus":0.0348962166270872,"score_gpt":0.26113133967667523,"score_spread":0.22623512304958804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W124314188","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008167391,0.002356579,0.43353584,0.0010669214,0.00012558042,0.0020723622,0.00012937127,0.000018820812,0.5525271],"genre_scores_gemma":[0.8463539,0.013541737,0.13639203,0.0016686919,0.000049363185,0.00009613855,0.00039912874,0.000015087392,0.0014839264],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924666,0.000016904962,0.00033964615,0.000113362395,0.00017882056,0.0001046143],"domain_scores_gemma":[0.99859625,0.000016830372,0.00016739195,0.001050901,0.00014818035,0.000020467285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041399134,0.000101009,0.000114656505,0.00019399209,0.0001319402,0.000043136453,0.0011265918,0.00011193937,8.367751e-7],"category_scores_gemma":[0.000021047947,0.000081179474,0.000025922274,0.00012414603,0.0006029611,0.00008858082,0.0005928404,0.00019827682,0.0000011031974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084817846,0.0001650022,0.00047010367,0.000290539,0.00003908711,0.000001341452,0.014622883,0.19356407,0.0018693105,0.6005199,0.0031196468,0.1852533],"study_design_scores_gemma":[0.0004762817,0.00012775039,0.0006948684,0.00013796061,0.0000061142605,0.000039189974,0.00006594811,0.88105166,0.00026000323,0.004200737,0.1126166,0.00032288753],"about_ca_topic_score_codex":0.000012664889,"about_ca_topic_score_gemma":0.000043535023,"teacher_disagreement_score":0.8381865,"about_ca_system_score_codex":0.000021185939,"about_ca_system_score_gemma":0.00023724606,"threshold_uncertainty_score":0.3310403},"labels":[],"label_agreement":null},{"id":"W129528139","doi":"10.1007/978-3-642-35267-6_17","title":"Enhancing Smartphone Malware Detection Performance by Applying Machine Learning Hybrid Classifiers","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Malware; Computer science; Machine learning; Artificial intelligence; Thread (computing); Phone; Classifier (UML); Cascading classifiers; Support vector machine; Operating system; Random subspace method","score_opus":0.020269384835075403,"score_gpt":0.2537384894754065,"score_spread":0.2334691046403311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W129528139","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017295903,0.0009185659,0.9801834,0.000116473304,0.0003307903,0.00048004466,0.000008628043,0.00048790954,0.017301193],"genre_scores_gemma":[0.65433997,0.01299838,0.32932404,0.00073413673,0.00008940863,0.00027098565,0.00012290975,0.000042292722,0.002077881],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997846,0.000047533777,0.0007892232,0.00038374143,0.0005297652,0.00040370287],"domain_scores_gemma":[0.99711853,0.00017113506,0.00058639975,0.0016323065,0.0003376724,0.0001539818],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013132516,0.00032589395,0.00029632248,0.0011143422,0.001098056,0.0004902313,0.0023637656,0.00014553413,0.000009264964],"category_scores_gemma":[0.000057300098,0.00035666002,0.000052944186,0.0005277754,0.000561774,0.01182523,0.002216666,0.0010598835,0.000058187507],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030702074,0.000009700545,0.000048783982,0.000046296198,0.0000043346595,1.8681412e-7,0.0005114556,0.00016530423,0.0003242635,0.009301618,0.000031893556,0.9895531],"study_design_scores_gemma":[0.00029372078,0.00013396272,0.00028938288,0.00029347232,0.000008249711,0.0001134596,0.00002091714,0.47956744,0.008529247,0.0010298988,0.5089927,0.0007276023],"about_ca_topic_score_codex":0.000015449803,"about_ca_topic_score_gemma":0.000010514286,"teacher_disagreement_score":0.9888255,"about_ca_system_score_codex":0.0004004633,"about_ca_system_score_gemma":0.00012158586,"threshold_uncertainty_score":0.99988854},"labels":[],"label_agreement":null},{"id":"W129830436","doi":"10.1007/978-3-642-21402-8_23","title":"Naive Bayesian Classifier Based on the Improved Feature Weighting Algorithm","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Weighting; Computer science; Naive Bayes classifier; Feature (linguistics); Classifier (UML); Text categorization; Artificial intelligence; Search engine indexing; Bayesian probability; Data mining; Categorization; Information retrieval; Machine learning; Pattern recognition (psychology); Support vector machine","score_opus":0.036231446674629415,"score_gpt":0.26089570440606147,"score_spread":0.22466425773143206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W129830436","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000027417782,0.000080482576,0.7194123,0.011211149,0.00020428468,0.000433782,0.000008131448,0.00022092332,0.26842618],"genre_scores_gemma":[0.09254213,0.0018011146,0.88390946,0.011775487,0.00008016842,0.00030373465,0.00008980077,0.000037532507,0.009460562],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998368,0.00004660796,0.0005114738,0.00036082024,0.00044017303,0.0002728765],"domain_scores_gemma":[0.9952272,0.0004841798,0.00047870114,0.0033947292,0.00033881312,0.0000763683],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0011313672,0.00027982253,0.00021456818,0.00091882795,0.00083388784,0.0008662243,0.0055482495,0.00022258684,0.00003102172],"category_scores_gemma":[0.00009427998,0.00020565477,0.00006582181,0.0005706344,0.0011156608,0.0035944816,0.0018432112,0.00080458843,0.000074885145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.974012e-7,0.000009449984,0.0000062738877,0.000004150764,0.0000025667882,1.2642698e-7,0.00033301403,0.0000033225192,0.0000024335989,0.712882,0.0007507562,0.28600505],"study_design_scores_gemma":[0.00014282728,0.000067824694,0.00025522636,0.00014009164,0.000003359053,0.0000036393697,0.000032661108,0.82160646,0.000075750075,0.033330716,0.1440541,0.0002873792],"about_ca_topic_score_codex":0.0000062776608,"about_ca_topic_score_gemma":0.0000028645757,"teacher_disagreement_score":0.8216031,"about_ca_system_score_codex":0.00014547782,"about_ca_system_score_gemma":0.00028089964,"threshold_uncertainty_score":0.9998322},"labels":[],"label_agreement":null},{"id":"W136302570","doi":"10.1007/978-3-642-29219-4_30","title":"An Intelligent Recommendation System for Individual and Group of Mobile Marketplace Users Based on the Influence of Items’ Features among User Profile","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Computer science; Recommender system; Purchasing; Mobile commerce; Mobile phone; Wireless; The Internet; Loyalty; World Wide Web; Business; Marketing","score_opus":0.032920845607483956,"score_gpt":0.2865635223419517,"score_spread":0.2536426767344677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W136302570","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014085159,0.00044194984,0.95274806,0.0007183833,0.00046777134,0.005530605,0.00022893633,0.00021505026,0.025564112],"genre_scores_gemma":[0.93121713,0.00026983037,0.06795925,0.0001881147,0.000013262694,0.00023923052,0.00007146739,0.000008190339,0.00003351999],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983946,0.000109590364,0.0007766751,0.00021818356,0.0003359221,0.00016503762],"domain_scores_gemma":[0.99653643,0.0006742098,0.0007986531,0.0015480572,0.00037183726,0.000070790025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030986452,0.0001905995,0.0002757042,0.00063227426,0.00027831498,0.0002748604,0.0021584593,0.00012605215,0.0000020605248],"category_scores_gemma":[0.00003196769,0.00014730083,0.000043088443,0.0002627669,0.000539389,0.003750885,0.0007202731,0.0002362442,6.9880014e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015933741,0.000072601404,0.0014864979,0.000416077,0.000017594182,3.5164593e-8,0.004540672,0.0007047389,0.00002396904,0.7155723,0.0005030738,0.27664652],"study_design_scores_gemma":[0.0008859342,0.001292064,0.05749176,0.0035109052,0.00004642555,0.000022801069,0.00080823526,0.8772859,0.0012074707,0.0027813565,0.05364037,0.0010267822],"about_ca_topic_score_codex":0.000039017792,"about_ca_topic_score_gemma":0.000010179108,"teacher_disagreement_score":0.91713196,"about_ca_system_score_codex":0.0000815066,"about_ca_system_score_gemma":0.000089266956,"threshold_uncertainty_score":0.6006754},"labels":[],"label_agreement":null},{"id":"W136738757","doi":"10.1007/978-3-642-02394-1_25","title":"Pairwise Well-Formed Scales and a Bestiary of Animals on the Hexagonal Lattice","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Musicology and Musical Analysis","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Centre for Interdisciplinary Research in Music Media and Technology","funders":"","keywords":"Lattice (music); Pairwise comparison; Combinatorics; Mathematics; Hexagonal lattice; Cardinality (data modeling); Hexagonal crystal system; Physics; Crystallography; Computer science; Chemistry; Condensed matter physics; Statistics; Data mining","score_opus":0.06297693009376046,"score_gpt":0.26787594676423443,"score_spread":0.20489901667047397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W136738757","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003996559,0.00050023285,0.00027237943,0.005418958,0.00008947279,0.00026644397,0.000027899529,0.00002067528,0.98940736],"genre_scores_gemma":[0.9813639,0.002358074,0.0024873617,0.008466066,0.00012019265,0.000019496252,0.000042640644,0.0000066914977,0.005135613],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99922,0.000027257895,0.00037169244,0.00010066185,0.00018441275,0.00009597478],"domain_scores_gemma":[0.99859977,0.00044584612,0.0002006409,0.0005333573,0.00018221787,0.00003815512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006211963,0.0001112395,0.00017441582,0.00031699825,0.00056571275,0.0001640818,0.0006132836,0.000053100393,0.00015089734],"category_scores_gemma":[0.00003187716,0.000075811105,0.000036061483,0.000057981473,0.002521584,0.00080366107,0.0003499488,0.00023934575,0.000022422657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004281054,0.000013383835,0.000010805851,0.000011551368,0.00000659229,6.186605e-8,0.003461962,0.0000061497394,4.539651e-7,0.9363142,0.0004629854,0.059707552],"study_design_scores_gemma":[0.00024402633,0.00020563026,0.003926113,0.00029356775,0.000038455015,0.000006302424,0.00036164376,0.022503225,0.000003869319,0.071628846,0.900519,0.00026932813],"about_ca_topic_score_codex":0.000014027571,"about_ca_topic_score_gemma":0.0000917402,"teacher_disagreement_score":0.98427176,"about_ca_system_score_codex":0.000017257431,"about_ca_system_score_gemma":0.000054474636,"threshold_uncertainty_score":0.9290882},"labels":[],"label_agreement":null},{"id":"W1409963766","doi":"10.1007/978-3-319-05416-2_8","title":"TTM/PAT: Specifying and Verifying Timed Transition Models","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Transition (genetics); Chemistry","score_opus":0.08261568473586745,"score_gpt":0.30593492464808036,"score_spread":0.22331923991221292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1409963766","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000044865257,0.00029862972,0.885579,0.0005318655,0.00023198742,0.0003153988,0.0000048661354,0.000109271445,0.11288412],"genre_scores_gemma":[0.040935762,0.0031595188,0.95449847,0.0009556219,0.00004823588,0.000029340714,0.000034922243,0.000012698627,0.00032545446],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980728,0.00007079619,0.0007457777,0.00037387814,0.00047969885,0.0002570341],"domain_scores_gemma":[0.9969829,0.00016189687,0.00036958273,0.0020543917,0.00030541382,0.00012586753],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0020951538,0.00025206245,0.00028760472,0.0009811458,0.00059774076,0.0007743425,0.0024050283,0.00017152203,0.0000034658365],"category_scores_gemma":[0.000042738673,0.00026911317,0.00003993764,0.00037822296,0.0007134216,0.009662795,0.0014337759,0.0004892106,0.00003113015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016202093,0.000003952539,0.0000015359207,0.000032311073,0.0000022480515,1.0778067e-7,0.0022559008,0.00064891804,0.000005438367,0.70484835,0.0000294032,0.2921702],"study_design_scores_gemma":[0.00021839321,0.00004051245,0.0001874609,0.00020769006,0.000005098397,0.00003108145,0.000019752018,0.94547427,0.000021386128,0.02778654,0.025711806,0.0002960165],"about_ca_topic_score_codex":0.000008814096,"about_ca_topic_score_gemma":0.000002554182,"teacher_disagreement_score":0.94482535,"about_ca_system_score_codex":0.00014283108,"about_ca_system_score_gemma":0.00014005676,"threshold_uncertainty_score":0.9999761},"labels":[],"label_agreement":null},{"id":"W1423767289","doi":"10.1007/978-3-642-11819-7_3","title":"How Do Emotions Induce Dominant Learners’ Mental States Predicted from Their Brainwaves?","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cognitive Science and Education Research","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Eurostars; Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability (semiconductor); Set (abstract data type); Psychology; Brain activity and meditation; Amplitude; Cognitive psychology; Computer science; Audiology; Electroencephalography; Physics; Neuroscience","score_opus":0.08786288318167061,"score_gpt":0.33762950664717195,"score_spread":0.24976662346550133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1423767289","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22393642,0.0007569364,0.04604751,0.06904491,0.005862974,0.0064610476,0.0041422676,0.000560898,0.64318705],"genre_scores_gemma":[0.978397,0.0065496187,0.0059740804,0.002227538,0.00012833872,0.00007188448,0.00045253066,0.000021446058,0.0061775804],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997931,0.00007838347,0.00047547725,0.0004502618,0.0007090678,0.00035579596],"domain_scores_gemma":[0.9969928,0.00064618886,0.0003057271,0.0014602374,0.0003870313,0.00020798908],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00089595444,0.00024571724,0.00022220789,0.0010668341,0.0012798741,0.001673813,0.002426853,0.00015687857,0.00010349686],"category_scores_gemma":[0.0004611082,0.00021493876,0.000053757623,0.0006579881,0.003501147,0.0059960918,0.0016894898,0.0010245204,0.00007978707],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002562683,0.0002067373,0.00032038664,0.00003751661,0.00001362461,0.0000013234469,0.05432011,0.00003236408,0.016679926,0.123800546,0.0014430116,0.8031188],"study_design_scores_gemma":[0.0013243672,0.00023335063,0.010171148,0.0006030665,0.000017316604,0.00006673583,0.004415414,0.08374584,0.014259345,0.041308716,0.84254175,0.0013129556],"about_ca_topic_score_codex":0.00003151602,"about_ca_topic_score_gemma":0.000030572046,"teacher_disagreement_score":0.8410987,"about_ca_system_score_codex":0.00012421727,"about_ca_system_score_gemma":0.00053971604,"threshold_uncertainty_score":0.9993625},"labels":[],"label_agreement":null},{"id":"W1425000130","doi":"10.1007/978-3-642-37186-8_28","title":"Assessing the Impact of In-government Cooperation Dynamics: A Simluation-Based Systems Inquiry","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alpha Technologies (Canada)","funders":"","keywords":"Gee; Proposition; Government (linguistics); Iterated function; Computer science; Dynamics (music); Key (lock); Generalized estimating equation; System dynamics; Operations research; Mathematics; Artificial intelligence; Psychology; Epistemology; Computer security; Machine learning; Linguistics","score_opus":0.21169883553944527,"score_gpt":0.4471062258214613,"score_spread":0.23540739028201604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1425000130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015255792,0.0010848207,0.7872927,0.00051891117,0.0009857925,0.0021513575,0.00006708112,0.000035641344,0.1926079],"genre_scores_gemma":[0.9962643,0.00005101666,0.0030394327,0.00009157906,0.00002963953,0.000034843604,0.000016257378,0.0000064231454,0.00046653155],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99524707,0.00019214282,0.0021040305,0.00028898037,0.0019606187,0.00020718186],"domain_scores_gemma":[0.9922822,0.0027252997,0.0013353076,0.0023337533,0.0012558141,0.000067636254],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007603069,0.00021414808,0.0004377094,0.0010928804,0.0004521173,0.0024958155,0.002565765,0.000116802774,0.000053628108],"category_scores_gemma":[0.0007608782,0.00013715579,0.00009860164,0.000943539,0.00082869857,0.0056183906,0.0010719603,0.00033508756,0.000055366712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009053249,0.000054631673,0.0043430845,0.000030265646,0.000012260823,3.4829245e-7,0.0042303503,0.25301936,0.000012405542,0.48498294,0.0012809014,0.2520244],"study_design_scores_gemma":[0.00022200713,0.000038519138,0.021925062,0.00029366754,0.000002523553,0.000004734821,0.00051257,0.9697662,6.502037e-7,0.004674658,0.0024125506,0.00014686988],"about_ca_topic_score_codex":0.00022662373,"about_ca_topic_score_gemma":0.00006380448,"teacher_disagreement_score":0.98100847,"about_ca_system_score_codex":0.0006621303,"about_ca_system_score_gemma":0.0006258195,"threshold_uncertainty_score":0.9985397},"labels":[],"label_agreement":null},{"id":"W1430091258","doi":"10.1007/978-3-319-05416-2_5","title":"Early Analysis of Soft Error Effects for Aerospace Applications Using Probabilistic Model Checking","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Radiation Effects in Electronics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure; Concordia University","funders":"","keywords":"Computer science; Aerospace; Probabilistic logic; Soft error; Model checking; Artificial intelligence; Aerospace engineering; Algorithm; Engineering; Electronic engineering","score_opus":0.024600854603288036,"score_gpt":0.2809173545025204,"score_spread":0.2563164998992324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1430091258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010403254,0.00024602638,0.9909297,0.000018843235,0.00005807751,0.00093098107,0.00002859659,0.00007487964,0.0066725356],"genre_scores_gemma":[0.80711174,0.0001901854,0.19200854,0.00008880703,0.000027454795,0.0002621617,0.00013672082,0.000030156692,0.0001442114],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884874,0.000012683094,0.00056160573,0.00015652367,0.00022801505,0.00019245426],"domain_scores_gemma":[0.99777776,0.0004482624,0.0002646154,0.001150521,0.00030378147,0.000055035063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006700475,0.0001802654,0.0003504631,0.0011888432,0.00021613603,0.0001113237,0.0008921165,0.00012260959,8.0327106e-7],"category_scores_gemma":[0.000053123073,0.000203661,0.000081898645,0.00067406904,0.0003901698,0.0009899633,0.00020011961,0.0002250614,0.0000019912716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.0949127e-7,0.000003732962,0.000008511356,0.00015509145,0.00004031666,3.2386642e-9,0.00042716344,0.87134236,0.0000126169425,0.105327524,0.0000073187057,0.022674544],"study_design_scores_gemma":[0.00013066092,0.00002003639,0.00018513452,0.00008268677,0.00015266788,5.725063e-7,0.0000020416855,0.9947059,0.000013993459,0.002442671,0.0020777008,0.00018592087],"about_ca_topic_score_codex":0.00000399866,"about_ca_topic_score_gemma":0.000009648235,"teacher_disagreement_score":0.80607146,"about_ca_system_score_codex":0.0002586364,"about_ca_system_score_gemma":0.00012678448,"threshold_uncertainty_score":0.83050543},"labels":[],"label_agreement":null},{"id":"W1456458654","doi":"10.1007/978-3-540-89682-1_3","title":"Procedural Natural Phenomena from Least-Cost Paths in a Weighted Graph","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Graph; Computer science; Lattice (music); Generator (circuit theory); Process (computing); Path (computing); Topology (electrical circuits); Algorithm; Theoretical computer science; Combinatorics; Mathematics; Physics; Programming language","score_opus":0.03366037246700519,"score_gpt":0.2894592462549842,"score_spread":0.255798873787979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1456458654","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040196185,0.0024802284,0.76005745,0.0034593446,0.001358578,0.0016786816,0.0002013963,0.0004062875,0.22995608],"genre_scores_gemma":[0.3959567,0.0533053,0.51558334,0.022296213,0.00038731218,0.00023357896,0.004203235,0.000086033804,0.007948296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998037,0.000033604516,0.0007992855,0.0003517603,0.0005108579,0.00026753504],"domain_scores_gemma":[0.9973618,0.000113960006,0.000342697,0.0017490446,0.0003202442,0.00011229849],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004391365,0.00024998962,0.00028416867,0.0014079249,0.00035522913,0.0006145099,0.0037300878,0.000105194726,0.000008773615],"category_scores_gemma":[0.00003632167,0.00024552233,0.00004623795,0.0009769412,0.0006992158,0.007842627,0.0020652902,0.0004942086,0.00006692177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005144757,0.0000721164,0.00024869194,0.000031161737,0.000011623368,0.0000030023443,0.008195121,0.0001593618,0.0000032524936,0.63462234,0.0025085132,0.3541397],"study_design_scores_gemma":[0.00045772965,0.000021624805,0.0018693422,0.00020798825,0.0000029350672,0.000016193111,0.000029441293,0.8139742,0.000004108934,0.0049512507,0.17809087,0.00037429432],"about_ca_topic_score_codex":0.000039996463,"about_ca_topic_score_gemma":0.000055238666,"teacher_disagreement_score":0.8138149,"about_ca_system_score_codex":0.00015372856,"about_ca_system_score_gemma":0.00037186858,"threshold_uncertainty_score":0.9999997},"labels":[],"label_agreement":null},{"id":"W1475923201","doi":"10.1007/978-3-642-32350-8_4","title":"Feature-First Hole Filling Strategy for 3D Meshes","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Feature (linguistics); Polygon mesh; Salient; Computer science; Planar; Process (computing); Filling-in; Ambiguity; Algorithm; Artificial intelligence; Computer graphics (images)","score_opus":0.043482553811258366,"score_gpt":0.2659798546514668,"score_spread":0.2224973008402084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1475923201","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006235511,0.0012965223,0.7859547,0.00044240302,0.00016060333,0.00032508635,0.00003708473,0.00014931214,0.21157193],"genre_scores_gemma":[0.36160195,0.020396719,0.60485506,0.0006885628,0.00021172964,0.00021322437,0.00066469837,0.000064661755,0.011303397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930066,0.000003336366,0.0002948359,0.00010707465,0.00014788623,0.00014620919],"domain_scores_gemma":[0.9988694,0.00009883873,0.00007617085,0.0007057737,0.00019774631,0.000052059284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003009535,0.00014582326,0.00017541193,0.00044046718,0.00030740176,0.00033830322,0.0007527582,0.000101311794,0.0000115682315],"category_scores_gemma":[0.000010930737,0.0001430633,0.0000437208,0.00013669224,0.00020634956,0.0018113382,0.0001957277,0.00023057693,0.000040283085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.933112e-7,0.0000056083327,0.0000070975752,0.00013599187,0.000023595465,5.1989133e-8,0.0010279975,0.57485795,0.0000023175728,0.048422553,0.0037346648,0.37178126],"study_design_scores_gemma":[0.00007388664,0.000008778458,0.00002079414,0.00010146475,0.000007660882,0.0000010177348,0.000013363136,0.8665868,0.0000028031384,0.0008995776,0.13213857,0.00014527173],"about_ca_topic_score_codex":0.0000051452726,"about_ca_topic_score_gemma":0.000011008397,"teacher_disagreement_score":0.371636,"about_ca_system_score_codex":0.000060469443,"about_ca_system_score_gemma":0.000041364863,"threshold_uncertainty_score":0.5833952},"labels":[],"label_agreement":null},{"id":"W1477413762","doi":"10.1007/978-3-642-29764-9_15","title":"Automated Reasoning Support for Ontology Development","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Ontology; Process ontology; Computer science; Ontology-based data integration; Upper ontology; Suggested Upper Merged Ontology; Automated reasoning; Description logic; Axiom; Software engineering; Artificial intelligence; Domain knowledge; Mathematics","score_opus":0.04963008229988195,"score_gpt":0.308715722192654,"score_spread":0.259085639892772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1477413762","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000062206884,0.00021605409,0.78461486,0.0010187805,0.0004443231,0.00065784965,0.000003744858,0.00045948205,0.21252272],"genre_scores_gemma":[0.009117318,0.00040428236,0.98669535,0.0011201502,0.000018539104,0.00010685728,0.000058773516,0.0000068869836,0.0024718195],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851364,0.000015586442,0.000665782,0.00026710166,0.00025744157,0.0002804628],"domain_scores_gemma":[0.99744403,0.00024847957,0.00031537097,0.0014848046,0.0004272923,0.00007999295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008723156,0.00019308891,0.0002645435,0.00068204344,0.0004828432,0.00053343456,0.0032021871,0.00014049404,0.000010130385],"category_scores_gemma":[0.00007093342,0.00018277457,0.000034056833,0.00019481871,0.00052601664,0.0044576344,0.0018689705,0.00020075866,0.00011309451],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.269942e-7,0.0000070479277,0.000029469124,0.000021820964,0.000005186975,1.7859247e-7,0.0016373158,0.000028919936,0.0000010605598,0.73988765,0.0011778637,0.25720266],"study_design_scores_gemma":[0.00025309916,0.000051076902,0.002493527,0.000108975095,0.0000031940797,0.00003244801,0.00001804382,0.62749374,0.000017829832,0.005034347,0.36420932,0.00028440828],"about_ca_topic_score_codex":0.000010469457,"about_ca_topic_score_gemma":0.000016457927,"teacher_disagreement_score":0.7348533,"about_ca_system_score_codex":0.00012799136,"about_ca_system_score_gemma":0.0005663549,"threshold_uncertainty_score":0.7453331},"labels":[],"label_agreement":null},{"id":"W1479855793","doi":"10.1007/978-3-540-88708-9_12","title":"VNEC - A Virtual Network Experiment Controller","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Virtual machine; Network topology; Distributed computing; Controller (irrigation); Virtual network; Topology (electrical circuits); Computer network; Operating system; Engineering","score_opus":0.02823943772392596,"score_gpt":0.26308126641958074,"score_spread":0.2348418286956548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1479855793","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000056433448,0.0019598429,0.7161395,0.0009809727,0.0010709994,0.0006428159,0.000003791509,0.0002142831,0.27893135],"genre_scores_gemma":[0.32506597,0.099999174,0.5409936,0.017818194,0.0014109933,0.0003979726,0.00015263191,0.000079147394,0.014082337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980265,0.000045125304,0.00074329664,0.0003272299,0.0005443778,0.0003134534],"domain_scores_gemma":[0.9972871,0.00018830516,0.0003514974,0.0017349494,0.00030490768,0.00013324659],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008296734,0.00024931727,0.0003065592,0.00061316596,0.00091825146,0.0005294226,0.0029539522,0.00016825229,0.000016394586],"category_scores_gemma":[0.000021846903,0.00024894148,0.000067636385,0.00047701527,0.00086628785,0.0060646017,0.0027103513,0.0005242846,0.000116090916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005271009,0.000015567099,0.0000033332583,0.000004144998,0.000006473966,5.9536427e-7,0.0020530694,0.0016329029,0.0000016581901,0.6858483,0.0036401965,0.3067885],"study_design_scores_gemma":[0.0003302826,0.0001001689,0.00008796159,0.00010187245,0.0000021789133,0.00004186649,0.000006457009,0.4500599,0.0000066427406,0.0036116864,0.5453933,0.0002577291],"about_ca_topic_score_codex":0.000011187069,"about_ca_topic_score_gemma":0.0000068395198,"teacher_disagreement_score":0.6822366,"about_ca_system_score_codex":0.00016737684,"about_ca_system_score_gemma":0.00023494086,"threshold_uncertainty_score":0.9999963},"labels":[],"label_agreement":null},{"id":"W1480087548","doi":"10.1007/978-3-540-70600-7_5","title":"Fast Structured Motif Search in DNA Sequences","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Motif (music); Suffix tree; Computer science; Suffix; Computational biology; Generalized suffix tree; Information retrieval; Theoretical computer science; Biology; Data structure; Programming language; Physics","score_opus":0.04631917222744384,"score_gpt":0.29691647539454136,"score_spread":0.2505973031670975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1480087548","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010242586,0.0014989638,0.7521669,0.0018929591,0.00088622904,0.0010638771,0.0000770703,0.0002315275,0.24115822],"genre_scores_gemma":[0.17810537,0.022714792,0.7946951,0.0017982484,0.00013621086,0.00005567643,0.00032168833,0.000027896185,0.002145033],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798554,0.000043815806,0.00068006595,0.00036216737,0.00063572347,0.00029265764],"domain_scores_gemma":[0.99696004,0.00014546701,0.00021624201,0.0022932028,0.00027041364,0.00011461824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007635855,0.00022741314,0.0002658073,0.0012765484,0.0004784312,0.000583179,0.004938252,0.00014091602,0.00000907216],"category_scores_gemma":[0.000022083572,0.00021127235,0.000035063316,0.0006345405,0.0009887012,0.008937226,0.004098461,0.0005831108,0.00004134233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024361175,0.000020732181,0.00015171216,0.00002705674,0.0000035830315,0.0000037285783,0.005539506,0.0014356928,0.000009410495,0.2707685,0.0004841642,0.7215535],"study_design_scores_gemma":[0.00036991813,0.000053268457,0.0066796457,0.00029879002,0.00000150201,0.00008526762,0.000034373334,0.9120482,0.000029279845,0.005400648,0.07456655,0.00043256633],"about_ca_topic_score_codex":0.000058892758,"about_ca_topic_score_gemma":0.000030624,"teacher_disagreement_score":0.9106125,"about_ca_system_score_codex":0.00016295069,"about_ca_system_score_gemma":0.00044374084,"threshold_uncertainty_score":0.9176582},"labels":[],"label_agreement":null},{"id":"W1491651839","doi":"10.1007/978-3-540-87477-5_64","title":"VNSOptClust: A Variable Neighborhood Search Based Approach for Unsupervised Anomaly Detection","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Computer science; Anomaly detection; Dependency (UML); Data mining; Partition (number theory); Statistic; Exploit; Pattern recognition (psychology); Variable (mathematics); Metaheuristic; Artificial intelligence; Algorithm; Mathematics; Statistics","score_opus":0.03938907254950063,"score_gpt":0.257669813603504,"score_spread":0.21828074105400336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1491651839","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018117958,0.00023634119,0.9189473,0.00023042748,0.00025801748,0.0007774043,0.00001288098,0.00013330464,0.07938621],"genre_scores_gemma":[0.098380245,0.0022313646,0.89657855,0.0015923578,0.00014252355,0.00020263148,0.00014954936,0.00002377489,0.00069897744],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99791014,0.000057458215,0.00070190354,0.00044808484,0.0005325341,0.00034988087],"domain_scores_gemma":[0.99658936,0.00028027853,0.00025879004,0.0020405308,0.0006921297,0.00013892194],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013209557,0.0002709401,0.00029706003,0.0012650517,0.0012242349,0.0006394334,0.0029077937,0.00023841085,0.00000697179],"category_scores_gemma":[0.00004228788,0.00028492056,0.00008149171,0.0009135567,0.00059346453,0.0060760407,0.0013316692,0.00054842647,0.000015890839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027416896,0.0000921934,0.000017096492,0.00013447808,0.000014174318,3.196811e-7,0.0018350284,0.014383593,0.000026679685,0.41715652,0.00037183618,0.5659407],"study_design_scores_gemma":[0.0004937394,0.00013615325,0.000076739176,0.00006644142,0.000004911187,0.00002705543,0.000007702979,0.906137,0.000054791806,0.0019266262,0.09078135,0.0002874778],"about_ca_topic_score_codex":0.000024248255,"about_ca_topic_score_gemma":0.0000060400894,"teacher_disagreement_score":0.89175344,"about_ca_system_score_codex":0.00021743977,"about_ca_system_score_gemma":0.0005208207,"threshold_uncertainty_score":0.9999603},"labels":[],"label_agreement":null},{"id":"W1499163112","doi":"10.1007/978-3-642-17578-7_9","title":"Exploring Empirically the Relationship between Lack of Cohesion and Testability in Object-Oriented Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Testability; Cohesion (chemistry); Computer science; Object-oriented programming; Engineering; Reliability engineering; Programming language; Chemistry","score_opus":0.28110740335610207,"score_gpt":0.36295490499261546,"score_spread":0.08184750163651339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1499163112","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2136199,0.0011221458,0.7626997,0.0028453635,0.0009784361,0.0026763205,0.000043161934,0.00030190658,0.015713051],"genre_scores_gemma":[0.97133994,0.00031668195,0.028190484,0.000030563926,0.00001626911,0.000041990716,0.000011490688,0.000005302885,0.00004728297],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99830794,0.000067219255,0.0007115914,0.00022807588,0.0005000968,0.00018504997],"domain_scores_gemma":[0.9925766,0.0048829154,0.00022306475,0.0019071031,0.00033503785,0.00007525396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029113689,0.00014307039,0.00022654317,0.0008496376,0.00028182485,0.00027366687,0.0021515333,0.00010733081,6.126391e-7],"category_scores_gemma":[0.0011795153,0.00011964956,0.000021639651,0.0007763325,0.00090802053,0.0039470224,0.0020656679,0.000835291,0.0000050006815],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004722777,0.000028245968,0.40244013,0.00023842264,0.0000058659575,3.8843675e-7,0.009972286,0.0006690797,0.000013051778,0.53390914,0.000017817123,0.052700877],"study_design_scores_gemma":[0.00019441028,0.000043011496,0.9193968,0.00033220733,0.0000024441408,0.00000687359,0.000033085344,0.07192397,0.000010814734,0.0024487276,0.005426648,0.00018100516],"about_ca_topic_score_codex":0.000050257604,"about_ca_topic_score_gemma":0.000014022618,"teacher_disagreement_score":0.75772005,"about_ca_system_score_codex":0.00010891666,"about_ca_system_score_gemma":0.00022401205,"threshold_uncertainty_score":0.48791674},"labels":[],"label_agreement":null},{"id":"W1507036518","doi":"10.1007/978-3-642-29166-1_10","title":"Knowledge Contribution in Social Media: Exploring Factors Influencing Social Taggers’ Acceptance towards Contributing and Sharing Tags","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Social media; Computer science; Social acceptance; World Wide Web; Internet privacy; Psychology; Social psychology","score_opus":0.14692666213656888,"score_gpt":0.3532895536018112,"score_spread":0.2063628914652423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1507036518","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1708367,0.0051058424,0.007062207,0.0017158665,0.0021729101,0.0020603405,0.00006393575,0.00038573524,0.81059647],"genre_scores_gemma":[0.9967865,0.0022682329,0.0003525649,0.000058050216,0.0002789713,0.000033165616,0.000047561058,0.000009035232,0.0001659367],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99797416,0.000069334776,0.0007138995,0.00026040422,0.0004242749,0.0005579331],"domain_scores_gemma":[0.99848366,0.00031831753,0.00037156892,0.0003272857,0.00038835919,0.00011078434],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0034978874,0.00023000689,0.00036382928,0.0009528153,0.0025722836,0.00067887624,0.001218548,0.00020597085,0.00001856072],"category_scores_gemma":[0.00033848788,0.00025968178,0.000050003477,0.00057596096,0.0011938866,0.007935228,0.002176535,0.00057943,0.000012875398],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035769904,0.000013762038,0.006606284,0.000038117614,0.0000073854985,1.9038129e-7,0.19207759,0.0000038965522,0.000002638707,0.6080899,0.000029774883,0.19312684],"study_design_scores_gemma":[0.003690306,0.00005717571,0.43544468,0.0019383816,0.00011877446,0.0000035349326,0.039205413,0.028729962,0.000049733826,0.033055134,0.45460677,0.003100116],"about_ca_topic_score_codex":0.0000970673,"about_ca_topic_score_gemma":0.0006597391,"teacher_disagreement_score":0.8259498,"about_ca_system_score_codex":0.0006706843,"about_ca_system_score_gemma":0.00020700606,"threshold_uncertainty_score":0.9999855},"labels":[],"label_agreement":null},{"id":"W1510620796","doi":"10.1007/978-3-642-13166-0_69","title":"Recognizing the “Transformational” in Preservice Digital Literacy Assignments","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Literacy, Media, and Education","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Laptop; Transformative learning; Computer science; Literacy; Context (archaeology); Digital literacy; Transformational leadership; Mathematics education; Information literacy; Pedagogy; Critical literacy; World Wide Web; Sociology; Psychology","score_opus":0.04754475313877641,"score_gpt":0.28338640663034526,"score_spread":0.23584165349156885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1510620796","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0088042235,0.00080864545,0.0014836261,0.0039674663,0.00247691,0.0010298969,0.00019709315,0.00006918269,0.98116297],"genre_scores_gemma":[0.9839429,0.001507233,0.0038116279,0.002607304,0.0005801992,0.000109978544,0.0010280207,0.000018503051,0.0063942308],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.99872464,0.000019403646,0.000615429,0.000116564195,0.0003314428,0.00019253296],"domain_scores_gemma":[0.9983242,0.00030223187,0.00022409207,0.000764247,0.0003244306,0.000060773626],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0008151548,0.00015226309,0.000132621,0.00054119894,0.0006177395,0.0016735628,0.0011512919,0.00007207929,0.00014012356],"category_scores_gemma":[0.00003930951,0.0001193755,0.000030189998,0.00010096918,0.00079882,0.015155556,0.00036119262,0.00056397944,0.00012064417],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003157352,0.000032843865,0.00024148045,0.00004772212,0.000004309342,4.8567365e-8,0.6006371,0.000007652172,2.7475363e-7,0.16939683,0.00015781194,0.22947076],"study_design_scores_gemma":[0.00020442187,0.000014642681,0.0018883201,0.00027205888,0.0000061958704,0.000005806489,0.0026678357,0.009016397,0.0000020142647,0.01037092,0.9753181,0.00023333724],"about_ca_topic_score_codex":0.000032934204,"about_ca_topic_score_gemma":0.0000900907,"teacher_disagreement_score":0.97516024,"about_ca_system_score_codex":0.000080911435,"about_ca_system_score_gemma":0.00016771114,"threshold_uncertainty_score":0.99936277},"labels":[],"label_agreement":null},{"id":"W1514750263","doi":"10.1007/978-3-031-25477-2","title":"Computer Vision, Imaging and Computer Graphics Theory and Applications","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Russian Academy of Sciences; Universidad de León; Institute of Materials Science and Engineering, Washington University in St. Louis; Universidade Lusófona de Humanidades e Tecnologias; Lomonosov Moscow State University; Université de Paris; Universidade de Trás-os-Montes e Alto Douro; Tokyo Metropolitan University; Istituto Italiano di Tecnologia; Universitat de Lleida; Universidade Federal do Rio Grande do Norte; Hochschule Niederrhein; Technische Universität Ilmenau; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Trakya Üniversitesi; Universidad de Zaragoza; Iran University of Science and Technology; National Taipei University of Technology; Università degli Studi di Torino; Universidade do Minho; Turun Yliopisto; Università degli Studi di Pavia; Università degli Studi di Genova; Kuwait University; Universidad de Las Palmas de Gran Canaria; Université Paris Descartes; Royal Holloway, University of London; Nanyang Technological University; Università di Catania; Università degli Studi di Firenze; Université de Strasbourg; Lunds Universitet; Manchester Metropolitan University; Albert-Ludwigs-Universität Freiburg; Universitatea Tehnică din Cluj-Napoca; Deakin University; Universitat Jaume I; Università di Bologna; Aristotle University of Thessaloniki; Universidad del Cauca; National Central University; University of Wollongong; Centre National de la Recherche Scientifique; Universitat de Barcelona; Friedrich-Schiller-Universität Jena; Edinburgh Napier University; University of Alberta; University of South Dakota; Sveučilište u Zagrebu; University of Western Macedonia; Oulun Yliopisto; Yale University; University of Glasgow; Universidad de Jaén; Politechnika Warszawska; Università degli Studi di Cagliari; University of Essex; Universitat de Girona; Norges Teknisk-Naturvitenskapelige Universitet; Université de Bourgogne; Università degli Studi di Salerno; University of Patras; Universidade de Aveiro; University of Northern Colorado; Universidad de Sevilla; University of Otago; University of Thessaly; Universidade da Beira Interior; Università degli Studi dell'Insubria; Liverpool John Moores University; Politecnico di Torino; Concordia University; Trinity College Dublin","keywords":"Computer graphics; Computer science; Graphics; Computer graphics (images); Artificial intelligence; Computer vision","score_opus":0.014546422479047267,"score_gpt":0.2789725952838887,"score_spread":0.26442617280484143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1514750263","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013313875,0.0044589923,0.982006,0.00012295066,0.00031201993,0.00046073584,0.000032816875,0.00043230757,0.01204102],"genre_scores_gemma":[0.115487434,0.19315077,0.6704464,0.011376147,0.0018756785,0.0009009339,0.0022173845,0.000396015,0.004149234],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987852,0.00004440844,0.00049074704,0.00023360799,0.00021754121,0.00022846866],"domain_scores_gemma":[0.99820876,0.000549024,0.00010622973,0.0008259756,0.00019533909,0.00011466572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012136097,0.00022923,0.0002276048,0.0009956846,0.0004776286,0.00084327563,0.0007454094,0.000103447666,0.0000013273593],"category_scores_gemma":[0.000010961851,0.0002363567,0.000025023766,0.0007508628,0.0012353878,0.002105137,0.0009414715,0.00046905992,0.000017065013],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019428567,0.000009393275,0.00017669369,0.00026447306,0.00001038194,3.6552674e-7,0.0013485228,0.00038556344,0.0000018432672,0.04739517,0.0019998068,0.94840586],"study_design_scores_gemma":[0.00017804233,0.000016417827,0.0023743466,0.00027185061,0.000011313515,0.00004018349,0.000027622193,0.8501629,0.0000025655463,0.009012933,0.13760473,0.00029705165],"about_ca_topic_score_codex":0.0000044427925,"about_ca_topic_score_gemma":0.0000030849517,"teacher_disagreement_score":0.9481088,"about_ca_system_score_codex":0.000056905516,"about_ca_system_score_gemma":0.000084955966,"threshold_uncertainty_score":0.9638347},"labels":[],"label_agreement":null},{"id":"W1519599518","doi":"10.1007/978-3-642-15810-0_16","title":"The Real-Time Embedded System for a Humanoid: Betty","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Implementation; Queue; Humanoid robot; Controller (irrigation); Real-time computing; Embedded system; Robot; Artificial intelligence; Programming language","score_opus":0.015525688194168417,"score_gpt":0.24525535481869434,"score_spread":0.22972966662452593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1519599518","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007667035,0.00028980992,0.21928805,0.0005222572,0.0009408976,0.001342172,0.000034697867,0.0004051285,0.7771003],"genre_scores_gemma":[0.50366855,0.019999092,0.43088755,0.0015919666,0.0010871425,0.0017993827,0.00089412427,0.00023667894,0.039835516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991251,0.000009032535,0.00045454426,0.000087819026,0.00016823149,0.0001552537],"domain_scores_gemma":[0.9983128,0.00018726049,0.00011087339,0.0011345287,0.00020051413,0.000054048982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007108746,0.00013377747,0.00015687624,0.00022653994,0.0006598428,0.00036603096,0.0011681616,0.00010668879,0.00000430492],"category_scores_gemma":[0.000014968269,0.00010829497,0.00004095496,0.00008944357,0.00043591668,0.0010099099,0.00024273247,0.00027623805,0.0000571772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037268323,0.0000054045654,0.0000022179327,0.00010473544,0.00001764488,7.1704456e-8,0.0014254611,0.0028110277,0.00011459286,0.7910213,0.00086864154,0.20362522],"study_design_scores_gemma":[0.00026847346,0.000014322068,0.000076665536,0.00009206248,0.000007440278,0.0000052310747,0.00002989258,0.8041529,0.000016567861,0.0012942214,0.19387884,0.00016336748],"about_ca_topic_score_codex":0.0000021851256,"about_ca_topic_score_gemma":0.000006488125,"teacher_disagreement_score":0.8013419,"about_ca_system_score_codex":0.000093780865,"about_ca_system_score_gemma":0.00007703356,"threshold_uncertainty_score":0.5075044},"labels":[],"label_agreement":null},{"id":"W1531219651","doi":"10.1007/978-3-642-00405-6_13","title":"Managing Sustainability with the Support of Business Intelligence Methods and Tools","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Sustainability; Corporate social responsibility; Business intelligence; Knowledge management; Business; Process (computing); Process management; Business process; Computer science; Public relations; Political science; Marketing; Work in process; Ecology","score_opus":0.09041916479179023,"score_gpt":0.35654693540861343,"score_spread":0.2661277706168232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1531219651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015190023,0.00034873292,0.67449015,0.0092370575,0.00013432842,0.0007688711,0.000007650048,0.000052131898,0.31480917],"genre_scores_gemma":[0.70070714,0.015372155,0.26278636,0.015400168,0.0005200585,0.00013731726,0.0005638982,0.00007419478,0.004438724],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99883986,0.000011620278,0.00049610034,0.00020368113,0.00028170127,0.0001670602],"domain_scores_gemma":[0.9968455,0.00020374572,0.00043916187,0.0012231414,0.0012755797,0.000012914932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018294976,0.00018373306,0.00023236503,0.0006071991,0.000374434,0.00087195693,0.0015887425,0.00006627807,0.000019823763],"category_scores_gemma":[0.00012825144,0.00012876619,0.000019235638,0.0007726978,0.0018650923,0.0103587955,0.0015517417,0.00025992896,0.00000648646],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005958886,0.000006947101,0.000055675264,0.00013145972,0.0000024200592,1.0694526e-7,0.00015990768,0.00017618827,6.0630896e-7,0.28302035,0.00008475145,0.7163556],"study_design_scores_gemma":[0.0001504204,0.000032451415,0.013520318,0.0004022828,0.000049568185,0.000024565434,0.00042320206,0.09290788,0.000018288454,0.075212955,0.8167329,0.00052517606],"about_ca_topic_score_codex":0.00006610875,"about_ca_topic_score_gemma":0.000032194428,"teacher_disagreement_score":0.8166481,"about_ca_system_score_codex":0.00004347178,"about_ca_system_score_gemma":0.00014044979,"threshold_uncertainty_score":0.8408301},"labels":[],"label_agreement":null},{"id":"W15394667","doi":"10.1007/978-3-642-11840-1_12","title":"SRAD, Optical Flow and Primitive Prior Based Active Contours for Echocardiography","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Vector flow; Active contour model; Speckle pattern; Artificial intelligence; Computer vision; Computer science; Optical flow; Speckle noise; Sensitivity (control systems); Flow (mathematics); Pattern recognition (psychology); Image (mathematics); Image segmentation; Mathematics; Geometry; Engineering","score_opus":0.025682665331086905,"score_gpt":0.30500427117869383,"score_spread":0.2793216058476069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W15394667","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000139586,0.00007353944,0.9710181,0.0010443772,0.00016855991,0.00091292185,0.000033635075,0.00012199854,0.026612941],"genre_scores_gemma":[0.0039958637,0.00065047806,0.9932641,0.00179215,0.000026544694,0.00012280245,0.000056691773,0.000007789385,0.000083603794],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841374,0.000029856117,0.0005389251,0.00034375628,0.000443884,0.00022983235],"domain_scores_gemma":[0.9967469,0.0008132946,0.00028415295,0.001388478,0.0005816736,0.00018552945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001084362,0.000221818,0.000284496,0.0009827497,0.00047449156,0.00060720503,0.0020584567,0.00019115431,0.0000044709386],"category_scores_gemma":[0.0001826837,0.00021709657,0.00007022638,0.00029544637,0.0018718077,0.0047325287,0.0011542558,0.0005325339,0.000004857408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055500655,0.000015816706,0.000009785961,0.000031826276,0.000007920707,2.4083332e-7,0.0008623107,0.000008079386,0.000036177462,0.13995679,0.000114404276,0.8589511],"study_design_scores_gemma":[0.0021084768,0.00042272595,0.003907718,0.00063291076,0.000042008163,0.00003179225,0.00007058215,0.90149355,0.0048082103,0.025205033,0.060151886,0.0011251265],"about_ca_topic_score_codex":0.0000033795282,"about_ca_topic_score_gemma":0.0000047468784,"teacher_disagreement_score":0.90148544,"about_ca_system_score_codex":0.000078452795,"about_ca_system_score_gemma":0.00039497725,"threshold_uncertainty_score":0.88529414},"labels":[],"label_agreement":null},{"id":"W1542164216","doi":"10.1007/978-3-540-88479-8_57","title":"High Level Analysis, Design and Validation of Distributed Mobile Systems with CoreASM","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Scope (computer science); Computer science; Formalism (music); Key (lock); Systems engineering; Engineering design process; Distributed computing; Systems design; Process (computing); Complex system; Software engineering; Artificial intelligence; Computer security; Engineering; Programming language","score_opus":0.08772538851800345,"score_gpt":0.3042700937711864,"score_spread":0.21654470525318298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1542164216","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035249811,0.00033667262,0.9961605,0.000041579475,0.00009840302,0.00061255833,0.000048641385,0.000051104038,0.002298011],"genre_scores_gemma":[0.15353695,0.002546596,0.8435422,0.000036919893,0.000008722654,0.00006166892,0.00017028766,0.0000059634112,0.00009067717],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981042,0.00010043972,0.00080278865,0.00029127134,0.0005322075,0.00016905088],"domain_scores_gemma":[0.9961616,0.00027713404,0.0007621872,0.001987062,0.00072489295,0.00008714182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00153394,0.00021100718,0.00039287462,0.0012866379,0.00033311875,0.00032823253,0.0019647332,0.00012117288,0.0000012810116],"category_scores_gemma":[0.00003940573,0.0001905504,0.000033875353,0.001215801,0.0011058437,0.005013041,0.00090197753,0.00024449435,0.0000037521409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016171405,0.00004355555,0.0002344527,0.00009249654,0.000092049995,5.722721e-7,0.0028732298,0.10043542,0.000009511605,0.82782835,0.00010752283,0.06826664],"study_design_scores_gemma":[0.00028287029,0.00015104855,0.0039866543,0.00013589746,0.000042612257,0.000044246037,0.000020146159,0.9900772,0.00014741196,0.000718377,0.0041047563,0.00028876442],"about_ca_topic_score_codex":0.00004635036,"about_ca_topic_score_gemma":0.0000016396086,"teacher_disagreement_score":0.8896418,"about_ca_system_score_codex":0.0001149605,"about_ca_system_score_gemma":0.0002446362,"threshold_uncertainty_score":0.77704203},"labels":[],"label_agreement":null},{"id":"W1558411928","doi":"10.1007/978-3-642-30721-8_2","title":"Unsupervised Feature Selection for Spherical Data Modeling: Application to Image-Based Spam Filtering","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Feature selection; Cluster analysis; Generalization; Support vector machine; Feature (linguistics); Relevance (law); Kernel (algebra); Statistical model; Maximization; Machine learning; Image (mathematics); Data mining; Mathematics","score_opus":0.0817836262420554,"score_gpt":0.32714676094063966,"score_spread":0.24536313469858426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1558411928","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000032639396,0.00018446703,0.9900807,0.0031829632,0.000101543206,0.00097426714,0.000038731476,0.00022714252,0.005206898],"genre_scores_gemma":[0.009036091,0.00042971288,0.98836535,0.0012819392,0.000073677955,0.0001595391,0.000359741,0.000014553449,0.00027940806],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982377,0.000026159247,0.00056187087,0.00046837184,0.00041419634,0.0002916903],"domain_scores_gemma":[0.99563575,0.00013512226,0.00024463897,0.0031135897,0.0007084555,0.00016241639],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012608074,0.00024489447,0.00024258756,0.0005991776,0.00049201807,0.00070485496,0.0048932093,0.0001666752,0.000003833442],"category_scores_gemma":[0.00006524095,0.0002495916,0.000044611857,0.00058018684,0.00023574026,0.007094572,0.0022434935,0.0003379824,0.000035280682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013329351,0.00004967709,0.000015477448,0.00009513226,0.00000673703,3.3980193e-8,0.00050130073,0.00070362363,0.0006905119,0.22179604,0.00065851316,0.7754696],"study_design_scores_gemma":[0.0001444221,0.00003875921,0.000035822024,0.00006548731,0.000006051135,0.0000038084793,0.0000034271663,0.8424572,0.00032298113,0.0014710854,0.15520293,0.0002480841],"about_ca_topic_score_codex":0.0000098994515,"about_ca_topic_score_gemma":0.000004150465,"teacher_disagreement_score":0.84175354,"about_ca_system_score_codex":0.00020120366,"about_ca_system_score_gemma":0.00031220115,"threshold_uncertainty_score":0.99999565},"labels":[],"label_agreement":null},{"id":"W1576259802","doi":"10.1007/978-3-540-92219-3_1","title":"Using the Web and ICT to Enable Persons with Disabilities","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Information and Communications Technology; World Wide Web; Computer science","score_opus":0.0774619202872908,"score_gpt":0.29855841477931744,"score_spread":0.22109649449202662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576259802","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006476203,0.00088186644,0.76691014,0.010377984,0.00024073807,0.000921162,0.000024633431,0.0003208258,0.21384646],"genre_scores_gemma":[0.64529014,0.0017451375,0.350057,0.0015006103,0.000027877633,0.00003410012,0.000006148838,0.00001065409,0.001328358],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907887,0.000019859566,0.00026138636,0.0002127099,0.00024212987,0.00018506164],"domain_scores_gemma":[0.9979511,0.00020960507,0.000119396806,0.0014834439,0.00017466667,0.00006177681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043010013,0.00015048611,0.00015814406,0.00046995783,0.0008276257,0.00039763906,0.0020774396,0.00006243959,0.0000012155219],"category_scores_gemma":[0.000033091117,0.00010670003,0.00001688335,0.00036749407,0.0018987725,0.00225494,0.0017000716,0.00030476393,0.0000074329855],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002500567,0.000014306157,0.00050250185,0.000020308877,0.00000814518,5.45512e-7,0.011169541,0.0004695022,0.000008259754,0.88844794,0.00053677324,0.09881968],"study_design_scores_gemma":[0.00034766085,0.00018906272,0.002557325,0.00036081395,0.000010642192,0.00034330384,0.00051597314,0.6706428,0.000024064635,0.0041531823,0.3202811,0.00057408185],"about_ca_topic_score_codex":0.000022997629,"about_ca_topic_score_gemma":0.00002127258,"teacher_disagreement_score":0.88429475,"about_ca_system_score_codex":0.0000781455,"about_ca_system_score_gemma":0.00022137904,"threshold_uncertainty_score":0.69961065},"labels":[],"label_agreement":null},{"id":"W1586378172","doi":"10.1007/978-3-642-17878-8_66","title":"Dynamic Sink Placement in Wireless Sensor Networks","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Sink (geography); Wireless sensor network; Computer science; Energy consumption; Computer network; Wireless; Dissemination; Key distribution in wireless sensor networks; Real-time computing; Distributed computing; Wireless network; Engineering; Telecommunications; Electrical engineering","score_opus":0.015505453495852764,"score_gpt":0.2555979927719363,"score_spread":0.24009253927608354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586378172","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00064478937,0.00029463958,0.8911654,0.0009490202,0.0009393863,0.00054836884,0.000005205969,0.00016339294,0.105289795],"genre_scores_gemma":[0.3902857,0.008584074,0.59501326,0.0024320628,0.000092500755,0.00008891393,0.00018554751,0.00004805968,0.0032698715],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974745,0.00005210108,0.0009704534,0.00046879283,0.00057311024,0.0004610492],"domain_scores_gemma":[0.99578804,0.00033168666,0.00043460322,0.0030064487,0.0002958521,0.00014339953],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001285841,0.00033905884,0.0003633276,0.0014081303,0.0004294486,0.0007080432,0.0044909483,0.0003263766,0.000007976569],"category_scores_gemma":[0.000021170938,0.0003571207,0.00005351483,0.00078376255,0.0010500266,0.0038031598,0.0032212608,0.001300326,0.000034046552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005408775,0.00006203027,0.00010052609,0.00002626341,0.0000068657473,0.000003524987,0.0014470246,0.19921201,0.000017113405,0.6115933,0.00007179628,0.18745412],"study_design_scores_gemma":[0.00030836495,0.000031945507,0.0005753106,0.00022284295,0.0000023905368,0.000022828004,0.00001026672,0.97521996,0.000005017046,0.0005960599,0.022630572,0.00037440605],"about_ca_topic_score_codex":0.000016460726,"about_ca_topic_score_gemma":0.00014049935,"teacher_disagreement_score":0.776008,"about_ca_system_score_codex":0.0002835506,"about_ca_system_score_gemma":0.00023977323,"threshold_uncertainty_score":0.99988806},"labels":[],"label_agreement":null},{"id":"W158795021","doi":"10.1007/978-3-642-21937-5_35","title":"Model Driven Prototyping with Modelibra","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Reuse; Rapid prototyping; Domain (mathematical analysis); Software engineering; Domain model; Process (computing); Software; Programming language; Engineering; Mathematics","score_opus":0.05240828203163433,"score_gpt":0.2604678778888263,"score_spread":0.20805959585719197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W158795021","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000063831394,0.00007568639,0.92529833,0.0001872791,0.000038516704,0.0005901984,0.0000045607603,0.00038053372,0.07341849],"genre_scores_gemma":[0.008005361,0.0007194904,0.9904434,0.00027957934,0.000008400974,0.000107986496,0.000012404281,0.000012988851,0.0004103574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853975,0.000012441854,0.0004928096,0.0003251872,0.00039137233,0.0002384638],"domain_scores_gemma":[0.99652445,0.000036385103,0.00023990707,0.0027472766,0.0003467923,0.0001052016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048656523,0.00025342635,0.00023696845,0.00090592797,0.00026857504,0.00040006664,0.004278053,0.00012754061,0.0000021459311],"category_scores_gemma":[0.0000030679307,0.0002359887,0.000031880205,0.00030432513,0.000595533,0.008927181,0.0026412345,0.0004649366,0.000015385021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012467076,0.0000060930283,0.0000072073694,0.000017593304,0.0000027654519,2.0759705e-7,0.0011446205,0.01249833,6.6404345e-7,0.8491363,0.000033881854,0.1371511],"study_design_scores_gemma":[0.00010432719,0.00004481697,0.00003107274,0.0002606795,0.0000026091827,0.000016205322,5.215539e-7,0.9402927,0.0000081008875,0.021276126,0.03767854,0.0002843103],"about_ca_topic_score_codex":0.000006144092,"about_ca_topic_score_gemma":0.0000030488352,"teacher_disagreement_score":0.92779434,"about_ca_system_score_codex":0.00011883636,"about_ca_system_score_gemma":0.0003490705,"threshold_uncertainty_score":0.962334},"labels":[],"label_agreement":null},{"id":"W1590835047","doi":"10.1007/978-3-540-70760-8_6","title":"A New Approach for the Trust Calculation in Social Networks","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Access Control and Trust","field":"Social Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Function (biology); Computer science; Block (permutation group theory); Social trust; Management science; Sociology; Mathematics; Social science; Engineering; Social capital","score_opus":0.07468095492307882,"score_gpt":0.33759821441117843,"score_spread":0.26291725948809963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590835047","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000068463264,0.0005190776,0.5359809,0.0019096787,0.00015215695,0.0008261352,0.0000055998084,0.00002650681,0.4605731],"genre_scores_gemma":[0.79482824,0.03198195,0.13344727,0.00435194,0.0022512935,0.00048655365,0.00042762607,0.00004385462,0.032181293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989285,0.00003439266,0.00040261887,0.00013479307,0.00030209756,0.00019759154],"domain_scores_gemma":[0.9987805,0.00032060817,0.00021282256,0.00045265534,0.00018158284,0.00005182892],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0012493427,0.000108255685,0.0001582347,0.0003211407,0.0018421186,0.00032415934,0.0013951949,0.00014793119,0.00000923979],"category_scores_gemma":[0.000054697048,0.00009146161,0.00004628298,0.00035010793,0.001073657,0.0023342492,0.00034293465,0.00029460754,0.0000046751356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000574644,0.0000067296323,0.00012909409,0.0000043726895,0.000003443698,3.078263e-8,0.011262496,0.0020712763,1.4152474e-8,0.52755517,0.0021663774,0.45679525],"study_design_scores_gemma":[0.00034168386,0.0000061801106,0.0049590813,0.000018736066,0.0000060146335,0.0000010139781,0.0001322366,0.53543675,2.347456e-8,0.0017500084,0.45721465,0.0001336379],"about_ca_topic_score_codex":0.00039595496,"about_ca_topic_score_gemma":0.0002959357,"teacher_disagreement_score":0.7948214,"about_ca_system_score_codex":0.0001477381,"about_ca_system_score_gemma":0.00044167542,"threshold_uncertainty_score":0.99945736},"labels":[],"label_agreement":null},{"id":"W1591589233","doi":"10.1007/978-3-540-70600-7_8","title":"Motif Location Prediction by Divide and Conquer","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Motif (music); Subsequence; Divide and conquer algorithms; Sequence motif; Computer science; Computational biology; Theoretical computer science; Artificial intelligence; Gene; Biology; Genetics; Mathematics; Algorithm","score_opus":0.01208314073644583,"score_gpt":0.23226488090511233,"score_spread":0.22018174016866648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1591589233","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09494909,0.016765676,0.40935323,0.0028090987,0.0011925545,0.0028387068,0.00090407755,0.00015123218,0.47103634],"genre_scores_gemma":[0.9155411,0.063441,0.014187351,0.0010458576,0.00008805462,0.000034108947,0.0022599122,0.000021643651,0.0033809429],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992955,0.000009986449,0.00031126302,0.00016120149,0.00012467621,0.000097415206],"domain_scores_gemma":[0.99892974,0.000015423268,0.00015200248,0.0006561829,0.00019451193,0.000052137093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020812251,0.000118932454,0.00009853761,0.00014672069,0.00024637152,0.00009862597,0.00041627348,0.00012562508,0.0000022479728],"category_scores_gemma":[0.000017807708,0.00012729756,0.00001440437,0.00006318815,0.00062679977,0.000101749334,0.0006025176,0.00012785147,0.000005137374],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044522832,0.000161563,0.0048579895,0.00035431114,0.00011198926,6.983836e-7,0.0057024215,0.0034463003,0.0055198963,0.11485948,0.04908969,0.81585115],"study_design_scores_gemma":[0.0005706834,0.00016516166,0.0059357067,0.00012249676,0.000012945726,0.000075269214,0.000028387523,0.15420802,0.00023205036,0.0010189478,0.83719736,0.00043296829],"about_ca_topic_score_codex":0.0000066259863,"about_ca_topic_score_gemma":0.0000063964944,"teacher_disagreement_score":0.82059205,"about_ca_system_score_codex":0.000033050208,"about_ca_system_score_gemma":0.000106190055,"threshold_uncertainty_score":0.51910436},"labels":[],"label_agreement":null},{"id":"W1596400532","doi":"10.1007/978-3-642-15810-0_14","title":"Imitation Learning from Humanoids in a Heterogeneous Setting","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Humanoid robot; Imitation; Robot; Task (project management); Human–computer interaction; Artificial intelligence; Computer science; Construct (python library); Social robot; Robot control; Computer vision; Mobile robot; Engineering; Psychology","score_opus":0.0342842481827293,"score_gpt":0.2619736285611059,"score_spread":0.2276893803783766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596400532","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022443198,0.0014090878,0.3536985,0.0004925161,0.0012610432,0.0010539825,0.0000075070952,0.0007901845,0.618844],"genre_scores_gemma":[0.96999407,0.0008308121,0.028472232,0.00014950264,0.000044845943,0.000015103697,0.00018475157,0.000018291263,0.000290409],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900436,0.000020276568,0.00050447905,0.00012816173,0.00019519482,0.00014754247],"domain_scores_gemma":[0.9990686,0.00015229941,0.00012400241,0.0005216227,0.00008812665,0.000045305216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045912853,0.0001484774,0.00015491905,0.0007699756,0.00024599925,0.00026047122,0.0005614487,0.00014540071,0.00003147067],"category_scores_gemma":[0.000039898037,0.00017460369,0.000023675359,0.00017328929,0.0002054648,0.0019476574,0.0002888037,0.00092462136,0.000052199972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017706559,0.0000053798653,0.000778805,0.000033608674,0.000005752493,6.2237143e-7,0.0076325354,0.77465224,0.00013223673,0.017162222,0.000017567323,0.19957723],"study_design_scores_gemma":[0.00016112239,0.000008923944,0.004227241,0.00013106884,0.0000023312898,0.0000036903698,0.000033869113,0.9668694,0.000016082313,0.0010052416,0.027345033,0.00019596798],"about_ca_topic_score_codex":0.000017496426,"about_ca_topic_score_gemma":0.000071249204,"teacher_disagreement_score":0.94755083,"about_ca_system_score_codex":0.000103718216,"about_ca_system_score_gemma":0.000040008224,"threshold_uncertainty_score":0.7120132},"labels":[],"label_agreement":null},{"id":"W1596642629","doi":"10.1007/978-3-642-04757-2","title":"Best Practices for the Knowledge Society. Knowledge, Learning, Development and Technology for All","year":2009,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Educational Technology and Optimization","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Åbo Akademi; University of the Aegean; Universidad de Valladolid; Università di Pisa; RWTH Aachen University; Università degli Studi di Salerno; Universidad de Zaragoza; Universidade Federal do Estado do Rio de Janeiro; Universidade de Vigo; Universidad Carlos III de Madrid; Universidad de Alcalá; Università Politecnica delle Marche; Goethe-Universität Frankfurt am Main; Turun Yliopisto; Arkansas State University; London Metropolitan University; University College Dublin; Centre National de la Recherche Scientifique; Macquarie University; Loughborough University; University of Warwick; De Montfort University; Sheffield Hallam University; Universität Siegen; Universitat de Lleida; Université de Technologie de Compiègne; Erasmus Universiteit Rotterdam; Università di Bologna; Copenhagen Business School; University of Wollongong; Universidad de Murcia; University of the Highlands and Islands; George Mason University; Concordia University; Institut national de recherche en informatique et en automatique (INRIA); Auckland University of Technology, New Zealand; Universidad Rey Juan Carlos; Manchester Metropolitan University; Technische Universität Wien; Universität Wien; Universidad Tecnológica Nacional; London School of Economics and Political Science; University of New South Wales","keywords":"Summit; Pleasure; Knowledge society; Political science; Computer science; Library science; World Wide Web; Knowledge management; Psychology; Geography; Cartography","score_opus":0.07103762272673256,"score_gpt":0.37345226685106625,"score_spread":0.3024146441243337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596642629","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017072709,0.0065185735,0.95506454,0.009980269,0.00023023594,0.0011529672,0.0000027920667,0.00014256623,0.026890973],"genre_scores_gemma":[0.0011380312,0.006858646,0.9759385,0.00067911774,0.00006253954,0.0005840318,0.00010444989,0.000008890804,0.014625781],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99888074,0.000025192072,0.00046059355,0.00028036613,0.00012726052,0.00022581626],"domain_scores_gemma":[0.996359,0.0012300583,0.00058289646,0.00092018687,0.00086573564,0.000042109943],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0016155748,0.00017130266,0.00017153095,0.000606097,0.0013595804,0.0004256813,0.0027236333,0.00024056673,4.1547509e-7],"category_scores_gemma":[0.00033938585,0.00014623384,0.000031134135,0.00076688273,0.00087193394,0.002885891,0.0012335114,0.00041982895,0.000008752104],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011702984,0.000049309954,0.000015490565,0.00004814577,0.000012154093,7.2655286e-9,0.004778771,0.00012845879,5.516891e-7,0.3842674,0.0043745977,0.60632396],"study_design_scores_gemma":[0.00016724959,0.000058745776,0.00006197263,0.00006672282,0.000008114666,0.0000071401837,0.00010290424,0.33365667,0.00000967699,0.006081611,0.6596524,0.00012681104],"about_ca_topic_score_codex":0.0000012773369,"about_ca_topic_score_gemma":0.000017412598,"teacher_disagreement_score":0.6552778,"about_ca_system_score_codex":0.00016101866,"about_ca_system_score_gemma":0.0014051801,"threshold_uncertainty_score":0.9999405},"labels":[],"label_agreement":null},{"id":"W1596854569","doi":"10.1007/978-3-540-85930-7_41","title":"Dynamic Neural Network-Based Pulsed Plasma Thruster (PPT) Fault Detection and Isolation for Formation Flying of Satellites","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Scheme (mathematics); Fault detection and isolation; Isolation (microbiology); Fault (geology); Artificial neural network; Computer science; Real-time computing; Aerospace engineering; Engineering; Artificial intelligence; Geology; Mathematics; Seismology","score_opus":0.020208765921837287,"score_gpt":0.24203678859575767,"score_spread":0.22182802267392038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596854569","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010564732,0.0017230883,0.970824,0.00011203746,0.0008414469,0.0017792155,0.000046695106,0.00025470703,0.013854046],"genre_scores_gemma":[0.99010485,0.0013107362,0.008285653,0.00006047606,0.000018790142,0.00006025464,0.00007800036,0.000012744392,0.00006850557],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988599,0.000018915769,0.0006775825,0.00011704593,0.00016792984,0.00015864389],"domain_scores_gemma":[0.99886894,0.00019335574,0.00024077792,0.00044679994,0.00021091523,0.000039183167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040991313,0.00017462934,0.00022617918,0.0005484935,0.0003628376,0.00013524934,0.0002986221,0.0001400733,0.000001798197],"category_scores_gemma":[0.000018869256,0.00018372572,0.000044952772,0.0001936106,0.00023068095,0.0024474496,0.0000850463,0.00020098203,0.0000029890762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030859028,0.0000070444194,0.00003834566,0.00035540742,0.000015115357,5.3317688e-8,0.0017084021,0.29118454,0.0004560203,0.0012192519,0.000050971703,0.704934],"study_design_scores_gemma":[0.00052551663,0.00005050435,0.00035146638,0.00015027904,0.000008445504,0.000014064206,0.000022373699,0.9871907,0.000084943335,0.0001082897,0.011322576,0.00017080417],"about_ca_topic_score_codex":0.0000042528595,"about_ca_topic_score_gemma":0.000034473713,"teacher_disagreement_score":0.9795401,"about_ca_system_score_codex":0.000117392396,"about_ca_system_score_gemma":0.00003107689,"threshold_uncertainty_score":0.7492117},"labels":[],"label_agreement":null},{"id":"W1598399217","doi":"10.1007/978-3-540-75274-5_4","title":"Terrain Synthesis By-Example","year":2007,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Terrain; Computer science; Process (computing); Resolution (logic); Terrain rendering; Scale (ratio); Artificial intelligence; Remote sensing; Computer vision; Computer graphics (images); Geology; Geography; Visualization; Cartography; Programming language","score_opus":0.06348324641825845,"score_gpt":0.3306473748796572,"score_spread":0.2671641284613987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1598399217","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000063190514,0.00027266497,0.8263092,0.0003523786,0.00014799817,0.00025326834,0.000011326728,0.0002097929,0.17243703],"genre_scores_gemma":[0.05481089,0.01754938,0.9118917,0.00917068,0.00015616145,0.00018355723,0.0002552493,0.00006793858,0.005914467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979807,0.00003202541,0.00079344015,0.00037677027,0.00053031987,0.00028673522],"domain_scores_gemma":[0.9962989,0.0003587554,0.00036313618,0.002451324,0.0003884207,0.0001394339],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018537571,0.00026351222,0.00027636875,0.0017298793,0.00047385652,0.00090768124,0.0044510197,0.00017156903,0.000009713961],"category_scores_gemma":[0.000037748607,0.00027518845,0.000059525184,0.0007038716,0.00075402955,0.005295776,0.003092033,0.0003866714,0.000027960341],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.4289644e-7,0.000011151506,0.000010556679,0.0000106090065,0.0000028525735,1.8294955e-7,0.0006320059,0.0000021015155,0.0000011427857,0.76950103,0.0018613702,0.22796656],"study_design_scores_gemma":[0.0001025731,0.00004074963,0.00015276196,0.00015763228,0.0000033848162,0.0000150728365,0.0000057073958,0.29610994,0.000058749476,0.020287214,0.6826859,0.00038031125],"about_ca_topic_score_codex":0.000049701503,"about_ca_topic_score_gemma":0.000011075262,"teacher_disagreement_score":0.7492138,"about_ca_system_score_codex":0.00012081123,"about_ca_system_score_gemma":0.00022519454,"threshold_uncertainty_score":0.99997},"labels":[],"label_agreement":null},{"id":"W1599483641","doi":"10.1007/978-3-540-85936-9_12","title":"A Software Engineering Lifecycle Standard for Very Small Enterprises","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":153,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Capability Maturity Model Integration; Product (mathematics); Quality (philosophy); Software; Engineering management; Process management; Business; Computer science; Manufacturing engineering; Software development; Software development process; Engineering; Operating system","score_opus":0.03475685849603668,"score_gpt":0.27312201135728054,"score_spread":0.23836515286124385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1599483641","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000030227753,0.00066131895,0.9941694,0.00023272708,0.0003025347,0.00036955706,0.00002215534,0.00038615428,0.0038259053],"genre_scores_gemma":[0.0027736921,0.004782398,0.99176174,0.00033615838,0.000039349525,0.000065901055,0.00002581155,0.000012144177,0.0002027741],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99882793,0.000008688628,0.00045605178,0.00023363523,0.0002575915,0.00021610956],"domain_scores_gemma":[0.997219,0.00070506724,0.00021502221,0.0014841876,0.00028942915,0.000087267166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062757364,0.00020465895,0.00022605812,0.0007053623,0.00030469886,0.00047903007,0.0025739917,0.00011201959,0.0000016530132],"category_scores_gemma":[0.00023417054,0.00021747488,0.00005859578,0.00023239931,0.00020267659,0.004643913,0.001502698,0.0003102781,0.0000072151493],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016962584,0.000031242824,0.0002106243,0.00025807464,0.000030797877,0.000002325857,0.0038724702,0.0042098053,0.000003247031,0.3025773,0.003293707,0.68549347],"study_design_scores_gemma":[0.00020866544,0.00010081255,0.0003920122,0.0002652999,0.0000048428533,0.000042566375,0.0000021564733,0.24276662,0.000016862297,0.0012199774,0.75463814,0.00034204972],"about_ca_topic_score_codex":0.0000048632082,"about_ca_topic_score_gemma":0.0000015425236,"teacher_disagreement_score":0.75134444,"about_ca_system_score_codex":0.00012244286,"about_ca_system_score_gemma":0.0002206793,"threshold_uncertainty_score":0.8868368},"labels":[],"label_agreement":null},{"id":"W1625963308","doi":"10.1007/978-3-642-20370-1_43","title":"A Privacy Access Control Framework for Web Services Collaboration with Role Mechanisms","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Internet privacy; Popularity; Authorization; Computer science; World Wide Web; Access control; Reputation; Web service; The Internet; Privacy policy; Information privacy; Privacy by Design; Privacy software; Control (management); Personally identifiable information; Service provider; Computer security; Service (business); Business","score_opus":0.04150393100612561,"score_gpt":0.33359591720899434,"score_spread":0.29209198620286875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1625963308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016343906,0.00039350847,0.84060645,0.0031993275,0.00044914513,0.0028215265,0.00020590845,0.00017139514,0.15198928],"genre_scores_gemma":[0.66097856,0.0064589013,0.32728517,0.0033130345,0.00029412948,0.00065333414,0.00040178956,0.000034928067,0.00058017205],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99860793,0.000056169483,0.0004320277,0.00023257494,0.00043484833,0.0002364523],"domain_scores_gemma":[0.9971328,0.00023492472,0.00046404346,0.0012432634,0.0008158545,0.00010911261],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014318044,0.0001742551,0.00021555476,0.00053196744,0.0014618606,0.0011687684,0.0031228592,0.00022224354,0.000022053484],"category_scores_gemma":[0.00013414143,0.00016655488,0.00002855503,0.00043850933,0.00081658125,0.009925019,0.0010189473,0.00029422966,0.000016189157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002356503,0.00001486439,0.00003369836,0.00003581714,0.000006558862,3.8092715e-8,0.011010609,0.000008795043,0.0000026371622,0.9673427,0.00005019234,0.02147054],"study_design_scores_gemma":[0.00059594767,0.00012397957,0.00033389468,0.00033500898,0.000024829757,0.00000198924,0.0007129795,0.021169094,0.000013893449,0.6377766,0.33855614,0.00035561493],"about_ca_topic_score_codex":0.00023392159,"about_ca_topic_score_gemma":0.00080741197,"teacher_disagreement_score":0.6608151,"about_ca_system_score_codex":0.00015789694,"about_ca_system_score_gemma":0.00072386285,"threshold_uncertainty_score":0.9998681},"labels":[],"label_agreement":null},{"id":"W1630476232","doi":"10.1007/978-3-540-88653-2_19","title":"A Security Hardening Language Based on Aspect-Orientation","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Software security assurance; Hardening (computing); Proposition; Computer security model; Computer security; Software engineering; Information security; Security service; Linguistics","score_opus":0.045844003879053456,"score_gpt":0.31885229368752416,"score_spread":0.2730082898084707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1630476232","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000034569308,0.0001903538,0.93904877,0.00028412053,0.0002830465,0.0002106883,0.0000061058254,0.00025078334,0.05969158],"genre_scores_gemma":[0.0350292,0.0008947835,0.96279526,0.00084924453,0.000034576133,0.000027309456,0.00004013149,0.000010866513,0.0003186126],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857366,0.000045336947,0.00043287483,0.00028572194,0.00046088066,0.00020154788],"domain_scores_gemma":[0.9968442,0.0006811167,0.00023768596,0.0019579125,0.000207047,0.00007203747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008667561,0.00020486323,0.00021087077,0.0009698423,0.00036247028,0.0002620638,0.0023048066,0.00010075648,0.0000030805968],"category_scores_gemma":[0.00024465265,0.00021318156,0.000040733463,0.00041063243,0.00048681407,0.0038426218,0.0010534688,0.0004823558,0.00003229662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075037956,0.00003267794,0.000033744225,0.000059476835,0.0000069643693,0.000005728193,0.015170197,0.10044729,0.0000072494167,0.5114749,0.00047947594,0.37227482],"study_design_scores_gemma":[0.00034309106,0.00009227218,0.0006137901,0.0002269634,0.0000027455433,0.000025680923,0.000030482908,0.95784914,0.000056632623,0.0070890407,0.033250544,0.0004195833],"about_ca_topic_score_codex":0.0000041148783,"about_ca_topic_score_gemma":0.0000018504187,"teacher_disagreement_score":0.8574019,"about_ca_system_score_codex":0.00019292552,"about_ca_system_score_gemma":0.0001963453,"threshold_uncertainty_score":0.86932915},"labels":[],"label_agreement":null},{"id":"W1658874752","doi":"10.1007/978-3-642-10546-3_18","title":"Link Shifting Based Pyramid Segmentation for Elongated Regions","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Segmentation; Pyramid (geometry); Partition (number theory); Homogeneous; Computer science; Node (physics); Image segmentation; Image (mathematics); Artificial intelligence; Set (abstract data type); Pattern recognition (psychology); Computer vision; Minimum spanning tree-based segmentation; Mathematics; Scale-space segmentation; Combinatorics; Geometry; Physics","score_opus":0.050223721901259705,"score_gpt":0.33087449948334235,"score_spread":0.2806507775820827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1658874752","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003036995,0.000103979735,0.96939737,0.0035774282,0.00014787554,0.0008866042,0.000011745283,0.00027709297,0.025594892],"genre_scores_gemma":[0.0019044194,0.0005902422,0.9918468,0.0045603313,0.000044593602,0.00010042671,0.00018879348,0.0000100847465,0.000754279],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794114,0.000040263705,0.0008780345,0.0003456126,0.000529272,0.00026566695],"domain_scores_gemma":[0.9965663,0.00040882704,0.000522362,0.0017456535,0.00061527704,0.00014158916],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014850692,0.00023730943,0.00025023636,0.0011525248,0.000574513,0.0007648216,0.0028864911,0.00015708143,0.000007056351],"category_scores_gemma":[0.00014083816,0.00024812095,0.000063028834,0.00051869557,0.00069055724,0.006311838,0.00074051466,0.00038004734,0.000017608168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019777854,0.000013162805,0.0000032277492,0.000027958244,0.0000029246685,2.133145e-7,0.0007152007,0.0001151371,0.000024126955,0.17328915,0.0004551013,0.82535183],"study_design_scores_gemma":[0.00066147157,0.0001592378,0.00023214181,0.00039024575,0.000010178646,0.000008920981,0.00001714262,0.9323254,0.0006439725,0.027369235,0.037721563,0.00046046468],"about_ca_topic_score_codex":0.0000063298266,"about_ca_topic_score_gemma":0.000004095536,"teacher_disagreement_score":0.93221027,"about_ca_system_score_codex":0.00022022253,"about_ca_system_score_gemma":0.00041225692,"threshold_uncertainty_score":0.9999971},"labels":[],"label_agreement":null},{"id":"W168473357","doi":"10.1007/978-3-642-40597-6_14","title":"A Privacy Preserving Approach to Smart Metering","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Metering mode; Demand side; Computer science; Power consumption; Entropy (arrow of time); Computer security; Home automation; Demand response; Transformer; Smart grid; Telecommunications; Electricity; Power (physics); Engineering; Environmental economics; Electrical engineering","score_opus":0.03681265928214726,"score_gpt":0.25145734517174884,"score_spread":0.21464468588960156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W168473357","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011782368,0.00040346754,0.13069433,0.00014777522,0.00033908786,0.0005826202,0.000007376865,0.00017205777,0.86647505],"genre_scores_gemma":[0.4555014,0.0075356746,0.53012776,0.0015174069,0.00021360748,0.00033459166,0.00012975132,0.000067559966,0.004572251],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990111,0.000008351335,0.00039838807,0.00014129112,0.00024676244,0.00019408988],"domain_scores_gemma":[0.99844044,0.0000684572,0.000055406574,0.001205904,0.00011984566,0.000109952416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038489368,0.00015983755,0.00016884509,0.0006291397,0.00022880988,0.0003581453,0.001771054,0.000086513566,0.0000125991555],"category_scores_gemma":[0.000025498106,0.00016007997,0.000025126375,0.0002569236,0.00027006338,0.0032479337,0.0014897897,0.0003280828,0.0001091567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050180324,0.000054539498,0.00019742487,0.0008299814,0.000042861957,4.840765e-7,0.031312864,0.0956108,0.00011764037,0.44641933,0.008690653,0.4167184],"study_design_scores_gemma":[0.00007396664,0.000012554173,0.0009054743,0.00016787126,0.0000027346248,0.00000958859,0.000025446252,0.7292354,0.000013458839,0.00061593496,0.26869884,0.000238712],"about_ca_topic_score_codex":0.000012397689,"about_ca_topic_score_gemma":0.0000028596469,"teacher_disagreement_score":0.8619028,"about_ca_system_score_codex":0.00008690275,"about_ca_system_score_gemma":0.000043180695,"threshold_uncertainty_score":0.65278715},"labels":[],"label_agreement":null},{"id":"W178949263","doi":"10.1007/978-3-319-12024-9_14","title":"Semantic Facets for Scientific Information Retrieval","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Information retrieval; Sentence; Ontology; Semantic search; Semantics (computer science); Filter (signal processing); Natural language processing; World Wide Web; Semantic Web","score_opus":0.03733782229050642,"score_gpt":0.3114533557815188,"score_spread":0.27411553349101236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W178949263","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018186567,0.00010134642,0.95982915,0.00078233035,0.00029450766,0.0006631511,0.000014110225,0.00021228346,0.03808493],"genre_scores_gemma":[0.0696274,0.0008449687,0.92466205,0.0015860113,0.00005527193,0.00007784481,0.0003331897,0.000016459591,0.0027967775],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977029,0.000025723548,0.0009873537,0.00033166842,0.00064252183,0.00030982945],"domain_scores_gemma":[0.99482375,0.00027387118,0.00066681276,0.0030267283,0.0010954055,0.00011344703],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0023081894,0.00026125586,0.00033342637,0.0021237272,0.0009245599,0.0020112458,0.0045282394,0.0001604167,0.0000033457434],"category_scores_gemma":[0.00017766704,0.00026619373,0.00008808271,0.0008081273,0.0011410431,0.015845485,0.0023513264,0.00034332284,0.00008158564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002008438,0.0000048290417,0.000004898019,0.000036640053,0.00000400875,2.7496215e-8,0.0007585644,0.00014584266,0.0000072498065,0.7892476,0.0005015564,0.20928684],"study_design_scores_gemma":[0.00020467598,0.00004873429,0.000081897604,0.00011898198,0.000007185568,0.0000075598077,0.0000064855135,0.5346768,0.000074728196,0.035560515,0.4289209,0.00029157795],"about_ca_topic_score_codex":0.0000027570316,"about_ca_topic_score_gemma":0.0000057659504,"teacher_disagreement_score":0.753687,"about_ca_system_score_codex":0.00020436292,"about_ca_system_score_gemma":0.0003159217,"threshold_uncertainty_score":0.999979},"labels":[],"label_agreement":null},{"id":"W1793586388","doi":"10.1007/978-3-540-74282-1_148","title":"Human-Like Learning Methods for a \"Conscious\" Agent","year":2007,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Autonomy; Unconscious mind; Cognitive science; Computer science; Cognition; Artificial intelligence; Psychology; Neuroscience","score_opus":0.10401151902575473,"score_gpt":0.39940874880379185,"score_spread":0.2953972297780371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1793586388","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00000439998,0.00056182273,0.7170731,0.00015319754,0.0003685522,0.00036400583,0.0000016924171,0.00010903386,0.2813642],"genre_scores_gemma":[0.0041779173,0.0009975506,0.9849254,0.0010336097,0.00007091643,0.000059936734,0.000041721916,0.0000128925985,0.00868005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99815065,0.000064421576,0.00075675757,0.00036722442,0.00030012036,0.0003608537],"domain_scores_gemma":[0.9964978,0.0005178047,0.00045061397,0.0017889502,0.00059941976,0.00014541465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0038609596,0.00025938303,0.00031685748,0.0011141483,0.001169332,0.00076460844,0.0038271125,0.00017878722,0.0000070592378],"category_scores_gemma":[0.00011692122,0.0002527453,0.00009539263,0.00042255112,0.0008120284,0.0037889434,0.002661832,0.00055095024,0.00004237247],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.8361646e-7,0.000008964985,0.000011596299,0.000018421042,0.000004166774,1.2656517e-7,0.0016917831,0.000060595386,0.0000033816516,0.6201363,0.00020015352,0.37786382],"study_design_scores_gemma":[0.00029277353,0.0000901118,0.00023685036,0.00010202157,0.000006635758,0.000019393427,0.000021519769,0.30329132,0.000010286407,0.019859407,0.675743,0.00032673587],"about_ca_topic_score_codex":0.000008708131,"about_ca_topic_score_gemma":0.00001392574,"teacher_disagreement_score":0.67554283,"about_ca_system_score_codex":0.00019231737,"about_ca_system_score_gemma":0.00027861178,"threshold_uncertainty_score":0.9999925},"labels":[],"label_agreement":null},{"id":"W1807037522","doi":"10.1007/978-3-319-25518-7_11","title":"Automatic Construction of a Semantic Knowledge Base from CEUR Workshop Proceedings","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; SPARQL; Information retrieval; Entity linking; Workflow; Linked data; Pipeline (software); RDF; Task (project management); Knowledge base; Leverage (statistics); Information extraction; Scalability; Named-entity recognition; Context (archaeology); Semantic Web; World Wide Web; Natural language processing; Database; Artificial intelligence; Programming language","score_opus":0.06899268990246396,"score_gpt":0.3059474681829819,"score_spread":0.23695477828051795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1807037522","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058480697,0.0036785044,0.5598633,0.0024930655,0.0015134566,0.0012248588,0.00003474225,0.00053651095,0.42480746],"genre_scores_gemma":[0.24365436,0.0015802064,0.75369126,0.00027602797,0.00006246024,0.000031663032,0.00004218414,0.00001333295,0.0006485131],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829876,0.000019838471,0.00078656117,0.000272347,0.00041420016,0.00020826061],"domain_scores_gemma":[0.99689674,0.00030304023,0.00052773353,0.0013748037,0.00078870106,0.000108985514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010330429,0.0002100653,0.0003554536,0.0009098813,0.00020639105,0.00038724017,0.0030475731,0.00014243663,0.000009095354],"category_scores_gemma":[0.00015724756,0.00019951418,0.00004579097,0.0005304105,0.0012006629,0.0053082537,0.0022656322,0.00030406864,0.000041263935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014572354,0.000020447726,0.00014541487,0.00006264613,0.000008100302,2.2569611e-7,0.0045585493,0.00001588206,0.000004152361,0.6953413,0.0004882922,0.29935354],"study_design_scores_gemma":[0.0003910917,0.000049171023,0.0016609263,0.0007336457,0.000016055003,0.00003342946,0.00021971205,0.91279954,0.00003153643,0.06627196,0.017452974,0.00033994025],"about_ca_topic_score_codex":0.000021410806,"about_ca_topic_score_gemma":0.000014520903,"teacher_disagreement_score":0.9127837,"about_ca_system_score_codex":0.00012084526,"about_ca_system_score_gemma":0.00048353535,"threshold_uncertainty_score":0.8135952},"labels":[],"label_agreement":null},{"id":"W180993545","doi":"10.1007/978-3-642-12035-0_1","title":"Service Discovery Protocols for VANET Based Emergency Preparedness Class of Applications: A Necessity Public Safety and Security","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Preparedness; Service (business); Class (philosophy); Computer security; Emergency response; Computer science; Emergency management; Service discovery; Medical emergency; Business; Medicine; Political science; Artificial intelligence","score_opus":0.0241250180531195,"score_gpt":0.2793340957044745,"score_spread":0.255209077651355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W180993545","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006285831,0.0005213823,0.94276553,0.00054787734,0.00023140934,0.017881118,0.0004671979,0.0002066799,0.036750205],"genre_scores_gemma":[0.61006,0.010565613,0.3366024,0.001628057,0.00043159287,0.035013616,0.004903644,0.00020246142,0.00059262576],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986144,0.000018266006,0.000742157,0.00018826351,0.00024035723,0.00019660927],"domain_scores_gemma":[0.99760646,0.00014855596,0.00028046448,0.0014036153,0.00046938917,0.000091532354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086406106,0.0001998613,0.00027398064,0.00035617166,0.00031160336,0.00020210502,0.0012022618,0.0001858091,0.000007439691],"category_scores_gemma":[0.0000238881,0.00021104675,0.000037453283,0.00033438948,0.00039979606,0.0033948289,0.0005535208,0.00038194962,0.0000022699144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008643982,0.0002090925,0.00065838004,0.0061588883,0.000096343094,2.0121028e-7,0.0074075833,0.16827568,0.00013935326,0.5475588,0.00093990983,0.26846933],"study_design_scores_gemma":[0.0002527318,0.000015709693,0.00022785214,0.00013209603,0.0000072800194,0.0000026811024,0.000015252517,0.75831926,0.0000108862005,0.0026152683,0.2382127,0.00018829509],"about_ca_topic_score_codex":0.000008377722,"about_ca_topic_score_gemma":0.00020372993,"teacher_disagreement_score":0.60943145,"about_ca_system_score_codex":0.00008498099,"about_ca_system_score_gemma":0.00020295152,"threshold_uncertainty_score":0.86062366},"labels":[],"label_agreement":null},{"id":"W182726612","doi":"10.1007/978-3-642-16397-5_14","title":"A Typology Framework of Loyalty Reward Programs","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Typology; Loyalty; Computer science; Loyalty business model; Foundation (evidence); Knowledge management; Field (mathematics); Marketing; Business; Data science; Sociology; Political science","score_opus":0.047044589400748876,"score_gpt":0.29880921105684904,"score_spread":0.25176462165610014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W182726612","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033039188,0.00028869457,0.015023378,0.003649685,0.001000409,0.0008092341,0.000010725328,0.00014831955,0.97576565],"genre_scores_gemma":[0.8389515,0.0015468297,0.14185692,0.014498969,0.00078115973,0.0000807259,0.0004830434,0.000045027537,0.0017557854],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988438,0.000006154062,0.00057524745,0.00014843782,0.00026700375,0.00015938889],"domain_scores_gemma":[0.9977029,0.00009544848,0.0004972522,0.0012303536,0.00045754187,0.000016512015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010016771,0.00014401371,0.00023260564,0.00073032384,0.00026840752,0.00027083495,0.0014696217,0.00021019332,0.000054235596],"category_scores_gemma":[0.00006159791,0.00014079435,0.000041987645,0.00039467105,0.0011829437,0.0035310087,0.0014341068,0.00059184537,0.00011672232],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000040470954,0.000018959552,0.00055631617,0.00013109419,0.0000033874135,7.7465884e-8,0.0004861779,0.000005993768,0.0000010982706,0.90241534,0.00005808928,0.09631941],"study_design_scores_gemma":[0.00021196014,0.000020124442,0.004227696,0.0003848474,0.000018491628,0.0000041576654,0.000096061725,0.011167228,0.0000023089513,0.084048264,0.8995106,0.00030824344],"about_ca_topic_score_codex":0.00013977813,"about_ca_topic_score_gemma":0.00015579785,"teacher_disagreement_score":0.9740099,"about_ca_system_score_codex":0.00002238598,"about_ca_system_score_gemma":0.00008532785,"threshold_uncertainty_score":0.5741427},"labels":[],"label_agreement":null},{"id":"W1866953180","doi":"10.1007/978-3-540-88653-2_15","title":"Detection of Spoofed MAC Addresses in 802.11 Wireless Networks","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Spoofing attack; Computer network; Computer science; Wireless; Wireless network; Computer security; Telecommunications","score_opus":0.03629532886794424,"score_gpt":0.27955777339293214,"score_spread":0.2432624445249879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1866953180","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00073028175,0.00090808835,0.9464105,0.00025449635,0.00043645088,0.0028650095,0.000008779346,0.00010718162,0.048279244],"genre_scores_gemma":[0.9500171,0.0123824645,0.036144007,0.00051702734,0.000087587614,0.00048198106,0.000038406248,0.000018477669,0.0003129443],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980436,0.000054946137,0.0009400866,0.0002817319,0.00041136626,0.00026825888],"domain_scores_gemma":[0.9969848,0.00026142734,0.00052990235,0.0018118268,0.0003307303,0.00008130736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090820383,0.00022768986,0.00035967148,0.001028676,0.0002839153,0.00024702022,0.0030746644,0.0001997832,0.0000036490505],"category_scores_gemma":[0.000017147353,0.00023298294,0.00005253355,0.0008315241,0.00078159635,0.00447538,0.0017983282,0.00048919744,0.000006925657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010754501,0.000043525546,0.00051804516,0.00006515094,0.000005895353,0.0000016605994,0.0019488342,0.011063146,0.000008041962,0.1425363,0.00019287202,0.84360576],"study_design_scores_gemma":[0.00040466926,0.0000648562,0.004636342,0.00056202075,0.0000022174056,0.000027398768,0.000008101245,0.95366997,0.000049335205,0.0010337725,0.03922749,0.0003138046],"about_ca_topic_score_codex":0.00005671209,"about_ca_topic_score_gemma":0.00013585131,"teacher_disagreement_score":0.9492868,"about_ca_system_score_codex":0.00011210411,"about_ca_system_score_gemma":0.00023111701,"threshold_uncertainty_score":0.9500769},"labels":[],"label_agreement":null},{"id":"W189421118","doi":"10.1007/978-3-642-45272-7_15","title":"A Mobile App for Learning Japanese","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mobile and Web Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Upload; Multimedia; Android (operating system); Computer science; Mobile device; Mobile apps; Vocabulary; The Internet; World Wide Web; Mobile technology; Mathematics education; Psychology; Linguistics; Operating system","score_opus":0.02881083877148619,"score_gpt":0.28582984552198304,"score_spread":0.2570190067504968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W189421118","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000028849,0.00039605884,0.69270426,0.0003776103,0.00014152711,0.0013575063,0.000008395745,0.00017459455,0.3048112],"genre_scores_gemma":[0.07040331,0.0077079157,0.8772246,0.0024230573,0.00015704743,0.0037399787,0.00028137662,0.00003977847,0.038022935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985697,0.00001708284,0.0005775771,0.00030734474,0.00028614546,0.00024212431],"domain_scores_gemma":[0.99681205,0.00026019508,0.00030644774,0.0020345326,0.000475349,0.000111456524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072830834,0.00019703773,0.00022173379,0.00066140393,0.0006342421,0.00073682197,0.0034034406,0.00012262366,0.000014020327],"category_scores_gemma":[0.000029995419,0.00019689031,0.000056745404,0.00034221573,0.00052829366,0.005243848,0.0018677096,0.00035599043,0.00021652071],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.030104e-7,0.000010580206,0.000004573695,0.00002140372,0.0000028842296,2.8651762e-8,0.0020559633,0.0002625575,0.000004346215,0.6530416,0.0007330347,0.34386253],"study_design_scores_gemma":[0.00015430334,0.00006666535,0.000050771872,0.000051266506,0.0000028397112,0.000007865758,0.000025375331,0.40350297,0.000004896421,0.0090750335,0.5868566,0.0002013993],"about_ca_topic_score_codex":0.000013044668,"about_ca_topic_score_gemma":0.0000026513344,"teacher_disagreement_score":0.64396656,"about_ca_system_score_codex":0.00008941223,"about_ca_system_score_gemma":0.00020825067,"threshold_uncertainty_score":0.8028954},"labels":[],"label_agreement":null},{"id":"W1896267853","doi":"10.1007/978-3-642-30721-8_10","title":"Face Detection and Facial Expression Recognition Using a Novel Variational Statistical Framework","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Correctness; Cluster analysis; Feature selection; Artificial intelligence; Pattern recognition (psychology); Face (sociological concept); Dirichlet process; Mixture model; Bayesian probability; Statistical model; Feature (linguistics); Bayesian information criterion; Facial expression; Expression (computer science); Algorithm","score_opus":0.08361531771053259,"score_gpt":0.3316799101567951,"score_spread":0.2480645924462625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1896267853","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000029290413,0.00022389504,0.9910914,0.00013895203,0.00029831947,0.00026831048,0.000037779922,0.000048108923,0.007863995],"genre_scores_gemma":[0.018275455,0.00055307936,0.98073924,0.00029069145,0.00006408803,0.000012335809,0.00002821837,0.000006295451,0.000030587908],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854136,0.00005385713,0.0005136091,0.00028165244,0.00038916274,0.00022035684],"domain_scores_gemma":[0.99810094,0.0003598809,0.00029835312,0.0008539949,0.00024892308,0.00013789436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011636748,0.00020022453,0.00020676329,0.0005691947,0.0005601006,0.00051251677,0.00091915467,0.00022450105,0.0000111101535],"category_scores_gemma":[0.0000923366,0.00020091515,0.00002503242,0.00024367747,0.0004593888,0.005932203,0.0013280027,0.0005055038,0.000009617463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022747774,0.000011082381,0.0000036533568,0.000013092415,0.0000021019853,5.0288957e-8,0.001172686,0.000030221263,0.000068605485,0.39733058,0.0000033902086,0.6013623],"study_design_scores_gemma":[0.0002349224,0.00003357117,0.00067289075,0.0002347035,0.00001008987,0.000055073022,0.000008878807,0.8401737,0.000053733213,0.14805855,0.010126146,0.00033772],"about_ca_topic_score_codex":0.000009876613,"about_ca_topic_score_gemma":0.0000022532981,"teacher_disagreement_score":0.8401435,"about_ca_system_score_codex":0.000113758746,"about_ca_system_score_gemma":0.00015287193,"threshold_uncertainty_score":0.8193082},"labels":[],"label_agreement":null},{"id":"W192901397","doi":"10.1007/978-3-642-30567-2_29","title":"Nonlinear-Based Human Activity Recognition Using the Kernel Technique","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; University of Windsor","funders":"","keywords":"Computer science; Kernel (algebra); Artificial intelligence; Activity recognition; Benchmark (surveying); Field (mathematics); Kernel method; Pattern recognition (psychology); Context (archaeology); Machine learning; Radial basis function kernel; Feature (linguistics); Support vector machine; Mathematics; Geography","score_opus":0.10691911172413104,"score_gpt":0.33276187084309305,"score_spread":0.225842759118962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W192901397","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006180415,0.000097449614,0.9420414,0.00054286554,0.00021903601,0.00068649405,0.000019431658,0.00013526474,0.055640012],"genre_scores_gemma":[0.45824787,0.0010594205,0.5362845,0.00305543,0.00030474082,0.00020087928,0.00025121606,0.000034305525,0.0005616697],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986416,0.00006395192,0.00046277093,0.00022120547,0.00038411887,0.00022636687],"domain_scores_gemma":[0.99736464,0.00015144731,0.00042709667,0.0015914968,0.00038362265,0.00008171527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013359175,0.0002038004,0.00017643177,0.00073740946,0.0010741487,0.0006067122,0.0020097517,0.00014583119,0.00002055469],"category_scores_gemma":[0.000018504441,0.00017624057,0.000058704136,0.00037297385,0.00069476507,0.0068057817,0.0010184131,0.00057370897,0.000058202273],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000298108,0.000078297635,0.000033523145,0.000046113164,0.000008249471,3.3318062e-7,0.00086189626,0.000090329886,0.00030889027,0.05723596,0.000093618255,0.94123983],"study_design_scores_gemma":[0.00039230168,0.00007743371,0.0007030789,0.00045159305,0.000021653286,0.000059358794,0.000015429841,0.912409,0.0014712244,0.013215392,0.070533305,0.00065021176],"about_ca_topic_score_codex":0.000025522893,"about_ca_topic_score_gemma":0.000009364578,"teacher_disagreement_score":0.9405896,"about_ca_system_score_codex":0.00017274858,"about_ca_system_score_gemma":0.0002321969,"threshold_uncertainty_score":0.8261592},"labels":[],"label_agreement":null},{"id":"W193587042","doi":"10.1007/978-3-642-30507-8_50","title":"Robust Wireless Sensor Networks with Compressed Sensing Theory","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Wireless sensor network; Computer science; Compressed sensing; Real-time computing; Key distribution in wireless sensor networks; Sensor node; Energy consumption; Computer network; Wireless; Wireless network; Telecommunications; Electrical engineering; Engineering; Algorithm","score_opus":0.035887522823653525,"score_gpt":0.2344550307298057,"score_spread":0.19856750790615219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W193587042","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018188365,0.0008324232,0.8457574,0.000039560604,0.00015428016,0.00024931098,0.00000496336,0.000355045,0.15242511],"genre_scores_gemma":[0.70752627,0.0075823357,0.28360912,0.0005194767,0.00015520348,0.000010746379,0.00011137548,0.000061324296,0.0004241425],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990719,0.000022611657,0.0003525585,0.00012076597,0.00020712918,0.00022504378],"domain_scores_gemma":[0.9982911,0.00016493042,0.000120390076,0.0011450908,0.0002034077,0.00007512586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004246921,0.00021755448,0.00022655627,0.00042547437,0.00025536955,0.00022712987,0.00066636427,0.00012420557,0.000005501326],"category_scores_gemma":[0.000003887555,0.00020165634,0.000024124667,0.00017448363,0.0007086976,0.0017207705,0.00042731228,0.00045896647,0.000010019768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000128991405,0.000012247209,0.000044287543,0.00004977397,0.000036898353,0.0000015395331,0.0016203476,0.2500009,0.000032750377,0.16754034,0.00058936054,0.58005863],"study_design_scores_gemma":[0.00012115705,0.0000140821385,0.00014282374,0.00040023433,0.000012535731,0.000039830786,0.000024295969,0.9731903,0.00005676179,0.0006028291,0.02510054,0.00029457448],"about_ca_topic_score_codex":0.0000036349818,"about_ca_topic_score_gemma":0.000004540761,"teacher_disagreement_score":0.7231894,"about_ca_system_score_codex":0.000076295786,"about_ca_system_score_gemma":0.00003602643,"threshold_uncertainty_score":0.82233065},"labels":[],"label_agreement":null},{"id":"W198523258","doi":"10.1007/978-3-642-25501-4_4","title":"Connectivity Criteria for Ranking Network Nodes","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Centrality; Computer science; Hierarchy; Measure (data warehouse); Ranking (information retrieval); Node (physics); Enhanced Data Rates for GSM Evolution; Weighted network; Data mining; Theoretical computer science; Complex network; Artificial intelligence; Mathematics; Combinatorics; World Wide Web","score_opus":0.06259090798941008,"score_gpt":0.32932694746690916,"score_spread":0.2667360394774991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W198523258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007432272,0.00011683684,0.6676173,0.000079552854,0.00009895241,0.0003604457,0.000021595546,0.000046176643,0.33158478],"genre_scores_gemma":[0.78896713,0.00037242958,0.20853506,0.0003654277,0.0003315311,0.00014625667,0.00028258283,0.000019772911,0.0009798054],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990284,0.00002042935,0.00045786935,0.00017061298,0.00013158277,0.00019113022],"domain_scores_gemma":[0.99809146,0.00023289034,0.00029571456,0.0010430015,0.00029112044,0.000045826302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095318875,0.00016446652,0.00025595623,0.00031157763,0.00049711054,0.00025052633,0.0010496249,0.0000513646,0.00007488977],"category_scores_gemma":[0.000006566143,0.000170953,0.00007414099,0.00017546535,0.0004836718,0.0017951176,0.00087810407,0.0002109682,0.000008406457],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027682497,0.000006526815,0.00040997087,0.0000084092935,0.000010920698,8.879993e-9,0.0003519845,0.00007248068,7.1002415e-7,0.8199065,0.00068279915,0.17854695],"study_design_scores_gemma":[0.00030511856,0.000037235994,0.001603708,0.0002890318,0.000035047546,0.0000013520461,0.000015164515,0.26094225,0.0000126175755,0.45150355,0.28480393,0.00045101347],"about_ca_topic_score_codex":0.00003240762,"about_ca_topic_score_gemma":0.000008631892,"teacher_disagreement_score":0.7888928,"about_ca_system_score_codex":0.00004232708,"about_ca_system_score_gemma":0.00008715965,"threshold_uncertainty_score":0.6971261},"labels":[],"label_agreement":null},{"id":"W201536414","doi":"10.1007/978-3-642-23147-6_18","title":"Learning of Facial Gestures Using SVMs","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Gesture; Support vector machine; Computer science; Artificial intelligence; Computer vision; Gesture recognition; Pattern recognition (psychology); Speech recognition","score_opus":0.07610475952834107,"score_gpt":0.2987381642267626,"score_spread":0.22263340469842152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W201536414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002199167,0.00037280953,0.6678031,0.000107580745,0.00039465755,0.00032260217,0.0000066628954,0.00007917806,0.3306935],"genre_scores_gemma":[0.58842754,0.003637713,0.40460047,0.00056156126,0.00013267409,0.000028572462,0.000051993866,0.000025490428,0.002533979],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984393,0.0000482292,0.000719764,0.00021079186,0.00040685877,0.00017504624],"domain_scores_gemma":[0.9975261,0.00013126775,0.0005532447,0.0012152763,0.0004965938,0.00007749986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010172111,0.00017681588,0.00027974104,0.0010100418,0.00032092113,0.00025086963,0.0024188606,0.0001394109,0.000007204549],"category_scores_gemma":[0.0000438031,0.00017200477,0.00005011178,0.00036596233,0.0006594159,0.004309176,0.0017255136,0.00041262986,0.000030190007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018524809,0.000014191851,0.00014755192,0.000051080784,0.000009019198,3.503718e-7,0.008512917,0.00029322586,0.000019323452,0.5253747,0.000039636252,0.46553618],"study_design_scores_gemma":[0.000766198,0.00024600216,0.0027413704,0.0012496639,0.000021976219,0.00015490968,0.00012743968,0.55222666,0.00017477538,0.02628261,0.4149623,0.0010461049],"about_ca_topic_score_codex":0.000025890033,"about_ca_topic_score_gemma":0.0000037820937,"teacher_disagreement_score":0.5882076,"about_ca_system_score_codex":0.00006474556,"about_ca_system_score_gemma":0.00026223395,"threshold_uncertainty_score":0.7014151},"labels":[],"label_agreement":null},{"id":"W202039301","doi":"10.1007/978-3-642-18472-7_6","title":"Dynamic Routing Using Health Information Policy with Apache Camel","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Routing (electronic design automation); Computer science; Policy-based routing; Adaptive routing; Architecture; Distributed computing; Static routing; Computer network; Routing protocol; World Wide Web; Geography","score_opus":0.07015197582868347,"score_gpt":0.3172567996501585,"score_spread":0.24710482382147503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W202039301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000114376744,0.0001316747,0.91818345,0.00103989,0.00015224976,0.0006137134,0.000022078117,0.00015538055,0.07958716],"genre_scores_gemma":[0.7199023,0.0011650709,0.27446413,0.0038014231,0.00004961873,0.000040631625,0.0001168966,0.000023536186,0.00043643656],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997666,0.00007165968,0.0010274398,0.00027704405,0.0005862902,0.00037156107],"domain_scores_gemma":[0.9962308,0.00014434659,0.00096300547,0.0018226228,0.00066249137,0.00017673417],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001585842,0.00030147214,0.0003815711,0.0020964246,0.0007700151,0.0010165367,0.0026955616,0.00013233995,0.0000038414128],"category_scores_gemma":[0.00004194743,0.00029129296,0.000048316302,0.00087330997,0.0006441665,0.02170396,0.0019305688,0.0005277614,0.00006761829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003290904,0.000014378027,0.00004030392,0.000058487298,0.000010864812,2.0705583e-7,0.01134798,0.00027396757,0.0000013292142,0.3198966,0.000026956777,0.6683256],"study_design_scores_gemma":[0.00054931134,0.00013302002,0.0012276503,0.0008589178,0.0000065520144,0.00021995272,0.00016122598,0.95972323,0.0000056709955,0.002446729,0.034047537,0.00062021444],"about_ca_topic_score_codex":0.00052644423,"about_ca_topic_score_gemma":0.00009060809,"teacher_disagreement_score":0.95944923,"about_ca_system_score_codex":0.0007180832,"about_ca_system_score_gemma":0.0017724615,"threshold_uncertainty_score":0.9999539},"labels":[],"label_agreement":null},{"id":"W204851212","doi":"10.1007/978-3-642-54525-2_44","title":"A Survey on Wi-Fi Protocols: WPA and WPA2","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Authentication Protocols Security","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Flexibility (engineering); Confidentiality; Computer security; Wireless; Wireless network; Vulnerability (computing); Computer network; Telecommunications","score_opus":0.07013585800742314,"score_gpt":0.34866361058090106,"score_spread":0.27852775257347795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W204851212","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009984179,0.00005256039,0.9223652,0.0007223016,0.00010391437,0.0130417375,0.000036326812,0.00013330033,0.06353471],"genre_scores_gemma":[0.14470866,0.002104009,0.79345185,0.013460623,0.0002182044,0.037305646,0.000521687,0.00011277147,0.008116539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978819,0.000103597675,0.0007618355,0.00044413033,0.0005486772,0.00025986013],"domain_scores_gemma":[0.9953039,0.0005009569,0.00050753454,0.0030461517,0.0004877985,0.00015360735],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0022507368,0.0002780406,0.00030822784,0.0007674673,0.00052905345,0.00082818756,0.0035834946,0.00013611729,0.000005539011],"category_scores_gemma":[0.0001750382,0.00027210356,0.000031743293,0.0004207021,0.0010933507,0.004074673,0.0028414477,0.0005130601,0.000074973155],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029798257,0.000015141011,0.00007055472,0.000027612334,0.000002033739,9.7159145e-8,0.00058692065,0.000033441884,5.313994e-7,0.7874915,0.000121855686,0.21164735],"study_design_scores_gemma":[0.000890558,0.0002861212,0.016548138,0.00079424353,0.0000040197806,0.000020753947,0.0000067447454,0.48991406,0.000028529894,0.13185844,0.3588271,0.00082129287],"about_ca_topic_score_codex":0.000010425809,"about_ca_topic_score_gemma":0.000016793836,"teacher_disagreement_score":0.65563303,"about_ca_system_score_codex":0.00011793461,"about_ca_system_score_gemma":0.0002270758,"threshold_uncertainty_score":0.9999731},"labels":[],"label_agreement":null},{"id":"W204991224","doi":"10.1007/978-3-540-89985-3_80","title":"A Novel Delay Fault Testing Methodology for Resistive Faults in Deep Sub-micron Technologies","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Resistive touchscreen; Fault (geology); Tracing; Computer science; Fault model; Voltage; Fault indicator; Stuck-at fault; Algorithm; Real-time computing; Electronic engineering; Fault detection and isolation; Electrical engineering; Engineering; Artificial intelligence; Electronic circuit","score_opus":0.15391857856491478,"score_gpt":0.32942769739964156,"score_spread":0.17550911883472678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W204991224","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014791379,0.00069580786,0.9766482,0.00054331956,0.00012774947,0.00049890846,0.000012433615,0.00021538342,0.021110276],"genre_scores_gemma":[0.080813214,0.0015902886,0.91687787,0.00045154776,0.00001959171,0.00009219481,0.00003397256,0.000012051279,0.00010929903],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980297,0.00004043844,0.0008604275,0.00042585217,0.00026731283,0.00037624312],"domain_scores_gemma":[0.9954232,0.0019346353,0.00049131893,0.0014903309,0.0006084943,0.000052024476],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017292522,0.0002577818,0.0003686278,0.0015478868,0.00061379425,0.00022257736,0.0036333415,0.00023048582,2.4695393e-7],"category_scores_gemma":[0.0010675114,0.00026435312,0.000048996393,0.00089745515,0.0010199776,0.0035536943,0.0021598004,0.0005627585,0.0000074648215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.746723e-7,0.000020503345,0.000111471534,0.00004141612,0.0000043668992,0.0000012911103,0.0023581567,0.0008259765,0.00014381413,0.13422139,0.000034303655,0.86223644],"study_design_scores_gemma":[0.00064587593,0.00011985936,0.001904401,0.00057069527,0.0000060592442,0.00023868008,0.00010391506,0.9722786,0.00013784283,0.0093990415,0.014015444,0.0005796153],"about_ca_topic_score_codex":0.000032728476,"about_ca_topic_score_gemma":0.00007567442,"teacher_disagreement_score":0.9714526,"about_ca_system_score_codex":0.0002062916,"about_ca_system_score_gemma":0.00034359426,"threshold_uncertainty_score":0.99998087},"labels":[],"label_agreement":null},{"id":"W207821930","doi":"10.1007/978-3-642-22095-1_45","title":"Sounds in Space: 3D Audio Experiences through Tangible Navigation","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Soundscape; Computer science; Human–computer interaction; Puppetry; Sonification; Interface (matter); Virtual reality; Space (punctuation); Metaphor; Multimedia; Sound (geography); Acoustics","score_opus":0.04894494905777967,"score_gpt":0.29249900862089767,"score_spread":0.24355405956311799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W207821930","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00076319533,0.0011062989,0.38934442,0.0010050437,0.00054104696,0.00037692036,0.0000035172877,0.00017763698,0.60668194],"genre_scores_gemma":[0.56721,0.009330202,0.4169672,0.0016539149,0.00006298673,0.00027165943,0.000047116893,0.000016617705,0.004440257],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984121,0.000028571341,0.0006229839,0.00032613563,0.00033845252,0.00027176784],"domain_scores_gemma":[0.9974956,0.00015232117,0.00029833458,0.001799815,0.00021042953,0.00004350205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084649253,0.00021960087,0.00027662073,0.0007724398,0.00057386764,0.00031628466,0.003229981,0.00020256819,0.000012462987],"category_scores_gemma":[0.000043409487,0.0002127098,0.000035625908,0.00067201565,0.0016905287,0.0075308615,0.0025159216,0.0004925249,0.000048107777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010917843,0.000012162357,0.00008610725,0.000011718884,0.0000030009437,6.1435657e-7,0.045395587,0.000017100872,3.4231638e-7,0.90875965,0.00021376934,0.045498874],"study_design_scores_gemma":[0.0006267515,0.0001516626,0.0017745914,0.00060212193,0.000007324446,0.00006536122,0.0011459143,0.080815874,0.000029286708,0.38500792,0.52885306,0.0009201159],"about_ca_topic_score_codex":0.000047276408,"about_ca_topic_score_gemma":0.000034616936,"teacher_disagreement_score":0.60224164,"about_ca_system_score_codex":0.00013532264,"about_ca_system_score_gemma":0.00020121144,"threshold_uncertainty_score":0.8674054},"labels":[],"label_agreement":null},{"id":"W2101882219","doi":"10.1007/978-3-540-70600-7_7","title":"Searching for Supermaximal Repeats in Large DNA Sequences","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Suffix; Suffix tree; Computer science; Index (typography); Tree (set theory); Algorithm; Generalized suffix tree; Computational biology; Biology; Mathematics; Data structure; Combinatorics; Programming language; Linguistics","score_opus":0.055909415260263,"score_gpt":0.31741569062001623,"score_spread":0.26150627535975324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101882219","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037238857,0.00084156706,0.9151082,0.0011497405,0.00039776493,0.0008843709,0.00007747307,0.000118271215,0.08105024],"genre_scores_gemma":[0.08953829,0.012770905,0.89393514,0.0018787789,0.00012192706,0.00014447338,0.00040709495,0.000022781323,0.001180621],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817914,0.000033222088,0.0006637373,0.00034786592,0.00044112813,0.00033488573],"domain_scores_gemma":[0.99732643,0.0002770823,0.00021313864,0.0018276405,0.00025897022,0.000096733354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013723774,0.00019726886,0.00025176027,0.0010265452,0.0006594647,0.00050040026,0.0037029837,0.00011188246,0.0000031341249],"category_scores_gemma":[0.00005394797,0.00018844123,0.000046067667,0.0003790985,0.0005108856,0.0094443625,0.003210634,0.00041248454,0.000015315642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042664783,0.000031619722,0.00010441215,0.0000402667,0.0000031825562,0.0000020424286,0.004811949,0.00023254726,0.0000063343164,0.6294575,0.00045590498,0.36485],"study_design_scores_gemma":[0.00042765785,0.000053855598,0.0014856901,0.00026083467,0.0000013034618,0.00004296478,0.00002108102,0.776513,0.000011591881,0.006527276,0.21436429,0.0002904863],"about_ca_topic_score_codex":0.00002621489,"about_ca_topic_score_gemma":0.000026563368,"teacher_disagreement_score":0.7762804,"about_ca_system_score_codex":0.00013267327,"about_ca_system_score_gemma":0.00038533838,"threshold_uncertainty_score":0.768441},"labels":[],"label_agreement":null},{"id":"W2104268806","doi":"10.1007/978-3-642-35795-4_5","title":"Software Testing is Necessary But Not Sufficient for Software Trustworthiness","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Trustworthiness; Software reliability testing; Software construction; Software quality; Verification and validation; Software engineering; Software; Software quality analyst; Software development; Software verification; Software quality assurance; Software metric; Reliability engineering; Programming language; Computer security; Engineering","score_opus":0.0683685272162676,"score_gpt":0.3153826507900473,"score_spread":0.2470141235737797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104268806","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002720613,0.00033306214,0.9893803,0.0013098099,0.00022860814,0.0008163945,0.000056025503,0.00023961665,0.007364135],"genre_scores_gemma":[0.012985924,0.0009898236,0.9799307,0.002816602,0.00007810497,0.00021224593,0.00011414669,0.000022072876,0.0028503768],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970732,0.000041423064,0.0009864161,0.0005632811,0.00087730924,0.00045840853],"domain_scores_gemma":[0.9926351,0.0018325034,0.00043847272,0.0030161748,0.0018824822,0.00019527861],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0018617655,0.00032170516,0.00042266923,0.0011663671,0.0010735332,0.0014804386,0.005527319,0.00020528796,0.000022051452],"category_scores_gemma":[0.0008454543,0.0003058142,0.00012068191,0.0010075682,0.0010150834,0.0068043587,0.0038361456,0.00058898545,0.00010357172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036988074,0.000047431655,0.0005241602,0.00019214874,0.000016322972,4.2850507e-7,0.0017217216,0.0011607469,0.0000023019675,0.09262095,0.001241531,0.90246856],"study_design_scores_gemma":[0.00036359555,0.000096441436,0.002274848,0.0003459679,0.00001226736,0.000016677686,0.000035194436,0.9229171,0.00002644484,0.012161697,0.061177075,0.0005726479],"about_ca_topic_score_codex":0.00005656018,"about_ca_topic_score_gemma":0.000005488881,"teacher_disagreement_score":0.9217564,"about_ca_system_score_codex":0.00020144093,"about_ca_system_score_gemma":0.00068794994,"threshold_uncertainty_score":0.9999394},"labels":[],"label_agreement":null},{"id":"W2121513851","doi":"10.1007/978-3-319-22689-7_35","title":"Hermes: A Targeted Fuzz Testing Framework","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Software security assurance; Fuzz testing; Computer science; Security testing; Test (biology); Software; Test case; Code (set theory); Variety (cybernetics); Buffer overflow; Computer security; Information security; Security information and event management; Security service; Cloud computing security; Artificial intelligence; Programming language; Set (abstract data type); Machine learning; Cloud computing; Operating system","score_opus":0.10195110765609292,"score_gpt":0.32900234293158076,"score_spread":0.22705123527548784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121513851","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008975598,0.0006887361,0.80367184,0.00057564507,0.00026069133,0.0002728484,0.000005703289,0.002470368,0.19204517],"genre_scores_gemma":[0.016123751,0.0002466156,0.98220235,0.0008882589,0.000041706604,0.000025229117,0.00001693356,0.000010374952,0.0004448003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99818444,0.00003340867,0.00063425873,0.000319685,0.0005530359,0.00027516758],"domain_scores_gemma":[0.9950364,0.0008128329,0.00037594792,0.0027546103,0.00086779497,0.0001523974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017248436,0.00024443585,0.00026324033,0.0009351019,0.00044580438,0.00078591146,0.0043042228,0.00018257703,0.0000030427832],"category_scores_gemma":[0.0008865908,0.00024454197,0.000033215303,0.0008152879,0.00072714774,0.004784951,0.0032986617,0.00063955167,0.000057966598],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.275956e-7,0.0000112019625,0.00014524262,0.000019583154,0.0000029707867,7.750529e-7,0.001481204,0.0000923881,4.7533808e-7,0.51316315,0.0028123688,0.48226988],"study_design_scores_gemma":[0.00012829032,0.00008009533,0.00058906333,0.00069037464,0.00000389105,0.000057781686,0.000004177716,0.3934938,0.0000024563521,0.5279137,0.0766055,0.0004308468],"about_ca_topic_score_codex":0.000021164784,"about_ca_topic_score_gemma":0.0000013436578,"teacher_disagreement_score":0.48183903,"about_ca_system_score_codex":0.0001812519,"about_ca_system_score_gemma":0.00056116254,"threshold_uncertainty_score":0.9972132},"labels":[],"label_agreement":null},{"id":"W2127791519","doi":"10.1007/978-3-540-79486-8_1","title":"Introduction: Why Transdisciplinary Digital Art?","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visual arts; Digital art; Term (time); Work (physics); Art; Sociology; Aesthetics; Engineering; Performance art; Art history; Mechanical engineering","score_opus":0.08325063432097508,"score_gpt":0.3752478787928559,"score_spread":0.29199724447188086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127791519","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003193966,0.00039331013,0.035764843,0.02472787,0.0007117046,0.00058536313,0.000100463396,0.00006967563,0.9373274],"genre_scores_gemma":[0.36147848,0.015028154,0.051982373,0.0055230595,0.0041406094,0.00032315808,0.0024824264,0.0001228974,0.55891883],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963356,0.000048713522,0.0011747867,0.00043620836,0.0017288205,0.0002758635],"domain_scores_gemma":[0.9952582,0.00038823672,0.00036263716,0.0023678455,0.0014547576,0.00016833933],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0020279102,0.00022962484,0.0003115887,0.0018511481,0.0009124175,0.001829482,0.0030455566,0.00013748762,0.00021550848],"category_scores_gemma":[0.0002221597,0.00019669591,0.00008150298,0.0011548803,0.0021943275,0.014731636,0.0020501483,0.00054225686,0.0012382078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073773444,0.00007734928,0.00006434942,0.000019138932,0.000014756006,0.0000044038857,0.018065672,0.0006830766,0.0000041228477,0.19980098,0.40588054,0.37531182],"study_design_scores_gemma":[0.00019739501,0.00012870836,0.00037947512,0.000042326657,0.0000023084337,0.00008143826,0.00040337,0.03499866,0.0000031337172,0.01507266,0.94845253,0.00023797003],"about_ca_topic_score_codex":5.319412e-7,"about_ca_topic_score_gemma":0.000018600605,"teacher_disagreement_score":0.542572,"about_ca_system_score_codex":0.00016641752,"about_ca_system_score_gemma":0.000493997,"threshold_uncertainty_score":0.99953943},"labels":[],"label_agreement":null},{"id":"W2138734937","doi":"10.1007/978-3-540-73986-9_14","title":"Synthesis of Non-interferent Distributed Systems","year":2007,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Property (philosophy); Computer science; Focus (optics); TRACE (psycholinguistics); Interference (communication); Bisimulation; Distributed computing; Theoretical computer science; Computer security; Human–computer interaction; Computer network; Channel (broadcasting)","score_opus":0.05804527178303598,"score_gpt":0.30570596162347785,"score_spread":0.24766068984044187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138734937","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000050613602,0.00027787688,0.8861989,0.00020082883,0.00046454166,0.00028658644,0.00002541716,0.00006324228,0.11243199],"genre_scores_gemma":[0.85786974,0.0022028936,0.13910139,0.00029550982,0.00007413421,0.000040403767,0.00007730132,0.000014323052,0.00032430663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784505,0.00003119919,0.0010965395,0.00028005143,0.00051473826,0.00023238982],"domain_scores_gemma":[0.99567467,0.00056667015,0.0006796812,0.002327586,0.00064856844,0.000102833554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017486328,0.00021102115,0.00034186293,0.0011321055,0.000310925,0.00044574108,0.004071725,0.00015114518,0.0000038432927],"category_scores_gemma":[0.000081960454,0.00021658669,0.00005829136,0.00056254596,0.00075581553,0.0032063737,0.0021727863,0.00037000616,0.000026546864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002161563,0.00002188832,0.000035087403,0.00008199692,0.000008433794,2.503279e-7,0.00103073,0.00067286694,0.0000037584982,0.8482613,0.00013895695,0.14974256],"study_design_scores_gemma":[0.00015141246,0.00003952324,0.0010035295,0.0006398664,0.000006771819,0.000021341042,0.000039747658,0.94447565,0.00009350134,0.0015747806,0.051655598,0.0002982679],"about_ca_topic_score_codex":0.000024757004,"about_ca_topic_score_gemma":0.0000031618797,"teacher_disagreement_score":0.9438028,"about_ca_system_score_codex":0.0001699606,"about_ca_system_score_gemma":0.00025265367,"threshold_uncertainty_score":0.8832149},"labels":[],"label_agreement":null},{"id":"W2139096462","doi":"10.1007/978-3-642-15666-3_15","title":"Software Engineering Support Activities for Very Small Entities","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Engineering management; Engineering; Information security management system; Software engineering; Process (computing); International standard; Systems engineering; Computer science","score_opus":0.03236296248743623,"score_gpt":0.2689469556484098,"score_spread":0.2365839931609736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139096462","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000049549017,0.0001346558,0.99042785,0.00022102501,0.00060004863,0.00031347197,0.000019265028,0.0003732857,0.0078608645],"genre_scores_gemma":[0.002623706,0.0009921301,0.99507195,0.0002834781,0.00005170893,0.00007750387,0.00004054115,0.000011954438,0.000847008],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99895203,0.0000062734675,0.0003960217,0.00021026762,0.00022075082,0.00021462727],"domain_scores_gemma":[0.9973037,0.0007342059,0.00021319411,0.0014780243,0.00020127604,0.00006956369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008285185,0.00020038824,0.00020091329,0.0007735023,0.00030275332,0.00078960275,0.0026095859,0.0001575352,0.000005354952],"category_scores_gemma":[0.00015821846,0.0002160485,0.0000531614,0.00016770478,0.00028102353,0.006618185,0.0015051061,0.00048657198,0.0000072744906],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025840502,0.000012556971,0.000043624583,0.00014927772,0.000011068454,3.572323e-7,0.0017072945,0.0003896849,0.000012066554,0.8094161,0.00028608614,0.18796927],"study_design_scores_gemma":[0.00017578721,0.000092751376,0.00038950128,0.00018023097,0.000008040858,0.000038194186,0.000007992604,0.11147992,0.00016733177,0.006742742,0.88023144,0.0004860436],"about_ca_topic_score_codex":0.000005909818,"about_ca_topic_score_gemma":0.0000052380997,"teacher_disagreement_score":0.8799454,"about_ca_system_score_codex":0.000068533496,"about_ca_system_score_gemma":0.00021820409,"threshold_uncertainty_score":0.8810202},"labels":[],"label_agreement":null},{"id":"W2178659164","doi":"10.1007/978-3-642-30567-2_7","title":"An SQA e-Learning System for Agile Software Development","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Agile software development; Computer science; Software engineering; Quality assurance; Lean software development; Agile Unified Process; Software quality assurance; Process (computing); Software quality; Software development; Software quality analyst; Coding (social sciences); Software; Software development process; Quality (philosophy); Engineering management; Process management; Engineering; Operations management","score_opus":0.0391812327975144,"score_gpt":0.2966397129443075,"score_spread":0.2574584801467931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2178659164","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016986589,0.0004087356,0.9889937,0.00007934276,0.0002573894,0.00033549292,0.000003635389,0.00051697635,0.009387711],"genre_scores_gemma":[0.022830306,0.00037364985,0.97629285,0.00012295353,0.00003772068,0.000078721736,0.000053384756,0.000009740488,0.00020065987],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878085,0.000022319837,0.00047945068,0.00020714359,0.00028028042,0.0002299318],"domain_scores_gemma":[0.9975105,0.0003551418,0.00030304238,0.0013995795,0.00031807047,0.00011369386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015956007,0.0001789996,0.00018197628,0.00057766284,0.00058656506,0.00063081796,0.0027634262,0.000115144416,0.0000021921587],"category_scores_gemma":[0.000059763857,0.00018289042,0.000028331298,0.00020308944,0.00015514542,0.008728769,0.001131302,0.00032782668,0.00002075466],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011171882,0.000009027199,0.000054728316,0.00008258041,0.0000040105933,9.076015e-8,0.001938523,0.00046765973,0.0000013206804,0.33342078,0.000056380704,0.6639638],"study_design_scores_gemma":[0.000121987374,0.00005821331,0.00043515846,0.0002409866,0.000004622152,0.000024354062,0.000019167348,0.25100252,0.000040677354,0.00070136046,0.74701357,0.0003374093],"about_ca_topic_score_codex":0.000003721601,"about_ca_topic_score_gemma":0.0000012198861,"teacher_disagreement_score":0.7469572,"about_ca_system_score_codex":0.0001781978,"about_ca_system_score_gemma":0.00021394505,"threshold_uncertainty_score":0.7458055},"labels":[],"label_agreement":null},{"id":"W2180906","doi":"10.1007/978-3-642-29752-6_25","title":"Using Social Network Analysis to Study the Knowledge Sharing Patterns of Health Professionals Using Web 2.0 Tools","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Social network analysis; World Wide Web; Process (computing); Knowledge management; Social network (sociolinguistics); Knowledge sharing; Health professionals; Network analysis; Health care; Data science; Social media; Engineering","score_opus":0.2314457414666685,"score_gpt":0.4444271780363277,"score_spread":0.2129814365696592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180906","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018575437,0.00014686146,0.9920171,0.0006272466,0.00017953698,0.0008157492,0.000028541213,0.000035010788,0.004292431],"genre_scores_gemma":[0.8049026,0.00040638246,0.18984513,0.0038343668,0.00013724552,0.00004077835,0.00014090168,0.000021633674,0.0006709672],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782467,0.00012728572,0.0010769648,0.0002667751,0.00046612942,0.00023815829],"domain_scores_gemma":[0.9968232,0.00015935686,0.0007325204,0.0016650677,0.0005410817,0.00007878276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027436519,0.00017778092,0.00039539105,0.0009964844,0.0011469413,0.000784211,0.0037970708,0.000057831032,0.000012796593],"category_scores_gemma":[0.000029490891,0.00014518734,0.00006688393,0.0017883183,0.00019114699,0.0035278187,0.0049739988,0.00023990509,0.000009914395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015358397,0.00018619906,0.003153267,0.000058658097,0.00019445122,1.3726326e-7,0.029104479,0.01709923,0.0000019192316,0.76040727,0.00033628824,0.18945657],"study_design_scores_gemma":[0.00011795687,0.00002560206,0.0055232695,0.0001290673,0.000034020923,0.0000013074404,0.00021552251,0.988707,4.3925306e-7,0.00065206503,0.004424631,0.00016909679],"about_ca_topic_score_codex":0.000047781978,"about_ca_topic_score_gemma":0.000035628967,"teacher_disagreement_score":0.9716078,"about_ca_system_score_codex":0.00013969357,"about_ca_system_score_gemma":0.00045401359,"threshold_uncertainty_score":0.8821461},"labels":[],"label_agreement":null},{"id":"W2181768912","doi":"10.1007/978-3-642-04579-0_6","title":"Melodic Clustering within Motivic Spaces: Visualization in OpenMusic and Application to Schumann’s Träumerei","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Melody; Cluster analysis; Visualization; Computer science; Gestalt psychology; Artificial intelligence; Mathematics; Pattern recognition (psychology); Natural language processing; Psychology; Perception; Art","score_opus":0.03202401203288839,"score_gpt":0.29875852616314397,"score_spread":0.26673451413025556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2181768912","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018835828,0.00054481823,0.94146115,0.0016402928,0.00016743745,0.0009120563,0.0000034704278,0.00017025559,0.05321696],"genre_scores_gemma":[0.8237771,0.0031391005,0.16730614,0.0043732543,0.00003972668,0.00016127444,0.000041558862,0.000016789025,0.0011450577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984257,0.000033468852,0.0006518444,0.00038456838,0.0002890814,0.00021533936],"domain_scores_gemma":[0.9979689,0.00009558925,0.00027542366,0.0014028624,0.00018163331,0.00007555821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011210812,0.00021996399,0.00028402027,0.001520238,0.00051325734,0.0005379733,0.0020145879,0.00015551328,0.0000014649928],"category_scores_gemma":[0.000046605932,0.00022880976,0.000019106808,0.00071751693,0.0005347012,0.0039265878,0.0023701352,0.00035060532,0.000017412138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017809798,0.000014436894,0.00012632245,0.000022507871,0.0000033404713,3.3304104e-7,0.008227863,0.0005956815,0.000003863518,0.7741975,0.000035159814,0.2167712],"study_design_scores_gemma":[0.0006196871,0.00016638442,0.009656703,0.00054704153,0.000010187736,0.00003830428,0.000153964,0.88863194,0.000014022872,0.05095811,0.048546772,0.00065689615],"about_ca_topic_score_codex":0.000030260839,"about_ca_topic_score_gemma":0.00025216426,"teacher_disagreement_score":0.88803625,"about_ca_system_score_codex":0.00011795249,"about_ca_system_score_gemma":0.00011516676,"threshold_uncertainty_score":0.9330591},"labels":[],"label_agreement":null},{"id":"W2185699297","doi":"10.1007/978-3-319-18422-7_14","title":"Data Sharing and Exchange: General Data-Mapping Semantics","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Semantics (computer science); Data exchange; Information retrieval; Data sharing; Meaning (existential); Conjunctive query; Information exchange; Theoretical computer science; Database; Programming language; Relational database","score_opus":0.2766356120714673,"score_gpt":0.36682020391340386,"score_spread":0.09018459184193656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2185699297","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007570662,0.0020711012,0.938875,0.005567956,0.00041867016,0.0004906849,0.0001416809,0.00034397002,0.05201523],"genre_scores_gemma":[0.0037822798,0.0046344157,0.9886236,0.001140118,0.00008881514,0.0000142249155,0.00060010323,0.000013028613,0.0011034214],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978609,0.00001786515,0.0006039616,0.00067959516,0.0005367429,0.00030091836],"domain_scores_gemma":[0.9877325,0.00010483173,0.00026778475,0.011409641,0.00033974138,0.00014545993],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0028349885,0.00023277689,0.0002733068,0.0010874288,0.00040951962,0.0013197311,0.022020748,0.00013490306,0.0000014426183],"category_scores_gemma":[0.00015075333,0.00023932151,0.000010298283,0.00064767577,0.00069339655,0.0120881265,0.0757201,0.00046521102,0.00003061826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.575413e-7,0.000008142389,0.00011460273,0.000040918374,0.000008819464,0.0000010771203,0.0014080609,0.0002513303,0.0000014032694,0.38744292,0.011331319,0.5993906],"study_design_scores_gemma":[0.00008170354,0.000012352834,0.00018386703,0.00011128334,0.0000027431786,0.000022688479,0.000011509417,0.6076103,4.080678e-7,0.005647924,0.38612378,0.00019147572],"about_ca_topic_score_codex":0.000017692186,"about_ca_topic_score_gemma":0.00003827191,"teacher_disagreement_score":0.60735893,"about_ca_system_score_codex":0.00010212627,"about_ca_system_score_gemma":0.00023167554,"threshold_uncertainty_score":0.999717},"labels":[],"label_agreement":null},{"id":"W2188396912","doi":"10.1007/978-3-642-23993-9_69","title":"Investment Value Analysis for Listed Companies of China Communications Industry","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Evaluation and Optimization Models","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"China; Corporation; Business; Investment (military); Value (mathematics); Listed company; Principal component analysis; Quarter (Canadian coin); Index (typography); Accounting; Finance; Computer science; Statistics; Geography; Mathematics; Political science","score_opus":0.10329819480633136,"score_gpt":0.3150920750254798,"score_spread":0.21179388021914847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188396912","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016729375,0.0007987107,0.6012926,0.00027432726,0.00013905221,0.000783185,0.0001696376,0.000126167,0.39624903],"genre_scores_gemma":[0.5134444,0.010776548,0.47092438,0.0009811748,0.000031819,0.00021131607,0.0015363141,0.00004422816,0.0020497956],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986145,0.000027301394,0.0008503726,0.00012497588,0.00024988956,0.00013295784],"domain_scores_gemma":[0.9970055,0.00015173346,0.00029239265,0.0020173816,0.00045557402,0.00007737627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000743014,0.00018064545,0.00033212642,0.0014102998,0.00024924387,0.00010409375,0.0016136436,0.00020412683,0.000027708387],"category_scores_gemma":[0.000031766223,0.00019548889,0.000082531784,0.00061793166,0.0008448926,0.0015976974,0.0006011662,0.00037098958,0.000005719453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021867554,0.000020875805,0.00011341934,0.000063436506,0.00009455896,9.597841e-9,0.0032087313,0.21242727,0.0000019696452,0.7710042,0.00013090574,0.012932425],"study_design_scores_gemma":[0.00021425373,0.000020906677,0.002467039,0.00007838157,0.00009105648,8.665256e-7,0.000022305632,0.9734281,0.000010932467,0.0066192104,0.016854705,0.00019226673],"about_ca_topic_score_codex":0.000013539211,"about_ca_topic_score_gemma":0.000021610706,"teacher_disagreement_score":0.764385,"about_ca_system_score_codex":0.00011123007,"about_ca_system_score_gemma":0.00013280558,"threshold_uncertainty_score":0.79718053},"labels":[],"label_agreement":null},{"id":"W2200810224","doi":"10.1007/978-3-642-11819-7_12","title":"Application of Hidden Topic Markov Models on Spoken Dialogue Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Partially observable Markov decision process; Sentence; Hidden Markov model; Artificial intelligence; Natural language processing; Latent Dirichlet allocation; Domain (mathematical analysis); Topic model; Speech recognition; Markov chain; Markov model; Machine learning; Mathematics","score_opus":0.030757061914135134,"score_gpt":0.26050149474606143,"score_spread":0.2297444328319263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2200810224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000114163384,0.00028933727,0.68546104,0.0003226838,0.0008066372,0.00081035914,0.00002913989,0.0000887496,0.31207788],"genre_scores_gemma":[0.8354296,0.0016208009,0.16014105,0.0006878802,0.00021539161,0.00017841102,0.00021554528,0.00002268654,0.0014886153],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808943,0.000036898113,0.00082495675,0.0003004304,0.0005420213,0.00020627792],"domain_scores_gemma":[0.99572474,0.00023191237,0.0005474018,0.0029699658,0.0004173432,0.00010866479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011124151,0.00021145986,0.0003291182,0.0009427055,0.0002503832,0.0003553321,0.0036773046,0.00021748115,0.0000014739022],"category_scores_gemma":[0.00003098278,0.00020254572,0.000052138323,0.00035330147,0.00056440145,0.0037164006,0.0012739549,0.00043294148,0.000050759205],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025046893,0.000013742064,0.000022999478,0.00003924078,0.0000033913939,1.3378633e-7,0.0006917134,0.00029117012,0.000015429467,0.8791567,0.000056711542,0.11970623],"study_design_scores_gemma":[0.0003986003,0.00010609624,0.00088245486,0.00027844892,0.0000061696883,0.00002367571,0.000017256962,0.8984664,0.00005870501,0.037512414,0.06183247,0.0004172688],"about_ca_topic_score_codex":0.00011089526,"about_ca_topic_score_gemma":0.000019583886,"teacher_disagreement_score":0.89817524,"about_ca_system_score_codex":0.000097619726,"about_ca_system_score_gemma":0.00024764775,"threshold_uncertainty_score":0.8259575},"labels":[],"label_agreement":null},{"id":"W220989916","doi":"10.1007/978-3-319-12024-9_16","title":"Extraction and Characterization of Citations in Scientific Papers","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Parsing; XML; Information retrieval; Information extraction; Metadata; Natural language processing; Annotation; Automatic summarization; Set (abstract data type); Section (typography); Sentence; Citation; Artificial intelligence; World Wide Web; Programming language","score_opus":0.03500837714932565,"score_gpt":0.28355985773608283,"score_spread":0.2485514805867572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W220989916","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020760568,0.00043277483,0.7904768,0.0026681102,0.0011530169,0.00095771294,0.000019714213,0.0001450974,0.18338619],"genre_scores_gemma":[0.9187774,0.0021557563,0.07758629,0.0003418854,0.000018982812,0.000024680086,0.000083677674,0.000006963023,0.0010043365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987325,0.000031836636,0.0005813607,0.00023335379,0.00028342358,0.00013749389],"domain_scores_gemma":[0.9980891,0.00020474906,0.00034727037,0.0010700023,0.00024402014,0.000044905777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011015616,0.00012686593,0.00019905475,0.0013677449,0.00025978862,0.00044175007,0.0012228475,0.0000916463,0.0000027179517],"category_scores_gemma":[0.000060678987,0.00012877762,0.000020365558,0.00048302885,0.0010076937,0.0038685712,0.000781757,0.00019606452,0.00000643203],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011285537,0.000009634387,0.000303775,0.000033692362,0.0000016707296,1.1128846e-7,0.0020030364,0.000032583375,0.00035454586,0.73671603,0.000008829682,0.260535],"study_design_scores_gemma":[0.0007173882,0.00011249528,0.21599533,0.0007109816,0.000010841414,0.00004042335,0.00010191982,0.65592945,0.00018490544,0.020154864,0.10541087,0.0006305703],"about_ca_topic_score_codex":0.000010638541,"about_ca_topic_score_gemma":0.000028267925,"teacher_disagreement_score":0.89801687,"about_ca_system_score_codex":0.000053537624,"about_ca_system_score_gemma":0.00015313651,"threshold_uncertainty_score":0.5251399},"labels":[],"label_agreement":null},{"id":"W2213883801","doi":"10.1007/978-3-662-46248-5_23","title":"Personalized Web Image Retrieval Based on User Interest Model","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Information retrieval; Image retrieval; Search engine; Image (mathematics); Region of interest; World Wide Web; Computer vision","score_opus":0.05651141051946466,"score_gpt":0.30331938852722434,"score_spread":0.2468079780077597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2213883801","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000038231947,0.00004810857,0.8269598,0.0027159764,0.00010347095,0.00029325698,0.000014090958,0.00019909575,0.1696624],"genre_scores_gemma":[0.044452276,0.002529505,0.9337829,0.007640023,0.0000619286,0.00004701561,0.00012053483,0.000033111864,0.011332716],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979824,0.000051972354,0.00069770886,0.00039488287,0.0006184929,0.0002545333],"domain_scores_gemma":[0.9958163,0.00024918574,0.00040400916,0.0027703857,0.0006257017,0.00013440852],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014309499,0.00029038644,0.0002961974,0.0011790885,0.00043172113,0.0009308956,0.0042528417,0.00017280191,0.000012263113],"category_scores_gemma":[0.00006380312,0.00027451463,0.00008616412,0.00048753622,0.001273971,0.004658533,0.0014633152,0.0005746249,0.00009244862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000081888265,0.000016760627,0.0000012302417,0.000022408873,0.0000020558589,2.0836114e-7,0.00027665036,0.000090637244,0.000049634113,0.973569,0.00049452815,0.025468709],"study_design_scores_gemma":[0.00029995554,0.00006626675,0.000017171977,0.00018512706,0.0000035068144,0.00000486456,0.0000040948103,0.89521426,0.0001667677,0.010837438,0.09291429,0.0002862443],"about_ca_topic_score_codex":0.0000018033575,"about_ca_topic_score_gemma":0.0000014330532,"teacher_disagreement_score":0.96273154,"about_ca_system_score_codex":0.00021113311,"about_ca_system_score_gemma":0.000508623,"threshold_uncertainty_score":0.9999707},"labels":[],"label_agreement":null},{"id":"W2217416062","doi":"10.1007/978-3-319-21380-4_120","title":"Is the Mood Really in the Eye of the Beholder?","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital","funders":"","keywords":"Mood; Computer science; Modal; Process (computing); Gaze; Artificial intelligence; Cognition; Feature extraction; Feature (linguistics); Set (abstract data type); Modality (human–computer interaction); Pattern recognition (psychology); Machine learning; Psychology; Social psychology","score_opus":0.1137188822588361,"score_gpt":0.33775603221846623,"score_spread":0.22403714995963014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2217416062","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005953614,0.00052306766,0.0032153407,0.02820216,0.0007148563,0.0015156934,0.000078533805,0.00004314833,0.9597536],"genre_scores_gemma":[0.98806095,0.00088163983,0.0013058644,0.007989554,0.000034318953,0.000025188489,0.000004760163,0.000007320203,0.0016904129],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983617,0.00012434761,0.00057409075,0.0001729603,0.00060850196,0.00015837398],"domain_scores_gemma":[0.9966955,0.00055774674,0.000357434,0.0021855216,0.00017575172,0.000028026108],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001721162,0.00014682571,0.00015318129,0.00025443753,0.00041575386,0.0003014947,0.0057491795,0.0000711093,0.0000055484375],"category_scores_gemma":[0.0001221889,0.00007556025,0.00005038342,0.00048360438,0.0018896012,0.0014800094,0.0018763607,0.00053765206,0.000013587161],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000082514425,0.00007027642,0.00043451448,0.000048713802,0.000005021888,3.2008913e-7,0.04799032,0.0009001031,0.000112687325,0.8573495,0.005819583,0.08726071],"study_design_scores_gemma":[0.00074510695,0.00015650973,0.013841731,0.0007649482,0.000018042643,0.000075846336,0.0006121629,0.1508928,0.0009818658,0.042840466,0.7885309,0.00053966313],"about_ca_topic_score_codex":0.000023733071,"about_ca_topic_score_gemma":0.000033327302,"teacher_disagreement_score":0.98210734,"about_ca_system_score_codex":0.0000484724,"about_ca_system_score_gemma":0.00020310984,"threshold_uncertainty_score":0.9996302},"labels":[],"label_agreement":null},{"id":"W2221716727","doi":"10.1007/978-3-319-64870-5_24","title":"Adaptive Non-local Means Using Weight Thresholding","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Thresholding; Non-local means; Smoothing; Noise reduction; Pixel; Artificial intelligence; Image (mathematics); Pattern recognition (psychology); Noise (video); Mathematics; Computer science; Image denoising; Gaussian; Gaussian noise; Video denoising; Algorithm; Computer vision","score_opus":0.08651298011232578,"score_gpt":0.3386288696842629,"score_spread":0.25211588957193715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2221716727","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007994255,0.000227981,0.78244656,0.00022608285,0.00034202295,0.00018227432,0.0000038250746,0.000042270938,0.21652098],"genre_scores_gemma":[0.027288757,0.0010320898,0.9692953,0.00084296765,0.00007677327,0.000009193369,0.000010722369,0.000012517687,0.001431664],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99822634,0.00004357504,0.0005855143,0.00033695332,0.0005153723,0.00029224006],"domain_scores_gemma":[0.995714,0.00019583564,0.0004641177,0.0030636801,0.00044496276,0.00011740543],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.001841954,0.00025234584,0.00031035638,0.0009158369,0.00132928,0.0013096652,0.005431541,0.00014664537,0.0000044170133],"category_scores_gemma":[0.00003847294,0.00024756347,0.00006529336,0.0001946911,0.0014731163,0.011203978,0.0037471836,0.0005444331,0.00003599749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003331658,0.000008673701,0.000008076495,0.000013557791,0.000007127175,0.0000020900611,0.0018838263,0.0008533978,0.000010388505,0.52924645,0.00011501772,0.46784803],"study_design_scores_gemma":[0.00029537408,0.00003591103,0.00015783227,0.0003253542,0.000007011003,0.000043403474,0.000011315492,0.94072694,0.000043654596,0.024049236,0.033990245,0.00031372465],"about_ca_topic_score_codex":0.000035088182,"about_ca_topic_score_gemma":0.000005852485,"teacher_disagreement_score":0.9398735,"about_ca_system_score_codex":0.00019950572,"about_ca_system_score_gemma":0.0004505153,"threshold_uncertainty_score":0.9999977},"labels":[],"label_agreement":null},{"id":"W2225812146","doi":"10.1007/978-3-642-27207-3_14","title":"COSMIC Functional Size Measurement Using UML Models","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Unified Modeling Language; Computer science; COSMIC cancer database; Programming language; Astronomy; Physics; Software","score_opus":0.18651982694562994,"score_gpt":0.2993028095764839,"score_spread":0.11278298263085398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2225812146","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038409922,0.00038904318,0.9490949,0.00015847065,0.00034072524,0.0002714558,0.0000040970694,0.0001295701,0.049573325],"genre_scores_gemma":[0.31876153,0.0020747543,0.67703146,0.0008648018,0.00008784326,0.000059732647,0.000019243167,0.000030192983,0.0010704579],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782735,0.000024838253,0.00054066203,0.0002903082,0.0010404297,0.0002764256],"domain_scores_gemma":[0.9963277,0.00032194576,0.00018751145,0.0021518408,0.0008825284,0.00012850139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017928217,0.00020844168,0.0001995151,0.0008615653,0.0003957997,0.0004683258,0.0032168587,0.00010737008,0.0000129650625],"category_scores_gemma":[0.00015906422,0.00021835868,0.00004424295,0.00042980778,0.00054656743,0.007157122,0.002756021,0.00047409997,0.000048754162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000307329,0.000023737313,0.000051329007,0.00004048526,0.000013740472,5.8002615e-7,0.0014406965,0.008151538,0.00001070668,0.84436864,0.00030029626,0.14559521],"study_design_scores_gemma":[0.00020531742,0.00002818101,0.0015815843,0.00019037766,0.0000037735742,0.000030401237,0.0000028940538,0.9590458,0.000010442516,0.027365098,0.011242032,0.00029405343],"about_ca_topic_score_codex":0.00002130941,"about_ca_topic_score_gemma":0.0000031198356,"teacher_disagreement_score":0.9508943,"about_ca_system_score_codex":0.00045627594,"about_ca_system_score_gemma":0.0006632698,"threshold_uncertainty_score":0.8904408},"labels":[],"label_agreement":null},{"id":"W2226565836","doi":"10.1007/978-3-642-37419-7_6","title":"The Smart-CondoTMInfrastructure and Experience","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Home automation; Middleware (distributed applications); Computer science; Variety (cybernetics); Automation; Feature (linguistics); Architecture; Actuator; Building automation; Competition (biology); Smart environment; Human–computer interaction; Real-time computing; Artificial intelligence; Embedded system; Telecommunications; Internet of Things; Engineering; Distributed computing; Geography","score_opus":0.032110957036939745,"score_gpt":0.2723175666407962,"score_spread":0.24020660960385645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2226565836","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010668307,0.0027143864,0.48158535,0.00570993,0.001530971,0.0017982038,0.000021243946,0.00028481765,0.50528824],"genre_scores_gemma":[0.8578488,0.012264428,0.1136591,0.0041841757,0.00014713705,0.0003776974,0.000040394334,0.000033503224,0.011444716],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984148,0.00004155892,0.0005914792,0.0002944745,0.0004208543,0.00023683932],"domain_scores_gemma":[0.9963987,0.00055560516,0.00035758398,0.002138048,0.0004308623,0.00011919921],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007779915,0.00021588929,0.00021230827,0.00041856852,0.0010181061,0.0020067676,0.0032371092,0.00011091991,0.000010553257],"category_scores_gemma":[0.00006559681,0.00016964445,0.000031878382,0.00028866614,0.0015426796,0.008774803,0.003006587,0.0004167361,0.00008154883],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.2325194e-7,0.000002406475,0.000051228737,0.000008412292,0.000003287847,1.3225781e-7,0.00268287,0.0000026470643,0.0000031329491,0.33378264,0.0003327451,0.66312987],"study_design_scores_gemma":[0.00032693482,0.000046244313,0.004428484,0.00020015553,0.000003987273,0.00014066977,0.00014803014,0.20056868,0.000019029008,0.019964287,0.7736707,0.00048280213],"about_ca_topic_score_codex":0.000026659807,"about_ca_topic_score_gemma":0.000022426198,"teacher_disagreement_score":0.856782,"about_ca_system_score_codex":0.00008280544,"about_ca_system_score_gemma":0.00018851383,"threshold_uncertainty_score":0.9990292},"labels":[],"label_agreement":null},{"id":"W2229414573","doi":"10.1007/978-3-319-23201-0_10","title":"Data Warehouse Design Methods Review: Trends, Challenges and Future Directions for the Healthcare Domain","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"","keywords":"Computer science; Data warehouse; Traceability; Schema (genetic algorithms); Data integration; Data science; Information integration; Domain (mathematical analysis); Information retrieval; Software engineering; Database; Data mining","score_opus":0.6732383815595341,"score_gpt":0.543693081677569,"score_spread":0.12954529988196506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2229414573","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.9096644e-8,0.27147704,0.58454937,0.10679663,0.000587398,0.0010799086,0.0004923876,0.000046376816,0.03497085],"genre_scores_gemma":[0.000009426927,0.6630327,0.3324037,0.0028182932,0.00009372531,0.00008233656,0.00023391322,0.0000066240536,0.0013192848],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972741,0.00037833964,0.000973967,0.00041850962,0.00077452156,0.00018053425],"domain_scores_gemma":[0.99050283,0.0028392903,0.0005199704,0.0053412225,0.0006803089,0.000116382675],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.027962858,0.00018317292,0.00034472195,0.00069236493,0.000853305,0.0005554814,0.0055951006,0.00008762954,0.0000118492535],"category_scores_gemma":[0.0006844412,0.0001215592,0.000036497542,0.00046395962,0.0008936714,0.0045948373,0.0045249625,0.00029634175,0.000014060042],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022435145,0.0000045703196,1.16375105e-7,0.00004029657,0.0000048335964,2.1463357e-8,0.0012832778,0.0000057853827,7.81641e-9,0.22910318,0.027718736,0.74183697],"study_design_scores_gemma":[0.00012469475,0.000035171262,0.00008381263,0.00017945723,0.000016879605,0.0000070699953,0.0005183663,0.018302651,3.8319648e-8,0.043146778,0.9374493,0.00013581412],"about_ca_topic_score_codex":0.000011467245,"about_ca_topic_score_gemma":0.00011808751,"teacher_disagreement_score":0.90973055,"about_ca_system_score_codex":0.000062614374,"about_ca_system_score_gemma":0.00020337987,"threshold_uncertainty_score":0.9997851},"labels":[],"label_agreement":null},{"id":"W2276754229","doi":"10.1007/978-3-642-31686-9_54","title":"A Fair and Efficient Gang Scheduling Algorithm for Multicore Processors","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Computer science; Multi-core processor; Parallel computing; Scheduling (production processes); Mathematics; Mathematical optimization","score_opus":0.038445402045293876,"score_gpt":0.2912399864883532,"score_spread":0.2527945844430593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2276754229","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000100009085,0.0013199989,0.9865389,0.00026819145,0.00031082256,0.0006077786,0.000025508643,0.00010756435,0.010721223],"genre_scores_gemma":[0.14925854,0.00068226986,0.84905344,0.00038064376,0.00009775491,0.00007153988,0.00008634415,0.0000134756165,0.00035599386],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838287,0.000021638602,0.0006174282,0.00030939392,0.00034066473,0.0003280249],"domain_scores_gemma":[0.9975454,0.000278389,0.00036371447,0.0011793171,0.00048431562,0.00014886683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013532407,0.0002358433,0.0002746034,0.0005833542,0.0006142456,0.0008108383,0.0021499638,0.00012750256,8.764444e-7],"category_scores_gemma":[0.00004577599,0.00022843955,0.0000440974,0.00031249243,0.00049656857,0.0028570823,0.0017644782,0.00028288848,0.000014275341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010070078,0.000020018657,0.000023099536,0.000088072484,0.000006561927,1.2883731e-7,0.003251797,0.0021080028,0.0000013846216,0.26990587,0.000041230265,0.7245528],"study_design_scores_gemma":[0.00029166354,0.000031232077,0.00019531339,0.0002655605,0.000005410473,0.000026110252,0.000025630721,0.9533929,0.000003628452,0.0013784479,0.044120774,0.00026327706],"about_ca_topic_score_codex":0.0000060290554,"about_ca_topic_score_gemma":0.000001228808,"teacher_disagreement_score":0.95128495,"about_ca_system_score_codex":0.00008837651,"about_ca_system_score_gemma":0.00019688482,"threshold_uncertainty_score":0.93154943},"labels":[],"label_agreement":null},{"id":"W228530811","doi":"10.1007/978-3-319-14136-7_74","title":"Unravelling the Literature Review: Helping Graduate Students in Education Re-conceptualize the Research Process","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Reflective Practices in Education","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Process (computing); Visualization; Identification (biology); Visual literacy; Graduate students; Information literacy; Graduate education; Concept map; Mind map; Computer science; Psychology; Mathematics education; Pedagogy; Library science; Medical education; Medicine","score_opus":0.18131333715853967,"score_gpt":0.5136307792421069,"score_spread":0.33231744208356717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W228530811","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008689066,0.04247493,0.0021747192,0.04655774,0.001488327,0.0038845092,0.000004635474,0.000050948172,0.90249527],"genre_scores_gemma":[0.33751225,0.6383073,0.005130752,0.010213932,0.00055499596,0.0006447353,0.00009169409,0.000024780264,0.0075195804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99654275,0.0008374984,0.0006647742,0.0002462913,0.0014233633,0.00028533433],"domain_scores_gemma":[0.994752,0.0015516724,0.0004922534,0.0014202863,0.0017225412,0.00006126999],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.018033633,0.00014722446,0.00017602797,0.0006712123,0.0022251538,0.0012999427,0.0041817855,0.00011577502,0.000010042434],"category_scores_gemma":[0.0014882118,0.00010429863,0.00003065644,0.0016504903,0.0026448725,0.0036786613,0.00073525903,0.0014235739,0.00003522093],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003825357,0.00003938003,0.00036362675,0.00022208004,0.0000053332205,6.733442e-8,0.24817458,0.000079456106,3.6141304e-7,0.41004768,0.002100718,0.3389629],"study_design_scores_gemma":[0.0001145929,0.000026263657,0.0027764572,0.007959499,0.000011328988,0.0000046628907,0.009451412,0.0026033537,0.0000016791635,0.035329677,0.9414642,0.00025689343],"about_ca_topic_score_codex":0.00018801495,"about_ca_topic_score_gemma":0.00031878022,"teacher_disagreement_score":0.9393635,"about_ca_system_score_codex":0.0004538743,"about_ca_system_score_gemma":0.0013308489,"threshold_uncertainty_score":0.9997368},"labels":[],"label_agreement":null},{"id":"W2286955625","doi":"10.1007/978-3-642-20573-6_38","title":"Hybrid Routing for Ad Hoc Wireless Networks","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer network; Computer science; Hybrid routing; Zone Routing Protocol; Wireless Routing Protocol; Routing protocol; Enhanced Interior Gateway Routing Protocol; Dynamic Source Routing; Optimized Link State Routing Protocol; Distributed computing; Link-state routing protocol; Wireless ad hoc network; Routing (electronic design automation); Wireless; Telecommunications","score_opus":0.03854846068641695,"score_gpt":0.26812668030881087,"score_spread":0.22957821962239391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2286955625","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000013047619,0.0007809231,0.9261413,0.00023762714,0.0005116933,0.000653623,0.000007939914,0.00012777623,0.07152606],"genre_scores_gemma":[0.23185717,0.020006647,0.7400031,0.003969416,0.00028301904,0.00041578125,0.00018992765,0.000060958886,0.0032140012],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979881,0.000028541885,0.00084091164,0.0003994496,0.0003363937,0.00040658202],"domain_scores_gemma":[0.99555194,0.00036512036,0.0005335211,0.0029219398,0.00048666348,0.00014080692],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0015015434,0.00028393185,0.00032462613,0.00055739185,0.00066881825,0.0007213042,0.005436168,0.0001453268,0.0000057644274],"category_scores_gemma":[0.000026171665,0.0002965568,0.00007761121,0.00029283288,0.0007348439,0.006413175,0.0034472952,0.0005191084,0.000026154585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018085955,0.000006595388,0.000003989924,0.000010013749,0.0000036457495,1.7614533e-7,0.00044883657,0.0005030939,1.6736169e-7,0.52623355,0.00033256007,0.47245553],"study_design_scores_gemma":[0.00022567209,0.00005665796,0.00009666267,0.0001842471,0.0000048928523,0.000016673474,0.000003327688,0.8646159,0.0000033611686,0.011869675,0.12261133,0.00031158328],"about_ca_topic_score_codex":0.000003869687,"about_ca_topic_score_gemma":0.00000631914,"teacher_disagreement_score":0.86411285,"about_ca_system_score_codex":0.00014490967,"about_ca_system_score_gemma":0.000255254,"threshold_uncertainty_score":0.9999487},"labels":[],"label_agreement":null},{"id":"W2293474702","doi":"10.1007/978-3-319-29510-7_5","title":"Towards a Body of Knowledge in Formal Methods for the Railway Domain: Identification of Settled Knowledge","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Identification (biology); Construct (python library); Computer science; Normative; Domain (mathematical analysis); Domain knowledge; Body of knowledge; Domain analysis; Formal methods; Data science; Artificial intelligence; Knowledge management; Epistemology; Software engineering; Mathematics; Software development; Programming language; Software; Philosophy","score_opus":0.058833714334708354,"score_gpt":0.37535808815211597,"score_spread":0.3165243738174076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293474702","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000070901006,0.0015750293,0.9517641,0.00071041164,0.00035915695,0.00062482373,0.00001451963,0.000024784511,0.044856288],"genre_scores_gemma":[0.29229817,0.0040725456,0.7020314,0.00017301599,0.000057488243,0.00023174893,0.00001987838,0.000015585661,0.0011001832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806327,0.00009388695,0.0012016001,0.0002168835,0.00020118637,0.0002231508],"domain_scores_gemma":[0.9951139,0.0014890196,0.0006854029,0.0019909237,0.00068224163,0.000038494098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049425215,0.00017415264,0.00035533772,0.00093068957,0.00024169567,0.000121611585,0.004094189,0.00012373498,0.0000022329525],"category_scores_gemma":[0.00017133796,0.00012213773,0.000084962805,0.0004988257,0.0011978204,0.0035391096,0.0020398942,0.00018361966,0.0000063411944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003600011,0.000016707123,0.000012359613,0.000054612276,0.000005169258,1.1814449e-8,0.0029622857,0.000007965686,0.00006169016,0.59573615,0.000029922601,0.40110955],"study_design_scores_gemma":[0.0017287845,0.00021938936,0.01121772,0.0008287459,0.00002644963,0.000015643282,0.00024004647,0.7189965,0.0017866474,0.124563016,0.13980375,0.00057329756],"about_ca_topic_score_codex":0.000007895393,"about_ca_topic_score_gemma":0.000019900814,"teacher_disagreement_score":0.71898854,"about_ca_system_score_codex":0.000092486385,"about_ca_system_score_gemma":0.00046239342,"threshold_uncertainty_score":0.760809},"labels":[],"label_agreement":null},{"id":"W2294267303","doi":"10.1007/978-3-319-25840-9_18","title":"Techniques for Merging Upper Ontologies","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Ontology components; Ontology; Computer science; Process ontology; IDEF5; Upper ontology; Ontology-based data integration; Merge (version control); Information retrieval; Open Biomedical Ontologies; Web Ontology Language; Ontology alignment; Suggested Upper Merged Ontology; Focus (optics); Bridge (graph theory); Semantic Web; Epistemology","score_opus":0.08994957818910755,"score_gpt":0.3407285614362266,"score_spread":0.25077898324711906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294267303","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007859019,0.0010132265,0.7443888,0.0020974586,0.000290069,0.00045405576,0.0000068695226,0.0002621882,0.25147945],"genre_scores_gemma":[0.008384822,0.0021715155,0.9865527,0.0009821713,0.000045003533,0.00009298101,0.000028591025,0.00000824191,0.0017339872],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986615,0.00001643405,0.0005157713,0.0002524737,0.00031792204,0.00023585939],"domain_scores_gemma":[0.99696636,0.0002941992,0.0002571654,0.0018409584,0.00057322904,0.00006810393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013039258,0.00019060067,0.00026311853,0.00080075336,0.00035377432,0.0005447766,0.0038495262,0.00013484477,0.0000017891795],"category_scores_gemma":[0.0001315369,0.0001728684,0.000047704656,0.00021851495,0.0007831619,0.005725491,0.0023824887,0.0002291916,0.000015361522],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.55988e-7,0.0000037873076,0.000015789465,0.000012669318,0.000002249554,9.402071e-8,0.00070662925,0.0000105315885,8.01791e-7,0.6825942,0.0009228245,0.31572953],"study_design_scores_gemma":[0.00020334635,0.000087331944,0.00028260428,0.0001710441,0.0000055601936,0.000024175479,0.000059821192,0.17221518,0.000039665967,0.10186422,0.7246834,0.00036364584],"about_ca_topic_score_codex":0.000011891427,"about_ca_topic_score_gemma":0.000012166254,"teacher_disagreement_score":0.7237606,"about_ca_system_score_codex":0.000128147,"about_ca_system_score_gemma":0.00032866263,"threshold_uncertainty_score":0.71534413},"labels":[],"label_agreement":null},{"id":"W2342981176","doi":"10.1007/978-3-319-57969-6_1","title":"NeuroHex: A Deep Q-learning Hex Agent","year":2017,"lang":"en","type":"preprint","venue":"Communications in computer and information science","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Olympiad; Reinforcement learning; Computer science; Q-learning; Champion; Artificial intelligence; Initialization; State (computer science); Convolutional neural network; Action (physics); Algorithm; Mathematics; Political science; Law; Mathematics education","score_opus":0.05352251106668458,"score_gpt":0.32683744967227296,"score_spread":0.27331493860558836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342981176","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00082196726,0.00020294395,0.9816179,0.0015354126,0.0008663356,0.00036503968,9.770782e-7,0.00018307565,0.014406336],"genre_scores_gemma":[0.7364022,0.002363465,0.26044562,0.0006339923,0.00003457424,0.00005068153,0.000028326167,0.000006525275,0.00003461298],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976854,0.00015088872,0.0007303031,0.00040076097,0.00064719527,0.00038549415],"domain_scores_gemma":[0.9938077,0.00020368317,0.00074099825,0.004723398,0.00037983365,0.00014438933],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0018433142,0.00024699335,0.00026927327,0.00090851734,0.0013580042,0.003815184,0.010279684,0.00013072869,0.0000025514582],"category_scores_gemma":[0.00037911063,0.0002580405,0.00005878957,0.0005801287,0.00082725985,0.007079501,0.020437043,0.0012617006,0.00006198742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001266403,0.000019993047,0.0014720523,0.00006117141,0.000006168578,0.0000010139414,0.0056246966,0.66592765,0.0000038618837,0.039742194,0.0000641004,0.28707582],"study_design_scores_gemma":[0.00017483212,0.000035542012,0.013776762,0.00012993002,0.0000030178303,0.000011996596,0.00002597636,0.96082646,0.000008117184,0.0007671694,0.02398334,0.00025685545],"about_ca_topic_score_codex":0.00003911544,"about_ca_topic_score_gemma":0.0000042197776,"teacher_disagreement_score":0.7355802,"about_ca_system_score_codex":0.00017100736,"about_ca_system_score_gemma":0.00035773075,"threshold_uncertainty_score":0.9999872},"labels":[],"label_agreement":null},{"id":"W2345785510","doi":"10.1007/978-3-319-27695-3_3","title":"Ambient Technology to Support Elderly People in Outdoor Risk Situations","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Elderly people; Assistive technology; Quality of life (healthcare); Activities of daily living; Older people; Independent living; Disabled people; Gerontology; Business; Internet privacy; Computer science; Environmental health; Medicine; Physical therapy; Nursing; Human–computer interaction; Life style","score_opus":0.056655608034804406,"score_gpt":0.3219722669084196,"score_spread":0.2653166588736152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345785510","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013314798,0.0002576828,0.8659056,0.007038855,0.000759196,0.001654713,0.00007611121,0.0003173613,0.12265905],"genre_scores_gemma":[0.8558488,0.0011133912,0.1390746,0.0012200432,0.000055446668,0.00033557968,0.00010898061,0.000024474879,0.0022186842],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99757224,0.00006548484,0.0009789459,0.0004354776,0.0006195416,0.00032831234],"domain_scores_gemma":[0.9955276,0.00024133133,0.00046519708,0.0026635022,0.00091133144,0.0001910199],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002107727,0.00025650652,0.00039391086,0.0035920106,0.00034953063,0.0005927351,0.0038392146,0.00019998838,0.000012252356],"category_scores_gemma":[0.00021016864,0.0002810592,0.000045704073,0.0017259757,0.0003838745,0.0059705856,0.0033672466,0.00062410155,0.00044926652],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023643468,0.000044500346,0.0006266161,0.000013749702,0.0000055074897,7.9079325e-7,0.00590402,0.00026140246,0.0000034781099,0.14986823,0.0010022703,0.84226704],"study_design_scores_gemma":[0.0013535371,0.0006798836,0.0074125556,0.0005316641,0.000015137071,0.0001383764,0.00036365996,0.24340531,0.000024425008,0.045509886,0.69930005,0.001265514],"about_ca_topic_score_codex":0.00010622726,"about_ca_topic_score_gemma":0.0009932924,"teacher_disagreement_score":0.85451734,"about_ca_system_score_codex":0.00042790815,"about_ca_system_score_gemma":0.00073548086,"threshold_uncertainty_score":0.9999642},"labels":[],"label_agreement":null},{"id":"W23725892","doi":"10.1007/978-3-642-37186-8_4","title":"Spectral Clustering: An Explorative Study of Proximity Measures","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Cluster analysis; Spectral clustering; Measure (data warehouse); Computer science; Euclidean distance; Similarity (geometry); Data mining; Similarity measure; Distance measures; Distance matrix; Usability; Boundary (topology); Artificial intelligence; Pattern recognition (psychology); Mathematics; Algorithm","score_opus":0.1191461492858851,"score_gpt":0.3554448074291799,"score_spread":0.2362986581432948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W23725892","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011990083,0.00010402004,0.9442823,0.00024785564,0.00018050915,0.0013261378,0.0000071908157,0.000108934066,0.05254404],"genre_scores_gemma":[0.4363323,0.0010768571,0.561143,0.00016655974,0.000052077696,0.0001803994,0.00002708958,0.00002198845,0.0009997815],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99773544,0.00008285829,0.0007410446,0.00035702257,0.0008202297,0.00026339825],"domain_scores_gemma":[0.9956167,0.00015840335,0.00037789583,0.002885641,0.00082199374,0.0001393968],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001101824,0.00022670737,0.0003141262,0.0010010952,0.00036197604,0.00052796083,0.004787133,0.00008243849,0.000007030543],"category_scores_gemma":[0.00005493222,0.00021806441,0.00002830586,0.0004916318,0.0006422452,0.015922507,0.00430326,0.00050076615,0.000030555184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008721258,0.00026215755,0.00007494577,0.000055411467,0.000018594965,0.0000011637918,0.03315069,0.005488986,0.000018358676,0.17825352,0.000042885877,0.7826246],"study_design_scores_gemma":[0.00041383048,0.0005840201,0.0013060104,0.00011513333,0.0000032654073,0.000014471438,0.00037127742,0.98471785,0.00002749124,0.00833835,0.0037843187,0.00032400023],"about_ca_topic_score_codex":0.000062021056,"about_ca_topic_score_gemma":0.00006681795,"teacher_disagreement_score":0.97922885,"about_ca_system_score_codex":0.0001588439,"about_ca_system_score_gemma":0.00025277157,"threshold_uncertainty_score":0.9978413},"labels":[],"label_agreement":null},{"id":"W2400023023","doi":"10.1007/978-3-319-25915-4_1","title":"Blueprints of an Automated Android Test-Bed","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thales (Canada); Cegep de Sainte Foy","funders":"","keywords":"Virtualization; Computer science; Android (operating system); Blueprint; Automation; Operating system; Virtual machine; Embedded system; Engineering; Cloud computing","score_opus":0.044570391099070766,"score_gpt":0.3376052011009867,"score_spread":0.2930348100019159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400023023","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016230093,0.00020429888,0.8758534,0.00024591602,0.00022940901,0.00059399556,0.000026398542,0.0012059495,0.12147828],"genre_scores_gemma":[0.0743818,0.00075681735,0.92401254,0.000309522,0.000018246947,0.000033089334,0.00003937175,0.000013047922,0.0004355497],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829996,0.00002903166,0.00073001755,0.00027334323,0.0004915398,0.00017610745],"domain_scores_gemma":[0.99547464,0.00017142232,0.0005089762,0.0027761818,0.00093732454,0.00013147316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011743336,0.00019296457,0.0002671255,0.0011261641,0.00022641546,0.00023409411,0.0037542337,0.00013189639,0.000004028957],"category_scores_gemma":[0.00013277045,0.00020118339,0.000030193383,0.000543549,0.0008135685,0.009083042,0.0024874767,0.00031778114,0.00002225723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031284953,0.000049935315,0.000020360065,0.000034121487,0.0000042497495,6.780557e-7,0.0016943874,0.00038736174,0.000055828343,0.41899973,0.00025737844,0.5784928],"study_design_scores_gemma":[0.00034416525,0.00023834831,0.00051403843,0.00018807821,0.000003948447,0.00006350641,0.000016728622,0.897564,0.0006489931,0.037871577,0.062145945,0.00040069074],"about_ca_topic_score_codex":0.000010639133,"about_ca_topic_score_gemma":0.0000065065,"teacher_disagreement_score":0.8971766,"about_ca_system_score_codex":0.00015144209,"about_ca_system_score_gemma":0.0003418943,"threshold_uncertainty_score":0.820402},"labels":[],"label_agreement":null},{"id":"W2400177336","doi":"10.1007/978-3-319-25840-9_21","title":"Multiple Dimensions to Data-Driven Ontology Evaluation","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Ontology; Computer science; Upper ontology; Ontology-based data integration; Process ontology; Correctness; Domain (mathematical analysis); Ontology Inference Layer; Information retrieval; Categorical variable; Suggested Upper Merged Ontology; Representation (politics); Natural language processing; Semantic Web; OWL-S; Data mining; Algorithm; Machine learning; Mathematics","score_opus":0.21736492769936597,"score_gpt":0.38071275980183905,"score_spread":0.16334783210247308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400177336","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019027304,0.001276321,0.7287967,0.0068759527,0.001243736,0.0014153965,0.000066136156,0.00025306732,0.25988242],"genre_scores_gemma":[0.1987849,0.0012049215,0.7955894,0.0029780143,0.00007682019,0.00008184979,0.00044634115,0.000014151819,0.00082362874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793524,0.000064514315,0.0006119796,0.00042776123,0.00071217516,0.00024834092],"domain_scores_gemma":[0.9934585,0.0003395379,0.0002487161,0.004976177,0.00081481657,0.00016226582],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0024197663,0.00019745222,0.00027341364,0.0009397133,0.00036315504,0.00041883584,0.0068448344,0.00012713426,0.0000066375233],"category_scores_gemma":[0.0004058292,0.00018808435,0.000022638262,0.00041204935,0.00052703853,0.0064274315,0.008440983,0.0002895652,0.0001268494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003097912,0.000022553764,0.00010507819,0.000010373956,0.000008473362,5.941006e-7,0.0022772965,0.0022461142,0.0000029890718,0.5713051,0.0067266487,0.4172917],"study_design_scores_gemma":[0.00023683277,0.000041376737,0.0011919811,0.00006479136,0.000007489282,0.000018009305,0.000022155344,0.79960024,0.0000011979724,0.0071399356,0.19147423,0.00020177086],"about_ca_topic_score_codex":0.000045650293,"about_ca_topic_score_gemma":0.00019466512,"teacher_disagreement_score":0.7973541,"about_ca_system_score_codex":0.00020041667,"about_ca_system_score_gemma":0.00071811397,"threshold_uncertainty_score":0.99957854},"labels":[],"label_agreement":null},{"id":"W2403791939","doi":"10.1007/978-3-319-29585-5_6","title":"A Framework for Designing On-line Listening Activities for Postsecondary Music Courses: What Students’ Performance and Perceptions Tells Us","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Diverse Music Education Insights","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Active listening; Perception; Psychology; Task (project management); Avatar; Musical; Mathematics education; Applied psychology; Computer science; Communication; Human–computer interaction; Engineering; Visual arts","score_opus":0.11533350739849843,"score_gpt":0.33067083433484357,"score_spread":0.21533732693634514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403791939","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05295033,0.0016156122,0.26717153,0.0058991113,0.009998668,0.009137294,0.0011358132,0.0004174744,0.65167415],"genre_scores_gemma":[0.7186665,0.015381903,0.18625544,0.014977916,0.002023929,0.0013666187,0.0005903856,0.000121774574,0.060615525],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99884707,0.0000150961005,0.00045365826,0.00021841952,0.00026467963,0.00020107323],"domain_scores_gemma":[0.99757177,0.00094265776,0.0003131054,0.0006679385,0.00043352795,0.00007098882],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005815218,0.00021037788,0.00022741387,0.00066341803,0.0015865569,0.0019474677,0.0008365913,0.0000869822,0.000116431096],"category_scores_gemma":[0.000043095584,0.00018355729,0.00004918223,0.00004352227,0.0015147836,0.0072123935,0.00040609713,0.0002307606,0.00001945129],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013742039,0.000025013462,0.000031755186,0.000079915444,0.000014170877,2.4412506e-8,0.059950657,0.000023192137,8.9657027e-7,0.83274543,0.00059633923,0.106518835],"study_design_scores_gemma":[0.00094189716,0.0005126122,0.00039856206,0.0035814906,0.00005201624,0.000007965424,0.012611415,0.011376867,0.0000084076655,0.023483561,0.9463253,0.0006999011],"about_ca_topic_score_codex":0.000002897045,"about_ca_topic_score_gemma":0.000017886732,"teacher_disagreement_score":0.94572896,"about_ca_system_score_codex":0.000118316304,"about_ca_system_score_gemma":0.00018978442,"threshold_uncertainty_score":0.99971324},"labels":[],"label_agreement":null},{"id":"W2403864102","doi":"10.1007/978-3-319-29585-5_29","title":"Can Playing Massive Multiplayer Online Role Playing Games (MMORPGs) Improve Older Adults’ Socio-Psychological Wellbeing?","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Loneliness; Psychology; Guild; Social support; Quality (philosophy); Depression (economics); Social psychology","score_opus":0.024487873126012884,"score_gpt":0.31183738252868654,"score_spread":0.2873495094026737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403864102","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087978624,0.0022515827,0.022721207,0.042679153,0.0032065837,0.005845019,0.0008380551,0.001886568,0.8325932],"genre_scores_gemma":[0.9606727,0.0034626513,0.0320079,0.0014506789,0.00016565983,0.00007425643,0.0000749385,0.00002299642,0.0020682162],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99749047,0.000077610195,0.0008076856,0.00046700402,0.0006246424,0.00053260924],"domain_scores_gemma":[0.99680984,0.00048847985,0.0005785981,0.0014527697,0.00048762624,0.00018270657],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0010715228,0.00031943986,0.000359192,0.00087401667,0.0017789702,0.00032999873,0.002912591,0.00052238663,0.00004420801],"category_scores_gemma":[0.00025502796,0.00028388636,0.000080786696,0.00032355814,0.003593443,0.0029855783,0.0015632064,0.00085879164,0.000063133884],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019733796,0.000093094844,0.0025217508,0.000034007455,0.00002288775,0.000002153444,0.04813228,0.000014862043,0.000043626955,0.32681325,0.00032644134,0.6219759],"study_design_scores_gemma":[0.013008653,0.00074639154,0.15380296,0.010126712,0.00016104957,0.00010354675,0.03408606,0.13899763,0.0001275182,0.087475844,0.55391705,0.0074465554],"about_ca_topic_score_codex":0.00015034722,"about_ca_topic_score_gemma":0.0004310977,"teacher_disagreement_score":0.8726941,"about_ca_system_score_codex":0.0003983468,"about_ca_system_score_gemma":0.00032879013,"threshold_uncertainty_score":0.9999613},"labels":[],"label_agreement":null},{"id":"W2415313051","doi":"10.1007/978-3-319-22689-7_19","title":"Asymmetry Theory and Asymmetry Based Parsing","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Asymmetry; Parsing; Computer science; Natural language processing; Physics; Particle physics","score_opus":0.036806962591631284,"score_gpt":0.3166785686922267,"score_spread":0.2798716061005954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2415313051","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009643333,0.0056294617,0.9007735,0.0007586399,0.00015105799,0.00022673437,0.000006132119,0.00023415359,0.092210665],"genre_scores_gemma":[0.036848985,0.0005964677,0.9601879,0.0018283204,0.000025867836,0.000011544477,0.000024664143,0.0000098733135,0.00046638612],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984601,0.00007045778,0.0004836388,0.00029543746,0.00047658492,0.0002137733],"domain_scores_gemma":[0.9969112,0.00040774915,0.0003001402,0.0018002026,0.0004494365,0.00013122646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031610199,0.0002185184,0.0002334618,0.001211886,0.00038138614,0.00088272616,0.0030186262,0.00016131632,0.0000025605445],"category_scores_gemma":[0.0001789863,0.00020558732,0.000027430635,0.00050517387,0.00097106077,0.006413405,0.002720399,0.0005395667,0.000011723734],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014839471,0.0000042925235,0.000009877241,0.000018020539,0.0000014097074,3.2063568e-7,0.0003342099,0.000005607023,0.0000015645995,0.67211103,0.00016380384,0.32734838],"study_design_scores_gemma":[0.00041398907,0.000094871,0.00017416239,0.0006776586,0.000010816473,0.00006586814,0.000028976536,0.40894935,0.000098578676,0.49529824,0.0935003,0.00068719976],"about_ca_topic_score_codex":0.0000057831157,"about_ca_topic_score_gemma":0.0000018462139,"teacher_disagreement_score":0.40894374,"about_ca_system_score_codex":0.00015295377,"about_ca_system_score_gemma":0.0003803144,"threshold_uncertainty_score":0.8512148},"labels":[],"label_agreement":null},{"id":"W2417822074","doi":"10.1007/978-3-319-27695-3_4","title":"Toward Context-Aware Smart Oven to Prevent Cooking Risks in Kitchen of Elderly People","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Context (archaeology); Microcontroller; Elderly people; Computer science; Ubiquitous computing; Assistive technology; Architecture; Context awareness; Life style; Population; Unit (ring theory); Focus (optics); Embedded system; Human–computer interaction; Medicine; Psychology; Gerontology; Environmental health; Geography","score_opus":0.13744608249980403,"score_gpt":0.3363749517815694,"score_spread":0.19892886928176537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2417822074","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039238944,0.0011819744,0.8626371,0.0036903014,0.0009952807,0.0028178426,0.000095405565,0.00020447199,0.12445372],"genre_scores_gemma":[0.9885724,0.00025911586,0.010322845,0.00042304848,0.000019984334,0.00006935218,0.00002857273,0.000009673587,0.00029501715],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99740744,0.0000963017,0.0011481533,0.00036806715,0.00070238486,0.00027767255],"domain_scores_gemma":[0.9959496,0.00037371478,0.0005888391,0.002003648,0.0009044153,0.00017973986],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0022444157,0.00025971633,0.00051947724,0.001510125,0.00015850789,0.0003779397,0.0034804025,0.0001583203,0.000008535904],"category_scores_gemma":[0.000112719485,0.00028098022,0.00006439057,0.0007949176,0.00030392257,0.0052380743,0.0029178252,0.00045163208,0.00006153485],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000077516415,0.000075916534,0.0007497394,0.0000905271,0.000013380412,8.8403357e-7,0.019640991,0.00029090297,0.0000059896265,0.0759376,0.00047482547,0.9027115],"study_design_scores_gemma":[0.002955207,0.00092612376,0.024121355,0.0051663094,0.00003404222,0.00018857964,0.0013373585,0.50638974,0.00021943847,0.022734618,0.43340072,0.002526529],"about_ca_topic_score_codex":0.0004750335,"about_ca_topic_score_gemma":0.00065132894,"teacher_disagreement_score":0.9846485,"about_ca_system_score_codex":0.00034333678,"about_ca_system_score_gemma":0.0006529633,"threshold_uncertainty_score":0.99996424},"labels":[],"label_agreement":null},{"id":"W24593649","doi":"10.1007/978-3-642-38833-0_2","title":"Derivation of Green Metrics for Software","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Green IT and Sustainability","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Dispose pattern; Sustainability; Software; Computer science; Set (abstract data type); Green computing; Software engineering; Software metric; Software development; Software construction; Operating system; Programming language; Ecology","score_opus":0.03256095637337255,"score_gpt":0.25974093513835306,"score_spread":0.2271799787649805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W24593649","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012474894,0.0005957146,0.91294646,0.00020133646,0.00024821545,0.0011748985,0.000053654872,0.00013513718,0.08339711],"genre_scores_gemma":[0.36576307,0.0031167562,0.6269665,0.00032789615,0.00007323057,0.00021340114,0.0004183123,0.00004178941,0.003079078],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924564,0.0000042067727,0.00042485798,0.000071670736,0.00015272631,0.00010090729],"domain_scores_gemma":[0.998452,0.00017634919,0.00010392987,0.00072508166,0.0005086217,0.00003398496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004129174,0.0000981855,0.00014961837,0.0006240409,0.00010533834,0.0000651312,0.00066049554,0.00008373652,0.00000739245],"category_scores_gemma":[0.00006847962,0.0001016382,0.000028794133,0.00023819141,0.00031997132,0.0019539904,0.00026504323,0.00012869414,0.000005643768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014399993,0.000006789576,0.00031764412,0.00041678912,0.0000078093935,1.4263096e-8,0.0015284248,0.0019224109,0.0000026993498,0.18355581,0.0005266875,0.81171346],"study_design_scores_gemma":[0.00026018723,0.000044855195,0.0043838434,0.00010497653,0.000009566665,0.0000018248306,0.000050833987,0.8251109,0.000025592295,0.026780447,0.14295574,0.00027123862],"about_ca_topic_score_codex":0.000016747506,"about_ca_topic_score_gemma":0.0000072908692,"teacher_disagreement_score":0.8231885,"about_ca_system_score_codex":0.00009840649,"about_ca_system_score_gemma":0.000066263965,"threshold_uncertainty_score":0.41446856},"labels":[],"label_agreement":null},{"id":"W2466557971","doi":"10.1007/978-3-319-25117-2_16","title":"Unsupervised Visual Hull Reconstruction of a Dense Dataset","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Visual hull; Artificial intelligence; Object (grammar); Computer science; Computer vision; Hull; Sequence (biology); Image (mathematics); 3D reconstruction; Iterative reconstruction; Pattern recognition (psychology); Computer graphics (images); Engineering","score_opus":0.06758085248480074,"score_gpt":0.3486920989234175,"score_spread":0.2811112464386168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2466557971","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000060056045,0.0008355463,0.9118105,0.00059590105,0.0004360375,0.00036358376,0.00010197697,0.00008286499,0.0857135],"genre_scores_gemma":[0.021812115,0.0042189294,0.97162515,0.001211237,0.00004653421,0.000017285067,0.0004372065,0.000014830995,0.00061672286],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984188,0.000030202142,0.00071405806,0.00023837002,0.00043433977,0.00016420688],"domain_scores_gemma":[0.997048,0.00011216737,0.00040108556,0.0017640701,0.0005612039,0.000113441274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009968044,0.0001669752,0.00024802738,0.0009519709,0.00021553742,0.00024746737,0.0023909744,0.00007636733,0.000009009981],"category_scores_gemma":[0.00006527363,0.00016678456,0.000030167936,0.00041629758,0.0008596682,0.008768078,0.002316846,0.00029375855,0.000036696023],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026824612,0.000012354097,0.000018529976,0.000018368988,0.0000028116146,2.330946e-7,0.0006490166,0.00008896692,0.000010618433,0.14601262,0.00058934366,0.85259444],"study_design_scores_gemma":[0.00042133944,0.00006842253,0.00018116152,0.0003060709,0.0000042352594,0.000072674084,0.00003570305,0.82045066,0.000027936947,0.011893779,0.16626635,0.0002716393],"about_ca_topic_score_codex":0.000008678341,"about_ca_topic_score_gemma":0.0000035792448,"teacher_disagreement_score":0.8523228,"about_ca_system_score_codex":0.00009905048,"about_ca_system_score_gemma":0.00034890597,"threshold_uncertainty_score":0.6801277},"labels":[],"label_agreement":null},{"id":"W2479442986","doi":"10.1007/978-3-642-34447-3","title":"Contemporary Research on E-business Technology and Strategy","year":2012,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Business Strategy and Innovation","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Works and Government Services Canada","funders":"","keywords":"China; Library science; Computer science; Political science; Law","score_opus":0.16542151987056705,"score_gpt":0.35584573290398863,"score_spread":0.19042421303342158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2479442986","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022766034,0.0006276019,0.001732772,0.0040492937,0.0003219692,0.0005381703,0.000004896103,0.000106420695,0.99034226],"genre_scores_gemma":[0.994712,0.0005679836,0.0011104803,0.001551331,0.00030162552,0.000057477737,0.00023351976,0.000013933398,0.0014516347],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986645,0.000015267246,0.00048024397,0.00020123727,0.00037698532,0.0002617583],"domain_scores_gemma":[0.9973258,0.00010181737,0.00027916272,0.0008891441,0.001389324,0.00001478578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019498036,0.00017122008,0.00019550882,0.0045912312,0.00073181966,0.00085200265,0.001050229,0.00021106811,0.00001027009],"category_scores_gemma":[0.000082347215,0.00016216355,0.000010618757,0.0038811227,0.0017674176,0.01202383,0.0013580484,0.00066264125,0.000117298616],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068320614,0.000028198587,0.00061169517,0.00012617529,0.0000023800674,2.0361186e-7,0.00005494161,0.00003253527,0.0000026343637,0.90949667,0.004900143,0.084737614],"study_design_scores_gemma":[0.00049093715,0.000027114393,0.03497211,0.0005512363,0.0000060061,0.000008939787,0.00016794547,0.019955741,0.0000030815424,0.030964158,0.9124446,0.0004081284],"about_ca_topic_score_codex":0.00003564389,"about_ca_topic_score_gemma":0.0000061808396,"teacher_disagreement_score":0.9924354,"about_ca_system_score_codex":0.000082966195,"about_ca_system_score_gemma":0.00038310574,"threshold_uncertainty_score":0.8716986},"labels":[],"label_agreement":null},{"id":"W2482088207","doi":"10.1007/978-3-319-40581-0_31","title":"Computing Theoretically-Sound Upper Bounds to Expected Support for Frequent Pattern Mining Problems over Uncertain Big Data","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Data mining; Uncertain data; Probabilistic logic; Database transaction; Big data; Upper and lower bounds; Tree (set theory); Transaction data; Artificial intelligence; Mathematics; Database","score_opus":0.09379594328863143,"score_gpt":0.33280221958336237,"score_spread":0.23900627629473092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2482088207","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000042256575,0.00006725871,0.9598421,0.0019078953,0.00038918667,0.000831595,0.00036014014,0.00012157881,0.03643803],"genre_scores_gemma":[0.038141686,0.0004218443,0.9536676,0.0041635437,0.00031214135,0.00022507916,0.0012585414,0.0000428431,0.0017667166],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99725676,0.000025535428,0.0009953988,0.0007262147,0.0005392802,0.00045682036],"domain_scores_gemma":[0.99315333,0.00060764083,0.00041036814,0.0051243757,0.00048635885,0.000217918],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0018761448,0.0003218265,0.00033743042,0.0008123234,0.0008029698,0.0014188539,0.008325228,0.00013250065,0.000012235813],"category_scores_gemma":[0.00011598138,0.00028291857,0.000049778355,0.00048461836,0.00078349997,0.0042300187,0.007615951,0.00026048027,0.000050547216],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.849284e-7,0.000016514556,0.000047491394,0.000020061083,0.000008109185,1.4243679e-7,0.0018726102,0.000028890081,0.0000031803745,0.33828208,0.00086425483,0.6588557],"study_design_scores_gemma":[0.0004911913,0.000120322846,0.0007233899,0.0004926239,0.000012002074,0.000021246029,0.000040736137,0.6530701,0.0000046807704,0.01790167,0.32649794,0.0006240948],"about_ca_topic_score_codex":0.000016657554,"about_ca_topic_score_gemma":0.000018573324,"teacher_disagreement_score":0.6582316,"about_ca_system_score_codex":0.00018097974,"about_ca_system_score_gemma":0.00043223845,"threshold_uncertainty_score":0.9999623},"labels":[],"label_agreement":null},{"id":"W2486074773","doi":"10.1007/978-3-642-22309-9","title":"Future Information Technology","year":2011,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Social Media and Politics","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Volume (thermodynamics); Set (abstract data type); Computer science; Library science; Information retrieval; Data science; Physics","score_opus":0.03835950389960433,"score_gpt":0.33184766416134687,"score_spread":0.2934881602617425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2486074773","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015731277,0.0003428934,0.0037386434,0.004045841,0.0014033223,0.00047022934,0.000021063286,0.00014225206,0.98967844],"genre_scores_gemma":[0.2758965,0.18635295,0.41960266,0.04021361,0.008388766,0.0011908234,0.0025370407,0.000119864875,0.06569779],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987409,0.000054010397,0.0004595031,0.000086216765,0.00038522691,0.00027413215],"domain_scores_gemma":[0.998207,0.00012287825,0.00027583932,0.00077007513,0.0005161942,0.00010805213],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007515544,0.000119652585,0.00016378856,0.0012665899,0.00095200073,0.0002882713,0.0018207398,0.0003310159,0.00002438143],"category_scores_gemma":[0.00017432464,0.000127776,0.000026529306,0.00096377847,0.002763249,0.0071215946,0.00062483584,0.0004604736,0.00016671213],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.704137e-7,0.0000050198178,0.00016064922,0.000011141498,0.0000016494469,3.760685e-8,0.038850624,6.475812e-7,5.2873485e-8,0.76154476,0.0024820704,0.19694269],"study_design_scores_gemma":[0.00009765163,0.000014803576,0.00028651915,0.00005270332,0.00000418891,0.0000014628616,0.0031734363,0.0003846064,0.0000014919049,0.024013452,0.9718263,0.00014335584],"about_ca_topic_score_codex":0.00012425406,"about_ca_topic_score_gemma":0.000089462475,"teacher_disagreement_score":0.96934426,"about_ca_system_score_codex":0.0003146529,"about_ca_system_score_gemma":0.0017275424,"threshold_uncertainty_score":0.99995065},"labels":[],"label_agreement":null},{"id":"W2486410140","doi":"10.1007/978-3-319-40548-3_67","title":"Speech-Enabled Intelligent Mobile Interfaces to Support Older Adults’ Storytelling Around Digital Family Pictures","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Storytelling; Digital storytelling; Computer science; Multimedia; Thesaurus; Human–computer interaction; World Wide Web; Natural language processing; Art; Literature; Narrative","score_opus":0.028152223972264096,"score_gpt":0.30352273618552533,"score_spread":0.27537051221326125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2486410140","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029803963,0.0010970177,0.08904063,0.0028165234,0.0016747286,0.003777452,0.00014876154,0.0007106052,0.8709303],"genre_scores_gemma":[0.97339964,0.004336633,0.011903838,0.001293809,0.00013087392,0.00011372157,0.000042240896,0.000024328336,0.008754907],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978929,0.00003146607,0.00072879915,0.00034807253,0.00060315675,0.00039558366],"domain_scores_gemma":[0.9973566,0.0002675932,0.0003078006,0.0013598953,0.00052203116,0.00018606507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010184936,0.00025883352,0.00028692727,0.0011506118,0.00080898055,0.0007614897,0.002968443,0.0002523638,0.000048582722],"category_scores_gemma":[0.00012167981,0.00023422264,0.000051788138,0.00037368713,0.0022105107,0.0048965667,0.0016186457,0.00044086497,0.0002964757],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009890728,0.000027714137,0.0001663526,0.000022766108,0.000010317669,7.543664e-7,0.035546813,0.00006521556,0.0000027903473,0.08028149,0.0007157093,0.88315016],"study_design_scores_gemma":[0.00038085948,0.00018170392,0.00051803223,0.0010107992,0.000009582538,0.000009022305,0.0046376246,0.0016583602,0.00005285072,0.0051172427,0.98577845,0.0006454958],"about_ca_topic_score_codex":0.00004491188,"about_ca_topic_score_gemma":0.00017602429,"teacher_disagreement_score":0.9850627,"about_ca_system_score_codex":0.00039000652,"about_ca_system_score_gemma":0.00044787233,"threshold_uncertainty_score":0.9551322},"labels":[],"label_agreement":null},{"id":"W2487880732","doi":"10.1007/978-3-319-40548-3_76","title":"Privacy Awareness and Design for Live Video Broadcasting Apps","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Broadcasting (networking); Computer science; Internet privacy; World Wide Web; Computer security","score_opus":0.11307033745721302,"score_gpt":0.3535803772852187,"score_spread":0.24051003982800567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2487880732","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000104232175,0.00088717643,0.8827816,0.00295922,0.00040400104,0.0017008771,0.0000672808,0.00010785331,0.110987715],"genre_scores_gemma":[0.2845496,0.06929193,0.6336959,0.0031762454,0.0011482268,0.00082075427,0.00029578357,0.00006969685,0.006951864],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987793,0.000068562615,0.00042041816,0.0002149514,0.00029278547,0.00022395764],"domain_scores_gemma":[0.99754846,0.00073903415,0.00029024537,0.0008950274,0.0004025835,0.00012462064],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0024754081,0.00014086229,0.00017647033,0.00043649325,0.0018945725,0.0005295397,0.0016177351,0.00014142224,0.000010859532],"category_scores_gemma":[0.0008727984,0.00013215315,0.000026239064,0.00015872464,0.0015026954,0.0053431354,0.001627815,0.00018931025,0.000017460652],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009774092,0.000009377412,0.000064634434,0.000044439254,0.00000459106,6.283543e-8,0.015712231,0.000010300786,0.0000029512291,0.46698016,0.00049214717,0.51666933],"study_design_scores_gemma":[0.00054224796,0.000079874466,0.00042217472,0.0005817025,0.000014148926,0.0000069216526,0.00040447427,0.03505091,0.000010883026,0.13161549,0.8308218,0.0004493461],"about_ca_topic_score_codex":0.00010940265,"about_ca_topic_score_gemma":0.0000564204,"teacher_disagreement_score":0.83032966,"about_ca_system_score_codex":0.00014795648,"about_ca_system_score_gemma":0.00057385635,"threshold_uncertainty_score":0.99940485},"labels":[],"label_agreement":null},{"id":"W2491214854","doi":"10.1007/978-3-319-40548-3_66","title":"An Information-Centric Framework for Mobile Collaboration Between Seniors and Caregivers that Balances Independence, Privacy, and Social Connectedness","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Social connectedness; Autonomy; Independence (probability theory); Cognition; Internet privacy; Aging in place; Psychology; Information sharing; Gerontology; Computer science; Social psychology; Medicine; World Wide Web; Psychiatry; Political science","score_opus":0.026949625188880118,"score_gpt":0.3239461462084812,"score_spread":0.2969965210196011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2491214854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21969011,0.0024980295,0.5946481,0.04217735,0.0028226783,0.019727342,0.002385986,0.0020599263,0.11399044],"genre_scores_gemma":[0.97686464,0.0028353473,0.01957379,0.00030675865,0.0000786682,0.00010597708,0.0001261248,0.000007869334,0.00010084419],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99854714,0.00005908143,0.000453234,0.00021911843,0.0004597932,0.0002616588],"domain_scores_gemma":[0.99760723,0.00054523756,0.00048315575,0.0005541284,0.0007042643,0.0001059786],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0010582285,0.00018665146,0.00026091118,0.0008133924,0.0017329945,0.0007146984,0.0011614525,0.00043859074,0.0000055123746],"category_scores_gemma":[0.0001337116,0.00018130463,0.000021034099,0.00038410097,0.002697681,0.010678198,0.0004698061,0.00031493895,0.0000049822784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006692719,0.000006311131,0.0033386543,0.000041362542,0.000008930959,6.725588e-8,0.06605071,0.000003074226,4.445826e-7,0.7261559,0.000097628494,0.20429024],"study_design_scores_gemma":[0.0021675332,0.00034281393,0.021349862,0.00066808594,0.00007011124,0.0000113606,0.031063903,0.004458002,0.00002125579,0.11127012,0.8272465,0.0013304717],"about_ca_topic_score_codex":0.000044242905,"about_ca_topic_score_gemma":0.0000972998,"teacher_disagreement_score":0.82714885,"about_ca_system_score_codex":0.00017984612,"about_ca_system_score_gemma":0.00051755045,"threshold_uncertainty_score":0.9995666},"labels":[],"label_agreement":null},{"id":"W2492853704","doi":"10.1007/978-3-319-40542-1_7","title":"Criss-Crossing Idea Landscapes via Idea Networks in Knowledge Forum","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Christian Studies; University of Toronto","funders":"","keywords":"Computer science; Information retrieval","score_opus":0.05672260570393281,"score_gpt":0.39503704554162455,"score_spread":0.3383144398376917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2492853704","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029246326,0.0009105956,0.4219398,0.0004973187,0.00058791885,0.0001948614,0.0000040336113,0.00005912675,0.5755139],"genre_scores_gemma":[0.92993194,0.00050297286,0.054320723,0.0015619323,0.00023160613,0.00006557542,0.00007907771,0.000040341627,0.013265815],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982521,0.00022279996,0.0007689805,0.00025100267,0.00016969396,0.0003354186],"domain_scores_gemma":[0.99748796,0.00061567244,0.0003667038,0.0012111156,0.00026277115,0.000055762564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037711717,0.00021725381,0.00028861457,0.0011498753,0.0006722169,0.00034387398,0.0012661086,0.00021603226,0.000045347755],"category_scores_gemma":[0.00008266376,0.00018985738,0.000040333354,0.00041717966,0.0010019502,0.0016257631,0.000823365,0.00094150624,0.00010168477],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060241964,0.00001489461,0.0010492967,0.000008880954,0.0000050312274,3.1208347e-7,0.0069473684,0.00011094665,0.0000017935799,0.404225,0.00033337894,0.5872971],"study_design_scores_gemma":[0.0011433471,0.000105342275,0.03911368,0.0010198648,0.000009602981,0.00004989466,0.00026966896,0.15645841,0.0000023424254,0.019633878,0.7814345,0.0007595028],"about_ca_topic_score_codex":0.000026042795,"about_ca_topic_score_gemma":0.00003129447,"teacher_disagreement_score":0.9296395,"about_ca_system_score_codex":0.00013887114,"about_ca_system_score_gemma":0.00013587151,"threshold_uncertainty_score":0.77421594},"labels":[],"label_agreement":null},{"id":"W2503804885","doi":"10.1007/978-3-319-40548-3_68","title":"Designing ICTs for Elders: Considering a Taxonomy of Dignity","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sheridan College","funders":"","keywords":"Dignity; ICTS; Taxonomy (biology); Computer science; Library science; World Wide Web; Information and Communications Technology; Political science; Biology; Zoology; Law","score_opus":0.10545453720143204,"score_gpt":0.32391348112325646,"score_spread":0.2184589439218244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2503804885","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015842917,0.00031857612,0.5702062,0.0027674409,0.00026355314,0.0017954402,0.00006573952,0.00015510625,0.4242695],"genre_scores_gemma":[0.40677512,0.0043860227,0.58429486,0.00073022454,0.000097396805,0.00033129528,0.000024633722,0.00002142794,0.0033390252],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892485,0.000027225913,0.00047653745,0.0001434094,0.0002286486,0.00019932422],"domain_scores_gemma":[0.9977058,0.00065047824,0.00037832363,0.0007558105,0.0004500815,0.000059515616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013850754,0.000112550515,0.0001982904,0.0006332225,0.0006257504,0.00008616724,0.0012843823,0.00015644587,0.0000069149874],"category_scores_gemma":[0.00030299017,0.00011007697,0.000036614514,0.0001710658,0.0024876911,0.0027696686,0.00059829635,0.0001739301,0.0000074530703],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029087487,0.0000075541225,0.00013809778,0.000031744297,0.000006589239,5.218902e-8,0.0060023717,0.000006528119,0.000012552765,0.74295175,0.00024820305,0.25059164],"study_design_scores_gemma":[0.00067263824,0.000067095905,0.00019481829,0.00091885397,0.000014504107,0.0000034230434,0.000788943,0.002153202,0.00020993361,0.050054323,0.94453627,0.00038600597],"about_ca_topic_score_codex":0.00003403683,"about_ca_topic_score_gemma":0.00014299112,"teacher_disagreement_score":0.9442881,"about_ca_system_score_codex":0.00016010668,"about_ca_system_score_gemma":0.000511777,"threshold_uncertainty_score":0.9166001},"labels":[],"label_agreement":null},{"id":"W2507969500","doi":"10.1007/978-3-319-44817-6_2","title":"Implementing the New ISO/IEC 29110 Systems Engineering Process Standard in a Small Public Transportation Company","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Capability Maturity Model Integration; Maturity (psychological); Process (computing); Engineering management; Engineering; Information security management system; Work (physics); Systems engineering; Computer science; Software development process; Software development; Software","score_opus":0.0454251061000584,"score_gpt":0.30455693402509826,"score_spread":0.25913182792503986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2507969500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005332898,0.00056955084,0.9860003,0.0035658511,0.00014361257,0.0006165274,0.00001961698,0.00010096212,0.008450281],"genre_scores_gemma":[0.9366106,0.0036124017,0.05777294,0.0005267525,0.00012820488,0.00017688438,0.00010352508,0.000027468219,0.0010412202],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976688,0.000047762464,0.0009222168,0.00030625606,0.00063144916,0.000423483],"domain_scores_gemma":[0.9969906,0.0004593545,0.000308361,0.0016137229,0.0005050424,0.00012291636],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0031415988,0.00019908337,0.00028562904,0.0010991776,0.00044921917,0.001352164,0.004070112,0.00009167291,0.000005177518],"category_scores_gemma":[0.00010549382,0.00014954736,0.000056179673,0.0009506725,0.0003411312,0.004789626,0.00077569997,0.00046398767,0.000012539593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024925378,0.000012167185,0.00066550344,0.000102764825,0.000011788645,4.7673836e-7,0.004043618,0.0028328786,0.0000026170064,0.75633526,0.00005676749,0.23593365],"study_design_scores_gemma":[0.0004799868,0.000042559677,0.0023647149,0.0006002399,0.0000061058518,0.000008635319,0.000103296436,0.84155506,0.00000732262,0.0059334594,0.14853473,0.0003638782],"about_ca_topic_score_codex":0.000061735474,"about_ca_topic_score_gemma":0.00021446988,"teacher_disagreement_score":0.9360773,"about_ca_system_score_codex":0.00022441923,"about_ca_system_score_gemma":0.0007043038,"threshold_uncertainty_score":0.9996845},"labels":[],"label_agreement":null},{"id":"W2527786628","doi":"10.1007/978-3-319-46565-4_5","title":"Entity Typing and Linking Using SPARQL Patterns and DBpedia","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Polytechnique Montréal","funders":"","keywords":"SPARQL; Computer science; Entity linking; Named graph; Information retrieval; Linked data; Pipeline (software); Ontology; Exploit; Context (archaeology); RDF; Semantic Web; Dependency (UML); Natural language processing; Knowledge base; World Wide Web; Artificial intelligence; Programming language; Biology","score_opus":0.04272373627817886,"score_gpt":0.30970495499498546,"score_spread":0.2669812187168066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527786628","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034664743,0.0020398404,0.9875564,0.00035822176,0.000139007,0.00024141687,0.0000070996552,0.00011042857,0.009200926],"genre_scores_gemma":[0.12118227,0.004043786,0.8739772,0.0005462013,0.00005016043,0.000010104837,0.000008065589,0.000008794332,0.00017342958],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989616,0.000021981248,0.0003770638,0.00025265932,0.00021371873,0.00017294243],"domain_scores_gemma":[0.99834096,0.00013792116,0.00026362852,0.000977478,0.00020500588,0.00007500957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081028807,0.0001648083,0.0001744421,0.0006379515,0.00044326187,0.00085562066,0.0015124057,0.000110063214,0.0000016596224],"category_scores_gemma":[0.00003319508,0.0001443204,0.000015738819,0.00016391033,0.0005702616,0.006763913,0.0035987971,0.0003053509,0.0000026674231],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.1566706e-7,0.0000032499613,0.0005004179,0.00007427371,0.0000028365862,4.3670687e-7,0.0013074741,0.0000019154304,0.000034476732,0.5495371,0.000005803503,0.44853127],"study_design_scores_gemma":[0.0007515054,0.00010493363,0.0037114788,0.005825132,0.000027083108,0.00040378026,0.000037630147,0.6789208,0.00030135302,0.27440384,0.033868928,0.0016435075],"about_ca_topic_score_codex":0.000014526478,"about_ca_topic_score_gemma":0.000007856063,"teacher_disagreement_score":0.6789189,"about_ca_system_score_codex":0.000079079575,"about_ca_system_score_gemma":0.00011320185,"threshold_uncertainty_score":0.825077},"labels":[],"label_agreement":null},{"id":"W2528039253","doi":"10.1007/978-3-319-46565-4_3","title":"Collective Disambiguation and Semantic Annotation for Entity Linking and Typing","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Polytechnique Montréal","funders":"","keywords":"Computer science; Heuristics; Task (project management); Natural language processing; Annotation; Information retrieval; Entity linking; Semantic annotation; Artificial intelligence; Knowledge base","score_opus":0.033698256612100214,"score_gpt":0.31277809580133026,"score_spread":0.2790798391892301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528039253","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014736681,0.0011861792,0.99059194,0.0008058511,0.000106478656,0.0004485963,0.000008175503,0.00009867209,0.0066067106],"genre_scores_gemma":[0.11409309,0.0016954974,0.88285,0.0004990855,0.00003495465,0.00005624432,0.00002830155,0.000008812203,0.00073400466],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990884,0.000019271789,0.0003454006,0.00024120587,0.00017128346,0.0001344259],"domain_scores_gemma":[0.9983272,0.0002919967,0.0002750374,0.0005900053,0.0004696398,0.00004614131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085269555,0.0001373269,0.00015502007,0.00062169414,0.0005574706,0.0007018457,0.0008306986,0.000096042975,4.4876597e-7],"category_scores_gemma":[0.00009269646,0.0001230607,0.000016099288,0.00021646004,0.0004733537,0.00606002,0.001138045,0.00016858932,0.0000013675793],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018393906,0.0000028441102,0.000038147453,0.00005517852,0.0000024454037,4.9659974e-8,0.001820963,0.0000015419397,0.000021251655,0.577164,0.000010604836,0.42088112],"study_design_scores_gemma":[0.0004727178,0.000093210656,0.0011428735,0.0011117803,0.000011850565,0.00003368509,0.00002082317,0.4865735,0.00012056803,0.501881,0.008103039,0.00043498987],"about_ca_topic_score_codex":0.0000041507665,"about_ca_topic_score_gemma":0.000008610519,"teacher_disagreement_score":0.48657194,"about_ca_system_score_codex":0.00015198895,"about_ca_system_score_gemma":0.0002167779,"threshold_uncertainty_score":0.67679137},"labels":[],"label_agreement":null},{"id":"W2528953081","doi":"10.1007/978-3-319-46565-4_24","title":"An Automatic Workflow for the Formalization of Scholarly Articles’ Structural and Semantic Elements","year":2016,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; SPARQL; Information retrieval; Workflow; Linked data; Task (project management); Leverage (statistics); Knowledge base; Pipeline (software); Entity linking; RDF; Scalability; Semantic Web; World Wide Web; Natural language processing; Database; Artificial intelligence; Programming language","score_opus":0.04082705378113091,"score_gpt":0.3059914529439521,"score_spread":0.2651643991628212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528953081","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021199593,0.00046703254,0.99209553,0.0011277254,0.00019398383,0.0005853191,0.000008822059,0.000055858705,0.003345766],"genre_scores_gemma":[0.74098814,0.0010430634,0.25729468,0.00047533563,0.000022704146,0.000033039745,0.000010941641,0.000005921328,0.00012613693],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987939,0.000023717615,0.0005708334,0.00016026787,0.0002888952,0.00016239357],"domain_scores_gemma":[0.99749506,0.00036130045,0.00035183533,0.0013698242,0.00037395264,0.00004804512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010931873,0.00012868636,0.00016777238,0.00037394062,0.0004623107,0.0008319458,0.002241657,0.000066358894,0.0000021927972],"category_scores_gemma":[0.00007717956,0.00008563548,0.000025032728,0.00019576868,0.0006521195,0.011830675,0.00087475986,0.000117619566,0.0000022874933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001071912,0.0000027908482,0.00030638868,0.000024560937,0.0000041462117,2.0189383e-8,0.0010561132,0.000022807893,0.000005841836,0.4799972,0.000010492032,0.5185686],"study_design_scores_gemma":[0.00029096802,0.00007126105,0.010628928,0.00016551024,0.000008859091,0.000009084243,0.00003643758,0.94274193,0.000024816087,0.04366598,0.0022233054,0.00013291334],"about_ca_topic_score_codex":0.0000047472304,"about_ca_topic_score_gemma":0.000011132019,"teacher_disagreement_score":0.9427191,"about_ca_system_score_codex":0.00003565201,"about_ca_system_score_gemma":0.00011087035,"threshold_uncertainty_score":0.8576954},"labels":[],"label_agreement":null},{"id":"W2587786246","doi":"10.1007/978-3-319-53946-1_6","title":"Formal Probabilistic Analysis of a WSN-Based Monitoring Framework for IoT Applications","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Internet of Things; Computer science; Probabilistic logic; Wireless sensor network; Embedded system; Computer network; Artificial intelligence","score_opus":0.045696978785536496,"score_gpt":0.31947562153986897,"score_spread":0.2737786427543325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587786246","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004327709,0.00019082334,0.9841965,0.000263619,0.00018099368,0.0006648648,0.000025934658,0.00006554789,0.014368449],"genre_scores_gemma":[0.13633198,0.00034240546,0.8626998,0.000115366296,0.000048451657,0.00022971466,0.00006945851,0.000010068557,0.00015275057],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99805254,0.00002041886,0.00082520134,0.00034215898,0.00046071375,0.0002989414],"domain_scores_gemma":[0.99338305,0.00085587054,0.0009246232,0.003961615,0.0007747863,0.00010006827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010975872,0.00022530778,0.00042961183,0.0017456281,0.00082994165,0.00062325236,0.0050768806,0.00019048591,0.0000015859188],"category_scores_gemma":[0.00011019994,0.0002344724,0.00014451324,0.00071970053,0.0009833829,0.0027127708,0.0014006632,0.00034104873,0.000003279368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020553346,0.000019439396,0.00005829908,0.000038546892,0.000027018319,3.6903906e-8,0.000392974,0.11119948,7.6764206e-7,0.7681169,0.0000034667426,0.120141044],"study_design_scores_gemma":[0.00015067069,0.000038309634,0.000838515,0.00022093566,0.00006859992,8.8170697e-7,0.00000649984,0.97332376,0.00001445845,0.013277868,0.011825083,0.00023443201],"about_ca_topic_score_codex":0.0000075722414,"about_ca_topic_score_gemma":0.00001031809,"teacher_disagreement_score":0.86212426,"about_ca_system_score_codex":0.0001349137,"about_ca_system_score_gemma":0.00038358392,"threshold_uncertainty_score":0.9561507},"labels":[],"label_agreement":null},{"id":"W25902527","doi":"10.1007/978-3-642-10238-7_6","title":"Voronoi-assisted Parallel Bidirectional Heuristic Search","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Heuristic; Speedup; Computer science; Overhead (engineering); Voronoi diagram; Process (computing); Heuristics; Variety (cybernetics); Exponential function; Algorithm; Parallel computing; Artificial intelligence; Mathematics","score_opus":0.06442006760290148,"score_gpt":0.31304050211553885,"score_spread":0.24862043451263738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W25902527","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007787218,0.00032548912,0.7942951,0.0013360961,0.00034177935,0.00026795885,0.000007904004,0.00016260696,0.20325528],"genre_scores_gemma":[0.004458705,0.0013405209,0.9883785,0.0010316181,0.0000661946,0.000019463461,0.00007570017,0.000009728121,0.0046195737],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99788934,0.00005141442,0.00068521465,0.000360586,0.00070002547,0.00031344],"domain_scores_gemma":[0.9967286,0.00026969393,0.00025377912,0.0021612453,0.00043388136,0.00015281321],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012731116,0.00024286161,0.00027252728,0.0011639444,0.00059754035,0.00073539204,0.003892515,0.00014267967,0.0000064733044],"category_scores_gemma":[0.0000513752,0.00025081763,0.00004987182,0.00055706897,0.00072209706,0.004634963,0.0017449036,0.0005963161,0.00014377812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015262171,0.000022275322,0.00002882263,0.000013386966,0.000005601725,0.0000016344035,0.00080350466,0.0031028264,0.0000011665228,0.3784911,0.0004386165,0.61708957],"study_design_scores_gemma":[0.0002524807,0.0000685646,0.008950988,0.00018040137,0.0000041578264,0.00010321781,0.000005889025,0.92298496,0.0000016681777,0.0058333618,0.061267003,0.0003473342],"about_ca_topic_score_codex":0.000016308622,"about_ca_topic_score_gemma":0.0000020541754,"teacher_disagreement_score":0.9198821,"about_ca_system_score_codex":0.00023128772,"about_ca_system_score_gemma":0.00050767785,"threshold_uncertainty_score":0.9999944},"labels":[],"label_agreement":null},{"id":"W2592238845","doi":"10.1007/978-3-319-55209-5_8","title":"Topic-Based Sentiment Analysis","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; SemEval; Sentence; Natural language processing; Classifier (UML); Artificial intelligence; Dependency (UML); Parsing; Polarity (international relations); Dependency grammar; Sentiment analysis; Exploit; Task (project management); Information retrieval","score_opus":0.050679811316329725,"score_gpt":0.32025495745484667,"score_spread":0.26957514613851696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592238845","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000026338665,0.00029710276,0.7308989,0.0022707875,0.00027100396,0.00020230524,0.0000056427643,0.000064759224,0.26596317],"genre_scores_gemma":[0.18963116,0.0031873754,0.76719934,0.004661902,0.00017448944,0.0000702093,0.000379326,0.000024489038,0.034671687],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983833,0.000021958445,0.00057937653,0.00030516108,0.00051820045,0.00019199333],"domain_scores_gemma":[0.99549335,0.00010344713,0.0005106478,0.0035109785,0.00028730283,0.00009426654],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000983209,0.00018554956,0.00031385475,0.0018743596,0.00072031363,0.0014447875,0.004175864,0.00008631482,0.00002890416],"category_scores_gemma":[0.000019464916,0.00018163529,0.00013763136,0.00040777866,0.00050003297,0.0043803677,0.0019489146,0.00023124731,0.000060022434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012115596,0.000025135712,0.0010214869,0.000016338314,0.000104889725,7.9138727e-7,0.0009923442,0.0015889556,0.0000013301477,0.68164116,0.00041336368,0.314193],"study_design_scores_gemma":[0.00016886045,0.00001679324,0.002654329,0.00006267005,0.00004829373,0.0000011902348,0.0000043428354,0.8284537,0.000010405855,0.0015084251,0.16684455,0.00022644317],"about_ca_topic_score_codex":0.000014899085,"about_ca_topic_score_gemma":0.000016342201,"teacher_disagreement_score":0.8268648,"about_ca_system_score_codex":0.000096411575,"about_ca_system_score_gemma":0.00020011421,"threshold_uncertainty_score":0.9995918},"labels":[],"label_agreement":null},{"id":"W2594661049","doi":"10.1007/978-981-10-3969-0_49","title":"Database Construction and Map Compilation of Provincial Common Geographic Maps","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Atlas (anatomy); Database; China; Key (lock); Computer science; Geography; Geographic information system; Cartography; Information retrieval; Archaeology; Computer security","score_opus":0.030946208132733893,"score_gpt":0.30895912969861905,"score_spread":0.27801292156588514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594661049","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000093023096,0.00030945463,0.9518547,0.0012050549,0.00016420393,0.0006757254,0.00015705742,0.00011009454,0.04543069],"genre_scores_gemma":[0.05459077,0.002938771,0.9413235,0.00033102577,0.000045919238,0.00006286264,0.00043125867,0.000012190538,0.0002636855],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998445,0.000022885879,0.0006839161,0.0003080789,0.0003826867,0.00015742895],"domain_scores_gemma":[0.99650705,0.00015616452,0.00079703605,0.0020142973,0.0004394855,0.0000859472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006252682,0.0002007917,0.00027643144,0.0008459698,0.00070526346,0.00037811868,0.0021813095,0.00011022183,0.0000017228874],"category_scores_gemma":[0.000022250695,0.00021459995,0.000037963153,0.00016705779,0.0018182024,0.0057849553,0.0022958647,0.0003296716,0.0000057580974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016712473,0.000009857183,0.0001396878,0.000034615172,0.0000028777422,1.237897e-7,0.00015870265,0.000058875907,0.0000078218845,0.7963851,0.000042308853,0.20315833],"study_design_scores_gemma":[0.00062466983,0.00013697767,0.005987367,0.00066344155,0.000019727957,0.0000890585,0.000017857172,0.39279336,0.00008536228,0.41312632,0.18576694,0.0006889158],"about_ca_topic_score_codex":0.00002502259,"about_ca_topic_score_gemma":0.000018734228,"teacher_disagreement_score":0.3927345,"about_ca_system_score_codex":0.00005958786,"about_ca_system_score_gemma":0.00019946102,"threshold_uncertainty_score":0.8751132},"labels":[],"label_agreement":null},{"id":"W26012853","doi":"10.1007/978-3-642-35076-4_5","title":"Green Cooperative Transmission Scheme for Estimate-and-Forward Relay Based Wireless Communication Systems","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Relay; Computer science; Wireless; Cooperative diversity; Relay channel; Transmitter power output; Diversity gain; Computer network; Power (physics); Decoding methods; Electronic engineering; Telecommunications; Real-time computing; Wireless network; Fading; Channel (broadcasting); Engineering; Transmitter","score_opus":0.05578673397327276,"score_gpt":0.31187289997697204,"score_spread":0.25608616600369927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W26012853","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006776223,0.00728652,0.9655489,0.002937898,0.00017772987,0.0013710868,0.000024302368,0.00016982708,0.022415997],"genre_scores_gemma":[0.2094075,0.042305242,0.74352306,0.0018090168,0.00007731405,0.0005510793,0.0004863955,0.00005280361,0.0017876164],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99772364,0.00014837648,0.0009709647,0.00037871674,0.00042186052,0.00035642544],"domain_scores_gemma":[0.9945881,0.0007419867,0.0004981031,0.0029823093,0.0009636101,0.00022593238],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00229265,0.00036854268,0.0004491002,0.00084296963,0.0014250181,0.00090944004,0.0038405575,0.00022258463,0.00000668988],"category_scores_gemma":[0.00004607118,0.00035928635,0.00006675495,0.00051431946,0.000995629,0.0063736755,0.002104327,0.0006025267,0.000018476427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000062610875,0.00002298155,0.000027768623,0.0000557737,0.000009234127,5.9137207e-8,0.0017564682,0.000581979,0.00001529511,0.7189874,0.0001571831,0.2783796],"study_design_scores_gemma":[0.0005089701,0.00005638167,0.00018632137,0.0005061775,0.000010539378,0.000010118798,0.00001966504,0.8364823,0.000014661703,0.0007494351,0.16108632,0.00036910895],"about_ca_topic_score_codex":0.000019641604,"about_ca_topic_score_gemma":0.000015777841,"teacher_disagreement_score":0.8359003,"about_ca_system_score_codex":0.00021129815,"about_ca_system_score_gemma":0.00037230898,"threshold_uncertainty_score":0.9998859},"labels":[],"label_agreement":null},{"id":"W2608504691","doi":"10.1007/978-3-319-57969-6_3","title":"Integrating Factorization Ranked Features in MCTS: An Experimental Study","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ranking (information retrieval); Factorization; Computer science; Tree (set theory); Feature (linguistics); Artificial intelligence; Factor (programming language); Monte Carlo method; Machine learning; Monte Carlo tree search; Statistics; Algorithm; Mathematics","score_opus":0.08026925698930258,"score_gpt":0.37100993813022587,"score_spread":0.2907406811409233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608504691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009427168,0.0008816309,0.6604391,0.0009060073,0.0019981165,0.0032219675,0.000017145969,0.00038483416,0.32272407],"genre_scores_gemma":[0.95546067,0.00019318389,0.04367478,0.00019419164,0.000036025314,0.00004223099,0.000025921921,0.000008351712,0.00036467283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806345,0.000071519215,0.00076516985,0.00037273575,0.0004997646,0.00022737675],"domain_scores_gemma":[0.9962202,0.00014974829,0.0004547459,0.0027880387,0.00029860044,0.000088678025],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001149455,0.00024319915,0.00026759907,0.0010168754,0.0007100203,0.0016846111,0.00533153,0.00012138139,0.0000056517865],"category_scores_gemma":[0.0001073657,0.0002382878,0.000030012203,0.00022376559,0.0007009718,0.014622723,0.0022787713,0.00051219674,0.00002141784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000642901,0.00023188535,0.0012869396,0.000010993323,0.0000064966266,0.0000019254112,0.05997856,0.00044085106,0.00003319706,0.62634957,0.00004931845,0.3116038],"study_design_scores_gemma":[0.0007751269,0.0008608783,0.015837438,0.00065741845,0.0000087931785,0.000031877884,0.003359761,0.9350763,0.00057931565,0.024216529,0.017232552,0.001363989],"about_ca_topic_score_codex":0.00012793651,"about_ca_topic_score_gemma":0.00027929025,"teacher_disagreement_score":0.9460335,"about_ca_system_score_codex":0.0002226254,"about_ca_system_score_gemma":0.00022690483,"threshold_uncertainty_score":0.99935174},"labels":[],"label_agreement":null},{"id":"W2612097007","doi":"10.1007/978-3-319-58753-0_89","title":"The Rise and Proliferation of Live-Streaming in China: Insights and Lessons","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Games and Media","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"China; Live streaming; Liberian dollar; The Internet; Phenomenon; Us dollar; Social media; Business; Advertising; Geography; Computer science; World Wide Web; Multimedia; Physics","score_opus":0.04126502768756149,"score_gpt":0.32714787648335464,"score_spread":0.2858828487957932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612097007","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009289848,0.003435484,0.00037843917,0.002976261,0.00018471853,0.00055778294,0.000009582096,0.0000149503085,0.9831529],"genre_scores_gemma":[0.9453257,0.04800008,0.0018084672,0.00006754643,0.000031541218,0.00001685985,0.000007800174,0.0000037304083,0.0047382847],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993063,0.000025244179,0.00027965225,0.00009010501,0.00019879697,0.000099873374],"domain_scores_gemma":[0.9989655,0.00017154084,0.0002340205,0.00045488955,0.0001215061,0.000052536117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087109086,0.00007298579,0.000116133546,0.00021068238,0.0006377325,0.00051552185,0.00059268705,0.000063116306,6.222424e-7],"category_scores_gemma":[0.000142,0.00005772746,0.000010510431,0.00006068351,0.0025234607,0.00276789,0.000499611,0.00015486247,0.0000011653852],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011690261,0.000003871254,0.00029934457,0.000008282825,9.622107e-7,4.359476e-8,0.023941742,0.0000028439836,2.9609333e-7,0.40144387,0.000008817508,0.5742887],"study_design_scores_gemma":[0.00028521998,0.000041792257,0.045625295,0.0004670166,0.0000056868407,0.0000025846991,0.0010396733,0.016899921,0.0000022349832,0.014978197,0.9204637,0.00018866715],"about_ca_topic_score_codex":0.000092787355,"about_ca_topic_score_gemma":0.0015165512,"teacher_disagreement_score":0.97841465,"about_ca_system_score_codex":0.000034576406,"about_ca_system_score_gemma":0.0001957816,"threshold_uncertainty_score":0.9297796},"labels":[],"label_agreement":null},{"id":"W2617180419","doi":"10.1007/978-3-319-66302-9_2","title":"Using Workflows to Automate Activities in MDE Tools","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Workflow; Computer science; Software engineering; Programming language; Information retrieval; Natural language processing; Database","score_opus":0.35146077925472646,"score_gpt":0.44752962386453055,"score_spread":0.09606884460980408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2617180419","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072476887,0.0002056895,0.16777556,0.0019745084,0.002292903,0.0011761349,0.000105129,0.00012158564,0.8191008],"genre_scores_gemma":[0.5059688,0.0009509125,0.45250738,0.003570397,0.0002221689,0.00007054266,0.000141177,0.00003958321,0.036529053],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99685836,0.000057435504,0.0010816753,0.00049660605,0.001211446,0.00029449209],"domain_scores_gemma":[0.99343354,0.00075070927,0.0005489694,0.004849378,0.00029356516,0.00012382293],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.007844896,0.00020079613,0.00033735775,0.0028359422,0.00086747797,0.004746604,0.0061580213,0.00008433823,0.000030784406],"category_scores_gemma":[0.00086415675,0.0001822042,0.00004790525,0.0005713364,0.0008401752,0.008642059,0.0064943973,0.0003077538,0.00018522743],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000428478,0.000013474231,0.00024591677,0.0000075522503,0.0000025268344,8.5549965e-7,0.0027748856,0.0049799015,0.0000028700715,0.065633155,0.0013667166,0.9249679],"study_design_scores_gemma":[0.00016795368,0.000018095416,0.0058811135,0.0003439314,0.0000030388283,0.000006649364,0.00011403719,0.50511163,0.0000026477594,0.010929843,0.47713852,0.00028255454],"about_ca_topic_score_codex":0.000047851383,"about_ca_topic_score_gemma":0.00011899117,"teacher_disagreement_score":0.9246853,"about_ca_system_score_codex":0.00020129175,"about_ca_system_score_gemma":0.00027786585,"threshold_uncertainty_score":0.9992191},"labels":[],"label_agreement":null},{"id":"W2644882662","doi":"10.1007/978-981-10-5421-1_2","title":"Security Analysis of a Design Variant of Randomized Hashing","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Random oracle; Hash function; Universal hashing; Computer science; Theoretical computer science; Ideal (ethics); Block cipher; Scheme (mathematics); Encryption; Discrete mathematics; Algorithm; Mathematics; Cryptography; Computer security; Double hashing; Cryptographic hash function; Public-key cryptography","score_opus":0.05787759745006473,"score_gpt":0.3294114474565487,"score_spread":0.271533850006484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2644882662","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000743951,0.00021956842,0.9610029,0.00022114173,0.00009463284,0.00046966656,0.00002836344,0.000018478326,0.037870865],"genre_scores_gemma":[0.6303102,0.0036828665,0.36566606,0.0001475484,0.000009231602,0.000035737394,0.0000675082,0.0000051085945,0.000075756856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997874,0.00010695171,0.001193038,0.00020328206,0.00047795498,0.00014474985],"domain_scores_gemma":[0.9945721,0.00075699965,0.0013415756,0.0026157696,0.00065564626,0.000057904577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047064563,0.00015627789,0.00076627854,0.0026569972,0.00037450992,0.00035818567,0.0035278518,0.000082757935,0.000009862986],"category_scores_gemma":[0.00015567249,0.00014586968,0.00019939763,0.00067107996,0.0016107465,0.0040225536,0.0017134727,0.00021674862,0.0000011807357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033164324,0.00001810836,0.000019775991,0.000020979247,0.00011305896,1.5461538e-7,0.005741186,0.00043215544,0.0000013315279,0.96831065,0.000016229622,0.025293225],"study_design_scores_gemma":[0.003622459,0.000028501834,0.00045315232,0.00011217201,0.00015719923,0.0000036582467,0.000022009768,0.94787675,0.000011609535,0.04525263,0.0022831229,0.00017671459],"about_ca_topic_score_codex":0.00009884784,"about_ca_topic_score_gemma":0.00003642256,"teacher_disagreement_score":0.9474446,"about_ca_system_score_codex":0.00003738584,"about_ca_system_score_gemma":0.00028141384,"threshold_uncertainty_score":0.6555685},"labels":[],"label_agreement":null},{"id":"W26774929","doi":"10.1007/978-3-642-21233-8_4","title":"Evaluation of Software Process Assessment Methods – Case Study","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Implementation; Process (computing); Software; Set (abstract data type); Evaluation methods; Software implementation; Software engineering; Reliability engineering; Engineering","score_opus":0.1674171664530736,"score_gpt":0.46246089928628353,"score_spread":0.29504373283320995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W26774929","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002443527,0.00023708594,0.96786237,0.000042813303,0.0001802577,0.0007210384,0.0000029713365,0.00013497387,0.030574158],"genre_scores_gemma":[0.14058597,0.0002442381,0.8589891,0.00004663572,0.000008130125,0.00007984058,0.0000048562533,0.0000060082843,0.00003519074],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997985,0.00017023987,0.0006660873,0.00024020973,0.0008072662,0.00013120072],"domain_scores_gemma":[0.9952943,0.00041929074,0.00053040124,0.0021204697,0.0015764863,0.00005905383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009749904,0.00017436987,0.00023302811,0.0008534733,0.00023681963,0.00024370434,0.0023946834,0.00008739232,0.00000965455],"category_scores_gemma":[0.00020584889,0.00017005073,0.000030892657,0.00043265315,0.00027072016,0.006219519,0.001554588,0.00035734003,0.000002449229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.245725e-7,0.000051502775,0.000120556615,0.00002862964,0.000012381637,0.0000019647111,0.0053869174,0.00040593752,2.523498e-7,0.0590477,0.000010895394,0.9349327],"study_design_scores_gemma":[0.00047336196,0.0003224879,0.0016194907,0.00022015013,0.00009133946,0.00048351032,0.00021708882,0.9411206,0.000022970935,0.047187682,0.007747031,0.0004942786],"about_ca_topic_score_codex":0.00005157609,"about_ca_topic_score_gemma":0.00000916269,"teacher_disagreement_score":0.94071466,"about_ca_system_score_codex":0.00013320717,"about_ca_system_score_gemma":0.0006196128,"threshold_uncertainty_score":0.6934467},"labels":[],"label_agreement":null},{"id":"W2736526444","doi":"10.1007/978-981-10-5780-9","title":"Advanced Informatics for Computing Research","year":2017,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Computer science; Informatics; Data science; World Wide Web; Library science; Political science; Law","score_opus":0.12218892638361444,"score_gpt":0.42299584633777076,"score_spread":0.3008069199541563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736526444","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015965454,0.00017841242,0.86080664,0.00094371865,0.00028353525,0.000838839,0.000050713978,0.00009503649,0.13678715],"genre_scores_gemma":[0.0012506021,0.0010010365,0.99374616,0.00039531308,0.00007394796,0.0001422424,0.0002242103,0.000009631354,0.0031568338],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977501,0.000040146333,0.0008535524,0.00028451873,0.0006205508,0.00045111158],"domain_scores_gemma":[0.9929069,0.0007768216,0.0005551079,0.0044692405,0.0011582989,0.00013362012],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.004329676,0.00020030262,0.0002792484,0.0012128283,0.0024419972,0.0025043776,0.0095683215,0.00013580016,6.9136274e-7],"category_scores_gemma":[0.00027180702,0.0002057372,0.000045357443,0.00065444555,0.0014189148,0.011505838,0.005969302,0.0006367193,0.000048515874],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.726178e-7,0.000012289333,0.0000032778773,0.000045817782,0.0000023987438,4.582998e-8,0.0021301627,0.00008053991,5.2937276e-7,0.2974243,0.0044724485,0.69582754],"study_design_scores_gemma":[0.00020350386,0.000036193604,0.00013466783,0.00017732091,0.0000014785569,0.000006130693,0.000038071463,0.5625597,0.0000030432932,0.006765557,0.4299156,0.00015870859],"about_ca_topic_score_codex":0.0000077617,"about_ca_topic_score_gemma":0.0000053303884,"teacher_disagreement_score":0.6956688,"about_ca_system_score_codex":0.0002650895,"about_ca_system_score_gemma":0.0012525723,"threshold_uncertainty_score":0.99885666},"labels":[],"label_agreement":null},{"id":"W2738756939","doi":"10.1007/978-981-10-5427-3","title":"Advances in Computing and Data Sciences","year":2017,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Information retrieval; Data science","score_opus":0.3816037324148056,"score_gpt":0.48544327055234704,"score_spread":0.10383953813754143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738756939","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008385393,0.011828028,0.102709435,0.010458433,0.00061304134,0.0013728886,0.00046234397,0.0001712999,0.871546],"genre_scores_gemma":[0.39109966,0.14621194,0.45486352,0.0025925764,0.00021634749,0.00009156424,0.00091635727,0.000030113546,0.003977915],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972658,0.00005446207,0.00096377666,0.0006199885,0.000830554,0.00026542434],"domain_scores_gemma":[0.9919939,0.001177608,0.00071809726,0.005798197,0.00024605662,0.000066113826],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["sts","scholarly_communication","open_science"],"category_scores_codex":[0.007514168,0.00017262608,0.00031804928,0.0015093352,0.0014395156,0.0022704247,0.014925385,0.00013079194,0.0000040277137],"category_scores_gemma":[0.0014108978,0.0001431058,0.000015424015,0.0010929186,0.005691566,0.016135205,0.015353404,0.00047265063,0.000034337714],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.268758e-7,0.000008843449,0.0009268496,0.000007882856,4.568463e-7,1.2085847e-7,0.00025881952,0.000060793933,2.4363533e-7,0.10082075,0.0019801047,0.8959345],"study_design_scores_gemma":[0.00014568018,0.000019252213,0.0062961658,0.0001668004,0.0000018121699,0.000011554049,0.00017091067,0.29748282,6.0136034e-7,0.046613324,0.64890426,0.00018682187],"about_ca_topic_score_codex":0.000026298829,"about_ca_topic_score_gemma":0.00016838618,"teacher_disagreement_score":0.89574766,"about_ca_system_score_codex":0.000074049676,"about_ca_system_score_gemma":0.0005566854,"threshold_uncertainty_score":0.99986047},"labels":[],"label_agreement":null},{"id":"W2740236408","doi":"10.1007/978-3-319-65172-9_44","title":"Machine Vision for Coin Recognition with ANNs: Effect of Training and Testing Parameters","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Currency Recognition and Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Task (project management); Artificial intelligence; Artificial neural network; Cognitive neuroscience of visual object recognition; Set (abstract data type); Segmentation; Pattern recognition (psychology); Object (grammar); Machine learning; Training set; Engineering","score_opus":0.1031899970968408,"score_gpt":0.32765766531948254,"score_spread":0.22446766822264175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2740236408","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020999536,0.0004775802,0.9134764,0.00034030073,0.0003660419,0.0015639073,0.00007740535,0.00013300245,0.081465416],"genre_scores_gemma":[0.39849937,0.001371982,0.59935075,0.0002579251,0.000033471384,0.00013037422,0.0001609022,0.000017461169,0.00017777969],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989093,0.000032268617,0.00044087393,0.00023857938,0.00023609506,0.0001428724],"domain_scores_gemma":[0.99739856,0.0007119551,0.00054937124,0.0008813389,0.00039169795,0.00006708814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013226602,0.00017396527,0.00026816613,0.00065058575,0.00053457025,0.00044897306,0.00089408224,0.000081973674,7.657105e-7],"category_scores_gemma":[0.0001943246,0.00014946682,0.000030584248,0.0001518224,0.0006759468,0.004505577,0.0004991838,0.00021673046,0.0000027335657],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011011561,0.0000053609233,0.000040981715,0.000075035765,0.000003876482,8.600004e-8,0.00069639954,0.00001828853,0.000007071407,0.0051168427,0.00000846296,0.9940166],"study_design_scores_gemma":[0.0015008226,0.0015974479,0.001133596,0.0016363758,0.00002605676,0.000107040774,0.000018576853,0.97421175,0.00016512659,0.010956811,0.008200422,0.00044597068],"about_ca_topic_score_codex":0.000013773564,"about_ca_topic_score_gemma":0.00001332927,"teacher_disagreement_score":0.9935706,"about_ca_system_score_codex":0.00003663277,"about_ca_system_score_gemma":0.000109093606,"threshold_uncertainty_score":0.60950804},"labels":[],"label_agreement":null},{"id":"W2748590498","doi":"10.1007/978-3-319-66562-7_21","title":"PISCIS: A Constraint-Based Planner for Self-adaptive Systems","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Adaptation (eye); Context (archaeology); Constraint (computer-aided design); Set (abstract data type); Planner; Executor; IBM; Software; Data mining; Artificial intelligence; Operating system; Engineering; Programming language","score_opus":0.09139900268376915,"score_gpt":0.3288732532619665,"score_spread":0.23747425057819732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748590498","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.629807e-7,0.00036945796,0.97164977,0.0002750115,0.0006125502,0.0006265381,0.00003968517,0.000287482,0.026138533],"genre_scores_gemma":[0.002940774,0.00029314982,0.995998,0.00020116447,0.00003254326,0.00010716404,0.000025089572,0.000009221141,0.0003928446],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854356,0.000034003486,0.00053402566,0.0003093674,0.0003147296,0.00026433484],"domain_scores_gemma":[0.99500024,0.0012184297,0.0004779031,0.0027187217,0.0004950456,0.000089655085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016358579,0.00024367514,0.00032189878,0.0007186554,0.0006503756,0.0008284727,0.0044385204,0.00014700316,4.5406483e-7],"category_scores_gemma":[0.00025373828,0.00023880186,0.00005299202,0.00010741924,0.00088074495,0.004920197,0.0013222079,0.00033128823,0.000011288613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000299123,0.000008132921,0.0000026889024,0.00005909756,0.000008364019,4.000051e-7,0.00072133885,0.01549377,8.3719056e-7,0.8847437,0.00012863359,0.09883007],"study_design_scores_gemma":[0.00036113468,0.00008762154,0.000061230254,0.00027183935,0.000005864222,0.000017499086,0.000015105122,0.8924627,0.0000069688153,0.017512387,0.088842615,0.00035503603],"about_ca_topic_score_codex":0.000004350758,"about_ca_topic_score_gemma":0.0000015262644,"teacher_disagreement_score":0.8769689,"about_ca_system_score_codex":0.00017965853,"about_ca_system_score_gemma":0.0004763508,"threshold_uncertainty_score":0.9738057},"labels":[],"label_agreement":null},{"id":"W2762364077","doi":"10.1007/978-981-10-6544-6_32","title":"Fault Tolerant Control, Artificial Intelligence and Predictive Analytics for Aerospace Systems: An Overview","year":2017,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Prognostics; Aerospace; Fault tolerance; Computer science; Analytics; Spacecraft; Predictive analytics; Fault (geology); Artificial intelligence; Engineering; Aerospace engineering; Data mining; Machine learning; Distributed computing","score_opus":0.07984969869934035,"score_gpt":0.31563981923460804,"score_spread":0.2357901205352677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762364077","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000086495646,0.0045732553,0.964621,0.00020686095,0.0009134715,0.0013991483,0.00022566704,0.0001461876,0.027827889],"genre_scores_gemma":[0.9883772,0.0069740005,0.0036068268,0.0001686443,0.0001381366,0.00016049258,0.000074580705,0.000022246366,0.00047788743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889475,0.000017793207,0.00056815165,0.00015727547,0.00020381805,0.00015819576],"domain_scores_gemma":[0.99825567,0.00013164796,0.00020567217,0.0010253428,0.0002847546,0.000096894466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007298728,0.00018271244,0.00030463547,0.00033593792,0.00044766933,0.00071139087,0.00077225047,0.00012820774,0.0000013507486],"category_scores_gemma":[0.000035439,0.00018115989,0.00003383544,0.000061715364,0.00044686437,0.0024233032,0.00015189628,0.000227415,0.0000065934396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031364572,0.000019106366,0.000015947273,0.00046537432,0.00006011121,3.2867771e-7,0.0028902206,0.1546431,0.000014776082,0.50876415,0.0001701268,0.3329254],"study_design_scores_gemma":[0.00013984114,0.000068802576,0.00006650097,0.00024601305,0.000015414354,0.000009934769,0.000087149376,0.9516811,0.000002555011,0.0012853164,0.046217225,0.00018018491],"about_ca_topic_score_codex":0.00001597051,"about_ca_topic_score_gemma":0.00004076845,"teacher_disagreement_score":0.98829067,"about_ca_system_score_codex":0.00009620409,"about_ca_system_score_gemma":0.000058684018,"threshold_uncertainty_score":0.7387486},"labels":[],"label_agreement":null},{"id":"W2781339187","doi":"10.1007/978-3-030-25109-3_11","title":"Managing Cybersecurity Break-ins Using Bluetooth Low Energy Devices to Verify Attackers: A Practical Study","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Computer science; Server; Computer security; Encryption; Operating system; Bluetooth; Botnet; Arduino; Bluetooth Low Energy; Embedded system; Raspberry pi; Computer network; The Internet; Wireless; Internet of Things","score_opus":0.05299509691527382,"score_gpt":0.32945785577204456,"score_spread":0.27646275885677074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781339187","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001350524,0.00048411594,0.9009528,0.0055036494,0.0005255494,0.001253017,0.000016730753,0.0005474993,0.08936607],"genre_scores_gemma":[0.646305,0.0023109596,0.3468791,0.0038232973,0.000046978996,0.00006929556,0.000037298956,0.00003074726,0.0004972899],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99733096,0.00009518345,0.00091940997,0.0005405155,0.0007019027,0.00041203154],"domain_scores_gemma":[0.9931925,0.00036803202,0.00053136307,0.0052196835,0.00051459705,0.00017383693],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0012372474,0.0003660316,0.00044287235,0.0017395556,0.0007164586,0.0013866774,0.0067489976,0.00021042177,0.000005350932],"category_scores_gemma":[0.00008514855,0.0003778453,0.00006407371,0.0010813379,0.00067824055,0.009189507,0.00911784,0.00071714225,0.000078419056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005638704,0.00010778162,0.00021477003,0.000038250622,0.000020196232,0.000001700604,0.0037798004,0.00091700826,0.0000030590825,0.8250448,0.00024494863,0.16962203],"study_design_scores_gemma":[0.00053491606,0.00022026415,0.0011670053,0.0004574745,0.00001865937,0.000048878195,0.0005061371,0.84105027,0.000023586292,0.005674212,0.14947537,0.00082324987],"about_ca_topic_score_codex":0.00013494701,"about_ca_topic_score_gemma":0.00016208377,"teacher_disagreement_score":0.84013325,"about_ca_system_score_codex":0.0002936004,"about_ca_system_score_gemma":0.0006831879,"threshold_uncertainty_score":0.9998673},"labels":[],"label_agreement":null},{"id":"W2781488941","doi":"10.1007/978-981-10-7796-8_2","title":"An Empirical Study of the Software Development Process, Including Its Requirements Engineering, at Very Large Organization: How to Use Data Mining in Such a Study","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Process (computing); Computer science; Software; Empirical research; Focus (optics); Data science; Software engineering","score_opus":0.15903600506905624,"score_gpt":0.379249727736557,"score_spread":0.22021372266750078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781488941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7480632,0.000039629213,0.2488489,0.00019943637,0.00034293425,0.0022326452,0.000018414734,0.00016880497,0.000086017266],"genre_scores_gemma":[0.93810314,0.000014455719,0.061616488,0.0000874779,0.000014119201,0.00003650251,0.000034819455,0.000013564247,0.00007944959],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99755305,0.000059153994,0.0006597818,0.0004525279,0.0009948427,0.00028064518],"domain_scores_gemma":[0.99477154,0.00037526942,0.00022125969,0.0037308803,0.0007955751,0.0001054975],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0020868946,0.00021319339,0.00024206037,0.0010091431,0.00047919495,0.0006062973,0.007954756,0.00007100488,0.000003792159],"category_scores_gemma":[0.0011976177,0.00019248783,0.00000935295,0.0018414643,0.000103506434,0.0071493024,0.014140453,0.00029186567,0.0000073998826],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007733017,0.0007897602,0.77651757,0.00014089237,0.00003856724,0.0000026553053,0.20405565,0.0047586593,0.000007320182,0.0004843212,0.0004050452,0.012791856],"study_design_scores_gemma":[0.0009381491,0.0003422752,0.64882773,0.00055188045,0.000007839972,0.000010445959,0.00071657734,0.34161448,0.000037796155,0.00001173667,0.0063891485,0.000551946],"about_ca_topic_score_codex":0.0000051367565,"about_ca_topic_score_gemma":0.0000935379,"teacher_disagreement_score":0.3368558,"about_ca_system_score_codex":0.0003562261,"about_ca_system_score_gemma":0.000482138,"threshold_uncertainty_score":0.9974127},"labels":[],"label_agreement":null},{"id":"W2803308433","doi":"10.1007/978-3-319-91476-3_59","title":"Modes of Sequential Three-Way Classifications","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Thesaurus; Information retrieval; Natural language processing","score_opus":0.09055087287090444,"score_gpt":0.30339387048640243,"score_spread":0.212842997615498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803308433","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005191124,0.00017073199,0.69124216,0.0005308384,0.00018107623,0.00024400104,0.00001655754,0.000055248212,0.3075075],"genre_scores_gemma":[0.25022605,0.0020686174,0.74621093,0.00061984686,0.00008011945,0.000033395892,0.00007175063,0.000011961003,0.0006773173],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983423,0.000022299311,0.00073215686,0.00026696827,0.0004298352,0.00020645314],"domain_scores_gemma":[0.99616724,0.00012496115,0.00045323366,0.0026342566,0.00053658604,0.0000837123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088563183,0.00018284185,0.0002426231,0.00081321975,0.00038794245,0.0003893911,0.0041923886,0.00012797225,0.000019713325],"category_scores_gemma":[0.000023453016,0.00017029567,0.000055556986,0.00044412888,0.0017266789,0.004704371,0.0023770141,0.00026715087,0.0000689797],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.015047e-7,0.000012494458,0.000012494635,0.000013789547,0.000004058296,7.821335e-8,0.00080023095,0.000101488156,0.000005863479,0.8785014,0.00023596438,0.12031123],"study_design_scores_gemma":[0.00017303498,0.00006846402,0.0006274524,0.00011197811,0.0000056748163,0.0000118045455,0.000015285466,0.85333014,0.000020874028,0.09088264,0.054504473,0.00024819735],"about_ca_topic_score_codex":0.000013870711,"about_ca_topic_score_gemma":0.000020003172,"teacher_disagreement_score":0.8532286,"about_ca_system_score_codex":0.00008097069,"about_ca_system_score_gemma":0.00029239935,"threshold_uncertainty_score":0.7790571},"labels":[],"label_agreement":null},{"id":"W2803892568","doi":"10.1007/978-3-319-91479-4_59","title":"Clustering of Propositions Equipped with Uncertainty","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Correctness; Cluster analysis; Social connectedness; Data mining; Consistency (knowledge bases); Graph; External Data Representation; Uncertain data; Information retrieval; Representation (politics); Theoretical computer science; Machine learning; Artificial intelligence; Algorithm","score_opus":0.03920596644374087,"score_gpt":0.28875485140283674,"score_spread":0.24954888495909588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803892568","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013366606,0.00014740408,0.8242956,0.00050203706,0.00013422876,0.00028876314,0.000006296248,0.00007229554,0.17441975],"genre_scores_gemma":[0.13803746,0.0010651253,0.8587512,0.0006564626,0.000040364546,0.000030612915,0.00003409334,0.000009881244,0.001374853],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880123,0.000017659673,0.00047861168,0.00019665883,0.00033544877,0.00017036597],"domain_scores_gemma":[0.9972364,0.0001297924,0.00031805114,0.0017733044,0.000489352,0.000053155803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054171693,0.00015058697,0.00021681757,0.0006259765,0.00028546425,0.00026217423,0.0026850158,0.0000751314,0.000008219988],"category_scores_gemma":[0.000021591204,0.00012373243,0.000026320682,0.00034127053,0.0015924919,0.0036862635,0.0020498314,0.0001876415,0.000017877901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009989039,0.000031702944,0.000107775624,0.000101975274,0.000017116192,7.9857864e-7,0.006517448,0.0012518797,0.000011960627,0.8511043,0.0003138926,0.14053115],"study_design_scores_gemma":[0.00041432586,0.00029433458,0.0015052875,0.0006486682,0.0000104408655,0.000063198124,0.000082176666,0.9584945,0.000042923242,0.012864095,0.025196701,0.00038338912],"about_ca_topic_score_codex":0.000018724906,"about_ca_topic_score_gemma":0.000045688164,"teacher_disagreement_score":0.9572426,"about_ca_system_score_codex":0.000067325425,"about_ca_system_score_gemma":0.0002939396,"threshold_uncertainty_score":0.5867603},"labels":[],"label_agreement":null},{"id":"W2804489692","doi":"10.1007/978-3-319-91476-3_60","title":"Determining Strategies in Game-Theoretic Shadowed Sets","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Set (abstract data type); Repetition (rhetorical device); Computer science; Mathematics; Repeated game; Game theory; Value (mathematics); Mathematical economics; Statistics","score_opus":0.10872826559506611,"score_gpt":0.39558064607791804,"score_spread":0.28685238048285194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804489692","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005984804,0.00018155042,0.13831815,0.0011424716,0.00041961903,0.00074046635,0.00004027332,0.000096658085,0.853076],"genre_scores_gemma":[0.9721994,0.00080655183,0.022408629,0.00087720744,0.000059217447,0.00006622872,0.00004322078,0.000013931908,0.003525661],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99725217,0.00008782621,0.0012905713,0.00037366137,0.0007594334,0.00023633725],"domain_scores_gemma":[0.99557155,0.0009176421,0.0005784178,0.0022783885,0.0005529445,0.000101068414],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00426853,0.00021248862,0.00030477985,0.001765833,0.00044090438,0.0011341805,0.0032753635,0.00015017731,0.00028085537],"category_scores_gemma":[0.00030959732,0.00019047041,0.000051172356,0.00089747825,0.0029440913,0.0062062787,0.0014001713,0.00042550632,0.0005641548],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003773339,0.000011116909,0.00009001332,0.000005405367,0.0000014965713,2.3532719e-7,0.0044485847,0.00027169386,0.0000020710402,0.86040646,0.00022311948,0.13453601],"study_design_scores_gemma":[0.0002735492,0.00005081525,0.002981215,0.0001683849,0.0000043193477,0.000026783424,0.00095815636,0.12909888,0.000007799872,0.72916627,0.13693154,0.00033226126],"about_ca_topic_score_codex":0.0000040412865,"about_ca_topic_score_gemma":0.000032925578,"teacher_disagreement_score":0.96621454,"about_ca_system_score_codex":0.00010476933,"about_ca_system_score_gemma":0.00036189397,"threshold_uncertainty_score":0.9999027},"labels":[],"label_agreement":null},{"id":"W2805637342","doi":"10.1007/978-981-10-8660-1_7","title":"Sparse Channel Estimation Based on Compressive Sensing with Overcomplete Dictionaries in OFDM Communication Systems","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Compressed sensing; Channel (broadcasting); Computer science; Orthogonal frequency-division multiplexing; Baseband; Algorithm; Signal recovery; Multipath propagation; SIGNAL (programming language); Telecommunications; Bandwidth (computing)","score_opus":0.032081127489619325,"score_gpt":0.2499525097593168,"score_spread":0.21787138226969746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805637342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020528971,0.0008263629,0.7406841,0.00039373498,0.00058482116,0.0016476768,0.00006753146,0.0008212752,0.2529216],"genre_scores_gemma":[0.94094706,0.00088970276,0.05745552,0.00027463955,0.000033165015,0.000029370274,0.00024300392,0.000030006151,0.00009751975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860674,0.000046218553,0.00058398565,0.000191413,0.00037168854,0.00019993715],"domain_scores_gemma":[0.99753463,0.00025165602,0.00024155005,0.0015792279,0.0003366615,0.000056243614],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046202922,0.00026926838,0.0003033264,0.0011732199,0.00033911646,0.0003624971,0.0007734288,0.00013680378,0.0000041374733],"category_scores_gemma":[0.00001986295,0.00026751086,0.000024609784,0.00032468987,0.0008953684,0.0019032105,0.00030899612,0.0004553357,0.000017720262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029602475,0.000024589473,0.00003305615,0.000070774106,0.000014497931,0.0000014520557,0.0022282607,0.923152,0.0000084670155,0.051236693,0.001048315,0.022152273],"study_design_scores_gemma":[0.00027659998,0.0000607092,0.0004697668,0.001758447,0.0000071003415,0.000014488211,0.000042927506,0.98623955,0.000027986753,0.0017184891,0.009102667,0.00028126812],"about_ca_topic_score_codex":0.000052361862,"about_ca_topic_score_gemma":0.00004739819,"teacher_disagreement_score":0.93889415,"about_ca_system_score_codex":0.00025660585,"about_ca_system_score_gemma":0.00008652209,"threshold_uncertainty_score":0.9999777},"labels":[],"label_agreement":null},{"id":"W2806023047","doi":"10.1007/978-3-319-93354-2_10","title":"Directional Distance-Bounding Identification","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Identification (biology); Bounding overwatch; Computer science; Information retrieval; Artificial intelligence; Biology; Botany","score_opus":0.034449012851772716,"score_gpt":0.2910843220941728,"score_spread":0.2566353092424001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806023047","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003462731,0.00028137516,0.86040217,0.0004331023,0.0006074834,0.00021138231,0.000033299384,0.00011374308,0.13788284],"genre_scores_gemma":[0.14020625,0.012712877,0.84090734,0.002153642,0.00046309238,0.0001319802,0.0008040409,0.00003416087,0.0025866453],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99827856,0.000025261917,0.00064804207,0.0003400055,0.0005034066,0.00020471646],"domain_scores_gemma":[0.9966236,0.00018029993,0.00036465618,0.002298332,0.00043737362,0.000095741336],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012775887,0.00018469845,0.00017499502,0.0010436666,0.0008078308,0.0012524263,0.0033502528,0.00010542121,0.00002371194],"category_scores_gemma":[0.000054479642,0.00019528354,0.000050256225,0.00064252847,0.001300999,0.011170053,0.002007965,0.00031624708,0.000117075884],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001114994,0.000009759133,0.000029433852,0.000011512639,0.0000029531607,9.982106e-8,0.0011642604,0.000005568694,0.000002894302,0.9244624,0.0005533918,0.07375663],"study_design_scores_gemma":[0.00019103884,0.00003389831,0.0019919982,0.00016161615,0.0000052752125,0.0000242473,0.00001882412,0.12686388,0.000023185588,0.14735243,0.72294986,0.00038376357],"about_ca_topic_score_codex":0.000006898992,"about_ca_topic_score_gemma":0.000020934549,"teacher_disagreement_score":0.77711,"about_ca_system_score_codex":0.00013794696,"about_ca_system_score_gemma":0.00019768387,"threshold_uncertainty_score":0.99978435},"labels":[],"label_agreement":null},{"id":"W2807200023","doi":"10.1007/978-3-319-92279-9_19","title":"ABLE: An Arts-Based, Interactive Physical Therapy Platform for Seniors with Dementia and Frailty","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Dementia; The arts; Gerontology; Computer science; Medicine; World Wide Web; Physical medicine and rehabilitation; Art; Visual arts; Internal medicine","score_opus":0.05682272561119397,"score_gpt":0.36472808892122693,"score_spread":0.307905363310033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807200023","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4061371,0.0012587318,0.3258757,0.003954377,0.0009151576,0.0076695485,0.00026040003,0.00029523572,0.25363377],"genre_scores_gemma":[0.7837577,0.0017222092,0.20901944,0.0035222305,0.00021929937,0.00017099401,0.00047452026,0.000032864293,0.0010807446],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920684,0.00000775259,0.00027467977,0.00016693679,0.0002153175,0.00012847426],"domain_scores_gemma":[0.9983455,0.00028921882,0.00017296603,0.0006592171,0.0004412251,0.00009189766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000352606,0.00014645178,0.00021399891,0.00043582925,0.00027712088,0.00013864887,0.00026391595,0.00006746216,0.000016029964],"category_scores_gemma":[0.000023708062,0.000108655375,0.000034627403,0.00011386783,0.0010546804,0.002149655,0.00013507604,0.00019528826,0.0000055463343],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067892944,0.00030409486,0.0023590918,0.0002664032,0.0001344356,3.985268e-7,0.018338894,0.00013049916,0.0000668732,0.07170684,0.0007966717,0.9052169],"study_design_scores_gemma":[0.0048432364,0.0036362542,0.023502441,0.0010898425,0.00008064543,0.00005473101,0.0007352406,0.48720047,0.00022862125,0.004212778,0.47380164,0.0006141192],"about_ca_topic_score_codex":0.0000044073154,"about_ca_topic_score_gemma":0.000007923908,"teacher_disagreement_score":0.90460277,"about_ca_system_score_codex":0.00006401462,"about_ca_system_score_gemma":0.00024066961,"threshold_uncertainty_score":0.44308376},"labels":[],"label_agreement":null},{"id":"W2810996379","doi":"10.1007/978-3-319-94767-9_12","title":"Optimizing Combination Warranty Policies Using Remanufactured Replacement Products from the Seller and Buyer’s Perspectives","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Warranty; Sustainability; Point (geometry); Computer science; Business; Legislation; Forcing (mathematics); Remanufacturing; Risk analysis (engineering); Operations research; Process management; Manufacturing engineering; Engineering; Mathematics","score_opus":0.028858255170756134,"score_gpt":0.2569140219840273,"score_spread":0.22805576681327117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810996379","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043556027,0.010150104,0.7451709,0.009037423,0.0020713178,0.0046428917,0.00015567896,0.0007030784,0.1845126],"genre_scores_gemma":[0.6877384,0.034171514,0.2759849,0.0007810627,0.0002194227,0.000045476805,0.00027209957,0.000045698136,0.0007413956],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991253,0.000020919058,0.00036014416,0.00016664782,0.00019682435,0.00013013757],"domain_scores_gemma":[0.9985203,0.00010797232,0.00012779735,0.0008779039,0.00033413857,0.000031853077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057954586,0.00015510581,0.0001476567,0.00021531037,0.00044586553,0.0003048313,0.0004990625,0.00008136808,0.0000107521755],"category_scores_gemma":[0.000056309094,0.00012720443,0.000014214886,0.00015518175,0.00083627546,0.0020600366,0.00039364686,0.00023135729,0.000004155224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000593158,0.00009091075,0.00016071212,0.00036501186,0.00013656978,2.7862865e-7,0.3926005,0.27835238,0.00031229292,0.23816425,0.005058596,0.08469918],"study_design_scores_gemma":[0.00023112194,0.000029981327,0.00068117987,0.00023241647,0.0000128554575,0.000004805771,0.0008126313,0.9668064,0.000071340786,0.002834823,0.028064301,0.00021811218],"about_ca_topic_score_codex":0.00003622821,"about_ca_topic_score_gemma":0.0000135128785,"teacher_disagreement_score":0.68845403,"about_ca_system_score_codex":0.00017421527,"about_ca_system_score_gemma":0.00005955665,"threshold_uncertainty_score":0.5187246},"labels":[],"label_agreement":null},{"id":"W2870292154","doi":"10.1007/978-981-13-0755-3_2","title":"Using Open Clinical Data to Create an Embeddable Prediction System for Hospital Stay","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thunder Bay Regional Research Institute; Lakehead University","funders":"","keywords":"Computer science; Bayesian network; Naive Bayes classifier; Tree (set theory); Classifier (UML); Medicine; Medical emergency; Data mining; Data science; Artificial intelligence; Mathematics","score_opus":0.683785439408603,"score_gpt":0.6109856988445617,"score_spread":0.07279974056404137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2870292154","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014054896,0.0002735451,0.7085819,0.0029949124,0.011608549,0.024649356,0.004555957,0.00050723297,0.23277362],"genre_scores_gemma":[0.11655752,0.001459315,0.86619705,0.0048170635,0.0020826312,0.00078891154,0.003624412,0.00010242707,0.004370663],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99675065,0.00020260268,0.0018988432,0.0004620843,0.00032108193,0.00036472233],"domain_scores_gemma":[0.99266833,0.00070800533,0.00071757764,0.004096389,0.0015402162,0.00026951134],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0071460996,0.00018695246,0.00037493886,0.0004644965,0.00238464,0.00030657323,0.0053050974,0.000300751,0.00003515803],"category_scores_gemma":[0.00037220048,0.0001829178,0.000026149512,0.00025684622,0.0006688015,0.007829385,0.0070227487,0.000615293,0.00016982653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002621174,0.00023773972,0.018287715,0.0016422983,0.000065624125,7.932037e-7,0.06652848,0.0009881473,0.000005292021,0.5430121,0.023759916,0.34520978],"study_design_scores_gemma":[0.00017071777,0.00030950608,0.00067121314,0.0012205482,0.0000146421025,0.0000018781056,0.0019914052,0.7597003,0.0000012619137,0.0014703244,0.23422895,0.00021924777],"about_ca_topic_score_codex":0.0004452425,"about_ca_topic_score_gemma":0.00042811007,"teacher_disagreement_score":0.7587122,"about_ca_system_score_codex":0.00046137048,"about_ca_system_score_gemma":0.0013561201,"threshold_uncertainty_score":0.9989141},"labels":[],"label_agreement":null},{"id":"W2882971404","doi":"10.1007/978-981-13-1053-9","title":"Altmetrics for Research Outputs Measurement and Scholarly Information Management","year":2018,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Altmetrics; Social media; Computer science; Data science; State (computer science); Information retrieval; World Wide Web","score_opus":0.4725498734386918,"score_gpt":0.4747758344258194,"score_spread":0.002225960987127573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2882971404","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012882319,0.00061768014,0.7054709,0.0019527551,0.001448767,0.002480276,0.00010041027,0.00007588931,0.28772447],"genre_scores_gemma":[0.039220143,0.0068545546,0.89802134,0.005722426,0.0005531984,0.0008767802,0.0010498817,0.000049148166,0.047652513],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9924956,0.00022453725,0.0016302372,0.0005816592,0.004591477,0.00047649728],"domain_scores_gemma":[0.9884273,0.0014198041,0.0005846458,0.0037663106,0.00560881,0.00019314283],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.06347546,0.00021573495,0.00029694432,0.0070791966,0.0017328381,0.009366546,0.0052815517,0.00012476514,0.0000078171715],"category_scores_gemma":[0.0041559082,0.00018931995,0.000049446553,0.003753284,0.0016663166,0.018858945,0.007139775,0.00046681092,0.0002448067],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006654266,0.000019300196,0.000054720764,0.00004853441,0.000007792624,7.645938e-8,0.0020683615,0.000035793182,1.922328e-7,0.11782049,0.109814525,0.77012354],"study_design_scores_gemma":[0.00039697308,0.000081222424,0.0028805747,0.00016181581,0.000007532279,0.0000028911536,0.00033938745,0.06963425,0.0000014313551,0.030812424,0.89548695,0.00019456065],"about_ca_topic_score_codex":0.000011672053,"about_ca_topic_score_gemma":0.000015222245,"teacher_disagreement_score":0.7856724,"about_ca_system_score_codex":0.00055625103,"about_ca_system_score_gemma":0.000530258,"threshold_uncertainty_score":0.9995668},"labels":[],"label_agreement":null},{"id":"W2884342870","doi":"10.1007/978-981-13-1648-7_15","title":"Improving Energy Demand Estimation Using an Adaptive Firefly Algorithm","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Firefly algorithm; Particle swarm optimization; Estimation; Computer science; Mathematical optimization; Energy demand; Weighting; Population; Energy (signal processing); Algorithm; Mathematics; Engineering; Economics; Statistics; Environmental economics","score_opus":0.036446996431429714,"score_gpt":0.2614611902246,"score_spread":0.2250141937931703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884342870","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002942708,0.00030106862,0.94319427,0.0000070960537,0.00029822814,0.000084458865,0.000015970347,0.00012324823,0.055681366],"genre_scores_gemma":[0.1257131,0.001151144,0.87213546,0.0002185994,0.00019049858,0.000015582524,0.00021466683,0.000038235718,0.00032269527],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901086,0.000012884403,0.0004469153,0.00014171422,0.00020764218,0.00017995472],"domain_scores_gemma":[0.99879426,0.000059417813,0.00014842988,0.0007292911,0.00018631155,0.00008227897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042168968,0.00018741877,0.00016386772,0.00055005465,0.00036628603,0.00026756123,0.0007020212,0.00012085802,0.0000112065045],"category_scores_gemma":[0.000009476702,0.00020193084,0.0000231611,0.00018582575,0.00043711893,0.0048275,0.00038751736,0.00020874513,0.0000079202955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001199578,0.000005849921,0.0000018744657,0.000020774067,0.000006361657,2.1108633e-7,0.0015567432,0.059367932,0.000009720102,0.024407672,0.000029113917,0.91459256],"study_design_scores_gemma":[0.00009350135,0.00004148065,0.00001677277,0.00017038024,0.0000064573946,0.000016094891,0.000018465957,0.9893394,0.00004331575,0.0017388962,0.008293043,0.00022215796],"about_ca_topic_score_codex":0.00004006512,"about_ca_topic_score_gemma":0.000021253629,"teacher_disagreement_score":0.9299715,"about_ca_system_score_codex":0.00014406978,"about_ca_system_score_gemma":0.00008694028,"threshold_uncertainty_score":0.8234501},"labels":[],"label_agreement":null},{"id":"W2884805154","doi":"10.1007/978-3-319-94959-8_16","title":"A Lexical and Semantical Analysis on REST Cloud Computing APIs","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Concordia University","funders":"","keywords":"Rest (music); Cloud computing; Computer science; World Wide Web; The Internet; Resource (disambiguation); Documentation; Information retrieval; Programming language; Operating system","score_opus":0.034420140370118514,"score_gpt":0.2938637711291861,"score_spread":0.25944363075906757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884805154","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006887612,0.00030605,0.7554905,0.0040702955,0.00057684915,0.00054393953,0.000007686913,0.00029818274,0.2318189],"genre_scores_gemma":[0.8123671,0.00071722886,0.17937517,0.0043371916,0.00034528246,0.000011173015,0.000039979153,0.000022551489,0.0027843555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99777514,0.000061487925,0.0007240163,0.00051500037,0.00060381467,0.0003205513],"domain_scores_gemma":[0.996535,0.00040442657,0.00030759178,0.002336957,0.00024746187,0.00016857557],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016463987,0.00027656925,0.00039332767,0.0017166098,0.00079549465,0.0009891747,0.0028613964,0.00013780597,0.00000705445],"category_scores_gemma":[0.000052770956,0.00025654174,0.00008654519,0.0010278983,0.0013972454,0.000517823,0.0053687557,0.0005020566,0.000066166715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000372389,0.000032259046,0.00012251872,0.000030280691,0.000055695877,0.000001571846,0.0029151489,0.0017650722,4.3696267e-7,0.84446985,0.00049951056,0.15010396],"study_design_scores_gemma":[0.00020374547,0.000106304695,0.002884798,0.00018338562,0.000034080123,0.000014894878,0.000022560114,0.94986326,0.0000015908716,0.0045460914,0.041829284,0.00030999372],"about_ca_topic_score_codex":0.000013598135,"about_ca_topic_score_gemma":0.000009046507,"teacher_disagreement_score":0.9480982,"about_ca_system_score_codex":0.00010442653,"about_ca_system_score_gemma":0.00009012998,"threshold_uncertainty_score":0.9999887},"labels":[],"label_agreement":null},{"id":"W2885735840","doi":"10.1007/978-3-319-97925-0_8","title":"An Analysis of IT Project Management Across Companies in an International Scenario","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Business; Project management; Knowledge management; Engineering management; Computer science; Engineering; Systems engineering","score_opus":0.1482533408528462,"score_gpt":0.44549378232191433,"score_spread":0.29724044146906814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885735840","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16828491,0.00011644413,0.04699698,0.00084775896,0.0016094593,0.0019386562,0.0002947281,0.000114229224,0.77979684],"genre_scores_gemma":[0.95575595,0.0017988568,0.038138624,0.00058006233,0.00005039295,0.000035577646,0.00032050724,0.000009234675,0.003310766],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99676335,0.000065996595,0.0014139217,0.00038944912,0.0011672861,0.00020000036],"domain_scores_gemma":[0.9958615,0.00016393865,0.0006979227,0.0023778267,0.0008416738,0.000057186848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042844024,0.00018505234,0.0003827331,0.005484087,0.00030340225,0.0010002131,0.0045248955,0.000084764746,0.00018415239],"category_scores_gemma":[0.00004668389,0.0001681011,0.000071084665,0.002324185,0.0014498703,0.010322982,0.0017613225,0.0002236808,0.00003517361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006098962,0.00014081744,0.060771205,0.00003587788,0.00014188672,8.5570247e-7,0.03739361,0.0066461954,0.0000015551858,0.23591493,0.000490148,0.6584019],"study_design_scores_gemma":[0.00029453277,0.00007312011,0.08636353,0.00007644966,0.000030824118,0.000002192648,0.0018320439,0.7661023,0.0000013665552,0.0019465643,0.14304894,0.00022810504],"about_ca_topic_score_codex":0.00006121199,"about_ca_topic_score_gemma":0.0011002626,"teacher_disagreement_score":0.78747106,"about_ca_system_score_codex":0.00012487761,"about_ca_system_score_gemma":0.00011325521,"threshold_uncertainty_score":0.9645078},"labels":[],"label_agreement":null},{"id":"W2887261712","doi":"10.1007/978-981-13-2122-1_4","title":"Learning Safe Graph Construction from Multiple Graphs","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Novelis (Canada)","funders":"","keywords":"Computer science; Graph; Information retrieval; Theoretical computer science","score_opus":0.03168101659383128,"score_gpt":0.2651982043060919,"score_spread":0.23351718771226065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887261712","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011877564,0.00044168675,0.84317344,0.001571884,0.00075947965,0.00049965444,0.000020028612,0.0007251919,0.15162085],"genre_scores_gemma":[0.23769489,0.008422094,0.7505514,0.0007973004,0.000071062736,0.00007131192,0.00023190863,0.000019706198,0.0021403476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983159,0.00003232075,0.00065113057,0.00036599123,0.0004169803,0.00021772986],"domain_scores_gemma":[0.9966659,0.00027354882,0.00048740619,0.0021093776,0.00038683673,0.00007694377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058061606,0.00022456748,0.00022664345,0.0013609568,0.0007072395,0.0008207116,0.0035026171,0.00018814573,0.000030239791],"category_scores_gemma":[0.000096192525,0.00022798851,0.000053950564,0.0006066957,0.0020592317,0.0071329637,0.002319132,0.00051916303,0.00014424123],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014621536,0.0000068362942,0.000487252,0.0000050238073,0.0000053634394,1.0514505e-7,0.0010654643,0.000024926201,0.000007608931,0.6283709,0.0002621095,0.369763],"study_design_scores_gemma":[0.000703524,0.00015936965,0.00580432,0.0002647144,0.000011597122,0.00002082417,0.0003492858,0.2533155,0.0001727825,0.37452412,0.36386317,0.0008107797],"about_ca_topic_score_codex":0.000021931022,"about_ca_topic_score_gemma":0.0000128944785,"teacher_disagreement_score":0.36895218,"about_ca_system_score_codex":0.000100028636,"about_ca_system_score_gemma":0.00015417018,"threshold_uncertainty_score":0.92971015},"labels":[],"label_agreement":null},{"id":"W2887611685","doi":"10.1007/978-3-319-99133-7_10","title":"Detecting Low Back Pain from Clinical Narratives Using Machine Learning Approaches","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Acronym; Text messaging; Set (abstract data type); Computer science; Artificial intelligence; Subject (documents); Information retrieval; Electronic medical record; Medical record; Plan (archaeology); Natural language processing; Machine learning; Test set; Electronic health record; Medicine; Health care; World Wide Web","score_opus":0.13784280048731015,"score_gpt":0.3456810875785564,"score_spread":0.20783828709124627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887611685","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061655235,0.005040383,0.85349095,0.000774611,0.0008233632,0.00072662265,0.00007394028,0.00010345964,0.07731141],"genre_scores_gemma":[0.23380192,0.0037044932,0.758216,0.0012833446,0.0005437864,0.000014595296,0.0007529928,0.00003041199,0.0016524246],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882096,0.00012851595,0.00051869435,0.00023864335,0.00014915488,0.00014401523],"domain_scores_gemma":[0.99867535,0.00015770084,0.00028555008,0.0006934487,0.00012229836,0.00006566228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019133788,0.00014907222,0.00019064885,0.00015464732,0.0003474526,0.00012991067,0.0007992027,0.00024020643,0.00001817423],"category_scores_gemma":[0.0002861914,0.0001365462,0.000046844867,0.00009039497,0.0017780514,0.00006627999,0.0010978817,0.00038282125,0.000014298847],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033871795,0.000046445602,0.0046244003,0.00006815375,0.000057006262,3.5247558e-7,0.004734365,0.00021182922,0.00034956602,0.0014671219,0.0003373621,0.98806953],"study_design_scores_gemma":[0.0005157894,0.00036662412,0.0008919855,0.0004210477,0.000008804023,0.000011300717,0.0005332008,0.6805649,0.00018336397,0.0013884336,0.3146163,0.0004982884],"about_ca_topic_score_codex":0.000013917236,"about_ca_topic_score_gemma":0.00002668974,"teacher_disagreement_score":0.98757124,"about_ca_system_score_codex":0.00002169403,"about_ca_system_score_gemma":0.00013082754,"threshold_uncertainty_score":0.65513045},"labels":[],"label_agreement":null},{"id":"W2888519339","doi":"10.1007/978-3-319-95921-4_8","title":"Quantitative Evaluation of Correction Methods and Simulation of Motion Artifacts for Rotary Pullback Imaging Catheters","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ground truth; Computer vision; Imaging phantom; Artificial intelligence; Computer science; Image registration; Image quality; Motion (physics); Rotation around a fixed axis; Motion estimation; Image (mathematics); Physics; Optics","score_opus":0.09248917575035341,"score_gpt":0.3985899606344506,"score_spread":0.3061007848840972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888519339","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004405524,0.0003758656,0.97841096,0.000040779007,0.0002035922,0.001028998,0.00002968927,0.000041002844,0.015463606],"genre_scores_gemma":[0.73638636,0.00039802617,0.2629814,0.000020290057,0.000011624965,0.000081913255,0.0000936536,0.000011103192,0.000015617026],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888176,0.000040639738,0.0005950358,0.00012986074,0.00025502968,0.00009766721],"domain_scores_gemma":[0.99757415,0.00049908174,0.00027492247,0.0005490783,0.0010645495,0.000038187816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019264534,0.00012542219,0.00018695675,0.00068746833,0.000120918325,0.000050523257,0.00029832282,0.0000705428,0.000008028881],"category_scores_gemma":[0.00013381174,0.00013824097,0.000035641402,0.00028533078,0.00075755344,0.0018126047,0.00012728445,0.0001255281,0.000001909749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009325751,0.000015999702,0.00006493979,0.00013021553,0.000016922235,2.9416347e-9,0.002652477,0.2158861,0.00021071792,0.023168523,0.00003736721,0.7578074],"study_design_scores_gemma":[0.00016851735,0.00004679846,0.0013855085,0.00013331504,0.00003611041,9.0487805e-7,0.00007008895,0.9871613,0.0002601945,0.009852163,0.0007696313,0.00011547591],"about_ca_topic_score_codex":0.0000048643956,"about_ca_topic_score_gemma":0.000005405471,"teacher_disagreement_score":0.77127516,"about_ca_system_score_codex":0.00008527867,"about_ca_system_score_gemma":0.000058409863,"threshold_uncertainty_score":0.5637303},"labels":[],"label_agreement":null},{"id":"W2888854509","doi":"10.1007/978-3-319-99972-2_2","title":"Metis: A Scalable Natural-Language-Based Intelligent Personal Assistant for Maritime Services","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scalability; Natural language; Parsing; Task (project management); Domain (mathematical analysis); Field (mathematics); Question answering; Artificial intelligence; Natural language processing; Information retrieval; Database","score_opus":0.024888619594436653,"score_gpt":0.2822263595750337,"score_spread":0.25733773998059706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888854509","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012804399,0.0024615044,0.9298319,0.0010753893,0.0010752885,0.0011670659,0.00009982314,0.00019089067,0.06397006],"genre_scores_gemma":[0.17064817,0.0007416766,0.8167607,0.005380775,0.00030650318,0.00026785306,0.0006091225,0.000033597684,0.005251556],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981903,0.00003154794,0.0006406723,0.00034608098,0.00048859924,0.0003028348],"domain_scores_gemma":[0.99701715,0.0002823351,0.0003512124,0.0015955496,0.00062684226,0.00012692489],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012731932,0.00024100137,0.0002800728,0.0008375463,0.00051082775,0.001081023,0.0033838684,0.00012554078,0.000018965935],"category_scores_gemma":[0.000034086243,0.00022523756,0.00008297982,0.0003745581,0.0006358464,0.0038219574,0.0012773864,0.00024883394,0.00009511312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042923017,0.00008662157,0.00006332776,0.00059431756,0.000043338358,0.0000018561169,0.021536028,0.00008581541,0.00003501967,0.33854574,0.003158247,0.63580674],"study_design_scores_gemma":[0.0002824929,0.00009369606,0.00014406892,0.00038556397,0.0000068658196,0.000014869308,0.00009908178,0.8449203,0.00007492938,0.0023940052,0.15126166,0.0003224972],"about_ca_topic_score_codex":0.000040613497,"about_ca_topic_score_gemma":0.00006565777,"teacher_disagreement_score":0.84483445,"about_ca_system_score_codex":0.00018340784,"about_ca_system_score_gemma":0.00040953135,"threshold_uncertainty_score":0.99995595},"labels":[],"label_agreement":null},{"id":"W2904516142","doi":"10.1007/978-981-13-3044-5_32","title":"Multi-kernel Collaboration-Induced Fuzzy Local Information C-Means Algorithm for Image Segmentation","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kernel (algebra); Artificial intelligence; Pattern recognition (psychology); Fuzzy logic; Image segmentation; Computer science; Radial basis function kernel; Cluster analysis; Kernel method; Algorithm; Mathematics; Segmentation; Support vector machine","score_opus":0.03464853237173302,"score_gpt":0.3330817609094066,"score_spread":0.29843322853767357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904516142","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005544879,0.000043124255,0.98462266,0.00064716104,0.00045508865,0.001509865,0.000086596534,0.0002533579,0.01237661],"genre_scores_gemma":[0.00038911024,0.00047364968,0.99605036,0.0018941902,0.00004829849,0.00022440396,0.0004930829,0.000011955348,0.00041495042],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971536,0.000055217464,0.0013054851,0.0003657021,0.00078516384,0.00033483325],"domain_scores_gemma":[0.9949583,0.0002538886,0.00079672236,0.0017704521,0.002026968,0.00019370025],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0016667704,0.00033912843,0.00032273095,0.0013793793,0.0006900966,0.0015832088,0.0029075923,0.00023183321,0.000022550485],"category_scores_gemma":[0.00012878355,0.00035598027,0.00006691777,0.00072399864,0.0011652805,0.025767347,0.0013815265,0.00035982236,0.00016156885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030547103,0.000029632722,0.0000015585732,0.00005018581,0.000010029808,2.2258672e-7,0.004867497,0.000023886214,0.00008277965,0.030087225,0.0021377704,0.96270615],"study_design_scores_gemma":[0.0009644223,0.00018159558,0.00007082157,0.00016450588,0.000011640763,0.0000151642225,0.0002787443,0.96720314,0.0011130295,0.0042207907,0.02530044,0.00047570805],"about_ca_topic_score_codex":0.000018225972,"about_ca_topic_score_gemma":0.000016827875,"teacher_disagreement_score":0.96717924,"about_ca_system_score_codex":0.00044229135,"about_ca_system_score_gemma":0.0006794773,"threshold_uncertainty_score":0.9998892},"labels":[],"label_agreement":null},{"id":"W2914381873","doi":"10.1007/978-981-13-6661-1_20","title":"A Modularity-Based Measure for Cluster Selection from Clustering Hierarchies","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Modularity (biology); Hierarchical clustering of networks; Cluster analysis; Hierarchy; Hierarchical clustering; Measure (data warehouse); Computer science; Data mining; Single-linkage clustering; Selection (genetic algorithm); Context (archaeology); Cluster (spacecraft); Correlation clustering; Artificial intelligence; CURE data clustering algorithm; Geography","score_opus":0.03134754300511575,"score_gpt":0.28811249609853373,"score_spread":0.25676495309341796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914381873","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014777908,0.000055592733,0.9435238,0.00028219185,0.00007669869,0.00056947,0.000058544378,0.000050833296,0.055235043],"genre_scores_gemma":[0.58590317,0.00006820945,0.41041088,0.00071805523,0.00022914556,0.00015084432,0.0011498587,0.000028772489,0.0013410387],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989301,0.000024699155,0.00045832878,0.00020598246,0.00022349447,0.00015738879],"domain_scores_gemma":[0.99821585,0.0002330275,0.00026675264,0.0009202712,0.00032108047,0.000043004948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005441011,0.00017844666,0.00024715913,0.0005751482,0.00035712757,0.00033442528,0.0008914198,0.0000681219,0.000025412757],"category_scores_gemma":[0.0000061557294,0.00018693079,0.0000844046,0.0001924596,0.00027647626,0.0015056514,0.00059191935,0.00029885952,0.000011053708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029314815,0.00004422831,0.0023752472,0.00005907098,0.00006546007,1.3966181e-8,0.0011368087,0.016291106,0.000020131805,0.42910784,0.0010978995,0.54977286],"study_design_scores_gemma":[0.00028316013,0.000024164772,0.00042176567,0.00015790359,0.000018137609,2.1870841e-7,0.000007957336,0.9095934,0.00001464827,0.01798309,0.07129043,0.00020514047],"about_ca_topic_score_codex":0.000071228045,"about_ca_topic_score_gemma":0.000055917066,"teacher_disagreement_score":0.89330226,"about_ca_system_score_codex":0.00008501077,"about_ca_system_score_gemma":0.0002024495,"threshold_uncertainty_score":0.7622816},"labels":[],"label_agreement":null},{"id":"W2922857","doi":"10.1007/978-3-642-10238-7_7","title":"Artificial K-Lines and Applications","year":2009,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Artificial intelligence; Artificial neural network; Causality (physics); Knowledge base; Machine learning; Physics","score_opus":0.06177799720094484,"score_gpt":0.3040433938657268,"score_spread":0.24226539666478197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922857","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014961705,0.000462781,0.84316456,0.0015784939,0.00009334322,0.00033108506,0.0000037639013,0.00008763396,0.15426336],"genre_scores_gemma":[0.035981853,0.007589031,0.94861406,0.003866525,0.00028141128,0.000112098096,0.00005944946,0.000015591293,0.0034799762],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987192,0.000013222452,0.0005500414,0.00027384676,0.00027949733,0.00016420554],"domain_scores_gemma":[0.99757695,0.000107239925,0.00020148669,0.0017981176,0.00022774815,0.00008846662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064322754,0.00015623317,0.00017234463,0.0006619703,0.00043338002,0.0006088741,0.0021568926,0.00009564641,0.0000024968463],"category_scores_gemma":[0.000016776728,0.00016103024,0.000022461581,0.00027471932,0.00051543844,0.004191707,0.0015555935,0.00028503189,0.000026573673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.6541063e-7,0.0000030194994,0.0000040470727,0.000004293503,5.993504e-7,4.1216104e-8,0.00021033363,0.00006347474,9.652825e-7,0.51194936,0.000016871494,0.48774683],"study_design_scores_gemma":[0.000080831574,0.000024498757,0.0003536138,0.000076142285,0.0000035527428,0.000023215756,0.000008315488,0.604958,0.0000070457763,0.10096237,0.29323915,0.0002632628],"about_ca_topic_score_codex":0.0000050516974,"about_ca_topic_score_gemma":0.0000066561124,"teacher_disagreement_score":0.6048945,"about_ca_system_score_codex":0.000056350935,"about_ca_system_score_gemma":0.0001597375,"threshold_uncertainty_score":0.6566623},"labels":[],"label_agreement":null},{"id":"W2939445241","doi":"10.1007/978-3-030-30278-8_34","title":"A Blockchain-Based Decentralized Self-balancing Architecture for the Web of Things","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"European Regional Development Fund; SBA Research; Université de Lyon; Libera Università di Bolzano; Université François-Rabelais; Universidad de Castilla-La Mancha; Università degli Studi di Torino; European Commission; Latvijas Universitate; Austrian Institute of Technology; Università di Bologna; Universität Wien; Universidade Estadual de Londrina; Javna Agencija za Raziskovalno Dejavnost RS; Universitat de València; Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture; Università degli Studi di Padova; Universität Ulm; Technische Universiteit Eindhoven; Università degli Studi di Milano-Bicocca; Sorbonne Université; Trinity College Dublin; University of Twente; University of Brighton; University of Haifa; Conservatoire National des Arts et Métiers; Fondazione Bruno Kessler; University of Carthage; San José State University; Université Laval; Université de Pau et des Pays de l'Adour; Universidad de Sevilla; Université de Lorraine; Politecnico di Torino; Sveučilište u Zagrebu; University of Ioannina; Aix-Marseille Université","keywords":"Computer science; Scalability; Distributed computing; Blockchain; Architecture; Edge computing; Enhanced Data Rates for GSM Evolution; Proof of concept; Container (type theory); Edge device; Cloud computing; Wireless sensor network; Computer network; Internet of Things; Computer security; Artificial intelligence; Database","score_opus":0.019715571389427863,"score_gpt":0.26185182100181015,"score_spread":0.24213624961238228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939445241","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011741172,0.0005902361,0.9666885,0.0022991016,0.0017435611,0.0009393421,0.0000029517464,0.00011731486,0.027501557],"genre_scores_gemma":[0.07297574,0.0008045786,0.9200391,0.0052146344,0.00023242961,0.00005866527,0.000034959692,0.000028958797,0.0006109292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983648,0.000029895424,0.0006673321,0.00024288846,0.00041174394,0.0002833486],"domain_scores_gemma":[0.99580765,0.0011801332,0.00051013177,0.001992994,0.0004490444,0.000060067247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015753406,0.00021332839,0.00028562025,0.0006348365,0.0005188938,0.00035512558,0.004174615,0.000110864974,8.6861064e-7],"category_scores_gemma":[0.000060020568,0.00016681652,0.00009584199,0.0004164277,0.00043174907,0.00083982426,0.0014380293,0.00038580486,0.00000727753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000147812925,0.00004450932,0.00015869658,0.00031314007,0.000037681955,2.2546674e-7,0.015449507,0.007824291,0.0000223714,0.50628775,0.001257408,0.46858966],"study_design_scores_gemma":[0.00036428214,0.00003244831,0.00010701806,0.00019568737,0.000007922304,0.0000057586954,0.0000071666186,0.80932075,0.000017143813,0.0018980718,0.18787865,0.0001651121],"about_ca_topic_score_codex":0.0000109058665,"about_ca_topic_score_gemma":0.0000021211683,"teacher_disagreement_score":0.80149645,"about_ca_system_score_codex":0.000094482886,"about_ca_system_score_gemma":0.0009538367,"threshold_uncertainty_score":0.7757543},"labels":[],"label_agreement":null},{"id":"W2946064590","doi":"10.1007/978-3-030-20257-6_23","title":"Image Classification Using Deep Neural Networks: Transfer Learning and the Handling of Unknown Images","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Transfer of learning; Computer science; Artificial intelligence; Scratch; Robustness (evolution); Artificial neural network; Machine learning; Deep learning; Contextual image classification; Training set; Pattern recognition (psychology); Deep neural networks; Set (abstract data type); Image (mathematics)","score_opus":0.03968660611179555,"score_gpt":0.28742525563879534,"score_spread":0.24773864952699978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946064590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019237702,0.0009278011,0.9637789,0.00049359165,0.00016226762,0.00035108137,0.0000011762687,0.00004356363,0.034049235],"genre_scores_gemma":[0.7925639,0.005289101,0.20086502,0.00056665466,0.000046393016,0.000014871162,0.00003281527,0.000018866203,0.00060233625],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983877,0.00012190052,0.000696305,0.00024600135,0.00035378867,0.0001942834],"domain_scores_gemma":[0.9977019,0.00058161374,0.0003533581,0.0009254691,0.0003789439,0.000058722995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018392433,0.0001889078,0.00028645838,0.00052120053,0.00060264533,0.00070111314,0.0015659382,0.000094349016,0.000004221859],"category_scores_gemma":[0.00007095268,0.00015545478,0.000054740645,0.0003855099,0.0016014087,0.004498589,0.00091308414,0.0005840495,0.0000044901067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011301199,0.000007645376,0.00009258243,0.000043719072,0.000009301842,1.4239603e-7,0.0042351964,0.0242171,0.000041890704,0.7053023,0.000004128209,0.26603472],"study_design_scores_gemma":[0.0005578253,0.000022392169,0.00055430934,0.000099717865,0.000009236379,0.000015324104,0.000097953154,0.9917998,0.00000382138,0.0007744739,0.005898585,0.00016658517],"about_ca_topic_score_codex":0.000009846416,"about_ca_topic_score_gemma":0.0000033157964,"teacher_disagreement_score":0.9675827,"about_ca_system_score_codex":0.000052872037,"about_ca_system_score_gemma":0.0001193762,"threshold_uncertainty_score":0.676085},"labels":[],"label_agreement":null},{"id":"W2953448948","doi":"10.1007/978-3-030-25109-3_9","title":"A Detailed Analysis of the CICIDS2017 Data Set","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":158,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Atlantic Canada Opportunities Agency","keywords":"Computer science; Intrusion detection system; Data mining; Metadata; Set (abstract data type); Network packet; The Internet; Random forest; Payload (computing); Attack model; Anomaly detection; Anomaly-based intrusion detection system; Machine learning; Computer security; World Wide Web","score_opus":0.06541843500189172,"score_gpt":0.30438121162502124,"score_spread":0.23896277662312954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953448948","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00080643955,0.0007816771,0.74425846,0.0020768857,0.0013331486,0.0009888902,0.00015858116,0.00010253665,0.24949336],"genre_scores_gemma":[0.80639005,0.012490517,0.16900079,0.005135865,0.00013112489,0.000031257532,0.0006896574,0.000028755649,0.006102005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984222,0.00004743356,0.00062642817,0.00027599672,0.00048632783,0.00014161303],"domain_scores_gemma":[0.992054,0.00020267833,0.00055150123,0.006846615,0.00030238935,0.00004283879],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0013388871,0.0001409073,0.0002857406,0.0010756945,0.00035111717,0.00032236558,0.0094544375,0.000104189196,0.000012988332],"category_scores_gemma":[0.00004694313,0.0001111866,0.000073224684,0.0014929296,0.00067387323,0.0056088036,0.009118926,0.0003606273,0.000022611712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028044126,0.000016288684,0.0005543264,0.000027851127,0.000083652354,7.212233e-8,0.002086385,0.0021102512,0.000003874779,0.8208938,0.00068428734,0.17353636],"study_design_scores_gemma":[0.00009611529,0.000017153761,0.0049853623,0.00007551567,0.000046413985,0.00000320536,0.000005567262,0.89375776,0.0000053311305,0.0017822583,0.0990954,0.00012989782],"about_ca_topic_score_codex":0.0000152139255,"about_ca_topic_score_gemma":0.00013932944,"teacher_disagreement_score":0.8916475,"about_ca_system_score_codex":0.00005858391,"about_ca_system_score_gemma":0.00030861932,"threshold_uncertainty_score":0.9988951},"labels":[],"label_agreement":null},{"id":"W2953660215","doi":"10.1007/978-3-642-22333-4","title":"Future Information Technology","year":2011,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science","score_opus":0.05786416786071543,"score_gpt":0.2876504572655312,"score_spread":0.22978628940481574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953660215","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008319708,0.00040738148,0.043389957,0.0025062892,0.0012848258,0.00052419776,0.000021241767,0.00023036274,0.95155257],"genre_scores_gemma":[0.28163463,0.062356215,0.4337948,0.13685767,0.015344488,0.0016892336,0.023482999,0.00031997883,0.044519976],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99873483,0.0000038995463,0.00059789955,0.00014596406,0.0002988133,0.00021860767],"domain_scores_gemma":[0.9974015,0.000023972132,0.0004784952,0.0013749595,0.0007073875,0.000013694711],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00060557533,0.00019453319,0.00019289782,0.0027096188,0.00042345983,0.0008364368,0.0025755214,0.00021746336,0.0000618242],"category_scores_gemma":[0.00006120227,0.00018331988,0.000026014095,0.0016006738,0.00092511583,0.031755786,0.0024718884,0.00043786556,0.00080723566],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002739344,0.000010750825,0.00017205437,0.00009660743,0.0000022416464,7.839456e-8,0.000206404,0.000008271321,2.8011613e-7,0.5866112,0.008902018,0.40398735],"study_design_scores_gemma":[0.00010370444,0.000004862511,0.0010756766,0.00012816674,0.0000070891,0.000006356058,0.00006436446,0.016774522,0.0000017942856,0.0144602815,0.96715367,0.00021950385],"about_ca_topic_score_codex":0.00003342165,"about_ca_topic_score_gemma":0.000017953389,"teacher_disagreement_score":0.95825166,"about_ca_system_score_codex":0.00008531263,"about_ca_system_score_gemma":0.00023039903,"threshold_uncertainty_score":0.99997073},"labels":[],"label_agreement":null},{"id":"W2954533597","doi":"10.1007/978-3-030-24337-1_7","title":"Analyzing the Impact of Knowledge and Search in Monte Carlo Tree Search in Go","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Monte Carlo tree search; Tree (set theory); Monte Carlo method; Information retrieval; Search tree; Search algorithm; Statistics; Mathematics; Algorithm; Combinatorics","score_opus":0.09255515193758446,"score_gpt":0.37890422392948514,"score_spread":0.2863490719919007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954533597","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18974662,0.010959543,0.27545515,0.0034280883,0.00067490037,0.0042435806,0.000049405888,0.00013831194,0.5153044],"genre_scores_gemma":[0.9895097,0.0026355763,0.007448374,0.000031050015,0.000009874142,0.000008366267,0.0000029785333,0.0000051225516,0.00034892934],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99831384,0.00010444188,0.0007603304,0.00024994704,0.00030277687,0.00026866797],"domain_scores_gemma":[0.9969936,0.0006665359,0.00017344294,0.0017660324,0.00033917712,0.00006123969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026159112,0.0001720886,0.00028580107,0.0015504396,0.00017230315,0.0003414494,0.0035006267,0.000099142184,0.0000033640865],"category_scores_gemma":[0.000054563134,0.00013493399,0.000050048762,0.0010206978,0.0011357766,0.00365799,0.0030835927,0.00062089926,0.000024100724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000069061894,0.000045249733,0.015865352,0.00004984205,0.000008846501,5.4951704e-7,0.03542706,0.017889434,0.000016817583,0.20158006,0.00006131318,0.72904855],"study_design_scores_gemma":[0.0001029509,0.00006236985,0.042670604,0.0002486059,0.0000011841545,0.0000058224127,0.00010741973,0.9543638,0.000023461018,0.001593867,0.0006675048,0.00015239594],"about_ca_topic_score_codex":0.00053795165,"about_ca_topic_score_gemma":0.00045035713,"teacher_disagreement_score":0.9364744,"about_ca_system_score_codex":0.00023524884,"about_ca_system_score_gemma":0.0006180235,"threshold_uncertainty_score":0.65050936},"labels":[],"label_agreement":null},{"id":"W2961012900","doi":"10.1007/978-3-030-23522-2_27","title":"Helping Users Secure Their Data by Supporting Mental Models of VeraCrypt","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Usability; Computer science; Task (project management); World Wide Web; Software walkthrough; Test (biology); Human–computer interaction; Cognitive walkthrough; User interface; Encryption; Software; Pluralistic walkthrough; Computer security; Operating system; Software development","score_opus":0.34942271687584003,"score_gpt":0.4365871207073432,"score_spread":0.08716440383150315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961012900","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009315014,0.001220009,0.17449859,0.0040403935,0.0014465456,0.0025158941,0.002768313,0.00014193647,0.8040533],"genre_scores_gemma":[0.9177927,0.0060491664,0.050620835,0.0044489703,0.00007788081,0.000027641616,0.004936424,0.000043907232,0.016002517],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966859,0.000035288238,0.0015130984,0.00030930428,0.0012419189,0.00021449606],"domain_scores_gemma":[0.9947076,0.00037308727,0.0011272616,0.0032097988,0.0005029332,0.00007932267],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0041611916,0.00020699768,0.0003422355,0.0010669327,0.00034280904,0.00069950573,0.0061708954,0.00010236847,0.0000687462],"category_scores_gemma":[0.00009586294,0.00017538528,0.000055430315,0.0004664969,0.0006400218,0.018724509,0.005037525,0.00031542798,0.00008786321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019040579,0.000049779665,0.0008410322,0.00007447067,0.000028201986,2.0219608e-7,0.017630706,0.0018289051,0.000030183484,0.41949812,0.03523018,0.5247692],"study_design_scores_gemma":[0.0002448088,0.000023838445,0.00029862399,0.000120317265,0.000007086892,0.000003255927,0.0007190135,0.7410954,0.000009126753,0.0042942916,0.25296047,0.00022374738],"about_ca_topic_score_codex":0.000013312973,"about_ca_topic_score_gemma":0.0000088304605,"teacher_disagreement_score":0.90847766,"about_ca_system_score_codex":0.000079358375,"about_ca_system_score_gemma":0.0002502615,"threshold_uncertainty_score":0.9992062},"labels":[],"label_agreement":null},{"id":"W2961014324","doi":"10.1007/978-981-13-9895-7_20","title":"A Review on the Admission Policies of Hong Kong Universities for Non-local Students from Mainland China","year":2019,"lang":"en","type":"review","venue":"Communications in computer and information science","topic":"Hong Kong and Taiwan Politics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas College","funders":"","keywords":"Mainland China; Mainland; China; Politics; Test (biology); Institution; Political science; Entrance exam; Public relations; Public administration; Medical education; Geography; Medicine; Law","score_opus":0.09367400263909186,"score_gpt":0.429946849577086,"score_spread":0.33627284693799414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961014324","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021050163,0.9783549,0.0049128626,0.0015843719,0.00029252443,0.0019276754,0.00015695093,0.000023409948,0.012536829],"genre_scores_gemma":[0.0029763514,0.99571306,0.0007765191,0.00041606903,0.000026695778,0.000015263187,0.00003636045,0.0000030554963,0.00003661501],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987099,0.00021100481,0.00044284176,0.00010401869,0.0003522638,0.00017993819],"domain_scores_gemma":[0.99772143,0.0009450328,0.0003315067,0.00078383676,0.00015539119,0.00006279072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016888418,0.00011733731,0.00040729356,0.00026103208,0.0006987507,0.00017315781,0.002199688,0.00006997411,0.0000041353837],"category_scores_gemma":[0.00013444308,0.00008082153,0.00008429442,0.0006822579,0.0011004199,0.00096544507,0.00058688223,0.0001929372,0.000010851234],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015737254,0.0000395827,0.000056249213,0.0036709202,0.000016817175,3.5505035e-8,0.015113911,0.000013096643,1.091154e-8,0.104413226,0.001347751,0.8753268],"study_design_scores_gemma":[0.00009991136,0.000028400891,0.00025255728,0.020846266,0.00004648497,4.0715742e-7,0.0016828018,0.0013600797,1.4655436e-7,0.00024672487,0.975318,0.00011822583],"about_ca_topic_score_codex":0.00043267195,"about_ca_topic_score_gemma":0.000023103956,"teacher_disagreement_score":0.97397023,"about_ca_system_score_codex":0.00017610898,"about_ca_system_score_gemma":0.000920301,"threshold_uncertainty_score":0.53742963},"labels":[],"label_agreement":null},{"id":"W296396633","doi":"10.1007/978-3-319-08852-5_41","title":"Learning Categories from Linked Open Data","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"RDF; Computer science; Linked data; Information retrieval; Process (computing); Extensional definition; Subject (documents); Representation (politics); Resource (disambiguation); Metadata; Hierarchy; Similarity (geometry); Web resource; World Wide Web; Data science; Semantic Web; Artificial intelligence","score_opus":0.11272261615473049,"score_gpt":0.3343144556611146,"score_spread":0.22159183950638411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W296396633","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022461398,0.00039457946,0.64611846,0.0018960256,0.00039750512,0.00031293096,0.00001487469,0.00013717616,0.35070598],"genre_scores_gemma":[0.13312745,0.0073635248,0.8460229,0.0037072063,0.00017194556,0.00004151829,0.001111124,0.000023345312,0.008431001],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99839514,0.000039224476,0.0005919817,0.0004178573,0.00035055174,0.00020526798],"domain_scores_gemma":[0.9937489,0.00048440954,0.00037122145,0.005069507,0.00024857465,0.00007735932],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0015345756,0.00019567092,0.0003013236,0.00043915163,0.0006214957,0.0023857153,0.019924859,0.00012399639,0.000008761045],"category_scores_gemma":[0.00015723983,0.00018397515,0.000019889643,0.00025970233,0.00082068436,0.013107636,0.028236048,0.0004961939,0.0001035273],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.535435e-7,0.0000035586654,0.000060730432,0.000005679074,0.000004042409,2.0663587e-7,0.0013746904,0.000046920708,4.126688e-7,0.5781727,0.00040897768,0.41992125],"study_design_scores_gemma":[0.00019833587,0.000034641464,0.0014433274,0.00010687268,0.0000046821,0.0000062391305,0.000037529706,0.48274857,0.000001952455,0.027718605,0.48744762,0.00025160122],"about_ca_topic_score_codex":0.00020408341,"about_ca_topic_score_gemma":0.00007079404,"teacher_disagreement_score":0.5504541,"about_ca_system_score_codex":0.000056891626,"about_ca_system_score_gemma":0.0003300739,"threshold_uncertainty_score":0.9986499},"labels":[],"label_agreement":null},{"id":"W2969414045","doi":"10.1007/978-3-030-29948-4_7","title":"Enabling Standard Geospatial Capabilities in Spark for the Efficient Processing of Geospatial Big Data","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Geospatial analysis; SPARK (programming language); Computer science; Big data; Geospatial PDF; Data science; Database; Geography; Remote sensing; Data mining","score_opus":0.07821030335994344,"score_gpt":0.30089710571526823,"score_spread":0.2226868023553248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969414045","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000046973873,0.00060434535,0.98570275,0.000632841,0.00053940486,0.000882964,0.0001528886,0.00002717636,0.011410646],"genre_scores_gemma":[0.3256238,0.006081311,0.66245717,0.0014595288,0.00047619094,0.00019443003,0.0014307576,0.000049935537,0.0022268689],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817896,0.000017862081,0.00074191834,0.00032625988,0.00050870207,0.00022628458],"domain_scores_gemma":[0.99546725,0.00043504295,0.0004293943,0.003299015,0.00033634264,0.000032973396],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0025576768,0.00017103828,0.00025579982,0.0006602422,0.00033677687,0.00066716067,0.0069336956,0.00006170481,0.0000017028714],"category_scores_gemma":[0.00009696297,0.00013773245,0.000029465686,0.00040639483,0.00064886594,0.0042015575,0.0060765534,0.0002443491,0.0000037937552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005329835,0.000012660697,0.000033205666,0.00010547099,0.000003995662,5.784077e-8,0.0021195328,0.0026091388,4.5280382e-7,0.11686441,0.00009162727,0.8781541],"study_design_scores_gemma":[0.00032830343,0.000042001084,0.0003874315,0.00022625695,0.0000060232614,0.0000012226451,0.00009494953,0.9137879,0.0000053373446,0.0013256805,0.08363288,0.00016199583],"about_ca_topic_score_codex":0.00006124482,"about_ca_topic_score_gemma":0.00008515215,"teacher_disagreement_score":0.91117877,"about_ca_system_score_codex":0.00008324028,"about_ca_system_score_gemma":0.00051766355,"threshold_uncertainty_score":0.99843925},"labels":[],"label_agreement":null},{"id":"W2969884593","doi":"10.1007/978-3-030-41258-6_5","title":"Studying Wythoff and Zometool Constructions Using Maple","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Chemical and Environmental Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Maple; Computer science; Polytope; Projection (relational algebra); Computation; Coxeter group; Feature (linguistics); Algorithm; Mathematics; Combinatorics; Linguistics; Biology; Botany","score_opus":0.06025726746144808,"score_gpt":0.28041934460965734,"score_spread":0.22016207714820926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969884593","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015921161,0.00081989926,0.90451336,0.0020949258,0.0002841253,0.00055769,0.000022328275,0.00017034663,0.0899452],"genre_scores_gemma":[0.27270582,0.0036837175,0.7221513,0.0008653866,0.00006668387,0.000023284552,0.0000325104,0.000017593286,0.00045369574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898607,0.000009581473,0.00032867084,0.0002174103,0.0003045464,0.00015374625],"domain_scores_gemma":[0.99881303,0.00010985713,0.000088788234,0.00080363674,0.000057483936,0.00012720068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031423624,0.00013487236,0.00015884456,0.00038503605,0.00034343314,0.0004275671,0.001317924,0.000061171035,0.000005047937],"category_scores_gemma":[0.000027032464,0.00013800495,0.000021404967,0.0003033747,0.0007773915,0.003041401,0.0034179732,0.00036156448,0.000016074126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016755707,0.000015889895,0.00014584699,0.00008142661,0.000011694746,0.0000011214896,0.0018168748,0.0011110876,0.00024599707,0.68108016,0.00007074376,0.3154175],"study_design_scores_gemma":[0.0001882819,0.000026044032,0.00056645623,0.00010976404,0.0000036759948,0.000058834892,0.000027851138,0.961628,0.00003033532,0.004849179,0.032275107,0.00023644253],"about_ca_topic_score_codex":0.000006596101,"about_ca_topic_score_gemma":7.38197e-7,"teacher_disagreement_score":0.9605169,"about_ca_system_score_codex":0.000105504136,"about_ca_system_score_gemma":0.00007934679,"threshold_uncertainty_score":0.56276786},"labels":[],"label_agreement":null},{"id":"W2970646592","doi":"10.1007/978-3-030-29238-6_10","title":"Empirical Analysis of Object-Oriented Metrics and Centrality Measures for Predicting Fault-Prone Classes in Object-Oriented Software","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Centrality; Computer science; Software metric; Software; Data mining; Object-oriented programming; Object (grammar); Software fault tolerance; Java; Software development; Artificial intelligence; Software quality; Programming language; Mathematics","score_opus":0.05846315919585426,"score_gpt":0.3387307878319006,"score_spread":0.2802676286360463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970646592","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006778946,0.0006204448,0.9898348,0.00019001408,0.0002335863,0.0008478082,0.00007447102,0.00011312934,0.0013068198],"genre_scores_gemma":[0.60329485,0.0018129572,0.39410207,0.00021244859,0.000024738116,0.00008094525,0.00021587643,0.00002028165,0.00023586626],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973414,0.00006357553,0.00097135146,0.00043032746,0.00083626504,0.00035705647],"domain_scores_gemma":[0.99410677,0.0026124716,0.0003787046,0.0018217254,0.0009575622,0.00012276635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022883012,0.00023749901,0.00053317787,0.0037722944,0.00022491663,0.0002703317,0.0020456987,0.00017482576,0.0000015644093],"category_scores_gemma":[0.0017978927,0.00023921828,0.000087920904,0.0034630147,0.0005548226,0.0029934149,0.00199211,0.00048450814,0.0000017364293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057521436,0.00024276033,0.4517023,0.0008064432,0.0004224592,0.0000014006512,0.019475542,0.02412357,0.000018884493,0.17337786,0.00030376323,0.3294675],"study_design_scores_gemma":[0.0005313394,0.00009507826,0.14318323,0.00019342262,0.000043380394,0.0000035249816,0.000051941966,0.84647816,0.000021978967,0.00031756947,0.0087925615,0.0002877914],"about_ca_topic_score_codex":0.00004560089,"about_ca_topic_score_gemma":0.00005046003,"teacher_disagreement_score":0.8223546,"about_ca_system_score_codex":0.0002711109,"about_ca_system_score_gemma":0.00049788255,"threshold_uncertainty_score":0.97550386},"labels":[],"label_agreement":null},{"id":"W2973421725","doi":"10.1007/978-3-030-30712-7_46","title":"Visual Exploration of Topic Controversy in Online Conversations","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Visualization; Data science; Online discussion; Work (physics); World Wide Web; Artificial intelligence; Engineering","score_opus":0.04436041703731572,"score_gpt":0.338240783602607,"score_spread":0.29388036656529126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973421725","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016095213,0.00014460675,0.94921005,0.0009210159,0.0001211262,0.00045066283,0.000010771186,0.00006517036,0.048915632],"genre_scores_gemma":[0.47776228,0.0055969018,0.51311535,0.0012302649,0.000035006524,0.000038663136,0.0002404348,0.000015095013,0.0019660208],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984603,0.000029429126,0.0007902213,0.00022060478,0.0003561053,0.00014336333],"domain_scores_gemma":[0.9974229,0.00022676842,0.00047210546,0.0014454224,0.0003921067,0.00004071346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057630765,0.00015416184,0.00030112383,0.0014804301,0.000095423835,0.00014054976,0.0019467912,0.00010200738,0.000004999123],"category_scores_gemma":[0.000054678858,0.00016394096,0.00004422139,0.0005808725,0.00046352774,0.011251553,0.0012574791,0.00029221177,0.000014564903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014316413,0.000027495707,0.00014938854,0.000017442866,0.000003693813,1.2726323e-7,0.0012297417,0.00055852707,0.000012380692,0.9015161,0.000023781608,0.09645993],"study_design_scores_gemma":[0.0005724682,0.00010726594,0.0021802841,0.00026885985,0.0000072951584,0.0000032495573,0.00008149534,0.93196374,0.00007633304,0.035525493,0.028879672,0.00033384404],"about_ca_topic_score_codex":0.000021139609,"about_ca_topic_score_gemma":0.000059912585,"teacher_disagreement_score":0.9314052,"about_ca_system_score_codex":0.00016868592,"about_ca_system_score_gemma":0.00029865868,"threshold_uncertainty_score":0.8157104},"labels":[],"label_agreement":null},{"id":"W2979049289","doi":"10.1007/978-3-030-41258-6_6","title":"Approximate GCD in Bernstein basis","year":2019,"lang":"en","type":"preprint","venue":"Communications in computer and information science","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Bipartite graph; Bernstein polynomial; Mathematics; Root (linguistics); Matching (statistics); Degree (music); Basis (linear algebra); Combinatorics; Discrete mathematics; Applied mathematics; Statistics; Graph; Physics; Geometry","score_opus":0.04903440410928161,"score_gpt":0.3396691884607903,"score_spread":0.2906347843515087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979049289","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029309855,0.00023193475,0.98899686,0.002045272,0.0006215765,0.00045078015,0.0000065723166,0.00007336855,0.0046426374],"genre_scores_gemma":[0.18318501,0.0009391988,0.8150602,0.0007181752,0.000015728941,0.000060602728,0.000011532079,0.0000036212275,0.0000059299036],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99795574,0.00017827273,0.0007361865,0.0003911209,0.0004122522,0.00032640347],"domain_scores_gemma":[0.99620676,0.0002834603,0.00028216484,0.0029378114,0.00019469419,0.00009509262],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0023886245,0.00019663954,0.00031335995,0.0010531738,0.00018130314,0.0009842402,0.0056048157,0.00011587431,0.0000020218777],"category_scores_gemma":[0.000099415935,0.00018815309,0.00004407288,0.0017922055,0.00042612883,0.0054872464,0.010789721,0.0007005621,0.000026297112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001302057,0.00006294575,0.0021473074,0.00007490056,0.0000024580697,4.1168292e-7,0.0031750372,0.00459079,0.0000062632894,0.06206281,0.0000357829,0.92784],"study_design_scores_gemma":[0.00021341312,0.000020328045,0.011922644,0.00016036148,0.0000010087407,0.000004938484,0.000032476764,0.9757204,0.000031932792,0.008126286,0.0035375846,0.00022860087],"about_ca_topic_score_codex":0.00010188399,"about_ca_topic_score_gemma":0.000006112801,"teacher_disagreement_score":0.97112966,"about_ca_system_score_codex":0.00015342017,"about_ca_system_score_gemma":0.00031314293,"threshold_uncertainty_score":0.99977535},"labels":[],"label_agreement":null},{"id":"W2984916732","doi":"10.1007/978-3-030-34866-3_1","title":"Optimal VNF Placement: Addressing Multiple Min-Cost Solutions","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Heuristic; Integer programming; Quality of service; Virtual network; Linear programming; Function (biology); Mathematical optimization; Computer network; Distributed computing; Algorithm; Mathematics; Artificial intelligence","score_opus":0.0827849293168979,"score_gpt":0.29626014100506504,"score_spread":0.21347521168816713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984916732","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000035255624,0.0013144589,0.8670754,0.00069360074,0.0006569563,0.00067020993,0.000028063521,0.0001723473,0.12935375],"genre_scores_gemma":[0.080774836,0.006962613,0.8966855,0.0037557797,0.0002450173,0.00016718707,0.00040414758,0.0000535477,0.010951378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979573,0.000032530043,0.00071557437,0.00037533362,0.0004974768,0.0004218053],"domain_scores_gemma":[0.996063,0.00046447944,0.00038907296,0.002594708,0.00035396413,0.00013480571],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010157934,0.00027455855,0.0002875019,0.00086938887,0.00088799844,0.0010401382,0.0037749966,0.00016487675,0.000013198417],"category_scores_gemma":[0.00005829966,0.00028048802,0.000067930385,0.0004963498,0.00067881745,0.0067798058,0.004114879,0.00054234284,0.00018780999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068909344,0.000049304464,0.00018806332,0.00006514803,0.000017519345,9.034386e-7,0.0031660853,0.026396032,0.000003666076,0.5790823,0.0056998893,0.38532418],"study_design_scores_gemma":[0.00035603446,0.0000338584,0.0005055539,0.00027699047,0.000004722799,0.000018248778,0.000013725407,0.72770274,0.0000027954384,0.0005685825,0.27021688,0.00029984725],"about_ca_topic_score_codex":0.000012523338,"about_ca_topic_score_gemma":0.000010214119,"teacher_disagreement_score":0.70130676,"about_ca_system_score_codex":0.00018691694,"about_ca_system_score_gemma":0.00056303036,"threshold_uncertainty_score":0.9999969},"labels":[],"label_agreement":null},{"id":"W2991832894","doi":"10.1007/978-3-030-36802-9_61","title":"Event Prediction in Complex Social Graphs via Feature Learning of Vertex Embeddings","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Vertex (graph theory); Event (particle physics); Computer science; Feature (linguistics); Artificial intelligence; Machine learning; Theoretical computer science; Graph; Physics; Astrophysics; Linguistics; Philosophy","score_opus":0.02425630440471985,"score_gpt":0.2851043032474795,"score_spread":0.2608479988427596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991832894","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00054498966,0.00034543735,0.92937875,0.0010716435,0.00050765387,0.00079997664,0.000016695556,0.00013697452,0.06719788],"genre_scores_gemma":[0.8935001,0.0015606289,0.102645606,0.0007410945,0.000035793502,0.000025616215,0.00019317186,0.000019798652,0.0012782161],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824774,0.000049194958,0.00069245754,0.00028899626,0.00048042968,0.00024115159],"domain_scores_gemma":[0.99791604,0.00017312418,0.0005434639,0.0010242489,0.00028911539,0.000054002754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071027974,0.0002125394,0.0003226774,0.0011993006,0.00031983844,0.00016492017,0.0024319182,0.00017368663,0.000004784131],"category_scores_gemma":[0.000021361284,0.0002244769,0.000069392714,0.0008475829,0.0006286308,0.0049322783,0.0017831753,0.00082003296,0.000013247639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061377827,0.000022172131,0.00059409253,0.000052241598,0.0000065071827,3.303363e-7,0.0030917497,0.008145055,0.00003159383,0.7510686,0.00048203915,0.23649949],"study_design_scores_gemma":[0.00035473958,0.000075197204,0.01381962,0.00019317126,0.0000033045453,0.000012902632,0.000019452013,0.9428949,0.0000046639466,0.019838005,0.022551391,0.00023266308],"about_ca_topic_score_codex":0.0000070525966,"about_ca_topic_score_gemma":0.000007737981,"teacher_disagreement_score":0.93474984,"about_ca_system_score_codex":0.00013151494,"about_ca_system_score_gemma":0.0001317798,"threshold_uncertainty_score":0.91539025},"labels":[],"label_agreement":null},{"id":"W2994962128","doi":"10.1007/978-981-15-1922-2_26","title":"Hybrid Machine Learning Models of Classifying Residential Requests for Smart Dispatching","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Naive Bayes classifier; Classifier (UML); Perceptron; Word embedding; Cluster analysis; Convolutional neural network; Benchmarking; Artificial neural network; Multilayer perceptron; Embedding; Support vector machine","score_opus":0.0672727803263816,"score_gpt":0.29967899170562595,"score_spread":0.23240621137924433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994962128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000083060484,0.00044307119,0.9543816,0.0009681039,0.00023627984,0.0004924823,0.00001832248,0.00016370091,0.043213405],"genre_scores_gemma":[0.5818003,0.00469442,0.4092362,0.00031771476,0.000028416765,0.00006565413,0.00019579957,0.000021234979,0.0036402778],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982836,0.000026949774,0.00078683376,0.0002966615,0.0003962695,0.00020967958],"domain_scores_gemma":[0.9968113,0.00032851266,0.00066668657,0.0017714464,0.0003745619,0.000047524252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011223096,0.00019254007,0.00028852597,0.0010474983,0.000398573,0.00046270422,0.0033293716,0.00010583066,0.0000024637022],"category_scores_gemma":[0.00008555186,0.00019361876,0.00006679618,0.00022947254,0.00053027226,0.0080346465,0.0023331442,0.00042393318,0.000010641746],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002617239,0.0000070605115,0.00006440476,0.00004883917,0.0000042102124,5.6915113e-8,0.00044077577,0.00074662006,0.000012543041,0.8737696,0.00008597284,0.12481732],"study_design_scores_gemma":[0.00026599455,0.000060229067,0.00018251473,0.0002059442,0.0000048791344,0.0000059684726,0.00001539961,0.88439053,0.00008935871,0.07935613,0.03520422,0.00021883332],"about_ca_topic_score_codex":0.00002053027,"about_ca_topic_score_gemma":0.000008261625,"teacher_disagreement_score":0.8836439,"about_ca_system_score_codex":0.00010842535,"about_ca_system_score_gemma":0.00028106206,"threshold_uncertainty_score":0.7895544},"labels":[],"label_agreement":null},{"id":"W2995095500","doi":"10.1007/978-3-030-36368-0_27","title":"Enhanced Priority-Based Routing Protocol (EPRP) for Inter-vehicular Communication","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Computer network; Routing protocol; Routing (electronic design automation); Link-state routing protocol; Vehicular communication systems; Mobility model; Protocol (science); Zone Routing Protocol; Wireless Routing Protocol; Vehicular ad hoc network; Distributed computing; Wireless ad hoc network; Wireless; Telecommunications","score_opus":0.020282118432233057,"score_gpt":0.2785355531754094,"score_spread":0.25825343474317636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995095500","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008629331,0.00013546013,0.84001595,0.0002542588,0.0002268913,0.033823844,0.000030535146,0.00030756617,0.12511922],"genre_scores_gemma":[0.4649323,0.0009211202,0.48279607,0.0019347745,0.00022496111,0.04590435,0.0013394813,0.00020350273,0.0017434545],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833363,0.000032711196,0.0008209117,0.00021443598,0.00029471584,0.0003035774],"domain_scores_gemma":[0.99659455,0.00030587328,0.00027932605,0.002337783,0.00039957624,0.00008286661],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012598631,0.00028523925,0.00032274963,0.0005493288,0.0003444368,0.00037615612,0.0019269845,0.00021198188,0.0000091048405],"category_scores_gemma":[0.00004348265,0.00031082693,0.00007940606,0.00024365296,0.00044270718,0.002406918,0.0007054101,0.0006071363,0.00004668073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017426575,0.000028660394,0.000031791697,0.00058816175,0.0000292721,1.3940388e-7,0.0014506971,0.58635205,0.00005871743,0.20787819,0.00051246036,0.20305245],"study_design_scores_gemma":[0.0005516346,0.000034498687,0.000074123505,0.0005586587,0.000007727058,0.0000024764774,0.0000100164025,0.8592826,0.00008171157,0.00085334294,0.13824749,0.00029567833],"about_ca_topic_score_codex":0.0000037859913,"about_ca_topic_score_gemma":0.000017625283,"teacher_disagreement_score":0.464846,"about_ca_system_score_codex":0.00031338405,"about_ca_system_score_gemma":0.00024828143,"threshold_uncertainty_score":0.9999344},"labels":[],"label_agreement":null},{"id":"W2995560424","doi":"10.1007/978-3-030-37584-3_5","title":"Modelling Alternative Staffing Scenarios for Workforce Rejuvenation","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence","funders":"","keywords":"Workforce; Staffing; Attrition; Workforce planning; Computer science; Work (physics); Service (business); Operations research; Operations management; Business; Mathematics; Engineering; Marketing; Economics; Management; Mechanical engineering; Medicine; Economic growth","score_opus":0.2322927041397261,"score_gpt":0.3985131027689909,"score_spread":0.16622039862926477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995560424","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019527538,0.00033808293,0.8843338,0.0010994258,0.0006126534,0.0006693533,0.00004930981,0.00004816634,0.112653926],"genre_scores_gemma":[0.296627,0.003296567,0.65864754,0.0019001196,0.00028250867,0.000118478434,0.0003315228,0.000053196283,0.038743075],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99702084,0.0000432636,0.0011751028,0.00040936953,0.0010584596,0.00029293433],"domain_scores_gemma":[0.9936384,0.0019526753,0.00075349864,0.0019317339,0.0016243361,0.00009936646],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0055376454,0.00021512443,0.00034553139,0.0018470262,0.0008030868,0.0011237859,0.0026829778,0.00015124683,0.000014940787],"category_scores_gemma":[0.0006985692,0.00019659464,0.00009982036,0.00065813866,0.00060243625,0.00514544,0.00093547034,0.00042184003,0.00016482465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059311506,0.000008565448,0.000017744616,0.0000061754704,0.0000048269467,3.3661774e-8,0.0012594713,0.42550257,5.3871497e-7,0.46828085,0.00023163606,0.10468165],"study_design_scores_gemma":[0.00023170843,0.000027622309,0.000017172297,0.0001518317,0.000006546894,0.0000029122948,0.00006098921,0.7924422,0.0000022760623,0.04755179,0.1593256,0.0001793553],"about_ca_topic_score_codex":0.0000174715,"about_ca_topic_score_gemma":0.00000841805,"teacher_disagreement_score":0.42072907,"about_ca_system_score_codex":0.00019616506,"about_ca_system_score_gemma":0.00054479454,"threshold_uncertainty_score":0.99991316},"labels":[],"label_agreement":null},{"id":"W2996363909","doi":"10.1007/978-3-030-37548-5_8","title":"Human Action Recognition Using Stereo Trajectories","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Trajectory; Set (abstract data type); Action (physics); Fuse (electrical); Action recognition; Engineering; Class (philosophy)","score_opus":0.1440951576846861,"score_gpt":0.3403771328969136,"score_spread":0.19628197521222754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996363909","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062248246,0.00022846437,0.52940786,0.0005115321,0.0018282733,0.0012120005,0.000047163994,0.0003934187,0.4601465],"genre_scores_gemma":[0.60220665,0.0048143133,0.37643,0.00422655,0.0006322635,0.0000910833,0.000930799,0.00008510444,0.01058324],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984076,0.000038294667,0.00063413876,0.0003033328,0.00040760633,0.00020905488],"domain_scores_gemma":[0.99761575,0.00007747128,0.00044215296,0.0013540733,0.00043351733,0.00007702761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006590839,0.00022108044,0.00023041204,0.0012508378,0.0006688028,0.0008474665,0.0015162732,0.00015859357,0.000031695534],"category_scores_gemma":[0.000013892976,0.00023975063,0.00005532274,0.0003562227,0.00040124537,0.012326954,0.00090414967,0.00044188584,0.00018909229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027774963,0.000032536616,0.000038066613,0.000086212305,0.00001293102,4.8478853e-7,0.0017139751,0.000105201434,0.00009454441,0.2880121,0.00020053751,0.70970064],"study_design_scores_gemma":[0.0015624036,0.0003413687,0.0038634648,0.0014956344,0.000050060462,0.00019511288,0.00017803376,0.7201903,0.00042807433,0.08653042,0.1831799,0.0019852526],"about_ca_topic_score_codex":0.000020097601,"about_ca_topic_score_gemma":0.00001776499,"teacher_disagreement_score":0.7200851,"about_ca_system_score_codex":0.00022888486,"about_ca_system_score_gemma":0.0002737309,"threshold_uncertainty_score":0.9776747},"labels":[],"label_agreement":null},{"id":"W2996447623","doi":"10.1007/978-3-030-37484-6_3","title":"NewYouthHack: Using Design Thinking to Reimagine Settlement Services for New Canadians","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Persona Design and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brampton Civic Hospital; McMaster University","funders":"","keywords":"Outreach; Computer science; World Wide Web; Software; Process (computing); Iterative and incremental development; Online community; User story; Iterative design; Software engineering; Software development; Engineering; Programming language; Political science","score_opus":0.07748648024417958,"score_gpt":0.3086448030610213,"score_spread":0.23115832281684173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996447623","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000006368721,0.00015561926,0.97480845,0.0049420753,0.00018489972,0.0011367748,0.000045165198,0.00006672083,0.018653922],"genre_scores_gemma":[0.0014926572,0.00018102097,0.9908745,0.0053919475,0.000055080858,0.000036087844,0.00006500783,0.000011630576,0.0018920389],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984434,0.000018435907,0.00052102027,0.0003470761,0.00036612377,0.00030390808],"domain_scores_gemma":[0.9970456,0.00018923981,0.0002452615,0.0019758935,0.00031910941,0.00022494102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009227696,0.00022020804,0.00022551038,0.00089425617,0.00057387364,0.000932872,0.0041278754,0.0000847307,0.000004200287],"category_scores_gemma":[0.00001239509,0.00023335245,0.000043962296,0.00045919357,0.00014604964,0.0038571153,0.0013916912,0.00021092533,0.00005638847],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028122106,0.000008935115,0.0000124862,0.000041798343,0.0000086126,1.3150103e-7,0.0073028305,0.005316729,0.00003601733,0.86415195,0.0017994216,0.12131825],"study_design_scores_gemma":[0.0002208504,0.00004009507,0.00007714412,0.00020315344,0.0000075103694,0.000009050847,0.00003875048,0.76010793,0.000012483697,0.011615668,0.22737236,0.0002950165],"about_ca_topic_score_codex":0.00036122144,"about_ca_topic_score_gemma":0.00013835171,"teacher_disagreement_score":0.8525363,"about_ca_system_score_codex":0.00028299977,"about_ca_system_score_gemma":0.001267183,"threshold_uncertainty_score":0.9515837},"labels":[],"label_agreement":null},{"id":"W2997520214","doi":"10.1007/978-981-15-1956-7_15","title":"A Conditional VAE-Based Conversation Model","year":2019,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Conversation; Computer science; Sequence (biology); Artificial intelligence; Block (permutation group theory); Latent variable; Domain (mathematical analysis); Encoder; Autoencoder; Natural language processing; Machine learning; Artificial neural network; Psychology; Mathematics; Communication","score_opus":0.056409538974410145,"score_gpt":0.2836610419750884,"score_spread":0.22725150300067826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997520214","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000019876848,0.0000643336,0.8888806,0.0015330757,0.00017775425,0.00029483627,0.000014559793,0.00007685917,0.10893808],"genre_scores_gemma":[0.2497546,0.00040046766,0.74196136,0.005217277,0.00004175441,0.000035401656,0.00025211665,0.000013730285,0.0023233036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998395,0.000019156803,0.0005645108,0.00029911316,0.0005329836,0.00018921442],"domain_scores_gemma":[0.9969427,0.00016842759,0.00030282835,0.0020982148,0.0004085492,0.000079276964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000785747,0.00018403266,0.00019765532,0.00087878166,0.00025905995,0.00047614623,0.0027603004,0.00012608354,0.000009391834],"category_scores_gemma":[0.000024948811,0.00019791818,0.000044661563,0.00022611607,0.00046790228,0.00631591,0.001291379,0.00034958404,0.00011725987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.8871974e-7,0.0000065014838,0.00001643566,0.000017727449,0.0000020574444,9.098993e-8,0.00061648246,0.04139134,0.000001695775,0.9285108,0.000103769526,0.02933222],"study_design_scores_gemma":[0.00028587205,0.000017609946,0.00011506719,0.00008165956,0.0000025849704,0.0000046762348,0.0000047584376,0.9560933,0.000005146157,0.029009713,0.014173903,0.00020570932],"about_ca_topic_score_codex":0.0000049469845,"about_ca_topic_score_gemma":0.0000027899887,"teacher_disagreement_score":0.91470194,"about_ca_system_score_codex":0.00019822267,"about_ca_system_score_gemma":0.0009882445,"threshold_uncertainty_score":0.80708694},"labels":[],"label_agreement":null},{"id":"W2997789040","doi":"10.1007/978-3-030-37873-8_6","title":"Umple-TL: A Model-Oriented, Dependency-Free Text Emission Tool","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Executable; Dependency (UML); Independence (probability theory); Java; Programming language; Artificial intelligence; Mathematics","score_opus":0.06432300757104473,"score_gpt":0.31129012170659237,"score_spread":0.24696711413554764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997789040","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008646812,0.00028781182,0.962659,0.0011339764,0.00024093808,0.0003016797,0.000014762789,0.00036609152,0.034987092],"genre_scores_gemma":[0.0024078134,0.0011760932,0.9948866,0.0007605836,0.00002543087,0.000027074488,0.000022526716,0.000012262437,0.00068166765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99790186,0.00003995476,0.0007420449,0.00042389726,0.0006060756,0.0002861908],"domain_scores_gemma":[0.99507594,0.0005139329,0.0003141132,0.0036071553,0.00034376356,0.00014506525],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0010367746,0.00029942725,0.0003244366,0.00069689576,0.0004152466,0.0003883306,0.006280215,0.00016312688,0.0000030924612],"category_scores_gemma":[0.00064341305,0.00030012676,0.0000599651,0.00055010564,0.00053706125,0.007539799,0.0074547115,0.00068813824,0.000036324123],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025284323,0.000007004489,0.000006192635,0.00003221553,0.0000037416964,8.164403e-7,0.0013738257,0.023864813,0.000011343593,0.7756744,0.00033232252,0.19869077],"study_design_scores_gemma":[0.00022638697,0.000038793358,0.0000490154,0.00014052523,0.0000034827613,0.000020619294,0.000009157597,0.8452266,0.000028545755,0.1179753,0.035931196,0.00035041722],"about_ca_topic_score_codex":0.0000027042108,"about_ca_topic_score_gemma":0.0000014669964,"teacher_disagreement_score":0.8213617,"about_ca_system_score_codex":0.00018276155,"about_ca_system_score_gemma":0.0003749479,"threshold_uncertainty_score":0.9999451},"labels":[],"label_agreement":null},{"id":"W3006779249","doi":"10.1007/978-3-030-41258-6_29","title":"Distributive Laws Between the Operads $${{\\,\\mathrm{\\textit{Lie}}\\,}}$$ and $${{\\,\\mathrm{\\textit{Com}}\\,}}$$","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Topics in Algebra","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Distributive property; Associative property; Lie algebra; Commutative property; Mathematics; Pure mathematics; Polynomial; Associative algebra; Algebra over a field; Universal enveloping algebra; Algebra representation; Division algebra; Mathematical analysis","score_opus":0.09013123938269249,"score_gpt":0.35101090844793964,"score_spread":0.2608796690652472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006779249","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018118267,0.002047331,0.47004288,0.019640084,0.00078075007,0.0033810202,0.0008475862,0.00051674753,0.50093174],"genre_scores_gemma":[0.50106746,0.018301351,0.46219724,0.0076742233,0.00095128926,0.0003244827,0.0013654103,0.00024929908,0.0078692725],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99741405,0.000077441655,0.0011144114,0.00041352058,0.0006316623,0.00034891535],"domain_scores_gemma":[0.9952075,0.0012555651,0.00059203274,0.0023785022,0.00037433032,0.0001920657],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012508046,0.00043114967,0.00056829763,0.0003528471,0.0011382853,0.00059089804,0.002893891,0.00023049544,0.000026726768],"category_scores_gemma":[0.00036275506,0.00035386434,0.00007959999,0.0004085259,0.002627451,0.0030392502,0.003907058,0.0011253392,0.000079514335],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002734879,0.000011221171,0.000065065615,0.000054502038,0.000018425066,5.6014767e-7,0.0022599616,0.000004802999,0.0000013838953,0.94568396,0.0005149084,0.05138249],"study_design_scores_gemma":[0.00050908007,0.00008746547,0.0012220825,0.00032710496,0.000055856715,0.00004376209,0.00013988139,0.010585253,0.000023821089,0.6979089,0.28846437,0.0006324485],"about_ca_topic_score_codex":0.000006578375,"about_ca_topic_score_gemma":0.000008704468,"teacher_disagreement_score":0.49925563,"about_ca_system_score_codex":0.00021194575,"about_ca_system_score_gemma":0.0002058192,"threshold_uncertainty_score":0.99989134},"labels":[],"label_agreement":null},{"id":"W3006785504","doi":"10.1007/978-3-030-41258-6_28","title":"Polynomial Factorization in Maple 2019","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Polynomial and algebraic computation","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Maple; Factorization; Polynomial; Factoring; Factorization of polynomials; Integer (computer science); Mathematics; Algebra over a field; Discrete mathematics; Computer science; Algorithm; Pure mathematics; Matrix polynomial; Botany; Biology; Programming language","score_opus":0.027239480163130693,"score_gpt":0.26152158392730496,"score_spread":0.23428210376417427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006785504","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016327623,0.0004357756,0.82395566,0.005676512,0.0009745646,0.0007279695,0.000026076632,0.00020087238,0.16783932],"genre_scores_gemma":[0.78206944,0.003839111,0.20469198,0.0056458283,0.00035248054,0.00006280826,0.00045132806,0.000039444094,0.002847602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829066,0.000032073975,0.0007292582,0.0003358652,0.00038879464,0.00022334531],"domain_scores_gemma":[0.9981617,0.00014628316,0.0002934273,0.001126758,0.00015171853,0.00012015091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052369584,0.0002184838,0.00026125787,0.001036317,0.00022482255,0.0005758485,0.0027439506,0.00012384758,0.000005795259],"category_scores_gemma":[0.000042950996,0.00023325448,0.00004070838,0.0006471825,0.00034550138,0.0067705587,0.0022357204,0.00042895335,0.000111165056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000047330204,0.000019812323,0.000114409835,0.00002546494,0.0000038096948,0.0000010031677,0.0028246278,0.0006446702,0.0000144139285,0.5576233,0.0018288892,0.4368948],"study_design_scores_gemma":[0.00059451675,0.000076628305,0.0056452905,0.00017376067,0.0000031018442,0.000012836774,0.000011563461,0.76802295,0.000021936175,0.011422854,0.21352033,0.00049424684],"about_ca_topic_score_codex":0.000038257436,"about_ca_topic_score_gemma":0.000022645603,"teacher_disagreement_score":0.7819061,"about_ca_system_score_codex":0.00021228117,"about_ca_system_score_gemma":0.00039778827,"threshold_uncertainty_score":0.95118415},"labels":[],"label_agreement":null},{"id":"W3006798337","doi":"10.1007/978-3-030-41258-6_30","title":"Classifying Discrete Structures by Their Stabilizers","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Thesaurus; Information retrieval; Artificial intelligence","score_opus":0.044780773188207126,"score_gpt":0.2818069300396792,"score_spread":0.2370261568514721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006798337","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000030753403,0.0009028716,0.84615326,0.005691623,0.00019225513,0.00026002023,0.00015397185,0.00014454284,0.1464707],"genre_scores_gemma":[0.5478621,0.01584161,0.41998658,0.012225425,0.00013067717,0.00005955599,0.0011075364,0.0000305886,0.002755913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983872,0.000033048174,0.00058248173,0.00035745944,0.00042294196,0.0002168396],"domain_scores_gemma":[0.9972802,0.00025023945,0.0002988174,0.00184252,0.00016913917,0.00015910272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005232955,0.000224658,0.00029681003,0.0007237108,0.0004500749,0.0008490802,0.004851808,0.00011092305,0.000020778461],"category_scores_gemma":[0.00007892222,0.0001763222,0.000065635584,0.0009890937,0.000986928,0.0054918933,0.0040073125,0.00045872203,0.00002927166],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.593073e-7,0.0000043047053,0.00002332853,0.000009105783,0.000007452877,1.9012715e-7,0.00054754945,0.000043021166,0.000002399766,0.7796754,0.0009996119,0.21868674],"study_design_scores_gemma":[0.00020939905,0.00007046503,0.00051577884,0.00004470766,0.000008647472,0.0000085050715,0.00005406125,0.2785572,0.000016484577,0.07302455,0.6470482,0.00044202083],"about_ca_topic_score_codex":0.000012675066,"about_ca_topic_score_gemma":0.0000036274846,"teacher_disagreement_score":0.7066509,"about_ca_system_score_codex":0.00008513832,"about_ca_system_score_gemma":0.00012638865,"threshold_uncertainty_score":0.90159464},"labels":[],"label_agreement":null},{"id":"W3007199277","doi":"10.1007/978-3-030-41258-6_2","title":"The LegendreSobolev Package and Its Applications in Handwriting Recognition","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Handwriting; Computer science; Speech recognition; Natural language processing; Artificial intelligence","score_opus":0.0467617885166808,"score_gpt":0.2857479680374212,"score_spread":0.2389861795207404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007199277","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015405718,0.0038209432,0.71906495,0.0070986804,0.00017166723,0.002388272,0.00006904148,0.00043984634,0.26679257],"genre_scores_gemma":[0.49957314,0.10341672,0.38602975,0.0067759994,0.00027267498,0.0016270858,0.0005952554,0.00008285129,0.0016265298],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99830186,0.000055048728,0.0007388083,0.0003343764,0.00034074453,0.0002291735],"domain_scores_gemma":[0.99758464,0.00056091824,0.00031554844,0.0010915952,0.00033379233,0.00011351907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011733169,0.0002098238,0.00021458016,0.0006528271,0.0008162543,0.0010258383,0.002323407,0.00012258759,0.0000024451545],"category_scores_gemma":[0.00010358354,0.00018877424,0.00003313182,0.0005878648,0.00057179114,0.004913025,0.0020862517,0.00056863145,0.00005124412],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.9156634e-7,0.0000065955905,0.000013584072,0.00002271247,0.0000020362274,2.9941666e-7,0.0007372142,0.0000013164312,0.000008788721,0.43655723,0.000052502775,0.5625968],"study_design_scores_gemma":[0.0009737979,0.0001698653,0.002034713,0.0011372346,0.000017312397,0.000107125015,0.00028637293,0.4049899,0.0008573351,0.20532803,0.3827217,0.0013766141],"about_ca_topic_score_codex":0.000006061989,"about_ca_topic_score_gemma":0.000026091673,"teacher_disagreement_score":0.56122017,"about_ca_system_score_codex":0.0000961205,"about_ca_system_score_gemma":0.00016732581,"threshold_uncertainty_score":0.9892183},"labels":[],"label_agreement":null},{"id":"W3007372112","doi":"10.1007/978-3-030-41258-6_10","title":"The Z_Polyhedra Library in Maple","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Polynomial and algebraic computation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Polyhedron; Maple; Integer (computer science); Computer science; Presburger arithmetic; Parametric statistics; Combinatorics; Discrete mathematics; Mathematics; Theoretical computer science; Programming language","score_opus":0.026015036108191895,"score_gpt":0.2513998400193202,"score_spread":0.2253848039111283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007372112","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000100196674,0.0021034048,0.2693701,0.03877434,0.0009984812,0.000874882,0.00001583248,0.00032317388,0.68743956],"genre_scores_gemma":[0.50938267,0.030182851,0.4187567,0.027336506,0.00059089495,0.0002302929,0.00028219342,0.00008491237,0.013152969],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99852645,0.00003644777,0.0006395137,0.00024800308,0.00033031582,0.00021927753],"domain_scores_gemma":[0.99785256,0.0003578735,0.00023386726,0.0013867117,0.000067960165,0.000101015474],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005569592,0.00017495807,0.0001807263,0.000512681,0.00048628027,0.0011563636,0.0043607857,0.00007694512,0.0000034013774],"category_scores_gemma":[0.000034606444,0.00014485233,0.000038303762,0.00060367456,0.000630528,0.007818243,0.0037748667,0.00045564506,0.00008663315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012125697,0.0000035326964,0.000018329303,0.00000570811,0.0000011538955,3.7722123e-7,0.0006969964,0.00006756134,4.9915514e-7,0.69705445,0.0004489791,0.30170122],"study_design_scores_gemma":[0.00019935488,0.00003155974,0.0015915217,0.000096165306,0.0000011797972,0.000009739062,0.000012172919,0.5212069,0.00000724023,0.070710145,0.40591773,0.000216241],"about_ca_topic_score_codex":0.000009110339,"about_ca_topic_score_gemma":0.000013819978,"teacher_disagreement_score":0.6742866,"about_ca_system_score_codex":0.000072266725,"about_ca_system_score_gemma":0.00037993756,"threshold_uncertainty_score":0.99988055},"labels":[],"label_agreement":null},{"id":"W3007772440","doi":"10.1007/978-3-030-41590-7_20","title":"Robustifying Direct VO to Large Baseline Motions","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Initialization; Computer science; Artificial intelligence; Odometry; Process (computing); Frame (networking); Heuristic; Baseline (sea); Feature (linguistics); Motion (physics); Computer vision; Robot","score_opus":0.03664899484932066,"score_gpt":0.2584013098097654,"score_spread":0.22175231496044473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007772440","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014200925,0.0001474449,0.83208704,0.0005574483,0.00020765937,0.00025023156,0.00004960964,0.00015101967,0.16653535],"genre_scores_gemma":[0.5848258,0.008620948,0.3955979,0.0067455885,0.00032836205,0.00008687745,0.0015140808,0.00011319391,0.0021672007],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901617,0.000012755167,0.00045568627,0.00013556736,0.00022164852,0.00015815439],"domain_scores_gemma":[0.9987951,0.00007426624,0.000061034632,0.0007513643,0.00019177789,0.00012648622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043547992,0.00015677851,0.00017667317,0.000576527,0.00027303846,0.0002234309,0.00066947733,0.00007888709,0.000015052625],"category_scores_gemma":[0.000056386878,0.00017260302,0.000028362423,0.00038777688,0.00012244214,0.0012429787,0.00040855393,0.00026018088,0.00009445043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.779608e-7,0.000008822023,0.00001958026,0.0000656437,0.0000070761594,3.3066473e-7,0.0010687788,0.7739754,0.000011283977,0.17984582,0.0016967965,0.043299507],"study_design_scores_gemma":[0.00008690968,0.000011845554,0.0001296428,0.000105313426,0.0000047548724,0.0000015382569,0.000011121942,0.8663635,0.0000066339753,0.00019943967,0.13291574,0.00016352617],"about_ca_topic_score_codex":0.0000028088848,"about_ca_topic_score_gemma":0.000011621149,"teacher_disagreement_score":0.5848116,"about_ca_system_score_codex":0.0001059182,"about_ca_system_score_gemma":0.00005621574,"threshold_uncertainty_score":0.7038547},"labels":[],"label_agreement":null},{"id":"W3008382057","doi":"10.1007/978-3-030-41258-6_16","title":"Using Maple to Make Manageable Matrices","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Algebraic and Geometric Analysis","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Maple; Algebra over a field; Computer science; Set (abstract data type); Subject (documents); Matrix (chemical analysis); Linear algebra; Symbolic computation; Computation; Basis (linear algebra); Rational function; Mathematics; Theoretical computer science; Algorithm; Pure mathematics; Programming language; World Wide Web","score_opus":0.13238275306092206,"score_gpt":0.35357981608961897,"score_spread":0.2211970630286969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008382057","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000103642145,0.00033366034,0.5663237,0.0012168349,0.00009491212,0.00039967147,0.000020686197,0.00007006825,0.43143684],"genre_scores_gemma":[0.026243899,0.0019053057,0.9594947,0.002979489,0.00008929234,0.000019143708,0.00005684524,0.000025479394,0.009185806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99864274,0.0000145400645,0.0005855006,0.00018742314,0.00040622658,0.000163577],"domain_scores_gemma":[0.9979994,0.00023755114,0.00028194595,0.0011317179,0.00022882885,0.000120497534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069874094,0.00016532911,0.00028449667,0.0013876603,0.00035934517,0.00028544507,0.0014366612,0.00008300236,0.00004312353],"category_scores_gemma":[0.00012488077,0.00016260635,0.000050771385,0.0011372885,0.0002903336,0.0013985613,0.0017154432,0.00024663945,0.00012160713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001895816,0.000008172859,0.000029273506,0.00006263672,0.000014936343,4.1256084e-7,0.001132483,0.00020899904,4.1781453e-7,0.9321403,0.0012044952,0.06519596],"study_design_scores_gemma":[0.00024920312,0.000050880564,0.00017361251,0.0002805843,0.000079613565,0.000017209852,0.00020143058,0.34581783,0.000003418642,0.18590972,0.46664932,0.00056716695],"about_ca_topic_score_codex":0.000017234417,"about_ca_topic_score_gemma":0.000009022726,"teacher_disagreement_score":0.7462306,"about_ca_system_score_codex":0.00011906942,"about_ca_system_score_gemma":0.00011611503,"threshold_uncertainty_score":0.6630894},"labels":[],"label_agreement":null},{"id":"W3008660402","doi":"10.1007/978-3-030-41258-6_11","title":"Detecting Singularities Using the PowerSeries Library","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Quantum chaos and dynamical systems","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Gravitational singularity; Singularity theory; Cusp (singularity); Singularity; Bifurcation; Dimension (graph theory); Type (biology); Mathematics; Pitchfork bifurcation; Computer science; Bifurcation theory; Pure mathematics; Mathematical analysis; Geometry; Physics; Nonlinear system","score_opus":0.03416458581455816,"score_gpt":0.2644960092872502,"score_spread":0.23033142347269203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008660402","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020160154,0.00047644472,0.13692757,0.0020158037,0.00045366204,0.00056143355,0.00007291933,0.000092682414,0.8573835],"genre_scores_gemma":[0.98726004,0.000067950416,0.01145709,0.00044793266,0.00013865736,0.000007420994,0.000052522835,0.000010896859,0.00055747054],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927104,0.000017080953,0.00034900126,0.00010016361,0.00015654451,0.00010620161],"domain_scores_gemma":[0.9990422,0.00010786095,0.00018909188,0.0005585113,0.000057984562,0.00004433557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020220687,0.000114370705,0.00013648873,0.00012742248,0.0005711378,0.0005531898,0.0008123677,0.000034261877,0.000023949562],"category_scores_gemma":[0.0000048554684,0.000088836765,0.00003639161,0.00014511052,0.0006488931,0.0027343866,0.00097447983,0.00028350935,0.00000972173],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011115102,0.0000026416199,0.0002892701,0.000012979798,0.0000051070097,4.923747e-8,0.0014827604,0.0001563771,0.0000025587299,0.9647614,0.000034561646,0.03325118],"study_design_scores_gemma":[0.00015418482,0.000026461072,0.0002832133,0.00028523628,0.000010938442,0.0000052564706,0.0007597836,0.7973283,0.000015962109,0.049170095,0.15164196,0.0003186367],"about_ca_topic_score_codex":0.00002991158,"about_ca_topic_score_gemma":0.0000013150859,"teacher_disagreement_score":0.98524404,"about_ca_system_score_codex":0.000019004412,"about_ca_system_score_gemma":0.00011434549,"threshold_uncertainty_score":0.5334422},"labels":[],"label_agreement":null},{"id":"W3009864101","doi":"10.1007/978-981-15-3380-8_27","title":"Genre-ous: The Movie Genre Detector","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Film genre; Computer science; Natural language processing; Artificial intelligence; Natural (archaeology); Linguistics; Literature; Art; History; Philosophy; Movie theater","score_opus":0.06717658756664655,"score_gpt":0.2998178060410262,"score_spread":0.23264121847437966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009864101","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000023983575,0.0010323436,0.8384513,0.008403372,0.00047821214,0.00053094665,0.000019419798,0.00019308127,0.1508673],"genre_scores_gemma":[0.37590805,0.011443108,0.56655705,0.03734245,0.0004965716,0.00020771487,0.00025948594,0.000064323365,0.007721263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99822825,0.00006464728,0.0006539678,0.00029993363,0.0005088815,0.00024433402],"domain_scores_gemma":[0.99661726,0.0002879915,0.00034455286,0.0022811228,0.00032619797,0.0001428674],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0013649446,0.00022543305,0.00022130409,0.00039918174,0.00090351765,0.00086776586,0.0055513317,0.00013158571,0.000012250229],"category_scores_gemma":[0.00009202389,0.0001798175,0.000064910826,0.00059925456,0.0007811715,0.004152996,0.0035382977,0.00071118237,0.00023316323],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012156129,0.0000036543559,0.000014694441,0.0000143321895,0.0000042332795,3.821724e-7,0.0020354083,0.00007249495,0.00000350023,0.809213,0.0002527818,0.18838431],"study_design_scores_gemma":[0.00019974109,0.000049096267,0.0007436575,0.000102047066,0.000006880545,0.000033387078,0.000043475342,0.5745452,0.000037165995,0.0148026375,0.40905163,0.00038507214],"about_ca_topic_score_codex":0.00000620296,"about_ca_topic_score_gemma":0.000005149542,"teacher_disagreement_score":0.79441035,"about_ca_system_score_codex":0.00011745119,"about_ca_system_score_gemma":0.00036247837,"threshold_uncertainty_score":0.9998291},"labels":[],"label_agreement":null},{"id":"W3013518738","doi":"10.1007/978-3-030-43823-4_38","title":"Deep Generative Multi-view Learning","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Generative grammar; Computer science; Artificial intelligence; Representation (politics); Generative model; Deep learning; Artificial neural network; Machine learning; Deep neural networks; Noise (video); Nonlinear system","score_opus":0.04984219845483839,"score_gpt":0.2814629641844362,"score_spread":0.23162076572959783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013518738","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[7.63567e-7,0.0008304794,0.9174146,0.001563247,0.00020296553,0.00024465995,0.0000020509362,0.00007596757,0.07966524],"genre_scores_gemma":[0.023128668,0.006545483,0.9659844,0.0027265744,0.000104265215,0.00002903468,0.000044894314,0.00001340389,0.001423265],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845386,0.0000755473,0.00057075196,0.00034675884,0.00033890194,0.00021415892],"domain_scores_gemma":[0.99781984,0.0001633613,0.00031575825,0.0011964735,0.0003685254,0.00013602847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006570084,0.00024423804,0.00029409246,0.00043286246,0.00067225914,0.00082725653,0.0028044712,0.000099623,0.000010863421],"category_scores_gemma":[0.000081052225,0.0002371842,0.000056889905,0.00042641224,0.00062021654,0.0061185453,0.0027826685,0.0005656057,0.00011784946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012120523,0.000011876264,0.000021196956,0.000017752165,0.000011183373,8.543191e-7,0.0030789995,0.011770566,0.0000072434273,0.49024683,0.00023777469,0.4945945],"study_design_scores_gemma":[0.00015117231,0.000036474838,0.00013494634,0.00006715918,0.0000037666543,0.00000566691,0.0000146428,0.84971744,0.0000127671055,0.0014144272,0.14821114,0.00023038936],"about_ca_topic_score_codex":0.0000050311073,"about_ca_topic_score_gemma":0.0000097137,"teacher_disagreement_score":0.8379469,"about_ca_system_score_codex":0.00009679335,"about_ca_system_score_gemma":0.00020881616,"threshold_uncertainty_score":0.9672091},"labels":[],"label_agreement":null},{"id":"W3013694547","doi":"10.1007/978-3-030-44900-1_10","title":"Using Twitter Streams for Opinion Mining: A Case Study on Airport Noise","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroDevNet","funders":"","keywords":"Computer science; Sentiment analysis; Support vector machine; Lexicon; Classifier (UML); Artificial intelligence; Natural language processing","score_opus":0.19790706520709853,"score_gpt":0.3833335053465498,"score_spread":0.18542644013945128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013694547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040323455,0.00017711631,0.9553034,0.0014286652,0.0008948472,0.001770293,0.000016973978,0.00014114969,0.03623525],"genre_scores_gemma":[0.5426859,0.0002870535,0.4532358,0.0028259219,0.00021858966,0.000098089804,0.00010977208,0.000029529774,0.00050928],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998121,0.00003214457,0.00077989395,0.00041587648,0.00044784628,0.00020318782],"domain_scores_gemma":[0.997159,0.00021918591,0.00046843314,0.001729263,0.0003005687,0.00012351753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090035994,0.00024970825,0.00031795623,0.0009376477,0.0006249826,0.00077251776,0.0019896557,0.00008080746,0.0000032543383],"category_scores_gemma":[0.000030449664,0.0002430041,0.000084139036,0.0004531462,0.00024333416,0.0031893677,0.001589255,0.00024134519,0.00001393424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000270857,0.00039012692,0.0023811331,0.0001160583,0.00014436268,0.000047422614,0.059306003,0.0041247737,0.000011040195,0.37253594,0.0023660804,0.55854994],"study_design_scores_gemma":[0.00052879646,0.00024674367,0.00014428978,0.0001436337,0.000015368141,0.00010409305,0.0006968621,0.9735457,0.0000041235,0.00045207914,0.023795322,0.00032303474],"about_ca_topic_score_codex":0.000019130308,"about_ca_topic_score_gemma":0.000004594449,"teacher_disagreement_score":0.9694209,"about_ca_system_score_codex":0.000106605024,"about_ca_system_score_gemma":0.00021273155,"threshold_uncertainty_score":0.990942},"labels":[],"label_agreement":null},{"id":"W3019994833","doi":"10.1007/978-3-030-46902-3_1","title":"Formal Verification of Cyber-Physical Systems Using Theorem Proving","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Cyber-physical system; Avionics; Computer science; Aerospace; Automotive industry; Systems engineering; Reliability (semiconductor); Automated theorem proving; Software engineering; Computer security; Engineering","score_opus":0.0750023494951009,"score_gpt":0.32315307202799637,"score_spread":0.24815072253289547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3019994833","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026357232,0.0001756911,0.9284294,0.00013933676,0.00033599883,0.00057278277,0.00001258521,0.000087769935,0.06998283],"genre_scores_gemma":[0.25840348,0.00036365207,0.7408396,0.00015345274,0.00006985048,0.00002926044,0.000033558765,0.000014451682,0.00009267051],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99777424,0.00008049876,0.00095533906,0.0003270798,0.0006209223,0.00024192806],"domain_scores_gemma":[0.9960218,0.00017239823,0.00088623556,0.002260502,0.0005513421,0.000107731044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016274432,0.00023945406,0.00036633646,0.00074970245,0.00037063492,0.00045193286,0.0036473356,0.00012901313,9.786532e-7],"category_scores_gemma":[0.00011031462,0.00024163938,0.00006268806,0.0006426997,0.0009385669,0.0113157015,0.002222858,0.0004348349,0.000018174884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027908586,0.000012244773,0.000008646234,0.00007256279,0.0000042586316,9.3930915e-8,0.0019455898,0.001169437,0.000068645844,0.9258392,0.000006921607,0.07086962],"study_design_scores_gemma":[0.00014609814,0.000063698346,0.00023955894,0.00020628261,0.000008067818,0.000018155493,0.00003907615,0.9858714,0.0001302369,0.006046086,0.006989596,0.0002417839],"about_ca_topic_score_codex":0.000015835229,"about_ca_topic_score_gemma":5.5736155e-7,"teacher_disagreement_score":0.98470193,"about_ca_system_score_codex":0.0001995265,"about_ca_system_score_gemma":0.00040412147,"threshold_uncertainty_score":0.98537683},"labels":[],"label_agreement":null},{"id":"W3033643657","doi":"10.1007/978-3-030-50146-4_53","title":"Feature Extraction with TF-IDF and Game-Theoretic Shadowed Sets","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"tf–idf; Computer science; Weighting; Zipf's law; Word (group theory); Set (abstract data type); Artificial intelligence; Feature (linguistics); Natural language processing; Information retrieval; Pattern recognition (psychology); Data mining; Machine learning; Mathematics; Statistics; Term (time); Linguistics","score_opus":0.021668961438360276,"score_gpt":0.25822920016229645,"score_spread":0.23656023872393617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033643657","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001969605,0.0009880163,0.764078,0.009435642,0.00018398042,0.0005477214,0.000016082562,0.00019425049,0.2243593],"genre_scores_gemma":[0.39845523,0.006087066,0.58941984,0.0031995743,0.00009298675,0.00003983437,0.0001436017,0.00003227953,0.0025295916],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873734,0.000023775212,0.0003597615,0.0003224198,0.0003741477,0.00018255993],"domain_scores_gemma":[0.99791515,0.000121081095,0.00035062424,0.0012256538,0.00025710306,0.0001303759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050239166,0.00021836287,0.000256772,0.0004891603,0.00042461758,0.000957376,0.0016058045,0.00010511092,0.0000067111046],"category_scores_gemma":[0.00002525347,0.00018674746,0.000033968394,0.00048768183,0.00081644655,0.0056198207,0.0014921633,0.00047784953,0.000019304396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048969946,0.0000062354875,0.00003979529,0.000032845113,0.0000098114815,0.0000011083738,0.0019415729,0.00018160316,0.0000030523938,0.72018754,0.00017251709,0.27741903],"study_design_scores_gemma":[0.00025929578,0.00012110346,0.0012494818,0.00022082802,0.00001667467,0.00010887385,0.000050355404,0.870604,0.0000055433443,0.006811945,0.12019248,0.00035941257],"about_ca_topic_score_codex":0.0000056769873,"about_ca_topic_score_gemma":0.00000973357,"teacher_disagreement_score":0.8704224,"about_ca_system_score_codex":0.000062086016,"about_ca_system_score_gemma":0.00013924885,"threshold_uncertainty_score":0.9231999},"labels":[],"label_agreement":null},{"id":"W3033726942","doi":"10.1007/978-3-030-50146-4_31","title":"Image-Based World-perceiving Knowledge Graph (WpKG) with Imprecision","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Knowledge graph; Computer science; Graph; Image (mathematics); Artificial intelligence; Psychology; Computer vision; Theoretical computer science","score_opus":0.03483505764970996,"score_gpt":0.31481331812448,"score_spread":0.27997826047477004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033726942","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000041073777,0.0003552919,0.8587051,0.0008180635,0.00008063553,0.0003522005,0.0000057270186,0.0002417015,0.13943718],"genre_scores_gemma":[0.016758285,0.0012350855,0.9798783,0.0014128404,0.000033467593,0.000031579002,0.00003222285,0.00001677069,0.0006014277],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819183,0.000036533078,0.0006319782,0.00041530366,0.00047043138,0.0002539079],"domain_scores_gemma":[0.99634224,0.00032589273,0.0003395674,0.0022273422,0.00060423143,0.00016073126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00072762906,0.0002998653,0.0003153585,0.001486274,0.00051363977,0.0008729557,0.0039379573,0.00008731501,0.000006522723],"category_scores_gemma":[0.000056637116,0.00026372465,0.00005928598,0.001336354,0.0010027733,0.009681345,0.0023226608,0.0006073578,0.00005935417],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009817771,0.000027171334,0.00002526506,0.000060131395,0.0000056004274,0.0000019016228,0.0014542196,0.00005315442,0.000034001558,0.25744835,0.0005609239,0.7403195],"study_design_scores_gemma":[0.0007458767,0.00035870945,0.0010945862,0.0012366695,0.000014131678,0.00003357175,0.000018635128,0.66540986,0.00049864675,0.028279103,0.30126634,0.0010438733],"about_ca_topic_score_codex":0.0000047915582,"about_ca_topic_score_gemma":0.000013645786,"teacher_disagreement_score":0.73927563,"about_ca_system_score_codex":0.00014507561,"about_ca_system_score_gemma":0.000417776,"threshold_uncertainty_score":0.9999815},"labels":[],"label_agreement":null},{"id":"W3037911116","doi":"10.1007/978-3-030-49559-6_2","title":"HCC-Learn Framework for Hybrid Learning in Recommender Systems","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Computer science; Preprocessor; Recommender system; Cluster analysis; Data pre-processing; Collaborative filtering; Machine learning; Artificial intelligence; Data mining; Supervised learning; Process (computing); Artificial neural network","score_opus":0.06415892099595029,"score_gpt":0.3111709289076554,"score_spread":0.24701200791170513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037911116","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000037138407,0.00045912017,0.9142178,0.0031117708,0.00046145022,0.00078101415,0.000007675882,0.0002018958,0.080755524],"genre_scores_gemma":[0.12408073,0.0047112517,0.8664213,0.0027258163,0.00015955973,0.00039385416,0.00010521886,0.000038959166,0.001363322],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979245,0.000072986375,0.0009768279,0.000394857,0.0003426008,0.00028823232],"domain_scores_gemma":[0.9970182,0.00055543444,0.0004940511,0.0015486693,0.00026729988,0.0001163261],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016918487,0.0002597285,0.0004320463,0.00095748046,0.00039495062,0.001060098,0.0033450555,0.00016362139,0.000002248264],"category_scores_gemma":[0.00011153844,0.0002668654,0.000064359825,0.00042034962,0.0002441577,0.004467658,0.0020490212,0.0008753508,0.000022461561],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015123644,0.000008278053,0.00004033486,0.00006547123,0.0000040630466,3.1286143e-7,0.0009952125,0.00018952024,3.111658e-7,0.86806065,0.0006841614,0.12995018],"study_design_scores_gemma":[0.00019266046,0.000081529135,0.000082375576,0.00050238904,0.0000021273106,0.00001640144,0.00004043225,0.5148174,0.0000042859965,0.037864503,0.4460969,0.00029898976],"about_ca_topic_score_codex":0.000028335082,"about_ca_topic_score_gemma":0.000005042124,"teacher_disagreement_score":0.83019614,"about_ca_system_score_codex":0.0002031089,"about_ca_system_score_gemma":0.00022897458,"threshold_uncertainty_score":0.99997836},"labels":[],"label_agreement":null},{"id":"W3043034578","doi":"10.1007/978-981-15-6634-9_4","title":"An Effective Vision Based Framework for the Identification of Tuberculosis in Chest X-Ray Images","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Identification (biology); Computer science; Support vector machine; Tuberculosis; Artificial intelligence; Convolutional neural network; Artificial neural network; Machine learning; Random forest; Software; Pattern recognition (psychology); Medicine; Pathology","score_opus":0.03502254041768277,"score_gpt":0.3669911098178975,"score_spread":0.33196856940021474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043034578","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005942995,0.00064507115,0.9433519,0.04875823,0.00027017333,0.0039524906,0.00009344145,0.00007329041,0.0022610773],"genre_scores_gemma":[0.89756596,0.0011982209,0.09311899,0.007604106,0.000048859867,0.00024990478,0.00017300826,0.00001629526,0.00002463152],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986594,0.000038969974,0.00069492863,0.00020058347,0.0003034098,0.0001027248],"domain_scores_gemma":[0.9957347,0.002001429,0.0003715076,0.0014107827,0.00042540248,0.0000561836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014814687,0.00013636494,0.00024917306,0.0006145332,0.00021080163,0.00014645231,0.0008378675,0.00011621524,0.0000044492763],"category_scores_gemma":[0.0005096032,0.00011320211,0.00005426713,0.0003643,0.00073782227,0.001355049,0.00026264388,0.00035158536,0.000005620188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012833289,0.00030151752,0.0011819428,0.0010369577,0.00003406683,3.9487023e-7,0.008663322,0.009767254,0.00072319905,0.12326828,0.000776885,0.8541179],"study_design_scores_gemma":[0.00067758316,0.00027545347,0.08919731,0.001299053,0.000055632583,0.0000016098761,0.0000743924,0.8783477,0.00055989885,0.0033342922,0.025983706,0.00019337275],"about_ca_topic_score_codex":0.00002246255,"about_ca_topic_score_gemma":0.000007645696,"teacher_disagreement_score":0.8969717,"about_ca_system_score_codex":0.0001473526,"about_ca_system_score_gemma":0.00021029265,"threshold_uncertainty_score":0.4616248},"labels":[],"label_agreement":null},{"id":"W3043611503","doi":"10.1007/978-981-15-6648-6_21","title":"A Method for Malware Detection in Virtualization Environment","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Malware; Computer science; Cryptovirology; Evasion (ethics); Virtual machine; Virtualization; Computer security; Process (computing); Function (biology); Hardware virtualization; Malware analysis; Obfuscation; Operating system; TRACE (psycholinguistics); Hypervisor; Cloud computing","score_opus":0.03346983843170452,"score_gpt":0.30853296483881093,"score_spread":0.2750631264071064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043611503","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016142246,0.00009535368,0.9905088,0.00067658554,0.00010587094,0.000798465,0.00001101143,0.00016808225,0.0076342323],"genre_scores_gemma":[0.0071921353,0.0010972623,0.9903808,0.0008659896,0.000022445252,0.00020111818,0.000033471522,0.0000117478485,0.00019498437],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839157,0.00004014672,0.00068913883,0.00038231365,0.00031426377,0.00018258652],"domain_scores_gemma":[0.9979279,0.00022562324,0.0003551272,0.0012462988,0.00016757408,0.00007745541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089891005,0.00020850747,0.00024096337,0.0010948355,0.00026701123,0.00027309035,0.0018495874,0.00014425986,0.0000029536338],"category_scores_gemma":[0.00006035882,0.0002359725,0.000045358232,0.0004438413,0.00023958327,0.005400154,0.0014635953,0.00033590168,0.000016454884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003578315,0.0000071087693,0.0000021132057,0.000022934,0.0000015763042,1.457742e-7,0.00061461655,0.0007900415,0.000025709398,0.3537648,0.000018972167,0.6447484],"study_design_scores_gemma":[0.00027077363,0.00011811321,0.00015704035,0.00008653292,0.0000028923291,0.000012115278,0.000013631177,0.7787249,0.0004387877,0.028730905,0.1911661,0.00027819787],"about_ca_topic_score_codex":0.000009146015,"about_ca_topic_score_gemma":0.000017304337,"teacher_disagreement_score":0.77793485,"about_ca_system_score_codex":0.00033763488,"about_ca_system_score_gemma":0.00011256617,"threshold_uncertainty_score":0.96226794},"labels":[],"label_agreement":null},{"id":"W3047483491","doi":"10.1007/978-3-642-10236-3","title":"Advances in Communication and Networking","year":2009,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science","score_opus":0.018582458592588346,"score_gpt":0.2759144739307259,"score_spread":0.25733201533813754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047483491","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000044283097,0.021835456,0.46263233,0.002001456,0.00030860282,0.0012254199,0.0000021023318,0.00017601957,0.51177436],"genre_scores_gemma":[0.060380947,0.38829923,0.5418983,0.0070103197,0.00014762413,0.00025799073,0.00019469291,0.000024728697,0.0017861532],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812406,0.00012333284,0.00073538604,0.00032743422,0.00038722297,0.00030255417],"domain_scores_gemma":[0.99645704,0.0003210273,0.0003709014,0.0026262584,0.00013984987,0.0000849066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018934753,0.00021568457,0.00026160805,0.0011369296,0.0003826703,0.00076946215,0.0039706617,0.00009751807,0.0000013264536],"category_scores_gemma":[0.00001797273,0.00023219657,0.000023514178,0.0011673372,0.0006200963,0.010511388,0.0035349017,0.00048718398,0.000010382457],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010060671,0.000012223677,0.00008628494,0.00002277763,9.61698e-7,3.3472972e-7,0.0007875915,0.0014287732,6.18664e-8,0.13789384,0.0007281876,0.85903794],"study_design_scores_gemma":[0.00023127696,0.000030228193,0.0013873645,0.0003701886,0.0000020431119,0.000005971883,0.000013520582,0.57658064,3.4831214e-7,0.012558836,0.40860647,0.00021307949],"about_ca_topic_score_codex":0.000010945828,"about_ca_topic_score_gemma":0.00006692689,"teacher_disagreement_score":0.8588249,"about_ca_system_score_codex":0.00037012316,"about_ca_system_score_gemma":0.00028465112,"threshold_uncertainty_score":0.94687015},"labels":[],"label_agreement":null},{"id":"W3050298219","doi":"10.1007/978-3-030-55814-7_2","title":"Extraction of a Knowledge Graph from French Cultural Heritage Documents","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Cultural heritage; Knowledge graph; Information extraction; Graph; Christian ministry; Relationship extraction; Knowledge extraction; Information retrieval; Context (archaeology); World Wide Web; Natural language processing; Artificial intelligence; Geography; Archaeology; Political science","score_opus":0.03249528905846527,"score_gpt":0.3237258388079702,"score_spread":0.2912305497495049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3050298219","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014167014,0.006085885,0.85968924,0.00090122694,0.0004048399,0.0004875528,0.00003778583,0.0003360738,0.1319157],"genre_scores_gemma":[0.14958884,0.0017087287,0.8478704,0.00034004342,0.000032414187,0.000017338505,0.00007825401,0.0000068464465,0.00035710752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99861115,0.000029186445,0.0006133361,0.0002616723,0.0003495566,0.00013508515],"domain_scores_gemma":[0.9975988,0.00014067184,0.00045103487,0.0013073314,0.0004232622,0.000078864745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037892236,0.00018894255,0.00024615135,0.00055267866,0.00021840265,0.0004301168,0.0034764884,0.00012481055,0.0000064754067],"category_scores_gemma":[0.000046035024,0.00017576663,0.00004945327,0.0005044939,0.0005793802,0.008816239,0.0022838,0.00044731845,0.000020821039],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021433389,0.00002613098,0.000039302067,0.000058163507,0.000010491288,6.9594086e-7,0.006583922,0.000007058778,0.00018151346,0.6858807,0.00068550266,0.30652437],"study_design_scores_gemma":[0.0010107341,0.00026958395,0.0023335645,0.0019318205,0.0000353058,0.000053957225,0.00011544593,0.35591453,0.0015986004,0.45555508,0.17963763,0.0015437601],"about_ca_topic_score_codex":0.00006418809,"about_ca_topic_score_gemma":0.00001264648,"teacher_disagreement_score":0.35590747,"about_ca_system_score_codex":0.000094091054,"about_ca_system_score_gemma":0.00017150551,"threshold_uncertainty_score":0.7167555},"labels":[],"label_agreement":null},{"id":"W3082381687","doi":"10.1007/978-3-030-58793-2_27","title":"Accountability in the A Posteriori Access Control: A Requirement and a Mechanism","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Access Control and Trust","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Accountability; Audit; A priori and a posteriori; Mechanism (biology); Access control; Control (management); Process (computing); Computer science; Business; Process management; Accounting; Computer security; Political science; Artificial intelligence; Law; Programming language; Epistemology","score_opus":0.08247380949723399,"score_gpt":0.3661989638761433,"score_spread":0.28372515437890933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082381687","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018931837,0.00086088,0.01780098,0.042919945,0.00039056953,0.0029092082,0.00005697206,0.000087469336,0.9330808],"genre_scores_gemma":[0.99304706,0.0015914412,0.00083568273,0.004356782,0.000040567724,0.000049472263,0.00000872239,0.0000031057675,0.000067138535],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986051,0.000105141626,0.00046574615,0.00017978594,0.00047103505,0.00017322288],"domain_scores_gemma":[0.9985434,0.00031447498,0.00021951347,0.0006693172,0.0001849311,0.000068370864],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0025107053,0.00012694682,0.00019988506,0.00027274273,0.000730162,0.0011412896,0.002280436,0.00008924662,0.000012063422],"category_scores_gemma":[0.000101129466,0.0001012224,0.000024966626,0.00029674367,0.0012923088,0.005285835,0.0009731273,0.00032753558,0.000007867802],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000930999,0.00000943243,0.0003143624,0.000013173429,0.0000027618769,2.7539667e-7,0.017868198,0.0000028525997,4.5783736e-7,0.9149854,0.000022425926,0.06677135],"study_design_scores_gemma":[0.003309171,0.00021687958,0.05942565,0.0005796018,0.000061024086,0.00001693733,0.0055590994,0.07972481,0.0000015250039,0.29805195,0.5519062,0.0011471133],"about_ca_topic_score_codex":0.00053858635,"about_ca_topic_score_gemma":0.0010508763,"teacher_disagreement_score":0.9911539,"about_ca_system_score_codex":0.00011406215,"about_ca_system_score_gemma":0.0002984358,"threshold_uncertainty_score":0.99989563},"labels":[],"label_agreement":null},{"id":"W3088025856","doi":"10.1007/978-981-15-9031-3_16","title":"Key Nodes Recognition in Opportunistic Network","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geomechanica (Canada)","funders":"","keywords":"Computer science; Key (lock); Computer network; Cache; Routing (electronic design automation); Focus (optics); Distributed computing; Computer security","score_opus":0.08039091138959764,"score_gpt":0.27574760584098,"score_spread":0.19535669445138237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088025856","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000067461783,0.00023247417,0.6885218,0.0012937046,0.00032457893,0.0002805639,0.000014721026,0.00008400856,0.3092414],"genre_scores_gemma":[0.34364903,0.016884694,0.62202144,0.013907536,0.00043993158,0.00011602775,0.00092485826,0.00004773754,0.002008719],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99787194,0.00004799042,0.00094815006,0.00037313954,0.00043734928,0.0003214346],"domain_scores_gemma":[0.99732125,0.00029217402,0.0003924188,0.0015356285,0.0002591433,0.0001993742],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011705143,0.0002594596,0.00034969763,0.0006192418,0.00034502978,0.0006284406,0.0028107304,0.00017229574,0.000014957151],"category_scores_gemma":[0.000020067564,0.00027685612,0.000046907888,0.0006551907,0.00065066636,0.0046744877,0.002209719,0.00064887595,0.00011859671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028874192,0.000009940244,0.000033307737,0.000018447667,0.0000027686563,0.0000037989298,0.0006490199,0.00016963923,1.570933e-7,0.48325968,0.0005567995,0.51529354],"study_design_scores_gemma":[0.00023702816,0.000040236475,0.00023650251,0.00031529024,0.0000046366886,0.000026117148,0.000010806812,0.8974148,1.9284388e-7,0.043914527,0.057481032,0.00031882312],"about_ca_topic_score_codex":0.0000106136085,"about_ca_topic_score_gemma":0.000012683727,"teacher_disagreement_score":0.89724517,"about_ca_system_score_codex":0.00012563678,"about_ca_system_score_gemma":0.0004835868,"threshold_uncertainty_score":0.99996835},"labels":[],"label_agreement":null},{"id":"W3092057871","doi":"10.1007/978-3-030-61834-6_3","title":"IRBASIR-B: Rule Induction from Similarity Relations, a Bayesian Approach","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Similarity (geometry); Computer science; Bayesian probability; Rule induction; Set (abstract data type); Bayes' theorem; Data mining; Artificial intelligence; Scheme (mathematics); Construct (python library); Process (computing); Algorithm; Pattern recognition (psychology); Machine learning; Mathematics","score_opus":0.0524866287513743,"score_gpt":0.2628876335784501,"score_spread":0.21040100482707577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092057871","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014675361,0.00027173728,0.65471673,0.0021037732,0.00022259686,0.00029909413,0.000026836866,0.00013320018,0.34221137],"genre_scores_gemma":[0.04408935,0.0011703802,0.9516941,0.0022421088,0.00010250089,0.00003304184,0.00033105034,0.000012306121,0.00032518723],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980358,0.000051562383,0.00072517345,0.00045317487,0.000518365,0.0002159642],"domain_scores_gemma":[0.9968683,0.00014922181,0.0003812897,0.002210374,0.0002307671,0.00016005138],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006790593,0.000256878,0.00029275724,0.00060189946,0.00065657205,0.00088166096,0.0034717997,0.00021441301,0.000012890601],"category_scores_gemma":[0.000045476037,0.0002546735,0.000060556227,0.00060220354,0.0006218667,0.0074332715,0.002554255,0.00075041514,0.000097208984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027166009,0.000026096715,0.00008361198,0.000013462524,0.000008175862,4.362178e-7,0.0022547492,0.00030804303,0.0000010008386,0.7226139,0.000786852,0.27390096],"study_design_scores_gemma":[0.0002277552,0.000043794087,0.0022763016,0.00006238324,0.000007284498,0.000010820178,0.000028380613,0.8466963,0.0000014890529,0.059572335,0.09073137,0.00034179856],"about_ca_topic_score_codex":0.000037254114,"about_ca_topic_score_gemma":0.000004542482,"teacher_disagreement_score":0.8463882,"about_ca_system_score_codex":0.00016265766,"about_ca_system_score_gemma":0.00029766938,"threshold_uncertainty_score":0.9999905},"labels":[],"label_agreement":null},{"id":"W3101086974","doi":"10.1007/978-3-030-60703-6_66","title":"Development of a Non-Immersive VR Reminiscence Therapy Experience for Patients with Dementia","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Identity, Memory, and Therapy","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Shores Centre for Mental Health Sciences; Ontario Tech University","funders":"","keywords":"Reminiscence; Dementia; Headset; Perception; Recall; Psychology; Virtual reality; Psychotherapist; Neurocognitive; Medicine; Computer science; Multimedia; Cognitive psychology; Cognition; Human–computer interaction; Psychiatry; Neuroscience","score_opus":0.05153153755000751,"score_gpt":0.33299386825112115,"score_spread":0.28146233070111365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3101086974","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04035741,0.0014743744,0.39928985,0.00064455945,0.0019272257,0.005784503,0.000120930425,0.00008168333,0.55031943],"genre_scores_gemma":[0.8055705,0.0013451403,0.19050126,0.0013160746,0.00004280593,0.00026616637,0.00022749188,0.00002494935,0.0007056483],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988023,0.000012027401,0.00054778194,0.00020081924,0.00028551946,0.00015155238],"domain_scores_gemma":[0.9982058,0.000079956546,0.0004233026,0.00080431317,0.0004289839,0.000057669546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003001106,0.0001574657,0.00020588902,0.00032026815,0.00031838962,0.000076441815,0.0012092727,0.00007043451,0.000028452438],"category_scores_gemma":[0.00000897231,0.0001421056,0.000029310138,0.00018395376,0.0006650132,0.0010925372,0.00028930797,0.00014521537,0.000017287859],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002075845,0.00022576797,0.0040391283,0.000088207446,0.000121647194,2.3612364e-7,0.20409714,0.0000097811935,0.000033645512,0.123924956,0.00036448965,0.6668874],"study_design_scores_gemma":[0.007055659,0.0012554248,0.13301568,0.0008945048,0.00004510645,0.0000062973336,0.003391145,0.00545182,0.000438326,0.001992262,0.8449701,0.0014836779],"about_ca_topic_score_codex":0.0000053305275,"about_ca_topic_score_gemma":0.0000064246747,"teacher_disagreement_score":0.8446056,"about_ca_system_score_codex":0.000043205408,"about_ca_system_score_gemma":0.0001978379,"threshold_uncertainty_score":0.5794898},"labels":[],"label_agreement":null},{"id":"W3101277380","doi":"10.1007/978-3-030-60703-6_67","title":"Neural Correlates of Mental Workload in Virtual Flight Simulation","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Workload; Neural correlates of consciousness; Computer science; Psychology; Operating system; Neuroscience; Cognition","score_opus":0.05341586985852496,"score_gpt":0.36838071101445213,"score_spread":0.31496484115592716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3101277380","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005823993,0.00051750883,0.02406405,0.0019896373,0.002155224,0.0010328892,0.00006752036,0.00013207643,0.9642171],"genre_scores_gemma":[0.9970145,0.00022023711,0.0008285943,0.0005083703,0.000022700982,0.000013123489,0.00008834302,0.0000065885347,0.0012974952],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849665,0.00004924552,0.000904872,0.00017047311,0.0002579537,0.000120779034],"domain_scores_gemma":[0.9984213,0.00027537099,0.00040850532,0.00066710915,0.00016878378,0.00005890962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004051116,0.00014859339,0.00022513395,0.0008111946,0.0001520421,0.00008739573,0.00073873176,0.0001242085,0.00031918343],"category_scores_gemma":[0.000034487264,0.00015593803,0.000043327134,0.00029936287,0.0005139175,0.0020099916,0.0004272941,0.00042455122,0.00018449956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006207642,0.00006899128,0.0011648521,0.000022710155,0.000017916787,7.2649624e-7,0.031902414,0.014027134,0.0000051413085,0.6466508,0.00052547845,0.30555174],"study_design_scores_gemma":[0.0006684722,0.00009383262,0.016037818,0.00023162241,0.000005478348,0.000008601433,0.00033826559,0.9256026,0.0000025436968,0.0009133322,0.05586927,0.00022815782],"about_ca_topic_score_codex":0.000010455456,"about_ca_topic_score_gemma":0.000012770685,"teacher_disagreement_score":0.99119055,"about_ca_system_score_codex":0.00010233524,"about_ca_system_score_gemma":0.000065146574,"threshold_uncertainty_score":0.6358968},"labels":[],"label_agreement":null},{"id":"W3103085915","doi":"10.1007/978-3-030-63820-7_43","title":"Edge Curve Estimation by the Nonparametric Parzen Kernel Method","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Nonparametric statistics; Kernel density estimation; Kernel (algebra); Kernel smoother; Variable kernel density estimation; Mathematics; Kernel method; Statistics; Pattern recognition (psychology); Artificial intelligence; Computer science; Radial basis function kernel; Combinatorics; Support vector machine","score_opus":0.032010283646224734,"score_gpt":0.31452655781584665,"score_spread":0.28251627416962194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3103085915","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000010251814,0.00037699638,0.8986541,0.0028626057,0.00015515994,0.00040541234,0.000012435353,0.00018577448,0.09734649],"genre_scores_gemma":[0.0138166305,0.0024777309,0.9741333,0.0072820424,0.000057011697,0.00010809553,0.00007682227,0.00001834419,0.0020299803],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982151,0.00008290758,0.0006659711,0.00032041324,0.0005103758,0.00020527067],"domain_scores_gemma":[0.99661624,0.0004513473,0.00042000104,0.002073315,0.00034429049,0.00009478467],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016135081,0.00023309683,0.00024240678,0.0007788804,0.0006580362,0.0010986491,0.004380987,0.00012986235,0.000006466395],"category_scores_gemma":[0.00013360866,0.00019196775,0.00006115156,0.0011294526,0.0005641693,0.006285104,0.0023680977,0.0006295697,0.00009526192],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010965907,0.000007925142,0.0000018902185,0.000013288414,0.0000044293142,1.8551525e-7,0.00086701725,0.00007783504,0.0000038810836,0.17014863,0.0050289747,0.82384485],"study_design_scores_gemma":[0.0001292271,0.000060110888,0.00008718069,0.000053141142,0.0000061380974,0.000030063526,0.000009509784,0.7563978,0.00043110046,0.018015977,0.22451979,0.0002599992],"about_ca_topic_score_codex":0.000041039428,"about_ca_topic_score_gemma":0.000003239925,"teacher_disagreement_score":0.82358485,"about_ca_system_score_codex":0.00015702532,"about_ca_system_score_gemma":0.00021721018,"threshold_uncertainty_score":0.9999383},"labels":[],"label_agreement":null},{"id":"W3104762188","doi":"10.1007/978-3-030-60703-6_82","title":"A Language-Oriented Analysis of Situation Awareness in Pilots in High-Fidelity Flight Simulation","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Fidelity; Aeronautics; High fidelity; Computer science; Flight simulator; Aerospace engineering; Psychology; Engineering; Simulation; Telecommunications; Electrical engineering","score_opus":0.058079623542616865,"score_gpt":0.39929169509874374,"score_spread":0.3412120715561269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3104762188","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18480667,0.0005090203,0.36626583,0.002799553,0.0017396671,0.0026599017,0.00033728828,0.00028311645,0.44059896],"genre_scores_gemma":[0.99693334,0.000089966765,0.0018449476,0.00034626707,0.000012974156,0.00002521642,0.00048803704,0.000005368978,0.0002539081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979084,0.0001104631,0.0012730018,0.00024485667,0.00033021366,0.00013307479],"domain_scores_gemma":[0.99771476,0.000364131,0.0005695978,0.00095633545,0.00034182024,0.000053361902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094739656,0.00015862598,0.00039185892,0.003047889,0.00010900354,0.000068480855,0.00062917115,0.00013843986,0.00022086348],"category_scores_gemma":[0.000099967205,0.00017226643,0.000058334466,0.0016325006,0.00027629203,0.0018031832,0.00030974025,0.00035775095,0.000048184273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010206807,0.00021544358,0.012434337,0.000081581275,0.00012564947,0.0000020291727,0.08207779,0.116368,0.000021959946,0.68904537,0.00010018954,0.09942555],"study_design_scores_gemma":[0.0005493878,0.000029529181,0.2763836,0.0001091261,0.000030343408,7.5656664e-7,0.00035114645,0.71772444,0.0000032423695,0.00052910595,0.004118441,0.00017086683],"about_ca_topic_score_codex":0.00034819037,"about_ca_topic_score_gemma":0.0007334179,"teacher_disagreement_score":0.81212664,"about_ca_system_score_codex":0.00021093104,"about_ca_system_score_gemma":0.00012230813,"threshold_uncertainty_score":0.7024821},"labels":[],"label_agreement":null},{"id":"W3108900336","doi":"10.1007/978-3-030-63119-2_65","title":"Textual Clustering: Towards a More Efficient Descriptors of Texts","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Cluster analysis; Hierarchical clustering; Computer science; Medoid; Artificial intelligence; Data mining; Artificial neural network; Document clustering; Pattern recognition (psychology); Brown clustering; Information retrieval; Correlation clustering; Canopy clustering algorithm","score_opus":0.04596565457403039,"score_gpt":0.2916378477862309,"score_spread":0.24567219321220052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108900336","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003420446,0.00020430713,0.86874527,0.002021539,0.00013163305,0.00035129153,0.00006475504,0.0000914664,0.1283555],"genre_scores_gemma":[0.10350668,0.00094516523,0.893097,0.0015619607,0.00005673586,0.00005813618,0.00014504183,0.000017493148,0.00061180355],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824256,0.000015643145,0.0007379434,0.000319895,0.0004950445,0.0001889289],"domain_scores_gemma":[0.99695873,0.00008959917,0.0003853607,0.0020664544,0.00036242927,0.00013742459],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057745853,0.00020628565,0.00027804295,0.00062741037,0.00028720315,0.00040826516,0.004271391,0.000092049624,0.000004210089],"category_scores_gemma":[0.000049357393,0.00020411576,0.000051117386,0.0006016084,0.0009492383,0.0024727536,0.0042171343,0.00032824837,0.000033289256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010384848,0.000019218183,0.0000047033536,0.000029412216,0.000004596202,2.2996565e-7,0.0020828145,0.00048305793,0.000005443648,0.533292,0.00028114382,0.46379638],"study_design_scores_gemma":[0.00016794584,0.000048699254,0.0005037547,0.00014799109,0.0000048071806,0.000013700563,0.00005465217,0.92007077,0.000019281933,0.0008452828,0.07790112,0.0002220008],"about_ca_topic_score_codex":0.0000190049,"about_ca_topic_score_gemma":0.0000031002294,"teacher_disagreement_score":0.91958773,"about_ca_system_score_codex":0.000089761365,"about_ca_system_score_gemma":0.00037295648,"threshold_uncertainty_score":0.8323599},"labels":[],"label_agreement":null},{"id":"W3114683363","doi":"10.1007/978-3-030-66039-0_3","title":"Risk Forecasting Automation on the Basis of MEHARI","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Information and Cyber Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Risk analysis (engineering); Computer science; Value (mathematics); Point (geometry); Risk assessment; Automation; Risk management; Operations research; Computer security; Business; Engineering; Finance; Machine learning; Mathematics","score_opus":0.057722829977289294,"score_gpt":0.2694411044824062,"score_spread":0.21171827450511693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114683363","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015930456,0.00007894439,0.39019224,0.0052582794,0.000286854,0.00058780087,0.00003372344,0.00012730042,0.60327554],"genre_scores_gemma":[0.80197656,0.00227478,0.18709199,0.007920404,0.000079596255,0.00006879732,0.00009362624,0.00001921252,0.00047504166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982605,0.000053726544,0.00079847116,0.00017651853,0.00056070264,0.00015008134],"domain_scores_gemma":[0.99659747,0.0004555407,0.00079085137,0.0016927208,0.00039341996,0.00007001113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001500259,0.00017806224,0.00020699816,0.00055322924,0.0005659352,0.00042191852,0.003267307,0.000089930865,0.000011518627],"category_scores_gemma":[0.0001790779,0.00014060375,0.000060348357,0.0005346705,0.00054989156,0.0049281893,0.001663219,0.000504327,0.00006839798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011478177,0.000005243967,0.000012774359,0.000013487951,0.0000036823153,5.186929e-8,0.0033056082,0.00015660544,3.2927136e-7,0.8609259,0.0002491356,0.13532603],"study_design_scores_gemma":[0.00014517177,0.00005565013,0.00073667313,0.00013474454,0.000004927274,0.0000059135486,0.0000395943,0.9472989,0.00004813709,0.014275336,0.03708146,0.00017347721],"about_ca_topic_score_codex":0.00001105351,"about_ca_topic_score_gemma":0.000004813885,"teacher_disagreement_score":0.9471423,"about_ca_system_score_codex":0.00008129373,"about_ca_system_score_gemma":0.00021108588,"threshold_uncertainty_score":0.60715234},"labels":[],"label_agreement":null},{"id":"W3118287326","doi":"10.1007/978-3-030-66196-0_17","title":"Design of a Biochemistry Procedure-Oriented Ontology","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Waterloo","funders":"","keywords":"Ontology; Computer science; Completeness (order theory); Subsequence; Cardinality (data modeling); Domain (mathematical analysis); Information retrieval; Decidability; Abstraction; Programming language; Theoretical computer science; Data mining; Mathematics","score_opus":0.037791606998318024,"score_gpt":0.29444910720483736,"score_spread":0.25665750020651934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118287326","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016146593,0.004191654,0.8335646,0.0031201642,0.0003609641,0.0009733481,0.00007160908,0.000078750934,0.15602426],"genre_scores_gemma":[0.49313152,0.007986672,0.4918715,0.0031903957,0.00015814413,0.000080260645,0.0007154398,0.000029505212,0.0028365478],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999213,0.000015001061,0.00036228888,0.00016767651,0.00014010223,0.00010195733],"domain_scores_gemma":[0.9988697,0.000039574534,0.00020597664,0.0006494585,0.00017815376,0.000057095695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029033737,0.000114833936,0.00016376057,0.00013626297,0.00008420894,0.000022451572,0.00077859755,0.00018579658,0.0000030789915],"category_scores_gemma":[0.00013570729,0.00010935603,0.000024433553,0.00011134915,0.001311412,0.00002722268,0.00073968264,0.00016774354,0.000004421765],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024119113,0.00016555368,0.00053330284,0.00073327904,0.00013498362,0.0000020877972,0.0041820677,0.00053833803,0.022386156,0.14017417,0.00835459,0.8225543],"study_design_scores_gemma":[0.00184369,0.0013547922,0.0010164537,0.00067204674,0.000048385344,0.00013094334,0.00023591555,0.106998466,0.015550247,0.0039364006,0.8670187,0.0011939848],"about_ca_topic_score_codex":0.0000019665824,"about_ca_topic_score_gemma":0.0000012203707,"teacher_disagreement_score":0.8586641,"about_ca_system_score_codex":0.000017038179,"about_ca_system_score_gemma":0.00031303987,"threshold_uncertainty_score":0.4831952},"labels":[],"label_agreement":null},{"id":"W3118569766","doi":"10.1007/978-3-030-62800-0_11","title":"A Comparison of Indoor Positioning Approaches with UWB, IMU, WiFi and Magnetic Fingerprinting","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Inertial measurement unit; Computer science; Dead reckoning; RSS; Real-time computing; Inertial navigation system; Indoor positioning system; Signal strength; Trajectory; Global Positioning System; Accelerometer; Inertial frame of reference; Wireless; Artificial intelligence; Telecommunications; Physics","score_opus":0.0440098426428637,"score_gpt":0.2540633953285481,"score_spread":0.2100535526856844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118569766","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069333035,0.0037957742,0.5273633,0.00075692625,0.00016252541,0.0009805659,0.00003399827,0.0006240832,0.4593495],"genre_scores_gemma":[0.95468044,0.0005560973,0.044620026,0.00004739566,0.000007371326,0.000010881462,0.000027859864,0.000009053963,0.000040853207],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991607,0.00000682579,0.00044062387,0.000113006645,0.00017304996,0.00010580413],"domain_scores_gemma":[0.9991875,0.000074590964,0.00013951446,0.00046131026,0.00010137515,0.000035668938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018890544,0.00014000978,0.00022896651,0.00054989476,0.00017319713,0.00014411967,0.00051998225,0.00008922049,0.0000027057504],"category_scores_gemma":[0.00001872816,0.00013554351,0.000014438663,0.00029857285,0.0007304814,0.0010578777,0.00043643636,0.00029750803,0.0000030670938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008086299,0.000014870983,0.003688415,0.00046095866,0.000019336228,2.8895863e-7,0.008873696,0.016800014,0.00003922712,0.5767637,0.00006994589,0.3932615],"study_design_scores_gemma":[0.00023802907,0.000088484405,0.002341864,0.00036965345,0.000012891917,0.000010940968,0.00026357014,0.99007195,0.0003064581,0.0010253756,0.0050158487,0.00025494542],"about_ca_topic_score_codex":0.0000022016075,"about_ca_topic_score_gemma":0.0000030497147,"teacher_disagreement_score":0.9732719,"about_ca_system_score_codex":0.00003610114,"about_ca_system_score_gemma":0.000038742965,"threshold_uncertainty_score":0.5527304},"labels":[],"label_agreement":null},{"id":"W3119276816","doi":"10.1007/978-3-030-66196-0_2","title":"Active Learning and Deep Learning for the Cold-Start Problem in Recommendation System: A Comparative Study","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Cold start (automotive); Computer science; Artificial intelligence; Deep learning; Information retrieval; Natural language processing; Physics","score_opus":0.07259082178479313,"score_gpt":0.3269006411743265,"score_spread":0.25430981938953334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119276816","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006705413,0.00033743773,0.9375843,0.0018113364,0.00016501316,0.0033445675,0.0000045854863,0.00019399036,0.056491747],"genre_scores_gemma":[0.89907515,0.0011533743,0.09852541,0.00025014384,0.000037254358,0.0006431574,0.000041933716,0.000013917127,0.00025967983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99830556,0.00016201391,0.00074362865,0.0003448013,0.00025081725,0.00019319577],"domain_scores_gemma":[0.9977228,0.00077760045,0.0005308924,0.000602582,0.00030023523,0.00006588176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018904295,0.00022299752,0.00035821655,0.00055446505,0.0008883198,0.0007974446,0.0014818831,0.00008313861,0.0000010887085],"category_scores_gemma":[0.00003494204,0.00018698013,0.00003333514,0.00042607682,0.00025787656,0.0036351033,0.0016614369,0.00069323025,0.000004441719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013790327,0.000043629956,0.00053363346,0.00013031815,0.00003110721,4.022847e-7,0.04248686,0.00051668106,0.0000032925504,0.5084562,0.00009465748,0.44768947],"study_design_scores_gemma":[0.000521154,0.00031022337,0.00077864935,0.00023439887,0.000008866185,0.000012655554,0.0026918342,0.86014235,0.0000053544995,0.0008551901,0.13418071,0.00025859653],"about_ca_topic_score_codex":0.000049215658,"about_ca_topic_score_gemma":0.00007719839,"teacher_disagreement_score":0.8990081,"about_ca_system_score_codex":0.00021260537,"about_ca_system_score_gemma":0.000112085414,"threshold_uncertainty_score":0.7689777},"labels":[],"label_agreement":null},{"id":"W3119346189","doi":"10.1007/978-981-33-6378-6_11","title":"Research on Testing Method of Low Voltage IGBT Module Parameter","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Insulated-gate bipolar transistor; Inverter; Voltage; Power (physics); Computer science; Realization (probability); Electronic engineering; Electrical engineering; Low voltage; Reliability engineering; Engineering; Physics; Mathematics","score_opus":0.16230434329929944,"score_gpt":0.3696611221870316,"score_spread":0.20735677888773218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119346189","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007068452,0.00096880115,0.12932964,0.0006129037,0.00057153543,0.0013251329,0.00009754914,0.0010107609,0.8590152],"genre_scores_gemma":[0.7526939,0.001146882,0.24550731,0.00030489307,0.000038407947,0.000047985937,0.000034996086,0.00003342762,0.0001921866],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882007,0.00002096597,0.0004799652,0.00014952252,0.00036373475,0.0001657605],"domain_scores_gemma":[0.9971678,0.0010272434,0.00009990173,0.0013332965,0.0003260224,0.000045697903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010150181,0.00013938824,0.00021597814,0.0010918943,0.00012277318,0.00011374508,0.001618526,0.00013700436,0.000004611625],"category_scores_gemma":[0.0003268063,0.00014299667,0.000025919036,0.00061341736,0.0008165199,0.0012119507,0.00093644304,0.0008045409,0.000030149047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030456943,0.000011871196,0.00006150263,0.00027325415,0.000015924641,5.4868735e-7,0.0013885,0.02002961,0.0025331574,0.32604063,0.0007420805,0.6488999],"study_design_scores_gemma":[0.00010605028,0.00005889514,0.00028427748,0.00033796133,0.000002413597,0.000005264571,0.000073148454,0.98225415,0.0021873522,0.008198347,0.006308452,0.00018368744],"about_ca_topic_score_codex":0.0000062057893,"about_ca_topic_score_gemma":0.0000013348673,"teacher_disagreement_score":0.96222454,"about_ca_system_score_codex":0.00011628736,"about_ca_system_score_gemma":0.000070166876,"threshold_uncertainty_score":0.5831235},"labels":[],"label_agreement":null},{"id":"W3122636519","doi":"10.1007/978-3-030-67435-9_11","title":"Conducting a College Through COVID-19: The Evolving Leadership Challenge","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acsenda School of Management","funders":"","keywords":"Notice; Coronavirus disease 2019 (COVID-19); Institution; Curriculum; Political science; Pandemic; Public relations; Organizational change; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Crisis management; Medicine; Law","score_opus":0.4974733320012847,"score_gpt":0.4654770111193323,"score_spread":0.03199632088195237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122636519","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000086204025,0.00962033,0.01599206,0.030632142,0.0011856342,0.0010352508,0.00007252716,0.000102084574,0.94127375],"genre_scores_gemma":[0.7246268,0.025185546,0.032895613,0.15998568,0.00065574143,0.0005072671,0.00057495467,0.00008803954,0.05548036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99835616,0.00010578421,0.00063243485,0.00027196456,0.00032956232,0.00030411372],"domain_scores_gemma":[0.9965224,0.0009947708,0.00033274837,0.0018003758,0.00020538474,0.00014428384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016295771,0.00019119923,0.00023282976,0.00031875254,0.0012085176,0.00018657657,0.0015306334,0.00014832942,0.00028798816],"category_scores_gemma":[0.00016138458,0.00016533709,0.00005175035,0.00035532977,0.0013693859,0.0019151442,0.0011004291,0.0006658301,0.00008528762],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004589372,0.000023547094,0.000043654447,0.00011322326,0.000009271968,0.0000017016077,0.029332278,0.000012510397,3.939378e-7,0.9382826,0.002125069,0.030051135],"study_design_scores_gemma":[0.0005415634,0.00006625928,0.00039378504,0.0002549427,0.000012179305,0.00007792759,0.009560124,0.0056663495,9.312171e-7,0.0056754122,0.97745687,0.00029367063],"about_ca_topic_score_codex":0.00026284365,"about_ca_topic_score_gemma":0.00017994603,"teacher_disagreement_score":0.9753318,"about_ca_system_score_codex":0.00057722453,"about_ca_system_score_gemma":0.0014507347,"threshold_uncertainty_score":0.9295063},"labels":[],"label_agreement":null},{"id":"W3128124300","doi":"10.1007/978-981-16-0425-6_13","title":"Grad-CAM-Based Classification of Chest X-Ray Images of Pneumonia Patients","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Segmentation; Convolutional neural network; Robustness (evolution); Artificial intelligence; Class (philosophy); Image segmentation; Contextual image classification; Test set; Pattern recognition (psychology); Image processing; Image (mathematics); Data mining","score_opus":0.058734176786718856,"score_gpt":0.3295027241783437,"score_spread":0.2707685473916248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128124300","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09823966,0.007140411,0.24169038,0.14840806,0.004542056,0.014175437,0.0012531609,0.0007507278,0.4838001],"genre_scores_gemma":[0.94237536,0.0019610024,0.05178692,0.002763035,0.000021863349,0.000031588406,0.0006202231,0.000017096472,0.00042288532],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983739,0.000027312808,0.0008336205,0.00017332117,0.00048147308,0.000110329034],"domain_scores_gemma":[0.9961489,0.00034159212,0.00062877417,0.0015590029,0.0012557119,0.00006606419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005677247,0.00014667692,0.00033828118,0.00086752314,0.00011706908,0.000053708714,0.000657802,0.00010690773,0.000013304808],"category_scores_gemma":[0.00019565165,0.00014817568,0.00006352637,0.00040308753,0.0010950067,0.0009514801,0.00042513083,0.00025168605,0.000006074646],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092582144,0.0015919849,0.058293313,0.0034732104,0.00010042723,0.0000011718478,0.0061723017,0.0017208899,0.0027850948,0.16466922,0.004988611,0.7561112],"study_design_scores_gemma":[0.0020717592,0.00035608318,0.657836,0.0037212817,0.0001064817,0.0000044906506,0.00007413766,0.11486795,0.0011770386,0.00046697474,0.2188508,0.00046696133],"about_ca_topic_score_codex":0.000017652732,"about_ca_topic_score_gemma":0.0000046670516,"teacher_disagreement_score":0.8441357,"about_ca_system_score_codex":0.00013050748,"about_ca_system_score_gemma":0.0006451292,"threshold_uncertainty_score":0.60424286},"labels":[],"label_agreement":null},{"id":"W3133782305","doi":"10.1007/978-981-15-9213-3_54","title":"Correction to: Scalable and Communication-Efficient Decentralized Federated Edge Learning with Multi-blockchain Framework","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Research (Canada)","funders":"","keywords":"Blockchain; Scalability; Computer science; Enhanced Data Rates for GSM Evolution; Section (typography); Information retrieval; Data science; World Wide Web; Library science; Database; Artificial intelligence; Computer security; Operating system","score_opus":0.036094346486950764,"score_gpt":0.28881132469528875,"score_spread":0.252716978208338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133782305","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018452622,0.00055945467,0.97118574,0.012677907,0.0002925095,0.0006913763,0.000009463576,0.00051264436,0.013886378],"genre_scores_gemma":[0.077996455,0.0019155145,0.9186773,0.0010396179,0.000009906922,0.000053007643,0.000053733813,0.000016030868,0.00023843533],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979464,0.00008986443,0.0006452275,0.0005120066,0.00048073646,0.00032579844],"domain_scores_gemma":[0.9920605,0.0006446404,0.0003887906,0.006238273,0.00047315666,0.00019464079],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0010586514,0.00030636473,0.00033463546,0.0007902726,0.0012029074,0.0013352172,0.015422013,0.000181898,0.000004411006],"category_scores_gemma":[0.0034190698,0.0002989137,0.000025891806,0.0011394685,0.0009989179,0.00204368,0.054438237,0.0012428852,0.00004016803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044378834,0.00013756403,0.00064515584,0.00011954059,0.000054051638,0.0000030572858,0.008326771,0.013602954,0.00002313762,0.4288639,0.014426487,0.533753],"study_design_scores_gemma":[0.00031492882,0.00008447201,0.0005968625,0.0006059983,0.0000054712136,0.000025044292,0.00006640998,0.9699425,0.000025544196,0.004642443,0.023337092,0.0003532433],"about_ca_topic_score_codex":0.000032770986,"about_ca_topic_score_gemma":0.00002428256,"teacher_disagreement_score":0.95633954,"about_ca_system_score_codex":0.00022176177,"about_ca_system_score_gemma":0.0002609371,"threshold_uncertainty_score":0.9999463},"labels":[],"label_agreement":null},{"id":"W3137092581","doi":"10.1007/978-3-030-71804-6_11","title":"From a Textual Narrative to a Visual Story","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human Motion and Animation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Narrative; Context (archaeology); Computer science; Motion (physics); Face (sociological concept); Variety (cybernetics); Virtual reality; Multimedia; Human–computer interaction; Artificial intelligence; Linguistics","score_opus":0.03091671116472395,"score_gpt":0.289468153612351,"score_spread":0.25855144244762707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137092581","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006589891,0.00076404854,0.27460957,0.0012236033,0.0007473689,0.0007288185,0.0001234384,0.00039782692,0.71481544],"genre_scores_gemma":[0.89329237,0.0024133069,0.09265354,0.0031274897,0.0003766467,0.00009670973,0.0010637229,0.000052110452,0.0069241193],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99924815,0.00001541755,0.00031014305,0.000114712486,0.00020860699,0.00010298951],"domain_scores_gemma":[0.9991083,0.00007110687,0.000055692184,0.00051404507,0.00017105656,0.000079786405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025933355,0.00012764178,0.00014414749,0.0004898252,0.00023096778,0.00023858502,0.0005060134,0.00007276129,0.000085964835],"category_scores_gemma":[0.000021097929,0.00014334645,0.00002280296,0.00017647188,0.00020283327,0.001740646,0.00036871445,0.0003038016,0.00011150208],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041991257,0.000027293336,0.00001201123,0.000059903854,0.000027522958,9.3463933e-7,0.07385528,0.007868937,0.00015139206,0.26267543,0.00675687,0.6485602],"study_design_scores_gemma":[0.00026551736,0.00004371965,0.0013914343,0.00039991745,0.000005899873,0.000004633456,0.0012414738,0.48473084,0.000027161253,0.0010049248,0.5104583,0.00042616253],"about_ca_topic_score_codex":0.000004302372,"about_ca_topic_score_gemma":0.000019102046,"teacher_disagreement_score":0.8867025,"about_ca_system_score_codex":0.0001450752,"about_ca_system_score_gemma":0.0000833058,"threshold_uncertainty_score":0.58454984},"labels":[],"label_agreement":null},{"id":"W3154401194","doi":"10.1007/978-3-030-73988-1_34","title":"Towards Modeling the Psychophysiology of Learning Interactions: The Effect of Agency on Arousal in Dyads Learning Physics with a Serious Computer Game","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Psychophysiology; Agency (philosophy); Arousal; Psychology; Cognitive psychology; Cognitive science; Computer science; Human–computer interaction; Neuroscience; Sociology; Social science","score_opus":0.04252697713080563,"score_gpt":0.3359183555458056,"score_spread":0.293391378415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154401194","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09148528,0.00039245063,0.8002159,0.0014921412,0.001009627,0.0014328859,0.000009758094,0.00007751336,0.103884436],"genre_scores_gemma":[0.9967205,0.00052262086,0.0017879541,0.00025278336,0.000051181978,0.000042811862,0.000078031066,0.000011560956,0.0005325375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851114,0.00029430696,0.00060609955,0.00018616045,0.0002672078,0.00013506532],"domain_scores_gemma":[0.9977521,0.0005098306,0.00056530716,0.0008244157,0.00032595257,0.000022414613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088508724,0.00017265549,0.00028821692,0.00032912687,0.0002697563,0.00007054521,0.0007260095,0.000091502385,0.000041066993],"category_scores_gemma":[0.00004861899,0.00011416711,0.000051040093,0.00050508935,0.00056887,0.00077868736,0.00030742332,0.00088664866,0.000013357074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009737495,0.00004975379,0.0013014979,0.00006415768,0.000043763655,4.086581e-7,0.015659936,0.4887979,0.000024432282,0.06429844,0.00004100297,0.42962134],"study_design_scores_gemma":[0.0005866527,0.0004888503,0.0047328714,0.00033797522,0.0000139276635,0.000015557142,0.00028497167,0.98669255,0.000013437105,0.00034806444,0.0063340194,0.00015112493],"about_ca_topic_score_codex":0.000031485884,"about_ca_topic_score_gemma":0.000014374365,"teacher_disagreement_score":0.90523523,"about_ca_system_score_codex":0.000078440855,"about_ca_system_score_gemma":0.00010678749,"threshold_uncertainty_score":0.46555996},"labels":[],"label_agreement":null},{"id":"W3156450849","doi":"10.1007/978-3-030-73988-1_33","title":"The Effect of Agency on Cognitive Load in Dyads Learning Physics with a Serious Computer Game","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Affect (linguistics); Agency (philosophy); Cognitive load; Cognition; Context (archaeology); Dyad; Task (project management); Cognitive psychology; Dual (grammatical number); Psychology; Cognitive architecture; Cognitive science; Computer science; Social psychology; Engineering; Communication; Sociology; Neuroscience","score_opus":0.020563675349623833,"score_gpt":0.27893363290017703,"score_spread":0.2583699575505532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156450849","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006708128,0.0006571338,0.82206297,0.0007664982,0.00041517793,0.0013350502,0.000008702241,0.000096882395,0.16794945],"genre_scores_gemma":[0.9768652,0.0035862902,0.017543945,0.0008002123,0.000064800195,0.000083955696,0.00003345241,0.00001586149,0.0010063167],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980537,0.00013269893,0.000491786,0.0003429228,0.00069399225,0.00028484073],"domain_scores_gemma":[0.9966337,0.0012031771,0.00040045113,0.0010561605,0.00063987327,0.000066651926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018106078,0.00024158848,0.0003167965,0.00041014538,0.00048473562,0.00054683327,0.0021244003,0.00007351448,0.0000016425788],"category_scores_gemma":[0.00010598035,0.00017736352,0.000052896386,0.000939519,0.0012429515,0.0030585104,0.0018461447,0.00065867,0.000015997026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000122134725,0.000012680221,0.00024263398,0.000034875604,0.0000076636225,0.0000021870205,0.0032156396,0.0007983297,0.0000028884062,0.08454767,0.000009609191,0.9111136],"study_design_scores_gemma":[0.0016474304,0.0015553943,0.008352974,0.0033712883,0.000016676942,0.00005335254,0.00010948794,0.96364266,0.0001724117,0.002282405,0.018090187,0.00070575177],"about_ca_topic_score_codex":0.000012248228,"about_ca_topic_score_gemma":0.000026633214,"teacher_disagreement_score":0.970157,"about_ca_system_score_codex":0.0001421033,"about_ca_system_score_gemma":0.00047575444,"threshold_uncertainty_score":0.72326744},"labels":[],"label_agreement":null},{"id":"W3157787540","doi":"10.1007/978-981-16-2336-3_7","title":"Episodic Training for Domain Generalization Using Latent Domains","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Artificial intelligence; Domain (mathematical analysis); Generalization; Classifier (UML); Machine learning; Feature (linguistics); Extractor; Cluster analysis; Pattern recognition (psychology); Mathematics","score_opus":0.11452061898146186,"score_gpt":0.3243889848396134,"score_spread":0.20986836585815155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157787540","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000105171835,0.00037810553,0.96522164,0.00072052114,0.0003689503,0.0004341131,0.000013558615,0.00008649027,0.032671418],"genre_scores_gemma":[0.011393189,0.0011346721,0.9843151,0.0016577941,0.00007114016,0.000040630573,0.00019673155,0.000017658938,0.0011730681],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980072,0.000057602592,0.0007957677,0.00036913974,0.00045619646,0.00031412073],"domain_scores_gemma":[0.9972282,0.00022432156,0.00045966695,0.0014461695,0.0005109224,0.00013069589],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014943264,0.00024082288,0.00030137986,0.00093138946,0.00086534355,0.0009991318,0.0019769226,0.0001442949,0.000009609893],"category_scores_gemma":[0.000067645866,0.00026405617,0.00008163223,0.0005495434,0.0004903805,0.00498968,0.0012291879,0.00030978932,0.000010433662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015166486,0.000007856968,0.000012996876,0.00002189555,0.0000062028057,4.4617644e-7,0.0038325174,0.0037659195,0.000024377074,0.8755052,0.000040349016,0.116780736],"study_design_scores_gemma":[0.00045013017,0.000032175707,0.00018596345,0.00018863434,0.000006386615,0.00003436705,0.00008372759,0.83400905,0.000007294588,0.016789807,0.1478883,0.0003241844],"about_ca_topic_score_codex":0.000005057953,"about_ca_topic_score_gemma":0.0000075173984,"teacher_disagreement_score":0.85871536,"about_ca_system_score_codex":0.00022943644,"about_ca_system_score_gemma":0.0005601369,"threshold_uncertainty_score":0.99998116},"labels":[],"label_agreement":null},{"id":"W3160466700","doi":"10.1007/978-3-030-29196-9","title":"Biomedical Engineering Systems and Technologies","year":2019,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Informatics; Focus (optics); Computer science; Health informatics; Electronics; Translational research informatics; Data science; Engineering; Engineering informatics; Medicine; Electrical engineering; Physics; Pathology","score_opus":0.01359825866067006,"score_gpt":0.22993123754386968,"score_spread":0.21633297888319963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160466700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005401967,0.051780842,0.7169851,0.0032798876,0.014165918,0.003066095,0.0001779954,0.0062540784,0.1988881],"genre_scores_gemma":[0.76383615,0.09730465,0.13023287,0.00037452078,0.00052055845,0.00044529163,0.0010535253,0.00013777,0.0060946792],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992533,0.000003562683,0.00030621677,0.000098683406,0.00018401066,0.00015424876],"domain_scores_gemma":[0.9991833,0.00009235316,0.000036407855,0.00058399996,0.000051141345,0.000052792733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313117,0.00012869696,0.00015710926,0.00078389485,0.00006138181,0.00017730708,0.0006102137,0.00017209617,7.6562475e-7],"category_scores_gemma":[0.00003142257,0.00012385135,0.0000104338,0.00037953278,0.0004024939,0.0011817091,0.00039828502,0.00035735275,0.000019501382],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001771145,0.00003844655,0.00012421803,0.0062766066,0.00004602827,7.0090675e-7,0.0034140742,0.023227435,0.000118371405,0.13860296,0.017970137,0.81017923],"study_design_scores_gemma":[0.00006619235,0.000010320387,0.00026925595,0.00032038978,0.0000023470507,0.000012471088,0.000042654254,0.72737426,0.000001982668,0.000068555884,0.27169853,0.00013306411],"about_ca_topic_score_codex":0.0000020826924,"about_ca_topic_score_gemma":2.2425353e-7,"teacher_disagreement_score":0.8100462,"about_ca_system_score_codex":0.00013484765,"about_ca_system_score_gemma":0.00009096225,"threshold_uncertainty_score":0.50505114},"labels":[],"label_agreement":null},{"id":"W3161799859","doi":"10.1007/978-3-030-76776-1_1","title":"Data Balancing for Credit Card Fraud Detection Using Complementary Neural Networks and SMOTE Algorithm","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Oversampling; Computer science; Credit card fraud; Credit card; Machine learning; Support vector machine; Class (philosophy); Artificial intelligence; Random forest; Algorithm; Artificial neural network; Boosting (machine learning); Logistic regression; Data mining; Bandwidth (computing); World Wide Web; Computer network","score_opus":0.0987028516425362,"score_gpt":0.3349643615855716,"score_spread":0.23626150994303538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161799859","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000020905676,0.0004793784,0.99656796,0.00039314572,0.00042124346,0.0005307311,0.0002906873,0.00012129983,0.0011746624],"genre_scores_gemma":[0.009868597,0.0017553053,0.98559237,0.00097351643,0.00012004381,0.000031797386,0.001589773,0.000013997635,0.00005457726],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998089,0.00004393892,0.0007329467,0.00051457854,0.00035017717,0.00026934195],"domain_scores_gemma":[0.9952049,0.0002696089,0.00043913853,0.0035419378,0.0004482593,0.000096144075],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013325908,0.0002343582,0.0002865696,0.0004454237,0.000753128,0.0009559498,0.0037454653,0.00012994131,0.0000018618895],"category_scores_gemma":[0.000049766884,0.00026138825,0.000030537107,0.00037737997,0.00054059905,0.008815779,0.0059655057,0.00040534118,9.678341e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001456066,0.000008131499,0.00002200117,0.000031569096,0.00000928362,3.3726823e-7,0.00021785153,0.0005676866,0.000012863664,0.03351504,0.00021607305,0.9653977],"study_design_scores_gemma":[0.00019299815,0.000029197914,0.00027372476,0.00010432389,0.000009709659,0.000040932722,0.00001839732,0.9315436,0.000020438765,0.0009607923,0.06655981,0.00024608543],"about_ca_topic_score_codex":0.000044848744,"about_ca_topic_score_gemma":0.000036975427,"teacher_disagreement_score":0.9651516,"about_ca_system_score_codex":0.0001766624,"about_ca_system_score_gemma":0.00015006626,"threshold_uncertainty_score":0.99998385},"labels":[],"label_agreement":null},{"id":"W3163611706","doi":"10.1007/978-3-030-76307-7_11","title":"A Genetic Algorithm for Flexible Job Shop Scheduling Problem with Scarce Cross Trained Setup Operators","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Bottleneck; Computer science; Job shop scheduling; Call for bids; Automation; Operator (biology); Scheduling (production processes); Genetic algorithm; Industrial engineering; Algorithm; Mathematical optimization; Operations research; Machine learning; Engineering; Operating system; Mechanical engineering; Mathematics; Schedule","score_opus":0.024847350806016563,"score_gpt":0.273626956975027,"score_spread":0.2487796061690104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163611706","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020738426,0.0006902438,0.9764099,0.00008589427,0.00017040636,0.000501338,0.000044492943,0.00020601682,0.021684326],"genre_scores_gemma":[0.0016488918,0.0010690577,0.9958742,0.00016872463,0.000049927006,0.00008666019,0.00014101733,0.000026136951,0.0009353304],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869436,0.0000105392855,0.0005609586,0.00021608264,0.0002756138,0.00024245611],"domain_scores_gemma":[0.9982708,0.000099036275,0.00010400044,0.0008444179,0.0005746755,0.000107049804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004557035,0.00023811379,0.00024857593,0.000504578,0.00043818096,0.0007498286,0.0008600601,0.00013513389,0.000011586275],"category_scores_gemma":[0.00001541014,0.00023599683,0.00004145495,0.0004119283,0.0004654501,0.001832612,0.0002827924,0.0003201936,0.000007805643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030247868,0.000010690573,0.000041099014,0.00012682306,0.000027484375,4.9454434e-7,0.0018387409,0.61648715,0.000003965208,0.014983424,0.000033241373,0.36644387],"study_design_scores_gemma":[0.00047236757,0.000033515178,0.000102634185,0.0002623228,0.000010041759,0.000024545034,0.00006480939,0.9917353,0.000033943856,0.00018418788,0.0067705126,0.00030585818],"about_ca_topic_score_codex":0.0000026453579,"about_ca_topic_score_gemma":0.0000031646953,"teacher_disagreement_score":0.37524813,"about_ca_system_score_codex":0.00011749705,"about_ca_system_score_gemma":0.00026324703,"threshold_uncertainty_score":0.9623672},"labels":[],"label_agreement":null},{"id":"W31679881","doi":"10.1007/978-3-642-37105-9_50","title":"Spatial and Temporal Variability Analysis in Rainfall Using Standardized Precipitation Index for the Fuhe Basin, China","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Climate variability and models","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Precipitation; China; Structural basin; Flood myth; Environmental science; Spatial distribution; Index (typography); Drainage basin; Climatology; Hydrology (agriculture); Physical geography; Water resource management; Geography; Meteorology; Geology; Cartography; Remote sensing; Computer science; Geomorphology","score_opus":0.036484197163683535,"score_gpt":0.2913147837264794,"score_spread":0.2548305865627959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W31679881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029535815,0.00004800048,0.939447,0.0009139134,0.0001207117,0.0018633517,0.00009862591,0.000024142148,0.02794848],"genre_scores_gemma":[0.9584553,0.00037011234,0.04067694,0.00023632172,0.000012008355,0.00005944764,0.00007465921,0.00000543971,0.00010975024],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858165,0.00007145909,0.00061796163,0.00025109673,0.0003067802,0.0001710785],"domain_scores_gemma":[0.99805015,0.00057570724,0.00026827885,0.00097087224,0.00007833718,0.00005663278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003361918,0.00015624322,0.0002554916,0.00034425,0.00046301234,0.00028476963,0.0007240572,0.00011070057,0.00009848086],"category_scores_gemma":[0.00013397398,0.00012637835,0.000053194384,0.0004302091,0.0012191852,0.002562305,0.0010412115,0.00023937026,0.0000039356087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012315782,0.00015336311,0.16173427,0.00015720449,0.000115181145,1.3948089e-7,0.02452735,0.14220548,0.0000234569,0.0800298,0.00016185967,0.59076875],"study_design_scores_gemma":[0.00029507044,0.000017808607,0.11247871,0.000023403272,0.00003413554,9.625398e-7,0.00002522496,0.8723186,6.317883e-7,0.008076015,0.0065939925,0.00013539844],"about_ca_topic_score_codex":0.0015029649,"about_ca_topic_score_gemma":0.00073860196,"teacher_disagreement_score":0.9289195,"about_ca_system_score_codex":0.00028926774,"about_ca_system_score_gemma":0.00008032611,"threshold_uncertainty_score":0.51535594},"labels":[],"label_agreement":null},{"id":"W3168455774","doi":"10.1007/978-3-030-62144-5_4","title":"Extraction of Complex DNN Models: Real Threat or Boogeyman?","year":2020,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Granularity; Adversary; Confidentiality; Artificial intelligence; Business model; Information extraction; Extraction (chemistry); Data mining; Machine learning; Computer security; Programming language","score_opus":0.11592522219046456,"score_gpt":0.34389868589094147,"score_spread":0.2279734637004769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168455774","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015333208,0.00006519341,0.74930555,0.00091891823,0.00017477415,0.00026430713,0.000007632356,0.00010057754,0.24914774],"genre_scores_gemma":[0.15803707,0.0049047093,0.83455914,0.0009741259,0.00009548621,0.00002560842,0.000099574056,0.000023903796,0.0012803882],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793535,0.000053959386,0.0008794816,0.0003330814,0.0005975105,0.00020060844],"domain_scores_gemma":[0.9965037,0.00038773316,0.0006655869,0.001943555,0.00038843628,0.00011096325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000826575,0.00024400662,0.00036756924,0.00072907837,0.0004030794,0.00031707023,0.0038878156,0.00013850059,0.000014905783],"category_scores_gemma":[0.00007206743,0.00022846712,0.000058077574,0.0005282765,0.0008164727,0.009315975,0.003272536,0.0005907033,0.00002375844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009272766,0.000012034003,0.000013541722,0.000039041966,0.000006723845,7.880051e-7,0.001958894,0.012301009,0.000007657203,0.8563981,0.00015504801,0.1290979],"study_design_scores_gemma":[0.0002588146,0.00007213021,0.00038940113,0.00012958178,0.000006968417,0.000024652714,0.000029368799,0.95840937,0.000004563099,0.018094745,0.022341926,0.00023845646],"about_ca_topic_score_codex":0.00004326715,"about_ca_topic_score_gemma":0.000013142503,"teacher_disagreement_score":0.9461084,"about_ca_system_score_codex":0.00016517266,"about_ca_system_score_gemma":0.0004079887,"threshold_uncertainty_score":0.93166184},"labels":[],"label_agreement":null},{"id":"W3183596842","doi":"10.1007/978-3-030-78642-7_50","title":"VR-DesignSpace: A Creativity Support Environment Integrating Virtual Reality Technology into Collaborative Data-Informed Evaluation of Design Alternatives","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Virtual reality; Creativity; Process (computing); Human–computer interaction; Engineering design process; Context (archaeology); Knowledge management; Systems engineering; Engineering","score_opus":0.15786694619309663,"score_gpt":0.39278021478381614,"score_spread":0.2349132685907195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183596842","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007447038,0.0003107214,0.9528328,0.0014354103,0.00008127537,0.0010390893,0.00008777644,0.000057415655,0.044081047],"genre_scores_gemma":[0.2652006,0.007940431,0.7248467,0.00038255486,0.000036422014,0.0002484934,0.0008296624,0.000020489739,0.0004946095],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965335,0.00025351456,0.001165625,0.00055597915,0.001225808,0.0002655364],"domain_scores_gemma":[0.99202,0.0006875759,0.0010598961,0.0046448293,0.0014578108,0.00012990022],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0059173494,0.0003135716,0.00047704033,0.0011759615,0.00048971846,0.00045952873,0.0047868825,0.00020910983,0.000021417145],"category_scores_gemma":[0.00076333387,0.00030730903,0.00003949901,0.0011187474,0.0017308005,0.008579547,0.0050100526,0.00047759485,0.000017948454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044363005,0.00005761506,0.00000925741,0.000020850546,0.000022612929,2.1603014e-7,0.00547528,0.0017719386,0.000044535653,0.486623,0.00016305014,0.5058072],"study_design_scores_gemma":[0.00053790526,0.00031133418,0.00024158784,0.0002868023,0.000035904515,0.000014947976,0.0006537844,0.9432479,0.0004615232,0.022860898,0.030931491,0.00041588163],"about_ca_topic_score_codex":0.000045468016,"about_ca_topic_score_gemma":0.000049595812,"teacher_disagreement_score":0.941476,"about_ca_system_score_codex":0.0005873222,"about_ca_system_score_gemma":0.0030613518,"threshold_uncertainty_score":0.9999379},"labels":[],"label_agreement":null},{"id":"W3184274587","doi":"10.1007/978-3-030-81698-8_5","title":"Bernoulli’s Problem $$x^y=y^x$$ and Maple","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sports Dynamics and Biomechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Maple; Bernoulli's principle; Parametric statistics; Function (biology); Mathematics; Computation; Applied mathematics; Computer science; Algorithm; Physics; Thermodynamics; Botany; Biology; Statistics","score_opus":0.015759470681562356,"score_gpt":0.22600097300755476,"score_spread":0.2102415023259924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184274587","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001331189,0.004488042,0.10577292,0.0007529376,0.00071407383,0.0007263893,0.000089438574,0.00029260907,0.8858324],"genre_scores_gemma":[0.3131945,0.16378286,0.5094118,0.0017379875,0.00018371532,0.000102358135,0.0012840198,0.00010414686,0.010198574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993392,0.0000026212324,0.00030312774,0.000098455545,0.00014724035,0.00010933799],"domain_scores_gemma":[0.99913865,0.000025958101,0.000057433375,0.0006150764,0.00011123471,0.000051651255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027189,0.00011650638,0.00012948574,0.00033456043,0.0001342196,0.00023468155,0.00044743516,0.00008480929,0.000010388502],"category_scores_gemma":[0.0000029660018,0.00012085293,0.000015418125,0.00014420939,0.00022493227,0.0011270792,0.0005757471,0.00021171306,0.0000073756987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.7773167e-7,0.000004684511,0.000030361438,0.0000822659,0.000007283483,5.1590575e-7,0.0006951307,0.00058160146,0.000010805817,0.7173302,0.00018060012,0.28107598],"study_design_scores_gemma":[0.000108908665,0.000010055484,0.0003036901,0.00015873335,0.000004908285,0.000027018214,0.000022360011,0.74204826,0.000004598646,0.005881051,0.25120813,0.00022230687],"about_ca_topic_score_codex":0.0000033237025,"about_ca_topic_score_gemma":0.000013868396,"teacher_disagreement_score":0.87563384,"about_ca_system_score_codex":0.000059315546,"about_ca_system_score_gemma":0.000052482996,"threshold_uncertainty_score":0.49282393},"labels":[],"label_agreement":null},{"id":"W3185311575","doi":"10.1007/978-3-030-78645-8_70","title":"ABLE Family: Remote, Intergenerational Play in the Age of COVID-19","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Loneliness; Mood; Dementia; Distancing; Cognition; Psychology; Isolation (microbiology); Coronavirus disease 2019 (COVID-19); Gerontology; Developmental psychology; Medicine; Clinical psychology; Psychiatry; Disease","score_opus":0.0703214908514669,"score_gpt":0.3469199332804451,"score_spread":0.27659844242897824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185311575","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016511944,0.001233051,0.04844347,0.017614827,0.00046831445,0.00096679,0.000046735197,0.000091869544,0.9294838],"genre_scores_gemma":[0.7504884,0.038035024,0.17318317,0.025565188,0.00023079233,0.00010319083,0.0009015792,0.000031763466,0.011460895],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985459,0.000111130605,0.00055535784,0.00015166898,0.00047579038,0.00016014418],"domain_scores_gemma":[0.9980397,0.00042337977,0.00022704173,0.001022358,0.00023856996,0.00004893338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002361803,0.00010617168,0.00017433161,0.000672896,0.00056966644,0.00018572935,0.0022924556,0.00016075223,0.000021269896],"category_scores_gemma":[0.00037112628,0.00009639476,0.0000322437,0.0005952167,0.0024681352,0.0015937409,0.00072484213,0.00039653655,0.00000790668],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014885657,0.000015032896,0.00013980875,0.000016198272,0.0000030438537,0.0000010467909,0.03145568,0.00018096733,0.0000062866047,0.9400302,0.0011916234,0.02695862],"study_design_scores_gemma":[0.0002751505,0.000020859721,0.0022093677,0.0001634953,0.000004259973,0.0000074899513,0.0021781386,0.0084247235,0.0000038332864,0.018044367,0.9684817,0.00018657565],"about_ca_topic_score_codex":0.00052860467,"about_ca_topic_score_gemma":0.0031549665,"teacher_disagreement_score":0.9672901,"about_ca_system_score_codex":0.00020395813,"about_ca_system_score_gemma":0.001120401,"threshold_uncertainty_score":0.9093947},"labels":[],"label_agreement":null},{"id":"W3194235020","doi":"10.1007/978-981-16-5188-5_15","title":"Cross Languages One-Versus-All Speech Emotion Classifier","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Classifier (UML); Computer science; Speech recognition; Artificial intelligence; Oversampling; Emotion recognition; Natural language processing; Principal component analysis; Pattern recognition (psychology)","score_opus":0.13498144232446063,"score_gpt":0.40153909343130295,"score_spread":0.2665576511068423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194235020","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011253203,0.00042134465,0.008254025,0.0007190249,0.0011014147,0.00028308938,0.00003331628,0.00007865461,0.9879838],"genre_scores_gemma":[0.45068154,0.021457171,0.13798265,0.014177545,0.0012108482,0.00023200217,0.006883417,0.00014431632,0.3672305],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998637,0.000051232433,0.0005457483,0.00024863795,0.00031548567,0.00020184973],"domain_scores_gemma":[0.99779856,0.00014949155,0.0002708339,0.0012519907,0.00044164996,0.00008747565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070063805,0.0001715529,0.00019461666,0.0006279278,0.00028901928,0.00037990444,0.00079074124,0.0002313852,0.0007245842],"category_scores_gemma":[0.00004250504,0.00018710045,0.000056474466,0.00022518626,0.0007309615,0.0020151879,0.0006132693,0.00048408782,0.00046517898],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001449094,0.0000524459,0.00005799113,0.00002754877,0.000024044137,0.0000013299687,0.0029612512,0.00000989263,0.000006516389,0.4648416,0.0008728157,0.5311301],"study_design_scores_gemma":[0.0025173035,0.00018241137,0.0187888,0.0005436513,0.00004947982,0.000096202864,0.0009155838,0.007158205,0.000045039204,0.003091515,0.96577775,0.0008340498],"about_ca_topic_score_codex":0.000020492873,"about_ca_topic_score_gemma":0.000035784513,"teacher_disagreement_score":0.96490496,"about_ca_system_score_codex":0.00011783786,"about_ca_system_score_gemma":0.000116289535,"threshold_uncertainty_score":0.79336894},"labels":[],"label_agreement":null},{"id":"W3196453586","doi":"10.1007/978-3-030-85347-1_15","title":"Towards Understanding Quality-Related Characteristics in Knowledge-Intensive Processes - A Systematic Literature Review","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Quality (philosophy); Computer science; Context (archaeology); Process (computing); Business process; Knowledge management; Systematic review; Management science; Process management; Data science; Risk analysis (engineering); Work in process; Business; Epistemology; Engineering; Political science; MEDLINE; History; Marketing","score_opus":0.08927887716176792,"score_gpt":0.3226959734518976,"score_spread":0.2334170962901297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196453586","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022109291,0.34024137,0.09746233,0.012888124,0.0012538644,0.0032805393,0.00005483212,0.00041091235,0.54418695],"genre_scores_gemma":[0.38218573,0.5905707,0.0042556818,0.016535075,0.00032212393,0.00022757267,0.002069693,0.00007378268,0.0037596326],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"systematic_review","domain_scores_codex":[0.997907,0.000021603091,0.0013025654,0.00025059428,0.00033735493,0.00018089618],"domain_scores_gemma":[0.9954258,0.00012665642,0.00084893854,0.0008531194,0.0027279186,0.000017531298],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016829016,0.00024783178,0.0006872835,0.0013829723,0.00030698796,0.0011178467,0.0009874012,0.00013095372,0.000011230966],"category_scores_gemma":[0.0008428587,0.00022318689,0.00006135772,0.0020569805,0.00030710295,0.005714058,0.0009419608,0.00045400285,0.00003174606],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038198546,0.00004591422,0.00011266136,0.25456622,0.000035407156,0.00000388758,0.0023974197,0.00008007505,5.66041e-7,0.72715217,0.00017808084,0.015423814],"study_design_scores_gemma":[0.00053981773,0.000008066513,0.0003356375,0.6005682,0.00022835958,0.000035670284,0.00084769883,0.36495557,3.6700598e-7,0.017245315,0.014186028,0.0010493125],"about_ca_topic_score_codex":0.000015590818,"about_ca_topic_score_gemma":0.00003876075,"teacher_disagreement_score":0.7099068,"about_ca_system_score_codex":0.00016542975,"about_ca_system_score_gemma":0.00030187125,"threshold_uncertainty_score":0.9999191},"labels":[],"label_agreement":null},{"id":"W3196831049","doi":"10.1007/978-3-030-85521-5_29","title":"An Exploratory Analysis of the Perception of the Utility of Proven Practices of the Software Basic Profile of ISO/IEC 29110 by a Set of VSEs in Mexico","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Context (archaeology); Software; Software development process; Engineering; Software engineering; Engineering management; Computer science; Software development; Process management","score_opus":0.049675589779568596,"score_gpt":0.3204944916612544,"score_spread":0.2708189018816858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196831049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2714967,0.0018255995,0.71319944,0.0016708489,0.000556069,0.0030697335,0.000872497,0.00009594892,0.0072131567],"genre_scores_gemma":[0.95691276,0.00037775803,0.0426261,0.000035231158,0.0000022163115,0.000013428337,0.00001387913,0.0000028653515,0.000015766747],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99813557,0.00020120833,0.00093360426,0.00014718034,0.0005050809,0.000077374636],"domain_scores_gemma":[0.99334675,0.0005895461,0.0026047912,0.0027489017,0.0006929358,0.000017069027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018179268,0.00011212565,0.00034057754,0.00038078555,0.00008316313,0.00003292308,0.0035774608,0.00008287505,0.000007514065],"category_scores_gemma":[0.00043241345,0.00007284942,0.00011538191,0.0015670429,0.0009156866,0.0025446995,0.0016211533,0.00025581784,5.7343257e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009041987,0.0013499632,0.24399923,0.003905708,0.0006089037,1.5632037e-7,0.1583996,0.017323196,0.0056423456,0.1253862,0.001039359,0.4422549],"study_design_scores_gemma":[0.00029973756,0.00019730945,0.28877282,0.0015198705,0.00019457896,0.00000395833,0.0010717406,0.6898707,0.012450826,0.0016339641,0.0036807344,0.0003037336],"about_ca_topic_score_codex":0.00011667395,"about_ca_topic_score_gemma":0.0000566536,"teacher_disagreement_score":0.68541604,"about_ca_system_score_codex":0.000028498416,"about_ca_system_score_gemma":0.00035666543,"threshold_uncertainty_score":0.6647872},"labels":[],"label_agreement":null},{"id":"W3199041733","doi":"10.1007/978-3-030-87101-7_23","title":"A Comparative Study of Deep Learning Approaches for Day-Ahead Load Forecasting of an Electric Car Fleet","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Computer science; Electric cars; Artificial intelligence; Automotive engineering; Engineering","score_opus":0.09492248453676443,"score_gpt":0.2860456767467332,"score_spread":0.19112319220996876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199041733","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21214907,0.0043500634,0.38162595,0.000021220518,0.0005486954,0.0023692495,0.00004862013,0.00022775908,0.39865938],"genre_scores_gemma":[0.97988564,0.00016244705,0.019772338,0.000005585168,0.000017040984,0.000026847152,0.00007012459,0.00000919048,0.00005081683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988001,0.00003169636,0.0006521303,0.00012946004,0.00023829006,0.00014830289],"domain_scores_gemma":[0.9984812,0.00028608486,0.0002651447,0.00056370295,0.00036031622,0.00004356489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079041487,0.00015858325,0.0003528699,0.00046908713,0.00020094674,0.00007216958,0.00065335736,0.00007176667,0.0000018143859],"category_scores_gemma":[0.000040874635,0.00016863555,0.000035552304,0.00034955653,0.00018149232,0.001361102,0.00027859025,0.00028712847,3.4461382e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066043135,0.00006476281,0.00008588693,0.0002079926,0.00004257977,1.621015e-7,0.040803496,0.57224375,0.00002933738,0.023376493,0.0000049993328,0.3631339],"study_design_scores_gemma":[0.00027651316,0.00018747107,0.0001792969,0.00015930594,0.000013695887,0.000004995762,0.000942998,0.9962947,0.00010244118,0.00016097522,0.0015220746,0.00015557247],"about_ca_topic_score_codex":0.000010930169,"about_ca_topic_score_gemma":0.00007174464,"teacher_disagreement_score":0.76773655,"about_ca_system_score_codex":0.00007607701,"about_ca_system_score_gemma":0.00008581713,"threshold_uncertainty_score":0.68767583},"labels":[],"label_agreement":null},{"id":"W3203750292","doi":"10.1007/978-3-030-88113-9_46","title":"Cbow Training Time and Accuracy Optimization Using SkipGram","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université du Québec à Montréal","funders":"","keywords":"Training (meteorology); Computer science; Artificial intelligence; Pattern recognition (psychology); Machine learning; Geography; Meteorology","score_opus":0.08994632349629471,"score_gpt":0.3138227792282719,"score_spread":0.22387645573197718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203750292","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011385096,0.0004262992,0.9581786,0.0005205961,0.0001557043,0.00020930718,0.0000040788136,0.00007320629,0.04031837],"genre_scores_gemma":[0.008007683,0.001615436,0.989073,0.0006865716,0.000037424714,0.000006344204,0.000040011648,0.0000083426185,0.00052523165],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854076,0.000033099255,0.00057353266,0.0003118874,0.00033743138,0.00020331984],"domain_scores_gemma":[0.99749386,0.00021508994,0.0002981527,0.0015709085,0.00032612987,0.00009587564],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008440286,0.00018432409,0.00023231763,0.0006313812,0.000490028,0.0010612028,0.0017552417,0.000114623275,0.000009263202],"category_scores_gemma":[0.00008649568,0.0002003486,0.000029031737,0.00034947184,0.0004178669,0.007656011,0.0025276868,0.00032045547,0.000007874616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.530225e-7,0.000008309359,0.000011846566,0.000023753799,0.0000061252667,7.6815e-7,0.0044976496,0.06710252,0.000007721221,0.3818042,0.000016866867,0.5465196],"study_design_scores_gemma":[0.00013590067,0.000011140899,0.000043747455,0.00019288757,0.0000039933543,0.00005171616,0.000021572136,0.9898408,0.0000026429893,0.0016485942,0.007837964,0.00020902116],"about_ca_topic_score_codex":0.000009229105,"about_ca_topic_score_gemma":0.0000022151805,"teacher_disagreement_score":0.9227383,"about_ca_system_score_codex":0.0001069159,"about_ca_system_score_gemma":0.00039276286,"threshold_uncertainty_score":0.9999758},"labels":[],"label_agreement":null},{"id":"W3203790825","doi":"10.1007/978-3-030-88113-9_5","title":"Valentino Braitenberg’s Table: Downhill Innovation of Vehicles via Darwinian Evolution","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Darwinism; Darwin (ADL); Survivability; Exploit; Context (archaeology); Artificial intelligence; Computer security; Evolutionary biology; Geography; Biology","score_opus":0.024604560431335815,"score_gpt":0.26546234600582497,"score_spread":0.24085778557448914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203790825","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016220927,0.00067781267,0.9121974,0.0013043706,0.00025020563,0.0003692286,0.00004081583,0.00008402218,0.08491391],"genre_scores_gemma":[0.28057227,0.0034937526,0.7088178,0.0012956804,0.00015124644,0.00012080116,0.0007268875,0.000029142882,0.0047924193],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99769735,0.000035911922,0.0011024454,0.00036341455,0.00056748226,0.0002333925],"domain_scores_gemma":[0.9953879,0.0001559716,0.00068082364,0.002219277,0.0014845956,0.00007139322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010171202,0.0002223776,0.00028649252,0.0013472886,0.0005117532,0.00029309976,0.0025862071,0.00015809067,0.0000140885395],"category_scores_gemma":[0.00005193367,0.00024225899,0.00004802279,0.0020592737,0.000830419,0.006439583,0.002192651,0.00038428893,0.000023400828],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.12766e-7,0.00003167406,0.00007132363,0.000028561515,0.000005874233,1.4887422e-7,0.00035361355,0.00025051535,0.000061448365,0.889196,0.00021843458,0.10978174],"study_design_scores_gemma":[0.0005669766,0.000085569794,0.014610172,0.00046892714,0.000016422553,0.00007367791,0.00004427879,0.75241697,0.00013103714,0.065326616,0.16558425,0.0006750938],"about_ca_topic_score_codex":0.000022981401,"about_ca_topic_score_gemma":0.0000066113307,"teacher_disagreement_score":0.82386935,"about_ca_system_score_codex":0.00018858959,"about_ca_system_score_gemma":0.00063467544,"threshold_uncertainty_score":0.9879035},"labels":[],"label_agreement":null},{"id":"W3204538367","doi":"10.1007/978-3-030-88113-9_18","title":"Towards Smart Customer Knowledge Management Systems","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Knowledge management","score_opus":0.09627442238656006,"score_gpt":0.31517266716093556,"score_spread":0.2188982447743755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204538367","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015490063,0.0011436106,0.011306358,0.00028782355,0.0009798739,0.00031985843,0.0000095215455,0.00006597552,0.9858715],"genre_scores_gemma":[0.6561749,0.06560432,0.055770475,0.016006516,0.0037189643,0.0006647815,0.005336455,0.00022700273,0.19649659],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985593,0.000006044692,0.0005931056,0.00025355382,0.00037496263,0.00021306422],"domain_scores_gemma":[0.9975126,0.00003554911,0.00029386996,0.0014723112,0.0006654081,0.000020255922],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007769046,0.00022272277,0.00024336543,0.0012077552,0.00042047174,0.0015068585,0.0018694765,0.00010686462,0.0000626921],"category_scores_gemma":[0.000019231185,0.0002155122,0.000041126634,0.0006850933,0.0005912419,0.007863786,0.003486332,0.00028311388,0.0007974382],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012252152,0.000014722814,0.00003339318,0.0002285119,0.0000064053356,5.5199246e-7,0.00006888962,0.000036173125,3.1260734e-7,0.83664525,0.0019961547,0.16096841],"study_design_scores_gemma":[0.000106674626,0.000002115683,0.00075173296,0.0004835144,0.000017417216,0.0000069791204,0.00006367386,0.04301891,6.7964095e-7,0.00084100507,0.9544486,0.00025869167],"about_ca_topic_score_codex":0.00005693846,"about_ca_topic_score_gemma":0.000017940654,"teacher_disagreement_score":0.9524524,"about_ca_system_score_codex":0.000090544585,"about_ca_system_score_gemma":0.00009908365,"threshold_uncertainty_score":0.99998057},"labels":[],"label_agreement":null},{"id":"W3212366111","doi":"10.1007/978-3-030-90176-9_36","title":"User Satisfaction with an AI-Enabled Customer Relationship Management Chatbot","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in Service Interactions","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Chatbot; Context (archaeology); Computer science; Customer satisfaction; Customer care; E-commerce; Customer relationship management; User satisfaction; Knowledge management; Computer user satisfaction; World Wide Web; User experience design; Human–computer interaction; Business; Marketing; Database; User interface design","score_opus":0.036047204757060865,"score_gpt":0.2984561813428591,"score_spread":0.26240897658579826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212366111","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022901388,0.00012860805,0.6938665,0.0027535106,0.0004972422,0.00066234136,0.000009649081,0.00023675832,0.3016164],"genre_scores_gemma":[0.14404723,0.001955986,0.8367565,0.0053003915,0.00009231414,0.00019055678,0.00023473828,0.00004050608,0.011381765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99780065,0.00006468981,0.00071403495,0.00046204467,0.00067427364,0.0002843163],"domain_scores_gemma":[0.9951077,0.00020185893,0.00039518607,0.0033964796,0.00074421224,0.00015455313],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0007544138,0.00029063,0.00025457743,0.0013309984,0.00083171035,0.0013808468,0.002605091,0.000147165,0.000036474506],"category_scores_gemma":[0.000015693699,0.00028570474,0.000042300806,0.0008959198,0.0004818432,0.019405378,0.0019619875,0.00072112033,0.00016772511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036737406,0.000021495622,0.00061513495,0.00003141531,0.000013180834,0.0000018182059,0.0010501192,0.001030287,7.0390996e-7,0.93098456,0.00020701169,0.06604062],"study_design_scores_gemma":[0.0011484668,0.00023973668,0.066920474,0.0011250302,0.00005982517,0.0003043594,0.00038053637,0.4956486,0.000013671867,0.019715479,0.41294357,0.0015002491],"about_ca_topic_score_codex":0.000055463875,"about_ca_topic_score_gemma":0.00023448773,"teacher_disagreement_score":0.91126907,"about_ca_system_score_codex":0.0003241774,"about_ca_system_score_gemma":0.00029024473,"threshold_uncertainty_score":0.9999595},"labels":[],"label_agreement":null},{"id":"W3212642796","doi":"10.1007/978-3-030-90176-9_48","title":"Comparing the Impact of State Versus Trait Factors on Memory Performance in a Virtual Reality Flight Simulator","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Trait; Aviation; Virtual reality; Computer science; Flight simulator; Variance (accounting); Simulation; State (computer science); Virtual machine; Human–computer interaction; Engineering; Aerospace engineering","score_opus":0.12465858080288772,"score_gpt":0.4061386083818155,"score_spread":0.28148002757892776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212642796","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30043864,0.00008050137,0.0024022995,0.00026033365,0.0009809356,0.0005856895,0.000080350146,0.00005544059,0.6951158],"genre_scores_gemma":[0.99857265,0.00016192193,0.00008051278,0.00008670329,0.000013600989,0.000011312612,0.00007835926,0.000005897769,0.0009890504],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983956,0.00009906018,0.0008547572,0.0001765114,0.0003033157,0.00017071914],"domain_scores_gemma":[0.99740165,0.0005965837,0.00043650065,0.0012677653,0.00023951923,0.00005799119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009035632,0.00018478904,0.00028866483,0.00064243603,0.00026488924,0.00012247033,0.0009923533,0.00009019143,0.00022710647],"category_scores_gemma":[0.000046120545,0.00014199491,0.00008364245,0.0003020095,0.00060722156,0.001382407,0.00036706383,0.0005672008,0.000035954807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005304142,0.00035023483,0.0052298694,0.000078425095,0.00017553158,0.0000013453695,0.11431333,0.20087442,0.000008042017,0.5077711,0.0010788732,0.16958842],"study_design_scores_gemma":[0.0018555464,0.00034764275,0.44025746,0.00036965913,0.000009824709,0.000007467648,0.00096214726,0.539322,0.000015958927,0.00022521843,0.016235812,0.00039126046],"about_ca_topic_score_codex":0.00013185982,"about_ca_topic_score_gemma":0.00008827357,"teacher_disagreement_score":0.698134,"about_ca_system_score_codex":0.00026537664,"about_ca_system_score_gemma":0.00019535977,"threshold_uncertainty_score":0.57903844},"labels":[],"label_agreement":null},{"id":"W36596141","doi":"10.1007/978-3-642-22410-2_35","title":"User Modeling to Build Mobile Advertising Algorithm","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Digital signage; Computer science; Merge (version control); Broadcasting (networking); Multimedia; Signage; Algorithm; World Wide Web; Information retrieval; Advertising; Computer network","score_opus":0.0559187490813379,"score_gpt":0.34364498181585695,"score_spread":0.287726232734519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W36596141","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009086838,0.00044623707,0.30262402,0.0015242109,0.00034690596,0.0008247233,0.000012123416,0.00019799036,0.6939329],"genre_scores_gemma":[0.11509475,0.025800634,0.84359115,0.0037628324,0.0001384277,0.00027496697,0.00009776284,0.000038747927,0.011200722],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985372,0.000049821952,0.0005634079,0.00020307081,0.00037923083,0.00026728548],"domain_scores_gemma":[0.99730825,0.00013569128,0.00018224592,0.0017442778,0.00046577177,0.00016375796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013661135,0.00015719059,0.00020713857,0.0010818158,0.0010463628,0.00023542032,0.0029252095,0.00021196567,0.00008630574],"category_scores_gemma":[0.000090449605,0.0001743529,0.00003698416,0.00042667342,0.0012543873,0.00263265,0.0018607354,0.00046142185,0.00018967432],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.723366e-7,0.00000952486,0.000011921104,0.0000031291502,0.0000023219222,6.275657e-8,0.009525977,0.00014579392,5.700937e-7,0.40716428,0.00010034536,0.58303523],"study_design_scores_gemma":[0.00012331922,0.000024116687,0.00003628385,0.0001275582,0.000004646675,0.0000021237977,0.00029806435,0.17627782,0.0000024314668,0.008553451,0.81430084,0.00024935158],"about_ca_topic_score_codex":0.0004369155,"about_ca_topic_score_gemma":0.00028640722,"teacher_disagreement_score":0.8142005,"about_ca_system_score_codex":0.00020800489,"about_ca_system_score_gemma":0.0003607289,"threshold_uncertainty_score":0.80478823},"labels":[],"label_agreement":null},{"id":"W4205583746","doi":"10.1007/978-3-030-93186-5_5","title":"Toward an Automated Pipeline for a Browser-Based, City-Scale Mobile 4D VR Application Based on Historical Images","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Visualization; Process (computing); Focus (optics); Virtual reality; Orientation (vector space); Human–computer interaction; Mobile device; Augmented reality; Dimension (graph theory); Computer graphics (images); Artificial intelligence; World Wide Web","score_opus":0.04656682657260826,"score_gpt":0.3413572968562856,"score_spread":0.29479047028367733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205583746","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005861428,0.0002323398,0.9872167,0.0008450911,0.00013349461,0.0009249142,0.000037053782,0.00061567454,0.009988867],"genre_scores_gemma":[0.024770657,0.0004565056,0.9704885,0.002771419,0.00005978374,0.00044426933,0.00040554276,0.000021022188,0.000582335],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99790406,0.00004649434,0.0007619389,0.00051013194,0.0005062801,0.00027110887],"domain_scores_gemma":[0.99542284,0.00036685143,0.00041145203,0.0027249942,0.0009229833,0.00015087555],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009817785,0.00029086688,0.0003470645,0.0008675664,0.0005634968,0.00068923703,0.0029262772,0.00017571294,0.0000044641906],"category_scores_gemma":[0.00007519711,0.00029767826,0.00009013199,0.00064102095,0.0004644561,0.0046137106,0.0007820065,0.00038957866,0.0000073400324],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002014265,0.0001841721,0.000017841165,0.000104807346,0.0000032385024,7.9948086e-7,0.00045274495,0.0039455285,0.00006302429,0.07831875,0.0013582862,0.9155307],"study_design_scores_gemma":[0.0002829629,0.00019221067,0.00003548342,0.00012224475,0.0000050317385,0.000004561184,0.000005192032,0.8214815,0.0006686864,0.0018893904,0.1750288,0.00028388377],"about_ca_topic_score_codex":0.000013738428,"about_ca_topic_score_gemma":0.0000051496895,"teacher_disagreement_score":0.9152468,"about_ca_system_score_codex":0.00054797804,"about_ca_system_score_gemma":0.00054238073,"threshold_uncertainty_score":0.99994755},"labels":[],"label_agreement":null},{"id":"W4205730035","doi":"10.1007/978-3-030-93956-4_5","title":"Granularity and Usability in Authorization Policies","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Usability; Principal (computer security); Set (abstract data type); Syntax; Authorization; World Wide Web; Context (archaeology); Resource (disambiguation); Computer security; Human–computer interaction; Programming language; Artificial intelligence","score_opus":0.06095335389733772,"score_gpt":0.3442671777863834,"score_spread":0.2833138238890457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205730035","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058056554,0.0014079995,0.02635264,0.014576414,0.0010236173,0.0024397736,0.00017290971,0.00021967822,0.9480013],"genre_scores_gemma":[0.9577835,0.026150737,0.013702796,0.0010498697,0.00011684618,0.000109639775,0.00032595982,0.000012532866,0.00074808946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867046,0.00012818958,0.00043407272,0.0001889774,0.00040483274,0.0001734438],"domain_scores_gemma":[0.9986091,0.00016678282,0.00018088942,0.0008273748,0.00014321346,0.000072595365],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0030064578,0.00010833906,0.00015539993,0.0006949369,0.0013455381,0.0003537849,0.0012392103,0.00011102289,0.000037046677],"category_scores_gemma":[0.0003637107,0.00012488909,0.000018325727,0.0004790131,0.0017572757,0.005382008,0.0021631564,0.00044530668,0.0000047056114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024060857,0.00001337314,0.0012438732,0.000015950678,7.983478e-7,5.6067236e-8,0.013339706,0.000012316325,5.077364e-7,0.92615384,0.000047018257,0.059170146],"study_design_scores_gemma":[0.00032987128,0.000049205017,0.033391643,0.00008764911,0.000006039405,0.0000041667968,0.0008409739,0.020700281,0.0000015048929,0.14992195,0.79430693,0.00035978676],"about_ca_topic_score_codex":0.0023800354,"about_ca_topic_score_gemma":0.0018115332,"teacher_disagreement_score":0.95197785,"about_ca_system_score_codex":0.0003109056,"about_ca_system_score_gemma":0.00031165598,"threshold_uncertainty_score":0.9999546},"labels":[],"label_agreement":null},{"id":"W4206219836","doi":"10.1007/978-981-16-8896-6","title":"Communication, Networks and Computing","year":2021,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.014781042505968331,"score_gpt":0.2655973228497469,"score_spread":0.25081628034377856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206219836","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020487263,0.005468624,0.94459426,0.001996459,0.0003510777,0.0003291131,0.0000045871056,0.00019038719,0.04686061],"genre_scores_gemma":[0.05831165,0.013084855,0.9222039,0.0041574463,0.0001721745,0.000023072167,0.00021087972,0.000028528937,0.0018075219],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792314,0.0001432838,0.0007572392,0.00042461877,0.00039995584,0.0003517578],"domain_scores_gemma":[0.9953961,0.0005917013,0.0003909336,0.0030106704,0.00045649183,0.00015414182],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0016394621,0.0002795862,0.00035918175,0.00073131244,0.0010494811,0.0016251996,0.004107721,0.00016382198,0.0000016801828],"category_scores_gemma":[0.00006940801,0.00028738249,0.000044589935,0.0010505847,0.0011723149,0.0035602744,0.008550522,0.0009084204,0.0000061343185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.9182524e-7,0.000028341732,0.000091039765,0.000051630068,0.000010473479,0.0000013593778,0.003418732,0.01115129,5.3911526e-7,0.30044967,0.0014482405,0.6833479],"study_design_scores_gemma":[0.00020156626,0.00002260901,0.0015468625,0.00036602374,0.0000037287666,0.00008548467,0.000020252324,0.9342341,9.669468e-7,0.0033539846,0.059867132,0.00029732802],"about_ca_topic_score_codex":0.000013055917,"about_ca_topic_score_gemma":0.0000082087,"teacher_disagreement_score":0.92308277,"about_ca_system_score_codex":0.0001290273,"about_ca_system_score_gemma":0.00058832415,"threshold_uncertainty_score":0.99995786},"labels":[],"label_agreement":null},{"id":"W4206905375","doi":"10.1007/978-3-030-95630-1_13","title":"Privacy Protection in Geolocation Monitoring Applications","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Geolocation; Privacy policy; Computer science; Robustness (evolution); Privacy protection; Computer security; Information privacy; Internet privacy; Information sensitivity; World Wide Web","score_opus":0.06753883418025779,"score_gpt":0.3068776768633046,"score_spread":0.23933884268304678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206905375","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001108389,0.00063736126,0.92187184,0.017822597,0.00043454263,0.0018757357,0.000017925584,0.00054831046,0.056680877],"genre_scores_gemma":[0.079930134,0.008977881,0.908247,0.0004945379,0.0000733199,0.0017663166,0.00014884649,0.0000264636,0.00033548518],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99785227,0.00004709756,0.00078703667,0.00046670463,0.000562155,0.00028474705],"domain_scores_gemma":[0.9882264,0.00015871404,0.00042456464,0.010906686,0.0002247398,0.000058879057],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0015482381,0.00022357491,0.00022269992,0.002074129,0.0006273685,0.00049205014,0.029550873,0.00015389733,0.000008066138],"category_scores_gemma":[0.0007894931,0.00026167784,0.000031379248,0.0013399095,0.0005769229,0.010350045,0.08745624,0.00096757174,0.000031643867],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017738213,0.00003264033,0.00024940626,0.00004119409,0.0000036301776,4.1973877e-7,0.0006480692,0.00027791777,0.0000093441695,0.31158787,0.00040003264,0.6867477],"study_design_scores_gemma":[0.00028929563,0.00005166042,0.0030436486,0.0001744152,0.0000031820398,0.000027169775,0.000029013647,0.4923253,0.00004013744,0.17020787,0.333365,0.00044330876],"about_ca_topic_score_codex":0.000055683497,"about_ca_topic_score_gemma":0.000007847264,"teacher_disagreement_score":0.6863044,"about_ca_system_score_codex":0.00065824477,"about_ca_system_score_gemma":0.00025740336,"threshold_uncertainty_score":0.99998355},"labels":[],"label_agreement":null},{"id":"W4206907523","doi":"10.1007/978-3-030-94893-1_11","title":"Efficient Range Sensing Using Imperceptible Structured Light","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Structured light; Range (aeronautics); Computer science; Materials science; Artificial intelligence","score_opus":0.028431603592223024,"score_gpt":0.27549502166462997,"score_spread":0.24706341807240695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206907523","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004537553,0.0017198196,0.6500259,0.0006664829,0.001056906,0.0008795767,0.000048366255,0.0014646364,0.33960077],"genre_scores_gemma":[0.26788706,0.0015528462,0.73012453,0.00021528924,0.000027923414,0.000007759288,0.000034644836,0.000032689328,0.000117219286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990945,0.000006761543,0.00035635693,0.0001247382,0.00023703932,0.00018064209],"domain_scores_gemma":[0.99867916,0.00006202247,0.00007671081,0.0010499868,0.00009316156,0.00003898545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024855483,0.0001584498,0.00016757999,0.00071875326,0.00035844563,0.00015286503,0.0008868559,0.000072222494,0.00001915224],"category_scores_gemma":[0.000024623754,0.00016927694,0.000024781586,0.00030600946,0.0005399982,0.0010739106,0.0012977868,0.0005054154,0.000008777356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018904415,0.0000050324415,0.00001230927,0.0000680202,0.000009322956,0.0000010397599,0.0019219049,0.55619264,0.00031318664,0.18266168,0.00009897949,0.25871402],"study_design_scores_gemma":[0.00008961973,0.0000069227635,0.000047468126,0.000059592756,0.0000042739834,0.000022275452,0.00003764595,0.95793784,0.000024922327,0.002048956,0.03952965,0.00019081772],"about_ca_topic_score_codex":0.0000029971902,"about_ca_topic_score_gemma":0.0000017239067,"teacher_disagreement_score":0.40174523,"about_ca_system_score_codex":0.00031013446,"about_ca_system_score_gemma":0.000044504955,"threshold_uncertainty_score":0.69029135},"labels":[],"label_agreement":null},{"id":"W4207072846","doi":"10.1007/978-3-030-95630-1_12","title":"Exploring the Security of Software Defined Network Controllers","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Denial-of-service attack; Software-defined networking; Virtual LAN; Computer science; Computer security; Network security; Cloud computing; Network management; Computer network; World Wide Web; Operating system","score_opus":0.06920679470872806,"score_gpt":0.25758861318739995,"score_spread":0.1883818184786719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4207072846","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003492591,0.005041141,0.8290269,0.0038046222,0.0025056796,0.0014646032,0.000044468074,0.0003918212,0.15737155],"genre_scores_gemma":[0.3406056,0.061045777,0.58934367,0.006130684,0.00046458523,0.00079303514,0.0002036067,0.000075179516,0.001337856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99814063,0.00006334163,0.0007370979,0.00024268989,0.0005423398,0.0002739052],"domain_scores_gemma":[0.99577075,0.00095563463,0.00047599984,0.0024582478,0.0002686385,0.00007071715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017112342,0.00020267186,0.00030695662,0.00040986697,0.000919199,0.00030404777,0.004650477,0.000054785825,0.0000137484985],"category_scores_gemma":[0.00008332671,0.00016956823,0.000080166705,0.00075822964,0.0007657257,0.005054717,0.004392806,0.00058536365,0.000008409711],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003946839,0.0000092766295,0.000111076915,0.00001763195,0.000009359284,2.5099416e-7,0.0020274632,0.0073492285,6.288802e-8,0.83464515,0.00069443235,0.15513211],"study_design_scores_gemma":[0.0005729178,0.00010948685,0.0029252963,0.00023780549,0.000014004894,0.000024232862,0.0000420461,0.3616633,0.0000012813147,0.036632907,0.59732765,0.00044905348],"about_ca_topic_score_codex":0.000021677044,"about_ca_topic_score_gemma":0.000008164203,"teacher_disagreement_score":0.79801226,"about_ca_system_score_codex":0.00010348771,"about_ca_system_score_gemma":0.00031292936,"threshold_uncertainty_score":0.864182},"labels":[],"label_agreement":null},{"id":"W420931213","doi":"10.1007/978-3-642-35795-4_1","title":"Software Trustworthiness: Past, Present and Future","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Information and Cyber Security","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Software deployment; Trustworthiness; Software; Computer science; Government (linguistics); Software quality assurance; Software engineering; Software system; Software peer review; The Internet; Software construction; Computer security; World Wide Web; Operating system","score_opus":0.01950044557171182,"score_gpt":0.2555972065324211,"score_spread":0.23609676096070925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W420931213","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007039353,0.0017346116,0.42751312,0.015104028,0.0010972131,0.0011358229,0.000023598966,0.00037111627,0.5529501],"genre_scores_gemma":[0.014628864,0.025846738,0.9353336,0.012882986,0.0015864816,0.00025329282,0.00031934812,0.00004556942,0.00910309],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983269,0.000024618488,0.0006681675,0.00025514027,0.00048123,0.00024396823],"domain_scores_gemma":[0.9970098,0.0001064862,0.00034129285,0.0019056754,0.0004812234,0.00015548451],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006513546,0.00024944462,0.00024323986,0.00072529627,0.0005543746,0.0012062446,0.002612312,0.0001635799,0.000028355678],"category_scores_gemma":[0.000008888914,0.00023014811,0.00003807203,0.0003487644,0.0006682342,0.013113682,0.0030122611,0.00047295296,0.00011888069],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.071449e-7,0.0000052335336,0.000020349546,0.000023810615,0.0000025942793,1.30492e-7,0.0022396625,0.000012559273,4.622832e-8,0.5484418,0.0017760306,0.44747722],"study_design_scores_gemma":[0.00022106362,0.000024996267,0.0021443919,0.00007255331,0.00000298114,0.00003371253,0.000033884044,0.14988984,0.0000010091859,0.009925923,0.83735555,0.00029406778],"about_ca_topic_score_codex":0.000011966868,"about_ca_topic_score_gemma":0.0000029222651,"teacher_disagreement_score":0.8355795,"about_ca_system_score_codex":0.000074770345,"about_ca_system_score_gemma":0.00018537437,"threshold_uncertainty_score":0.9998306},"labels":[],"label_agreement":null},{"id":"W4212807595","doi":"10.1007/978-3-030-96040-7_3","title":"On the Performance Implications of Deploying IoT Apps as FaaS","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Software deployment; Internet of Things; Overhead (engineering); Cloud computing; Container (type theory); Architecture; Distributed computing; Computer security; Operating system; Engineering","score_opus":0.036586623837313315,"score_gpt":0.28207357319215665,"score_spread":0.24548694935484333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212807595","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014712028,0.0009180398,0.12698114,0.011318825,0.0012557842,0.002695176,0.000041136234,0.00057102,0.84150684],"genre_scores_gemma":[0.97587436,0.003278208,0.01769963,0.0022281017,0.00002890971,0.00019640045,0.00001827419,0.000017795934,0.0006583084],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812484,0.000049964703,0.00078181864,0.0002708926,0.0005648484,0.0002076483],"domain_scores_gemma":[0.9950636,0.00066852215,0.00048042205,0.003397349,0.00032805532,0.00006204061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001847291,0.00019303245,0.00023188657,0.00063354213,0.0010832519,0.00022059857,0.004937297,0.00008005624,0.000032819637],"category_scores_gemma":[0.00007815078,0.0001482373,0.00006214098,0.0006787289,0.0008529428,0.0025473875,0.0027627493,0.0005522414,0.00007777196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016395376,0.00001555602,0.00021168233,0.00003135736,0.000004300992,3.8384623e-8,0.0012747794,0.0008067067,0.0000016682403,0.8965513,0.0001634786,0.10093749],"study_design_scores_gemma":[0.0006532564,0.0005457487,0.0156066865,0.00080574193,0.000018996177,0.000111257556,0.00013122772,0.51740676,0.000110594076,0.06564717,0.3979303,0.0010322455],"about_ca_topic_score_codex":0.00001836903,"about_ca_topic_score_gemma":0.0000025096992,"teacher_disagreement_score":0.9611623,"about_ca_system_score_codex":0.00017497473,"about_ca_system_score_gemma":0.0004112042,"threshold_uncertainty_score":0.91748095},"labels":[],"label_agreement":null},{"id":"W4214519772","doi":"10.1007/978-3-030-96878-6_8","title":"Event-Based Looming Objects Detection","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Looming; Asynchronous communication; Event (particle physics); Computer science; Artificial intelligence; Computer vision; Telecommunications; Physics; Optics","score_opus":0.026995332752361045,"score_gpt":0.26548564461994,"score_spread":0.23849031186757896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214519772","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021438587,0.0010895394,0.66333115,0.00013976103,0.0014467001,0.0007292722,0.000021036378,0.000617976,0.3304807],"genre_scores_gemma":[0.9885473,0.00079747423,0.009977761,0.00032517037,0.000037970192,0.000024801646,0.000043113094,0.00001608677,0.00023032143],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918276,0.000011891277,0.00035502313,0.00011142346,0.00019866286,0.00014020894],"domain_scores_gemma":[0.9990252,0.00012120337,0.00009771413,0.00064799574,0.0000626721,0.000045203262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036656475,0.00013566377,0.00012743607,0.00054694,0.00046972456,0.00009761951,0.0006363941,0.000049650185,0.000019349298],"category_scores_gemma":[0.000015256294,0.00015716108,0.000028647173,0.00023606047,0.0001912703,0.0021804862,0.00043997928,0.0004583162,0.000013032366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003742845,0.0000059281733,0.0000061908386,0.000083770494,0.000004295706,6.334023e-7,0.0008375508,0.4167745,0.00020256109,0.020388085,0.000025440617,0.56166726],"study_design_scores_gemma":[0.00015404512,0.000026980424,0.00006897417,0.00008430592,0.000003357015,0.000010591887,0.000018218263,0.91139764,0.0004360378,0.0005999852,0.086991586,0.00020826753],"about_ca_topic_score_codex":0.000001328114,"about_ca_topic_score_gemma":0.0000053933663,"teacher_disagreement_score":0.98640347,"about_ca_system_score_codex":0.00018363714,"about_ca_system_score_gemma":0.000054515764,"threshold_uncertainty_score":0.6408843},"labels":[],"label_agreement":null},{"id":"W4220810508","doi":"10.1007/978-981-19-1280-1_23","title":"Gradient Acoustic Surfaces","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","score_opus":0.02376983729566815,"score_gpt":0.2513111723055403,"score_spread":0.22754133500987214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220810508","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008095877,0.00093989365,0.1053258,0.00048439123,0.00081632315,0.000579542,0.000060014496,0.0003313305,0.89065313],"genre_scores_gemma":[0.93537116,0.02104213,0.038310606,0.001071323,0.00005309919,0.0001277904,0.0007462455,0.000042983647,0.003234634],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991303,0.000010347244,0.00037608435,0.000093737886,0.00025334724,0.0001361764],"domain_scores_gemma":[0.9991028,0.00009539321,0.00007960999,0.0005863091,0.00008606081,0.00004983714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038958946,0.00012374314,0.00012257448,0.00040710185,0.0003033547,0.00015876231,0.00063472125,0.00004565959,0.00008040009],"category_scores_gemma":[0.000014562336,0.00013828883,0.00001889895,0.00019659994,0.00027754612,0.0023905968,0.0002842044,0.0003096419,0.000035696477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036182207,0.000014684688,0.00003146853,0.00009712572,0.000015876201,3.793587e-7,0.0074515315,0.16700932,0.000086783344,0.6675985,0.0028903154,0.1548004],"study_design_scores_gemma":[0.00012770327,0.00003218273,0.0005157891,0.000035748773,0.000005322024,0.0000084871135,0.000040172068,0.8020167,0.00000828879,0.0023225183,0.19467603,0.00021109154],"about_ca_topic_score_codex":0.000003321774,"about_ca_topic_score_gemma":0.000011697305,"teacher_disagreement_score":0.9345616,"about_ca_system_score_codex":0.00018568189,"about_ca_system_score_gemma":0.000077621306,"threshold_uncertainty_score":0.56392545},"labels":[],"label_agreement":null},{"id":"W4220958842","doi":"10.1007/978-981-19-1280-1_22","title":"CDPR Studio: A Parametric Design Tool for Simulating Cable-Suspended Parallel Robots","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Innovations in Concrete and Construction Materials","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Parallel manipulator; Winch; Fabrication; Computer science; Robot; Frame (networking); Parametric statistics; Mobile robot; Control engineering; Simulation; Engineering; Mechanical engineering; Telecommunications; Artificial intelligence","score_opus":0.06471241352422899,"score_gpt":0.2899715112525515,"score_spread":0.2252590977283225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220958842","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002631648,0.00034290794,0.9040999,0.00012579077,0.0010166498,0.0015107596,0.000078296725,0.00025162153,0.092310935],"genre_scores_gemma":[0.13318582,0.0025813787,0.86138546,0.0005521755,0.0001273425,0.0006217133,0.0003439823,0.000051694573,0.0011504352],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844146,0.000027015518,0.0008386452,0.00017730432,0.0002914773,0.00022411384],"domain_scores_gemma":[0.99794984,0.0005078303,0.00021889698,0.0009747189,0.00031319252,0.00003550593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012605751,0.00021357821,0.0002802875,0.0011056674,0.0006861259,0.0003479037,0.000999167,0.00010252368,0.00011399535],"category_scores_gemma":[0.00009316352,0.00024253459,0.000042910422,0.00059918116,0.0003049255,0.0024386747,0.0005598433,0.00030831163,0.000014673258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068366676,0.0000040243485,0.000012140452,0.000064604494,0.000021621476,1.6296367e-7,0.00046598326,0.6094394,0.000008346748,0.29600957,0.0005945457,0.093372785],"study_design_scores_gemma":[0.0003965972,0.000040526247,0.000040697563,0.000055712906,0.00001245951,0.000012861434,0.00003517343,0.86107,0.000013671261,0.005482007,0.13251474,0.0003255708],"about_ca_topic_score_codex":0.000004411708,"about_ca_topic_score_gemma":9.390759e-7,"teacher_disagreement_score":0.29052758,"about_ca_system_score_codex":0.00023933272,"about_ca_system_score_gemma":0.00015784928,"threshold_uncertainty_score":0.9890274},"labels":[],"label_agreement":null},{"id":"W4225754821","doi":"10.1007/978-3-030-99885-1_40","title":"Assessing Media and Information Literacy: Teenagers’ Practices and Competence in Information Search and Multimedia Creation","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Competence (human resources); Information literacy; Media literacy; Computer science; Multimedia; World Wide Web; Literacy; Psychology; Pedagogy; Social psychology","score_opus":0.07280668638688935,"score_gpt":0.3983541777892038,"score_spread":0.3255474914023144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225754821","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1771221,0.0047032274,0.020116948,0.038897425,0.0022192958,0.005886347,0.00020060876,0.0005701549,0.7502839],"genre_scores_gemma":[0.94662935,0.021627532,0.030498091,0.00068481907,0.000034289787,0.000066346474,0.0003882854,0.0000061462224,0.00006515605],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981639,0.00013166179,0.0007188923,0.00018359105,0.000558327,0.00024364147],"domain_scores_gemma":[0.9976368,0.00075329613,0.00061422196,0.0004879149,0.0003952263,0.00011253827],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0030300515,0.00017851694,0.00021189611,0.0018292296,0.0012829207,0.0016204816,0.00062155956,0.00019910207,0.000023543651],"category_scores_gemma":[0.0006404785,0.00019620203,0.000013727878,0.0005716749,0.001926795,0.048104737,0.0009287653,0.0006750305,0.0000075226753],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059031854,0.000015568532,0.003872944,0.00007679085,0.000004745078,1.6808528e-7,0.15141934,0.00004185649,0.0000018497527,0.24119647,0.000026195283,0.6033382],"study_design_scores_gemma":[0.0015945694,0.00012818053,0.2519699,0.00059966336,0.00004638957,0.00006853399,0.045757238,0.21560119,0.000007902304,0.01566391,0.4674916,0.0010709126],"about_ca_topic_score_codex":0.0008028269,"about_ca_topic_score_gemma":0.00024516482,"teacher_disagreement_score":0.7695072,"about_ca_system_score_codex":0.0002291213,"about_ca_system_score_gemma":0.000479616,"threshold_uncertainty_score":0.99941593},"labels":[],"label_agreement":null},{"id":"W4225772450","doi":"10.1007/978-981-19-9865-2_10","title":"Machine Learning for Multimodal Electronic Health Records-Based Research: Challenges and Perspectives","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Health records; Modalities; Unstructured data; Electronic health record; Machine learning; Artificial intelligence; Digital library; Data science; Information retrieval; Data mining; Big data; Health care","score_opus":0.2531785037105655,"score_gpt":0.4162408136605928,"score_spread":0.1630623099500273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225772450","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000093275645,0.053317625,0.7257612,0.12636104,0.0007589623,0.004644929,0.000050646195,0.0012071166,0.08780522],"genre_scores_gemma":[0.20340975,0.28488192,0.5023238,0.0020820075,0.00023643022,0.00057133165,0.00028297235,0.00010231548,0.006109502],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99757206,0.00022386879,0.0005875732,0.00050324487,0.0005557789,0.0005574817],"domain_scores_gemma":[0.99576193,0.0015443962,0.0003371369,0.0014752977,0.0007207857,0.00016043129],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006332593,0.00021788948,0.0003088399,0.0017543092,0.0013683143,0.0004230444,0.0023512654,0.00012535488,0.0000019359768],"category_scores_gemma":[0.0004207505,0.00022511976,0.00004137378,0.00045728896,0.0008266307,0.0022222619,0.0018837625,0.0014544104,0.000013264488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003302557,0.0000071701866,0.00002295911,0.00009718545,0.0000027441322,8.247101e-8,0.008237649,0.00046026742,8.749233e-8,0.5726699,0.000027694208,0.41847095],"study_design_scores_gemma":[0.00029503647,0.00035467395,0.0011430727,0.00025376957,0.0000010892842,0.000006658427,0.00020998776,0.88355273,2.8645624e-7,0.0167271,0.09725396,0.00020163327],"about_ca_topic_score_codex":0.00010725307,"about_ca_topic_score_gemma":0.00021155569,"teacher_disagreement_score":0.88309246,"about_ca_system_score_codex":0.000392996,"about_ca_system_score_gemma":0.0010284389,"threshold_uncertainty_score":0.99993175},"labels":[],"label_agreement":null},{"id":"W4225828609","doi":"10.1007/978-3-030-98876-0_11","title":"KG-Visual: A Tool for Visualizing RDF Knowledge Graphs","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cape Breton University","funders":"","keywords":"SPARQL; RDF; Computer science; RDF Schema; Visualization; Information retrieval; Simple Knowledge Organization System; JavaScript; Linked data; Zoom; Semantic Web; Named graph; Cwm; Python (programming language); World Wide Web; Data mining; Programming language","score_opus":0.062317874764127514,"score_gpt":0.35119905284797676,"score_spread":0.2888811780838492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225828609","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021314262,0.0025734073,0.7632057,0.0016344102,0.0012445285,0.0012602845,0.000021042311,0.00036587712,0.22948158],"genre_scores_gemma":[0.11053714,0.016386082,0.8586442,0.006307385,0.0001721523,0.0008510693,0.00029885652,0.000060728664,0.0067423917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99824816,0.000039149276,0.0007045251,0.00034449584,0.00036554335,0.00029813114],"domain_scores_gemma":[0.99689084,0.0005854606,0.0003283052,0.0017837341,0.0003424571,0.00006918436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015263456,0.00023335028,0.0002965768,0.0012104741,0.00096382794,0.0006989582,0.0041921334,0.000100151774,0.000012774868],"category_scores_gemma":[0.00008819416,0.00023689873,0.000089237066,0.0005479956,0.0006266776,0.0059802895,0.004103941,0.00034525534,0.000024339688],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016173332,0.000016479962,0.000025865638,0.00003001614,0.0000044625217,1.5050306e-7,0.001625512,0.000026304626,0.0000013876265,0.8370166,0.00049922185,0.16075242],"study_design_scores_gemma":[0.00035252277,0.00012035021,0.0006497914,0.00010587502,0.000007278289,0.00001986328,0.000061347775,0.39561456,0.000008183061,0.0359538,0.56670934,0.00039712357],"about_ca_topic_score_codex":0.00000990432,"about_ca_topic_score_gemma":0.000008939765,"teacher_disagreement_score":0.80106276,"about_ca_system_score_codex":0.00014879549,"about_ca_system_score_gemma":0.00038428378,"threshold_uncertainty_score":0.96604496},"labels":[],"label_agreement":null},{"id":"W4226194913","doi":"10.1007/978-3-031-04112-9_3","title":"Color Vision Deficiency and Live Recoloring","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"RGB color model; Computer science; Artificial intelligence; Computer vision; Trichromacy; Blindness; Color space; Scheme (mathematics); Color vision; Compensation (psychology); Classification scheme; Optometry; Medicine; Mathematics; Image (mathematics); Psychology; Information retrieval","score_opus":0.030875507558446914,"score_gpt":0.2985303995455743,"score_spread":0.2676548919871274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226194913","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00031301196,0.0009813734,0.52837163,0.0015386122,0.00046333033,0.00088670786,0.000009657019,0.0003382182,0.46709743],"genre_scores_gemma":[0.080175646,0.018771373,0.89603204,0.0022726548,0.000039081504,0.00021932136,0.000053592634,0.000021942828,0.002414355],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984486,0.00003431735,0.00052618975,0.00032071848,0.00045384263,0.00021632228],"domain_scores_gemma":[0.9976102,0.000200451,0.00029654524,0.0016104389,0.00021177999,0.00007058023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013747541,0.00018321574,0.00019148148,0.0009227877,0.0008252819,0.00066329056,0.0029720268,0.00007078928,0.000022578388],"category_scores_gemma":[0.000041564537,0.00019439042,0.000024977713,0.00039348996,0.00069167773,0.009574505,0.0066527547,0.00042933546,0.00002593064],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011538673,0.000012761126,0.000018993222,0.000018576544,0.0000013497419,4.810724e-7,0.0016601444,0.00002721092,0.000010974781,0.70898104,0.00021577795,0.28905153],"study_design_scores_gemma":[0.0003646783,0.00042972623,0.0018655981,0.0002529238,0.0000074822183,0.00006663105,0.00005743215,0.49924776,0.0000751097,0.019438824,0.4774767,0.00071716827],"about_ca_topic_score_codex":0.000013086474,"about_ca_topic_score_gemma":0.0000068532736,"teacher_disagreement_score":0.68954223,"about_ca_system_score_codex":0.00022276177,"about_ca_system_score_gemma":0.0001941802,"threshold_uncertainty_score":0.82921827},"labels":[],"label_agreement":null},{"id":"W4230690017","doi":"10.1007/978-3-030-36368-0","title":"Advances in Data Science, Cyber Security and IT Applications","year":2019,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Data science","score_opus":0.02838750736149086,"score_gpt":0.30965641823436924,"score_spread":0.28126891087287836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230690017","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011467573,0.0045135794,0.4304322,0.0026258691,0.000852045,0.0018632339,0.000053579588,0.00016399106,0.5593808],"genre_scores_gemma":[0.18406609,0.3206391,0.47734377,0.011079529,0.0005978655,0.0007086419,0.0009634005,0.00006289689,0.004538717],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99760795,0.00005673715,0.00071294664,0.0006416076,0.0006383662,0.00034240945],"domain_scores_gemma":[0.9946783,0.00027393227,0.00033357696,0.0042482154,0.0003420204,0.00012396646],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.0028716703,0.0002113302,0.0002685235,0.0017096298,0.00070413825,0.0010735051,0.007751777,0.00012923767,0.00000393949],"category_scores_gemma":[0.00006635952,0.00021676769,0.000017859904,0.0025951352,0.002092135,0.033663835,0.009522306,0.00064303493,0.00004794623],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002315413,0.000041365638,0.000105690975,0.000075444645,0.0000014686435,1.8921328e-7,0.002743056,0.00019005379,0.0000017983492,0.4115666,0.0009936821,0.58427835],"study_design_scores_gemma":[0.0001671921,0.000018871408,0.00029916526,0.00012930467,0.0000016849037,0.000014750579,0.000027158663,0.42984244,0.000002225878,0.009354751,0.5599461,0.00019632968],"about_ca_topic_score_codex":0.000015506657,"about_ca_topic_score_gemma":0.00011870797,"teacher_disagreement_score":0.584082,"about_ca_system_score_codex":0.00023947355,"about_ca_system_score_gemma":0.0010851335,"threshold_uncertainty_score":0.99996346},"labels":[],"label_agreement":null},{"id":"W4233750073","doi":"10.1007/978-3-030-93736-2_56","title":"Dream to Explore: 5-HT2a as Adaptive Temperature Parameter for Sophisticated Affective Inference","year":2021,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Psychedelics and Drug Studies","field":"Psychology","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Inference; Adversarial system; Computer science; Artificial intelligence; Dream; Psychology; Dopamine; Machine learning; Cognitive psychology; Cognitive science; Neuroscience","score_opus":0.13898076247569832,"score_gpt":0.4008947501175498,"score_spread":0.2619139876418515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233750073","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016215506,0.0019252893,0.13894068,0.0052235243,0.0017836522,0.0028143732,0.00023518858,0.00014170719,0.84731406],"genre_scores_gemma":[0.88484204,0.0024946919,0.08825297,0.009035185,0.00022416156,0.0015301309,0.0005053686,0.000051388255,0.013064053],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986483,0.000041286967,0.00048646604,0.00034523616,0.0002282891,0.00025044303],"domain_scores_gemma":[0.99652857,0.00095455116,0.00019931418,0.0013621162,0.0008418259,0.00011363257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005973787,0.0002441787,0.00032178787,0.00056627515,0.00046389486,0.000247399,0.0010387925,0.00017360724,0.000037769634],"category_scores_gemma":[0.00025739917,0.0002349747,0.000060538016,0.0003567703,0.0006575874,0.0008710785,0.00095116434,0.0003782355,0.00012430424],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002897022,0.000040687795,0.000019500609,0.000015162156,0.00003995447,5.048014e-7,0.012140588,0.00003418818,0.0000065875597,0.90262663,0.0028896374,0.082157604],"study_design_scores_gemma":[0.0023331668,0.0012713918,0.0068176594,0.0013344802,0.0001037674,0.00006034987,0.004083479,0.026101142,0.000076165736,0.097575895,0.858072,0.0021705448],"about_ca_topic_score_codex":0.000017103328,"about_ca_topic_score_gemma":0.000019262372,"teacher_disagreement_score":0.8832205,"about_ca_system_score_codex":0.00011422743,"about_ca_system_score_gemma":0.00019874643,"threshold_uncertainty_score":0.95819896},"labels":[],"label_agreement":null},{"id":"W4236178279","doi":"10.1007/978-3-030-36365-9","title":"Advances in Data Science, Cyber Security and IT Applications","year":2019,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Network security; Computer security; Information security; Data science","score_opus":0.19542752318846085,"score_gpt":0.42541409552921283,"score_spread":0.22998657234075198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236178279","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032190248,0.0047807684,0.07316661,0.010419447,0.0003936331,0.0030604142,0.00101433,0.00016810531,0.9066748],"genre_scores_gemma":[0.41464573,0.27461183,0.2829666,0.009116889,0.00033695923,0.0016297991,0.0038597486,0.00007948075,0.012752926],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962732,0.000046339308,0.0012144392,0.0008489949,0.0012620329,0.00035500136],"domain_scores_gemma":[0.989792,0.0009877029,0.0005624833,0.007908114,0.00063165784,0.00011806276],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.006600542,0.00022094123,0.00036263457,0.0025646025,0.00078495307,0.001429977,0.013407706,0.0001678309,0.00001295609],"category_scores_gemma":[0.0006671801,0.00019201945,0.000021112777,0.004344832,0.0054597375,0.021801531,0.013517541,0.00065175287,0.00016697338],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018119407,0.000038686365,0.0006269292,0.000022766106,0.0000010704127,7.98532e-8,0.0007697287,0.000056843488,0.0000019001536,0.3232496,0.00581613,0.66941446],"study_design_scores_gemma":[0.00016481332,0.000011378012,0.0015220405,0.00007256742,0.0000028271497,0.000008542197,0.00032649736,0.08967214,0.00000160076,0.044825483,0.86317825,0.00021385218],"about_ca_topic_score_codex":0.00001657294,"about_ca_topic_score_gemma":0.00018897478,"teacher_disagreement_score":0.89392185,"about_ca_system_score_codex":0.00019676719,"about_ca_system_score_gemma":0.0011985797,"threshold_uncertainty_score":0.9996066},"labels":[],"label_agreement":null},{"id":"W4237811319","doi":"10.1007/978-3-642-22098-2_79","title":"Verbalizing Images","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Web Applications and Data Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Usability; Appeal; Meaning (existential); Computer science; World Wide Web; Content (measure theory); Multimedia; Human–computer interaction; Information retrieval; Psychology; Mathematics","score_opus":0.049219989293695386,"score_gpt":0.28034492898736646,"score_spread":0.23112493969367107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237811319","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000013654359,0.00020748311,0.51054496,0.0004696525,0.00009793739,0.00018962135,0.000008364957,0.00006993823,0.4884107],"genre_scores_gemma":[0.026017902,0.012760396,0.9504626,0.0029761821,0.00006601192,0.00012396042,0.00015362239,0.000020320835,0.0074190353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986801,0.000013372072,0.0005091843,0.0002914497,0.00030985987,0.00019600334],"domain_scores_gemma":[0.9960861,0.00006834383,0.00025233667,0.0032807696,0.00022729264,0.00008514805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083267066,0.00017514694,0.00016759205,0.00085357676,0.0004055693,0.0007403112,0.0048062555,0.00007078694,0.000014514269],"category_scores_gemma":[0.000013878693,0.00017737076,0.000031524418,0.0003679899,0.00061334524,0.009027552,0.005109783,0.00025377652,0.00020805407],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.4293132e-7,0.0000061812193,0.0000061243736,0.00000829749,0.000001913544,1.3493349e-7,0.00030920198,0.000006763792,6.344921e-7,0.7610629,0.00070902985,0.23788856],"study_design_scores_gemma":[0.00015266535,0.000026199821,0.0010331967,0.000096201395,0.000004821255,0.000011408769,0.00000808283,0.053470295,0.0000117319505,0.050956473,0.8939146,0.00031434765],"about_ca_topic_score_codex":0.000021964548,"about_ca_topic_score_gemma":0.0000037606726,"teacher_disagreement_score":0.8932055,"about_ca_system_score_codex":0.00009042982,"about_ca_system_score_gemma":0.00014613854,"threshold_uncertainty_score":0.8931298},"labels":[],"label_agreement":null},{"id":"W42443586","doi":"10.1007/978-3-642-36907-0_19","title":"An Approach on Merging Agents’ Trust Distributions in a Possibilitic Domain","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Access Control and Trust","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Trustworthiness; Computer science; Set (abstract data type); Order (exchange); Domain (mathematical analysis); Distribution (mathematics); Block (permutation group theory); Multi-agent system; Artificial intelligence; Computer security; Mathematics; Business","score_opus":0.046085823323221274,"score_gpt":0.33289160534924067,"score_spread":0.2868057820260194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W42443586","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033146746,0.00011062062,0.019666227,0.0011122611,0.00015400516,0.0007606573,0.00003777508,0.00006222968,0.9747816],"genre_scores_gemma":[0.9832311,0.0007326704,0.014097842,0.0005120568,0.000060045335,0.00008916195,0.00016768774,0.0000071761237,0.0011022153],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841845,0.00009579345,0.0005337446,0.0002282247,0.00043798736,0.00028581166],"domain_scores_gemma":[0.9982098,0.00016166815,0.00020464492,0.0010733947,0.00020815812,0.00014233745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015195478,0.00015669705,0.00020651736,0.00069479976,0.0010860683,0.0006557027,0.001791802,0.00013526613,0.00006138279],"category_scores_gemma":[0.00006985438,0.00015267992,0.00003585165,0.00042987894,0.0016315213,0.005146988,0.0003680361,0.00041117147,0.0000638022],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017712928,0.00004004246,0.00029730995,0.000006916382,0.0000018675507,1.2444595e-7,0.0069111073,0.000111971895,2.3117607e-7,0.92674476,0.000046940975,0.06583698],"study_design_scores_gemma":[0.0016899239,0.0001531467,0.068410896,0.0005476349,0.000021226882,0.0000069781886,0.0047935117,0.39093697,0.0000012951854,0.14343245,0.3887004,0.0013055763],"about_ca_topic_score_codex":0.00039805143,"about_ca_topic_score_gemma":0.00015911093,"teacher_disagreement_score":0.97991645,"about_ca_system_score_codex":0.00032222518,"about_ca_system_score_gemma":0.00032749271,"threshold_uncertainty_score":0.83532697},"labels":[],"label_agreement":null},{"id":"W4245334931","doi":"10.1007/978-981-15-0108-1","title":"Advanced Informatics for Computing Research","year":2019,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Internet of Things and AI","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Informatics; Computer science; Data science; Information retrieval; World Wide Web; Library science; Political science","score_opus":0.07401254102139372,"score_gpt":0.38761042091115405,"score_spread":0.31359787988976034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245334931","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000071978044,0.00018364676,0.76338935,0.0008679162,0.0006818483,0.000960678,0.000010599422,0.000089683585,0.2337443],"genre_scores_gemma":[0.0125843575,0.000824579,0.9716646,0.0022377796,0.000100463396,0.00006392479,0.00011031226,0.000016304692,0.012397678],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759865,0.00005129749,0.0009213556,0.00024066356,0.0007194821,0.00046857592],"domain_scores_gemma":[0.99504524,0.0008364031,0.0004235693,0.0023762223,0.0012228665,0.0000956767],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.004222551,0.00020121431,0.00029272976,0.0015048431,0.0007168377,0.001465949,0.006801801,0.00014651188,0.0000013532276],"category_scores_gemma":[0.00015665493,0.0001991322,0.00005961723,0.0008474838,0.0007141989,0.0100628305,0.005471194,0.00073977414,0.00009163745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002568383,0.000015418485,0.000007433906,0.00014374127,0.0000041871945,6.853146e-8,0.0066836737,0.00081922236,0.0000015676968,0.65768176,0.0068903863,0.32774994],"study_design_scores_gemma":[0.0002525403,0.00007602538,0.000054315584,0.00027795945,0.000001091307,0.00000656686,0.000053875916,0.6227822,0.0000071589607,0.005535865,0.37077832,0.00017411837],"about_ca_topic_score_codex":0.000004787861,"about_ca_topic_score_gemma":0.0000022707995,"teacher_disagreement_score":0.6521459,"about_ca_system_score_codex":0.0003565936,"about_ca_system_score_gemma":0.0009942574,"threshold_uncertainty_score":0.9995706},"labels":[],"label_agreement":null},{"id":"W4246152626","doi":"10.1007/978-3-030-50153-2","title":"Information Processing and Management of Uncertainty in Knowledge-Based Systems","year":2020,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Knowledge representation and reasoning; Fuzzy logic; Semantics (computer science); Artificial intelligence; Representation (politics); Knowledge acquisition; Machine learning; Information retrieval; Natural language processing; Programming language","score_opus":0.029792051275755828,"score_gpt":0.27282049400534697,"score_spread":0.24302844272959115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246152626","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001028537,0.0035648681,0.5944511,0.0010635268,0.00039955866,0.0016494009,0.000015867607,0.00011880509,0.39863402],"genre_scores_gemma":[0.94745696,0.002927551,0.048018508,0.0008198865,0.00003845104,0.0002499882,0.000116545576,0.000009052426,0.00036306336],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982871,0.00007066177,0.0009296839,0.00016537987,0.00036286208,0.00018435494],"domain_scores_gemma":[0.99810094,0.00011810664,0.00048206243,0.0009128772,0.00030919912,0.0000768368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011556884,0.00017199675,0.0003123872,0.0008378094,0.0001782212,0.0005860776,0.0020875204,0.00009538226,1.6580384e-7],"category_scores_gemma":[0.000017745022,0.0001627921,0.000023580513,0.0010259121,0.00043179325,0.0064135273,0.00131978,0.00023997642,0.000009072279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007544407,0.00003333254,0.0001078639,0.0018794144,0.000007435815,4.866746e-7,0.007387483,0.009377224,8.3690225e-7,0.5106874,0.00034614146,0.47016484],"study_design_scores_gemma":[0.0005445118,0.000041443862,0.0013002781,0.0010351322,0.000003831644,0.0000042902134,0.00015456873,0.9580326,5.2564087e-7,0.0011113978,0.037595116,0.00017630044],"about_ca_topic_score_codex":0.000026665914,"about_ca_topic_score_gemma":0.0000059509043,"teacher_disagreement_score":0.94865537,"about_ca_system_score_codex":0.00020321154,"about_ca_system_score_gemma":0.00057679147,"threshold_uncertainty_score":0.6638469},"labels":[],"label_agreement":null},{"id":"W4249646270","doi":"10.1007/978-3-642-40576-1","title":"Security in Computing and Communications","year":2013,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Information and Cyber Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Computer security","score_opus":0.026100628482499427,"score_gpt":0.295029595458491,"score_spread":0.26892896697599156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249646270","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011693154,0.0022708478,0.19286579,0.006812208,0.0006153602,0.0018760829,0.000027330258,0.0003601866,0.7940029],"genre_scores_gemma":[0.5603971,0.018460728,0.40839374,0.009810558,0.00010091654,0.00020219585,0.00040551872,0.000035152127,0.0021941194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764234,0.00012721884,0.0010970759,0.0003103026,0.0004519305,0.00037112224],"domain_scores_gemma":[0.9949723,0.0003880832,0.00044716793,0.003623696,0.00041339736,0.00015534348],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0018976721,0.00027349085,0.00035030453,0.0015225593,0.0006361538,0.001319819,0.0058750175,0.00019196114,0.0000047548383],"category_scores_gemma":[0.00007313042,0.00029097396,0.000036930378,0.0011812657,0.0014042368,0.013192047,0.008094251,0.00092729816,0.00007902952],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.238165e-7,0.000036033885,0.00025020028,0.000058643338,0.0000032694913,2.3347803e-7,0.01400531,0.00003970349,3.8563246e-7,0.8392098,0.0012603054,0.14513539],"study_design_scores_gemma":[0.00039402128,0.000024682906,0.004881828,0.00022733619,0.0000023362536,0.000029242326,0.00010836063,0.8465234,0.0000016842915,0.015413319,0.1320347,0.00035910512],"about_ca_topic_score_codex":0.000075556985,"about_ca_topic_score_gemma":0.000080910024,"teacher_disagreement_score":0.84648365,"about_ca_system_score_codex":0.00029530431,"about_ca_system_score_gemma":0.00061259256,"threshold_uncertainty_score":0.9999542},"labels":[],"label_agreement":null},{"id":"W4285109489","doi":"10.1007/978-3-031-06388-6_30","title":"Beyond Skin-Deep Investigations of Epidermal Activity to Predict Mental Workload Using Multiple Phasic Components: Implications for Real-Time Analysis Using Affordable Wearables","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Workload; Principal component analysis; Task (project management); Computer science; Simulation; Artificial intelligence; Engineering; Operating system","score_opus":0.10286066977910345,"score_gpt":0.35636206708347234,"score_spread":0.2535013973043689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285109489","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010990446,0.00008118432,0.97777396,0.0004806414,0.0001103516,0.001414552,0.0012440019,0.000058359128,0.00784652],"genre_scores_gemma":[0.05645093,0.0002972687,0.9424676,0.00014156883,0.00002699144,0.00010978443,0.00033194738,0.000018855824,0.00015510552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818087,0.000058960544,0.00087235065,0.0002680377,0.00036212668,0.000257629],"domain_scores_gemma":[0.9964674,0.0014167405,0.0005633823,0.0010450423,0.00034261675,0.00016482864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007676201,0.00022161109,0.000512807,0.0010184816,0.0009738103,0.000119869735,0.00096408546,0.00007834453,0.000052588788],"category_scores_gemma":[0.00018748215,0.00023097836,0.0001254731,0.0011284592,0.0007499562,0.0016576112,0.0010651414,0.00022447183,0.0000028378392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091828624,0.0006844584,0.0014672503,0.00035967247,0.00058332394,2.7204786e-7,0.007330768,0.032893673,0.001907854,0.6704502,0.000399142,0.28383157],"study_design_scores_gemma":[0.00031525866,0.000057612448,0.0012891247,0.000098390745,0.0001815319,0.000005271266,0.00003744402,0.9562657,0.000035141773,0.039128732,0.0023332678,0.00025254072],"about_ca_topic_score_codex":0.00015767067,"about_ca_topic_score_gemma":0.000022514481,"teacher_disagreement_score":0.92337203,"about_ca_system_score_codex":0.00029533094,"about_ca_system_score_gemma":0.00017753577,"threshold_uncertainty_score":0.94190246},"labels":[],"label_agreement":null},{"id":"W4285126916","doi":"10.1007/978-3-031-06767-9_11","title":"An MR Image Segmentation Method Based on Dictionary Learning Preprocessing and Probability Statistics","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preprocessor; Artificial intelligence; Pattern recognition (psychology); Computer science; Segmentation; Computer vision","score_opus":0.03704505967374353,"score_gpt":0.3574921288469968,"score_spread":0.3204470691732533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285126916","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001610047,0.00003688417,0.9804914,0.00035667143,0.000080708414,0.00047401027,0.000022008307,0.00018991904,0.018332273],"genre_scores_gemma":[0.0020660963,0.00032537378,0.996179,0.0010183344,0.000011215233,0.000079607606,0.00019746019,0.000008082528,0.00011481921],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978421,0.00020698263,0.0006317737,0.0004282235,0.00072027545,0.0001706619],"domain_scores_gemma":[0.9972959,0.0005014568,0.00042222557,0.0013156465,0.00033401608,0.00013072764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025634626,0.0001973824,0.00019381038,0.00077864376,0.00091912964,0.00076687743,0.0015361648,0.000072260715,0.000045738463],"category_scores_gemma":[0.00013407838,0.00020931181,0.000019745998,0.0003617256,0.00069668674,0.008109361,0.0011481785,0.00063195964,0.0000050103076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005631449,0.000052909058,0.00008153327,0.00008291737,0.0000030181839,6.9198785e-7,0.0022187177,0.0027439774,0.000058954614,0.12196365,0.00008715372,0.87270087],"study_design_scores_gemma":[0.00021411531,0.00019984112,0.00057888124,0.000081861464,0.000005033672,0.0000101848855,0.00003578215,0.9849203,0.00011061387,0.009631137,0.003989715,0.00022248391],"about_ca_topic_score_codex":0.0000129945665,"about_ca_topic_score_gemma":0.0000017985413,"teacher_disagreement_score":0.98217636,"about_ca_system_score_codex":0.00024629457,"about_ca_system_score_gemma":0.00032914005,"threshold_uncertainty_score":0.8535488},"labels":[],"label_agreement":null},{"id":"W4285212321","doi":"10.1007/978-3-031-06417-3_44","title":"A Web-Based Tool to Identify Interventions to Reduce Transmission of Antimicrobial Resistance","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; Mount Royal University; University of Calgary","funders":"","keywords":"Sociotechnical system; SPARK (programming language); Psychological intervention; Knowledge management; Transmission (telecommunications); Antimicrobial stewardship; Resistance (ecology); Business; Computer science; Antibiotic resistance; Data science; Medicine; Risk analysis (engineering); Biology; Nursing","score_opus":0.40146761219438803,"score_gpt":0.5973304687012219,"score_spread":0.19586285650683383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285212321","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013201149,0.00019852904,0.39864582,0.10320387,0.00256412,0.012887295,0.00191452,0.0003329508,0.46705174],"genre_scores_gemma":[0.3142024,0.0015862392,0.5784353,0.08554945,0.00017923121,0.0017571527,0.00040669402,0.00008261922,0.017800929],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961837,0.00026256707,0.002101278,0.0003173873,0.00072110567,0.00041394963],"domain_scores_gemma":[0.9958682,0.00082311494,0.00072972436,0.0015880904,0.00073167874,0.0002591992],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0046396726,0.00019086107,0.000347267,0.00209464,0.0015585407,0.00007714859,0.0022102233,0.00010286035,0.00045754135],"category_scores_gemma":[0.00042250982,0.00020806528,0.0000794064,0.0012551479,0.0004379805,0.0019663805,0.0015382653,0.0006729642,0.00014526246],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028104067,0.0001802124,0.000629284,0.0059411395,0.000021333477,0.0000013546462,0.084182195,0.0024343957,0.0024868366,0.52869403,0.11638948,0.2587587],"study_design_scores_gemma":[0.00071627693,0.000073194155,0.0035445548,0.002074249,0.000008120994,0.0000010837028,0.00014310714,0.0018601234,0.00003835277,0.00032376542,0.9909561,0.0002610533],"about_ca_topic_score_codex":0.000053793883,"about_ca_topic_score_gemma":0.00012223105,"teacher_disagreement_score":0.8745666,"about_ca_system_score_codex":0.0005307261,"about_ca_system_score_gemma":0.0021090452,"threshold_uncertainty_score":0.9997413},"labels":[],"label_agreement":null},{"id":"W4285230831","doi":"10.1007/978-3-031-06417-3_5","title":"The Impact of Tutorial Design on the Novice Gaming Experience","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Educational Games and Gamification","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Onboarding; Thematic analysis; Video game; Computer science; Context (archaeology); Game design; Multimedia; Point (geometry); Human–computer interaction; Psychology; Applied psychology; Qualitative research; Social psychology","score_opus":0.10504992702731429,"score_gpt":0.3946792465667669,"score_spread":0.2896293195394526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285230831","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003395555,0.0011548415,0.019118147,0.0045633554,0.002474765,0.001696013,0.000054705808,0.000049137092,0.9674935],"genre_scores_gemma":[0.9862968,0.002807974,0.004173715,0.0008663246,0.00020752905,0.0004176328,0.000075772026,0.000019187966,0.0051350887],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987854,0.00009849885,0.00049276766,0.00014114073,0.00034122152,0.00014102216],"domain_scores_gemma":[0.99603754,0.0016304036,0.00042504878,0.0016349969,0.00023852417,0.00003346541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016420388,0.00012330132,0.00011309715,0.00024056961,0.0008378838,0.00015883299,0.0019409481,0.00005235486,0.00017529262],"category_scores_gemma":[0.00009545073,0.00007753643,0.000052383606,0.00028598862,0.0010506704,0.000754306,0.00046021596,0.0003704555,0.000032366916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015295695,0.000020692682,0.000031769283,0.000001707515,0.0000085082975,2.5439705e-8,0.014767635,0.00053381914,0.0000027780145,0.9225562,0.000970771,0.061090767],"study_design_scores_gemma":[0.00043497077,0.0004207497,0.027693061,0.00012484203,0.000013480709,0.000023735298,0.002650929,0.038567528,0.000010228006,0.012838319,0.9167967,0.00042544413],"about_ca_topic_score_codex":0.00007956231,"about_ca_topic_score_gemma":0.0000022601848,"teacher_disagreement_score":0.9829012,"about_ca_system_score_codex":0.00016601577,"about_ca_system_score_gemma":0.00026839293,"threshold_uncertainty_score":0.64444095},"labels":[],"label_agreement":null},{"id":"W4285240509","doi":"10.1007/978-3-031-06394-7_21","title":"Age-Friendly Protocol to Support Investigations of Autonomous Driving Disengagement on Driver Safety","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Bruyère; Carleton University","funders":"","keywords":"Disengagement theory; Driving simulator; Automotive industry; Task (project management); Protocol (science); Computer science; Dropout (neural networks); Simulation; Applied psychology; Engineering; Psychology; Systems engineering; Medicine; Machine learning; Gerontology","score_opus":0.08956360304100947,"score_gpt":0.41028335992753906,"score_spread":0.3207197568865296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285240509","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00042874253,0.000006455948,0.008865398,0.0041483194,0.00060024165,0.056010988,0.00016334311,0.00017599526,0.92960054],"genre_scores_gemma":[0.28425258,0.0014509319,0.333445,0.026460845,0.00053687947,0.27610618,0.0015343227,0.0002676584,0.07594556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973247,0.00016183908,0.0013326224,0.00027388596,0.000598333,0.00030862715],"domain_scores_gemma":[0.9963265,0.0007224182,0.0006637042,0.001752808,0.00039246498,0.00014209368],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001853658,0.00023214515,0.00035434362,0.0010802331,0.0023889886,0.000053919448,0.0015830252,0.00008922637,0.00024165897],"category_scores_gemma":[0.0002652907,0.00022941956,0.000048250193,0.00043804737,0.0008487586,0.0015327896,0.004329027,0.0010048358,0.00011176177],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017493863,0.00011687319,0.009313905,0.00052396324,0.00003924724,0.0000012189929,0.056216884,0.002031407,0.00000685908,0.8339899,0.01132744,0.08641477],"study_design_scores_gemma":[0.0005312578,0.0002754736,0.048133988,0.0007934494,0.00001085173,0.0000010032269,0.0003670246,0.003332213,0.0000023194395,0.0012350818,0.94502884,0.00028850965],"about_ca_topic_score_codex":0.000032593012,"about_ca_topic_score_gemma":0.00016563371,"teacher_disagreement_score":0.9337014,"about_ca_system_score_codex":0.0006022686,"about_ca_system_score_gemma":0.00074099185,"threshold_uncertainty_score":0.9989098},"labels":[],"label_agreement":null},{"id":"W4285279863","doi":"10.1007/978-3-031-08974-9_9","title":"A Novel Variable Selection Approach Based on Multi-criteria Decision Analysis","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Interpretability; Computer science; Feature selection; Variable (mathematics); Selection (genetic algorithm); Reliability (semiconductor); Machine learning; Data mining; Artificial intelligence; Mathematics","score_opus":0.05582469198713108,"score_gpt":0.3408269924939031,"score_spread":0.285002300506772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285279863","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000021109265,0.000039394945,0.9439385,0.00017628299,0.00015272325,0.00038848995,0.000021728969,0.00023355377,0.055047244],"genre_scores_gemma":[0.0049722106,0.00013386333,0.99339515,0.0010826893,0.000011248529,0.000073044714,0.00007892651,0.000010041351,0.00024285527],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99732983,0.000048901373,0.00085399736,0.000569269,0.0009376095,0.00026039322],"domain_scores_gemma":[0.9949896,0.0005825668,0.0004928846,0.0032450794,0.000590343,0.000099547746],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0020868927,0.0002879268,0.00037874517,0.0038688767,0.0009058017,0.0007581683,0.0047331527,0.00013866984,0.00003288424],"category_scores_gemma":[0.00018427745,0.00029439913,0.00009796981,0.0030093824,0.00034001272,0.0058319517,0.0032902472,0.0006480957,0.000011273298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009965617,0.0001296373,0.000015682352,0.00001170278,0.00001770155,2.5793813e-7,0.00042541762,0.068005204,0.000011508009,0.7294828,0.00024117075,0.20164894],"study_design_scores_gemma":[0.0002530887,0.000070707996,0.00026610392,0.00006660891,0.000015981623,0.000010814165,0.0000038695694,0.9161135,0.0000040946866,0.008032862,0.07488098,0.00028138096],"about_ca_topic_score_codex":0.000018689754,"about_ca_topic_score_gemma":0.000004872652,"teacher_disagreement_score":0.8481083,"about_ca_system_score_codex":0.00046582049,"about_ca_system_score_gemma":0.000340839,"threshold_uncertainty_score":0.9999508},"labels":[],"label_agreement":null},{"id":"W4296500117","doi":"10.1007/978-3-031-16210-7_9","title":"Reinforcement of BERT with Dependency-Parsing Based Attention Mask","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université du Québec à Montréal","funders":"","keywords":"Padding; Computer science; Dependency grammar; Parsing; Reinforcement learning; Dependency (UML); Filter (signal processing); Artificial intelligence; Speech recognition; Computer vision; Computer security","score_opus":0.03140664009761266,"score_gpt":0.27540618129268707,"score_spread":0.24399954119507442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296500117","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005412933,0.00011605083,0.8952379,0.0008788289,0.00009296972,0.0005164676,0.0000072523367,0.00006729742,0.10302909],"genre_scores_gemma":[0.24179953,0.0014588053,0.7539968,0.0011991055,0.000024241352,0.0001843798,0.00019008448,0.000020600677,0.001126458],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812675,0.000026738566,0.0006935287,0.00028817204,0.00066000805,0.00020482889],"domain_scores_gemma":[0.99651116,0.0001852686,0.0005957247,0.0023418616,0.00028997034,0.000075988864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006080728,0.000192745,0.00022325653,0.00080352696,0.00054497033,0.00016720618,0.00296398,0.000056745128,0.000020284455],"category_scores_gemma":[0.0000114576305,0.00019065027,0.000040933002,0.0007058393,0.0006148141,0.0050571724,0.00197701,0.0003747282,0.000008898706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048146944,0.000017554064,0.00006232512,0.000026351203,0.0000046812047,2.920703e-7,0.00037395753,0.022501683,0.0000109675175,0.8725582,0.000040614184,0.104398556],"study_design_scores_gemma":[0.00040806684,0.00014719553,0.0007353151,0.00019957218,0.00000949618,0.00002279561,0.000014963704,0.90833294,0.000033313452,0.0065170447,0.08324411,0.00033517054],"about_ca_topic_score_codex":0.000010012234,"about_ca_topic_score_gemma":0.000008165533,"teacher_disagreement_score":0.8858313,"about_ca_system_score_codex":0.0001993642,"about_ca_system_score_gemma":0.0003193997,"threshold_uncertainty_score":0.77744925},"labels":[],"label_agreement":null},{"id":"W4296500923","doi":"10.1007/978-3-031-16210-7_55","title":"Stochastic Expectation Propagation Learning for Unsupervised Feature Selection","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Frequentist inference; Dirichlet distribution; Feature selection; Computer science; Cluster analysis; Artificial intelligence; Machine learning; Feature (linguistics); Unsupervised learning; Bayesian probability; Pattern recognition (psychology); Model selection; Selection (genetic algorithm); Dirichlet process; Algorithm; Data mining; Bayesian inference; Mathematics","score_opus":0.033928913838547604,"score_gpt":0.2976711487856283,"score_spread":0.26374223494708066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296500923","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011098835,0.00017127121,0.974047,0.0009899675,0.0002461816,0.00077644136,0.0000046994314,0.000117828706,0.02363548],"genre_scores_gemma":[0.019577656,0.00048807368,0.976461,0.00050197827,0.0000667109,0.0002804172,0.00017699618,0.000017139955,0.0024300609],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849075,0.00007617678,0.00045833236,0.00034321085,0.0004138034,0.00021770364],"domain_scores_gemma":[0.99799734,0.00027009487,0.00036209915,0.00085167657,0.00044522653,0.00007354231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013559018,0.00020792703,0.00021965502,0.0009605892,0.0010783866,0.00049801293,0.0016691126,0.00012257343,0.000009189538],"category_scores_gemma":[0.00008721814,0.00021898077,0.000056289315,0.0005282693,0.00022255836,0.005964358,0.0009440109,0.00059484417,0.0000051205197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000039987876,0.00000790755,0.000003080011,0.000023397351,0.0000035413086,4.491413e-8,0.0020222839,0.0022690373,0.000012030656,0.6847216,0.00010485778,0.31082824],"study_design_scores_gemma":[0.00031152405,0.0001180119,0.00013433909,0.00006365442,0.0000072037524,0.000017517528,0.000017679318,0.92551994,0.0000105247755,0.019943926,0.053595353,0.00026034296],"about_ca_topic_score_codex":0.000004662403,"about_ca_topic_score_gemma":0.0000038465287,"teacher_disagreement_score":0.9232509,"about_ca_system_score_codex":0.00024656902,"about_ca_system_score_gemma":0.0003276665,"threshold_uncertainty_score":0.89297765},"labels":[],"label_agreement":null},{"id":"W4297283065","doi":"10.1007/978-3-031-17718-7_7","title":"Performance Evaluation of Embedded Time Series Indexes Using Bitmaps, Partitioning, and Trees","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Search engine indexing; Bitmap; Partition (number theory); Index (typography); Hash function; Database index; Data structure; Range query (database); Series (stratigraphy)","score_opus":0.056605889095519786,"score_gpt":0.3088618256095822,"score_spread":0.2522559365140624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297283065","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042472083,0.0057975976,0.66476643,0.0010691403,0.0013427102,0.0035196797,0.000398503,0.00039557778,0.28023827],"genre_scores_gemma":[0.28417057,0.007893792,0.70577794,0.00032470658,0.0000688193,0.0001512868,0.00037168662,0.000027020451,0.0012141888],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982899,0.00006358754,0.0006142256,0.00022287032,0.00066314783,0.00014625942],"domain_scores_gemma":[0.9976304,0.00008590558,0.00049007626,0.001281269,0.0004614296,0.000050893595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018591677,0.00016221381,0.00023791514,0.00065443,0.00062149356,0.0001535402,0.0009358502,0.000054370197,0.000027698672],"category_scores_gemma":[0.00004334568,0.0001655964,0.000023093438,0.00035342536,0.000822023,0.011791427,0.0020601407,0.00020526827,0.0000044541616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004818487,0.00001529138,0.0003508861,0.0000643861,0.000010064198,1.4749088e-7,0.004007555,0.0063170223,0.00004256451,0.79432696,0.000050016184,0.19481029],"study_design_scores_gemma":[0.00025273903,0.00007447196,0.0018159365,0.0002388905,0.0000120782415,0.00003807458,0.000047321864,0.9438639,0.00005050813,0.0015901846,0.051770568,0.0002452954],"about_ca_topic_score_codex":0.000019337356,"about_ca_topic_score_gemma":0.000011126701,"teacher_disagreement_score":0.9375469,"about_ca_system_score_codex":0.0001182955,"about_ca_system_score_gemma":0.00036188526,"threshold_uncertainty_score":0.85485},"labels":[],"label_agreement":null},{"id":"W4298286664","doi":"10.1007/978-3-031-39141-5_4","title":"Evaluation of Search Methods on Community Documents","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's and Gender Studies et Recherches Féministes; York University","funders":"","keywords":"Computer science; Information retrieval; Search engine; Domain (mathematical analysis); Search analytics; World Wide Web; Semantic search; Full text search; Web search query; Mathematics","score_opus":0.25751136249603956,"score_gpt":0.4624863153932656,"score_spread":0.20497495289722606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298286664","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003814948,0.00016311374,0.5327857,0.0008271006,0.00038375836,0.0005261569,0.000041998304,0.00014463466,0.46474603],"genre_scores_gemma":[0.18023948,0.0035818405,0.8111841,0.00092052337,0.00005008225,0.000082299906,0.0003975503,0.00003009799,0.0035140235],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970203,0.00055730407,0.00068387797,0.00020918334,0.0013513126,0.00017802141],"domain_scores_gemma":[0.9941933,0.00075843284,0.00033217898,0.0034834014,0.0011597159,0.00007297543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019102508,0.00016327282,0.00026511014,0.0016592903,0.00053051056,0.00035898417,0.0045713685,0.00009495613,0.000006938851],"category_scores_gemma":[0.0002805234,0.00015942566,0.0000531081,0.00090275955,0.0006563121,0.0038306117,0.003519489,0.00062247063,0.000071508286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.946818e-7,0.000018308328,0.000010214069,0.000014912536,0.000013394847,3.9526604e-8,0.0019921097,0.0010489124,0.000003784458,0.28134716,0.00011160033,0.71543884],"study_design_scores_gemma":[0.00027485227,0.000080928396,0.0012137431,0.0002765207,0.000028300841,0.0000025874733,0.00007147143,0.9695527,0.00005478698,0.021126192,0.007114022,0.00020390292],"about_ca_topic_score_codex":0.000072235576,"about_ca_topic_score_gemma":0.0000138705645,"teacher_disagreement_score":0.9685038,"about_ca_system_score_codex":0.00018329937,"about_ca_system_score_gemma":0.0004810924,"threshold_uncertainty_score":0.8494816},"labels":[],"label_agreement":null},{"id":"W4298306767","doi":"10.1007/978-981-13-1648-7","title":"Computational Intelligence and Intelligent Systems","year":2018,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Internet of Things and AI","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial neural network; Cloud computing; Artificial intelligence; Computational intelligence; Architecture; Transfer of learning; Evolutionary computation; Machine learning; Data science; Geography; Operating system","score_opus":0.040669191005865385,"score_gpt":0.3001382617401092,"score_spread":0.25946907073424386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298306767","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002802493,0.0007115334,0.91655576,0.0006361743,0.0006543657,0.00031299415,0.0000075238627,0.00008049271,0.08101311],"genre_scores_gemma":[0.14363137,0.0074811536,0.82776845,0.0049339267,0.00037273407,0.00011793705,0.00018690986,0.00003581354,0.015471703],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998083,0.000054580876,0.0007490729,0.0003491457,0.00050660747,0.00025759664],"domain_scores_gemma":[0.9972783,0.0002858041,0.00035028908,0.0013656736,0.0005905949,0.00012939345],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014579075,0.0002260277,0.00025468122,0.0009241731,0.0004384168,0.0017153992,0.0037579366,0.00011981281,0.000003795653],"category_scores_gemma":[0.000056183155,0.00021868646,0.00003198209,0.0005078827,0.0013637365,0.006041562,0.0040854537,0.00038881396,0.000088666144],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012250763,0.000016243577,0.000017053037,0.00005294018,0.0000060433777,4.106211e-7,0.0028586176,0.0024344565,1.5345044e-7,0.87178737,0.003102174,0.11972333],"study_design_scores_gemma":[0.00005889643,0.00006486714,0.00013121529,0.00027044996,0.0000024157112,0.000052398074,0.000027741306,0.82878363,0.0000030912202,0.018106919,0.15227376,0.00022462386],"about_ca_topic_score_codex":0.00002111858,"about_ca_topic_score_gemma":0.000002953259,"teacher_disagreement_score":0.85368043,"about_ca_system_score_codex":0.00020616555,"about_ca_system_score_gemma":0.00045634652,"threshold_uncertainty_score":0.9993209},"labels":[],"label_agreement":null},{"id":"W4299620609","doi":"10.1007/978-3-031-45725-8","title":"Computer Vision, Imaging and Computer Graphics Theory and Applications","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"U.S. National Library of Medicine; Russian Academy of Sciences; Université de Poitiers; Universidade Lusófona de Humanidades e Tecnologias; Haute école Spécialisée de Suisse Occidentale; Universidade do Minho; Universidad de Córdoba; Technische Universität Ilmenau; Universidade da Beira Interior; German University in Cairo; Universidad de Zaragoza; Université Claude Bernard Lyon 1; Université de Limoges; Universidad de Cantabria; Centre National de la Recherche Scientifique; Universitat de Barcelona; Instituto Superior Técnico; Technische Universität München; Universidade de São Paulo; Universidade Federal do Rio Grande do Sul; Politecnico di Torino; Universidade do Porto; Universitat Jaume I; Politechnika Warszawska; Universidad de Jaén; Università degli Studi di Genova; Lomonosov Moscow State University; University of Waterloo; Le Mans Université; Pontifícia Universidade Católica do Rio de Janeiro; Liverpool John Moores University; Universitat Politècnica de Catalunya; Universidade de Aveiro; George Washington University; Albert-Ludwigs-Universität Freiburg; Lunds Universitet; King Abdullah University of Science and Technology; Islamic Azad University; Université de Strasbourg; Università degli Studi di Cagliari; Università degli Studi di Milano; Université du Littoral Côte d'Opale; University of Ioannina; Université de Sherbrooke; Sveučilište u Zagrebu; Západočeská Univerzita v Plzni; Peking University; Yale University; University of Aizu; Université de Bourgogne; University of Patras; Athens University of Economics and Business; Universidade de Lisboa; University of Otago; Aalborg Universitet; Technische Universiteit Delft; Instituto de Telecomunicações; Oulun Yliopisto; Universidade de Coimbra","keywords":"Computer graphics; Computer science; Computer graphics (images); Graphics; Visualization; Human–computer interaction; Computer vision; Artificial intelligence","score_opus":0.014546422479047267,"score_gpt":0.2789725952838887,"score_spread":0.26442617280484143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299620609","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013313875,0.0044589923,0.982006,0.00012295066,0.00031201993,0.00046073584,0.000032816875,0.00043230757,0.01204102],"genre_scores_gemma":[0.115487434,0.19315077,0.6704464,0.011376147,0.0018756785,0.0009009339,0.0022173845,0.000396015,0.004149234],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987852,0.00004440844,0.00049074704,0.00023360799,0.00021754121,0.00022846866],"domain_scores_gemma":[0.99820876,0.000549024,0.00010622973,0.0008259756,0.00019533909,0.00011466572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012136097,0.00022923,0.0002276048,0.0009956846,0.0004776286,0.00084327563,0.0007454094,0.000103447666,0.0000013273593],"category_scores_gemma":[0.000010961851,0.0002363567,0.000025023766,0.0007508628,0.0012353878,0.002105137,0.0009414715,0.00046905992,0.000017065013],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019428567,0.000009393275,0.00017669369,0.00026447306,0.00001038194,3.6552674e-7,0.0013485228,0.00038556344,0.0000018432672,0.04739517,0.0019998068,0.94840586],"study_design_scores_gemma":[0.00017804233,0.000016417827,0.0023743466,0.00027185061,0.000011313515,0.00004018349,0.000027622193,0.8501629,0.0000025655463,0.009012933,0.13760473,0.00029705165],"about_ca_topic_score_codex":0.0000044427925,"about_ca_topic_score_gemma":0.0000030849517,"teacher_disagreement_score":0.9481088,"about_ca_system_score_codex":0.000056905516,"about_ca_system_score_gemma":0.000084955966,"threshold_uncertainty_score":0.9638347},"labels":[],"label_agreement":null},{"id":"W4312261918","doi":"10.1007/978-3-031-19682-9_89","title":"Attention and Human AI Collaboration - The Context of Automated Vehicles","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; HEC Montréal","funders":"","keywords":"Automation; Computer science; Context (archaeology); Process (computing); Human–computer interaction; Human-in-the-loop; Systems engineering; Process management; Software engineering; Engineering","score_opus":0.04355965400628471,"score_gpt":0.38404932028593286,"score_spread":0.34048966627964816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312261918","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015155955,0.000680045,0.0032007487,0.009923781,0.0015558021,0.0017401669,0.00019505479,0.0004191804,0.9671293],"genre_scores_gemma":[0.99469674,0.00033883582,0.0005029083,0.0014264185,0.000019746849,0.000060480448,0.00020802938,0.000007941455,0.002738885],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998687,0.00009469936,0.0007003948,0.00014578647,0.0002731414,0.00009896242],"domain_scores_gemma":[0.9980438,0.00018364248,0.00049396884,0.0008620351,0.00038082644,0.000035728863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089338335,0.0001220059,0.00016914733,0.0005648142,0.0007981543,0.00018724373,0.0006551785,0.00007881559,0.00036162356],"category_scores_gemma":[0.000020911299,0.00010836998,0.000029017723,0.000268757,0.0009278338,0.001976317,0.00050043286,0.0003425597,0.00003207564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000062586796,0.000019044917,0.00015167086,0.000013794688,0.000011982393,8.25551e-8,0.008365723,0.000023819355,0.000017732105,0.95799,0.002524195,0.030875701],"study_design_scores_gemma":[0.00085867546,0.00015405356,0.04832832,0.00012988636,0.000023896217,0.000034524757,0.0028385215,0.08103212,0.000007310109,0.002483094,0.863802,0.00030759073],"about_ca_topic_score_codex":0.00006388279,"about_ca_topic_score_gemma":0.000046897487,"teacher_disagreement_score":0.9795408,"about_ca_system_score_codex":0.00009165214,"about_ca_system_score_gemma":0.000087626024,"threshold_uncertainty_score":0.6138838},"labels":[],"label_agreement":null},{"id":"W4312449391","doi":"10.1007/978-3-031-20302-2_17","title":"The Interdisciplinary Role of Archaeoacoustics and Its Applications","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cultural Heritage Management and Preservation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Recreation; Perspective (graphical); Subject (documents); Function (biology); Epistemology; History; Engineering ethics; Aesthetics; Sociology; Computer science; Engineering; Visual arts; Art; Political science; Library science; Philosophy; Law","score_opus":0.08070988486407261,"score_gpt":0.28194934848472175,"score_spread":0.20123946362064915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312449391","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012761961,0.0022966885,0.0006223792,0.0011846379,0.00011611225,0.0005676487,0.000054928427,0.0000236554,0.9950063],"genre_scores_gemma":[0.9094909,0.037606604,0.003966924,0.00072611106,0.00028454207,0.0005056164,0.0006281067,0.000027557619,0.04676365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99934155,0.000012766091,0.0003190106,0.00007787592,0.00017639817,0.00007237601],"domain_scores_gemma":[0.9989805,0.0001755163,0.00018514649,0.00045633162,0.00018200977,0.000020461839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004291005,0.00007707742,0.00008399553,0.00019035304,0.0012656694,0.0002222369,0.00076148816,0.000018188219,0.00006023337],"category_scores_gemma":[0.000008383752,0.000060311246,0.000017061206,0.000053099553,0.00093810016,0.0016418985,0.0027744193,0.0001754989,0.0000048090687],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001550771,0.0000030114406,0.0000026131431,0.000019004337,0.000002856449,8.9830925e-9,0.011734539,0.00001753798,7.051544e-7,0.8799429,0.000102904276,0.1081724],"study_design_scores_gemma":[0.00004848892,0.00002234839,0.00006540479,0.000027337253,0.000006314161,8.462004e-7,0.0014022181,0.039443273,5.479607e-7,0.034042645,0.9248661,0.0000744656],"about_ca_topic_score_codex":0.000008736726,"about_ca_topic_score_gemma":0.00008379226,"teacher_disagreement_score":0.94824266,"about_ca_system_score_codex":0.000027522829,"about_ca_system_score_gemma":0.00002626431,"threshold_uncertainty_score":0.9734633},"labels":[],"label_agreement":null},{"id":"W4312449599","doi":"10.1007/978-3-031-20302-2_16","title":"Reuse, a Challenge for the Preservation of 20th Century Heritage. The Royal Bank of Canada, Santo Domingo, Dominican Republic","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cultural Heritage Management and Preservation","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Prestige; Adaptive reuse; Architecture; Architectural style; Architectural engineering; Adaptation (eye); Cultural heritage; Reuse; Work (physics); Old town; The Republic; Style (visual arts); Civil engineering; Engineering; Economy; History; Archaeology","score_opus":0.1044962287483041,"score_gpt":0.26211177097797994,"score_spread":0.15761554222967583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312449599","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00077447866,0.0028587375,0.00060364755,0.01690522,0.0008926315,0.0026420865,0.00034477963,0.000031838437,0.97494656],"genre_scores_gemma":[0.93755627,0.010913342,0.0037484095,0.0025180571,0.0004011417,0.0006248886,0.00089283223,0.00003607023,0.043308977],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987419,0.000036260877,0.00061811233,0.000109155735,0.00037580103,0.00011872777],"domain_scores_gemma":[0.9971287,0.00057370425,0.00055517803,0.0013490147,0.0003729534,0.00002040442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012618726,0.00011378612,0.00016764643,0.00014748439,0.0009292871,0.00018867862,0.0021618686,0.000028497,0.00020939266],"category_scores_gemma":[0.00010027853,0.000074944415,0.000048581893,0.00008856023,0.0007376381,0.0018223667,0.0013652984,0.00019930337,2.7813516e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015234249,0.000009678107,0.000005723604,0.000071035196,0.000017047967,1.7706137e-8,0.02163551,0.00018937512,1.9374771e-7,0.93976253,0.0091464445,0.029147215],"study_design_scores_gemma":[0.00018075523,0.000045861838,0.00065957033,0.000052229338,0.000014647907,1.8457884e-7,0.0015099922,0.035769425,5.467297e-7,0.0021721036,0.9595045,0.00009019758],"about_ca_topic_score_codex":0.013733109,"about_ca_topic_score_gemma":0.080302365,"teacher_disagreement_score":0.95035803,"about_ca_system_score_codex":0.000076823235,"about_ca_system_score_gemma":0.0002050755,"threshold_uncertainty_score":0.9928345},"labels":[],"label_agreement":null},{"id":"W4312710248","doi":"10.1007/978-3-031-21385-4_19","title":"ML_SPS: Stroke Prediction System Employing Machine Learning Approach","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Random forest; Gradient boosting; Decision tree; Stroke (engine); Machine learning; Computer science; Artificial intelligence; Boosting (machine learning); Ensemble learning; Engineering","score_opus":0.19156478492683154,"score_gpt":0.4246137521139707,"score_spread":0.23304896718713913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312710248","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00056614657,0.0009885826,0.039579708,0.0006148676,0.0014236527,0.0021291473,0.00022949022,0.00045866257,0.9540098],"genre_scores_gemma":[0.8943467,0.013760137,0.06254247,0.0024370186,0.00066407316,0.0015021588,0.0025137903,0.00012401331,0.022109596],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99711686,0.00026804014,0.0013631217,0.0002815587,0.0006098983,0.00036052425],"domain_scores_gemma":[0.99689937,0.0005119401,0.0007073603,0.0012779769,0.00047552088,0.00012781458],"candidate_categories":["sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0029912551,0.00020806816,0.00030330458,0.00097427826,0.0043064235,0.00009439031,0.001420702,0.00021385019,0.00010631698],"category_scores_gemma":[0.000120367586,0.00021615403,0.000044482185,0.00035301613,0.0005122354,0.0028087483,0.0022983782,0.0024171358,0.00012060297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017448303,0.000022451999,0.012768726,0.0007852838,0.0000131537045,4.8116834e-7,0.02336457,0.0061508026,0.0000021935646,0.8486551,0.00026415288,0.10795566],"study_design_scores_gemma":[0.000098075696,0.00005291417,0.0005142221,0.00037825716,0.000007377922,0.0000078149715,0.002065243,0.68413097,4.610949e-7,0.00027476894,0.31229678,0.00017314851],"about_ca_topic_score_codex":0.00047545283,"about_ca_topic_score_gemma":0.000074795134,"teacher_disagreement_score":0.93190014,"about_ca_system_score_codex":0.0010328331,"about_ca_system_score_gemma":0.0005629916,"threshold_uncertainty_score":0.9998843},"labels":[],"label_agreement":null},{"id":"W4312839873","doi":"10.1007/978-981-19-8746-5_11","title":"Hierarchical Topic Model Inference by Community Discovery on Word Co-occurrence Networks","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Alberta","funders":"","keywords":"Topic model; Latent Dirichlet allocation; Computer science; Hierarchy; Inference; Set (abstract data type); Probabilistic logic; Graph; Community structure; Graphical model; Word (group theory); Artificial intelligence; Data science; Information retrieval; Natural language processing; Theoretical computer science; Mathematics","score_opus":0.071469626240898,"score_gpt":0.31919113455464243,"score_spread":0.24772150831374443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312839873","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021656448,0.00014324776,0.89685464,0.00080942205,0.00026774954,0.00031766956,0.00008705597,0.0000999423,0.10120372],"genre_scores_gemma":[0.8214335,0.008204679,0.15517947,0.010148775,0.000087134045,0.00022180658,0.0012508067,0.000030387091,0.0034434737],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976515,0.00014817965,0.00077712844,0.00037382587,0.00070284965,0.00034651454],"domain_scores_gemma":[0.99486315,0.0007239144,0.00034125408,0.0037793107,0.00015160463,0.00014077776],"candidate_categories":["metaepi_narrow","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0015753055,0.00029958115,0.00031536494,0.00065058173,0.0013767817,0.0009703209,0.0070275622,0.00013759591,0.000010641288],"category_scores_gemma":[0.00007469212,0.0003119605,0.000059209273,0.00039757846,0.0008734058,0.0077340975,0.005423885,0.0022051611,0.000012081513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028400723,0.000036931368,0.000036996134,0.000014207975,0.0000034504021,2.2658516e-7,0.001440986,0.04147955,4.8246176e-7,0.7903857,0.00049338693,0.1661052],"study_design_scores_gemma":[0.00017578807,0.000060298844,0.00010899693,0.000097563665,0.0000023811776,0.0000051219786,0.00001187118,0.94438994,0.000001374035,0.0119899325,0.042841278,0.0003154766],"about_ca_topic_score_codex":0.000028254559,"about_ca_topic_score_gemma":0.000008193146,"teacher_disagreement_score":0.90291035,"about_ca_system_score_codex":0.00027570364,"about_ca_system_score_gemma":0.0004080249,"threshold_uncertainty_score":0.99993324},"labels":[],"label_agreement":null},{"id":"W4312992626","doi":"10.1007/978-981-19-8234-7_33","title":"ITCareerBot: A Personalized Career Counselling Chatbot","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in Service Interactions","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Chatbot; Computer science; World Wide Web","score_opus":0.05699028172449259,"score_gpt":0.2937278657567349,"score_spread":0.2367375840322423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312992626","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000033992234,0.0013166198,0.575734,0.004179355,0.0011561838,0.0006056126,0.00004184022,0.00026747864,0.41666493],"genre_scores_gemma":[0.050141715,0.046727758,0.8567283,0.021549867,0.00037882722,0.0006859193,0.00064848206,0.00012035931,0.023018774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99756557,0.00004866042,0.00076753256,0.0004020664,0.00090406,0.0003120895],"domain_scores_gemma":[0.9956235,0.00035138635,0.0004381153,0.0028774545,0.00057713804,0.00013240335],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0011892524,0.0002783543,0.000293676,0.0011928761,0.0010644784,0.0009033913,0.006070275,0.00011125864,0.00017817637],"category_scores_gemma":[0.000024673638,0.00030831355,0.00008235259,0.0006577767,0.00076911994,0.010434583,0.0030364369,0.0008634743,0.00011778661],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000018626155,0.000013284958,0.000011416272,0.000019168589,0.000008405651,9.736983e-7,0.0067040366,0.0006044323,0.0000020758987,0.9403348,0.00037644626,0.051923074],"study_design_scores_gemma":[0.00018417212,0.00003658846,0.00006297236,0.000093699506,0.0000059648396,0.00005757021,0.000071071525,0.31652266,0.0000023366508,0.0073313876,0.67532575,0.00030585454],"about_ca_topic_score_codex":0.000046765486,"about_ca_topic_score_gemma":0.000024415216,"teacher_disagreement_score":0.9330034,"about_ca_system_score_codex":0.00038884697,"about_ca_system_score_gemma":0.000425759,"threshold_uncertainty_score":0.9999369},"labels":[],"label_agreement":null},{"id":"W4313061161","doi":"10.1007/978-3-031-19679-9_63","title":"Reinforcement Learning for Exploring Pedagogical Strategies in Virtual Reality Training","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"TUTOR; Reinforcement learning; Computer science; Virtual reality; Reinforcement; Human–computer interaction; Training (meteorology); Multimedia; Artificial intelligence; Psychology","score_opus":0.3056666438607475,"score_gpt":0.3725653755714306,"score_spread":0.06689873171068311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313061161","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003759839,0.00004971129,0.8763994,0.00048238563,0.0002703469,0.0004935682,0.0000015241333,0.00009883327,0.12216661],"genre_scores_gemma":[0.79577297,0.006289433,0.18947321,0.0011100938,0.00013546427,0.0008656256,0.0003903971,0.00004739622,0.0059153866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974515,0.00006485577,0.0010489289,0.0003630795,0.00067934976,0.0003923113],"domain_scores_gemma":[0.99732447,0.00052362034,0.00046868675,0.0013840065,0.00020602289,0.000093195275],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0026219455,0.00025685603,0.00032814054,0.0011541363,0.0008124138,0.00088211073,0.003214277,0.000093997594,0.000020306568],"category_scores_gemma":[0.00013436057,0.00028374692,0.000063154854,0.00047929186,0.0004678682,0.0112615945,0.0032459476,0.0009493324,0.000008067975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023069092,0.0000028613194,0.0000070886204,0.000012701226,0.0000019865033,2.2908911e-7,0.0077508916,0.4714378,4.6617347e-7,0.48526406,0.000008429138,0.03551115],"study_design_scores_gemma":[0.00033155162,0.00018282392,0.0001453863,0.00010577515,0.0000025346603,0.0000065709746,0.0008118945,0.8412448,9.235936e-7,0.0026076606,0.15428632,0.00027370692],"about_ca_topic_score_codex":0.000020232785,"about_ca_topic_score_gemma":0.000008991491,"teacher_disagreement_score":0.7957354,"about_ca_system_score_codex":0.00039160153,"about_ca_system_score_gemma":0.0005951292,"threshold_uncertainty_score":0.9999615},"labels":[],"label_agreement":null},{"id":"W4313341993","doi":"10.1007/978-3-031-21637-4","title":"Cloud Computing and Services Science","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Science and Technology Facilities Council; Magyar Tudományos Akadémia Számítástechnikai és Automatizálási Kutatóintézet; Universitatea Politehnica din București; Université de Franche-Comté; Harokopio University; Istanbul Teknik Üniversitesi; Politechnika Swietokrzyska w Kielcach; Universitatea din București; Università di Pisa; Universidade Federal de Santa Catarina; Universität Stuttgart; Universidade de Vigo; Universidade Federal do Rio Grande do Sul; National and Kapodistrian University of Athens; Szegedi Tudományegyetem; Università degli Studi di Parma; Ben-Gurion University of the Negev; Scuola Superiore Sant'Anna; Università degli Studi di Padova; Universitetet i Oslo; Universidade Federal de Uberlândia; Edinburgh Napier University; York University; University of Macedonia; Universidad de La Laguna; Universitat de les Illes Balears; Università di Catania; National Technical University of Athens; Lunds Universitet; Universität Ulm; Università Degli Studi di Modena e Reggio Emila; University of the West of England; Universitetet i Stavanger; State University of New York; Université de Sfax; Universidad Carlos III de Madrid; National Institute of Advanced Industrial Science and Technology; Shandong University; České Vysoké Učení Technické v Praze; Università degli Studi di Messina; Newcastle University; Universität Wien; Old Dominion University; University of New England","keywords":"Cloud computing; Computer science; World Wide Web; Data science; Operating system","score_opus":0.059164900789094234,"score_gpt":0.3152643057532709,"score_spread":0.25609940496417666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313341993","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077891825,0.0017092504,0.017811775,0.002516067,0.003093361,0.0011882005,0.00004635225,0.0003316729,0.9655141],"genre_scores_gemma":[0.9146305,0.0076883226,0.037228588,0.031009747,0.0024025033,0.00011035253,0.0013863681,0.00008262759,0.0054610036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99832654,0.00000765878,0.0004915313,0.00030423998,0.00059905264,0.00027094848],"domain_scores_gemma":[0.9979112,0.00009194314,0.00040206866,0.0011309799,0.00044018665,0.000023617426],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001919111,0.00018376726,0.00019458267,0.0015566775,0.0017394873,0.0021006365,0.0031818093,0.00005446581,0.00004761894],"category_scores_gemma":[0.000049682545,0.00018374757,0.000018064538,0.0018439844,0.002227659,0.01619233,0.0085441815,0.00039700852,0.000052010513],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007898988,0.000040535022,0.0015802219,0.0006072485,0.0000047782323,5.861737e-7,0.0015675187,0.00033690652,0.000007108323,0.5844711,0.0031251046,0.408251],"study_design_scores_gemma":[0.00010884285,0.0000069887956,0.0031240734,0.00018020243,0.000007431297,0.00001052088,0.00014233378,0.29075918,0.0000014577295,0.00307052,0.70233554,0.00025289928],"about_ca_topic_score_codex":0.00009996221,"about_ca_topic_score_gemma":0.000024098617,"teacher_disagreement_score":0.96005315,"about_ca_system_score_codex":0.00012844603,"about_ca_system_score_gemma":0.00031691082,"threshold_uncertainty_score":0.9995601},"labels":[],"label_agreement":null},{"id":"W4313342026","doi":"10.1007/978-3-031-20664-1","title":"Biomedical Engineering Systems and Technologies","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Kauno Technologijos Universitetas; Szegedi Tudományegyetem; Lietuvos Sveikatos Mokslų Universitetas; Daegu Gyeongbuk Institute of Science and Technology; National Taiwan University; National Yang-Ming University; Orta Doğu Teknik Üniversitesi; Tsinghua University; Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences; Chung-Ang University; Universidade de Coimbra; North Dakota State University; Hebrew University of Jerusalem; Università degli Studi di Salerno; Università degli Studi di Milano-Bicocca; University of West Attica; University of Zanjan; Chinese Academy of Sciences; Université de Sherbrooke; Politechnika Lódzka; Middlesex University; Indian Council of Agricultural Research; Westfälische Wilhelms-Universität Münster; Durham University; Universidade do Porto; Commonwealth Scientific and Industrial Research Organisation; Università degli Studi di Milano; Johns Hopkins University; University of Washington; Massachusetts General Hospital","keywords":"Computer science","score_opus":0.01496512730883578,"score_gpt":0.23259616073696643,"score_spread":0.21763103342813064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313342026","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056412797,0.088854074,0.6166522,0.0058789733,0.018772172,0.0037419188,0.00039199655,0.010429001,0.24963841],"genre_scores_gemma":[0.67109084,0.15448317,0.16356559,0.0005910045,0.0006612777,0.001588725,0.0022812607,0.00019938202,0.0055387663],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921817,0.000005220373,0.00030698284,0.00009762453,0.00022141855,0.00015058281],"domain_scores_gemma":[0.9992542,0.00009042283,0.000036395864,0.0005287035,0.000035315414,0.000054926375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038604098,0.0001209014,0.00014025516,0.00086244446,0.0001297397,0.0001542829,0.00068375526,0.000110992645,0.0000033732313],"category_scores_gemma":[0.00003319291,0.00012330999,0.000010454922,0.0004914495,0.00041813805,0.0010125679,0.0006499911,0.00044799474,0.0000051035286],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016575781,0.000043071017,0.00006220047,0.0032905433,0.000038536004,0.0000012470944,0.004108931,0.02870082,0.000059992737,0.1308309,0.019378161,0.81348395],"study_design_scores_gemma":[0.000050677085,0.000010362948,0.00014962803,0.0001082007,0.0000020658188,0.0000160857,0.00007501679,0.56952053,8.71633e-7,0.00008396987,0.42986995,0.000112608046],"about_ca_topic_score_codex":0.0000029138887,"about_ca_topic_score_gemma":2.5397586e-7,"teacher_disagreement_score":0.81337136,"about_ca_system_score_codex":0.00019945129,"about_ca_system_score_gemma":0.000091280184,"threshold_uncertainty_score":0.50284356},"labels":[],"label_agreement":null},{"id":"W4313342128","doi":"10.1007/978-3-031-22228-3_6","title":"Underpinning Layered Enterprise Architecture Development with Formal Concept Analysis","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Golder Associates (Canada)","funders":"","keywords":"Metamodeling; Computer science; Underpinning; Identification (biology); Knowledge management; Architecture; Table (database); Lead (geology); Ontology; Process management; Software engineering; Business; Engineering; Epistemology; Data mining","score_opus":0.026350320334990608,"score_gpt":0.24597243778691233,"score_spread":0.21962211745192173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313342128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007606191,0.000388259,0.82190496,0.0015161259,0.00010582319,0.00031727582,0.0000098288765,0.00014428944,0.17485283],"genre_scores_gemma":[0.9557882,0.00032568126,0.038065296,0.0033890042,0.00010817777,0.00006455043,0.00091617217,0.000023966391,0.0013189454],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849176,0.0000054086922,0.0005396199,0.00023792795,0.00050134485,0.00022395827],"domain_scores_gemma":[0.99829745,0.000041622006,0.00047562076,0.0007912242,0.00037459223,0.000019480285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060908624,0.00021886255,0.00030296383,0.0023925835,0.0010383036,0.000722322,0.0012465916,0.000056702913,0.00009449357],"category_scores_gemma":[0.0000130622475,0.0001936935,0.000060132872,0.0014255845,0.00040573228,0.00651392,0.0017150146,0.00038264671,0.000015143867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029704906,0.0000489826,0.0013527412,0.00017880608,0.00028093724,0.0000015159354,0.0036713777,0.23223065,6.8665463e-7,0.21263295,0.000121803576,0.54944986],"study_design_scores_gemma":[0.00033338132,0.000008056344,0.0010130004,0.00013472866,0.00016808616,0.0000036355314,0.00013609807,0.639107,6.020028e-7,0.0011278858,0.3575408,0.0004267439],"about_ca_topic_score_codex":0.000072076306,"about_ca_topic_score_gemma":0.00008338737,"teacher_disagreement_score":0.9550276,"about_ca_system_score_codex":0.00009402896,"about_ca_system_score_gemma":0.000172284,"threshold_uncertainty_score":0.79858965},"labels":[],"label_agreement":null},{"id":"W4313342271","doi":"10.1007/978-3-031-22405-8","title":"Cognition and Recognition","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Mysore; Nitte Meenakshi Institute of Technology; Norges Teknisk-Naturvitenskapelige Universitet; Indian Institute of Technology Kharagpur; Visvesvaraya Technological University; University of Waterloo; Samsung; Kuvempu University; Griffith University; Indian Institute of Technology Delhi; Indian Institute of Information Technology, Allahabad; Amrita Vishwa Vidyapeetham University; Indian Institute of Science","keywords":"Computer science; Cognition; Cognitive science; Artificial intelligence; Information retrieval; Pattern recognition (psychology); Psychology; Neuroscience","score_opus":0.09287591672143339,"score_gpt":0.30363084845412536,"score_spread":0.21075493173269197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313342271","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018680133,0.00023407611,0.0069769546,0.001968519,0.00075543224,0.0011978346,0.00014793692,0.00025497723,0.9865962],"genre_scores_gemma":[0.8630449,0.04013465,0.027694896,0.030744758,0.00038429766,0.0014960658,0.0020835532,0.000110328154,0.03430652],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986173,0.00011674614,0.0004446001,0.00028368726,0.00038124673,0.00015645036],"domain_scores_gemma":[0.998473,0.00034438036,0.000289989,0.0006984022,0.00011847758,0.000075749755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079658534,0.0001411766,0.00013886458,0.0008977662,0.0008453253,0.00036394788,0.00069624314,0.000074209565,0.00006932975],"category_scores_gemma":[0.00022196933,0.0001582759,0.000021590376,0.000667561,0.0010646976,0.0036379949,0.0008609746,0.000500613,0.00006211904],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014260964,0.000049665465,0.000010078564,0.00006788629,0.0000020366613,6.0438464e-7,0.0024154389,0.000014397496,0.0006597889,0.055274818,0.002544625,0.9389464],"study_design_scores_gemma":[0.0010434198,0.00018790246,0.001790511,0.00020608325,0.000022928016,0.00028970567,0.00025940346,0.11040363,0.0013043827,0.039874278,0.84384567,0.0007721023],"about_ca_topic_score_codex":0.0000034606471,"about_ca_topic_score_gemma":0.0000032094993,"teacher_disagreement_score":0.95228976,"about_ca_system_score_codex":0.00019612793,"about_ca_system_score_gemma":0.00025266752,"threshold_uncertainty_score":0.6501644},"labels":[],"label_agreement":null},{"id":"W4313342405","doi":"10.1007/978-3-031-22228-3_2","title":"Towards Endeavor Architecture to Support Knowledge Dynamics of Societal Adaptation","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Global Affairs Canada","funders":"","keywords":"Adaptation (eye); Architecture; Computer science; Knowledge management; Ontology; Knowledge sharing; Dynamics (music); Data science; Epistemology; Sociology; Psychology","score_opus":0.09384505706414825,"score_gpt":0.32283882812615244,"score_spread":0.2289937710620042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313342405","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013919054,0.00012246384,0.16552094,0.0018324136,0.00059160776,0.0005232698,0.000104671526,0.00006069367,0.83110476],"genre_scores_gemma":[0.8693202,0.002461355,0.10503198,0.00824986,0.0007488629,0.0002152964,0.00642137,0.00008871038,0.007462321],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99872315,0.000005672438,0.0005472275,0.00018663185,0.0003813615,0.00015596075],"domain_scores_gemma":[0.99821174,0.000052429787,0.00035212308,0.0009010501,0.00046417283,0.000018486611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007389295,0.00016838517,0.00020718071,0.0010975368,0.0003436036,0.0002772797,0.0017656795,0.00007296553,0.00021217081],"category_scores_gemma":[0.000053169664,0.00017005802,0.000047662248,0.00066632027,0.0004801153,0.0045740413,0.0028988088,0.00031836113,0.00007398656],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000398736,0.000015140325,0.00002104506,0.0000849001,0.0000031361005,7.483931e-8,0.00072869397,0.0006482647,7.445757e-7,0.48837698,0.00045162093,0.5096654],"study_design_scores_gemma":[0.00012505888,0.000028035445,0.0007304255,0.00010976886,0.000015000307,0.0000054474576,0.0001447742,0.22317886,0.000002210871,0.009028281,0.7663565,0.0002755924],"about_ca_topic_score_codex":0.000098798446,"about_ca_topic_score_gemma":0.00015293239,"teacher_disagreement_score":0.86918104,"about_ca_system_score_codex":0.00011985614,"about_ca_system_score_gemma":0.00022580623,"threshold_uncertainty_score":0.69347644},"labels":[],"label_agreement":null},{"id":"W4313342439","doi":"10.1007/978-3-031-22228-3_1","title":"On Understanding and Modelling Complex Systems, Through a Pandemic","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Global Affairs Canada","funders":"","keywords":"Ontology; Domain (mathematical analysis); Computer science; Epistemology; Cognition; Data science; Cognitive science; Psychology; Mathematics; Philosophy","score_opus":0.5360036803196486,"score_gpt":0.4291361438404375,"score_spread":0.1068675364792111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313342439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012050863,0.0011364055,0.6087033,0.00023235058,0.0004364446,0.0004693653,0.000045069824,0.00005280106,0.38880375],"genre_scores_gemma":[0.97186494,0.0022311597,0.02124641,0.0011487147,0.00006258172,0.000041981104,0.00003572469,0.00002340429,0.0033451112],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99570495,0.00012353878,0.0015317556,0.00048526473,0.0018776424,0.00027686206],"domain_scores_gemma":[0.9938082,0.0028390533,0.0007736542,0.0021378654,0.0003341291,0.000107103966],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0052340575,0.00025756125,0.0004933732,0.0015807961,0.0016802788,0.0017731072,0.0023951484,0.00010335507,0.000113358816],"category_scores_gemma":[0.00019717608,0.00022192088,0.00006023827,0.00066504016,0.00083813537,0.0041024117,0.0032417246,0.00057153765,0.00005266863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059950107,0.000005176839,0.000033819855,0.000008775011,0.0000031722102,3.9532733e-7,0.0014937837,0.023628168,2.9547357e-7,0.965882,0.0010013158,0.007937125],"study_design_scores_gemma":[0.00017150976,0.000036335943,0.000057136862,0.000118897806,0.0000026756902,0.000036114547,0.00040506275,0.5679924,1.6244751e-8,0.20326148,0.22774445,0.00017394869],"about_ca_topic_score_codex":0.000055371245,"about_ca_topic_score_gemma":0.000012959531,"teacher_disagreement_score":0.9717444,"about_ca_system_score_codex":0.00041260404,"about_ca_system_score_gemma":0.00018317509,"threshold_uncertainty_score":0.9996194},"labels":[],"label_agreement":null},{"id":"W4313342934","doi":"10.1007/978-3-031-23236-7","title":"Optimization, Learning Algorithms and Applications","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Uniwersytet Opolski; Universidade Tecnológica Federal do Paraná; Slovenská technická univerzita v Bratislave; Kauno Technologijos Universitetas; Instituto Politécnico de Bragança; Technische Universität Wien; Universidade de Trás-os-Montes e Alto Douro; Hanzehogeschool Groningen; Université de Sherbrooke; Universidade do Minho; Politechnika Poznańska; Università degli Studi di Genova; Universidad de León; Politechnika Opolska; Universitatea Tehnică „Gheorghe Asachi” din Iaşi; Universidade do Porto; Université de Lorraine","keywords":"Computer science; Artificial intelligence; Information retrieval; Machine learning; Algorithm","score_opus":0.017893685971174567,"score_gpt":0.2806644264973409,"score_spread":0.26277074052616634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313342934","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.06829e-7,0.0009483757,0.9242507,0.000046413577,0.00004119789,0.00025737562,0.000021736785,0.00032886316,0.07410439],"genre_scores_gemma":[0.00068555045,0.026422959,0.9702011,0.00022300737,0.000043038995,0.00042855297,0.0009823918,0.000025949457,0.000987493],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992159,0.0000151966005,0.00033544184,0.00012932884,0.00018259222,0.00012155402],"domain_scores_gemma":[0.99894583,0.0000943875,0.00009897424,0.0007012728,0.00011346798,0.000046056663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004196061,0.0001228578,0.00012522927,0.0005747763,0.00054211495,0.00023102967,0.00088344316,0.000058060526,0.000011401988],"category_scores_gemma":[0.000021203165,0.00014594935,0.000009010864,0.0005009036,0.00046812848,0.0034087328,0.0010866406,0.00048022892,0.0000035046826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.6905413e-7,0.000006607868,0.000018744993,0.00008970955,0.000003777123,7.150953e-8,0.0008628226,0.3139176,8.8124847e-7,0.022943713,0.0012914743,0.6608641],"study_design_scores_gemma":[0.000039703405,0.0000062813338,0.000016127655,0.000025004992,0.0000015318632,0.000006441103,0.000016541682,0.56227446,0.0000013833043,0.00096559443,0.43654498,0.00010195493],"about_ca_topic_score_codex":0.0000011832827,"about_ca_topic_score_gemma":5.7394163e-7,"teacher_disagreement_score":0.6607622,"about_ca_system_score_codex":0.00018868262,"about_ca_system_score_gemma":0.000120464436,"threshold_uncertainty_score":0.5951642},"labels":[],"label_agreement":null},{"id":"W4313343095","doi":"10.1007/978-3-031-22918-3","title":"Technology and Innovation in Learning, Teaching and Education","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Technology-Enhanced Education Studies","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Ioannina; Universidade de Trás-os-Montes e Alto Douro; University of Thessaly; Universidad de Valladolid; Universitatea din București; Universidade do Porto; Universidade do Minho; University of Western Macedonia; Université du Québec à Montréal; National Taiwan Normal University; Universidade de Aveiro; University of Macedonia; Universidade da Beira Interior; Instituto Politécnico de Viseu; Aristotle University of Thessaloniki","keywords":"Computer science; Mathematics education; Multimedia; Psychology","score_opus":0.03323475195018712,"score_gpt":0.3721407273626643,"score_spread":0.3389059754124772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313343095","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058919992,0.00462101,0.003497877,0.020041408,0.0008493921,0.0015105236,0.0000078826615,0.0006460505,0.90990585],"genre_scores_gemma":[0.77296853,0.034891505,0.098823376,0.0025847072,0.00016748428,0.0009789014,0.00024274117,0.000034172994,0.0893086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986869,0.00013218341,0.0005226411,0.00021561918,0.00025037647,0.00019225253],"domain_scores_gemma":[0.99865437,0.00025144208,0.00034652997,0.0004657121,0.00025115156,0.000030771676],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029015744,0.00011735332,0.00017532209,0.0054417364,0.0019217465,0.00021507873,0.0007523634,0.00015829167,0.000008278081],"category_scores_gemma":[0.000869104,0.00014009212,0.0000067766887,0.002843455,0.0023337372,0.0024915906,0.0013550852,0.0011634965,0.0000031707955],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.891529e-7,0.000012416629,0.0020223458,0.000011631159,0.0000011983201,1.9206922e-8,0.021165626,0.000007758766,0.0000017515655,0.51474833,0.00074409,0.46128425],"study_design_scores_gemma":[0.00012155814,0.000027967944,0.005772782,0.00009563979,0.0000028502116,0.000004893798,0.010126375,0.0010809774,0.0000010366114,0.02651799,0.9560779,0.00017003206],"about_ca_topic_score_codex":0.000107906635,"about_ca_topic_score_gemma":0.00012116436,"teacher_disagreement_score":0.9553338,"about_ca_system_score_codex":0.00059461646,"about_ca_system_score_gemma":0.0014869582,"threshold_uncertainty_score":0.9993776},"labels":[],"label_agreement":null},{"id":"W4313343126","doi":"10.1007/978-3-031-22918-3_35","title":"A Toolkit for Re-Mar to Enhance Classroom Ocean Literacy","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mobile and Web Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Ontology; Literacy; Computer science; Process (computing); Domain (mathematical analysis); World Wide Web; Knowledge management; Psychology; Pedagogy","score_opus":0.027043835565069944,"score_gpt":0.32044878153388023,"score_spread":0.2934049459688103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313343126","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002148938,0.00019701033,0.848258,0.005554573,0.00026270506,0.0012546002,0.000060918625,0.00012038848,0.14427029],"genre_scores_gemma":[0.019104134,0.002192083,0.9613967,0.008991232,0.000106600295,0.00083137176,0.0002555774,0.000026301102,0.007096021],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99797696,0.000026403959,0.0007756298,0.00046261062,0.00045646992,0.0003019015],"domain_scores_gemma":[0.99528646,0.0004079514,0.00032200755,0.0033505945,0.00046880008,0.00016419005],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001144536,0.00023324952,0.00025957494,0.0009904032,0.00093438197,0.00087801606,0.0055257753,0.00008520828,0.000029573936],"category_scores_gemma":[0.00005613854,0.0002544958,0.00007146665,0.0007362327,0.00029213057,0.006593367,0.00411399,0.0003860779,0.00007056014],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019315253,0.00001508693,0.000006777571,0.000016638152,0.0000028608906,8.748943e-8,0.0017082217,0.00019729373,0.0000024328208,0.69759417,0.0027278552,0.29772663],"study_design_scores_gemma":[0.00010592323,0.00008043956,0.00008076643,0.00006020192,0.000003439477,0.000006012374,0.00001120281,0.13620818,0.000012152649,0.018387081,0.84477454,0.00027003195],"about_ca_topic_score_codex":0.000011194666,"about_ca_topic_score_gemma":0.000008531922,"teacher_disagreement_score":0.84204674,"about_ca_system_score_codex":0.00022570726,"about_ca_system_score_gemma":0.00046488957,"threshold_uncertainty_score":0.9999907},"labels":[],"label_agreement":null},{"id":"W4313446831","doi":"10.1007/978-3-031-23098-1","title":"Emerging Information Security and Applications","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Information security; Computer science; Data science; Computer security","score_opus":0.014435904510607816,"score_gpt":0.26378628340567406,"score_spread":0.24935037889506625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313446831","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000048876183,0.000981365,0.7512396,0.0017903657,0.000557737,0.0011109527,0.000031882686,0.00027352353,0.24396573],"genre_scores_gemma":[0.14338607,0.12798855,0.6730309,0.03700388,0.0015129359,0.005572125,0.003555834,0.00012787632,0.007821816],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981238,0.00007658743,0.00073301565,0.00026538048,0.0005481749,0.0002530265],"domain_scores_gemma":[0.99727154,0.00018118812,0.00042590735,0.0017178473,0.00028435147,0.00011915229],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014378155,0.0002045731,0.00021664273,0.0013595766,0.001366417,0.0010245915,0.0026558987,0.00011593819,0.000021010164],"category_scores_gemma":[0.00003391788,0.00023016192,0.00003577577,0.0013429987,0.0005823418,0.017956262,0.004802421,0.0007301226,0.00003439838],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013715659,0.000012525238,0.000010681557,0.000041585277,0.000002996536,7.710232e-8,0.00386684,0.00017310666,2.9674425e-7,0.46004537,0.0013529155,0.53449225],"study_design_scores_gemma":[0.00014764769,0.00003266575,0.00015174253,0.000033062297,0.0000030109218,0.000026057705,0.000051900704,0.25844428,0.0000015190617,0.015559562,0.7253494,0.00019914615],"about_ca_topic_score_codex":0.000020170393,"about_ca_topic_score_gemma":0.000009323678,"teacher_disagreement_score":0.7239965,"about_ca_system_score_codex":0.00028341854,"about_ca_system_score_gemma":0.00043687184,"threshold_uncertainty_score":0.99993366},"labels":[],"label_agreement":null},{"id":"W4318218939","doi":"10.1007/978-3-031-24978-5","title":"Applied Technologies","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"State University of New York Polytechnic Institute; King Faisal University; Innopolis University; Universidad de Ibagué; Universidad Rey Juan Carlos; Universidad Autónoma de Baja California; Universitat Politècnica de València; Blekinge Tekniska Högskola; Universitat Politècnica de Catalunya; Universidade Federal de Pernambuco; Université de Fribourg; Universidad de Chile; University of Baghdad; Universidade Federal de Minas Gerais; Universidad de Córdoba; Universidad del Cauca; Sheffield Hallam University; Chonbuk National University; Universidade Federal do Piauí; Institut Universitaire de France; University of Waterloo; Universiti Malaya; Griffith University; Technische Universiteit Eindhoven; Universidad Politécnica de Madrid; State University of New York; Aalborg Universitet; Escuela Politécnica Nacional; Aalto-Yliopisto; Universiteit Utrecht; Escuela Superior Politécnica del Litoral; Université de Lyon; Universidad de Oviedo; Universidad de Especialidades Espíritu Santo; Escuela Superior Politécnica de Chimborazo; Universidad Tecnológica Nacional; Swinburne University of Technology; Université Grenoble Alpes; Northwestern University; Universidad de Málaga; Universidad de Cuenca; Universidad de Sevilla; Universidad Técnica Federico Santa María; Tsinghua University; University of Technology - Iraq; Korea Institute of Science and Technology; Universitat Rovira i Virgili; Universidad Técnica Particular de Loja; Institut National Polytechnique de Toulouse; Università Politecnica delle Marche; Sveučilište u Zagrebu","keywords":"Computer science","score_opus":0.0959387797402871,"score_gpt":0.31136771595583057,"score_spread":0.2154289362155435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318218939","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000045039986,0.00023630091,0.01953137,0.0020377112,0.0006493379,0.00046307212,0.000013877088,0.0007669061,0.9762564],"genre_scores_gemma":[0.48085788,0.07817413,0.17182681,0.050386664,0.0056279213,0.0024473446,0.014420295,0.0005127631,0.19574618],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99891776,0.0000018549378,0.0004067065,0.00018416432,0.00029761117,0.00019190382],"domain_scores_gemma":[0.9980752,0.000076259435,0.0002592169,0.0013231897,0.00026008402,0.0000060583347],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006511636,0.00015282007,0.00016751811,0.0016087736,0.0003823059,0.0009126908,0.00257774,0.00012417127,0.000010621515],"category_scores_gemma":[0.00008915412,0.0001432939,0.000019364701,0.0015286707,0.0010755248,0.0074715195,0.0038180586,0.0003182764,0.0009333085],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001613572,0.000008853989,0.0000649455,0.00013706916,0.0000021721369,1.388254e-7,0.00008101043,0.000048074493,0.0000014417566,0.5834475,0.014270852,0.40193632],"study_design_scores_gemma":[0.00008284802,0.000002079868,0.00090945244,0.00018587668,0.0000057894513,0.0000016012945,0.000075325355,0.039932147,0.0000027099036,0.02631311,0.9322548,0.00023429],"about_ca_topic_score_codex":0.000013582663,"about_ca_topic_score_gemma":0.000016967751,"teacher_disagreement_score":0.91798395,"about_ca_system_score_codex":0.00006662509,"about_ca_system_score_gemma":0.00013789264,"threshold_uncertainty_score":0.99984455},"labels":[],"label_agreement":null},{"id":"W4318464700","doi":"10.1007/978-3-031-23633-4_11","title":"Intrusion Detection Using Ensemble Models","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Computer science; Intrusion detection system; Ensemble learning; Context (archaeology); Machine learning; Majority rule; Artificial intelligence; Data mining; Outcome (game theory); Particle swarm optimization; Voting; Ensemble forecasting; Scheme (mathematics); Field (mathematics); Mathematics","score_opus":0.06960518694493413,"score_gpt":0.28609266304127223,"score_spread":0.21648747609633812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318464700","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020056118,0.00013166727,0.92432374,0.00023860882,0.0007624856,0.00031105583,0.0000032753924,0.000251086,0.07377754],"genre_scores_gemma":[0.43914607,0.024378844,0.52766967,0.0028151965,0.0004845525,0.00009843465,0.0000915405,0.00008878537,0.005226913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981741,0.000038962873,0.00066358765,0.0003394456,0.00052048627,0.00026345105],"domain_scores_gemma":[0.99724436,0.00014497718,0.00034208168,0.0017908079,0.00037453359,0.00010322608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011945305,0.00022077323,0.00022859487,0.0015005488,0.0008536424,0.0006906426,0.002248836,0.00020293637,0.0000037479012],"category_scores_gemma":[0.000028088878,0.00023540569,0.00005348073,0.00089144,0.00045150967,0.011054981,0.0031800421,0.0005446139,0.0000875732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021212209,0.000005999741,7.7658905e-7,0.00001449659,0.0000027769822,3.418499e-7,0.00083688926,0.0047972985,0.00003515016,0.5113201,0.000031151685,0.4829529],"study_design_scores_gemma":[0.00012746488,0.00003955438,0.000035221154,0.00015061472,0.0000034946295,0.000029140723,0.0000074585378,0.89932114,0.000055762608,0.07936433,0.020633621,0.00023220442],"about_ca_topic_score_codex":0.00003991451,"about_ca_topic_score_gemma":0.000046647016,"teacher_disagreement_score":0.89452386,"about_ca_system_score_codex":0.0002263549,"about_ca_system_score_gemma":0.00019370946,"threshold_uncertainty_score":0.9599565},"labels":[],"label_agreement":null},{"id":"W4318619120","doi":"10.1007/978-981-19-9697-9_13","title":"Mutual Authentication Protocol in a Distributed Heterogeneous Environment: A Blockchain-Based Approach","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Authentication protocol; Computer science; Public key infrastructure; Authentication (law); Lightweight Extensible Authentication Protocol; Protocol (science); Blockchain; Data Authentication Algorithm; Computer security; Public-key cryptography; Single point of failure; Challenge-Handshake Authentication Protocol; Identity (music); Mutual authentication; Key (lock); Computer network; Encryption","score_opus":0.035884070196393406,"score_gpt":0.27420623883519996,"score_spread":0.23832216863880656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318619120","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000066588014,0.00003181817,0.969496,0.0004611675,0.00009253279,0.015807632,0.00014682191,0.0002159991,0.013681433],"genre_scores_gemma":[0.2177144,0.00048214453,0.71963215,0.0018720421,0.000112818394,0.057222992,0.0025120787,0.00007859149,0.00037277184],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99790066,0.000057490175,0.00078295823,0.0004300193,0.00053235074,0.0002965346],"domain_scores_gemma":[0.99673516,0.0001793124,0.0003342941,0.002532476,0.00010791298,0.000110841356],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011788828,0.00025122872,0.00024670854,0.0014052091,0.00033117953,0.00047531273,0.0033234335,0.00015477861,0.0000048826414],"category_scores_gemma":[0.00003309321,0.00026114195,0.000061547085,0.0008377387,0.000802414,0.0013823943,0.0020579752,0.00043953993,0.00006177582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011319696,0.00015032924,0.00011482187,0.00010926584,0.0000072141474,0.0000016517722,0.0026000722,0.009524219,0.0000029654748,0.92320096,0.00007556928,0.0642016],"study_design_scores_gemma":[0.0005209517,0.00004817786,0.00076525786,0.000111365334,0.0000029414773,0.000009155091,0.00000978196,0.9557448,0.0000064261517,0.010709792,0.031780634,0.0002906923],"about_ca_topic_score_codex":0.000012863418,"about_ca_topic_score_gemma":0.000010699172,"teacher_disagreement_score":0.9462206,"about_ca_system_score_codex":0.00015857795,"about_ca_system_score_gemma":0.00022242995,"threshold_uncertainty_score":0.9999841},"labels":[],"label_agreement":null},{"id":"W4318619475","doi":"10.1007/978-981-19-9697-9_27","title":"A Lattice-Based Multisignature Scheme for Blockchain-Enabled Systems","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Blockchain; Computer science; Factoring; Discrete logarithm; Theoretical computer science; Scheme (mathematics); Lattice-based cryptography; Hash function; Database transaction; Lattice (music); Digital signature; Computer security; Public-key cryptography; Mathematics; Quantum","score_opus":0.03371621953797392,"score_gpt":0.2796456697621473,"score_spread":0.24592945022417334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318619475","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007544712,0.0007155173,0.96911067,0.004107895,0.00050314335,0.0019321318,0.0000734791,0.00072532654,0.022756414],"genre_scores_gemma":[0.07180909,0.0010541917,0.91770303,0.0022283574,0.00011682257,0.0013568981,0.00021138399,0.000053886335,0.005466318],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807644,0.000024153776,0.0007314366,0.00044085144,0.0003839269,0.00034319528],"domain_scores_gemma":[0.9951847,0.0005552281,0.00041444605,0.0030315986,0.00070886296,0.00010517063],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015606876,0.0002718645,0.0003357439,0.0014234706,0.00078045763,0.000548495,0.0045477925,0.00038543998,0.0000013986164],"category_scores_gemma":[0.00008562106,0.0002769937,0.000070281814,0.0008493027,0.00079604494,0.0009368274,0.0017295522,0.0006238012,0.000048353668],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016377167,0.000015924332,0.000007212039,0.00006115682,0.000006631579,2.39169e-7,0.00028983576,0.00079133915,0.0000034742586,0.9720006,0.0003908565,0.026431108],"study_design_scores_gemma":[0.0003915296,0.000038652557,0.00006042706,0.00016217421,0.0000051326433,0.000006483766,0.000013344381,0.88328505,0.000009046232,0.018948726,0.09680332,0.0002761102],"about_ca_topic_score_codex":0.000012432937,"about_ca_topic_score_gemma":0.0000107469095,"teacher_disagreement_score":0.95305187,"about_ca_system_score_codex":0.00013722687,"about_ca_system_score_gemma":0.00038260047,"threshold_uncertainty_score":0.99996823},"labels":[],"label_agreement":null},{"id":"W4318812094","doi":"10.1007/978-3-031-24801-6_32","title":"Indoor Positioning and Navigation Using Bluetooth Low Energy and Cloud Service in Healthcare Perspective","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Bluetooth; Computer science; Global Positioning System; Beacon; Mobile device; Cloud computing; Navigation system; Bluetooth Low Energy; Wearable computer; Hybrid positioning system; Wireless; Telecommunications; Real-time computing; Embedded system; Positioning system; World Wide Web; Engineering","score_opus":0.04263587172443938,"score_gpt":0.30120706063259695,"score_spread":0.25857118890815756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318812094","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035034116,0.008459011,0.8335343,0.034853566,0.002733982,0.0035390658,0.00023765235,0.0005648322,0.08104345],"genre_scores_gemma":[0.9687095,0.0016489557,0.026434375,0.0028941988,0.00006532558,0.00006265659,0.00008679326,0.000015705242,0.00008248622],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982676,0.00012417865,0.0006013399,0.00039141733,0.0004063417,0.00020913841],"domain_scores_gemma":[0.9977711,0.0002782287,0.00040881487,0.0009056787,0.0005310669,0.00010509687],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010036172,0.00020995467,0.00027948382,0.0010938231,0.00073270773,0.00070087606,0.0010676626,0.00010917392,0.000003379425],"category_scores_gemma":[0.00002420568,0.00024839424,0.000022112088,0.0007459304,0.00035644782,0.00783126,0.0024469292,0.000442631,0.0000019240063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059832755,0.000021715095,0.0003340732,0.00009047393,0.000007767498,0.0000016308812,0.013304893,0.00019485425,0.000013053625,0.86121774,0.000012805166,0.12479502],"study_design_scores_gemma":[0.00085071806,0.00010809663,0.003090532,0.0010892722,0.0000084556705,0.00036924964,0.0007331469,0.95833695,0.000015151903,0.017612185,0.01711491,0.0006713375],"about_ca_topic_score_codex":0.0013390837,"about_ca_topic_score_gemma":0.00036865557,"teacher_disagreement_score":0.9581421,"about_ca_system_score_codex":0.00052894786,"about_ca_system_score_gemma":0.00037752127,"threshold_uncertainty_score":0.99999684},"labels":[],"label_agreement":null},{"id":"W4320083536","doi":"10.1007/978-3-031-23119-3","title":"Advances in Model and Data Engineering in the Digitalization Era","year":2022,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Minia University; Peking University; Università degli Studi di Salerno; Université de Bordeaux; University of Ioannina; University of Tokyo; Orta Doğu Teknik Üniversitesi; Università di Bologna; Hunan University; Université de Lorraine; University of Macedonia; Université Grenoble Alpes; Université Cadi Ayyad; Universidad de Oviedo; Univerzita Karlova v Praze; Virginia Commonwealth University; Universidad de Almería; Universidade do Minho; Université de Moncton; Università degli Studi di Milano; Høgskulen på Vestlandet; Iowa State University; Indian Institute of Technology, Patna","keywords":"Computer science; Data science; Information retrieval","score_opus":0.03566883747931315,"score_gpt":0.29619326654690725,"score_spread":0.2605244290675941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320083536","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000041809053,0.00065313745,0.99252695,0.0002576513,0.000050411058,0.00030332577,0.000011907453,0.000087071305,0.0060677305],"genre_scores_gemma":[0.039638296,0.011909834,0.947236,0.0006071552,0.000016266778,0.00017622412,0.00031996449,0.00001253112,0.0000837535],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987081,0.00003711807,0.00046035915,0.000269466,0.00035632448,0.0001686166],"domain_scores_gemma":[0.99712133,0.00018479949,0.00012259682,0.0024860913,0.00005647718,0.00002869983],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0015461948,0.00014302084,0.00015443738,0.00095029775,0.00014203011,0.00048260763,0.005773161,0.00005333946,4.2623057e-7],"category_scores_gemma":[0.000029117266,0.00013532839,0.000009448782,0.00097168935,0.00017246882,0.013068266,0.004962931,0.000478028,6.0705094e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.3617987e-7,0.000015638738,0.00011606612,0.00004407027,6.0621375e-7,4.5297946e-7,0.0040716203,0.20101774,2.0482102e-7,0.53775316,0.0002102902,0.2567696],"study_design_scores_gemma":[0.0000942909,0.000012079073,0.0005836622,0.000092934,6.2737473e-7,0.000009135669,0.0000051292614,0.905569,1.8259884e-7,0.0023553057,0.09114494,0.00013270508],"about_ca_topic_score_codex":0.0000068743548,"about_ca_topic_score_gemma":0.000016294487,"teacher_disagreement_score":0.7045513,"about_ca_system_score_codex":0.00017319953,"about_ca_system_score_gemma":0.00024578677,"threshold_uncertainty_score":0.9996061},"labels":[],"label_agreement":null},{"id":"W4320925529","doi":"10.1007/978-981-99-0272-9_27","title":"Differentially Private Clustering Algorithm for Mixed Data","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Computer science; Categorical variable; Cluster analysis; Data mining; Inference; Consistency (knowledge bases); Noise (video); Algorithm; Machine learning; Artificial intelligence","score_opus":0.11497945274300307,"score_gpt":0.3300075392084677,"score_spread":0.21502808646546462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320925529","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000022064453,0.00009383369,0.9829103,0.0045190835,0.00077258056,0.00057888974,0.00025003552,0.0005484877,0.010324586],"genre_scores_gemma":[0.0001970099,0.0022224893,0.99609905,0.00025181432,0.000034505047,0.000051260628,0.0006339843,0.0000151048625,0.0004947811],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978083,0.00001761674,0.00076402177,0.0005775826,0.00047903557,0.00035345048],"domain_scores_gemma":[0.97511125,0.000474638,0.00039075047,0.023681344,0.00026433708,0.00007770979],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0017343716,0.00025888602,0.00029473827,0.0010929249,0.00054606446,0.0011069307,0.0821571,0.00018387807,0.000001634662],"category_scores_gemma":[0.0016132271,0.00026675835,0.00003710719,0.0005339793,0.00080696406,0.0098579405,0.30533755,0.00045341506,0.000046555462],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.148799e-7,0.0000067130036,0.000002246809,0.000029439521,0.0000076088136,2.6504466e-7,0.00008571349,0.000011968836,0.000001160285,0.11471271,0.0070066005,0.87813497],"study_design_scores_gemma":[0.00019576395,0.000024347355,0.00014507906,0.00015837334,0.000004320302,0.0000074187737,0.0000036429808,0.8203964,0.000006551501,0.09418532,0.084627874,0.00024487925],"about_ca_topic_score_codex":0.000008018194,"about_ca_topic_score_gemma":0.000021930633,"teacher_disagreement_score":0.8778901,"about_ca_system_score_codex":0.00011874762,"about_ca_system_score_gemma":0.00021668612,"threshold_uncertainty_score":0.9999785},"labels":[],"label_agreement":null},{"id":"W4323527480","doi":"10.1007/978-3-031-27609-5","title":"Soft Computing and Its Engineering Applications","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Technology Hamirpur; Jaypee University of Information Technology; Université de Tunis El Manar; Charotar University of Science and Technology; Universiti Kebangsaan Malaysia; Concordia University; Université de Tunis; University of Mauritius; National Institute of Technology Karnataka, Surathkal; Amity University","keywords":"Computer science; Soft computing; Artificial intelligence; Artificial neural network","score_opus":0.025483299537605017,"score_gpt":0.26482410232056197,"score_spread":0.23934080278295694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323527480","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000023376413,0.0014953583,0.9103188,0.0008462568,0.0003597436,0.0008014594,0.00001071237,0.00041964,0.08572463],"genre_scores_gemma":[0.46632892,0.015237953,0.47949842,0.0058002127,0.001136614,0.0013314959,0.0004264897,0.00013755955,0.030102339],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843466,0.00002984654,0.00059544225,0.00031104047,0.00035168623,0.0002772937],"domain_scores_gemma":[0.99762917,0.00042451124,0.00024296386,0.0013253271,0.00025852278,0.000119517696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011492361,0.0001979742,0.00025955873,0.0008328948,0.0004849524,0.0007577074,0.002849597,0.00011650664,3.0018842e-7],"category_scores_gemma":[0.000054099655,0.00020247119,0.00003035657,0.00095673674,0.00023907285,0.0037845233,0.0030673915,0.00036989877,0.00008236896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.8214614e-7,0.0000061598485,0.00001948369,0.0000946347,0.000005956663,3.3683332e-7,0.0011915272,0.0010128693,0.0000047270923,0.84090376,0.0004221244,0.15633805],"study_design_scores_gemma":[0.0001729065,0.00001753118,0.0006376962,0.00015650934,0.0000030629408,0.000021701437,0.000013408559,0.9282376,0.0000011321265,0.004859435,0.06563929,0.00023968423],"about_ca_topic_score_codex":0.0000043448226,"about_ca_topic_score_gemma":0.0000021328876,"teacher_disagreement_score":0.92722476,"about_ca_system_score_codex":0.00013426873,"about_ca_system_score_gemma":0.00033109667,"threshold_uncertainty_score":0.82565355},"labels":[],"label_agreement":null},{"id":"W4323780700","doi":"10.1007/978-3-031-27639-2_8","title":"Challenges for XR in Games","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Entertainment; Rendering (computer graphics); Dream; Computer science; Multimedia; Tracking (education); Human–computer interaction; Sociology; Psychology; Artificial intelligence; Art; Visual arts","score_opus":0.14860273150942932,"score_gpt":0.35187696007107255,"score_spread":0.20327422856164323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323780700","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000025431382,0.0010393955,0.5510668,0.011002593,0.00033217092,0.0012756331,0.000037155187,0.00022890014,0.4349919],"genre_scores_gemma":[0.1384273,0.153208,0.6875401,0.005529334,0.00023389544,0.0013661317,0.0003642756,0.0000888917,0.013242029],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854565,0.000017243632,0.0005930391,0.000296627,0.00029443638,0.00025301534],"domain_scores_gemma":[0.99698156,0.0004221358,0.00021813285,0.0020379177,0.00024934765,0.000090916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014703633,0.00017081473,0.00023014651,0.0012382937,0.000237899,0.000421019,0.0030694057,0.000119853015,0.0000010428055],"category_scores_gemma":[0.000101592355,0.0001741866,0.00004022862,0.0004957218,0.000426999,0.004665664,0.0016669271,0.00025873896,0.000059254187],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.503811e-7,0.0000066595658,0.0000023719656,0.000017263417,0.0000011270972,5.0236192e-8,0.0009767805,0.000058990943,4.7630147e-7,0.63625306,0.00010282623,0.36257985],"study_design_scores_gemma":[0.0004295322,0.00009485721,0.0049095773,0.00032267373,0.000002929818,0.00000939608,0.000061602856,0.48102713,0.000006449353,0.14380027,0.3689353,0.00040030628],"about_ca_topic_score_codex":0.0000131406305,"about_ca_topic_score_gemma":0.00007710045,"teacher_disagreement_score":0.49245277,"about_ca_system_score_codex":0.00012328607,"about_ca_system_score_gemma":0.00026239015,"threshold_uncertainty_score":0.71031237},"labels":[],"label_agreement":null},{"id":"W4323780753","doi":"10.1007/978-3-031-27639-2_6","title":"Enhancing Students’ Learning Experience Through Gamification: Perspectives and Challenges","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Educational Games and Gamification","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Point (geometry); Face (sociological concept); Domain (mathematical analysis); Computer science; Engineering ethics; Mathematics education; Knowledge management; Psychology; Engineering; Sociology; Social science","score_opus":0.12871940372516844,"score_gpt":0.3985405418598253,"score_spread":0.26982113813465686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323780753","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068856,0.031285655,0.02103202,0.011533685,0.0016086957,0.0015758196,0.000023174432,0.00045583316,0.9255995],"genre_scores_gemma":[0.641966,0.28563654,0.023143463,0.00081538805,0.00031739008,0.000515203,0.00020417779,0.000065013366,0.047336858],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99845266,0.000051126535,0.00054196216,0.00037173636,0.00038739768,0.00019510358],"domain_scores_gemma":[0.99787086,0.00035205763,0.00032544218,0.0010419718,0.00034398463,0.00006566999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009048178,0.00018772432,0.00019598016,0.0004913018,0.000489647,0.0002838525,0.001064921,0.00012860016,0.00004219426],"category_scores_gemma":[0.00008002859,0.00019935564,0.000027376254,0.0002562722,0.0010872288,0.0021551142,0.0007130434,0.00042054028,0.00015599508],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025551528,0.000022106826,0.00021616655,0.000024751682,0.000008655558,1.2696432e-7,0.15335302,0.000011633349,0.0000026614082,0.7804642,0.000030913005,0.06586325],"study_design_scores_gemma":[0.00066094485,0.0001769232,0.21192917,0.00067832007,0.000028070004,0.000056639044,0.08842215,0.003616011,0.000009012297,0.0161754,0.67730236,0.0009449992],"about_ca_topic_score_codex":0.000021912057,"about_ca_topic_score_gemma":0.000014715562,"teacher_disagreement_score":0.87826264,"about_ca_system_score_codex":0.00010331453,"about_ca_system_score_gemma":0.00008696167,"threshold_uncertainty_score":0.8129487},"labels":[],"label_agreement":null},{"id":"W4352976756","doi":"10.1007/978-3-031-28719-0_24","title":"Value Cores for Inner and Outer Alignment: Simulating Personality Formation via Iterated Policy Selection and Preference Learning with Self-World Modeling Active Inference Agents","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Iterated function; Selection (genetic algorithm); Inference; Preference; Value (mathematics); Artificial intelligence; Computer science; Personality; Machine learning; Psychology; Mathematics; Statistics; Social psychology","score_opus":0.24261878147536317,"score_gpt":0.41469309620417333,"score_spread":0.17207431472881016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4352976756","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28925523,0.000062851366,0.69335324,0.0008478591,0.00022887337,0.0016726177,0.00010206459,0.00023437855,0.014242872],"genre_scores_gemma":[0.97682816,0.0002903705,0.022166887,0.00019971372,0.000027638189,0.000033511096,0.0000650068,0.000011984341,0.0003767174],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977628,0.00007376463,0.00093466224,0.00040813768,0.0005876723,0.00023293494],"domain_scores_gemma":[0.9966346,0.0011715806,0.00065769523,0.0005470189,0.00088170776,0.000107410255],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002165758,0.0002452346,0.0003231417,0.0015471869,0.001000849,0.0013919112,0.0007282541,0.00011654087,0.0000043090936],"category_scores_gemma":[0.00039814928,0.00020447987,0.000032451353,0.0007113084,0.00032856874,0.006294458,0.00090677175,0.00038053727,0.000009797568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054314554,0.000023739165,0.0013625663,0.000046680678,0.000016210106,2.0782694e-7,0.014088472,0.09711016,0.000006673912,0.03330194,0.000024319672,0.8539647],"study_design_scores_gemma":[0.00033946856,0.00008980078,0.0014083992,0.00021819066,0.000013969248,0.000010216715,0.00017817657,0.96611845,0.0000045894926,0.028994836,0.002386372,0.0002375327],"about_ca_topic_score_codex":0.00006730992,"about_ca_topic_score_gemma":0.00011840065,"teacher_disagreement_score":0.8690083,"about_ca_system_score_codex":0.00020391037,"about_ca_system_score_gemma":0.00019265515,"threshold_uncertainty_score":0.99964476},"labels":[],"label_agreement":null},{"id":"W4352976823","doi":"10.1007/978-3-031-28719-0_23","title":"Efficient Search of Active Inference Policy Spaces Using k-Means","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Tree traversal; Embedding; Computer science; Inference; Cluster analysis; Graph traversal; Selection (genetic algorithm); Sample (material); Graph; Space (punctuation); Point (geometry); Space policy; Vector space; Theoretical computer science; Data mining; Machine learning; Artificial intelligence; Mathematics; Algorithm","score_opus":0.06879035466039136,"score_gpt":0.36479731378653923,"score_spread":0.2960069591261479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4352976823","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009577524,0.00008396532,0.89729244,0.0012758841,0.00028939778,0.0003526958,0.000026949356,0.00015063217,0.099570304],"genre_scores_gemma":[0.40161794,0.002061601,0.5917883,0.0005928717,0.00016118969,0.00002167462,0.000056340832,0.000034888086,0.0036651953],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983483,0.00004895386,0.0005261152,0.00024838428,0.0005829592,0.00024526264],"domain_scores_gemma":[0.9971719,0.00037006653,0.00032537323,0.0015808318,0.00045993295,0.00009192984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010772076,0.00017929108,0.00024885658,0.0018463206,0.0003932673,0.00036442527,0.0030142274,0.00009091294,0.0000026625755],"category_scores_gemma":[0.00011909604,0.00017419753,0.000045014192,0.0010982518,0.0009064924,0.00154704,0.0033693332,0.00049603055,0.000032030297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010881954,0.0000117587115,0.000031138872,0.000031758074,0.0000048908273,2.508103e-7,0.0046095,0.051775947,0.0000058213272,0.69262016,0.0000063471152,0.25090134],"study_design_scores_gemma":[0.00012140006,0.000035860852,0.00094745803,0.00022303055,0.0000022648605,0.000006779234,0.000040462895,0.9931331,0.000015275038,0.0027698637,0.0025328647,0.00017161528],"about_ca_topic_score_codex":0.00020596516,"about_ca_topic_score_gemma":0.000006853202,"teacher_disagreement_score":0.9413572,"about_ca_system_score_codex":0.00013137706,"about_ca_system_score_gemma":0.0007418311,"threshold_uncertainty_score":0.7103569},"labels":[],"label_agreement":null},{"id":"W4352976831","doi":"10.1007/978-3-031-28183-9","title":"Advanced Network Technologies and Intelligent Computing","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Kalinga Institute of Industrial Technology; Hong Kong Polytechnic University; Motilal Nehru National Institute of Technology Allahabad; Delhi Technological University; Defence Research and Development Organisation; Netaji Subhas University of Technology","keywords":"Computer science; Analytics; Data science; Big data; Artificial intelligence; Data mining","score_opus":0.06814844675642116,"score_gpt":0.3180885655894477,"score_spread":0.24994011883302653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4352976831","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048621786,0.0025665292,0.28689966,0.013382621,0.0050617913,0.004773804,0.000078855104,0.005726023,0.67664856],"genre_scores_gemma":[0.8480676,0.050484367,0.07203707,0.0059871734,0.00025199607,0.00025678024,0.00014932992,0.00009420547,0.022671489],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855345,0.00005522089,0.0005377906,0.00031164754,0.00029199335,0.00024988066],"domain_scores_gemma":[0.99789137,0.0005986283,0.0003147943,0.0010309963,0.00011293625,0.00005129009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008406838,0.00016838321,0.00018901305,0.00071110314,0.0007424566,0.0003943362,0.001261485,0.000117799194,0.0000014575335],"category_scores_gemma":[0.00037622984,0.00016981746,0.000022882412,0.0011990664,0.0016186014,0.0019514841,0.0018158245,0.000507085,0.00006276447],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028574148,0.000008222139,0.000023432725,0.000034591194,0.0000010930664,2.8306061e-7,0.0007810004,0.00058853725,0.00006130115,0.11628241,0.0011089771,0.8811073],"study_design_scores_gemma":[0.00036595904,0.000090398935,0.0022234896,0.00054338836,0.000006980065,0.00006697268,0.00054403103,0.67377585,0.0006130956,0.025304103,0.29588923,0.000576526],"about_ca_topic_score_codex":0.0000015614725,"about_ca_topic_score_gemma":0.0000061567107,"teacher_disagreement_score":0.8805308,"about_ca_system_score_codex":0.00015598061,"about_ca_system_score_gemma":0.00017856984,"threshold_uncertainty_score":0.6924955},"labels":[],"label_agreement":null},{"id":"W4353004412","doi":"10.1007/978-3-031-28719-0_7","title":"Mapping Husserlian Phenomenology onto Active Inference","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Phenomenology (philosophy); Inference; Consciousness; Epistemology; Philosophy; Cognitive science; Generative grammar; Computer science; Artificial intelligence; Psychology","score_opus":0.12058985638455762,"score_gpt":0.3293113613935764,"score_spread":0.20872150500901882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353004412","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001134626,0.0000308304,0.005473797,0.0010434656,0.00036122443,0.00035846003,0.000039101473,0.00017298028,0.99240667],"genre_scores_gemma":[0.9584871,0.013040554,0.011179111,0.0054547787,0.00013938564,0.00014707977,0.00019717203,0.00004421542,0.011310595],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985287,0.00003770522,0.00051363226,0.00031321772,0.00033232954,0.00027437002],"domain_scores_gemma":[0.9979077,0.00046380857,0.0002904079,0.0010504778,0.0002000237,0.00008758066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044004348,0.0001973001,0.00021422099,0.0011972393,0.0006055563,0.00026839948,0.0015513767,0.000134468,0.000019903442],"category_scores_gemma":[0.00019166419,0.0002056429,0.000033198423,0.0005028108,0.0011999955,0.003853414,0.00143662,0.0005348625,0.00044895013],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027367407,0.0000072020557,0.0000048764823,0.000014861474,0.000001421761,4.356786e-7,0.0024884467,0.000032388405,0.000030776875,0.8382011,0.00003626208,0.15917951],"study_design_scores_gemma":[0.000739267,0.00015691854,0.0011371108,0.00071202713,0.000010999208,0.000044689194,0.0006518481,0.107483,0.0002612512,0.7362183,0.15158194,0.001002669],"about_ca_topic_score_codex":0.000009913399,"about_ca_topic_score_gemma":0.000025834239,"teacher_disagreement_score":0.9810961,"about_ca_system_score_codex":0.0001456365,"about_ca_system_score_gemma":0.0002105593,"threshold_uncertainty_score":0.83858734},"labels":[],"label_agreement":null},{"id":"W4353004456","doi":"10.1007/978-3-031-28719-0_16","title":"A Novel Model for Novelty: Modeling the Emergence of Innovation from Cumulative Culture","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Novelty; Status quo; Inference; Legitimacy; Computer science; Population; Dynamics (music); Data science; Knowledge management; Epistemology; Sociology; Artificial intelligence; Psychology; Political science; Social psychology","score_opus":0.1649427190250501,"score_gpt":0.3802152872773252,"score_spread":0.2152725682522751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353004456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002967033,0.00018384588,0.9259078,0.0011271603,0.00020774482,0.0007444547,0.00017749784,0.00005016129,0.07130464],"genre_scores_gemma":[0.75741565,0.008309207,0.21104133,0.0020136228,0.00034983427,0.00022951144,0.001366293,0.00003212944,0.019242428],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988024,0.0000136662775,0.00055310945,0.00012794485,0.00037302444,0.00012981388],"domain_scores_gemma":[0.99779934,0.00013259538,0.00035238653,0.0004960084,0.0011950635,0.00002461477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011159417,0.00010129612,0.0001340613,0.00024329688,0.000818467,0.000115568226,0.0010247569,0.000114663606,0.000004767188],"category_scores_gemma":[0.00022851536,0.00007634814,0.000032218482,0.00064371055,0.00068143656,0.0023949684,0.0003690452,0.00018897784,0.000004855785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030269161,0.0000057729835,0.0000022446065,0.000007832703,0.0000053353147,4.95809e-9,0.06931418,0.02124485,0.00002980147,0.8925694,0.00021536397,0.016602179],"study_design_scores_gemma":[0.000113364724,0.000007924676,0.000017302431,0.00009364728,0.000007663659,1.3175405e-7,0.0019153231,0.9612936,0.0000022096167,0.03029538,0.0061533065,0.000100174104],"about_ca_topic_score_codex":0.00044358586,"about_ca_topic_score_gemma":0.0005202301,"teacher_disagreement_score":0.9400487,"about_ca_system_score_codex":0.00006450786,"about_ca_system_score_gemma":0.00031520842,"threshold_uncertainty_score":0.62950695},"labels":[],"label_agreement":null},{"id":"W4361012607","doi":"10.1007/978-3-031-28180-8","title":"Advanced Network Technologies and Intelligent Computing","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"AI and Big Data Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Kalinga Institute of Industrial Technology; Hong Kong Polytechnic University; Motilal Nehru National Institute of Technology Allahabad; Delhi Technological University; Defence Research and Development Organisation; Netaji Subhas University of Technology","keywords":"Computer science; World Wide Web","score_opus":0.04709880987916615,"score_gpt":0.3142795240861733,"score_spread":0.2671807142070072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361012607","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004468423,0.0010379334,0.9655244,0.0022340477,0.00032613217,0.0005549975,0.000016220307,0.00072506326,0.029536547],"genre_scores_gemma":[0.018492272,0.02611662,0.94976574,0.0015026861,0.000103243816,0.00014086849,0.00031897146,0.000025365402,0.003534235],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983863,0.000027480128,0.0005961484,0.00036056223,0.00031255762,0.00031695713],"domain_scores_gemma":[0.99672234,0.00039585461,0.00029783556,0.0022942335,0.00022179713,0.00006793753],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0010662434,0.00020050108,0.00023588692,0.00072887563,0.00074297294,0.0007230029,0.00422091,0.00013582998,4.7708824e-7],"category_scores_gemma":[0.00007091057,0.00019587712,0.000024445004,0.0015323797,0.0010588213,0.004420762,0.008299747,0.00045924704,0.00006058225],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.488619e-7,0.0000054840366,0.000029043242,0.000018290604,0.000002463778,1.5745236e-7,0.00052248134,0.00033832237,5.633279e-7,0.31232247,0.0020456768,0.68471473],"study_design_scores_gemma":[0.00014713005,0.000040314997,0.0012417305,0.00029770788,0.000004192597,0.000021047292,0.000107068474,0.68359995,0.000006222241,0.037756216,0.27642012,0.00035831783],"about_ca_topic_score_codex":0.0000044518883,"about_ca_topic_score_gemma":0.000011789045,"teacher_disagreement_score":0.6843564,"about_ca_system_score_codex":0.0001310573,"about_ca_system_score_gemma":0.00032298858,"threshold_uncertainty_score":0.99972093},"labels":[],"label_agreement":null},{"id":"W4361802645","doi":"10.1007/978-3-031-29548-5_8","title":"Improving Student Mental Health Through Health Objectives in a Mobile App","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Mobile apps; Mental health; Computer science; Multimedia; Psychology; World Wide Web; Psychiatry","score_opus":0.07381840998777567,"score_gpt":0.44474820895918454,"score_spread":0.3709297989714089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361802645","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015424223,0.010510056,0.018819803,0.016376274,0.0065304246,0.009438688,0.00082880835,0.0006437268,0.93530977],"genre_scores_gemma":[0.79575336,0.023558125,0.08009064,0.028620467,0.0003038483,0.0037806584,0.0028407034,0.0002396619,0.06481254],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976298,0.000078307945,0.0012495955,0.0002999115,0.00035253714,0.0003898547],"domain_scores_gemma":[0.9979381,0.00012998737,0.00059653656,0.0011291218,0.00008535454,0.00012089158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015305635,0.00019616549,0.00032889083,0.0008960007,0.00048207925,0.00021236241,0.0011988566,0.00007847725,0.000019415082],"category_scores_gemma":[0.000011548093,0.00021273288,0.00005287775,0.0004671001,0.0006183567,0.0026742436,0.0014229973,0.00048565213,0.00023526775],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000065527347,0.00015369013,0.00009626136,0.00011671906,0.0000078486255,3.322343e-7,0.03219866,0.000024989735,6.766394e-8,0.36357436,0.00093542424,0.6028851],"study_design_scores_gemma":[0.0062778466,0.0055056945,0.07028858,0.009467999,0.000012377336,0.00021117463,0.020358784,0.026692105,0.0000041185713,0.047126736,0.81164294,0.0024116435],"about_ca_topic_score_codex":0.0004797044,"about_ca_topic_score_gemma":0.00046735635,"teacher_disagreement_score":0.8704973,"about_ca_system_score_codex":0.0008679702,"about_ca_system_score_gemma":0.0004267329,"threshold_uncertainty_score":0.86749953},"labels":[],"label_agreement":null},{"id":"W4361805659","doi":"10.1007/978-3-031-29548-5_6","title":"A Living-Lab Methodology for the Testing of an Immersive Capsule in Elder Care Home","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Psychology; Living lab; Activities of daily living; Gerontology; Cognition; Assisted Living Facility; Medicine; Computer science; Assisted living; Human–computer interaction; Psychiatry","score_opus":0.25264739872911024,"score_gpt":0.4656592195610759,"score_spread":0.21301182083196568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361805659","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029928027,0.0067300806,0.20924823,0.0022595194,0.00519271,0.011774092,0.0004922338,0.00038100954,0.7339941],"genre_scores_gemma":[0.7395713,0.0070323357,0.24043961,0.005766402,0.00039094134,0.00094269204,0.00033184906,0.00008420302,0.005440721],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9986114,0.0001923346,0.0006689545,0.0001413974,0.00016329184,0.00022260139],"domain_scores_gemma":[0.9942408,0.0037013076,0.00044668483,0.00081574154,0.0007538408,0.000041626045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025098065,0.00011911189,0.00027073416,0.0004913035,0.0009423566,0.000027196713,0.0011523265,0.00017102604,0.0000074896348],"category_scores_gemma":[0.00043496198,0.00010059716,0.000033379485,0.00034410966,0.0006787126,0.0010096473,0.0010038621,0.00051823194,0.000008938581],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059882873,0.000012693616,0.0015435179,0.0003385526,0.000013171169,1.9817985e-7,0.7172968,0.00011999025,0.0000052237697,0.16188319,0.00010705894,0.118673645],"study_design_scores_gemma":[0.0024406987,0.0007586463,0.11240935,0.007390639,0.00015064057,0.000008889907,0.556762,0.1730686,0.000026447151,0.08307184,0.06221979,0.0016924617],"about_ca_topic_score_codex":0.00061835925,"about_ca_topic_score_gemma":0.0007580837,"teacher_disagreement_score":0.72855335,"about_ca_system_score_codex":0.000112014524,"about_ca_system_score_gemma":0.00044436596,"threshold_uncertainty_score":0.72479403},"labels":[],"label_agreement":null},{"id":"W4365790733","doi":"10.1007/978-981-99-1645-0_2","title":"ScriptNet: A Two Stream CNN for Script Identification in Camera-Based Document Images","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Scripting language; Artificial intelligence; Computer vision; Identification (biology); Perspective (graphical); Image (mathematics); Pattern recognition (psychology)","score_opus":0.04299313466075153,"score_gpt":0.3224235304960374,"score_spread":0.27943039583528584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365790733","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000035423116,0.0001721224,0.9643437,0.0021658824,0.00041171155,0.0014945611,0.00006200071,0.0003883324,0.03092623],"genre_scores_gemma":[0.10721684,0.0035535882,0.8758297,0.0040783607,0.00010857457,0.0016921653,0.0008346507,0.00006604403,0.0066200835],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99751705,0.000052970146,0.0011192902,0.0004594594,0.00052067125,0.00033057795],"domain_scores_gemma":[0.9962893,0.00033395176,0.0004922242,0.002130753,0.00065239245,0.00010136677],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002269477,0.0002743839,0.00031099716,0.0024288837,0.00039305762,0.0012171835,0.0034077289,0.0001269022,0.0000051378447],"category_scores_gemma":[0.00010443262,0.00029840367,0.00007326404,0.00083468395,0.000640025,0.00688125,0.0012403623,0.00037538513,0.00008644392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004101661,0.000033733668,0.000038012677,0.000071917486,0.0000052195023,6.251363e-7,0.00089280226,0.0002058555,0.000035123878,0.39163175,0.0013070751,0.6057738],"study_design_scores_gemma":[0.0016139711,0.00018363567,0.0019116087,0.0010733391,0.000014881529,0.000013409547,0.000060746523,0.77985966,0.0014608869,0.13934503,0.07345845,0.0010043954],"about_ca_topic_score_codex":0.00005972996,"about_ca_topic_score_gemma":0.00006632105,"teacher_disagreement_score":0.7796538,"about_ca_system_score_codex":0.00030516903,"about_ca_system_score_gemma":0.000419252,"threshold_uncertainty_score":0.99994683},"labels":[],"label_agreement":null},{"id":"W4365794469","doi":"10.1007/978-981-99-1642-9_3","title":"Binary Orthogonal Non-negative Matrix Factorization","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Factorization; Matrix decomposition; Binary number; Computer science; Matrix (chemical analysis); Cluster analysis; Pattern recognition (psychology); Logical matrix; Space (punctuation); Non-negative matrix factorization; Artificial intelligence; Algorithm; Mathematics; Arithmetic; Physics; Eigenvalues and eigenvectors; Chemistry","score_opus":0.041931324097486435,"score_gpt":0.3055638094217586,"score_spread":0.26363248532427214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365794469","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001924573,0.000088255045,0.8196226,0.0015738033,0.0010560533,0.00069707644,0.00005334901,0.00034934143,0.1763671],"genre_scores_gemma":[0.25310367,0.021097444,0.6825042,0.004110466,0.00038208877,0.00034563165,0.0015109055,0.00010702311,0.036838554],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982731,0.000028112525,0.00061305,0.0003132854,0.00054085196,0.0002316172],"domain_scores_gemma":[0.9973928,0.00027328718,0.00034247013,0.0014275948,0.00045482526,0.000109042245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007108882,0.00022139322,0.00022045239,0.0012955772,0.0005367338,0.0005986989,0.0024125574,0.00016067846,0.000012439972],"category_scores_gemma":[0.000055652905,0.0002173489,0.00004955978,0.00073136453,0.00048069845,0.008452414,0.0024628716,0.00041165604,0.00044607194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005143242,0.000028063241,0.00008019384,0.00006200272,0.000011444278,0.0000017413864,0.003982268,0.0008307371,0.000044080443,0.7596067,0.0020374912,0.23331009],"study_design_scores_gemma":[0.0005065707,0.000108858374,0.0041953167,0.00061599945,0.000007762014,0.000016841319,0.00005857894,0.89441496,0.00007075277,0.050663374,0.04869622,0.0006447558],"about_ca_topic_score_codex":0.000008885248,"about_ca_topic_score_gemma":0.00000572221,"teacher_disagreement_score":0.89358425,"about_ca_system_score_codex":0.00010454604,"about_ca_system_score_gemma":0.00030179773,"threshold_uncertainty_score":0.8863231},"labels":[],"label_agreement":null},{"id":"W4365802316","doi":"10.1007/978-981-99-1639-9_21","title":"Fast Estimation of Multidimensional Regression Functions by the Parzen Kernel-Based Method","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Kernel (algebra); Kernel density estimation; Computer science; Convergence (economics); Kernel regression; Algorithm; Set (abstract data type); Variable kernel density estimation; Parametric statistics; Computational complexity theory; Estimation; Function (biology); Regression; Kernel method; Mathematical optimization; Mathematics; Artificial intelligence; Support vector machine; Statistics","score_opus":0.03961786151655413,"score_gpt":0.30510604741991854,"score_spread":0.2654881859033644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365802316","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012928947,0.00024856813,0.9622439,0.00028416593,0.0002382104,0.00030964543,0.00004997321,0.00028590398,0.036210347],"genre_scores_gemma":[0.31379887,0.0027951337,0.6783249,0.0006782687,0.00006374871,0.00011891104,0.0010035611,0.0000763442,0.0031402768],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907124,0.000024624534,0.00042489107,0.00010399979,0.00027028585,0.000104969906],"domain_scores_gemma":[0.99835014,0.00033291444,0.00016065358,0.0009278921,0.00019543344,0.000032936958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005383087,0.00014147586,0.00015969157,0.00040142555,0.00025385825,0.00006797686,0.00060793606,0.00009234302,0.0000046720647],"category_scores_gemma":[0.000028383392,0.00011111883,0.00003617309,0.0002526666,0.00042982923,0.0007805727,0.00033918826,0.00028067306,0.000018156263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005588801,0.000016129434,0.000013347224,0.00005033274,0.000018308761,1.7037e-7,0.000947091,0.33656737,0.00023230935,0.047185753,0.0131151,0.6018485],"study_design_scores_gemma":[0.00009369886,0.000013757779,0.00016602494,0.00030142002,0.000007769093,0.0000032988112,0.00001584113,0.97897476,0.0004298216,0.001176574,0.01870155,0.000115495386],"about_ca_topic_score_codex":0.00001217833,"about_ca_topic_score_gemma":0.000003440856,"teacher_disagreement_score":0.64240736,"about_ca_system_score_codex":0.000054176522,"about_ca_system_score_gemma":0.00006110746,"threshold_uncertainty_score":0.45312944},"labels":[],"label_agreement":null},{"id":"W4367156149","doi":"10.1007/978-3-031-31353-0_2","title":"PACTDet - An Artificially Intelligent Approach to Detect Pulmonary Illnesses: Pneumonia, Asthma, COVID-19, and Tuberculosis","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Asthma; Pneumonia; Medicine; Pulmonary tuberculosis; Disease; Decision tree; Preprocessor; Intensive care medicine; Artificial intelligence; Coronavirus disease 2019 (COVID-19); Tuberculosis; Machine learning; Random forest; Computer science; Infectious disease (medical specialty); Immunology; Internal medicine; Pathology","score_opus":0.0906070873394395,"score_gpt":0.3561413153680736,"score_spread":0.2655342280286341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367156149","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008248879,0.0021738757,0.6460655,0.1431828,0.0022453752,0.011689905,0.0004544576,0.002022758,0.18391648],"genre_scores_gemma":[0.46724108,0.029444681,0.2913852,0.20194207,0.00056643895,0.0011785406,0.0022709235,0.0002824909,0.005688554],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979003,0.000054028827,0.0007721703,0.00044872405,0.0005477772,0.00027700196],"domain_scores_gemma":[0.9964711,0.00048579412,0.00021747392,0.001951073,0.00034091095,0.0005336552],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017091894,0.00028585925,0.00039601742,0.0017204952,0.000629056,0.00042150822,0.0009877743,0.00017425552,0.000009787124],"category_scores_gemma":[0.00043584348,0.00028566667,0.00005284494,0.0007327634,0.0008845024,0.001821497,0.0015076483,0.00047420277,0.00007412559],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054277032,0.00018628739,0.00032814138,0.00077664043,0.00003921485,0.0000064990118,0.014024729,0.0037682264,0.000084374355,0.054688368,0.0016585336,0.9243847],"study_design_scores_gemma":[0.00038573833,0.00037185516,0.008055337,0.0008071865,0.00006344231,0.0001971806,0.00045554052,0.33634818,0.000044749406,0.004758116,0.64768255,0.00083011563],"about_ca_topic_score_codex":0.00014718164,"about_ca_topic_score_gemma":0.00006484219,"teacher_disagreement_score":0.9235546,"about_ca_system_score_codex":0.000412343,"about_ca_system_score_gemma":0.00080654473,"threshold_uncertainty_score":0.9999595},"labels":[],"label_agreement":null},{"id":"W4378419870","doi":"10.1007/978-3-031-34020-8_20","title":"Binary Black Widow with Hill Climbing Algorithm for Feature Selection","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Hill climbing; Computer science; Algorithm; Feature selection; Metaheuristic; Binary number; Convergence (economics); Set (abstract data type); Ideal (ethics); Extension (predicate logic); Domain (mathematical analysis); Artificial intelligence; Mathematics","score_opus":0.04667246751670973,"score_gpt":0.3125757170518372,"score_spread":0.26590324953512745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378419870","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000001835491,0.00006357111,0.9689488,0.0015841548,0.00023529754,0.0008696741,0.000038510716,0.00020557742,0.028052608],"genre_scores_gemma":[0.00017432334,0.001452995,0.98933226,0.00047390917,0.000060331164,0.00008396732,0.00019060708,0.000022979042,0.008208645],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778277,0.000058329708,0.00059897744,0.00044641484,0.00074707053,0.00036643285],"domain_scores_gemma":[0.9960912,0.0005429978,0.00038157243,0.0016356289,0.0011916653,0.00015692972],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0022103596,0.00026608634,0.0003060357,0.0016598479,0.00071930554,0.001034044,0.0030303556,0.0001770793,0.0000044507156],"category_scores_gemma":[0.000108057095,0.0002471123,0.00005103292,0.0012911925,0.0008549691,0.0053568296,0.0018100714,0.00059835665,0.000066768785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004020851,0.000021458152,0.000010512099,0.00005264228,0.000016651751,8.1163387e-7,0.00090614817,0.004743462,0.0000017888972,0.28211734,0.0017522412,0.7103729],"study_design_scores_gemma":[0.0003701519,0.00014228819,0.00018313227,0.00013943855,0.000006174811,0.00001950851,0.000013739299,0.95590806,0.000006458035,0.0025958738,0.040333,0.00028216545],"about_ca_topic_score_codex":0.0000064590045,"about_ca_topic_score_gemma":0.0000066477764,"teacher_disagreement_score":0.9511646,"about_ca_system_score_codex":0.00019931802,"about_ca_system_score_gemma":0.00054797035,"threshold_uncertainty_score":0.9999981},"labels":[],"label_agreement":null},{"id":"W4378420044","doi":"10.1007/978-3-031-34020-8_5","title":"Solving the Nurse Scheduling Problem Using the Whale Optimization Algorithm","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Scheduling (production processes); Mathematical optimization; Nurse scheduling problem; Job shop scheduling; Workforce; Whale; Operations research; Mathematics; Flow shop scheduling; Economics","score_opus":0.1587079479008343,"score_gpt":0.3851310353442011,"score_spread":0.2264230874433668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378420044","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003556988,0.00042338425,0.9322259,0.0035321047,0.0006564771,0.0005309229,0.000021269938,0.00009846808,0.062475897],"genre_scores_gemma":[0.009013741,0.0014644593,0.9815759,0.0011925015,0.00019919784,0.000050737868,0.000056423043,0.00003090597,0.006416114],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99682176,0.000121718425,0.0011329071,0.0003251693,0.0012835718,0.00031485554],"domain_scores_gemma":[0.9936216,0.0019522022,0.00067684223,0.002555963,0.0011131108,0.00008032087],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009005613,0.00021071793,0.0002463195,0.0010462871,0.002842071,0.0022558118,0.0041429023,0.0001281502,0.000023860446],"category_scores_gemma":[0.0008076154,0.00012973095,0.000087586704,0.0016993334,0.0017729234,0.003967194,0.001200288,0.0006854201,0.00013916001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001427324,0.000010518056,0.00002781076,0.0000046420005,0.000010983813,1.8054197e-7,0.0040392596,0.6212995,0.0000010676338,0.16783065,0.00025170873,0.20652223],"study_design_scores_gemma":[0.00010285181,0.000009622389,0.00007597912,0.00013601272,0.000014750302,0.000017738168,0.00058680866,0.9694901,0.00000127096,0.012049248,0.01735652,0.00015910681],"about_ca_topic_score_codex":0.0000349277,"about_ca_topic_score_gemma":0.00001386294,"teacher_disagreement_score":0.34819055,"about_ca_system_score_codex":0.00011824912,"about_ca_system_score_gemma":0.00049660663,"threshold_uncertainty_score":0.99877995},"labels":[],"label_agreement":null},{"id":"W4378603662","doi":"10.1007/978-3-031-33231-9_2","title":"A Parsing Tool for Short Linguistic Constructions","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Parsing; Linguistics; Computer science; Natural language processing; Artificial intelligence; Philosophy","score_opus":0.04977500912787741,"score_gpt":0.33312790076413007,"score_spread":0.28335289163625266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378603662","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005253578,0.0003568277,0.96952003,0.0005533763,0.00044958817,0.0004920703,0.000020001615,0.00046882528,0.02813402],"genre_scores_gemma":[0.007680704,0.00056876655,0.99029815,0.00040778975,0.000049957263,0.000065788074,0.000045491386,0.000010578849,0.0008727917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863565,0.000012415589,0.0005624659,0.00026937752,0.00029932175,0.00022076943],"domain_scores_gemma":[0.99725413,0.0003731988,0.00018473933,0.0015437523,0.0005855743,0.000058578593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095833064,0.00017662956,0.00020574003,0.0009902748,0.00061326515,0.0008000672,0.0027840156,0.000120810546,0.0000010174808],"category_scores_gemma":[0.00023346978,0.00018052914,0.000047440484,0.0004688892,0.0007251791,0.003460494,0.0017810519,0.00034975688,0.000014599868],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.7263435e-7,0.0000025740662,0.000005718681,0.00002457898,0.0000021641492,1.957123e-7,0.000522611,0.000010849956,0.000002361739,0.7737629,0.0001228621,0.22554263],"study_design_scores_gemma":[0.00017985395,0.000057494774,0.00007845833,0.0005891386,0.000011359246,0.0000614918,0.0000125102415,0.5199607,0.000049136022,0.3921187,0.08636327,0.0005178819],"about_ca_topic_score_codex":0.0000040327905,"about_ca_topic_score_gemma":0.0000042182546,"teacher_disagreement_score":0.51994985,"about_ca_system_score_codex":0.00012746791,"about_ca_system_score_gemma":0.00032393297,"threshold_uncertainty_score":0.7715066},"labels":[],"label_agreement":null},{"id":"W4380048172","doi":"10.1007/978-981-99-3581-9_10","title":"Several Misconceptions and Misuses of Deep Neural Networks and Deep Learning","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Deep learning; Artificial intelligence; Deep neural networks; Computer science; Point (geometry); Artificial neural network; Cognitive science; Psychology; Mathematics","score_opus":0.028580471860879267,"score_gpt":0.2781438316203467,"score_spread":0.24956335975946747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380048172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002387031,0.0005652868,0.9834961,0.00049620355,0.000076889424,0.00028234496,0.000003389834,0.000169899,0.0146711795],"genre_scores_gemma":[0.7831729,0.01729926,0.19726059,0.00059926143,0.000055178305,0.000096185344,0.000048213504,0.0000229352,0.001445474],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988716,0.0000267441,0.00050225895,0.0002422683,0.00019436532,0.00016274108],"domain_scores_gemma":[0.9983493,0.0002192713,0.00029865513,0.0008289781,0.00021659321,0.00008719313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004704569,0.00015890333,0.00020320465,0.00055748643,0.0005638147,0.0003285061,0.0010623954,0.00010924968,0.00000281403],"category_scores_gemma":[0.000024574914,0.00016428086,0.000030454386,0.0004113448,0.001021236,0.00247464,0.0017516447,0.00038433008,0.0000036617778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011097891,0.0000067815677,0.00014466666,0.000022647468,0.0000050203953,1.5021982e-7,0.0012360086,0.003200334,0.000003287592,0.468292,0.000018221794,0.52706975],"study_design_scores_gemma":[0.00010879596,0.000048885624,0.002532154,0.000047788624,0.0000049468317,0.000025274932,0.000041877654,0.98514485,0.0000033357858,0.004115948,0.007756003,0.00017013526],"about_ca_topic_score_codex":0.000016025517,"about_ca_topic_score_gemma":0.000017344295,"teacher_disagreement_score":0.9819445,"about_ca_system_score_codex":0.000031725715,"about_ca_system_score_gemma":0.000033797078,"threshold_uncertainty_score":0.66991794},"labels":[],"label_agreement":null},{"id":"W4380187447","doi":"10.1007/978-3-031-35445-8","title":"Information Management and Big Data","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Instituto Superior Técnico; Leibniz-Gemeinschaft; University of Illinois at Urbana-Champaign; National Institutes of Health; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg; Universidade Estadual de Maringá; Universidad de Oviedo; La Rochelle Université; Universidade de Coimbra; Guangzhou University; Pontificia Universidad Católica del Perú; Universidade Federal do Amazonas; Universidad de la República Uruguay; Universidade Federal de Juiz de Fora; Barcelona Supercomputing Center; Universidad Nacional del Centro de la Provincia de Buenos Aires; Université Lumière Lyon 2; Università di Bologna; Universidad de Chile; Universidade de Lisboa; Universidad Autónoma de Tamaulipas; Universidade de São Paulo; Université de Lille; King Abdulaziz University; Universidad Politécnica de Madrid; University of Toronto; Universitat de València; Universitat Politècnica de València; Université de Montpellier; University of Technology Sydney; Newcastle University; Pontifícia Universidade Católica do Rio de Janeiro; Missouri University of Science and Technology; Universidade Federal do ABC; Universitetet i Oslo; Universidad Peruana Cayetano Heredia; University of Oxford; Vrije Universiteit Amsterdam; Universidad del Pacífico; Liverpool Hope University; Institut \"Jožef Stefan\"; London School of Hygiene and Tropical Medicine; Aix-Marseille Université; Universität Wien; Universitat Rovira i Virgili; Politecnico di Torino; Universidad Michoacana de San Nicolás de Hidalgo; Universidad Nacional de Córdoba; Govind Ballabh Pant University of Agriculture and Technology; Centre de Coopération Internationale en Recherche Agronomique pour le Développement; Norges Teknisk-Naturvitenskapelige Universitet; Université de Strasbourg; Universidade de Brasília; Universidade Federal do Rio de Janeiro; University of Ottawa","keywords":"Big data; Computer science; Information retrieval; Data science; Data mining","score_opus":0.18300822130937378,"score_gpt":0.3297189180083294,"score_spread":0.14671069669895564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380187447","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007602875,0.00037961948,0.08391235,0.002410145,0.002192249,0.0011098646,0.0001956632,0.0003398725,0.9093842],"genre_scores_gemma":[0.1205703,0.19707343,0.21067268,0.11389621,0.011778683,0.0013177239,0.16025908,0.00043677597,0.18399513],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986317,0.000004157271,0.0005728256,0.00018554654,0.00040345534,0.00020228646],"domain_scores_gemma":[0.9970874,0.00006882337,0.00034191486,0.0022014284,0.0002830191,0.000017395285],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0011720109,0.00017813242,0.00017027628,0.001681541,0.00044971268,0.0018029814,0.0030422686,0.000087170505,0.000007886545],"category_scores_gemma":[0.00007298992,0.00017260885,0.000012638926,0.0011927097,0.00066069706,0.028904341,0.009619421,0.0002451522,0.00040751573],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024073356,0.0000073255355,0.00012179022,0.00031059052,0.0000051229745,1.6756597e-7,0.00015455259,0.000019179433,4.1446434e-8,0.11282346,0.030024912,0.8565305],"study_design_scores_gemma":[0.00012922085,0.0000024720239,0.0044895136,0.00023255224,0.000013629404,0.0000029971154,0.00007039365,0.105167806,1.0924913e-7,0.005259391,0.8844322,0.00019972281],"about_ca_topic_score_codex":0.000052342148,"about_ca_topic_score_gemma":0.00003279328,"teacher_disagreement_score":0.85633075,"about_ca_system_score_codex":0.0000552129,"about_ca_system_score_gemma":0.00010129516,"threshold_uncertainty_score":0.99923325},"labels":[],"label_agreement":null},{"id":"W4380519992","doi":"10.1007/978-3-031-35299-7","title":"Computer and Communication Engineering","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Thesaurus; Artificial intelligence","score_opus":0.015310224006136306,"score_gpt":0.24931457594391593,"score_spread":0.23400435193777963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380519992","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006287161,0.012705468,0.66306585,0.0008252291,0.003834096,0.0025483514,0.000097602344,0.0060972776,0.30453897],"genre_scores_gemma":[0.14903586,0.039804507,0.8030443,0.00060446764,0.0003768925,0.00033880383,0.0009840999,0.00027547637,0.0055356035],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894875,0.000015060338,0.00045412398,0.00014285654,0.00021943061,0.00021979968],"domain_scores_gemma":[0.9984429,0.00023944264,0.00006867949,0.0010881309,0.00007760932,0.00008323807],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005422284,0.00021313645,0.0002125625,0.00083355146,0.00019563595,0.00032057182,0.001017974,0.00012240176,0.0000022871448],"category_scores_gemma":[0.000022112054,0.00025266595,0.000021796604,0.0004636525,0.00035016466,0.0023401205,0.0012034843,0.0005724944,0.00004966319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023856928,0.000020321062,0.0001967475,0.0007285746,0.000051430794,0.0000012702817,0.010584074,0.67950517,0.00012737606,0.08257804,0.007159491,0.21904512],"study_design_scores_gemma":[0.00012682403,0.000012726499,0.0013950687,0.00032902777,0.0000033999193,0.000011567745,0.000016242195,0.92187595,0.000010950621,0.00013579341,0.07583836,0.00024410863],"about_ca_topic_score_codex":0.0000036166505,"about_ca_topic_score_gemma":0.0000022926527,"teacher_disagreement_score":0.29900336,"about_ca_system_score_codex":0.00025119918,"about_ca_system_score_gemma":0.000054338638,"threshold_uncertainty_score":0.99999255},"labels":[],"label_agreement":null},{"id":"W4382566926","doi":"10.1007/978-3-031-36336-8_38","title":"Quantifying Re-engagement in Minecraft","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Educational Games and Gamification","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Operationalization; Quarter (Canadian coin); Psychology; Social engagement; Computer science; Applied psychology; Geography; Political science","score_opus":0.22175733955891513,"score_gpt":0.41760200389141355,"score_spread":0.19584466433249842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382566926","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001063716,0.000639024,0.005346797,0.0052207843,0.0014120077,0.00078853156,0.000026979978,0.00010899649,0.98539317],"genre_scores_gemma":[0.80649847,0.013744121,0.057416964,0.0053889533,0.0003335767,0.0006849381,0.0013803382,0.00009422784,0.11445843],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985839,0.000047024914,0.00067872304,0.00022987676,0.00027003346,0.00019042195],"domain_scores_gemma":[0.9978633,0.00034348166,0.00025086364,0.0013116441,0.00017761507,0.000053109336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017700006,0.0001447874,0.00016850515,0.00126265,0.0002092932,0.00016575758,0.0010834147,0.00011390043,0.00008654804],"category_scores_gemma":[0.000055395296,0.00015543807,0.000029147117,0.00046169065,0.00044157633,0.0012773289,0.00057351525,0.0004399019,0.0004934072],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028435802,0.000026622103,0.00074250693,0.000020837215,0.000004859893,3.113297e-7,0.010535832,0.00008191463,0.000001254236,0.87418646,0.0013215345,0.11307504],"study_design_scores_gemma":[0.0005334762,0.00005608368,0.15279944,0.00049136236,0.000009898618,0.000009048299,0.0015537032,0.027340824,0.0000013127155,0.009740262,0.80697006,0.00049454754],"about_ca_topic_score_codex":0.0000570641,"about_ca_topic_score_gemma":0.000114458555,"teacher_disagreement_score":0.8709347,"about_ca_system_score_codex":0.00013433333,"about_ca_system_score_gemma":0.00014150936,"threshold_uncertainty_score":0.6341916},"labels":[],"label_agreement":null},{"id":"W4382566942","doi":"10.1007/978-3-031-36336-8_79","title":"Evaluating Language Learning Apps for Behaviour Change Using the Behaviour Change Scale","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Scale (ratio); Computer science; Behaviour change; Language acquisition; World Wide Web; Human–computer interaction; Multimedia; Mathematics education; Psychology","score_opus":0.49647002150304964,"score_gpt":0.49536705282588456,"score_spread":0.0011029686771650837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382566942","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6203708,0.006104069,0.2464269,0.031593565,0.010443604,0.026388314,0.0014260701,0.0036196965,0.053627007],"genre_scores_gemma":[0.8878872,0.0018229485,0.09281322,0.0027101485,0.00036169315,0.0011875473,0.00034939786,0.00009263431,0.012775233],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969911,0.00010422691,0.0010481973,0.00040800293,0.0011056841,0.00034279478],"domain_scores_gemma":[0.9955452,0.00076124043,0.0007775707,0.0020204068,0.00080684264,0.00008874956],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0072140247,0.00025265125,0.00033046256,0.0015949904,0.0015705153,0.0007641017,0.0034477117,0.0002596476,0.00002526593],"category_scores_gemma":[0.0004488711,0.00019819653,0.000110125715,0.0009192716,0.0010704722,0.0036267433,0.0023496463,0.00080068834,0.000095656214],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010345191,0.00003793737,0.020158397,0.000019108395,0.0000074587424,9.668454e-7,0.029635724,0.00022509578,0.000022875369,0.052833006,0.0002451746,0.8968039],"study_design_scores_gemma":[0.0010944828,0.00026918194,0.117041096,0.0006029684,0.00010578777,0.0000777999,0.0071050366,0.8318471,0.000025073696,0.009272434,0.031517297,0.0010417507],"about_ca_topic_score_codex":0.000076119395,"about_ca_topic_score_gemma":0.00009760281,"teacher_disagreement_score":0.89576215,"about_ca_system_score_codex":0.00013081882,"about_ca_system_score_gemma":0.00014366061,"threshold_uncertainty_score":0.9997293},"labels":[],"label_agreement":null},{"id":"W4382566946","doi":"10.1007/978-3-031-36336-8","title":"Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Education","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of Massachusetts Amherst; University of Illinois at Urbana-Champaign; Leibniz-Gemeinschaft; Universidade Federal de Alagoas; Dipartimento di Matematica e Informatica, Università degli Studi di Catania; Sorbonne Université; Singapore Management University; University of Tsukuba; Technion-Israel Institute of Technology; California State University, Fullerton; Università di Bologna; Universidad de Chile; Universidade Federal do Rio Grande do Sul; Universidad Politécnica de Madrid; University of Sydney; University of Pennsylvania; École Polytechnique Fédérale de Lausanne; Université de Lyon; Gottfried Wilhelm Leibniz Universität Hannover; Beijing Normal University; Università degli Studi di Cagliari; Kindai University; University of South Australia; McGill University; University of Pittsburgh; Athabasca University; North Carolina State University; Carnegie Mellon University; University of Technology Sydney; University of Central Florida; Georgia Institute of Technology; Euskal Herriko Unibertsitatea; Kanazawa University; Georgia State University; University of Colorado Boulder; Universiteit Utrecht; Educational Testing Service","keywords":"Sky; Library science; Computer science; Engineering; Geography; Meteorology","score_opus":0.08978216961997332,"score_gpt":0.36670442789923685,"score_spread":0.27692225827926353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382566946","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46712404,0.006715558,0.42875814,0.049433134,0.012300594,0.0076108025,0.00024601584,0.0009770119,0.026834678],"genre_scores_gemma":[0.8787482,0.012273688,0.103928715,0.0022292282,0.00044083767,0.00021579964,0.00039937865,0.000041930587,0.0017222443],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99727833,0.00013681361,0.0013751192,0.00054948416,0.0003638841,0.00029634777],"domain_scores_gemma":[0.9968829,0.00084838347,0.0006873064,0.00092926255,0.0005233973,0.000128719],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002657457,0.00027276576,0.0002952215,0.0022926151,0.0005754755,0.0016513595,0.00089862134,0.00034446493,0.0000011672826],"category_scores_gemma":[0.0006291074,0.0003027995,0.000012901876,0.0023589185,0.001453975,0.008268078,0.0014147499,0.0009174524,0.0000062529366],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012896582,0.00004722902,0.00055788714,0.000061015307,0.000005416843,5.399501e-7,0.014066599,0.00024196763,0.000016020731,0.24520995,0.00030517884,0.7394753],"study_design_scores_gemma":[0.00044640005,0.0002711201,0.058813516,0.0027512843,0.000043927565,0.00025613687,0.0065740175,0.72413516,0.00021130766,0.15636288,0.04813098,0.0020032693],"about_ca_topic_score_codex":0.0001273906,"about_ca_topic_score_gemma":0.00012041501,"teacher_disagreement_score":0.73747206,"about_ca_system_score_codex":0.0002346146,"about_ca_system_score_gemma":0.001127228,"threshold_uncertainty_score":0.9999424},"labels":[],"label_agreement":null},{"id":"W4382566950","doi":"10.1007/978-3-031-36336-8_94","title":"Impact of Experiencing Misrecognition by Teachable Agents on Learning and Rapport","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Conversation; Computer science; Teachable moment; Artificial intelligence; Psychology; Communication; Psychotherapist","score_opus":0.06663819570248916,"score_gpt":0.324522156627977,"score_spread":0.2578839609254878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382566950","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018034521,0.0007664215,0.26477852,0.00040731835,0.0010660492,0.0016004867,0.00007483455,0.0005175749,0.71275425],"genre_scores_gemma":[0.9643714,0.0041076993,0.025387606,0.00030324495,0.000052863244,0.00006344845,0.00026934897,0.000025624287,0.005418787],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987207,0.00002870217,0.00050668005,0.00022046083,0.00034275086,0.00018067076],"domain_scores_gemma":[0.99844474,0.00016425716,0.00034922242,0.0007501595,0.00019559206,0.00009602396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009426644,0.00015944173,0.00021747591,0.0007661908,0.00030681858,0.00028153407,0.0010538399,0.000091053866,0.0000042379506],"category_scores_gemma":[0.00005693334,0.00015053997,0.00004401078,0.00033007388,0.00035245754,0.0027470181,0.00089731364,0.00027418695,0.000030874486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016076428,0.000071475464,0.0021873266,0.000119289245,0.00003857122,0.000001440082,0.020341216,0.0005626694,0.00011768647,0.112209514,0.004737534,0.8595972],"study_design_scores_gemma":[0.0016066834,0.0012216368,0.014205823,0.001433684,0.0000147999335,0.00007416051,0.0004873596,0.91278374,0.0001878515,0.00832881,0.05839013,0.0012653256],"about_ca_topic_score_codex":0.000046599554,"about_ca_topic_score_gemma":0.0000019982756,"teacher_disagreement_score":0.94633687,"about_ca_system_score_codex":0.000085442036,"about_ca_system_score_gemma":0.0001957905,"threshold_uncertainty_score":0.6138842},"labels":[],"label_agreement":null},{"id":"W4382567046","doi":"10.1007/978-3-031-36336-8_84","title":"Towards Extracting Adaptation Rules from Neural Networks","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; École de Technologie Supérieure","funders":"","keywords":"Adaptation (eye); Computer science; Artificial neural network; Artificial intelligence; Decision tree; Machine learning; Tree (set theory); Adaptive system; Modal; Reading (process); Linguistics; Psychology","score_opus":0.11608820435518728,"score_gpt":0.3293326420590116,"score_spread":0.21324443770382429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382567046","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009443218,0.0002632853,0.9323006,0.000985295,0.00087392627,0.00025939025,0.000012792269,0.00025442653,0.06495584],"genre_scores_gemma":[0.28546137,0.006720491,0.7025621,0.0021827836,0.00038842426,0.00008795998,0.00033441026,0.00004997541,0.0022124825],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979998,0.000040040468,0.0008248209,0.0003440088,0.0005160683,0.00027525148],"domain_scores_gemma":[0.9966071,0.000590101,0.00044376886,0.0018745263,0.00038366925,0.000100803765],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010154874,0.00022815248,0.00023365712,0.00075615896,0.00054609816,0.0011426323,0.0038795252,0.00015666874,0.000008360642],"category_scores_gemma":[0.00012042802,0.0002382601,0.000053063915,0.00046977052,0.00069637265,0.008932373,0.0027732335,0.0005726182,0.00015449822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.707406e-7,0.0000039772076,0.0000130455255,0.000003152882,0.0000028477202,4.8865377e-7,0.0021931666,0.0108388,5.6741396e-7,0.33990365,0.000056578665,0.64698285],"study_design_scores_gemma":[0.00004320934,0.00001927212,0.0006478509,0.000107240274,0.0000033547446,0.0000046527057,0.000068971436,0.95595556,0.0000056119343,0.033031948,0.009876714,0.00023559469],"about_ca_topic_score_codex":0.00014593861,"about_ca_topic_score_gemma":0.00006395756,"teacher_disagreement_score":0.94511676,"about_ca_system_score_codex":0.00012596119,"about_ca_system_score_gemma":0.00019789216,"threshold_uncertainty_score":0.99989426},"labels":[],"label_agreement":null},{"id":"W4382567068","doi":"10.1007/978-3-031-36336-8_47","title":"Enhancing the Automatic Identification of Common Math Misconceptions Using Natural Language Processing","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Interpretability; Identification (biology); Computer science; Domain (mathematical analysis); Mathematics education; Cluster analysis; Blank; Natural (archaeology); Natural language processing; Artificial intelligence; Data science; Psychology; Mathematics","score_opus":0.04389635562848965,"score_gpt":0.31960401044598463,"score_spread":0.275707654817495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382567068","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037688965,0.0013054896,0.98191583,0.00045193822,0.0008504307,0.0006914193,0.000009228357,0.00024363156,0.010763134],"genre_scores_gemma":[0.95459116,0.00024204794,0.040553436,0.00013696418,0.000057905756,0.000020227244,0.000021858012,0.000014683167,0.0043617007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982277,0.000050061983,0.00092831976,0.00019016003,0.00042988537,0.00017387122],"domain_scores_gemma":[0.9973711,0.00023133623,0.0007702013,0.0012694693,0.0003253731,0.000032521035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017100648,0.00015376996,0.00020976076,0.00058495696,0.00068382634,0.00058295863,0.0022664764,0.000064689884,0.0000011295335],"category_scores_gemma":[0.00005729058,0.0001249922,0.00004756318,0.00048971863,0.0004802094,0.0034356832,0.0011741401,0.0003910511,0.000024467034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.8989856e-7,0.000008541756,0.000018171311,0.000117727,0.000006559991,3.2010124e-7,0.016034085,0.0014921671,0.0003703482,0.784114,0.0000063348507,0.19783138],"study_design_scores_gemma":[0.000055834065,0.000010698382,0.00071561744,0.00070540427,0.0000061097803,0.000016059143,0.00036181306,0.9951146,0.00012659165,0.00087974366,0.0018594534,0.00014807333],"about_ca_topic_score_codex":0.000040829324,"about_ca_topic_score_gemma":0.000015707332,"teacher_disagreement_score":0.9936224,"about_ca_system_score_codex":0.00012143073,"about_ca_system_score_gemma":0.00021921929,"threshold_uncertainty_score":0.5621484},"labels":[],"label_agreement":null},{"id":"W4382567310","doi":"10.1007/978-3-031-36336-8_83","title":"How Useful Are Educational Questions Generated by Large Language Models?","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Canadian Institute for International Peace and Security; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Computer science; Quality (philosophy); Domain (mathematical analysis); Mathematics education; Natural language processing; Psychology; Epistemology; Mathematics","score_opus":0.05845123054466652,"score_gpt":0.2962198031426312,"score_spread":0.23776857259796466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382567310","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000084603766,0.00069385156,0.9505878,0.009601752,0.0004612394,0.00032235502,0.00009504582,0.00022850696,0.037924826],"genre_scores_gemma":[0.22292659,0.01018271,0.6703973,0.007217496,0.00043502767,0.00034721638,0.0016675316,0.00009387036,0.08673226],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983382,0.000035642035,0.00048352114,0.00035994482,0.0004985827,0.00028407702],"domain_scores_gemma":[0.996699,0.00016488649,0.00032880827,0.0022411165,0.000442765,0.000123423],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00077689014,0.00021939797,0.00021394459,0.00083264674,0.0005777803,0.0012940497,0.0032255522,0.00013983097,0.000004508299],"category_scores_gemma":[0.00006093826,0.00023133625,0.000041994805,0.0005471669,0.00031828324,0.008399913,0.002176347,0.00043490544,0.00006095345],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.3151423e-7,0.00001656106,0.000022334125,0.000016048441,0.0000047289022,2.7612032e-7,0.0017013331,0.0011011593,0.000005187305,0.9729417,0.002077938,0.022112383],"study_design_scores_gemma":[0.00015987156,0.000009401692,0.00023562016,0.00013354784,0.0000033240608,0.0000094312745,0.000056406363,0.9355635,0.0000043753685,0.02021181,0.04333968,0.00027303756],"about_ca_topic_score_codex":0.000017941307,"about_ca_topic_score_gemma":0.00003179202,"teacher_disagreement_score":0.9527299,"about_ca_system_score_codex":0.00016176031,"about_ca_system_score_gemma":0.00037107646,"threshold_uncertainty_score":0.9997427},"labels":[],"label_agreement":null},{"id":"W4382567344","doi":"10.1007/978-3-031-36336-8_50","title":"GPTutor: A ChatGPT-Powered Programming Tool for Code Explanation","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Personalization; Code (set theory); Source code; Microsoft Visual Studio; Studio; Programming language; Visual programming language; Extension (predicate logic); Multimedia; Software engineering; Program code; Human–computer interaction; World Wide Web; Software","score_opus":0.07773957927845275,"score_gpt":0.31722444014096063,"score_spread":0.23948486086250786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382567344","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000023385497,0.0001138358,0.97207445,0.0012625116,0.00054403086,0.00087032,0.000021846476,0.00023522649,0.024854401],"genre_scores_gemma":[0.009269138,0.0013848472,0.983443,0.0009444993,0.0001037366,0.00032071047,0.00016193962,0.000023852244,0.0043482776],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981516,0.00001810992,0.00073607446,0.00035571528,0.00045348704,0.00028503634],"domain_scores_gemma":[0.99677193,0.0002983671,0.00034646352,0.0020638322,0.00044582537,0.000073553005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015523438,0.00020303689,0.0002287439,0.0009759595,0.0005095782,0.0008747267,0.003144923,0.00013298198,0.00000197289],"category_scores_gemma":[0.00010235168,0.00021523066,0.000056273846,0.00039509012,0.00031141378,0.005936291,0.0018031832,0.00027077983,0.00005515023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.3440616e-7,0.0000046194514,0.0000061962915,0.000024740659,0.0000028514619,1.09494096e-7,0.0013118525,0.00017936739,9.1618267e-7,0.6395426,0.0001082303,0.35881758],"study_design_scores_gemma":[0.00025187185,0.000035396137,0.00010767999,0.00015228677,0.0000034658951,0.000007261343,0.000016905338,0.7461804,0.00000386816,0.014230038,0.23876163,0.00024919512],"about_ca_topic_score_codex":0.00000579516,"about_ca_topic_score_gemma":0.000013687581,"teacher_disagreement_score":0.746001,"about_ca_system_score_codex":0.00015954966,"about_ca_system_score_gemma":0.00029180816,"threshold_uncertainty_score":0.8776852},"labels":[],"label_agreement":null},{"id":"W4382567577","doi":"10.1007/978-3-031-36336-8_33","title":"Decomposed Prompting to Answer Questions on a Course Discussion Board","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Vector Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Course (navigation); Computer science; Information retrieval; Mathematics education; Psychology; Engineering; Aerospace engineering","score_opus":0.043309764366456185,"score_gpt":0.3330772662312522,"score_spread":0.28976750186479605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382567577","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019339383,0.00013255012,0.8762834,0.016031774,0.0016203529,0.0013021813,0.000011931814,0.0012833009,0.10314111],"genre_scores_gemma":[0.054992042,0.00037569605,0.92676544,0.0037496234,0.00013496462,0.00015428558,0.000075038966,0.000043289292,0.013709598],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99818695,0.000062004154,0.0005565656,0.00037779176,0.000519756,0.0002969553],"domain_scores_gemma":[0.99705344,0.00021629359,0.00024759458,0.0020513805,0.00024118953,0.00019007118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001511689,0.00023352995,0.00022635779,0.001174,0.00088673324,0.0010288521,0.0030351928,0.00011116997,0.0000019307722],"category_scores_gemma":[0.00011142157,0.00018893376,0.00005073537,0.0006466544,0.0003087908,0.002835959,0.0022813904,0.0007332341,0.00026491156],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013051948,0.00002137597,0.000027399103,0.000010706179,0.0000024627595,3.5531974e-7,0.002357349,0.0009527093,8.9699193e-7,0.28865764,0.00030673825,0.70766103],"study_design_scores_gemma":[0.00022791862,0.00018865195,0.0033332594,0.001385509,0.000006759936,0.0000140154325,0.00006322284,0.21543773,0.000001911902,0.0032106156,0.7756076,0.0005228431],"about_ca_topic_score_codex":0.000022168244,"about_ca_topic_score_gemma":0.000015065926,"teacher_disagreement_score":0.7753008,"about_ca_system_score_codex":0.00013619603,"about_ca_system_score_gemma":0.00038241255,"threshold_uncertainty_score":0.9921245},"labels":[],"label_agreement":null},{"id":"W4383099037","doi":"10.1007/978-3-031-37189-9","title":"Computer-Aided Architectural Design. INTERCONNECTIONS: Co-computing Beyond Boundaries","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Università degli Studi di Brescia; Syddansk Universitet; Technion-Israel Institute of Technology; Universidade Federal de Juiz de Fora; Universidade do Porto; Tallinna Tehnikaülikool; Nottingham Trent University; İzmir Yüksek Teknoloji Enstitüsü; University of Southern California; Trent University; University of East London; University of Thessaly; Université de Liège; Technische Universiteit Delft; Aarhus Universitet; Universidade do Minho; Eidgenössische Technische Hochschule Zürich; RMIT University; Massachusetts Institute of Technology; Technische Universität München; KU Leuven","keywords":"Futures contract; Computer science; Architectural design; Architectural engineering; Architecture; Systems engineering; Data science; Human–computer interaction; Engineering; Visual arts; Business; Art","score_opus":0.03448093971174093,"score_gpt":0.28600956452595006,"score_spread":0.2515286248142091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383099037","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002698348,0.00019583276,0.97677654,0.0002473563,0.0008376332,0.0006408899,0.00004170175,0.0007742171,0.020215973],"genre_scores_gemma":[0.07360742,0.0016764745,0.9201891,0.00090379565,0.00047767337,0.00029884576,0.0010371619,0.00011535158,0.0016942237],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980569,0.000049884,0.00090506143,0.0002687026,0.0003604889,0.00035899592],"domain_scores_gemma":[0.9973435,0.0006237575,0.0001831257,0.0014558131,0.00028454332,0.00010929351],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001006024,0.0003080655,0.0003254085,0.001303724,0.0010399931,0.0011741272,0.0018500303,0.00015857942,0.0000045794227],"category_scores_gemma":[0.000053837826,0.00034293474,0.000057139412,0.0008777819,0.0014257734,0.0021114268,0.0009968872,0.00074053754,0.00017521981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030845774,0.000019096005,0.000020047119,0.0001674165,0.000034083994,4.4147222e-7,0.008635235,0.54470545,0.000010869327,0.031530194,0.009717734,0.40515634],"study_design_scores_gemma":[0.00017021174,0.000031919848,0.00031802812,0.00022508658,0.000008614627,0.000024943085,0.000029988689,0.9566378,0.000013651434,0.0071771853,0.03502519,0.00033740947],"about_ca_topic_score_codex":0.0000235941,"about_ca_topic_score_gemma":0.000036027228,"teacher_disagreement_score":0.41193232,"about_ca_system_score_codex":0.00040850812,"about_ca_system_score_gemma":0.00046819143,"threshold_uncertainty_score":0.99990225},"labels":[],"label_agreement":null},{"id":"W4383099097","doi":"10.1007/978-3-031-37189-9_13","title":"Wieringa Surface: The Implementation of Aperiodicity into Architectural Acoustics","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Quasicrystal Structures and Properties","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Aperiodic graph; Surface (topology); Parametrization (atmospheric modeling); Parametric surface; Parametric statistics; Computer science; Penrose tiling; Acoustics; Mathematics; Geometry; Optics; Physics; Quasicrystal; Combinatorics","score_opus":0.03245847369609491,"score_gpt":0.30269971880183316,"score_spread":0.27024124510573827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383099097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8642707,0.001982504,0.05634668,0.00509776,0.002970406,0.00331717,0.0005186405,0.00041416625,0.065082006],"genre_scores_gemma":[0.9861839,0.0009929086,0.012227086,0.00023873763,0.00002650064,0.000008528437,0.00003681311,0.000007846846,0.00027771477],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989028,0.000026912172,0.0004932032,0.000114812414,0.00032918874,0.00013306149],"domain_scores_gemma":[0.9986045,0.0001408909,0.00027375555,0.00075307314,0.00019473929,0.000033086704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008094097,0.0001208485,0.0001535384,0.00015726942,0.00048633394,0.00023410324,0.0012018054,0.000050388524,0.00003569503],"category_scores_gemma":[0.000022242255,0.00008422066,0.000026887608,0.00016690299,0.0014577699,0.0010225794,0.0011763748,0.00019619716,0.000019274694],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030307718,0.000013892283,0.00040137226,0.00051340746,0.000019563848,4.2575476e-7,0.063900664,0.010285654,0.025490038,0.34340373,0.00037220417,0.55556875],"study_design_scores_gemma":[0.0032525128,0.0013809712,0.09657513,0.002556451,0.0001875883,0.00019952367,0.009711422,0.41500977,0.024176411,0.2079271,0.23504005,0.0039830976],"about_ca_topic_score_codex":0.00020099859,"about_ca_topic_score_gemma":0.00007567169,"teacher_disagreement_score":0.5515857,"about_ca_system_score_codex":0.000052064286,"about_ca_system_score_gemma":0.00014295342,"threshold_uncertainty_score":0.53712136},"labels":[],"label_agreement":null},{"id":"W4383616612","doi":"10.1007/978-3-031-36004-6_28","title":"An Interactive Digital Twin of a Composite Manufacturing Process for Training Operators via Immersive Technology","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Usability; Headset; Computer science; Human–computer interaction; Process (computing); Virtual reality; Personalization; User interface; System usability scale; Multimedia; World Wide Web; Heuristic evaluation; Operating system","score_opus":0.0425656324963016,"score_gpt":0.32777341564616774,"score_spread":0.28520778314986617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383616612","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00057970686,0.000023445527,0.9866787,0.0007495018,0.000106989944,0.00076333684,0.000074456606,0.00012547094,0.010898387],"genre_scores_gemma":[0.9426342,0.00013351935,0.056369063,0.00024276106,0.00002046958,0.00020735741,0.0002115585,0.000018859695,0.00016220115],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984831,0.000012519496,0.000680472,0.00032217056,0.00028112408,0.00022060356],"domain_scores_gemma":[0.99710935,0.00023965338,0.0004875866,0.0015715522,0.00050963095,0.000082199265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046947444,0.0001970968,0.00028288545,0.0015118727,0.00039674604,0.00035987227,0.003625117,0.0001322719,8.5549755e-7],"category_scores_gemma":[0.000027516227,0.00020710201,0.000045571003,0.00058032066,0.00089255034,0.0075011654,0.0013047362,0.0003361117,0.000011341632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007836134,0.00005623288,0.000027391545,0.00008929256,0.000033371165,3.0885806e-7,0.01763609,0.0040210662,0.00009400209,0.4949734,0.000017716562,0.4830433],"study_design_scores_gemma":[0.00045282548,0.00016990739,0.00024125795,0.00036695026,0.000011563064,0.000030435302,0.0008636587,0.94483477,0.0015705179,0.046031024,0.0049883365,0.00043877226],"about_ca_topic_score_codex":0.000004693001,"about_ca_topic_score_gemma":0.0000044382305,"teacher_disagreement_score":0.9420545,"about_ca_system_score_codex":0.00011836753,"about_ca_system_score_gemma":0.0002518367,"threshold_uncertainty_score":0.8445375},"labels":[],"label_agreement":null},{"id":"W4383616807","doi":"10.1007/978-3-031-35989-7_56","title":"A Transparency Framework for App Store Descriptions","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Transparency (behavior); Upload; Internet privacy; Mental health; Smartphone app; Computer science; Smartphone application; World Wide Web; Coronavirus disease 2019 (COVID-19); Pandemic; App store; Bridge (graph theory); Work (physics); Business; Computer security; Medicine; Multimedia; Engineering; Psychiatry; Infectious disease (medical specialty)","score_opus":0.16555918369345834,"score_gpt":0.4260199239619577,"score_spread":0.26046074026849936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383616807","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000049314996,0.0004817997,0.48581305,0.0026931874,0.0027545341,0.001544982,0.00057955866,0.00026877943,0.5058148],"genre_scores_gemma":[0.29325688,0.002572152,0.5365621,0.0055614146,0.0004424795,0.003842847,0.002513149,0.00018367448,0.15506528],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985028,0.000017528917,0.0007800036,0.00022315688,0.00021793616,0.00025857837],"domain_scores_gemma":[0.9977302,0.00036200997,0.00025711232,0.0013198244,0.00022087048,0.000110002686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006501713,0.00016692143,0.00019957183,0.00083777326,0.0005110675,0.00021358735,0.001304196,0.00016952647,0.000046203186],"category_scores_gemma":[0.00005160489,0.00018262946,0.00008298441,0.00033075034,0.0007730694,0.0019029669,0.0003858627,0.00038514176,0.00041730222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044107232,0.000027988463,0.000011980828,0.000044662862,0.0000066026855,9.8263996e-8,0.0020533951,0.0000070617243,4.7597005e-8,0.85478234,0.0009201407,0.14214124],"study_design_scores_gemma":[0.0006276278,0.00037288968,0.003545403,0.0017087488,0.00002828209,0.000022071137,0.00039597784,0.009395525,0.0000012035432,0.51551104,0.46784678,0.0005444245],"about_ca_topic_score_codex":0.000015920135,"about_ca_topic_score_gemma":0.000033791694,"teacher_disagreement_score":0.46692663,"about_ca_system_score_codex":0.00015037083,"about_ca_system_score_gemma":0.00012279466,"threshold_uncertainty_score":0.7447413},"labels":[],"label_agreement":null},{"id":"W4383616850","doi":"10.1007/978-3-031-35998-9_46","title":"Data-Driven Approach for Student Engagement Modelling Based on Learning Behaviour","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Personalization; Computer science; Student engagement; Attrition; Perception; Artificial intelligence; Data science; Mathematics education; World Wide Web; Psychology","score_opus":0.173544679419602,"score_gpt":0.37010617084788067,"score_spread":0.19656149142827867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383616850","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010728822,0.000022910526,0.97398585,0.0008456701,0.0001315133,0.0003688187,0.000031614738,0.0001585864,0.024444293],"genre_scores_gemma":[0.0395795,0.0005809135,0.9558082,0.0005456361,0.00006088834,0.000048676317,0.0009389484,0.000019779745,0.002417459],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819815,0.000049315786,0.0005482378,0.0004137539,0.000560345,0.00023018669],"domain_scores_gemma":[0.9962861,0.00038456565,0.00030710513,0.0026727684,0.00027032348,0.00007913062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002345366,0.00019709874,0.00022137903,0.0008951148,0.000752642,0.0007661608,0.0052106306,0.00008786078,8.1129974e-7],"category_scores_gemma":[0.000051505383,0.00019688693,0.000044917997,0.00034618558,0.0002335169,0.002330203,0.0032598884,0.0006941352,0.000020915011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.827819e-7,0.000028359136,0.00004140608,0.000022648286,0.000004306222,1.4024931e-7,0.0006245581,0.7786782,6.2243096e-8,0.1904804,0.000094821786,0.030024141],"study_design_scores_gemma":[0.00021887544,0.00007661933,0.00009180741,0.00011955609,0.000009030093,8.8746805e-7,0.000033871314,0.9763604,1.8566142e-7,0.00079074374,0.022090772,0.00020726136],"about_ca_topic_score_codex":0.0000038352696,"about_ca_topic_score_gemma":0.0000012815626,"teacher_disagreement_score":0.19768222,"about_ca_system_score_codex":0.00009653269,"about_ca_system_score_gemma":0.00023816635,"threshold_uncertainty_score":0.96827346},"labels":[],"label_agreement":null},{"id":"W4383650537","doi":"10.1007/978-3-031-35989-7_2","title":"Temperature, Entropy, and Usability: The Theoretical and Practical Resemblances Between Thermodynamics and User Interface Design","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Interactivity; Usability; Computer science; User interface; Entropy (arrow of time); Bridging (networking); Set (abstract data type); Human–computer interaction; World Wide Web; Physics; Thermodynamics; Programming language","score_opus":0.253229587192586,"score_gpt":0.44710967020335707,"score_spread":0.1938800830107711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383650537","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20333213,0.0025910987,0.44627962,0.12156799,0.0015585149,0.008569108,0.00045584652,0.00057904125,0.21506666],"genre_scores_gemma":[0.9649054,0.007496948,0.023599783,0.0014375767,0.00006330783,0.000044589204,0.000034121993,0.000016943837,0.0024013503],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977689,0.00015105511,0.0007749434,0.00028977726,0.0008235901,0.00019173596],"domain_scores_gemma":[0.99493295,0.00329775,0.00029284388,0.0010376113,0.00032724353,0.00011162381],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0060171452,0.00019713659,0.00027204285,0.00055890356,0.00069876213,0.0021239782,0.0010668759,0.00012710186,0.00001384737],"category_scores_gemma":[0.0006183012,0.00012698284,0.000025604753,0.00038580614,0.0039119446,0.004543871,0.0025814506,0.0005117235,0.000027959031],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013720582,0.0000062279246,0.0021092026,0.000013596237,0.000009191234,3.0645714e-7,0.0024577812,0.000023551504,0.0000023741716,0.9316532,0.00079443876,0.062916435],"study_design_scores_gemma":[0.0007824729,0.00023232089,0.13095802,0.00027927788,0.00007852281,0.00006708974,0.0020096712,0.49661732,0.000009191018,0.25661936,0.11156471,0.0007820492],"about_ca_topic_score_codex":0.0000043036316,"about_ca_topic_score_gemma":0.0000067013775,"teacher_disagreement_score":0.76157326,"about_ca_system_score_codex":0.00003595975,"about_ca_system_score_gemma":0.000094872725,"threshold_uncertainty_score":0.9989119},"labels":[],"label_agreement":null},{"id":"W4384134809","doi":"10.1007/978-3-031-35641-4","title":"Advanced Computing","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"North South University; Motilal Nehru National Institute of Technology Allahabad; Jaypee Institute of Information Technology; International Institute of Information Technology, Hyderabad; Jadavpur University; Trinity College Dublin; Indian Institute of Technology Guwahati; Indian Institute of Technology Kharagpur; Indian Institute of Technology Delhi; RMIT University; Osmania University; Liverpool John Moores University; ITM University-Gwalior; Queen's University; Nitte Meenakshi Institute of Technology; Defence Research and Development Organisation; Indian Institute of Science; Jawaharlal Nehru Technological University Hyderabad; Netaji Subhas University of Technology; Indian Institute of Technology Jodhpur; Ramaiah Institute Of Technology; Indian Institute of Technology Roorkee; National Institute of Standards and Technology; Queen's University Belfast; University of Rwanda; Gandhi Institute of Technology and Management; Thapar Institute of Engineering and Technology; BMS College of Engineering; De Montfort University; Al-Balqa' Applied University","keywords":"Computer science; Artificial intelligence","score_opus":0.032611961561829335,"score_gpt":0.26890360582419853,"score_spread":0.2362916442623692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384134809","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03463994,0.0012626578,0.0011429967,0.00928904,0.0022616247,0.0020024742,0.00017560381,0.0010537724,0.9481719],"genre_scores_gemma":[0.6534439,0.02884107,0.07107139,0.023179276,0.003982698,0.00031918508,0.0110889515,0.000023114255,0.20805043],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99894065,0.000023646307,0.00038273673,0.00017607676,0.00026954478,0.0002073625],"domain_scores_gemma":[0.9989865,0.00032821277,0.0001749478,0.00025745804,0.0001841291,0.00006877468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005638704,0.00013778756,0.00016888327,0.0001052986,0.00049901026,0.00028767047,0.0013152322,0.000096792166,0.000009277178],"category_scores_gemma":[0.00003610152,0.000060157232,0.00003635014,0.00086484995,0.0003582533,0.001914714,0.0012053548,0.0002775318,0.00014618857],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016491861,0.000013982856,0.00020136412,0.00001403568,0.0000029254745,2.8560405e-7,0.00063184195,0.000076192715,0.00009540059,0.012688799,0.0076998184,0.9785737],"study_design_scores_gemma":[0.00015410334,0.00007860921,0.058019605,0.00028778307,0.0000051346933,0.00001058312,0.00014635826,0.02145418,0.000011903261,0.0022522067,0.9171882,0.00039131282],"about_ca_topic_score_codex":0.000011319258,"about_ca_topic_score_gemma":0.00007418398,"teacher_disagreement_score":0.9781824,"about_ca_system_score_codex":0.00007831544,"about_ca_system_score_gemma":0.000060962488,"threshold_uncertainty_score":0.3838034},"labels":[],"label_agreement":null},{"id":"W4384209983","doi":"10.1007/978-3-031-35644-5","title":"Advanced Computing","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"North South University; Motilal Nehru National Institute of Technology Allahabad; Jaypee Institute of Information Technology; International Institute of Information Technology, Hyderabad; Jadavpur University; Trinity College Dublin; Indian Institute of Technology Guwahati; Indian Institute of Technology Kharagpur; Indian Institute of Technology Delhi; RMIT University; Osmania University; Liverpool John Moores University; ITM University-Gwalior; Queen's University; Nitte Meenakshi Institute of Technology; Defence Research and Development Organisation; Indian Institute of Science; Jawaharlal Nehru Technological University Hyderabad; Netaji Subhas University of Technology; Indian Institute of Technology Jodhpur; Ramaiah Institute Of Technology; Indian Institute of Technology Roorkee; National Institute of Standards and Technology; Queen's University Belfast; University of Rwanda; Gandhi Institute of Technology and Management; Thapar Institute of Engineering and Technology; BMS College of Engineering; De Montfort University; Al-Balqa' Applied University","keywords":"Computer science; Artificial intelligence","score_opus":0.032611961561829335,"score_gpt":0.26890360582419853,"score_spread":0.2362916442623692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384209983","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03463994,0.0012626578,0.0011429967,0.00928904,0.0022616247,0.0020024742,0.00017560381,0.0010537724,0.9481719],"genre_scores_gemma":[0.6534439,0.02884107,0.07107139,0.023179276,0.003982698,0.00031918508,0.0110889515,0.000023114255,0.20805043],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99894065,0.000023646307,0.00038273673,0.00017607676,0.00026954478,0.0002073625],"domain_scores_gemma":[0.9989865,0.00032821277,0.0001749478,0.00025745804,0.0001841291,0.00006877468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005638704,0.00013778756,0.00016888327,0.0001052986,0.00049901026,0.00028767047,0.0013152322,0.000096792166,0.000009277178],"category_scores_gemma":[0.00003610152,0.000060157232,0.00003635014,0.00086484995,0.0003582533,0.001914714,0.0012053548,0.0002775318,0.00014618857],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016491861,0.000013982856,0.00020136412,0.00001403568,0.0000029254745,2.8560405e-7,0.00063184195,0.000076192715,0.00009540059,0.012688799,0.0076998184,0.9785737],"study_design_scores_gemma":[0.00015410334,0.00007860921,0.058019605,0.00028778307,0.0000051346933,0.00001058312,0.00014635826,0.02145418,0.000011903261,0.0022522067,0.9171882,0.00039131282],"about_ca_topic_score_codex":0.000011319258,"about_ca_topic_score_gemma":0.00007418398,"teacher_disagreement_score":0.9781824,"about_ca_system_score_codex":0.00007831544,"about_ca_system_score_gemma":0.000060962488,"threshold_uncertainty_score":0.3838034},"labels":[],"label_agreement":null},{"id":"W4384303279","doi":"10.1007/978-3-031-37249-0_9","title":"Bootless Application of Greedy Re-ranking Algorithms in Fair Neural Team Formation","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Expert finding and Q&A systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Popularity; Ranking (information retrieval); Computer science; Artificial intelligence; Code (set theory); Machine learning; sort; Algorithm; Information retrieval; Psychology; Social psychology","score_opus":0.05539926057455542,"score_gpt":0.3046228611609021,"score_spread":0.24922360058634668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384303279","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002654503,0.0002630467,0.90994984,0.0008501556,0.00055206445,0.0008775728,0.0000166125,0.00022286538,0.087002404],"genre_scores_gemma":[0.91038996,0.0016557993,0.08603141,0.00047512326,0.00009121923,0.0001837232,0.00018291411,0.000029650679,0.00096021453],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99763954,0.000050336614,0.0011626903,0.00029992612,0.0005918067,0.00025570468],"domain_scores_gemma":[0.99682,0.00023356227,0.00065541634,0.0018978014,0.00032553214,0.00006769776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017900039,0.00021667055,0.00033297556,0.0017769074,0.0002955391,0.00032794094,0.003137423,0.00016180385,7.381547e-7],"category_scores_gemma":[0.000038216855,0.0002224143,0.00005310756,0.0009968024,0.0004235009,0.0067010983,0.0016312798,0.00040410392,0.000036712183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002756936,0.000025560332,0.0002616819,0.00012752163,0.0000045897623,4.2795673e-7,0.011191867,0.0018999077,0.000025746987,0.5260452,0.0001967118,0.460218],"study_design_scores_gemma":[0.00026613937,0.00003839264,0.0014179506,0.0003445314,0.0000020810537,0.0000146753755,0.000100545294,0.983482,0.000026412667,0.004231012,0.009835367,0.00024086013],"about_ca_topic_score_codex":0.000117473195,"about_ca_topic_score_gemma":0.00009260683,"teacher_disagreement_score":0.9815821,"about_ca_system_score_codex":0.00019110172,"about_ca_system_score_gemma":0.00013609166,"threshold_uncertainty_score":0.90697914},"labels":[],"label_agreement":null},{"id":"W4384346102","doi":"10.1007/978-3-031-37249-0_8","title":"Addressing Biases in the Texts Using an End-to-End Pipeline Approach","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Pipeline (software); Popularity; Computer science; Social media; Set (abstract data type); Word (group theory); Natural language processing; Artificial intelligence; Information retrieval; Data science; World Wide Web; Linguistics; Psychology; Social psychology","score_opus":0.20470570782572706,"score_gpt":0.35259485108072064,"score_spread":0.14788914325499358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384346102","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011928646,0.00017715321,0.87761337,0.0010250288,0.0004889837,0.000916815,0.000018500697,0.00023712909,0.118330136],"genre_scores_gemma":[0.39830035,0.0012333764,0.5937615,0.0045865816,0.00023458079,0.0001112895,0.000215032,0.000041047482,0.001516238],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980356,0.00009503841,0.00062127004,0.00033470162,0.0005995775,0.000313824],"domain_scores_gemma":[0.99701995,0.00027739926,0.00022502532,0.0021597208,0.00021050524,0.00010740135],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002702379,0.00020648511,0.00020560615,0.0015301331,0.0006738205,0.0012729915,0.0039677196,0.00010897871,0.0000028950733],"category_scores_gemma":[0.00009798118,0.00017459095,0.000035551442,0.0013189557,0.00043124612,0.005712143,0.0015927964,0.00050289056,0.00004255989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034663299,0.00006122182,0.00002943858,0.000031822306,0.0000034557822,0.000002229646,0.010811345,0.015786115,0.000022357613,0.1627781,0.00017334383,0.81029713],"study_design_scores_gemma":[0.00014571693,0.000043485634,0.0007337181,0.0002502722,0.0000033340175,0.000053588337,0.000113245405,0.9826366,0.00001427644,0.0023156751,0.01343605,0.00025407737],"about_ca_topic_score_codex":0.00007826805,"about_ca_topic_score_gemma":0.000059795246,"teacher_disagreement_score":0.96685046,"about_ca_system_score_codex":0.00012162244,"about_ca_system_score_gemma":0.00027505416,"threshold_uncertainty_score":0.9997638},"labels":[],"label_agreement":null},{"id":"W4385146622","doi":"10.1007/978-3-031-37940-6","title":"Advances in Computing and Data Sciences","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Sharda University; Amity University","keywords":"Computer science; Data science; Focus (optics); Physics","score_opus":0.17310960365721031,"score_gpt":0.3909052087378936,"score_spread":0.21779560508068327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385146622","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011051126,0.0062282123,0.04957222,0.0039732745,0.0019040938,0.0011828507,0.00008600121,0.00035010246,0.93559813],"genre_scores_gemma":[0.55057096,0.23692456,0.16078359,0.027010271,0.004081684,0.00015898417,0.009979041,0.00019188435,0.010299014],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985998,0.000008640191,0.00050591346,0.00032877052,0.0003347621,0.00022210617],"domain_scores_gemma":[0.99810344,0.00021527894,0.00028641283,0.0012258817,0.000157331,0.0000116278925],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.002182614,0.00015021968,0.00019108615,0.0014963461,0.00052732206,0.0012242153,0.0034784016,0.00006638351,0.00000490709],"category_scores_gemma":[0.0001834708,0.00014160457,0.000008694295,0.0017814904,0.0016735648,0.025201531,0.0077103153,0.0002736657,0.000074459764],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021770127,0.0000161354,0.003096407,0.00027891702,0.0000011998359,4.5615627e-7,0.00025764125,0.00042574733,3.4775223e-7,0.18490191,0.0025830893,0.808436],"study_design_scores_gemma":[0.000097722615,0.0000036232202,0.0052425084,0.0004909502,0.0000032896817,0.0000032261912,0.00007224133,0.6007898,1.4080649e-7,0.0072111967,0.38589197,0.00019332959],"about_ca_topic_score_codex":0.00007284828,"about_ca_topic_score_gemma":0.00019787293,"teacher_disagreement_score":0.9252991,"about_ca_system_score_codex":0.000040798797,"about_ca_system_score_gemma":0.0001847448,"threshold_uncertainty_score":0.9998126},"labels":[],"label_agreement":null},{"id":"W4385151647","doi":"10.1007/978-3-031-38854-5","title":"Biomedical Engineering Systems and Technologies","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Universitat Politècnica de València; University of Illinois at Urbana-Champaign; Nile University; Lietuvos Sveikatos Mokslų Universitetas; Kauno Technologijos Universitetas; Szegedi Tudományegyetem; Politechnika Lódzka; Westfälische Wilhelms-Universität Münster; Universidade do Minho; Universidade de Coimbra; University of Zanjan; Slovak Academic Information Agency; Universidad Nacional de Mar del Plata; Athabasca University; Universidad de Las Palmas de Gran Canaria; Universidade de Lisboa; Instituto Superior Técnico; Tsinghua University; Technische Universität München; National Yang-Ming University; Virginia Commonwealth University; Ondokuz Mayis Üniversitesi; Instituto Mexicano del Seguro Social; Universidad de Murcia; Universidade de São Paulo; Università di Pisa; Fondazione Bruno Kessler; Fudan University; Università degli Studi di Milano-Bicocca; Università degli Studi di Brescia; Aalto-Yliopisto; Julius-Maximilians-Universität Würzburg; Islamic Azad University; University of Southampton; Chung-Ang University; University of Bristol; University of Twente; Orta Doğu Teknik Üniversitesi; University of the West of Scotland; Weizmann Institute of Science; Middlesex University; Indian Council of Agricultural Research; North Dakota State University; Kitasato University; Università degli Studi di Milano; Hebrew University of Jerusalem; Università degli Studi di Torino; Queen Mary University of London; Hannam University; Masarykova Univerzita; Academia Militar; University of Pittsburgh; Universidad de León; Johns Hopkins University; Universitat Politècnica de Catalunya; Universidade de Aveiro; George Washington University; Massachusetts General Hospital","keywords":"Computer science; Electronics; Systems engineering; Nanotechnology; Data science; Engineering; Electrical engineering; Materials science","score_opus":0.01960219683685146,"score_gpt":0.2442939410833639,"score_spread":0.22469174424651245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385151647","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049669943,0.040541064,0.78729063,0.0060507283,0.01977924,0.0032425341,0.00028879094,0.018364258,0.11947573],"genre_scores_gemma":[0.5652929,0.24419585,0.17009534,0.00046666354,0.001156141,0.0013076686,0.0022521014,0.00033034786,0.0149029745],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923164,0.0000034985167,0.0003147331,0.00009700667,0.0001898047,0.00016332051],"domain_scores_gemma":[0.9992334,0.00011491545,0.000032465316,0.00051096117,0.00004858438,0.000059633076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037301608,0.00012426963,0.0001448057,0.00097247906,0.00008268496,0.00018091513,0.0005929273,0.00016340606,4.4118136e-7],"category_scores_gemma":[0.00005091202,0.0001214908,0.0000101817395,0.00059995695,0.00046556353,0.0009957835,0.00044852507,0.00034372753,0.000022836814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012267608,0.000027451848,0.00006181354,0.0047198213,0.00004384381,0.00000141546,0.00345282,0.018871984,0.00007721824,0.108031526,0.023843847,0.84086704],"study_design_scores_gemma":[0.00006000646,0.000009154816,0.0003922501,0.0003713735,0.0000025989955,0.000011246744,0.00006409632,0.8281735,0.0000016392203,0.00019467573,0.170576,0.00014344741],"about_ca_topic_score_codex":0.0000024950207,"about_ca_topic_score_gemma":5.007566e-7,"teacher_disagreement_score":0.8407236,"about_ca_system_score_codex":0.00012557332,"about_ca_system_score_gemma":0.00007611589,"threshold_uncertainty_score":0.49542508},"labels":[],"label_agreement":null},{"id":"W4385399313","doi":"10.1007/978-3-031-39059-3_12","title":"A Novel Probabilistic Approach for Detecting Concept Drift in Streaming Data","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Concept drift; Streaming data; Computer science; Benchmark (surveying); Probabilistic logic; Lag; Data mining; Data stream mining; Classifier (UML); Time lag; Constant false alarm rate; Precision and recall; False alarm; Artificial intelligence; Machine learning; Algorithm","score_opus":0.13924573285751413,"score_gpt":0.3386332427871062,"score_spread":0.1993875099295921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385399313","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000006332141,0.000048356214,0.9658109,0.000187943,0.00011760574,0.0008577728,0.0001716614,0.00025897013,0.03254046],"genre_scores_gemma":[0.0066917865,0.00017348444,0.9919362,0.00013942567,0.000022739208,0.00011537507,0.00063133764,0.000013506193,0.00027613228],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807996,0.000016338714,0.0007111156,0.0005437398,0.00035258124,0.00029627918],"domain_scores_gemma":[0.99398357,0.0006555251,0.00037837762,0.0046783206,0.0002383585,0.000065843495],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0021512613,0.00022465101,0.00028066355,0.0011354142,0.00033120974,0.000750184,0.009047164,0.00012971293,4.1859425e-7],"category_scores_gemma":[0.00039445952,0.00023793802,0.000025712674,0.0006888896,0.0006499896,0.0077544074,0.009154109,0.00041684136,0.000004501961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011888917,0.000026454574,0.000012492807,0.0000565942,0.0000034237603,1.6827408e-7,0.0016603301,0.00035811952,0.0000023027528,0.47416973,0.00021353028,0.5234957],"study_design_scores_gemma":[0.0002434269,0.0000372535,0.0002351692,0.00027249957,0.000003592618,0.0000136170065,0.000039655002,0.98470896,0.0000052344335,0.0049937405,0.009177322,0.00026952903],"about_ca_topic_score_codex":0.000045836256,"about_ca_topic_score_gemma":0.00003675689,"teacher_disagreement_score":0.98435086,"about_ca_system_score_codex":0.0001435603,"about_ca_system_score_gemma":0.00034376158,"threshold_uncertainty_score":0.99885964},"labels":[],"label_agreement":null},{"id":"W4385507389","doi":"10.1007/978-3-031-38821-7_1","title":"A Digital Twin Description Framework and Its Mapping to Asset Administration Shell","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Scope (computer science); Asset (computer security); Computer science; Pace; Scale (ratio); Checklist; Process management; Knowledge management; Data science; Systems engineering; Engineering management; Engineering; Computer security; Geography; Cartography","score_opus":0.0781508561469355,"score_gpt":0.280552306480442,"score_spread":0.20240145033350648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385507389","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016471951,0.00016701671,0.22214338,0.0007197394,0.0006871773,0.0008582269,0.00022323261,0.00055827276,0.77299577],"genre_scores_gemma":[0.9637714,0.0023963973,0.028640402,0.00060513517,0.0001089302,0.000113540074,0.0005245705,0.000054391705,0.0037852013],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878895,0.000005390101,0.0005883797,0.00014293555,0.0002954481,0.00017890113],"domain_scores_gemma":[0.9989431,0.0001376612,0.00008041152,0.00055361504,0.00016122872,0.0001240141],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00031701836,0.00018810532,0.00016312483,0.0008922838,0.00018365534,0.001180545,0.00062143663,0.00018073809,0.0000059422996],"category_scores_gemma":[0.00005831967,0.00021861,0.000022422026,0.0004447202,0.00017808624,0.00838589,0.0003477609,0.00042761152,0.00020017764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005269584,0.000014778476,0.00012557798,0.00031866247,0.000020641117,8.741033e-7,0.005076154,0.006917501,0.0000149301095,0.56503457,0.0012340444,0.421237],"study_design_scores_gemma":[0.00035640335,0.00012228539,0.003201436,0.002164607,0.00001211761,0.000060909962,0.0005814691,0.62875265,0.00004590931,0.017170323,0.3464153,0.0011165987],"about_ca_topic_score_codex":4.5649867e-7,"about_ca_topic_score_gemma":0.0000024148508,"teacher_disagreement_score":0.9621242,"about_ca_system_score_codex":0.00011829105,"about_ca_system_score_gemma":0.000071590366,"threshold_uncertainty_score":0.99985635},"labels":[],"label_agreement":null},{"id":"W4385612375","doi":"10.1007/978-3-031-40501-3","title":"Computer Supported Education","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Innovative Educational Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Education, Nanyang Technological University; Universitat Politècnica de València; Leibniz-Gemeinschaft; University of Michigan-Dearborn; University of West Attica; Universitas Telkom; Szegedi Tudományegyetem; Technical University of Sofia; Instituto Politécnico de Viseu; Universidade do Minho; Silesian University of Technology; Universidad de Valladolid; Sunway University; Imperial College London; Universidade Federal de Santa Catarina; Università di Bologna; Universidade de São Paulo; Jyväskylän Yliopisto; Universidade Federal do Rio Grande do Sul; University of Crete; Newcastle University; Università degli Studi di Trento; University of Thessaly; Université de Genève; University of Surrey; Bulgarian Academy of Sciences; Gottfried Wilhelm Leibniz Universität Hannover; Universiteit Maastricht; University of Twente; Universidade de Vigo; Technische Universiteit Delft; TU Graz, Internationale Beziehungen und Mobilitätsprogramme; Athabasca University; Universiteit Utrecht; Università degli Studi di Milano; Curtin University of Technology; Universidad Pública de Navarra; Université Claude Bernard Lyon 1; Nanyang Technological University; Universidad de Extremadura; Universidad de Guadalajara; Universidade do Porto; Universität Duisburg-Essen; Universidade Feevale; University of Portsmouth; Universiti Tunku Abdul Rahman; Le Mans Université; Universidad de Zaragoza; Norges Teknisk-Naturvitenskapelige Universitet; Sveučilište u Zagrebu; University of the Sunshine Coast; Educational Testing Service; Kennesaw State University; State University of New York; Kungliga Tekniska Högskolan; University of Warwick; Rīgas Tehniskā Universitāte; Deakin University; Universidad de La Rioja; University of Macedonia; Universidade de Aveiro; University of Maryland, Baltimore County; University of Technology Sydney","keywords":"Computer science; World Wide Web; Library science; Multimedia; Engineering management; Engineering","score_opus":0.05437539316809363,"score_gpt":0.3409788996038886,"score_spread":0.28660350643579496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385612375","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015441493,0.00027613167,0.75302947,0.008980487,0.003861758,0.0010837885,0.000025469573,0.0012162464,0.23137225],"genre_scores_gemma":[0.007907418,0.0021523004,0.9477539,0.0056596813,0.00035918603,0.00036674587,0.0007406239,0.000039855382,0.035020307],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977329,0.00005146627,0.00083849294,0.00042679382,0.0006076726,0.0003426853],"domain_scores_gemma":[0.99500304,0.0003393739,0.0004657504,0.0029707376,0.0011376955,0.000083369196],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0013713533,0.00027147538,0.00027551514,0.0028797921,0.0005045695,0.0008944964,0.0062117246,0.00019826929,0.000004758334],"category_scores_gemma":[0.00012706165,0.00028372413,0.00004258413,0.0029774322,0.0011980395,0.008625254,0.004669843,0.0006322646,0.0003591065],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.057871e-7,0.000030980056,0.00005638823,0.000026082515,0.000004212878,1.7369337e-7,0.0008839051,0.000034571854,0.0000014641139,0.67531896,0.025277589,0.2983653],"study_design_scores_gemma":[0.00028429067,0.00009459634,0.014462673,0.0004419844,0.000005998695,0.000047615875,0.000085064756,0.31109628,0.000029982484,0.11500862,0.557659,0.0007839481],"about_ca_topic_score_codex":0.00000999614,"about_ca_topic_score_gemma":0.0000051552815,"teacher_disagreement_score":0.5603103,"about_ca_system_score_codex":0.00052971806,"about_ca_system_score_gemma":0.003920312,"threshold_uncertainty_score":0.9999615},"labels":[],"label_agreement":null},{"id":"W4385640767","doi":"10.1007/978-3-031-40564-8","title":"Computing Science, Communication and Security","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Prince Sultan University; Universitas Airlangga; University of Dar es Salaam; Birla Institute of Technology and Science, Pilani; Ege Üniversitesi; Defence Research and Development Organisation; Indian Space Research Organisation; SRM Institute of Science and Technology; Missouri University of Science and Technology; Jazan University; King Khalid University; University of Windsor; King Abdulaziz University; University of Oklahoma","keywords":"Computer science","score_opus":0.07521615172757612,"score_gpt":0.326543245226252,"score_spread":0.2513270934986759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385640767","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004942135,0.0011230819,0.0146450335,0.0035954982,0.0013777768,0.0012877407,0.00003997406,0.00059699715,0.9723918],"genre_scores_gemma":[0.94602543,0.011988006,0.02447123,0.008528099,0.00092713087,0.000082705425,0.0015820699,0.00008217045,0.00631315],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981914,0.000011661323,0.00061167363,0.0003132286,0.0005627183,0.00030932887],"domain_scores_gemma":[0.9968221,0.00018766042,0.0004451212,0.001717149,0.0007981825,0.000029781653],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts","scholarly_communication"],"category_scores_codex":[0.0028456491,0.00021089331,0.00023708507,0.002181355,0.0014746458,0.0023005523,0.0031386062,0.00010457576,0.000010011755],"category_scores_gemma":[0.0002288902,0.00021164605,0.000022600045,0.0026081647,0.0040116413,0.016929997,0.007209524,0.00047237842,0.00018081094],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000045986953,0.000033328834,0.0013273011,0.00032823702,0.0000051476554,3.210246e-7,0.0013482248,0.000100271674,0.0000043782175,0.75206643,0.006848367,0.23793338],"study_design_scores_gemma":[0.0002244439,0.0000069621005,0.013138607,0.00063398323,0.0000149112875,0.000010026313,0.00015745845,0.5460684,0.00000251371,0.032819025,0.4064662,0.00045751457],"about_ca_topic_score_codex":0.00011466587,"about_ca_topic_score_gemma":0.00007331373,"teacher_disagreement_score":0.96607864,"about_ca_system_score_codex":0.00013392059,"about_ca_system_score_gemma":0.00038098628,"threshold_uncertainty_score":0.9998253},"labels":[],"label_agreement":null},{"id":"W4385712057","doi":"10.1007/978-3-031-39141-5_25","title":"Designing PIDs for Reproducible Science Using Time-Series Data","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Identifier; Computer science; Series (stratigraphy); Information retrieval; Data mining; Data science; Biology; Paleontology","score_opus":0.16843606145393786,"score_gpt":0.33723987986103743,"score_spread":0.16880381840709957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385712057","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012664023,0.0001846625,0.944424,0.0006964294,0.00035692015,0.00047480347,0.000040757186,0.00018448623,0.053625274],"genre_scores_gemma":[0.0012906023,0.000667116,0.9936323,0.0002241453,0.00007924742,0.000016527874,0.00011502115,0.000016795853,0.0039582048],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975007,0.000014057769,0.0007729314,0.0007450702,0.0005839974,0.00038321532],"domain_scores_gemma":[0.9925409,0.0002415177,0.00047284542,0.005900206,0.0007353397,0.000109218156],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.00545141,0.00021844044,0.00030777638,0.0014448683,0.0016860128,0.0017475222,0.008879954,0.00007744685,0.0000038655776],"category_scores_gemma":[0.00034993753,0.00021937063,0.000044278033,0.0015676965,0.0018080516,0.02001851,0.010156815,0.0002496127,0.00004322193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004073158,0.000011717952,0.00001885875,0.000055894205,0.000013463023,4.1897798e-7,0.0016725449,0.0024194235,0.00015135316,0.65320796,0.0005352947,0.34190902],"study_design_scores_gemma":[0.00009925323,0.00004011038,0.000050409413,0.00016732802,0.000010070171,0.000017793882,0.000025960704,0.95297766,0.00006469158,0.0062780622,0.039997153,0.0002715258],"about_ca_topic_score_codex":0.000016469481,"about_ca_topic_score_gemma":0.000005775095,"teacher_disagreement_score":0.95055825,"about_ca_system_score_codex":0.00013845488,"about_ca_system_score_gemma":0.0008129189,"threshold_uncertainty_score":0.99961364},"labels":[],"label_agreement":null},{"id":"W4385712138","doi":"10.1007/978-3-031-39141-5_17","title":"Scoring Ontologies for Reuse: An Approach for Fitting Semantic Requirements","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Ontology; Reuse; Set (abstract data type); Process (computing); Selection (genetic algorithm); Information retrieval; Software engineering; Data science; Artificial intelligence; Programming language; Engineering","score_opus":0.18174248235207593,"score_gpt":0.36096108394355003,"score_spread":0.1792186015914741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385712138","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000068663,0.00015146607,0.9749318,0.00064534665,0.0004331775,0.000960527,0.0000131534225,0.00029246075,0.022503423],"genre_scores_gemma":[0.0124050025,0.0007202313,0.98505926,0.00039879742,0.000056358727,0.00022609755,0.00010476768,0.000013867716,0.001015593],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981946,0.000021171401,0.00070693763,0.00040925437,0.00031764508,0.00035044283],"domain_scores_gemma":[0.99566704,0.00057508145,0.00037800262,0.0028799034,0.00042975202,0.00007023893],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0020154535,0.00022154447,0.00031097812,0.0007818258,0.000778345,0.0008203021,0.005774509,0.00013503328,3.4174747e-7],"category_scores_gemma":[0.00037036513,0.00021482805,0.000063596824,0.00030338057,0.00051596994,0.0066437325,0.0029742194,0.00019928702,0.0000059297504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004151501,0.000017114568,0.000068215224,0.00015684399,0.000009591144,1.5972688e-7,0.0023229443,0.00048059152,0.0000040621862,0.80083793,0.0002654001,0.195833],"study_design_scores_gemma":[0.00038067924,0.000113372684,0.0007418909,0.00019701407,0.000009098486,0.000009773109,0.00012468855,0.94603574,0.00001465781,0.040937535,0.011109038,0.00032650435],"about_ca_topic_score_codex":0.000012418616,"about_ca_topic_score_gemma":0.000011655472,"teacher_disagreement_score":0.94555515,"about_ca_system_score_codex":0.00009722377,"about_ca_system_score_gemma":0.00020950036,"threshold_uncertainty_score":0.9996047},"labels":[],"label_agreement":null},{"id":"W4386775099","doi":"10.1007/978-3-031-43940-7_13","title":"OISHI: An Ontology Integration Framework for Domains of Socio-Humanitarian Importance Incorporating Hybrid Machine Intelligence","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Ontology; Open Biomedical Ontologies; Ontology-based data integration; Upper ontology; Ontology alignment; Latent Dirichlet allocation; Semantic integration; Process ontology; Information retrieval; Data science; Semantic Web; Topic model; Semantic Web Stack","score_opus":0.07295056711677525,"score_gpt":0.33410223147438994,"score_spread":0.2611516643576147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386775099","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014893444,0.00017847618,0.98683774,0.00093358476,0.00041830604,0.00047843135,0.00003563139,0.00013703249,0.01083184],"genre_scores_gemma":[0.21149449,0.0007706373,0.78671414,0.0005897299,0.00004665407,0.000057323854,0.0001725967,0.000013121422,0.00014133654],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99794805,0.000043502743,0.0010587476,0.0003592955,0.000343908,0.00024650065],"domain_scores_gemma":[0.99568325,0.0007892582,0.0008416407,0.0020529272,0.00055618916,0.000076726734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016757627,0.0002387478,0.0003839143,0.00079775054,0.0005036242,0.00036049087,0.003846596,0.00016635237,0.0000028108107],"category_scores_gemma":[0.00031685244,0.00023197672,0.0000654029,0.0003832429,0.0011439897,0.004991151,0.0014089753,0.00044142822,0.000010276992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002699724,0.000012658308,0.00011256878,0.00002707177,0.0000045923953,3.5270887e-7,0.0017679849,0.000076479766,0.0000022484267,0.8470943,0.000023090646,0.15087596],"study_design_scores_gemma":[0.00010572738,0.00015632989,0.00092341786,0.00020439892,0.0000065848035,0.000014643961,0.00015298759,0.37805206,0.000047912672,0.618904,0.0011842258,0.00024772168],"about_ca_topic_score_codex":0.000047311594,"about_ca_topic_score_gemma":0.00031117984,"teacher_disagreement_score":0.37797558,"about_ca_system_score_codex":0.000117799565,"about_ca_system_score_gemma":0.00031572153,"threshold_uncertainty_score":0.94597363},"labels":[],"label_agreement":null},{"id":"W4387048904","doi":"10.1007/978-3-031-43605-5_11","title":"Application of Near-Infrared (NIR) Hyperspectral Imaging System for Protein Content Prediction in Chickpea Flour","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Lethbridge College","funders":"","keywords":"Hyperspectral imaging; Partial least squares regression; Near-infrared spectroscopy; Content (measure theory); Calibration; Mathematics; Food science; Wheat flour; Chemistry; Computer science; Statistics; Biology; Artificial intelligence","score_opus":0.041574999321110265,"score_gpt":0.28583462590202435,"score_spread":0.2442596265809141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387048904","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012131399,0.0018574477,0.4286575,0.0011631064,0.0004130678,0.0036890507,0.0007814688,0.00067276903,0.5506342],"genre_scores_gemma":[0.9574877,0.0004554081,0.036110837,0.00007618617,0.00007943315,0.00046861434,0.00057936786,0.00003087503,0.004711606],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985411,0.000007636479,0.00078306795,0.00021269932,0.00027657562,0.00017890194],"domain_scores_gemma":[0.9981751,0.00010279307,0.0004385645,0.0009134875,0.00032204195,0.000048015798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005736253,0.00016110745,0.00028382338,0.0007269328,0.00022718328,0.00013865612,0.0008795279,0.00011029265,0.0000070407873],"category_scores_gemma":[0.00006278419,0.0001693573,0.000060399212,0.00051749515,0.0004542155,0.0011594342,0.00032686125,0.00027269358,0.00000990118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001274882,0.00021031382,0.006271435,0.0034659058,0.00012793294,9.827999e-7,0.008303668,0.0023185778,0.014425713,0.813772,0.00041303446,0.15056291],"study_design_scores_gemma":[0.0011644906,0.000043037096,0.0021849377,0.0008395105,0.000055279415,0.000013769106,0.0010691339,0.97805303,0.005802532,0.0028604881,0.0075072283,0.00040653374],"about_ca_topic_score_codex":0.000054459386,"about_ca_topic_score_gemma":0.00000837336,"teacher_disagreement_score":0.9757345,"about_ca_system_score_codex":0.0003251225,"about_ca_system_score_gemma":0.00017081395,"threshold_uncertainty_score":0.69061905},"labels":[],"label_agreement":null},{"id":"W4387048924","doi":"10.1007/978-3-031-43605-5_8","title":"Fast Rotated Bounding Box Annotations for Object Detection","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Annotation; Computer science; Minimum bounding box; Workload; Bounding overwatch; Object (grammar); Publication; Data mining; Object detection; Artificial intelligence; Information retrieval; Pattern recognition (psychology); Image (mathematics); Operating system","score_opus":0.05062299964689058,"score_gpt":0.3157571102447346,"score_spread":0.265134110597844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387048924","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001662788,0.00007355549,0.97133183,0.0010603208,0.00042860792,0.0010075902,0.000032460706,0.00037537064,0.025673617],"genre_scores_gemma":[0.046995692,0.003732077,0.9386854,0.0016686264,0.00020341852,0.0012082196,0.00041329494,0.00006937536,0.007023878],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998104,0.000023479433,0.00075422286,0.0004138632,0.00037109206,0.0003333542],"domain_scores_gemma":[0.99628407,0.00060170237,0.00044261734,0.0019797145,0.00057852844,0.000113399416],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007992798,0.0002489137,0.00024407721,0.0012725531,0.0012968687,0.0007432359,0.002756425,0.00012743386,0.0000013903159],"category_scores_gemma":[0.00009306148,0.00027464665,0.0000668322,0.0012353897,0.00059515215,0.0066316132,0.0015160106,0.00039376845,0.000083733736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002048416,0.0000084590765,0.000003920216,0.000020502217,0.0000053994563,1.3050595e-7,0.0008621606,0.002279799,0.00003174046,0.6013654,0.00016811882,0.39525232],"study_design_scores_gemma":[0.00028140724,0.000060233582,0.0003514531,0.00011879852,0.000007369157,0.000016753887,0.000022555976,0.85858184,0.00006557579,0.054505404,0.08562641,0.00036220878],"about_ca_topic_score_codex":0.0000057945595,"about_ca_topic_score_gemma":0.00004117318,"teacher_disagreement_score":0.856302,"about_ca_system_score_codex":0.00022105005,"about_ca_system_score_gemma":0.00022449195,"threshold_uncertainty_score":0.99997056},"labels":[],"label_agreement":null},{"id":"W4387145716","doi":"10.1007/978-3-031-42430-4","title":"Recent Challenges in Intelligent Information and Database Systems","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"North South University; Al-Farabi Kazakh National University; Uniwersytet Śląski w Katowicach; Politechnika Swietokrzyska w Kielcach; Politechnika Koszalińska; Tokyo Metropolitan University; Politechnika Krakowska; Griffith University; National Taiwan University; Fujian University of Technology; National Taiwan University of Science and Technology; Universidad de Granada; Sungkyunkwan University; Universidad de Chile; Univerzita Hradec Králové; Yeungnam University; Universiti Teknologi Malaysia; Ben-Gurion University of the Negev; Instituto Tecnológico y de Estudios Superiores de Monterrey; Universitatea Politehnica Timisoara; Universidade de Macau; Euskal Herriko Unibertsitatea; Silesian University of Technology; Waseda University; Universidad Complutense de Madrid; Chungbuk National University; Sharif University of Technology; Vrije Universiteit Amsterdam; Universität Passau; University College London; Trường Đại học Hàng hải Việt Nam; University of Ulsan; Eötvös Loránd Tudományegyetem; Uniwersytet Morski w Gdyni; University of the West of England; Universiti Teknologi Petronas; University of Cyprus; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; University of Notre Dame; Cheng Shiu University; Chaoyang University of Technology; Technische Universität Berlin; Nanyang Technological University; University of Waikato; Swinburne University of Technology; Uniwersytet Kardynała Stefana Wyszyńskiego w Warszawie; Deakin University; Birmingham City University; University of Brighton; Univerzita Karlova v Praze; Auckland University of Technology, New Zealand; Virginia Commonwealth University; Politechnika Gdańska; Concordia University; Indian National Science Academy; Université de Technologie de Troyes; King Saud University; Wojskowa Akademia Techniczna; Uniwersytet Opolski; Université de Lorraine","keywords":"Computer science; Information retrieval; Thesaurus; Database; World Wide Web; Artificial intelligence","score_opus":0.1911045705798801,"score_gpt":0.33459111084848414,"score_spread":0.14348654026860405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387145716","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024947273,0.013331049,0.034974452,0.021527525,0.006913299,0.0077783135,0.0004780404,0.0013425212,0.91116005],"genre_scores_gemma":[0.08724779,0.90221566,0.0026886573,0.002682043,0.00012137159,0.00057584833,0.0005304927,0.000039495586,0.0038986206],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980654,0.00012737699,0.0008690795,0.00026595886,0.00044740678,0.00022475686],"domain_scores_gemma":[0.9977365,0.0004443358,0.00038259014,0.0011607907,0.00017871767,0.00009704053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016099425,0.00018306565,0.00020777155,0.0017322336,0.00030903504,0.00054586027,0.0010273722,0.00011739899,0.0000031047755],"category_scores_gemma":[0.00046998393,0.00018732248,0.000016435182,0.0010172148,0.00069446245,0.0069903443,0.0010138488,0.0004869754,0.00014168675],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008311579,0.00002511799,0.000015166709,0.00017805108,0.0000012594749,4.5123755e-7,0.0039842427,0.00022890352,0.000027288537,0.1503847,0.0009066615,0.84423983],"study_design_scores_gemma":[0.00034540385,0.00004347136,0.0015023579,0.000427706,0.0000032152727,0.0000439795,0.0006098862,0.30037844,0.000076561504,0.0011529971,0.6951086,0.00030738366],"about_ca_topic_score_codex":0.000012058393,"about_ca_topic_score_gemma":0.000032416174,"teacher_disagreement_score":0.90726143,"about_ca_system_score_codex":0.00032996314,"about_ca_system_score_gemma":0.00033054614,"threshold_uncertainty_score":0.7638789},"labels":[],"label_agreement":null},{"id":"W4387145727","doi":"10.1007/978-3-031-42430-4_12","title":"Enhanced Energy Characterization and Feature Selection Using Explainable Non-parametric AGGMM","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Interpretability; Feature selection; Markov chain Monte Carlo; Smart meter; Data mining; Feature (linguistics); Context (archaeology); Mixture model; Machine learning; Bayesian probability; Parametric statistics; Artificial intelligence; Engineering; Smart grid; Mathematics","score_opus":0.02320888097918546,"score_gpt":0.24123973512011013,"score_spread":0.21803085414092466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387145727","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005896624,0.0004658366,0.8953898,0.00007530579,0.0009337839,0.0002786679,0.000026445772,0.00036971568,0.09656381],"genre_scores_gemma":[0.88935006,0.03948407,0.058817945,0.00042805812,0.00027993618,0.00007448569,0.0009705288,0.00010350783,0.0104914075],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992105,0.000008082992,0.00030941505,0.0001334844,0.0001684619,0.00017009619],"domain_scores_gemma":[0.9992391,0.000072430616,0.00011979779,0.00037611317,0.00013683841,0.00005574136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026803365,0.00016467494,0.0001644948,0.0010920202,0.00032357426,0.0002646729,0.00035656177,0.00013908977,0.000002572072],"category_scores_gemma":[0.000016072516,0.00018208542,0.000018076931,0.0006862168,0.00016604397,0.002609828,0.0003033016,0.00025046043,0.0000055649557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059268345,0.000011167233,0.000062051084,0.00026848947,0.000029634844,5.6804134e-7,0.003065512,0.07132444,0.0027030723,0.123601,0.00019083971,0.7987373],"study_design_scores_gemma":[0.00010715036,0.000015756079,0.0004453346,0.00024140574,0.0000055173696,0.000011487435,0.000010303266,0.96719635,0.00031031045,0.00024850044,0.031195842,0.00021202573],"about_ca_topic_score_codex":0.000011606789,"about_ca_topic_score_gemma":0.000010459536,"teacher_disagreement_score":0.89587194,"about_ca_system_score_codex":0.00011004289,"about_ca_system_score_gemma":0.000052758,"threshold_uncertainty_score":0.7425228},"labels":[],"label_agreement":null},{"id":"W4387145819","doi":"10.1007/978-3-031-42430-4_30","title":"A Projected Upper Bound for Mining High Utility Patterns from Interval-Based Event Sequences","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Pruning; Interval (graph theory); Upper and lower bounds; Event (particle physics); Constraint (computer-aided design); Computer science; Branch and bound; Data mining; Mathematical optimization; Algorithm; Mathematics; Combinatorics; Physics","score_opus":0.07527730592061883,"score_gpt":0.32622547633851956,"score_spread":0.25094817041790074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387145819","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008878924,0.00006170234,0.99110156,0.0018398486,0.00041509382,0.00080559705,0.0006673442,0.000236963,0.0039839754],"genre_scores_gemma":[0.08278038,0.0005128325,0.9117039,0.0013718165,0.000098403885,0.000573951,0.0018674249,0.00002689651,0.0010644282],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979739,0.000031789325,0.0008009506,0.0004895817,0.0004209016,0.00028285015],"domain_scores_gemma":[0.99599344,0.00062876055,0.00041323082,0.0024273775,0.0004343225,0.00010286595],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001095248,0.00024957335,0.00028965966,0.00069561077,0.0006245818,0.0010696161,0.004037803,0.00012410295,0.00000804754],"category_scores_gemma":[0.00007964279,0.00024458632,0.000071745955,0.00043373328,0.0005691176,0.0038132907,0.0019602682,0.00027676058,0.00003401826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004617075,0.00004527928,0.00023939117,0.00006628283,0.000018061164,4.2059898e-7,0.0028587205,0.00013325346,0.0000045652505,0.2834808,0.00080412265,0.71234447],"study_design_scores_gemma":[0.00031018202,0.000059941412,0.00413002,0.00040883102,0.000009285674,0.0000023168736,0.00004420564,0.942945,0.000020058855,0.012759781,0.03898763,0.0003227439],"about_ca_topic_score_codex":0.00018538679,"about_ca_topic_score_gemma":0.000068432484,"teacher_disagreement_score":0.9428117,"about_ca_system_score_codex":0.00012514245,"about_ca_system_score_gemma":0.0005140306,"threshold_uncertainty_score":0.9999674},"labels":[],"label_agreement":null},{"id":"W4387145866","doi":"10.1007/978-3-031-42430-4_10","title":"The Completion of a Smart Factory Research Project by Concluding a DAO","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Factory (object-oriented programming); Computer science; Engineering management; Business; State (computer science); Engineering","score_opus":0.20572215100374022,"score_gpt":0.4011474744119047,"score_spread":0.19542532340816446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387145866","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025576862,0.00081962626,0.67950445,0.005912304,0.0009839595,0.0027374856,0.00012660843,0.00045364286,0.3092062],"genre_scores_gemma":[0.49906722,0.025191337,0.41145447,0.0031261188,0.00028269543,0.0012096529,0.0008851468,0.00019514037,0.058588207],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973155,0.000121513294,0.0009145765,0.00027999043,0.0010439635,0.00032440224],"domain_scores_gemma":[0.99365145,0.001792948,0.00044859078,0.0025737195,0.0014797476,0.000053551903],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0054487423,0.00016959134,0.00023329753,0.0013459024,0.0015769438,0.00090372365,0.005512551,0.00011188236,0.0000016701343],"category_scores_gemma":[0.0003144553,0.00014512788,0.00004128499,0.0018582543,0.0024978162,0.004085607,0.004848022,0.0007537804,0.00005784135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019627937,0.000010676092,0.00006333923,0.000023241144,0.000007344408,1.1433817e-7,0.002966376,0.000021512018,0.000011432227,0.9173194,0.0067149955,0.07285961],"study_design_scores_gemma":[0.000302855,0.00013316798,0.0010691219,0.00040726486,0.000003770227,0.000012246972,0.00020379214,0.17863448,0.000034757206,0.02035723,0.79848486,0.00035643924],"about_ca_topic_score_codex":0.00007710016,"about_ca_topic_score_gemma":0.000033799875,"teacher_disagreement_score":0.89696217,"about_ca_system_score_codex":0.00020341328,"about_ca_system_score_gemma":0.0007488541,"threshold_uncertainty_score":0.9998681},"labels":[],"label_agreement":null},{"id":"W4387170531","doi":"10.1007/978-3-031-45137-9","title":"E-Business and Telecommunications","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Impact of AI and Big Data on Business and Society","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of South Africa; Università di Bologna; Soochow University; Università degli Studi di Genova; University of Waterloo; Università degli Studi di Padova; Florida International University; University of Macedonia; Università degli Studi Mediterranea di Reggio Calabria; Università degli Studi di Milano; Technische Universität Ilmenau; Universidad de Málaga; International Islamic University Malaysia; Central Queensland University; Université Mohammed V de Rabat; Auckland University of Technology, New Zealand; Università di Catania; Middlesex University; Universitat Politècnica de Catalunya; George Mason University","keywords":"Telecommunications; Computer science; Computer security","score_opus":0.16089195600548242,"score_gpt":0.39853022420679807,"score_spread":0.23763826820131564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387170531","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026209494,0.0035334874,0.107985325,0.038492754,0.0024521104,0.0020558177,0.0007246571,0.00051890675,0.841616],"genre_scores_gemma":[0.19827431,0.21508034,0.2655724,0.021793304,0.00094364176,0.0004303895,0.004397225,0.00018586073,0.29332253],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99739665,0.000080629405,0.0009835095,0.00030405156,0.0009733518,0.00026179847],"domain_scores_gemma":[0.99392635,0.0012965935,0.0004290316,0.0029567059,0.0012597966,0.00013154285],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0045723333,0.00020077344,0.0003464852,0.0013925673,0.0010428323,0.0018931732,0.0039128913,0.00016420001,0.000015166672],"category_scores_gemma":[0.0010124748,0.0001630174,0.00004222921,0.0028156908,0.0019663584,0.007211289,0.0042037675,0.00043004335,0.00019225823],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000047989806,0.00004509941,0.0009795135,0.000046962687,0.000010455727,4.734159e-7,0.0045175687,0.00013477089,0.0000027650908,0.09777948,0.05704991,0.8394282],"study_design_scores_gemma":[0.00033193256,0.000024645475,0.09585277,0.00019303258,0.00000888929,0.000021121896,0.00031050615,0.04677878,7.4946723e-7,0.02339123,0.8327012,0.00038512851],"about_ca_topic_score_codex":0.000033334676,"about_ca_topic_score_gemma":0.000040615425,"teacher_disagreement_score":0.8390431,"about_ca_system_score_codex":0.00010804532,"about_ca_system_score_gemma":0.0008230888,"threshold_uncertainty_score":0.99914294},"labels":[],"label_agreement":null},{"id":"W4387224557","doi":"10.1007/978-3-031-44112-7_2","title":"Progress on Land Surface Phenology Estimation with Multispectral Remote Sensing","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Phenology; Multispectral image; Remote sensing; Vegetation (pathology); Satellite; Environmental science; Computer science; Environmental resource management; Geography; Ecology; Engineering","score_opus":0.022813800767385855,"score_gpt":0.26292545331395073,"score_spread":0.24011165254656489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387224557","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021239158,0.00010597963,0.13438438,0.006449917,0.00082877034,0.0024850196,0.000032505577,0.00072615786,0.8337481],"genre_scores_gemma":[0.10536339,0.0006636666,0.88844144,0.00069236115,0.000042299354,8.0014917e-7,0.00016595781,0.000033129058,0.0045969407],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987172,0.000027399687,0.00034375355,0.0002573938,0.00043559822,0.00021864577],"domain_scores_gemma":[0.99854445,0.00013014836,0.00024511703,0.0009513577,0.000061529296,0.00006736575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044839492,0.0001983318,0.00017945928,0.00019412306,0.0003897205,0.00021098788,0.0006744396,0.00012704986,0.000008333051],"category_scores_gemma":[0.00002481729,0.00015643396,0.000019719273,0.0003660989,0.0015314705,0.0013515837,0.0006914436,0.00041763904,0.00030687565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013386072,0.000010255801,0.00024075656,0.000017978942,0.000007165998,0.000002954454,0.0019213553,0.05185414,0.000010637196,0.006928693,0.0003854517,0.9386072],"study_design_scores_gemma":[0.0002269243,0.00008273616,0.007861097,0.00025747597,0.000006262002,0.000056370565,0.000015352734,0.98042876,0.000013913112,0.001775094,0.00901854,0.00025748272],"about_ca_topic_score_codex":0.00006933198,"about_ca_topic_score_gemma":0.00015252501,"teacher_disagreement_score":0.9383497,"about_ca_system_score_codex":0.00023625283,"about_ca_system_score_gemma":0.00003814293,"threshold_uncertainty_score":0.6379192},"labels":[],"label_agreement":null},{"id":"W4387869738","doi":"10.1007/978-3-031-46813-1_7","title":"From Naive Interest to Shortage During COVID-19: A Google Trends and News Analysis","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Popularity; Pandemic; Scarcity; Economic shortage; Coronavirus disease 2019 (COVID-19); Period (music); Tracking (education); Computer science; Advertising; World Wide Web; Geography; Political science; Business; Medicine; Psychology; Economics","score_opus":0.07452087295758843,"score_gpt":0.3613502059208051,"score_spread":0.28682933296321667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387869738","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10892588,0.002601878,0.16417699,0.062365606,0.0016110705,0.0051666545,0.011453692,0.0022544647,0.6414438],"genre_scores_gemma":[0.89868104,0.007202889,0.05202905,0.012421642,0.00024352667,0.00016660838,0.008523337,0.00006476168,0.02066714],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986546,0.000024031466,0.00056438503,0.00030100901,0.00028987954,0.00016607154],"domain_scores_gemma":[0.99728966,0.0001996351,0.00019175594,0.0017556478,0.00015680226,0.00040649675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040979384,0.00017932407,0.000383922,0.002299825,0.0002930691,0.00023613758,0.0007983308,0.00007666685,0.00006096405],"category_scores_gemma":[0.00017592293,0.00017799757,0.000066053275,0.0011238015,0.0005342235,0.0012339887,0.0017656619,0.00025754346,0.00006695499],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028952627,0.00016962894,0.06133127,0.0005551369,0.0011119754,0.00004276569,0.038251933,0.0022231298,0.00006922226,0.065384835,0.013219702,0.81735086],"study_design_scores_gemma":[0.0015913082,0.00014075954,0.48496798,0.0006121335,0.00040744545,0.000028091164,0.0004953843,0.11207709,0.000006651389,0.0015259451,0.3972915,0.0008556806],"about_ca_topic_score_codex":0.00021395732,"about_ca_topic_score_gemma":0.00067995576,"teacher_disagreement_score":0.8164952,"about_ca_system_score_codex":0.00018446699,"about_ca_system_score_gemma":0.00020143006,"threshold_uncertainty_score":0.725853},"labels":[],"label_agreement":null},{"id":"W4387960435","doi":"10.1007/978-3-031-46739-4_32","title":"Rural Migration in Colombia","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Social Issues and Sustainability","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Poverty; Latin Americans; Sustainability; Begging; Agriculture; Rural area; Geography; Development economics; Agricultural productivity; Economic growth; Quarter (Canadian coin); Political science; Socioeconomics; Business; Economics; Ecology","score_opus":0.04900817558869703,"score_gpt":0.3609341866946239,"score_spread":0.3119260111059269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387960435","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075331884,0.00025051594,0.0006341201,0.008920354,0.00064989785,0.00114864,0.000015321566,0.00016420617,0.98068374],"genre_scores_gemma":[0.93683195,0.022443632,0.005564722,0.0011563769,0.00020091516,0.00012319889,0.00017046677,0.000022363662,0.033486374],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987898,0.00006258976,0.0004426696,0.00011713583,0.0003775644,0.00021025332],"domain_scores_gemma":[0.9986449,0.00026380285,0.00014839259,0.00055484794,0.00032224553,0.0000658335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002174293,0.00009714322,0.00016245343,0.00056817103,0.00068904954,0.00033378697,0.00096005964,0.00014904198,0.0000158835],"category_scores_gemma":[0.00021987903,0.00010909257,0.000029055705,0.0005789925,0.0016158425,0.0028206813,0.0005115184,0.00028216568,0.0000497395],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024255207,0.000010831812,0.001762892,0.000013996386,0.000001361676,2.608711e-7,0.051338673,0.000043819775,1.6876868e-7,0.8319915,0.00051602296,0.114318065],"study_design_scores_gemma":[0.00029856132,0.000037847036,0.035890017,0.00020320743,0.0000047115645,6.356744e-7,0.008837303,0.020029202,4.7605963e-7,0.062008068,0.87231237,0.00037761548],"about_ca_topic_score_codex":0.0022278507,"about_ca_topic_score_gemma":0.008618555,"teacher_disagreement_score":0.9471974,"about_ca_system_score_codex":0.00040787595,"about_ca_system_score_gemma":0.00049246027,"threshold_uncertainty_score":0.5953639},"labels":[],"label_agreement":null},{"id":"W4388336536","doi":"10.1007/978-3-031-46338-9_14","title":"A Real-Time Deep UAV Detection Framework Based on a YOLOv8 Perception Module","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Drone; Computer science; Artificial intelligence; Deep learning; Inference; Object detection; Popularity; Computer vision; Machine learning; Real-time computing; Pattern recognition (psychology)","score_opus":0.031422292435214605,"score_gpt":0.2928416212418092,"score_spread":0.2614193288065946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388336536","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005532688,0.000014629013,0.933009,0.0012054652,0.00024602763,0.00060206925,0.000009426243,0.00048475797,0.064373285],"genre_scores_gemma":[0.08413327,0.0034141864,0.90659374,0.0024310728,0.0001692004,0.00037326055,0.00016466035,0.000057330195,0.002663288],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782133,0.00005172623,0.00068402337,0.0005062472,0.000611932,0.00032476784],"domain_scores_gemma":[0.9952087,0.00064349204,0.0004015766,0.0032666905,0.00034024377,0.00013933278],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007925062,0.00029897984,0.00026927888,0.0013104511,0.0008155669,0.0005070344,0.003130022,0.00022935521,0.00001150389],"category_scores_gemma":[0.00008172795,0.00031609737,0.0000714925,0.0012187134,0.0006196798,0.0040091644,0.0014524086,0.00068530213,0.0006893681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066523285,0.000029472321,0.0000065810677,0.000019648993,0.000003941765,5.1095526e-7,0.0008121318,0.023582682,0.000063107924,0.47138542,0.000112006324,0.50397784],"study_design_scores_gemma":[0.00014521525,0.00008401018,0.0011749688,0.00017480977,0.0000041348735,0.0000067292326,0.000006429463,0.95665574,0.000010603436,0.03340915,0.0080220485,0.00030618516],"about_ca_topic_score_codex":0.00000846408,"about_ca_topic_score_gemma":0.000008957077,"teacher_disagreement_score":0.93307304,"about_ca_system_score_codex":0.00032501438,"about_ca_system_score_gemma":0.00015302195,"threshold_uncertainty_score":0.99992913},"labels":[],"label_agreement":null},{"id":"W4388337125","doi":"10.1007/978-3-031-46335-8_6","title":"A Semi-supervised Teacher-Student Model Based on MMAN for Brain Tissue Segmentation","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Segmentation; Artificial intelligence; Exploit; Medical diagnosis; Labeled data; Set (abstract data type); Pattern recognition (psychology); Supervised learning; Machine learning; Data set; Image segmentation; Artificial neural network; Radiology; Medicine","score_opus":0.062446489358525176,"score_gpt":0.35563548471391626,"score_spread":0.2931889953553911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388337125","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016320582,0.000028770912,0.9608017,0.004871977,0.00014240442,0.0012987194,0.000032618114,0.00024214093,0.03256531],"genre_scores_gemma":[0.019588184,0.00063910004,0.96186346,0.0077443533,0.000094888084,0.0010912004,0.00049164286,0.0000511233,0.008436078],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979645,0.00003056774,0.0006987541,0.00045777712,0.000551147,0.00029727383],"domain_scores_gemma":[0.9961843,0.0006146986,0.00033842973,0.0024249903,0.0003146652,0.00012293652],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00095213676,0.0002789579,0.0002501857,0.0009086656,0.00068433676,0.00048161324,0.0034382914,0.00012743351,0.0000024557812],"category_scores_gemma":[0.00004861264,0.00029330672,0.000057054538,0.00061360205,0.00038815988,0.0033412222,0.0012768395,0.000363431,0.00006262045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000042354372,0.00003598587,0.000006215067,0.000028014227,0.0000039181327,1.4955035e-7,0.0011021579,0.12184882,0.00003059648,0.6112216,0.0013524051,0.2643659],"study_design_scores_gemma":[0.00040049106,0.00008137422,0.0000978994,0.000110881134,0.0000044126414,0.0000018183731,0.000010860476,0.95982814,0.00002977267,0.016265668,0.022883346,0.0002853284],"about_ca_topic_score_codex":0.0000021994215,"about_ca_topic_score_gemma":0.000008339252,"teacher_disagreement_score":0.8379793,"about_ca_system_score_codex":0.00024276257,"about_ca_system_score_gemma":0.00024648182,"threshold_uncertainty_score":0.9999519},"labels":[],"label_agreement":null},{"id":"W4388358900","doi":"10.1007/978-3-031-46338-9","title":"Intelligent Systems and Pattern Recognition","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ajman University; Bahria University; Université de Sfax; Eidgenössisches Nuklearsicherheitsinspektorat; United Arab Emirates University; Gauhati University; Universidad de Las Palmas de Gran Canaria; Qatar University; Universidade do Porto; University of South Dakota; King Fahd University of Petroleum and Minerals; Indian Institute of Technology Roorkee; Loughborough University; Université de Technologie de Compiègne; Menofia University; National University of Sciences and Technology; University of Dayton; Lakehead University; Université Mohammed V de Rabat; Arkansas Tech University; Middle Tennessee State University","keywords":"Computer science; Artificial intelligence; Data science; Pattern recognition (psychology)","score_opus":0.07671250517799462,"score_gpt":0.33662285328269875,"score_spread":0.25991034810470415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388358900","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018235845,0.00026861648,0.97729886,0.00090120645,0.00021216723,0.00049751136,0.000024480187,0.000277604,0.020501345],"genre_scores_gemma":[0.032440644,0.036492255,0.9123751,0.0044706203,0.0003157451,0.0013674466,0.0012020846,0.000076785705,0.0112593435],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984818,0.000036047306,0.0006018604,0.00032302708,0.0003534767,0.00020377978],"domain_scores_gemma":[0.99765384,0.0003029832,0.00029173715,0.0012834106,0.00036823508,0.00009982009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007242619,0.00018290589,0.00019979315,0.0008898896,0.000403925,0.0007643858,0.0019447957,0.00010149512,7.78071e-7],"category_scores_gemma":[0.000030069154,0.0001902635,0.000025245494,0.0008265405,0.0004821868,0.004146155,0.0023644923,0.00033043965,0.00008725701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.6482135e-7,0.0000114716895,0.000010435154,0.000045406352,0.0000033398267,3.1601064e-7,0.00061586004,0.00041926614,6.799992e-7,0.1756235,0.0011617169,0.8221076],"study_design_scores_gemma":[0.000103973805,0.000036741076,0.00042670738,0.00026872326,0.0000033217457,0.000032059866,0.000020392836,0.8374103,0.0000036302235,0.05239324,0.10902001,0.00028090936],"about_ca_topic_score_codex":0.000012401308,"about_ca_topic_score_gemma":0.000003702144,"teacher_disagreement_score":0.836991,"about_ca_system_score_codex":0.00017837594,"about_ca_system_score_gemma":0.00026366836,"threshold_uncertainty_score":0.77587205},"labels":[],"label_agreement":null},{"id":"W4388358919","doi":"10.1007/978-3-031-46335-8","title":"Intelligent Systems and Pattern Recognition","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ajman University; Bahria University; Université de Sfax; Eidgenössisches Nuklearsicherheitsinspektorat; United Arab Emirates University; Gauhati University; Universidad de Las Palmas de Gran Canaria; Qatar University; Universidade do Porto; University of South Dakota; King Fahd University of Petroleum and Minerals; Indian Institute of Technology Roorkee; Loughborough University; Université de Technologie de Compiègne; Menofia University; National University of Sciences and Technology; University of Dayton; Lakehead University; Université Mohammed V de Rabat; Arkansas Tech University; Middle Tennessee State University","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology)","score_opus":0.07671250517799462,"score_gpt":0.33662285328269875,"score_spread":0.25991034810470415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388358919","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018235845,0.00026861648,0.97729886,0.00090120645,0.00021216723,0.00049751136,0.000024480187,0.000277604,0.020501345],"genre_scores_gemma":[0.032440644,0.036492255,0.9123751,0.0044706203,0.0003157451,0.0013674466,0.0012020846,0.000076785705,0.0112593435],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984818,0.000036047306,0.0006018604,0.00032302708,0.0003534767,0.00020377978],"domain_scores_gemma":[0.99765384,0.0003029832,0.00029173715,0.0012834106,0.00036823508,0.00009982009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007242619,0.00018290589,0.00019979315,0.0008898896,0.000403925,0.0007643858,0.0019447957,0.00010149512,7.78071e-7],"category_scores_gemma":[0.000030069154,0.0001902635,0.000025245494,0.0008265405,0.0004821868,0.004146155,0.0023644923,0.00033043965,0.00008725701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.6482135e-7,0.0000114716895,0.000010435154,0.000045406352,0.0000033398267,3.1601064e-7,0.00061586004,0.00041926614,6.799992e-7,0.1756235,0.0011617169,0.8221076],"study_design_scores_gemma":[0.000103973805,0.000036741076,0.00042670738,0.00026872326,0.0000033217457,0.000032059866,0.000020392836,0.8374103,0.0000036302235,0.05239324,0.10902001,0.00028090936],"about_ca_topic_score_codex":0.000012401308,"about_ca_topic_score_gemma":0.000003702144,"teacher_disagreement_score":0.836991,"about_ca_system_score_codex":0.00017837594,"about_ca_system_score_gemma":0.00026366836,"threshold_uncertainty_score":0.77587205},"labels":[],"label_agreement":null},{"id":"W4388693539","doi":"10.1007/978-3-031-47958-8_6","title":"Towards Understanding Persons and Their Personalities with Cybernetic Big 5 Theory and the Free Energy Principle and Active Inference (FEP-AI) Framework","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mental Health and Psychiatry","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Cybernetics; Inference; Free energy principle; Personality psychology; Computer science; Formalism (music); Personality; Epistemology; Artificial intelligence; Cognitive science; Management science; Psychology; Philosophy; Machine learning; Social psychology; Engineering","score_opus":0.09755421479925765,"score_gpt":0.30449850147733254,"score_spread":0.2069442866780749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388693539","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035237586,0.005658324,0.054360505,0.011001603,0.0008417288,0.0011367563,0.00048941164,0.00014115364,0.92284673],"genre_scores_gemma":[0.9775614,0.010259563,0.0016214009,0.004168838,0.00015010263,0.0000539059,0.000049415183,0.000019202891,0.0061161695],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99920255,0.0000623253,0.00025051754,0.00015246515,0.00017585892,0.00015625598],"domain_scores_gemma":[0.9982747,0.0008986414,0.00015256651,0.00051558024,0.000079465,0.00007903653],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007451137,0.00016966842,0.00018721171,0.00026020122,0.0012699154,0.0006014357,0.00045572128,0.000062953135,0.000015959165],"category_scores_gemma":[0.000031411113,0.00010696059,0.000016238691,0.00006124434,0.0043139383,0.0009529178,0.0006976786,0.00034281393,0.00000131325],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027662147,0.0000025571885,0.000018548668,0.000046632278,0.000008753779,4.093575e-8,0.08714215,9.924507e-7,1.2218585e-8,0.89206797,0.000033943557,0.020650713],"study_design_scores_gemma":[0.0007518355,0.00013687435,0.0006830478,0.0008295536,0.000020853087,0.000018458111,0.029356942,0.010668795,4.4603703e-7,0.8808645,0.07634706,0.0003216239],"about_ca_topic_score_codex":0.00015654015,"about_ca_topic_score_gemma":0.00067883194,"teacher_disagreement_score":0.97403765,"about_ca_system_score_codex":0.000050303115,"about_ca_system_score_gemma":0.00015510821,"threshold_uncertainty_score":0.99839574},"labels":[],"label_agreement":null},{"id":"W4388693584","doi":"10.1007/978-3-031-47958-8_7","title":"On Embedded Normativity an Active Inference Account of Agency Beyond Flesh","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Flesh; Agency (philosophy); Inference; Epistemology; Computer science; Philosophy; Biology; Horticulture","score_opus":0.09346781037970876,"score_gpt":0.34637138354413594,"score_spread":0.2529035731644272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388693584","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002121106,0.000011127541,0.0035686912,0.0001469124,0.00030524476,0.00047720346,0.0001691252,0.00011211551,0.9930885],"genre_scores_gemma":[0.9936174,0.0020549798,0.0025905564,0.0010081409,0.000025119698,0.000035792025,0.000111758505,0.000014248358,0.00054199016],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982291,0.00006427786,0.0006304984,0.00028883957,0.00057634426,0.00021092816],"domain_scores_gemma":[0.9970101,0.00069099956,0.000486459,0.001392988,0.00032760104,0.00009186308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068041706,0.00021373166,0.0002535154,0.0010321499,0.0004383668,0.00019374887,0.0015846404,0.00012749873,0.000020100453],"category_scores_gemma":[0.0003439209,0.0002103831,0.00004315748,0.0004926657,0.0011624575,0.005961265,0.0009095986,0.00050333556,0.00014858914],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010474453,0.000031939002,0.0000025498005,0.000025342264,0.0000013591659,2.8211917e-7,0.0036827058,0.00020817695,0.000064764274,0.83980227,0.000028997963,0.15614112],"study_design_scores_gemma":[0.00062078645,0.00032582207,0.00095150096,0.00057987793,0.000015480846,0.000013120525,0.00018859148,0.17271447,0.0019377072,0.81934506,0.002629688,0.00067790446],"about_ca_topic_score_codex":0.000008018378,"about_ca_topic_score_gemma":0.000013172218,"teacher_disagreement_score":0.9925465,"about_ca_system_score_codex":0.00009274099,"about_ca_system_score_gemma":0.00023356735,"threshold_uncertainty_score":0.8579174},"labels":[],"label_agreement":null},{"id":"W4388694426","doi":"10.1007/978-3-031-47958-8_9","title":"Designing Explainable Artificial Intelligence with Active Inference: A Framework for Transparent Introspection and Decision-Making","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; HEC Montréal","funders":"","keywords":"Introspection; Computer science; Inference; Artificial intelligence; Covert; Machine learning; Cognitive science; Psychology","score_opus":0.10643249706039275,"score_gpt":0.364949812949029,"score_spread":0.25851731588863625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388694426","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000106157815,0.00008279967,0.9946224,0.0003605007,0.00026526817,0.0007833878,0.000010335321,0.00014880874,0.003620322],"genre_scores_gemma":[0.1730718,0.0011640298,0.82528895,0.00019094284,0.000044861965,0.00016281675,0.000011686504,0.00001670012,0.000048220583],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997782,0.000026300535,0.0007941258,0.00050639646,0.00050159934,0.00038957485],"domain_scores_gemma":[0.99527735,0.002258,0.00039800946,0.0013388612,0.00061421975,0.00011357677],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012763735,0.0002917181,0.00032406766,0.0011711972,0.0010880496,0.001246446,0.0021124335,0.00017915624,0.000004207164],"category_scores_gemma":[0.00032711655,0.0002812919,0.000041267347,0.0009257035,0.0008852325,0.00673065,0.0011063673,0.0005379262,0.000022579785],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014515218,0.00000804847,0.000006022107,0.000020455116,0.000004230347,4.4895427e-7,0.0035674768,0.0022769577,0.0000020755913,0.57615906,0.0000026681012,0.41793802],"study_design_scores_gemma":[0.000036569716,0.00015030056,0.00009205118,0.0008579226,0.0000064776827,0.000009678047,0.00041819422,0.44912812,0.00016012724,0.5483702,0.00049934536,0.00027101955],"about_ca_topic_score_codex":0.000012995903,"about_ca_topic_score_gemma":0.000065919994,"teacher_disagreement_score":0.44685116,"about_ca_system_score_codex":0.00023077788,"about_ca_system_score_gemma":0.00033943148,"threshold_uncertainty_score":0.99996394},"labels":[],"label_agreement":null},{"id":"W4388745381","doi":"10.1007/978-981-99-8296-7_16","title":"Utilizing InfoGAN and PE Header Features for Synthetic Ransomware Image Generation: An Experimental Study","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Ransomware; Computer science; Malware; Header; Artificial intelligence; Executable; Convolutional neural network; Context (archaeology); Data mining; Machine learning; Computer security; Operating system","score_opus":0.07899061533469427,"score_gpt":0.35825133827222505,"score_spread":0.2792607229375308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388745381","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006519118,0.00034519262,0.9870015,0.0005838617,0.00042061092,0.001974008,0.000024976616,0.00065454305,0.008343435],"genre_scores_gemma":[0.23975973,0.00087414234,0.75671566,0.00082252146,0.00010953191,0.0005223729,0.00009253559,0.000038654372,0.0010648516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984434,0.000039685394,0.00054520933,0.00040957556,0.00035054077,0.00021159214],"domain_scores_gemma":[0.9974133,0.00017207279,0.00023169747,0.0017122655,0.00036679505,0.00010388241],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008530422,0.00024284088,0.00024329378,0.00088007556,0.00084590964,0.00093953195,0.0017965559,0.000103800005,0.0000020175414],"category_scores_gemma":[0.000049036007,0.00025230658,0.000034802335,0.0003233045,0.00056987844,0.008537601,0.0015626107,0.00029327368,0.0000060759953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014143668,0.0001611894,0.000023538243,0.00007661884,0.000015668686,0.000001725842,0.024957653,0.00021551258,0.0004041782,0.58022225,0.0004332545,0.39347428],"study_design_scores_gemma":[0.0025120312,0.0024932916,0.0014616487,0.00049443264,0.0000349727,0.0002113752,0.003153022,0.8879702,0.0043681446,0.017176015,0.077896036,0.0022287988],"about_ca_topic_score_codex":0.000008464267,"about_ca_topic_score_gemma":0.000025949934,"teacher_disagreement_score":0.88775474,"about_ca_system_score_codex":0.00010477669,"about_ca_system_score_gemma":0.00011619135,"threshold_uncertainty_score":0.9999929},"labels":[],"label_agreement":null},{"id":"W4388967086","doi":"10.1007/978-981-99-8104-5_11","title":"Long-Term Blockchain Transactions Spanning Multiplicity of Smart Contract Methods","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University; Dalhousie University","funders":"","keywords":"Blockchain; Smart contract; Database transaction; Computer science; Distributed transaction; Atomicity; Term (time); Scope (computer science); Computer security; Transaction processing; Database; Programming language","score_opus":0.04601045040134573,"score_gpt":0.3332421278213875,"score_spread":0.2872316774200418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388967086","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032436143,0.00025720254,0.98658526,0.00084604695,0.00019951462,0.00050010724,0.000021641661,0.00026667697,0.010999186],"genre_scores_gemma":[0.32986417,0.0032090289,0.6652031,0.00043221,0.000021197802,0.00014447754,0.0000324759,0.0000232215,0.0010700986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979939,0.000060897684,0.00095784664,0.00036837606,0.00034180764,0.00027716224],"domain_scores_gemma":[0.9955582,0.00059388526,0.0005313798,0.0027555285,0.0004601862,0.00010082757],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021787838,0.0002479683,0.0004004944,0.0014469821,0.0005593046,0.00018970309,0.0038055652,0.00028311048,0.000007353929],"category_scores_gemma":[0.000054722463,0.00026284595,0.000089850764,0.0009410992,0.0013850001,0.0015496037,0.0012086424,0.00073624763,0.000024026767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016127766,0.000029020788,0.0001155897,0.00003785749,0.00001244668,3.2095275e-7,0.001209028,0.00019026412,0.000020118878,0.5151657,0.000008852868,0.48320922],"study_design_scores_gemma":[0.000411002,0.00007239079,0.005590366,0.00028239464,0.000017349503,0.000034893303,0.00001890567,0.97060955,0.00029975115,0.01752612,0.004699335,0.0004379449],"about_ca_topic_score_codex":0.00003243594,"about_ca_topic_score_gemma":0.000039322895,"teacher_disagreement_score":0.9704193,"about_ca_system_score_codex":0.00009411724,"about_ca_system_score_gemma":0.00023212809,"threshold_uncertainty_score":0.99998236},"labels":[],"label_agreement":null},{"id":"W4388998814","doi":"10.1007/978-981-99-8132-8_32","title":"Federated Learning Using the Particle Swarm Optimization Model for the Early Detection of COVID-19","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brandon University","funders":"","keywords":"Computer science; Particle swarm optimization; Coronavirus disease 2019 (COVID-19); Process (computing); Convergence (economics); Artificial intelligence; Federated learning; Machine learning; Data mining","score_opus":0.1533684044276493,"score_gpt":0.3783115203668231,"score_spread":0.2249431159391738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388998814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005003346,0.00009616881,0.9917653,0.0064445822,0.000079969686,0.0007261332,0.0000064250275,0.000055521443,0.00032556927],"genre_scores_gemma":[0.95067143,0.002815692,0.0364129,0.008584398,0.000056035737,0.00013873207,0.00006915639,0.000032427524,0.0012191974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990299,0.000027878441,0.00044458732,0.000117642616,0.0002635127,0.00011651939],"domain_scores_gemma":[0.99761194,0.0009888306,0.00030733045,0.0005807995,0.00045730307,0.000053817344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013497991,0.0001000029,0.00014412816,0.0002226213,0.001050936,0.00018574596,0.00040820526,0.00007095016,0.0000015336367],"category_scores_gemma":[0.00049344666,0.00007183684,0.000041941617,0.0003953618,0.0006085832,0.00081825326,0.00037294687,0.00026487894,0.000002150191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014718475,0.000007651925,0.000036104855,0.000051765255,0.00000869032,2.9622786e-8,0.0028316749,0.9786901,0.000029651415,0.0046571614,0.000034595872,0.0136378715],"study_design_scores_gemma":[0.00031791136,0.000043762928,0.00013195933,0.00010996633,0.000035686564,0.0000043368104,0.00008376522,0.9933898,0.000044092318,0.00027687656,0.0054902267,0.00007162655],"about_ca_topic_score_codex":0.00008142338,"about_ca_topic_score_gemma":0.000025777232,"teacher_disagreement_score":0.9553524,"about_ca_system_score_codex":0.00019815323,"about_ca_system_score_gemma":0.0005140314,"threshold_uncertainty_score":0.8083057},"labels":[],"label_agreement":null},{"id":"W4388999256","doi":"10.1007/978-981-99-8141-0_10","title":"LDW-RS Loss: Label Density-Weighted Loss with Ranking Similarity Regularization for Imbalanced Deep Fetal Brain Age Regression","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Regression; Similarity (geometry); Artificial intelligence; Ranking (information retrieval); Regularization (linguistics); Pattern recognition (psychology); Computer science; Machine learning; Mathematics; Statistics","score_opus":0.03795491185278576,"score_gpt":0.29141419559120224,"score_spread":0.2534592837384165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388999256","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014172777,0.000072386116,0.97731626,0.0021100757,0.0002804586,0.00074452074,0.000010649639,0.00027912104,0.0190448],"genre_scores_gemma":[0.06403749,0.0012919264,0.9220009,0.0036987048,0.0001119643,0.00013926442,0.000857905,0.00006211285,0.007799753],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764216,0.00008244243,0.0007666947,0.0004920482,0.0006459191,0.00037074156],"domain_scores_gemma":[0.99613017,0.00059468014,0.0006368917,0.0017916395,0.00070650474,0.00014013781],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018131392,0.00032969768,0.00037719266,0.0010410215,0.0011650831,0.0010281258,0.002535809,0.00021087193,0.000003604508],"category_scores_gemma":[0.0001451301,0.0003012137,0.000061682535,0.0009510584,0.0009010985,0.0052642575,0.0014510453,0.0005435986,0.000025688387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028647584,0.00002860801,0.0001654931,0.000082639686,0.000017899003,0.000004720666,0.003807431,0.0011985403,0.000019293135,0.7873126,0.00019204979,0.20714204],"study_design_scores_gemma":[0.0012909515,0.00010013378,0.0018110108,0.00050729024,0.00001077961,0.000037620168,0.00004236751,0.9455783,0.000020318812,0.022550397,0.027572628,0.00047819628],"about_ca_topic_score_codex":0.000005846679,"about_ca_topic_score_gemma":0.000033120028,"teacher_disagreement_score":0.94437975,"about_ca_system_score_codex":0.00017531664,"about_ca_system_score_gemma":0.00028824457,"threshold_uncertainty_score":0.999944},"labels":[],"label_agreement":null},{"id":"W4389000655","doi":"10.1007/978-981-99-8132-8_31","title":"PSO-Enabled Federated Learning for Detecting Ships in Supply Chain Management","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brandon University","funders":"","keywords":"Supply chain; Scalability; Particle swarm optimization; Computer science; Supply chain management; Robustness (evolution); Software deployment; Swarm behaviour; Risk analysis (engineering); Process management; Operations research; Business; Artificial intelligence; Database; Engineering; Machine learning","score_opus":0.042111714297225065,"score_gpt":0.2705371098098316,"score_spread":0.22842539551260652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389000655","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008156748,0.00017680142,0.9014848,0.002794061,0.00066497945,0.0014914357,0.000009665679,0.00046345126,0.09209915],"genre_scores_gemma":[0.614891,0.0073257987,0.35244644,0.0020618844,0.00014926957,0.0003953198,0.0003463338,0.00007343028,0.022310516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983699,0.00002729588,0.0006560323,0.00030316185,0.00033960052,0.0003040357],"domain_scores_gemma":[0.99838054,0.00025547203,0.00023968812,0.00076455664,0.0002939974,0.000065716624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015583279,0.00019496014,0.00021165342,0.0013433455,0.00079012266,0.0007395513,0.0020142014,0.00009659507,0.0000026981834],"category_scores_gemma":[0.000066678425,0.00020574752,0.000030865933,0.0010563819,0.00020949903,0.004259184,0.0019679484,0.00040292513,0.00006216923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059605463,0.000018090319,0.0006899127,0.00015461659,0.000010006034,0.0000011244091,0.002624104,0.008449517,0.000004385022,0.68293566,0.00017881695,0.30492783],"study_design_scores_gemma":[0.00044071302,0.0000490141,0.004908612,0.00032077124,0.0000028331935,0.000007901127,0.00005061478,0.9574322,0.000016357544,0.009453138,0.027007503,0.00031033563],"about_ca_topic_score_codex":0.000011077998,"about_ca_topic_score_gemma":0.000032136806,"teacher_disagreement_score":0.9489827,"about_ca_system_score_codex":0.00016730254,"about_ca_system_score_gemma":0.00016287781,"threshold_uncertainty_score":0.83901405},"labels":[],"label_agreement":null},{"id":"W4389010731","doi":"10.1007/978-981-99-8145-8_15","title":"Traffic Accident Forecasting Based on a GrDBN-GPR Model with Integrated Road Features","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Support vector machine; Benchmark (surveying); Feature (linguistics); Kriging; Artificial intelligence; Key (lock); Machine learning; Data mining; Ground-penetrating radar; Stability (learning theory); Gaussian process; Gaussian; Radar; Geography; Computer security","score_opus":0.03953975423910483,"score_gpt":0.24536697715694045,"score_spread":0.20582722291783562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389010731","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003230498,0.00032853294,0.35906574,0.00088432763,0.00073576026,0.0015347346,0.00011557331,0.0019522416,0.6321526],"genre_scores_gemma":[0.93764794,0.0011303063,0.05809968,0.00047597414,0.000037172038,0.00006291904,0.00033639616,0.000051449784,0.0021581636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896246,0.000008462677,0.0003838919,0.00014685553,0.00030922395,0.00018911995],"domain_scores_gemma":[0.9987513,0.00010623092,0.00009294726,0.0008338976,0.00014531605,0.000070323935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037249428,0.00021751344,0.0001919647,0.00075108244,0.0002833138,0.00020012488,0.00088396796,0.000114859526,0.0000029337543],"category_scores_gemma":[0.000013658117,0.00018014165,0.0000328823,0.00035868556,0.00030733162,0.0011691342,0.00019926873,0.0005263851,0.00002371469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044227436,0.0000041141566,0.0000038708054,0.000018370609,0.0000039155316,2.950761e-7,0.0007568127,0.8051885,1.4088424e-7,0.0065032477,0.0002615505,0.18725479],"study_design_scores_gemma":[0.0002306524,0.00003484943,0.0009897411,0.00040912224,0.0000057181733,0.00000676167,0.00003713857,0.99442905,9.793788e-7,0.00009556842,0.003545905,0.00021451664],"about_ca_topic_score_codex":0.000003606718,"about_ca_topic_score_gemma":0.000047344256,"teacher_disagreement_score":0.9344174,"about_ca_system_score_codex":0.00013665712,"about_ca_system_score_gemma":0.00015674163,"threshold_uncertainty_score":0.7345963},"labels":[],"label_agreement":null},{"id":"W4389011106","doi":"10.1007/978-981-99-8181-6_4","title":"LSiF: Log-Gabor Empowered Siamese Federated Learning for Efficient Obscene Image Classification in the Era of Industry 5.0","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brandon University","funders":"","keywords":"Computer science; Robustness (evolution); Overhead (engineering); Multimedia; Artificial intelligence; Machine learning; Operating system","score_opus":0.05396469271284767,"score_gpt":0.33077059476695825,"score_spread":0.2768059020541106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389011106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039119928,0.00007752877,0.98428535,0.001679684,0.00019159145,0.001058322,0.000014029197,0.0002256849,0.012076588],"genre_scores_gemma":[0.60656154,0.001549694,0.38951802,0.0008646928,0.00004591492,0.00044926323,0.0001543685,0.000034560013,0.0008219386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980409,0.00008291815,0.00088604284,0.00030874697,0.00044434235,0.00023704903],"domain_scores_gemma":[0.9965577,0.00063763914,0.0006272359,0.001462038,0.0006674327,0.000047932605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020560834,0.00020581663,0.00025900552,0.000924296,0.00047852396,0.00043481632,0.0027983547,0.00024322206,0.0000016971279],"category_scores_gemma":[0.00028006922,0.00018454535,0.000051827614,0.0011206914,0.0006744083,0.00249936,0.001024905,0.0011833477,0.000009989518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013979457,0.00006963271,0.000057948488,0.00008480091,0.000007649224,7.246499e-7,0.0058857063,0.0049375435,0.00019022576,0.5808748,0.00024239856,0.40763456],"study_design_scores_gemma":[0.00044257648,0.0001486474,0.004292336,0.00036576774,0.000004708204,0.00001409734,0.0002702107,0.9645969,0.00026388533,0.006565494,0.02269251,0.00034280913],"about_ca_topic_score_codex":0.000012354414,"about_ca_topic_score_gemma":0.000011968103,"teacher_disagreement_score":0.9596594,"about_ca_system_score_codex":0.00015888074,"about_ca_system_score_gemma":0.00028104516,"threshold_uncertainty_score":0.7525541},"labels":[],"label_agreement":null},{"id":"W4389011186","doi":"10.1007/978-981-99-8181-6_1","title":"Road Meteorological State Recognition in Extreme Weather Based on an Improved Mask-RCNN","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Chromatin structure remodeling (RSC) complex; Cascade; Christian ministry; Artificial intelligence; Deep learning; Real-time computing; Environmental science; Engineering","score_opus":0.06442751623945028,"score_gpt":0.26256044083463753,"score_spread":0.19813292459518725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389011186","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023860482,0.00026573375,0.21724369,0.0007169692,0.0038024513,0.0028375871,0.00024041208,0.0016497936,0.7493829],"genre_scores_gemma":[0.9310835,0.0023739226,0.06392046,0.0009822646,0.00014153909,0.00015200207,0.0004369846,0.00006251916,0.0008468133],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901885,0.000018651586,0.00042670275,0.00014901577,0.0001820836,0.00020469226],"domain_scores_gemma":[0.9989615,0.000075759905,0.00007939211,0.0007293861,0.00009960071,0.000054345448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006371829,0.00017275751,0.00017005955,0.00079710427,0.00011648573,0.00015190065,0.000630572,0.000114432034,0.000009857908],"category_scores_gemma":[0.000022965387,0.0001631902,0.000024944771,0.00023537033,0.00020940822,0.0015953603,0.00018746259,0.0004462051,0.00003794075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000138784535,0.000012248875,0.000072586845,0.000041072828,0.000004585465,0.0000011429711,0.0015643862,0.033583205,0.00005828285,0.004580961,0.000041533538,0.96002614],"study_design_scores_gemma":[0.00027624698,0.00006751491,0.0043036975,0.00019330527,0.0000025515455,0.0000018971548,0.000026030079,0.9861632,0.000026529326,0.0040256,0.004680271,0.00023316829],"about_ca_topic_score_codex":0.000012782398,"about_ca_topic_score_gemma":0.000034660283,"teacher_disagreement_score":0.959793,"about_ca_system_score_codex":0.00014879875,"about_ca_system_score_gemma":0.000050621016,"threshold_uncertainty_score":0.6654703},"labels":[],"label_agreement":null},{"id":"W4389252023","doi":"10.1007/978-3-031-49263-1_4","title":"A Public-Key System Based on Primes and Addition","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BP (Canada); University of New Brunswick","funders":"","keywords":"Plaintext; Encryption; Integer (computer science); Key (lock); Set (abstract data type); Computer science; Construct (python library); Matrix (chemical analysis); Public-key cryptography; Theoretical computer science; Discrete mathematics; Mathematics; Algorithm; Computer security; Computer network; Programming language","score_opus":0.06476485525147908,"score_gpt":0.2698688879290397,"score_spread":0.2051040326775606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389252023","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022263146,0.00008449191,0.781293,0.0032089374,0.0004155263,0.0006130984,0.000047925114,0.00051789836,0.21379688],"genre_scores_gemma":[0.4207919,0.002596296,0.56431574,0.007092702,0.0002594942,0.00039050847,0.00094399625,0.00009046982,0.0035188948],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99805063,0.000059334598,0.0006102524,0.00037547943,0.00065434905,0.00024993307],"domain_scores_gemma":[0.9965975,0.00046627666,0.0003616601,0.0019852868,0.00044466648,0.00014460801],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015041578,0.0002453053,0.000239338,0.0017830642,0.00056619145,0.0012049717,0.0022125181,0.00013108319,0.0000047668314],"category_scores_gemma":[0.00009047814,0.00024736786,0.000042872787,0.0006822283,0.0006681821,0.006627791,0.0014918975,0.0004094535,0.00014458003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002310235,0.00001114477,0.0000062045797,0.000059571143,0.0000026767016,6.896191e-7,0.00037485934,0.0003304905,0.0000036583456,0.88294536,0.00039744773,0.115865566],"study_design_scores_gemma":[0.00031107725,0.00008945852,0.0007254883,0.000500249,0.0000037897303,0.000016131851,0.000015175582,0.9628249,0.000011291306,0.0035387913,0.03168408,0.00027958344],"about_ca_topic_score_codex":0.000009697927,"about_ca_topic_score_gemma":0.0000056726667,"teacher_disagreement_score":0.9624944,"about_ca_system_score_codex":0.0002873324,"about_ca_system_score_gemma":0.00040453268,"threshold_uncertainty_score":0.99999785},"labels":[],"label_agreement":null},{"id":"W4389565321","doi":"10.1007/978-3-031-49215-0_16","title":"End-To-End Intelligent Automation Loops","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Process (computing); Automation; Perception; Action (physics); Cognition; Human–computer interaction; End user; End-to-end principle; Knowledge management; Artificial intelligence; Process management; Engineering; World Wide Web; Psychology; Neuroscience","score_opus":0.08849029319986937,"score_gpt":0.39339713633428486,"score_spread":0.3049068431344155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389565321","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014573456,0.0000625997,0.074327685,0.0027387918,0.002087616,0.00067966053,0.000071117276,0.00039236943,0.91949445],"genre_scores_gemma":[0.43864217,0.0047404077,0.074977286,0.02121331,0.0008069895,0.0009826084,0.002460604,0.00021069575,0.45596594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99792296,0.0000550371,0.0010195904,0.0002890271,0.000464939,0.00024845047],"domain_scores_gemma":[0.9970818,0.00032356498,0.00037127917,0.0016436586,0.00042581503,0.00015384752],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012411096,0.00022739371,0.00024937204,0.001974435,0.00046407725,0.0003604938,0.0013762284,0.00016910747,0.0012905572],"category_scores_gemma":[0.00007358822,0.00023980472,0.00006232089,0.00054101215,0.0005292792,0.0021971965,0.0008949054,0.00048824397,0.0067551453],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004983739,0.000016910402,0.000017660386,0.000012696411,0.00001124747,4.004858e-7,0.0074072527,0.00014897253,0.0000016108096,0.7063894,0.0047269156,0.2812619],"study_design_scores_gemma":[0.0002525676,0.00007074597,0.008265448,0.00021788843,0.000009765074,0.00002760975,0.0002964723,0.049067996,0.000006679648,0.005003615,0.93640345,0.00037777165],"about_ca_topic_score_codex":0.000026004345,"about_ca_topic_score_gemma":0.000054415712,"teacher_disagreement_score":0.9316765,"about_ca_system_score_codex":0.00023217719,"about_ca_system_score_gemma":0.00015369848,"threshold_uncertainty_score":0.9996224},"labels":[],"label_agreement":null},{"id":"W4389565353","doi":"10.1007/978-3-031-49215-0_1","title":"Features of Persuasive AI in the Workplace","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Persuasive technology; Computer science; Vignette; Process (computing); Human–computer interaction; Context (archaeology); Component (thermodynamics); Knowledge management; Psychology; Persuasion; Social psychology","score_opus":0.03824944677507944,"score_gpt":0.3214775571517836,"score_spread":0.28322811037670415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389565353","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000093153874,0.00042619245,0.1489788,0.02393677,0.00098353,0.00097588927,0.00002127886,0.00015222482,0.82443213],"genre_scores_gemma":[0.504259,0.01688951,0.4163692,0.03646867,0.0002961134,0.00046542828,0.0002548219,0.00008554585,0.024911728],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850535,0.000051199866,0.0005827731,0.00019797265,0.00048624858,0.00017648074],"domain_scores_gemma":[0.9963049,0.00074061414,0.0003082001,0.0022497894,0.00036040452,0.000036035293],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0012173492,0.0001541563,0.00018910914,0.0010973074,0.00025821305,0.00041198145,0.0057232287,0.00009807513,0.0000030158824],"category_scores_gemma":[0.00006677238,0.00012736593,0.00004489438,0.0009896929,0.0006359056,0.005090589,0.0021714482,0.0006749172,0.000054958466],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014161129,0.000012869192,0.000025329697,0.0000194223,0.000003340534,5.1477025e-7,0.011038304,0.0002494853,0.0000013264352,0.9151171,0.0011930095,0.072337925],"study_design_scores_gemma":[0.00088936894,0.00022329671,0.045833144,0.0018713059,0.000020654024,0.00018670014,0.002024869,0.50907296,0.000027384607,0.11833335,0.3204063,0.0011106718],"about_ca_topic_score_codex":0.00005049195,"about_ca_topic_score_gemma":0.00012502828,"teacher_disagreement_score":0.79952043,"about_ca_system_score_codex":0.00009372816,"about_ca_system_score_gemma":0.00023609983,"threshold_uncertainty_score":0.99965626},"labels":[],"label_agreement":null},{"id":"W4389565381","doi":"10.1007/978-3-031-49215-0_48","title":"A Follow-Up to an Age-Friendly Protocol to Support Investigations of Autonomous Driving Disengagement on Driver Safety: Results and Recommendations","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Bruyère; Carleton University","funders":"","keywords":"Disengagement theory; Surprise; Applied psychology; Driving simulator; Protocol (science); Psychology; Situation awareness; Simulation; Computer science; Medicine; Engineering; Gerontology; Social psychology","score_opus":0.12916741421072092,"score_gpt":0.43261813297413726,"score_spread":0.30345071876341634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389565381","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005740282,0.000009264551,0.04456907,0.06852176,0.0031942902,0.20632567,0.0019626624,0.0012093068,0.6684677],"genre_scores_gemma":[0.22448559,0.0013871084,0.4791224,0.024330381,0.0005903351,0.15708612,0.0032238269,0.0003418987,0.10943234],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970856,0.00017893416,0.0015457335,0.00039662232,0.00044364878,0.00034951445],"domain_scores_gemma":[0.9957744,0.001011174,0.0005616276,0.001763776,0.00059832714,0.00029071505],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0024607559,0.0002656829,0.00038519612,0.0015053917,0.0020343878,0.00011589611,0.0011383716,0.00012492696,0.000016974609],"category_scores_gemma":[0.0007546761,0.00026303745,0.000035247005,0.00064539723,0.0005774743,0.001748311,0.0029503212,0.0006770972,0.000144519],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009660663,0.00014002032,0.0049437024,0.000616929,0.000076083685,0.0000016054654,0.24388286,0.0011972542,0.000019848398,0.42437586,0.037336733,0.2873125],"study_design_scores_gemma":[0.002386559,0.0011061176,0.109294124,0.0043296223,0.000033822635,0.000002035461,0.0025222367,0.0100716185,0.0000069988687,0.003687135,0.86577773,0.00078199466],"about_ca_topic_score_codex":0.000059134953,"about_ca_topic_score_gemma":0.0014311302,"teacher_disagreement_score":0.828441,"about_ca_system_score_codex":0.00031195683,"about_ca_system_score_gemma":0.0005098637,"threshold_uncertainty_score":0.9999822},"labels":[],"label_agreement":null},{"id":"W4389565405","doi":"10.1007/978-3-031-49215-0_20","title":"The Dynamics of Collaborative Decision-Making with Intelligent Systems","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Intelligent decision support system; Point (geometry); Artificial intelligence; Knowledge management; Data science; Decision support system; Management science; Engineering","score_opus":0.058436393814531945,"score_gpt":0.31267248186533425,"score_spread":0.25423608805080233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389565405","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028835636,0.001164873,0.518159,0.0015667555,0.0018604344,0.0015358946,0.00009661031,0.00015441973,0.47517365],"genre_scores_gemma":[0.9415754,0.020937292,0.027666584,0.0015238809,0.00056376884,0.00020178204,0.0007338664,0.000101449055,0.00669596],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986803,0.0000049608807,0.0005877829,0.00014315337,0.00044135356,0.00014245762],"domain_scores_gemma":[0.9966694,0.00047966436,0.00058465917,0.0010856967,0.0011718156,0.000008756234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009883125,0.00014948747,0.00018469176,0.00067328656,0.0005756925,0.00095798157,0.0018018746,0.00006521012,0.0000046875866],"category_scores_gemma":[0.0001202121,0.00010141289,0.000019095272,0.0009901028,0.0011608718,0.0042228536,0.0015425532,0.00021501191,0.00006425902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008337318,0.0000038968865,0.00008029223,0.00004870064,0.0000049507516,1.3134336e-7,0.00010738391,0.0010034471,4.3222865e-8,0.7913094,0.00022457108,0.20720884],"study_design_scores_gemma":[0.00008131202,0.000013563754,0.00058378885,0.0014883751,0.000014263384,0.0000053173685,0.0004255453,0.7880062,4.5354295e-7,0.012974597,0.19618165,0.00022495406],"about_ca_topic_score_codex":0.000037330898,"about_ca_topic_score_gemma":0.00023786986,"teacher_disagreement_score":0.94128704,"about_ca_system_score_codex":0.000070118054,"about_ca_system_score_gemma":0.00013769748,"threshold_uncertainty_score":0.92378384},"labels":[],"label_agreement":null},{"id":"W4389733846","doi":"10.1007/978-3-031-49662-2","title":"Operations Research and Enterprise Systems","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence","funders":"Université de Technologie de Troyes; Ministère de la Défense Nationale; Universidad de La Sabana; Universidade Federal Fluminense; Universidade do Minho; RWTH Aachen University; Università di Catania; Kuwait University; Centre National de la Recherche Scientifique; Universiteit Gent; Technische Universität Wien; Sapienza Università di Roma; Hamad Bin Khalifa University; Università di Bologna; Qatar University; Università di Pisa; Università degli Studi dell'Aquila; Technische Universiteit Eindhoven; Universiteit Utrecht; KU Leuven; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; University of Warwick; Università degli Studi di Genova; Coventry University; Khalifa University of Science, Technology and Research; Università degli Studi di Milano; University of Southampton","keywords":"Computer science; Information retrieval","score_opus":0.11302133768466956,"score_gpt":0.3496448705139352,"score_spread":0.23662353282926568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389733846","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007708842,0.0059027146,0.15778762,0.011895681,0.002412128,0.0026500903,0.00006254076,0.0010068055,0.8105736],"genre_scores_gemma":[0.88582695,0.023512868,0.00924149,0.0035826326,0.0018251308,0.00058120297,0.0015784681,0.0001008604,0.073750414],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866635,0.0000125765,0.00046000528,0.00020793326,0.00044633835,0.00020682612],"domain_scores_gemma":[0.99791044,0.00010666323,0.000099937126,0.00083669025,0.0010280495,0.000018230696],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0020298786,0.00012776464,0.00018825494,0.0023839818,0.0010151139,0.0025316377,0.0011003196,0.00008453438,0.0000025522909],"category_scores_gemma":[0.00009718711,0.0001215754,0.000017492319,0.0013913381,0.00083601504,0.007688835,0.002027015,0.00037746312,0.00015684613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008435106,0.0000946229,0.00072427286,0.0011774374,0.000030615865,0.0000012872046,0.0022323276,0.032033376,0.000004331797,0.77010965,0.01365654,0.17992711],"study_design_scores_gemma":[0.00010360242,0.0000036155704,0.0003101017,0.00031532074,0.00000612199,0.0000016486841,0.00014515506,0.9047708,7.656048e-8,0.0032011897,0.09100863,0.00013372317],"about_ca_topic_score_codex":0.00030365918,"about_ca_topic_score_gemma":0.00007546333,"teacher_disagreement_score":0.8781181,"about_ca_system_score_codex":0.00007357967,"about_ca_system_score_gemma":0.00020076563,"threshold_uncertainty_score":0.9985038},"labels":[],"label_agreement":null},{"id":"W4390109863","doi":"10.1007/978-3-031-49425-3","title":"Computer-Human Interaction Research and Applications","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Escuela Politécnica Nacional; Universität Rostock; Universidade Federal Fluminense; Tokyo University of Agriculture; University of Aizu; Universidade de Lisboa; Foundation for Research and Technology-Hellas; Tokyo University of Agriculture and Technology; Daegu University; Universiteit van die Vrystaat; Università degli Studi di Genova; Tokyo City University; Sapienza Università di Roma; Kennesaw State University; LOEWE Zentrum AdRIA; Centre National de la Recherche Scientifique; Korea University; Technische Universiteit Delft; National Chiao Tung University; Universidad del Cauca; University of Wollongong; Shanghai Educational Development Foundation; University of Glasgow; Univerza v Mariboru; Université Bretagne Sud; Indian Institute of Technology Guwahati; Università degli Studi di Milano; Ulsan National Institute of Science and Technology; Utah State University; Northwestern University; Alpen-Adria-Universität Klagenfurt; University of Worcester; Politecnico di Torino; McMaster University; Universitat Politècnica de València; Universität Ulm; Clemson University; North Carolina State University; Aix-Marseille Université","keywords":"Computer science; Information retrieval; Thesaurus; Natural language processing","score_opus":0.17747789766168157,"score_gpt":0.41478472821318446,"score_spread":0.2373068305515029,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390109863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013789814,0.00023765485,0.8831315,0.00141328,0.0006214749,0.0016126243,0.000027781518,0.00046415735,0.11235361],"genre_scores_gemma":[0.496445,0.017365174,0.37574214,0.005700249,0.003522593,0.0069426927,0.0024136992,0.00029621416,0.09157227],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99724966,0.00018593666,0.00084781746,0.00054711086,0.00078840833,0.0003810358],"domain_scores_gemma":[0.9946501,0.0011422288,0.00036756607,0.0025575873,0.0011081707,0.00017432847],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0033231827,0.00023899706,0.000325135,0.0028448675,0.0013611661,0.0019953183,0.0035836475,0.00017731245,0.000002816727],"category_scores_gemma":[0.000045307625,0.00026262458,0.00003915993,0.0020990276,0.0014193304,0.009457861,0.005721722,0.0009766286,0.00026937196],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014571424,0.000054221397,0.00007368551,0.00010443794,0.000010711892,6.481057e-7,0.0023541886,0.000034047764,0.0000074525005,0.2869629,0.004585995,0.70581025],"study_design_scores_gemma":[0.00053258345,0.00020505472,0.0029370107,0.0007066601,0.0000059314193,0.00011340193,0.0001426341,0.3554605,0.000011393103,0.037586197,0.6016635,0.00063515024],"about_ca_topic_score_codex":0.000047277692,"about_ca_topic_score_gemma":0.00006585988,"teacher_disagreement_score":0.7051751,"about_ca_system_score_codex":0.0004384447,"about_ca_system_score_gemma":0.00053178566,"threshold_uncertainty_score":0.9999826},"labels":[],"label_agreement":null},{"id":"W4390121140","doi":"10.1007/978-3-031-50920-9","title":"Advanced Engineering, Technology and Applications","year":2023,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National University of Computer and Emerging Sciences; Dongguan University of Technology; Yarmouk University; VIT University; Istanbul Teknik Üniversitesi; Università di Catania; Imam Khomeini International University; University of New South Wales; Birmingham City University; National Institute of Technology Srinagar; Southeast University; European Space Agency; Wilfrid Laurier University; Università degli Studi di Cagliari; Trường Đại học Hàng hải Việt Nam; Khalifa University of Science, Technology and Research; Université Moulay Ismaïl; İstanbul Medipol Üniversitesi; Ball State University; Manchester Metropolitan University; South China University of Technology; Beni-Suef University","keywords":"Computer science","score_opus":0.030427260266538487,"score_gpt":0.2845159148632539,"score_spread":0.2540886545967154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390121140","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015133152,0.0012313281,0.3168018,0.011887775,0.0016977102,0.005780355,0.00018206022,0.00346799,0.6574377],"genre_scores_gemma":[0.6022369,0.06584749,0.1400184,0.012897023,0.0007329275,0.008002224,0.0006025999,0.00033391497,0.16932848],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988608,0.000019597164,0.00041420327,0.00029022197,0.0002294602,0.0001857562],"domain_scores_gemma":[0.9982417,0.00026575147,0.00020162288,0.0011017267,0.000116759235,0.000072407594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038539484,0.00014859575,0.00015332273,0.0020721855,0.00042280823,0.00022413748,0.0010721543,0.00012589595,0.0000024216795],"category_scores_gemma":[0.00020782219,0.00016121705,0.000017101733,0.0019729969,0.0010573798,0.001872376,0.00087555347,0.00042246617,0.0001080899],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015445065,0.000013081101,0.000013887057,0.000049170543,0.000001129443,1.8300035e-7,0.00029388498,0.00014171192,0.00052291004,0.61393774,0.00039397003,0.38463077],"study_design_scores_gemma":[0.0003048348,0.000040289,0.0010073818,0.00012434975,0.000004800118,0.000054660588,0.000049423295,0.14127575,0.0005075743,0.010508263,0.84578687,0.00033580497],"about_ca_topic_score_codex":6.0883633e-7,"about_ca_topic_score_gemma":0.0000017892949,"teacher_disagreement_score":0.8453929,"about_ca_system_score_codex":0.00013504025,"about_ca_system_score_gemma":0.00019829119,"threshold_uncertainty_score":0.65742403},"labels":[],"label_agreement":null},{"id":"W4390504941","doi":"10.1007/978-3-031-51452-4","title":"Videogame Sciences and Arts","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Educational Games and Gamification","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universidade Federal de Santa Catarina; Universidade de Coimbra; Universidade Federal Fluminense; Simon Fraser University; Queen's University; Universidad Complutense de Madrid; Blekinge Tekniska Högskola; Université de Liège; Aalborg Universitet; Universitat Pompeu Fabra; University of Aizu; University of Waterloo; University of Brighton; Universidade Feevale; Università degli Studi di Milano; Universidad de Alicante; Universidade da Beira Interior; Universitat de les Illes Balears; Jyväskylän Yliopisto; Universidade de Aveiro","keywords":"The arts; Computer science; Library science; Information retrieval; Art; Visual arts","score_opus":0.07890041157366007,"score_gpt":0.3930554661189409,"score_spread":0.3141550545452808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390504941","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005894412,0.005498233,0.0037641157,0.005424464,0.0010660052,0.000386532,0.000025261477,0.000071301365,0.9831746],"genre_scores_gemma":[0.40847966,0.032512225,0.16796818,0.021274518,0.0013965629,0.0009885432,0.0011418498,0.00010865004,0.3661298],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99884707,0.00003052299,0.0004298401,0.00026407506,0.000256894,0.00017158713],"domain_scores_gemma":[0.99855155,0.00026037105,0.00015681132,0.00081280194,0.00014971118,0.00006877712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012051914,0.00013410128,0.00013991157,0.00090785587,0.00033584674,0.0005236925,0.00092275656,0.00009897543,0.00003826537],"category_scores_gemma":[0.000032173186,0.00012618973,0.000020835518,0.0005818631,0.0020864266,0.0019117836,0.0006529781,0.0003133501,0.00026545694],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.810193e-7,0.000014192897,0.00009162844,0.000029092604,0.000004348572,1.10730646e-7,0.0065877466,0.000008770655,6.512111e-7,0.83138776,0.010506495,0.15136823],"study_design_scores_gemma":[0.00010743776,0.000048974613,0.01066628,0.00021344666,0.000009924549,0.00003899442,0.00036532956,0.010946337,6.683432e-7,0.021790981,0.95560586,0.00020578389],"about_ca_topic_score_codex":0.000018480681,"about_ca_topic_score_gemma":0.0000069686425,"teacher_disagreement_score":0.94509935,"about_ca_system_score_codex":0.000097652955,"about_ca_system_score_gemma":0.00043193658,"threshold_uncertainty_score":0.7687526},"labels":[],"label_agreement":null},{"id":"W4390545676","doi":"10.1007/978-981-99-9331-4","title":"Frontiers in Cyber Security","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Computer security; Cryptography; Network security; Quantum cryptography; Quantum; Physics; Quantum information","score_opus":0.016174996168805435,"score_gpt":0.26210571140447286,"score_spread":0.24593071523566742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390545676","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015862474,0.0034411338,0.58719647,0.0025581857,0.0036313068,0.00073217944,0.000013042213,0.00028607802,0.401983],"genre_scores_gemma":[0.09736311,0.04842237,0.8271888,0.009954676,0.00068483077,0.00038825886,0.00029050378,0.000070285074,0.01563719],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823856,0.00006624837,0.0006596426,0.0003389115,0.0004236354,0.00027301916],"domain_scores_gemma":[0.99775827,0.0001069826,0.00016824833,0.0017125176,0.00016606066,0.00008792211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014506663,0.00019572066,0.0002479123,0.0019044937,0.0002587549,0.00095023063,0.003254859,0.00017586036,0.000004194657],"category_scores_gemma":[0.000030943294,0.00020051954,0.000045220415,0.0018181163,0.000594092,0.0084637385,0.003008113,0.0008766803,0.00008848504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028441611,0.000033091997,0.00007190012,0.000087118955,0.0000059167296,0.000001946829,0.0077324742,0.00027690938,5.0854237e-7,0.46073404,0.03147715,0.49957612],"study_design_scores_gemma":[0.00011359965,0.000020930398,0.00019692484,0.00021207126,0.0000017677937,0.000013039499,0.0000134388665,0.5442196,0.0000024779192,0.054773927,0.40025097,0.0001812423],"about_ca_topic_score_codex":0.000020519692,"about_ca_topic_score_gemma":0.000040340463,"teacher_disagreement_score":0.5439427,"about_ca_system_score_codex":0.00040387842,"about_ca_system_score_gemma":0.0005474676,"threshold_uncertainty_score":0.9163096},"labels":[],"label_agreement":null},{"id":"W4390570531","doi":"10.1007/978-981-99-9614-8_10","title":"Adversarial Example Attacks and Defenses in DNS Data Exfiltration","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Adversarial system; Computer security; Network packet; Protocol (science); Phone; The Internet; Voting; Internet privacy; Computer network; World Wide Web; Artificial intelligence","score_opus":0.07848318458146727,"score_gpt":0.30431623907523414,"score_spread":0.22583305449376687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390570531","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00076205493,0.0046874923,0.6423898,0.0035627182,0.0027503266,0.0013792706,0.00008716844,0.00038501635,0.3439962],"genre_scores_gemma":[0.45670125,0.07931144,0.45172933,0.0047441483,0.0008138372,0.0001333289,0.0012724579,0.00007176848,0.0052224505],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983918,0.000032328866,0.0006086076,0.00043157992,0.00034351958,0.00019216389],"domain_scores_gemma":[0.99704874,0.00021962899,0.00017857892,0.0023484197,0.00013015234,0.00007446069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013056664,0.00018381767,0.00019956387,0.0009849351,0.00032225266,0.0009628618,0.0027428558,0.00014439327,0.0000074732925],"category_scores_gemma":[0.000036851623,0.00018890214,0.000019514919,0.0005304036,0.00055089843,0.010151413,0.004821817,0.00051836285,0.00004134857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029846046,0.000009707026,0.000021141386,0.000030234716,0.000003270167,7.118648e-7,0.002118313,0.00011579258,0.0000024450947,0.7279814,0.00037695342,0.26933706],"study_design_scores_gemma":[0.00019248095,0.000042554508,0.00038581406,0.00021663657,0.0000045350207,0.00003187694,0.00001829024,0.64775074,0.000003496483,0.02351729,0.32761687,0.00021944787],"about_ca_topic_score_codex":0.0001032371,"about_ca_topic_score_gemma":0.00028068793,"teacher_disagreement_score":0.7044641,"about_ca_system_score_codex":0.000095788244,"about_ca_system_score_gemma":0.00019325386,"threshold_uncertainty_score":0.92848986},"labels":[],"label_agreement":null},{"id":"W4390735355","doi":"10.1007/978-3-031-48981-5_17","title":"Chatbots Scenarios for Education","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in Service Interactions","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Conversation; Chatbot; Multimedia; World Wide Web; Artificial intelligence; Psychology","score_opus":0.03700198453381071,"score_gpt":0.3286774739321411,"score_spread":0.2916754893983304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390735355","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000124011995,0.0010108247,0.54138744,0.0079024,0.002360176,0.0009775524,0.000027150647,0.0002413592,0.4460807],"genre_scores_gemma":[0.018553577,0.004500147,0.9259844,0.008007379,0.00037662135,0.0006170217,0.00026920153,0.000050177514,0.04164152],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99845576,0.000010259248,0.00063995767,0.00034487495,0.0003295402,0.0002195832],"domain_scores_gemma":[0.99648184,0.00025694404,0.0002570654,0.0022367472,0.00066488865,0.00010251532],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006716098,0.00021854548,0.00019760315,0.0013316585,0.00044223256,0.001203749,0.0036001187,0.00013176881,0.000008057911],"category_scores_gemma":[0.000036165715,0.00022554824,0.000065895496,0.00044818482,0.00040364606,0.008790267,0.0022166318,0.00041896696,0.00023446904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.80321e-7,0.000012193718,0.0000018993401,0.000047001555,0.0000039410506,5.398458e-8,0.0010797903,0.00009368355,0.000001495384,0.80591434,0.001122546,0.19172236],"study_design_scores_gemma":[0.000070604285,0.000029401886,0.00004182573,0.00030347198,0.0000059429867,0.00002352746,0.000023695451,0.38697052,0.0000039513297,0.06368849,0.5486376,0.0002009713],"about_ca_topic_score_codex":0.000014844188,"about_ca_topic_score_gemma":0.000019681163,"teacher_disagreement_score":0.7422259,"about_ca_system_score_codex":0.0002709283,"about_ca_system_score_gemma":0.00083400274,"threshold_uncertainty_score":0.9998331},"labels":[],"label_agreement":null},{"id":"W4390783588","doi":"10.1007/978-3-031-48981-5_5","title":"Android Malware Detection Using Artificial Intelligence","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Malware; Android malware; Artificial intelligence; Machine learning; Android (operating system); Classifier (UML); Decision tree; Computer security; Operating system","score_opus":0.065200141398644,"score_gpt":0.32939593934456624,"score_spread":0.26419579794592224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390783588","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001969512,0.00033973606,0.9617742,0.00027375686,0.00052712765,0.00033346156,0.000008078918,0.000403223,0.03632073],"genre_scores_gemma":[0.1584914,0.0024574853,0.8373692,0.000562359,0.00011594569,0.000057664285,0.000018677683,0.000030414347,0.00089685345],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981372,0.000018912184,0.0007688288,0.00040215979,0.00043236467,0.0002405433],"domain_scores_gemma":[0.9972363,0.000114978735,0.00028467848,0.0018748912,0.00039593966,0.000093175455],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00078314415,0.0002523571,0.00022358357,0.0017126725,0.00048612684,0.0009339818,0.002501626,0.00016665664,0.0000059759222],"category_scores_gemma":[0.0000394883,0.00026903526,0.000056688557,0.00083733245,0.00071714877,0.007856379,0.0027358148,0.00063694,0.00008533514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.385564e-7,0.0000037788304,3.5075914e-7,0.000018350185,0.0000018943134,5.748728e-7,0.00025850013,0.00031856203,0.000018531913,0.5655,0.0000029270682,0.4338756],"study_design_scores_gemma":[0.00002178951,0.000056302364,0.000010893545,0.00020475821,0.0000050806625,0.00009228884,0.000017520273,0.7032023,0.0007953234,0.25956666,0.035722964,0.00030410427],"about_ca_topic_score_codex":0.000012377358,"about_ca_topic_score_gemma":0.000017877306,"teacher_disagreement_score":0.7028838,"about_ca_system_score_codex":0.00034103595,"about_ca_system_score_gemma":0.00019545526,"threshold_uncertainty_score":0.99997616},"labels":[],"label_agreement":null},{"id":"W4391395149","doi":"10.1007/978-3-031-52823-1_5","title":"Intruder Vehicle Detection During a Platoon Joining Maneuver","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Platoon; Computer science; Aeronautics; Automotive engineering; Artificial intelligence; Engineering; Control (management)","score_opus":0.013261784116173575,"score_gpt":0.2245919348384983,"score_spread":0.21133015072232472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391395149","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03536986,0.0026882645,0.0963074,0.0007406336,0.0014163089,0.0008186228,0.00003197283,0.0025010735,0.86012584],"genre_scores_gemma":[0.993923,0.0013433566,0.003770955,0.00008810024,0.000026780104,0.00001764898,0.000012930559,0.000015614538,0.0008016187],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992271,0.0000036560077,0.00037046123,0.00012213556,0.0001286619,0.00014800402],"domain_scores_gemma":[0.9991379,0.00003689975,0.000055247,0.00068151817,0.000052833573,0.000035612517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002561554,0.00014143263,0.00013420565,0.00071194983,0.0003232624,0.00018538933,0.00057974516,0.00017499816,0.000010398892],"category_scores_gemma":[0.000005345563,0.00015304443,0.000024613099,0.00020993958,0.00046465956,0.0018539046,0.0005817247,0.00063379185,0.00011043724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006324283,0.000008029014,0.00006610484,0.00029316478,0.000035575606,0.0000027437704,0.0040432266,0.014250565,0.00030110413,0.47570083,0.00007061367,0.5052217],"study_design_scores_gemma":[0.00015807597,0.000015774362,0.001176363,0.00020948549,0.000008396978,0.000044688084,0.000031666,0.93841547,0.00032848693,0.0063492055,0.05299537,0.00026701667],"about_ca_topic_score_codex":0.0000022039349,"about_ca_topic_score_gemma":0.00001672946,"teacher_disagreement_score":0.95855314,"about_ca_system_score_codex":0.0001761824,"about_ca_system_score_gemma":0.000036427155,"threshold_uncertainty_score":0.6240971},"labels":[],"label_agreement":null},{"id":"W4391407400","doi":"10.1007/978-3-031-53025-8","title":"Optimization, Learning Algorithms and Applications","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Uniwersytet Opolski; Slovenská technická univerzita v Bratislave; Université de Reims Champagne-Ardenne; Kauno Technologijos Universitetas; Instituto Politécnico de Bragança; Universidade de Trás-os-Montes e Alto Douro; Instituto Politécnico do Porto; Universidade do Porto; Università degli Studi di Genova; Hanzehogeschool Groningen; Université de Sherbrooke; Universidade do Minho; Università degli Studi di Parma; Universidad de León; Politechnika Opolska; Universitatea Tehnică „Gheorghe Asachi” din Iaşi; Université de Lorraine","keywords":"Computer science; Artificial intelligence; Machine learning; Information retrieval","score_opus":0.030866000400886245,"score_gpt":0.3185919237356132,"score_spread":0.2877259233347269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391407400","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1628054e-7,0.0012298254,0.8949389,0.0008912397,0.0001554006,0.0005455705,0.000008974013,0.00018326861,0.10204662],"genre_scores_gemma":[0.00013207746,0.011369701,0.9742891,0.00043433195,0.00009104955,0.00022504397,0.00015027907,0.000018741295,0.013289643],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99772435,0.00009319129,0.00073381833,0.00048482095,0.00066418183,0.0002996394],"domain_scores_gemma":[0.9967988,0.00037028428,0.00023414863,0.0017170047,0.0006913249,0.00018842901],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0017600309,0.00024045308,0.00026565307,0.0018461647,0.0006868962,0.0021890202,0.0029673267,0.00014529625,0.000011008132],"category_scores_gemma":[0.00012564956,0.0002459959,0.000031651645,0.0018726353,0.0010475673,0.005799602,0.0043200958,0.0008145468,0.00010029964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.961569e-7,0.000018988274,0.000010791031,0.00011479109,0.000010080957,6.8138166e-7,0.0012566238,0.033310976,2.193836e-7,0.40857685,0.0012534002,0.555446],"study_design_scores_gemma":[0.00010736775,0.000020910878,0.000028371729,0.00007823425,0.000004630969,0.000025523277,0.00001257611,0.7544595,6.993419e-7,0.0033670627,0.24170664,0.00018849366],"about_ca_topic_score_codex":0.000005297549,"about_ca_topic_score_gemma":0.0000011314166,"teacher_disagreement_score":0.7211485,"about_ca_system_score_codex":0.00021601909,"about_ca_system_score_gemma":0.0009312659,"threshold_uncertainty_score":0.9999992},"labels":[],"label_agreement":null},{"id":"W4391407522","doi":"10.1007/978-3-031-53025-8_6","title":"A Pattern Mining Heuristic for the Extension of Multi-trip Vehicle Routing","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Extension (predicate logic); Vehicle routing problem; Computer science; Heuristic; Routing (electronic design automation); Information retrieval; Artificial intelligence; Computer network; Programming language","score_opus":0.06408659692197742,"score_gpt":0.32001787985576213,"score_spread":0.2559312829337847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391407522","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001400677,0.0010152753,0.9882924,0.00015788087,0.00032092212,0.00036901652,0.000021808992,0.00009455596,0.009588102],"genre_scores_gemma":[0.5187801,0.002510863,0.4774317,0.00025539412,0.00006372827,0.00005823963,0.00004936831,0.000042125273,0.00080842647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905515,0.00001187622,0.00053804857,0.00010791699,0.00016308592,0.0001239185],"domain_scores_gemma":[0.99818987,0.0006491365,0.00013147289,0.0007767775,0.0002240225,0.000028713528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012236496,0.00012211892,0.00015567336,0.00034068077,0.0002186258,0.0001524234,0.0007273645,0.000070447626,0.0000023488444],"category_scores_gemma":[0.00009660017,0.000104783554,0.000037379057,0.00021583756,0.00029905638,0.0007085238,0.00045662487,0.00022684078,0.0000055645783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016994841,0.0000066175508,0.000055013956,0.00025973533,0.000017786342,1.3900676e-7,0.005654463,0.22763354,0.000024683975,0.029782685,0.00012021618,0.7364434],"study_design_scores_gemma":[0.0001306104,0.000010428339,0.00031614752,0.00032378995,0.000012640487,0.0000041608205,0.000060731007,0.99222493,0.000014882469,0.0002455822,0.0065485975,0.0001074758],"about_ca_topic_score_codex":0.000003918608,"about_ca_topic_score_gemma":0.0000030302947,"teacher_disagreement_score":0.7645914,"about_ca_system_score_codex":0.000060875424,"about_ca_system_score_gemma":0.000044429842,"threshold_uncertainty_score":0.42729494},"labels":[],"label_agreement":null},{"id":"W4391488220","doi":"10.1007/978-3-031-53036-4","title":"Optimization, Learning Algorithms and Applications","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Uniwersytet Opolski; Slovenská technická univerzita v Bratislave; Université de Reims Champagne-Ardenne; Kauno Technologijos Universitetas; Instituto Politécnico de Bragança; Universidade de Trás-os-Montes e Alto Douro; Instituto Politécnico do Porto; Universidade do Porto; Università degli Studi di Genova; Hanzehogeschool Groningen; Université de Sherbrooke; Universidade do Minho; Università degli Studi di Parma; Universidad de León; Politechnika Opolska; Universitatea Tehnică „Gheorghe Asachi” din Iaşi; Université de Lorraine","keywords":"Computer science; Artificial intelligence; Algorithm","score_opus":0.030866000400886245,"score_gpt":0.3185919237356132,"score_spread":0.2877259233347269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391488220","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1628054e-7,0.0012298254,0.8949389,0.0008912397,0.0001554006,0.0005455705,0.000008974013,0.00018326861,0.10204662],"genre_scores_gemma":[0.00013207746,0.011369701,0.9742891,0.00043433195,0.00009104955,0.00022504397,0.00015027907,0.000018741295,0.013289643],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99772435,0.00009319129,0.00073381833,0.00048482095,0.00066418183,0.0002996394],"domain_scores_gemma":[0.9967988,0.00037028428,0.00023414863,0.0017170047,0.0006913249,0.00018842901],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0017600309,0.00024045308,0.00026565307,0.0018461647,0.0006868962,0.0021890202,0.0029673267,0.00014529625,0.000011008132],"category_scores_gemma":[0.00012564956,0.0002459959,0.000031651645,0.0018726353,0.0010475673,0.005799602,0.0043200958,0.0008145468,0.00010029964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.961569e-7,0.000018988274,0.000010791031,0.00011479109,0.000010080957,6.8138166e-7,0.0012566238,0.033310976,2.193836e-7,0.40857685,0.0012534002,0.555446],"study_design_scores_gemma":[0.00010736775,0.000020910878,0.000028371729,0.00007823425,0.000004630969,0.000025523277,0.00001257611,0.7544595,6.993419e-7,0.0033670627,0.24170664,0.00018849366],"about_ca_topic_score_codex":0.000005297549,"about_ca_topic_score_gemma":0.0000011314166,"teacher_disagreement_score":0.7211485,"about_ca_system_score_codex":0.00021601909,"about_ca_system_score_gemma":0.0009312659,"threshold_uncertainty_score":0.9999992},"labels":[],"label_agreement":null},{"id":"W4391817437","doi":"10.1007/978-3-031-53656-4","title":"Computer Supported Education","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Leibniz-Gemeinschaft; Indiana University Bloomington; Universitat Politècnica de València; Universidad de Valladolid; Wageningen University and Research; Universidad de Zaragoza; Nanyang Technological University; Université Claude Bernard Lyon 1; Universidad de Córdoba; Università di Bologna; Universidade de São Paulo; Jyväskylän Yliopisto; University of Crete; Universität St. Gallen; Universidad de Guadalajara; Universidad de Extremadura; Newcastle University; Università degli Studi di Trento; Le Mans Université; Universiti Tunku Abdul Rahman; Université de Genève; Bulgarian Academy of Sciences; University of Thessaly; Universidade de Vigo; National Institute of Education, Nanyang Technological University; Universität des Saarlandes; Technische Universiteit Delft; University of Michigan-Dearborn; Universidade de Aveiro; Universitat Politècnica de Catalunya; Università degli Studi di Milano; Curtin University of Technology; Universitat de les Illes Balears; Multimedia University; Sunway University; Imperial College London; University of South Australia; Gottfried Wilhelm Leibniz Universität Hannover; Technical University of Sofia; University of Patras; State University of New York; Universidade Feevale; University of West Attica; Silesian University of Technology; Sveučilište u Zagrebu; Athabasca University; Universitas Telkom; University of Warwick; British University in Egypt; University of Maryland, Baltimore County","keywords":"Computer science; Thesaurus; Information retrieval; Artificial intelligence","score_opus":0.04174027915064115,"score_gpt":0.36458606259794607,"score_spread":0.3228457834473049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391817437","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004501003,0.0004224098,0.0016542254,0.002009371,0.0011990791,0.000568877,0.00003221035,0.00016102042,0.99350274],"genre_scores_gemma":[0.39867514,0.011734787,0.122934885,0.012660517,0.0026163708,0.0006795315,0.0028994193,0.0001167481,0.44768262],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982072,0.00006657662,0.0006266157,0.00025561758,0.0005815037,0.00026245127],"domain_scores_gemma":[0.99779046,0.000247895,0.00017839242,0.0011565542,0.0004920576,0.00013466818],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016956812,0.00016443706,0.00019735974,0.0008683105,0.0006143105,0.0018901174,0.0020947314,0.00014261069,0.000039217153],"category_scores_gemma":[0.000111272355,0.0001693895,0.00005497185,0.00086667173,0.0036337392,0.009738294,0.0013451204,0.00037144584,0.00026530982],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.053955e-7,0.000040528274,0.00014593954,0.00008322993,0.0000035374683,5.8523717e-8,0.01402843,0.000008070898,5.936372e-8,0.5894385,0.016099053,0.3801517],"study_design_scores_gemma":[0.000057886802,0.00002056343,0.0009111724,0.00029313954,0.000007506153,0.000002284399,0.00062218285,0.008001381,4.4402202e-7,0.06722184,0.9226328,0.0002287786],"about_ca_topic_score_codex":0.00017421645,"about_ca_topic_score_gemma":0.00027555422,"teacher_disagreement_score":0.9065338,"about_ca_system_score_codex":0.0006959264,"about_ca_system_score_gemma":0.00469956,"threshold_uncertainty_score":0.99914604},"labels":[],"label_agreement":null},{"id":"W4392148527","doi":"10.1007/978-3-031-54303-6_1","title":"Unlocking the Power of Explainability in Ranking Systems: A Visual Analytics Approach with XAI Techniques","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Ranking (information retrieval); Visual analytics; Analytics; Computer science; Data science; Information retrieval; Visualization; Data mining","score_opus":0.04257029119110668,"score_gpt":0.3098513979998137,"score_spread":0.26728110680870704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392148527","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039360454,0.00058456924,0.8630013,0.0004526808,0.0001307864,0.0008474531,0.000003548466,0.000100253164,0.13448581],"genre_scores_gemma":[0.9464093,0.00044506742,0.05261287,0.00016584435,0.000015649643,0.000074328585,0.000007808609,0.00000990177,0.00025924205],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99786323,0.000059196325,0.0009323616,0.00032073839,0.0005756902,0.00024880588],"domain_scores_gemma":[0.99664146,0.00035178039,0.00037104616,0.0020605035,0.000527473,0.00004776825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029687122,0.00021542166,0.00030578743,0.0011826362,0.0003058426,0.0007729179,0.0034051493,0.00010949226,0.0000012705927],"category_scores_gemma":[0.000053557324,0.00015925009,0.000042037274,0.0012958362,0.0012297482,0.004138361,0.002136135,0.00057027815,0.0000053243107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050338826,0.000027491988,0.00008975631,0.00010000298,0.000006756611,7.7170125e-7,0.008280604,0.0033016093,0.0000025411725,0.96400213,0.000013211102,0.02417009],"study_design_scores_gemma":[0.00005855535,0.00010423129,0.00015453406,0.000635618,0.0000064736673,0.00002864174,0.00074142404,0.9763462,0.00007284251,0.013111179,0.008492081,0.00024824226],"about_ca_topic_score_codex":0.00008492871,"about_ca_topic_score_gemma":0.000028214725,"teacher_disagreement_score":0.9730446,"about_ca_system_score_codex":0.00025466242,"about_ca_system_score_gemma":0.00034404927,"threshold_uncertainty_score":0.7453265},"labels":[],"label_agreement":null},{"id":"W4392173314","doi":"10.1007/978-3-031-54321-0","title":"ICT Innovations 2023. Learning: Humans, Theory, Machines, and Data","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universitat Politècnica de València; Serbian Academy of Sciences and Arts; New Bulgarian University; Kauno Technologijos Universitetas; Universität Innsbruck; Masarykova Univerzita; Linnéuniversitetet; Universidad de Zaragoza; Universität Stuttgart; Universidade de Vigo; Centre National de la Recherche Scientifique; Università degli Studi di Pavia; Radboud Universiteit; Université du Luxembourg; Sveučilište u Zagrebu; Silesian University of Technology; Universiteit van Amsterdam; Université de Limoges; Univerza v Ljubljani; University of Wollongong; Instituto de Física Interdisciplinar y Sistemas Complejos; Universidad Politécnica de Madrid; University of Patras; National Academy of Sciences of Armenia; London South Bank University; Institut \"Jožef Stefan\"; University of Tasmania; Institute of Physics Belgrade; Polytechnique Montréal; Chaoyang University of Technology; University of St. Thomas","keywords":"Computer science; Information and Communications Technology; Data science; World Wide Web","score_opus":0.11613589355230361,"score_gpt":0.3520200048187347,"score_spread":0.23588411126643108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392173314","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015374842,0.0035754018,0.040996455,0.0037702199,0.001145327,0.0006772893,0.00015309289,0.00027310944,0.94925535],"genre_scores_gemma":[0.29295215,0.07833433,0.083834,0.05389226,0.009793187,0.00060967705,0.108177245,0.00046927534,0.37193787],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985822,0.000011380815,0.0005578442,0.00034132536,0.0003191823,0.00018811008],"domain_scores_gemma":[0.99726635,0.0001443087,0.00027499523,0.0019302295,0.0003691571,0.000014941651],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0019744625,0.00020721993,0.0001957936,0.0014051193,0.0006717551,0.0022103908,0.0030568284,0.00010341666,0.000053897664],"category_scores_gemma":[0.00021113404,0.00018890834,0.000015348267,0.0014645639,0.001004136,0.013794285,0.007683266,0.0006302935,0.00027878347],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023251405,0.000012943526,0.00025152057,0.00022188749,0.0000068784443,2.8101334e-7,0.00017249996,0.000026064683,7.596399e-7,0.6771231,0.0313126,0.29086912],"study_design_scores_gemma":[0.00006152162,0.0000034607797,0.0011071354,0.0002322708,0.0000172591,0.0000046729137,0.000028155391,0.18992515,1.1573433e-7,0.018579977,0.7898485,0.00019180511],"about_ca_topic_score_codex":0.00006737791,"about_ca_topic_score_gemma":0.00004846298,"teacher_disagreement_score":0.75853586,"about_ca_system_score_codex":0.00004810945,"about_ca_system_score_gemma":0.00021087541,"threshold_uncertainty_score":0.9999993},"labels":[],"label_agreement":null},{"id":"W4392173336","doi":"10.1007/978-3-031-54321-0_6","title":"Disaster-Resilient Messaging Using Dew Computing","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Dew; Computer science; World Wide Web; Physics; Meteorology","score_opus":0.03822010077535391,"score_gpt":0.30419927178543454,"score_spread":0.2659791710100806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392173336","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000072509305,0.0011554193,0.68122226,0.00037167597,0.0008376242,0.00037669804,0.000004490175,0.00018884613,0.31577048],"genre_scores_gemma":[0.40144587,0.002303504,0.5890392,0.0023831164,0.0003200982,0.0000302532,0.0000636442,0.000058865833,0.0043554185],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764955,0.00003156307,0.0008905649,0.00046337198,0.0005871568,0.00037779193],"domain_scores_gemma":[0.9962827,0.00024330943,0.00034075757,0.002660268,0.00032993685,0.00014305761],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012799095,0.00030811352,0.00031287005,0.0010458159,0.00058427785,0.0016146069,0.004248557,0.00013290512,0.0000058445125],"category_scores_gemma":[0.000026772808,0.0003120917,0.00006847741,0.0007127255,0.00078918476,0.004537182,0.0072462563,0.00070044637,0.00009106814],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7474526e-7,0.0000065867534,0.000012045178,0.00004025476,0.000005850005,0.0000010311358,0.0014118167,0.0046641105,0.0000018821924,0.882499,0.0001526136,0.111204326],"study_design_scores_gemma":[0.00010012816,0.000017382614,0.000082728155,0.0005391801,0.0000074340373,0.000033731714,0.000019207448,0.8676025,0.0000030355252,0.012857349,0.118437365,0.00029990575],"about_ca_topic_score_codex":0.000013909707,"about_ca_topic_score_gemma":0.000008895105,"teacher_disagreement_score":0.86964166,"about_ca_system_score_codex":0.00030544735,"about_ca_system_score_gemma":0.00029713823,"threshold_uncertainty_score":0.9999331},"labels":[],"label_agreement":null},{"id":"W4392181195","doi":"10.1007/978-3-031-54303-6_7","title":"Explanations of Symbolic Reasoning to Effect Patient Persuasion and Education","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Empathy and Medical Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Dalhousie University; University of Ottawa","funders":"","keywords":"Persuasion; Computer science; Psychology; Social psychology","score_opus":0.020829572666161925,"score_gpt":0.33025564259760065,"score_spread":0.30942606993143873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392181195","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16821289,0.0065154466,0.0033345353,0.007768955,0.0016608268,0.003175374,0.000045892124,0.00013186758,0.8091542],"genre_scores_gemma":[0.9707585,0.0040642703,0.019967426,0.0016218822,0.00008371408,0.00011326043,0.0002469751,0.000015822216,0.00312813],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990102,0.000013259428,0.00042907122,0.00015644921,0.00029308375,0.00009792443],"domain_scores_gemma":[0.9987201,0.00010557349,0.00012947265,0.0006002631,0.00028746543,0.00015713582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051218056,0.0001205904,0.00020454967,0.0009964779,0.00014175042,0.000067134824,0.00021464424,0.000088370754,0.000009153451],"category_scores_gemma":[0.00017047359,0.000106915635,0.000027553162,0.0002943367,0.00034806074,0.0007542767,0.0003544516,0.00027043276,0.000020852594],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013161165,0.000042342897,0.00010775304,0.00031235936,0.000008637461,1.5713405e-7,0.03585936,0.00000952581,0.000021048332,0.15757781,0.00046946027,0.8055784],"study_design_scores_gemma":[0.0023563714,0.0040944954,0.048297673,0.031561296,0.0005497306,0.000630187,0.0132529475,0.1048902,0.0007373701,0.018560354,0.7733417,0.0017276382],"about_ca_topic_score_codex":0.00002238844,"about_ca_topic_score_gemma":0.0000029852447,"teacher_disagreement_score":0.8060261,"about_ca_system_score_codex":0.000118463984,"about_ca_system_score_gemma":0.00046385365,"threshold_uncertainty_score":0.4359893},"labels":[],"label_agreement":null},{"id":"W4392306974","doi":"10.1007/978-981-97-0827-7_8","title":"A Critical Review of Multi Criteria Decision Analysis Method for Decision Making and Prediction in Big Data Healthcare Applications","year":2024,"lang":"en","type":"review","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Big data; Health care; Data science; Data mining; Operations research; Engineering; Political science","score_opus":0.6335345748561209,"score_gpt":0.6751389515833436,"score_spread":0.041604376727222725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392306974","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[6.6962593e-7,0.5307113,0.46604937,0.00037959695,0.0002527795,0.0020411822,0.0005175413,0.00001945708,0.000028090037],"genre_scores_gemma":[0.0001439977,0.7066405,0.2915438,0.00039464716,0.00004504794,0.00089020864,0.00033260664,0.000008315026,8.539887e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99487853,0.000716522,0.003162739,0.0005337255,0.000370725,0.00033774646],"domain_scores_gemma":[0.9865778,0.008832208,0.00063332135,0.0028209002,0.0010132475,0.00012251624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009007405,0.00022917439,0.0011114554,0.002344753,0.00075730385,0.00009960907,0.0019722353,0.00026519358,0.000007679576],"category_scores_gemma":[0.0034445848,0.00019468003,0.00009885584,0.0052081444,0.00043163644,0.0019438404,0.0029190497,0.00083054544,0.00001540125],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032595945,0.00002013287,0.00012883279,0.048099067,0.000009610738,5.2440445e-8,0.00077770674,0.0000046833547,1.786833e-8,0.0032503894,0.00016954457,0.9475367],"study_design_scores_gemma":[0.000053514505,0.000025451185,0.000194178,0.13384296,0.00029317432,0.000004422638,0.00025096454,0.48996058,1.9635754e-8,0.001173801,0.37405366,0.00014727503],"about_ca_topic_score_codex":0.00020135623,"about_ca_topic_score_gemma":0.00077742315,"teacher_disagreement_score":0.9473894,"about_ca_system_score_codex":0.00031074954,"about_ca_system_score_gemma":0.0010937661,"threshold_uncertainty_score":0.79388213},"labels":[],"label_agreement":null},{"id":"W4392307080","doi":"10.1007/978-981-97-0903-8_8","title":"Semantic Similarity Functions and Their Applications","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Similarity (geometry); Semantic similarity; Information retrieval; Natural language processing; Artificial intelligence","score_opus":0.038711229711014795,"score_gpt":0.27834463780351576,"score_spread":0.23963340809250097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392307080","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022113427,0.0024256136,0.70468146,0.00322417,0.0002877704,0.00045491857,0.000020804058,0.00023805734,0.28864512],"genre_scores_gemma":[0.55763644,0.037634484,0.35896567,0.0072168563,0.0004341972,0.0007618709,0.00032654806,0.00008326967,0.03694069],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987228,0.000014869796,0.00049044995,0.00034815483,0.00021987244,0.00020385318],"domain_scores_gemma":[0.9973125,0.0002660135,0.00015013557,0.001956819,0.00022156403,0.00009295597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067271147,0.00022253748,0.0002335028,0.0008613413,0.00056783715,0.0009771957,0.0021709087,0.0001265455,0.0000037571194],"category_scores_gemma":[0.00001991002,0.00019129209,0.000043089032,0.00046206499,0.0010864179,0.0037923055,0.003043215,0.00044665174,0.0000993095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.1612413e-7,0.0000068399418,0.000019979267,0.00003816056,0.000005730069,1.7786482e-7,0.0008276096,0.00001477455,0.0000013759196,0.82639396,0.00018830015,0.17250276],"study_design_scores_gemma":[0.00013829944,0.000038449652,0.00079779676,0.00019132328,0.000012287091,0.000076676166,0.00010897224,0.38400394,0.0000059605827,0.16109201,0.45315665,0.00037762985],"about_ca_topic_score_codex":0.00001294464,"about_ca_topic_score_gemma":0.000027287773,"teacher_disagreement_score":0.665302,"about_ca_system_score_codex":0.00007075639,"about_ca_system_score_gemma":0.00018753202,"threshold_uncertainty_score":0.942312},"labels":[],"label_agreement":null},{"id":"W4392693097","doi":"10.1007/978-981-97-1274-8_21","title":"Detection of Cyberbullying in Social Media Texts Using Explainable Artificial Intelligence","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Social media; Computer science; Artificial intelligence; Information retrieval; World Wide Web","score_opus":0.06479327528948592,"score_gpt":0.3013920897076237,"score_spread":0.2365988144181378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392693097","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017639471,0.0006395076,0.9299515,0.00029551593,0.0010811451,0.0004991335,0.000009902119,0.00014305586,0.06561629],"genre_scores_gemma":[0.93734634,0.0008527912,0.061340846,0.00008840871,0.00010714492,0.000023170975,0.000012935781,0.000015246885,0.00021312416],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980769,0.000031127587,0.00089652865,0.00029702848,0.00044669557,0.00025169476],"domain_scores_gemma":[0.9983261,0.00018657139,0.00031235837,0.0008506433,0.00026624984,0.000058026308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013073565,0.00019603822,0.0002603697,0.0019617486,0.00038942343,0.00044964798,0.0016502814,0.00017034229,0.000004013785],"category_scores_gemma":[0.000059658072,0.00021336292,0.000053477357,0.0011120997,0.000551701,0.0041900035,0.001394826,0.00053355296,0.000031390515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029257183,0.000011474361,0.000002246209,0.000051856867,0.0000028401694,0.0000010275423,0.0040575787,0.0005885132,0.00016082858,0.55434227,0.0000023431494,0.4407761],"study_design_scores_gemma":[0.000074421456,0.000040746938,0.000109810055,0.0005242066,0.0000072216008,0.000035837962,0.00017090568,0.85729945,0.0012812081,0.13538152,0.004735706,0.00033895817],"about_ca_topic_score_codex":0.000038974154,"about_ca_topic_score_gemma":0.000079090794,"teacher_disagreement_score":0.9355824,"about_ca_system_score_codex":0.00026022238,"about_ca_system_score_gemma":0.00024132944,"threshold_uncertainty_score":0.8700687},"labels":[],"label_agreement":null},{"id":"W4392720234","doi":"10.1007/978-981-97-1274-8_25","title":"Blockchain-Based Privacy-Preservation Platform for Data Storage and Query Processing","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Blockchain; Computer science; Information retrieval; Database; Computer security","score_opus":0.10589648915979645,"score_gpt":0.3311721315361624,"score_spread":0.22527564237636594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392720234","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000115218936,0.0014362218,0.96674174,0.017624917,0.00029773166,0.0009063034,0.0001691594,0.000522416,0.012186298],"genre_scores_gemma":[0.018573187,0.00068758597,0.9790311,0.0008124181,0.000042067913,0.000080321835,0.0004358631,0.00002064995,0.00031680585],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99779826,0.000012908838,0.0007405433,0.0006525364,0.0004884027,0.00030735743],"domain_scores_gemma":[0.98303306,0.00046630413,0.00038261057,0.01567347,0.0003598888,0.00008467282],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0020630728,0.00028511696,0.00027778198,0.0012588445,0.00059610576,0.0015830947,0.042433765,0.00021689686,0.0000014358873],"category_scores_gemma":[0.002089726,0.000283228,0.000027825588,0.0005930619,0.0009958211,0.008281007,0.13832511,0.0005664013,0.0000095441155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055745268,0.000020175301,0.000024034567,0.00043475197,0.000010839496,8.0058345e-7,0.00065186404,0.0001938368,0.000005623728,0.42115864,0.008127945,0.5693659],"study_design_scores_gemma":[0.0001733659,0.000030439756,0.00004542658,0.00038665766,0.000006883921,0.000008493482,0.000007154062,0.75231344,0.000008126112,0.14561449,0.10116947,0.00023604975],"about_ca_topic_score_codex":0.000015373986,"about_ca_topic_score_gemma":0.000013289044,"teacher_disagreement_score":0.7521196,"about_ca_system_score_codex":0.00017842073,"about_ca_system_score_gemma":0.0005373742,"threshold_uncertainty_score":0.999962},"labels":[],"label_agreement":null},{"id":"W4393149634","doi":"10.1007/978-3-031-56700-1","title":"Advanced Computing","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Internet of Things and AI","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Dr B R Ambedkar National Institute of Technology Jalandhar; North South University; Thapar Institute of Engineering and Technology; Motilal Nehru National Institute of Technology Allahabad; Jaypee Institute of Information Technology; Indian Statistical Institute; Deenbandhu Chhotu Ram University of Science and Technology; SSN College of Engineering; Kurukshetra University; Indian Institute of Technology Kharagpur; Indian Institute of Technology Delhi; Jawaharlal Nehru Technological University Hyderabad; Guru Jambheshwar University of Science and Technology; VIT University; RMIT University; Osmania University; National Institute of Technology Karnataka, Surathkal; Liverpool John Moores University; Politechnika Wrocławska; ITM University-Gwalior; Indian Institute of Technology Madras; Ministry of Earth Sciences; Defence Research and Development Organisation; International Institute of Information Technology, Hyderabad; Jadavpur University; Universiti Malaya; Trinity College Dublin; Cardiff University; Netaji Subhas University of Technology; Amity University; Indian Institute of Technology Jodhpur; University of the Punjab; Queen's University; San José State University; De Montfort University; Indian Institute of Technology Roorkee; Queen's University Belfast; University of Rwanda; Vidyasirimedhi Institute of Science and Technology","keywords":"Computer science","score_opus":0.020321147890390457,"score_gpt":0.2987235136573942,"score_spread":0.2784023657670037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393149634","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000039716633,0.0009938405,0.4769681,0.0021497947,0.0012344661,0.00028866154,0.0000057982734,0.00025713933,0.5180625],"genre_scores_gemma":[0.0507109,0.0028290283,0.9046773,0.0068756863,0.00023555108,0.00003641798,0.00009693612,0.000032104996,0.034506124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998353,0.000025409374,0.0006032774,0.00031949749,0.0004268716,0.00027191904],"domain_scores_gemma":[0.9974422,0.00015479702,0.00022421595,0.0018298073,0.00026174964,0.00008725346],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010744063,0.0002042792,0.00022283394,0.0010110714,0.00033260207,0.0016156926,0.0051184776,0.00010048598,0.0000026497771],"category_scores_gemma":[0.000034510063,0.00019672794,0.000052060812,0.00073115603,0.00053868606,0.0077513014,0.0058102557,0.0006171853,0.00020843069],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.2259973e-7,0.0000071815753,0.0000024025499,0.000046519363,0.0000032354576,7.059868e-7,0.0023699794,0.0001888511,0.0000014201264,0.62267333,0.004099243,0.3706067],"study_design_scores_gemma":[0.000092314534,0.000027034184,0.000071428185,0.000391693,0.0000021088633,0.000023130648,0.000009926349,0.6003224,0.000005656183,0.011410171,0.38744533,0.00019879361],"about_ca_topic_score_codex":0.0000056282734,"about_ca_topic_score_gemma":0.0000025746979,"teacher_disagreement_score":0.61126316,"about_ca_system_score_codex":0.0002473046,"about_ca_system_score_gemma":0.00053951197,"threshold_uncertainty_score":0.9994207},"labels":[],"label_agreement":null},{"id":"W4393169450","doi":"10.1007/978-3-031-56703-2","title":"Advanced Computing","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Internet of Things and AI","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Dr B R Ambedkar National Institute of Technology Jalandhar; North South University; Thapar Institute of Engineering and Technology; Motilal Nehru National Institute of Technology Allahabad; Jaypee Institute of Information Technology; Indian Statistical Institute; Deenbandhu Chhotu Ram University of Science and Technology; SSN College of Engineering; Kurukshetra University; Indian Institute of Technology Kharagpur; Indian Institute of Technology Delhi; Jawaharlal Nehru Technological University Hyderabad; Guru Jambheshwar University of Science and Technology; VIT University; RMIT University; Osmania University; National Institute of Technology Karnataka, Surathkal; Liverpool John Moores University; Politechnika Wrocławska; ITM University-Gwalior; Indian Institute of Technology Madras; Ministry of Earth Sciences; Defence Research and Development Organisation; International Institute of Information Technology, Hyderabad; Jadavpur University; Universiti Malaya; Trinity College Dublin; Cardiff University; Netaji Subhas University of Technology; Amity University; Indian Institute of Technology Jodhpur; University of the Punjab; Queen's University; San José State University; De Montfort University; Indian Institute of Technology Roorkee; Queen's University Belfast; University of Rwanda; Vidyasirimedhi Institute of Science and Technology","keywords":"Computer science","score_opus":0.020321147890390457,"score_gpt":0.2987235136573942,"score_spread":0.2784023657670037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393169450","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000039716633,0.0009938405,0.4769681,0.0021497947,0.0012344661,0.00028866154,0.0000057982734,0.00025713933,0.5180625],"genre_scores_gemma":[0.0507109,0.0028290283,0.9046773,0.0068756863,0.00023555108,0.00003641798,0.00009693612,0.000032104996,0.034506124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998353,0.000025409374,0.0006032774,0.00031949749,0.0004268716,0.00027191904],"domain_scores_gemma":[0.9974422,0.00015479702,0.00022421595,0.0018298073,0.00026174964,0.00008725346],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010744063,0.0002042792,0.00022283394,0.0010110714,0.00033260207,0.0016156926,0.0051184776,0.00010048598,0.0000026497771],"category_scores_gemma":[0.000034510063,0.00019672794,0.000052060812,0.00073115603,0.00053868606,0.0077513014,0.0058102557,0.0006171853,0.00020843069],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.2259973e-7,0.0000071815753,0.0000024025499,0.000046519363,0.0000032354576,7.059868e-7,0.0023699794,0.0001888511,0.0000014201264,0.62267333,0.004099243,0.3706067],"study_design_scores_gemma":[0.000092314534,0.000027034184,0.000071428185,0.000391693,0.0000021088633,0.000023130648,0.000009926349,0.6003224,0.000005656183,0.011410171,0.38744533,0.00019879361],"about_ca_topic_score_codex":0.0000056282734,"about_ca_topic_score_gemma":0.0000025746979,"teacher_disagreement_score":0.61126316,"about_ca_system_score_codex":0.0002473046,"about_ca_system_score_gemma":0.00053951197,"threshold_uncertainty_score":0.9994207},"labels":[],"label_agreement":null},{"id":"W4394626935","doi":"10.1007/978-3-031-57639-3_9","title":"Systems Thinking Application to Ethical and Privacy Considerations in AI-Enabled Syndromic Surveillance Systems: Requirements for Under-Resourced Countries in Southern Africa","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Internet privacy; Computer security; Business","score_opus":0.1564977920764924,"score_gpt":0.40767963970912774,"score_spread":0.25118184763263535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394626935","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.075836875,0.020612022,0.6065594,0.1822658,0.0047156382,0.039869606,0.00059706194,0.0007192474,0.06882435],"genre_scores_gemma":[0.9940901,0.0006193021,0.002636465,0.001538846,0.000049944723,0.00041212613,0.000096156975,0.00001468263,0.00054240436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797183,0.000048793838,0.0011158304,0.0002951608,0.00033582727,0.00023257657],"domain_scores_gemma":[0.9977319,0.00069491984,0.00021146673,0.0007522712,0.00050705665,0.0001023756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002412647,0.00017290033,0.00034718285,0.0010765577,0.0003270588,0.00049315876,0.00033492845,0.00026031633,0.0000020144332],"category_scores_gemma":[0.00021186365,0.00017253358,0.000021890499,0.00035478902,0.00034744377,0.00070315023,0.000298514,0.0005885781,0.000032059357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004277188,0.00003980929,0.0018495044,0.0012154935,0.000014520517,9.660132e-7,0.0523435,0.009125571,0.000017641589,0.93022025,0.00051477057,0.004615208],"study_design_scores_gemma":[0.00033952485,0.00018338968,0.0015883484,0.004258038,0.000024045925,0.00007387023,0.004607096,0.881425,0.0000055389687,0.03804245,0.06898125,0.00047144285],"about_ca_topic_score_codex":0.0005332253,"about_ca_topic_score_gemma":0.00033725862,"teacher_disagreement_score":0.9182532,"about_ca_system_score_codex":0.0004876057,"about_ca_system_score_gemma":0.000534196,"threshold_uncertainty_score":0.7035715},"labels":[],"label_agreement":null},{"id":"W4396713553","doi":"10.1007/978-3-031-59057-3_23","title":"Interacting with a Visuotactile Countertop","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; York University","funders":"","keywords":"Computer science; Psychology","score_opus":0.05491093988980664,"score_gpt":0.32442917241726776,"score_spread":0.2695182325274611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396713553","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009072516,0.00004599792,0.0026205871,0.0009992338,0.0007394775,0.00034655418,0.0000365357,0.0001434302,0.99416095],"genre_scores_gemma":[0.9602449,0.00203824,0.0042939936,0.002670475,0.00010510073,0.000055027675,0.00003278654,0.000036868652,0.030522589],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99866915,0.000015856996,0.00046669698,0.00029401804,0.00035853003,0.00019573976],"domain_scores_gemma":[0.9978944,0.00057337235,0.00022950997,0.0010612488,0.00016306853,0.00007838068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015298244,0.00020619728,0.00018548916,0.00094624766,0.00043100276,0.0008410053,0.0010195241,0.000075283446,0.000059134127],"category_scores_gemma":[0.00008826352,0.00017687595,0.00003784363,0.00032859505,0.0007749286,0.0059217378,0.00074004626,0.00075885275,0.00041198713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003122297,0.00004321581,0.000023711156,0.000096878815,0.000011822335,0.000010531805,0.006689447,0.00024859485,0.0005994954,0.9003519,0.00085884065,0.09103435],"study_design_scores_gemma":[0.00018552186,0.000095868665,0.000035109977,0.0008802287,0.0000152039,0.0003862441,0.0001530735,0.13518162,0.0007328351,0.00219569,0.85976607,0.00037251337],"about_ca_topic_score_codex":0.00001283796,"about_ca_topic_score_gemma":0.000021276455,"teacher_disagreement_score":0.96363837,"about_ca_system_score_codex":0.00016567332,"about_ca_system_score_gemma":0.00016011905,"threshold_uncertainty_score":0.81098336},"labels":[],"label_agreement":null},{"id":"W4396713560","doi":"10.1007/978-3-031-59057-3_2","title":"Robot Vision and Deep Learning for Automated Planogram Compliance in Retail","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Image stitching; Computer science; Artificial intelligence; Computer vision; Identification (biology); Robot; Concatenation (mathematics); Deep learning; Mathematics","score_opus":0.05634033942380258,"score_gpt":0.3080339893937218,"score_spread":0.2516936499699192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396713560","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035594762,0.014136851,0.42877078,0.0005947942,0.0044553047,0.0052100066,0.000078356046,0.003664103,0.53953034],"genre_scores_gemma":[0.9700832,0.006292997,0.021288631,0.00010632691,0.000104144085,0.00012597334,0.00016655041,0.000045150147,0.0017870262],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990429,0.000011482647,0.00050961797,0.00014120119,0.00015159424,0.0001431739],"domain_scores_gemma":[0.9992424,0.00014711978,0.00008513713,0.00038016032,0.00010067737,0.000044493558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007016952,0.00015006293,0.0002069037,0.0007584749,0.00020565579,0.0003661609,0.00031517417,0.00016048283,0.0000025318218],"category_scores_gemma":[0.000022473798,0.00014693518,0.000025199324,0.00026946113,0.00018479498,0.0013874728,0.00025183128,0.00042932466,0.000017945607],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009185226,0.000005693807,0.000046477922,0.00035188746,0.000009340792,4.512033e-7,0.0017074748,0.04923834,0.000033058554,0.028775755,0.00018861031,0.91963375],"study_design_scores_gemma":[0.00019428108,0.00004296656,0.00043999,0.00057274656,0.0000029353048,0.000010818465,0.000024564035,0.8617983,0.0000040558493,0.00040114103,0.13636951,0.00013872044],"about_ca_topic_score_codex":0.000008468646,"about_ca_topic_score_gemma":0.000021604392,"teacher_disagreement_score":0.9665237,"about_ca_system_score_codex":0.00011100133,"about_ca_system_score_gemma":0.000024840296,"threshold_uncertainty_score":0.5991843},"labels":[],"label_agreement":null},{"id":"W4396713641","doi":"10.1007/978-3-031-59057-3_14","title":"Multi-UAV Weed Spraying","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Plant Surface Properties and Treatments","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MD Precision (Canada); University of Regina","funders":"","keywords":"Weed; Computer science; Botany; Biology","score_opus":0.07048765134879477,"score_gpt":0.26576512727414237,"score_spread":0.1952774759253476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396713641","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018593784,0.0073746555,0.00045887742,0.0057040905,0.0011292002,0.0017961566,0.00045850567,0.0004113413,0.96407336],"genre_scores_gemma":[0.8838514,0.015434619,0.04208352,0.0022982887,0.00017722404,0.00013867853,0.0011442914,0.000006408492,0.054865576],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99920374,0.0000073228907,0.00030008118,0.00015930618,0.00018602323,0.00014354858],"domain_scores_gemma":[0.99945366,0.000086203814,0.00009386519,0.00021823,0.00008945925,0.000058595964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028789276,0.00013585443,0.00013495624,0.00008777444,0.00034930065,0.0003583876,0.000754922,0.00007710601,0.00003156223],"category_scores_gemma":[0.000008352353,0.000058072168,0.000033905868,0.00016970816,0.0003122989,0.0015185144,0.0008819459,0.00021260302,0.00024114216],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000624151,0.000039834526,0.000323676,0.000036822363,0.000019262003,0.0000017734361,0.00084246113,0.000049990664,0.00077086006,0.0759098,0.00028489166,0.92171437],"study_design_scores_gemma":[0.00016019425,0.00007373592,0.0072848545,0.00036684299,0.000013497465,0.000022173426,0.00006413829,0.074120075,0.00002231493,0.0019733056,0.9155492,0.00034962595],"about_ca_topic_score_codex":0.000089037785,"about_ca_topic_score_gemma":0.00010231278,"teacher_disagreement_score":0.9213648,"about_ca_system_score_codex":0.00005769989,"about_ca_system_score_gemma":0.000022514425,"threshold_uncertainty_score":0.34559396},"labels":[],"label_agreement":null},{"id":"W4396713670","doi":"10.1007/978-3-031-59057-3","title":"Robotics, Computer Vision and Intelligent Systems","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Samsung; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Université Claude Bernard Lyon 1; Universidad Carlos III de Madrid; Universität Bremen; Universidade de Lisboa; Turun Yliopisto; Egypt-Japan University of Science and Technology; Universiti Malaysia Perlis; Slovenská technická univerzita v Bratislave; Università degli Studi della Campania Luigi Vanvitelli; Kungliga Tekniska Högskolan; Università degli Studi di Trento; RMIT University; International Science and Technology Center; Universidade de Coimbra; University of Glasgow; Imperial College London; Kyungpook National University; Universidad de Alcalá; Universidad de Guanajuato; Sveučilište u Zagrebu; Harvard University; Trent University; Nottingham Trent University; Politechnika Warszawska; Staffordshire University; Instituto Politécnico Nacional; York University; Chuo University; Universidad Autónoma de Yucatán; Université du Québec à Chicoutimi; Gebze Teknik Üniversitesi; Universidad de Alicante; Southeast University; Friedrich-Alexander-Universität Erlangen-Nürnberg","keywords":"Robotics; Artificial intelligence; Computer science; Computer vision; Robot","score_opus":0.031435570261879736,"score_gpt":0.27991560724093517,"score_spread":0.24848003697905544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396713670","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004240857,0.0099685425,0.7783292,0.00027858556,0.010639144,0.0017375165,0.000056410052,0.0007609391,0.19780558],"genre_scores_gemma":[0.8470046,0.04841168,0.078777894,0.0009743141,0.0032606232,0.00031378164,0.0006771022,0.00024123711,0.020338776],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874735,0.000029076302,0.0006319025,0.00016253968,0.00026986323,0.00015924772],"domain_scores_gemma":[0.99883723,0.00012279509,0.00008606683,0.0007211143,0.00015157866,0.00008123322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008398212,0.0001899061,0.00024721684,0.0008961451,0.00019979036,0.0009370642,0.0004885971,0.0001851547,0.0000016082406],"category_scores_gemma":[0.000008992639,0.0001710703,0.000029613493,0.00039935447,0.00029886703,0.0017816548,0.00063777337,0.00048297952,0.000090965055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000049681025,0.000015524489,0.000015071483,0.0009326138,0.000033957724,0.0000016380096,0.00303281,0.15064022,0.000008635785,0.080760896,0.035093036,0.72946066],"study_design_scores_gemma":[0.0000709881,0.000041046096,0.00004399911,0.00055182196,0.000005285567,0.00003236422,0.000020288016,0.7383814,0.0000021669944,0.00020104938,0.26050165,0.00014796204],"about_ca_topic_score_codex":0.000012609571,"about_ca_topic_score_gemma":0.0000034816355,"teacher_disagreement_score":0.8465805,"about_ca_system_score_codex":0.0002433413,"about_ca_system_score_gemma":0.00009918494,"threshold_uncertainty_score":0.90361315},"labels":[],"label_agreement":null},{"id":"W4399145934","doi":"10.1007/978-3-031-58950-8_5","title":"Mapping for Quality Analysis of the Instructional Model for MOOCs. Case Study: Open Campus Initiative","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Quality (philosophy); Library science; Information retrieval; World Wide Web; Physics","score_opus":0.15905691045565595,"score_gpt":0.4141904944579001,"score_spread":0.2551335840022442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399145934","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011814708,0.000056614197,0.98709595,0.0016623834,0.00019397399,0.0011158565,0.00018346723,0.000029594441,0.008480671],"genre_scores_gemma":[0.6201888,0.000094939416,0.37701094,0.00059779285,0.000029795807,0.0001438741,0.000078871104,0.000009685734,0.0018453059],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985188,0.0000332763,0.0007748932,0.00025903626,0.00028596728,0.0001279986],"domain_scores_gemma":[0.99677813,0.00045671727,0.0005232458,0.0014948783,0.00070596,0.00004103951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019066639,0.00014295983,0.00032551846,0.0010166445,0.00059329637,0.0005925028,0.0033676545,0.00006550731,5.817175e-7],"category_scores_gemma":[0.00008847926,0.000115651885,0.00012801992,0.0011087635,0.00042363937,0.0024520028,0.0033681518,0.00026172042,7.1840986e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022030597,0.000034418394,0.00014616379,0.000050839473,0.0001371202,2.485907e-7,0.011338739,0.04027078,3.1978973e-7,0.89866346,0.000041905456,0.04931381],"study_design_scores_gemma":[0.00021600894,0.00003063707,0.00033948154,0.000063222826,0.00006797417,0.000012886353,0.000382998,0.96125406,3.7303383e-7,0.0348521,0.0026481904,0.0001320429],"about_ca_topic_score_codex":0.00004784472,"about_ca_topic_score_gemma":0.00013049181,"teacher_disagreement_score":0.9209833,"about_ca_system_score_codex":0.000097200085,"about_ca_system_score_gemma":0.00047379578,"threshold_uncertainty_score":0.6257996},"labels":[],"label_agreement":null},{"id":"W4399262338","doi":"10.1007/978-3-031-61947-2_18","title":"Practical Utility and Factors Driving Use of Virtual Cardiac Rehabilitation: A Patient-Centric and Disabilities View to Innovation","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint John Regional Hospital; Horizon Health Network; National Research Council Canada","funders":"","keywords":"Rehabilitation; Physical medicine and rehabilitation; Computer science; Psychology; Medicine; Physical therapy","score_opus":0.06485432056194033,"score_gpt":0.3407754993378338,"score_spread":0.27592117877589345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399262338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9579804,0.0013235812,0.00893247,0.0074590766,0.00091711414,0.003243136,0.00017589405,0.00010963016,0.019858677],"genre_scores_gemma":[0.9591566,0.0019596263,0.037954867,0.0002850272,0.00002195236,0.000031785203,0.00008536872,0.00001096616,0.00049380877],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984678,0.000040186776,0.0008006263,0.00022804938,0.00034702377,0.00011631637],"domain_scores_gemma":[0.99646384,0.002022212,0.00018129288,0.0006572762,0.000576954,0.00009845788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006598161,0.00016013546,0.00033882694,0.0011225638,0.00014573176,0.00017353786,0.00011698411,0.00010350196,0.000009038764],"category_scores_gemma":[0.0015393409,0.00013832019,0.0000442497,0.0005850916,0.0012726907,0.0022253273,0.000584028,0.00028451026,0.0000043400755],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004255312,0.000084439926,0.05437218,0.00090909237,0.00004257374,1.8810528e-7,0.021906307,0.000020329544,0.000021593101,0.6348022,0.00069442886,0.2871041],"study_design_scores_gemma":[0.0007507083,0.0018573145,0.4661411,0.003718371,0.00014683539,0.000043287968,0.00586229,0.04304829,0.000030956508,0.0056780665,0.4719974,0.0007253905],"about_ca_topic_score_codex":0.00001209123,"about_ca_topic_score_gemma":0.0000025545326,"teacher_disagreement_score":0.62912416,"about_ca_system_score_codex":0.000114039234,"about_ca_system_score_gemma":0.0002107918,"threshold_uncertainty_score":0.5640534},"labels":[],"label_agreement":null},{"id":"W4399262361","doi":"10.1007/978-3-031-61947-2_19","title":"Cultural Dimensions Affecting Perception of Privacy and Intrusiveness of Video Monitoring Technologies for Aging at Home","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Intrusiveness; Perception; Computer science; Internet privacy; Multimedia; Psychology; Social psychology; Neuroscience","score_opus":0.04108676911479978,"score_gpt":0.34223670711652004,"score_spread":0.30114993800172024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399262361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9214164,0.0068123555,0.017407093,0.007561616,0.0016520665,0.0037161948,0.00011095786,0.0010731871,0.040250108],"genre_scores_gemma":[0.9680399,0.005432626,0.026283516,0.000008396648,0.000014404869,0.000021276657,0.000007988088,0.0000048811457,0.00018701318],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990674,0.000015120337,0.00041146894,0.00015496336,0.0002097612,0.00014127609],"domain_scores_gemma":[0.99847335,0.00033221339,0.00028576155,0.00052641134,0.000358412,0.000023864664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079079013,0.00010914562,0.0002020687,0.00072577235,0.0006049559,0.000088341025,0.00081948854,0.00016102444,9.783112e-7],"category_scores_gemma":[0.00019655428,0.000104736864,0.00003232521,0.00030867333,0.0024458368,0.0018132671,0.0016852056,0.00021960975,0.0000015380211],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006799228,0.000014456212,0.003773388,0.00040858542,0.000020166293,1.3105286e-7,0.08642997,0.000056619916,0.0008182067,0.49295315,0.000040257302,0.41547826],"study_design_scores_gemma":[0.003835234,0.00085124484,0.078905255,0.025543807,0.00039239143,0.00010313487,0.1535148,0.084545456,0.005474105,0.334704,0.30835378,0.0037767864],"about_ca_topic_score_codex":0.00005119335,"about_ca_topic_score_gemma":0.000031959316,"teacher_disagreement_score":0.41170147,"about_ca_system_score_codex":0.00016947935,"about_ca_system_score_gemma":0.00008845235,"threshold_uncertainty_score":0.9011787},"labels":[],"label_agreement":null},{"id":"W4399266712","doi":"10.1007/978-3-031-62110-9_28","title":"Exploring Privacy in Smart Homes: A Cognitive Walkthrough of Automation Levels for Data Monetization","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; University of Ottawa","funders":"","keywords":"Monetization; Digitization; Software walkthrough; Computer science; Cognition; World Wide Web; Internet privacy; Data science; Psychology; Telecommunications; Software; Operating system","score_opus":0.3649041526513648,"score_gpt":0.4407571121942103,"score_spread":0.07585295954284554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399266712","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003436953,0.00087981933,0.40964738,0.0019189523,0.0028027932,0.0031940702,0.0009198921,0.00030035526,0.57689977],"genre_scores_gemma":[0.95564157,0.0026249923,0.031313438,0.0005976945,0.000112293645,0.0005567303,0.0030930366,0.000046959307,0.006013266],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99811715,0.000038435577,0.0011038708,0.0003051896,0.0002714274,0.00016394437],"domain_scores_gemma":[0.9972029,0.00049432175,0.00044377727,0.0013974054,0.0004184321,0.000043202464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001185181,0.00017942842,0.00026931145,0.0014666857,0.00016896221,0.00017493671,0.0012120956,0.00011341966,0.000112354974],"category_scores_gemma":[0.00013227535,0.00019123571,0.000038231494,0.00042860533,0.00041332707,0.006058613,0.0009181833,0.00031172918,0.00010313508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026153684,0.00005868633,0.000098993405,0.00021019309,0.00003236536,2.939321e-7,0.032512814,0.00012418274,0.0000034638017,0.6562759,0.00050601753,0.3101509],"study_design_scores_gemma":[0.001537025,0.00014025555,0.026014527,0.0024269882,0.000046137324,0.00002222116,0.0015750485,0.7316872,0.000017913486,0.012107174,0.22384845,0.0005770733],"about_ca_topic_score_codex":0.000041794156,"about_ca_topic_score_gemma":0.00003435933,"teacher_disagreement_score":0.95220464,"about_ca_system_score_codex":0.00013558967,"about_ca_system_score_gemma":0.0001513847,"threshold_uncertainty_score":0.7798366},"labels":[],"label_agreement":null},{"id":"W4399266852","doi":"10.1007/978-3-031-61966-3_5","title":"Side Effect Reporting in Online Drug Reviews","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Drug; Information retrieval; Computer science; Medicine; Pharmacology","score_opus":0.06278568900251985,"score_gpt":0.38082969355834956,"score_spread":0.3180440045558297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399266852","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009941292,0.0020051284,0.00007276813,0.0015906952,0.0005126528,0.0005084814,0.000007361,0.00006414923,0.99424464],"genre_scores_gemma":[0.6286728,0.16662996,0.03830189,0.0050668353,0.0014128275,0.00031870615,0.00055466825,0.00009124356,0.15895107],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99784315,0.00009905201,0.0012840758,0.00017806819,0.0003854024,0.00021026391],"domain_scores_gemma":[0.99786854,0.00060127256,0.00069129653,0.00062248745,0.00013119524,0.00008521309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008889703,0.00013639274,0.00031140936,0.00060199434,0.00039918907,0.0005109768,0.0009824504,0.00009804492,0.0000063374932],"category_scores_gemma":[0.0020546168,0.00012914967,0.00005920547,0.0004960077,0.0011125208,0.0023204319,0.00067540666,0.0005030053,0.00006387874],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016835457,0.000010513628,0.00033347277,0.00010091365,0.0000020288687,0.0000013502371,0.019129394,0.0000081991275,2.3696221e-7,0.28412586,0.000536524,0.6957498],"study_design_scores_gemma":[0.0000863446,0.000015317059,0.00081851444,0.0016788396,0.000005835435,0.0000021717196,0.00036355364,0.002889832,3.2961825e-7,0.01222046,0.98170674,0.00021208357],"about_ca_topic_score_codex":0.00022622071,"about_ca_topic_score_gemma":0.0010792672,"teacher_disagreement_score":0.9811702,"about_ca_system_score_codex":0.00023393845,"about_ca_system_score_gemma":0.00031262398,"threshold_uncertainty_score":0.52665704},"labels":[],"label_agreement":null},{"id":"W4399266878","doi":"10.1007/978-3-031-62110-9_3","title":"Decoding the Alignment Problem: Revisiting the 1958 NYT Report on Rosenblatt’s Perceptron Through the Lens of Information Theory","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Decoding methods; Multilayer perceptron; Computer science; Through-the-lens metering; Perceptron; Psychology; Artificial intelligence; Lens (geology); Artificial neural network; Algorithm; Physics; Optics","score_opus":0.04354096666828808,"score_gpt":0.2996474996249506,"score_spread":0.2561065329566625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399266878","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000088425084,0.0008207063,0.46552384,0.045022003,0.0005006406,0.0018542488,0.000020266998,0.00013410294,0.48603576],"genre_scores_gemma":[0.78211117,0.024003176,0.15808098,0.025327317,0.000995665,0.0008425317,0.0002960143,0.00007431793,0.008268818],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99784034,0.0000715388,0.0010347393,0.00022300886,0.00060616725,0.00022417176],"domain_scores_gemma":[0.99524546,0.0007955589,0.0007075787,0.0029487566,0.00027149534,0.00003115125],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0028760852,0.00021009665,0.0001899597,0.00020408374,0.0013161467,0.0009992318,0.004033428,0.000074439864,0.0000044765225],"category_scores_gemma":[0.00004012699,0.00011529023,0.000088732515,0.0005727325,0.0010546534,0.004666728,0.0023469778,0.0006509216,0.000050011113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.721806e-7,0.0000028587526,0.0000017261017,0.000017594168,0.0000059678055,1.04833575e-7,0.004218902,0.0015115595,0.0000011401654,0.84539443,0.00032368622,0.14852105],"study_design_scores_gemma":[0.000109230125,0.000044976583,0.00046253088,0.00056688755,0.000023868724,0.000093515795,0.00032745354,0.30444124,0.00001054819,0.13260451,0.56105155,0.00026369313],"about_ca_topic_score_codex":0.00001848927,"about_ca_topic_score_gemma":0.000004900399,"teacher_disagreement_score":0.7820228,"about_ca_system_score_codex":0.00010997218,"about_ca_system_score_gemma":0.00015668519,"threshold_uncertainty_score":0.999984},"labels":[],"label_agreement":null},{"id":"W4399266893","doi":"10.1007/978-3-031-61966-3_32","title":"Human-Centered Design of Cadre: A Digital Platform to Support Cardiac Arrest (Co-)Survivorship","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"North York General Hospital; Toronto General Hospital; University Health Network; University of Toronto","funders":"","keywords":"Survivorship curve; Computer science; Medicine; Internal medicine","score_opus":0.08656729767758396,"score_gpt":0.34581340893768275,"score_spread":0.2592461112600988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399266893","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035308555,0.0005012438,0.03345195,0.0010239924,0.0029549897,0.0027147916,0.00040995792,0.00016099976,0.9552512],"genre_scores_gemma":[0.97870183,0.001116887,0.010627003,0.00054021616,0.00025219237,0.000070113034,0.0008999861,0.000038554626,0.0077532004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99849796,0.0000097178545,0.0006699033,0.00018921326,0.00046115968,0.00017204971],"domain_scores_gemma":[0.9982404,0.00011821074,0.00017837032,0.0010120769,0.0003058229,0.00014512229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007584748,0.00018232671,0.0003526246,0.00096526026,0.00017137303,0.00024934576,0.00053079636,0.00011972314,0.00001117637],"category_scores_gemma":[0.000039265266,0.00016734842,0.00009977735,0.0003190271,0.0005887838,0.0017563284,0.0005477313,0.0003283392,0.00012724553],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020493405,0.00019580191,0.004485771,0.0019195022,0.00031405664,0.0000107424285,0.028044619,0.001336531,0.00036108991,0.5887125,0.014333077,0.36008137],"study_design_scores_gemma":[0.0020853886,0.0011052173,0.027605474,0.004767807,0.0002423315,0.000041403113,0.00064975204,0.027211078,0.0001924902,0.012386927,0.92218107,0.0015310597],"about_ca_topic_score_codex":0.000012912076,"about_ca_topic_score_gemma":0.0000043981718,"teacher_disagreement_score":0.97517097,"about_ca_system_score_codex":0.00014264093,"about_ca_system_score_gemma":0.00028412257,"threshold_uncertainty_score":0.68242705},"labels":[],"label_agreement":null},{"id":"W4399267067","doi":"10.1007/978-3-031-61966-3_1","title":"Growing Up with Passwords","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Password; Computer science; World Wide Web; Information retrieval; Internet privacy; Computer security","score_opus":0.032442445329972744,"score_gpt":0.27695845026393007,"score_spread":0.2445160049339573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399267067","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000116892545,0.0011231559,0.3682479,0.0061374665,0.0013129916,0.00068713364,0.000014404528,0.0004387983,0.62192124],"genre_scores_gemma":[0.8177128,0.003793141,0.11931403,0.005288275,0.00021597928,0.00017577433,0.00014958112,0.00006447799,0.053285982],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99836534,0.00001786173,0.0005624584,0.00031266428,0.0005327,0.00020897202],"domain_scores_gemma":[0.9971061,0.00011003682,0.00019013433,0.0021851459,0.00029952067,0.00010909708],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00084748084,0.00020868171,0.00021609313,0.0010549079,0.00033422478,0.0014017939,0.003233156,0.00009656708,0.000006042397],"category_scores_gemma":[0.000011114079,0.00018008074,0.000038861108,0.00058081385,0.00058984885,0.008539233,0.001894492,0.00042904099,0.00022126289],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.421168e-7,0.0000042762167,0.0000104977835,0.000035759076,0.000005728063,4.9790884e-7,0.010156775,0.000007687349,7.2906545e-7,0.94453096,0.00016424878,0.045082185],"study_design_scores_gemma":[0.00018688115,0.000044464938,0.00016197008,0.00047794823,0.000007663535,0.000059078895,0.000050798135,0.5004584,0.0000059990543,0.023836052,0.47437632,0.00033439827],"about_ca_topic_score_codex":0.000009809413,"about_ca_topic_score_gemma":0.0000142636845,"teacher_disagreement_score":0.92069495,"about_ca_system_score_codex":0.00011886578,"about_ca_system_score_gemma":0.0002739487,"threshold_uncertainty_score":0.99963486},"labels":[],"label_agreement":null},{"id":"W4399267137","doi":"10.1007/978-3-031-61966-3_3","title":"Automatic Verbalizer for Extracting Fine-Grained Customer Opinions from Non-English Social Media Comments","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Social media; Computer science; Information retrieval; Sentiment analysis; Natural language processing; Data science; Artificial intelligence; World Wide Web","score_opus":0.049607234966070314,"score_gpt":0.3214743613390805,"score_spread":0.2718671263730102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399267137","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003323583,0.0009163099,0.70168066,0.006311923,0.006016364,0.0015859847,0.00038020618,0.00062040304,0.28215575],"genre_scores_gemma":[0.18714039,0.0014619525,0.7983943,0.0032730482,0.0014186819,0.00036941143,0.003982911,0.000087830864,0.003871448],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99788094,0.000022901435,0.0009111602,0.00037631483,0.0005260453,0.00028262392],"domain_scores_gemma":[0.9968944,0.0008987766,0.00043008573,0.0012415681,0.00043405555,0.00010108098],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010053567,0.00027014982,0.00037124558,0.001025578,0.0007902849,0.0013391675,0.0028234052,0.0001500686,0.000032021748],"category_scores_gemma":[0.00009659768,0.0002701579,0.00013872936,0.0005596479,0.00038633047,0.0046093827,0.0020479744,0.00041071553,0.00009623185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002364245,0.00003500432,0.00002994487,0.00006416667,0.000065515436,4.3889025e-7,0.025442543,0.00007717739,0.0000038215962,0.6780435,0.01004354,0.28619197],"study_design_scores_gemma":[0.00038090264,0.000013614176,0.00031022177,0.00028136786,0.000026789608,0.0000012908242,0.00013384882,0.77128327,0.000005361659,0.007916855,0.21933523,0.0003112715],"about_ca_topic_score_codex":0.000009412146,"about_ca_topic_score_gemma":0.000011037474,"teacher_disagreement_score":0.7712061,"about_ca_system_score_codex":0.00014558918,"about_ca_system_score_gemma":0.00019225785,"threshold_uncertainty_score":0.9999751},"labels":[],"label_agreement":null},{"id":"W4399861067","doi":"10.1007/978-981-97-3626-3_14","title":"Human-Centered Financial Signal Processing: A Case Study on Stock Chart Analysis","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Chart; Stock (firearms); Computer science; Finance; Business; Statistics; Geography; Mathematics","score_opus":0.26420571467430504,"score_gpt":0.4605631743490507,"score_spread":0.19635745967474566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399861067","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028542442,0.0005421347,0.20793037,0.001340215,0.0010037045,0.0033250046,0.00015822033,0.00033174345,0.75682616],"genre_scores_gemma":[0.9756529,0.000021715037,0.013817564,0.0004084479,0.00007883603,0.0000708965,0.000022214814,0.000015667934,0.009911804],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956968,0.00016440735,0.001612263,0.0006104755,0.0016491311,0.00026691784],"domain_scores_gemma":[0.9948503,0.0009310272,0.00069933006,0.002475717,0.00090187846,0.00014175999],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008673303,0.0003164844,0.00056028395,0.005107812,0.0010927487,0.0018804654,0.0030669942,0.00013693588,0.000070480346],"category_scores_gemma":[0.00041143794,0.00026361758,0.00015339363,0.0028803677,0.0008864591,0.002636568,0.0023682339,0.0007416239,0.0001077346],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014348108,0.00014131296,0.0010726042,0.000022007911,0.000053187563,0.00004675809,0.013515017,0.0006592858,0.0000010257975,0.03335362,0.0010391243,0.9500817],"study_design_scores_gemma":[0.00085688726,0.000727529,0.014908083,0.0004270192,0.00029674603,0.00045702467,0.0016101693,0.8548322,0.000001905771,0.028987827,0.09590778,0.0009868551],"about_ca_topic_score_codex":0.000031396816,"about_ca_topic_score_gemma":0.00012004282,"teacher_disagreement_score":0.94909483,"about_ca_system_score_codex":0.00019428912,"about_ca_system_score_gemma":0.00036483858,"threshold_uncertainty_score":0.9999816},"labels":[],"label_agreement":null},{"id":"W4399879499","doi":"10.1007/978-3-031-62495-7_16","title":"Intelligent Framework for Monitoring Student Emotions During Online Learning","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Thesaurus; Online learning; Information retrieval; World Wide Web; Multimedia; Natural language processing","score_opus":0.09858600171163037,"score_gpt":0.4135555120417727,"score_spread":0.3149695103301423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399879499","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011861983,0.0029387327,0.45342636,0.0021926921,0.0077471943,0.0023368746,0.0001491891,0.0005568546,0.5187901],"genre_scores_gemma":[0.73695916,0.015093295,0.1775728,0.0005885029,0.0010792488,0.00037985263,0.0007722827,0.00009047414,0.0674644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876755,0.000019469531,0.0005788489,0.00022613481,0.00021758364,0.0001904242],"domain_scores_gemma":[0.99854475,0.00021869282,0.00019773458,0.0006943154,0.0002690324,0.00007547361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004955634,0.00016724724,0.0001703808,0.00088501076,0.0004922562,0.0002840293,0.00070154626,0.00016245057,0.000052899548],"category_scores_gemma":[0.000040649345,0.00017412282,0.00006554176,0.00021871016,0.000319337,0.0009115618,0.0006388532,0.0007382379,0.00017391014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000051470315,0.000054806904,0.00013573036,0.00008076047,0.00002718119,3.6810047e-7,0.010409678,0.00026395448,0.000003178378,0.7978127,0.000044803804,0.19116168],"study_design_scores_gemma":[0.0017064767,0.0005896634,0.054148477,0.007900924,0.00019013211,0.00015430203,0.009085353,0.051989492,0.00006136799,0.15726301,0.71492165,0.001989142],"about_ca_topic_score_codex":0.0000037868012,"about_ca_topic_score_gemma":0.000003573275,"teacher_disagreement_score":0.7250972,"about_ca_system_score_codex":0.00015012932,"about_ca_system_score_gemma":0.000046281944,"threshold_uncertainty_score":0.71005225},"labels":[],"label_agreement":null},{"id":"W4400055183","doi":"10.1007/978-3-031-61816-1_6","title":"NBD-Tree: Neural Bounded Deformation Tree for Collision Culling of Deformable Objects","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Tree (set theory); Bounded function; Computer science; Culling; Artificial intelligence; Collision; Pattern recognition (psychology); Mathematics; Combinatorics; Biology; Mathematical analysis; Computer security; Ecology","score_opus":0.023975836138464147,"score_gpt":0.2855369790007874,"score_spread":0.26156114286232324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400055183","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007299848,0.0012905996,0.7884031,0.00012887045,0.00027309352,0.000872188,0.00005301151,0.00039113758,0.20785803],"genre_scores_gemma":[0.6094436,0.0069244746,0.38150087,0.00020241903,0.0000615914,0.00016895817,0.00047822113,0.00004952891,0.0011703119],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998681,0.000005454532,0.0007627363,0.000121131365,0.00026030766,0.00016936337],"domain_scores_gemma":[0.9986353,0.00013188788,0.00018966648,0.0007158148,0.00027604168,0.000051324227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043761893,0.0001827864,0.00027831743,0.0008842849,0.00018873315,0.00016733703,0.0007631359,0.000106614956,0.0000019397985],"category_scores_gemma":[0.000024467208,0.00017178622,0.000076471915,0.0004461427,0.00034590502,0.0036577755,0.00038487907,0.00026260747,0.000009432172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015049497,0.0000190332,0.000013295059,0.00077046285,0.000041326457,1.8692839e-7,0.0028676689,0.113832645,0.00014933919,0.30415118,0.00037821298,0.5777616],"study_design_scores_gemma":[0.00012360042,0.00003891649,0.000020742105,0.0002290027,0.000017811142,0.000005538034,0.000029825636,0.95485467,0.00041333475,0.01755722,0.026533287,0.00017604881],"about_ca_topic_score_codex":0.000005195105,"about_ca_topic_score_gemma":0.000019997511,"teacher_disagreement_score":0.841022,"about_ca_system_score_codex":0.00020268332,"about_ca_system_score_gemma":0.000049176106,"threshold_uncertainty_score":0.70052385},"labels":[],"label_agreement":null},{"id":"W4400136137","doi":"10.1007/978-3-031-62843-6","title":"Artificial intelligence and Machine Learning","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Univerzita Pardubice; Slezská Univerzita v Opavě; Uniwersytet Mikolaja Kopernika w Toruniu; Wojskowa Akademia Techniczna; Politechnika Wrocławska; Politechnika Warszawska; York University; Uniwersytet Szczeciński; Politechnika Poznańska; Západočeská Univerzita v Plzni","keywords":"Computer science; Artificial intelligence; Machine learning","score_opus":0.056795207967137475,"score_gpt":0.3151915606809349,"score_spread":0.2583963527137974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400136137","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014328102,0.0035508901,0.9325934,0.00013775163,0.00013993043,0.00014940862,0.000021966865,0.0004842289,0.06290809],"genre_scores_gemma":[0.092354044,0.06348309,0.8412042,0.00039671347,0.000118995216,0.000092863746,0.0006435339,0.000057612186,0.0016488932],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993126,0.00000829833,0.0003344133,0.000106517145,0.00012997119,0.000108244814],"domain_scores_gemma":[0.99927336,0.00008621858,0.00004713969,0.0004945347,0.00006234738,0.00003640423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042941648,0.00011478693,0.000110860274,0.0005406915,0.00017158627,0.00035883574,0.00066964445,0.00006536632,0.0000020700047],"category_scores_gemma":[0.000034312186,0.000118392745,0.000008598366,0.0003387008,0.00052332156,0.0027514463,0.00088312593,0.00053686055,0.000022735989],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.2237895e-7,0.000001946919,0.0000042424645,0.00011256038,0.0000018556437,1.5958287e-7,0.0009548771,0.0027010613,0.0000033341614,0.06394745,0.00032801172,0.9319441],"study_design_scores_gemma":[0.0000060532557,0.000009723384,0.000008865219,0.00020164977,0.0000019562094,0.0000093921635,0.000010298004,0.7910811,0.00004084171,0.027001914,0.18150881,0.00011940046],"about_ca_topic_score_codex":0.0000018243113,"about_ca_topic_score_gemma":0.000004272101,"teacher_disagreement_score":0.9318247,"about_ca_system_score_codex":0.00009920128,"about_ca_system_score_gemma":0.00007347071,"threshold_uncertainty_score":0.4827916},"labels":[],"label_agreement":null},{"id":"W4400187156","doi":"10.1007/978-3-031-64315-6_40","title":"Leveraging GPT-4 for Accuracy in Education: A Comparative Study on Retrieval-Augmented Generation in MOOCs","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Computer science; Information retrieval; Thesaurus; Multimedia; World Wide Web; Natural language processing","score_opus":0.1403529106960152,"score_gpt":0.375658543416284,"score_spread":0.23530563272026883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400187156","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023764532,0.002898982,0.7224041,0.0039437427,0.005354165,0.010521792,0.000028781935,0.00035225082,0.2307316],"genre_scores_gemma":[0.9708411,0.00038839082,0.021247553,0.0005424846,0.00015254169,0.00022798662,0.00006992853,0.000016416683,0.0065135965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794155,0.00006551469,0.00092389435,0.00042969626,0.00041051328,0.0002287985],"domain_scores_gemma":[0.9977641,0.0003659134,0.00030934735,0.001148074,0.00035884118,0.000053692303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017461677,0.00024350177,0.00031333577,0.0019038601,0.00029029808,0.00085331255,0.001632349,0.00008756296,0.0000019817128],"category_scores_gemma":[0.00007268959,0.00024522434,0.000041335883,0.0007578939,0.00013455906,0.003489492,0.00081146136,0.00056777266,0.00003635834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008630818,0.00012503282,0.00014644445,0.00004503727,0.000008133603,7.6719346e-7,0.031340808,0.006108467,0.000011231898,0.92522186,0.00013162721,0.03685196],"study_design_scores_gemma":[0.0005253647,0.00023958158,0.0020088397,0.0010410219,0.0000048335232,0.0000075694547,0.001131964,0.8737441,0.000031477433,0.0043358626,0.11650561,0.0004238367],"about_ca_topic_score_codex":0.00004089506,"about_ca_topic_score_gemma":0.000037764592,"teacher_disagreement_score":0.94707656,"about_ca_system_score_codex":0.0005459582,"about_ca_system_score_gemma":0.0004715897,"threshold_uncertainty_score":0.99999577},"labels":[],"label_agreement":null},{"id":"W4400218313","doi":"10.1007/978-981-97-4393-3_19","title":"Safety Zone and Its Utilization in Collision Avoidance Control of Industrial Robot","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Collision avoidance; Control (management); Robot; Collision; Computer science; Simulation; Real-time computing; Environmental science; Computer security; Artificial intelligence","score_opus":0.07538811579882493,"score_gpt":0.30358851325907543,"score_spread":0.2282003974602505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400218313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010900059,0.002096277,0.9718201,0.00093981455,0.0004990086,0.000642533,0.00003700257,0.00006553363,0.023790743],"genre_scores_gemma":[0.6537418,0.01310506,0.32969967,0.000823605,0.0001272169,0.000069894166,0.00014223279,0.000034179582,0.0022563748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981212,0.000047008103,0.0009109815,0.0002968313,0.000435521,0.0001884601],"domain_scores_gemma":[0.997908,0.00035181013,0.00035826786,0.0010207226,0.00028598684,0.00007523892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016060851,0.00019204846,0.0003290063,0.0011666572,0.00018212118,0.00028635585,0.0017386351,0.00018172091,0.0000014073973],"category_scores_gemma":[0.00009456289,0.00019379256,0.000025373227,0.0007512138,0.00042827794,0.003829079,0.0013992935,0.0005055548,0.00001368815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001033292,0.000023166145,0.0001439819,0.000066816894,0.000007582168,0.0000015570783,0.0026910617,0.018194422,0.000010413999,0.7747306,0.00004692784,0.2040731],"study_design_scores_gemma":[0.00060105126,0.000056341712,0.00085304066,0.0008041025,0.000004988137,0.000017130573,0.000011680239,0.9876928,0.000016777796,0.0024096912,0.0073455335,0.00018689415],"about_ca_topic_score_codex":0.000012280016,"about_ca_topic_score_gemma":0.000004969775,"teacher_disagreement_score":0.96949834,"about_ca_system_score_codex":0.00013555292,"about_ca_system_score_gemma":0.00029651605,"threshold_uncertainty_score":0.7902631},"labels":[],"label_agreement":null},{"id":"W4400248355","doi":"10.1007/978-3-031-58181-6_38","title":"ConvMTL: Multi-task Learning via Self-supervised Learning for Simultaneous Dense Predictions","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Computer science; Task (project management); Artificial intelligence; Supervised learning; Machine learning; Engineering; Artificial neural network","score_opus":0.03268561146353205,"score_gpt":0.28626544466361087,"score_spread":0.2535798332000788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400248355","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002304973,0.00067547965,0.95476466,0.0005637102,0.0005370389,0.0007054559,0.0000072663984,0.0006556922,0.042067647],"genre_scores_gemma":[0.20622973,0.0052584196,0.76460123,0.0011719003,0.00015449671,0.00023031657,0.0002701813,0.0000682491,0.02201548],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759847,0.00007002375,0.00092552626,0.0005033657,0.0005121071,0.0003905337],"domain_scores_gemma":[0.9964361,0.0010549003,0.0003926033,0.001229356,0.00069636345,0.000190649],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015072094,0.0003385101,0.0003319222,0.0012646898,0.0013697982,0.0011852911,0.0024095443,0.00020761664,0.000009033856],"category_scores_gemma":[0.00025394507,0.00035904627,0.00010947719,0.0006254661,0.000527181,0.004392595,0.0017667584,0.0013184405,0.00018295836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008340328,0.00004487451,0.00006449712,0.00018260234,0.000045423138,0.0000046152413,0.018169235,0.09253634,0.000021838818,0.42188928,0.00012349931,0.46690947],"study_design_scores_gemma":[0.00033405295,0.00008303141,0.00004343868,0.00015292954,0.000013617447,0.00004210321,0.000074368894,0.7116804,0.0000015158942,0.0015146733,0.2857874,0.00027248854],"about_ca_topic_score_codex":0.000007993523,"about_ca_topic_score_gemma":0.0000070974907,"teacher_disagreement_score":0.6191441,"about_ca_system_score_codex":0.00023206962,"about_ca_system_score_gemma":0.00035336136,"threshold_uncertainty_score":0.99993026},"labels":[],"label_agreement":null},{"id":"W4400438538","doi":"10.1007/978-3-031-63787-2_1","title":"Seeking Interpretability and Explainability in Binary Activated Neural Networks","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Interpretability; Binary number; Artificial neural network; Computer science; Artificial intelligence; Mathematics; Arithmetic","score_opus":0.036713966182022446,"score_gpt":0.30121830911232206,"score_spread":0.2645043429302996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400438538","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017457802,0.00310868,0.81524634,0.005530919,0.001592729,0.0021177614,0.00001462911,0.0005535999,0.15437752],"genre_scores_gemma":[0.98672986,0.0007381044,0.011907803,0.00038565043,0.000019395593,0.000035436908,0.00001013112,0.000008316942,0.00016532448],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794436,0.00006772355,0.000859034,0.0004959085,0.0003054248,0.00032756565],"domain_scores_gemma":[0.9969778,0.00045768823,0.00020063118,0.0020026527,0.00025125832,0.00010998867],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019816635,0.00025810933,0.00029323163,0.0010608045,0.00033363502,0.00096308475,0.0025352398,0.0001594347,0.000004513501],"category_scores_gemma":[0.00009775773,0.00026051493,0.00004116304,0.0008666002,0.0012155871,0.008920732,0.004720196,0.00086139713,0.000013625224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007506354,0.000029739445,0.0005383287,0.00008926723,0.000004715275,0.0000032169396,0.0071082404,0.005390376,0.000018893461,0.7312997,0.000020132777,0.25548992],"study_design_scores_gemma":[0.00005990988,0.00004663281,0.0014347311,0.00023122698,0.0000022885504,0.00001694979,0.00008261006,0.965652,0.00001694778,0.029093927,0.0031160747,0.00024672973],"about_ca_topic_score_codex":0.0000692099,"about_ca_topic_score_gemma":0.00007272075,"teacher_disagreement_score":0.969272,"about_ca_system_score_codex":0.00032530446,"about_ca_system_score_gemma":0.00015474307,"threshold_uncertainty_score":0.9999847},"labels":[],"label_agreement":null},{"id":"W4400438864","doi":"10.1007/978-3-031-63797-1","title":"Explainable Artificial Intelligence","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Oak Ridge National Laboratory; Università degli Studi di Perugia; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Università degli Studi di Torino; Universidad de Granada; University of Illinois at Urbana-Champaign; Université de Bordeaux; Tallinna Tehnikaülikool; Universiteit Utrecht; Università degli Studi di Pavia; University of Waterloo; Kungliga Tekniska Högskolan; Universiteit Maastricht; Aristotle University of Thessaloniki; Universita degli Studi di Bari Aldo Moro; Dublin City University; Haute école Spécialisée de Suisse Occidentale; Technische Universität Berlin; University of Galway; Imperial College London; Università degli Studi di Napoli Federico II","keywords":"Computer science; Thesaurus; Artificial intelligence; Information retrieval","score_opus":0.06743547468698971,"score_gpt":0.327571071654115,"score_spread":0.2601355969671253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400438864","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012188337,0.0008039643,0.7595713,0.0020880685,0.0008431455,0.0004274172,0.0000075162916,0.00024668046,0.2359997],"genre_scores_gemma":[0.07866707,0.012172459,0.86268204,0.0062312535,0.0006473735,0.00054949673,0.0002198228,0.00009468594,0.038735766],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971247,0.00006450876,0.0010960405,0.00053389097,0.00067925215,0.00050166034],"domain_scores_gemma":[0.99557275,0.00036820208,0.00026292595,0.0031019326,0.00052773766,0.00016643877],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0021584292,0.00031009017,0.00030657434,0.0019049245,0.0006416037,0.0025335192,0.006682411,0.00018285404,0.000013691937],"category_scores_gemma":[0.00013297732,0.0003175061,0.000068565656,0.0021781651,0.001283395,0.012617327,0.005253973,0.00080348755,0.0011328342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.328373e-7,0.000014997164,0.0000010625668,0.00004648568,0.0000027147858,0.0000018440692,0.0024614965,0.00034776525,0.0000027166616,0.729669,0.00089040445,0.2665607],"study_design_scores_gemma":[0.000014155263,0.000048069272,0.000010387192,0.00028046587,0.0000039288807,0.00002494869,0.00010947441,0.5907298,0.00016836164,0.2587889,0.14950214,0.00031938148],"about_ca_topic_score_codex":0.000029054809,"about_ca_topic_score_gemma":0.00002787767,"teacher_disagreement_score":0.590382,"about_ca_system_score_codex":0.00051212986,"about_ca_system_score_gemma":0.0013381555,"threshold_uncertainty_score":0.9999277},"labels":[],"label_agreement":null},{"id":"W4400438951","doi":"10.1007/978-3-031-63800-8_7","title":"Evaluating the Faithfulness of Causality in Saliency-Based Explanations of Deep Learning Models for Temporal Colour Constancy","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Color perception and design","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada); University of British Columbia","funders":"","keywords":"Causality (physics); Artificial intelligence; Computer science; Natural language processing; Cognitive psychology; Psychology; Physics","score_opus":0.2211839654853968,"score_gpt":0.4321309570282689,"score_spread":0.21094699154287214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400438951","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005982363,0.00077676104,0.6597317,0.001054848,0.00052523613,0.0020660544,0.00013374079,0.00006145173,0.3296679],"genre_scores_gemma":[0.9855024,0.00006382532,0.013413027,0.00014246882,0.000008494864,0.000149518,0.00008033206,0.000006812741,0.00063311245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984889,0.00009084474,0.0008603515,0.00015927565,0.0002727822,0.00012783166],"domain_scores_gemma":[0.9975832,0.0007937274,0.00041359704,0.0007331003,0.00044761234,0.000028739585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025249082,0.00011982062,0.00022915655,0.00072029047,0.00020959043,0.00006462363,0.00076480233,0.000102417456,0.000045219498],"category_scores_gemma":[0.00007188024,0.0001036494,0.000051521398,0.00038286048,0.0008748378,0.00069759315,0.00023655698,0.00032452217,0.000006958292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026545047,0.000031652267,0.0001725006,0.000079448124,0.0000072638186,7.3105824e-8,0.010477603,0.021083353,0.0000065066033,0.9117852,0.000038727478,0.05629113],"study_design_scores_gemma":[0.00047109684,0.00014605022,0.001439358,0.00020799127,0.00001408373,0.0000026909452,0.00093415374,0.9697658,0.0000043928935,0.024022102,0.0028612697,0.00013102431],"about_ca_topic_score_codex":0.0000596586,"about_ca_topic_score_gemma":0.00013357427,"teacher_disagreement_score":0.97952,"about_ca_system_score_codex":0.00008352011,"about_ca_system_score_gemma":0.00026725372,"threshold_uncertainty_score":0.42266998},"labels":[],"label_agreement":null},{"id":"W4400439049","doi":"10.1007/978-3-031-63803-9","title":"Explainable Artificial Intelligence","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Università degli Studi di Perugia; Haute école Spécialisée de Suisse Occidentale; Technological University Dublin; University of Illinois at Urbana-Champaign; Universidade do Minho; Università di Pisa; Università degli Studi di Salerno; Universität Paderborn; Università degli Studi di Torino; Universidad de Granada; Università di Bologna; Tallinna Tehnikaülikool; Universidade de Coimbra; Università degli Studi di Camerino; Universiteit Utrecht; Universita degli Studi di Bari Aldo Moro; University of Waterloo; Technische Universiteit Eindhoven; Universiteit Maastricht; Universität Bielefeld; University of Texas at San Antonio; Università degli Studi di Milano-Bicocca; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Universidad Complutense de Madrid; Dublin City University; Università degli Studi di Milano; Trinity College Dublin; Sapienza Università di Roma; Technische Universität Berlin; University of Galway; University College Dublin; Université de Bordeaux; Università degli Studi di Napoli Federico II; Oak Ridge National Laboratory; Imperial College London; Kungliga Tekniska Högskolan; Università degli Studi di Siena; Aristotle University of Thessaloniki; Università degli Studi di Pavia; Sveučilište u Zagrebu","keywords":"Computer science; Thesaurus; Artificial intelligence; Information retrieval","score_opus":0.06743547468698971,"score_gpt":0.327571071654115,"score_spread":0.2601355969671253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400439049","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012188337,0.0008039643,0.7595713,0.0020880685,0.0008431455,0.0004274172,0.0000075162916,0.00024668046,0.2359997],"genre_scores_gemma":[0.07866707,0.012172459,0.86268204,0.0062312535,0.0006473735,0.00054949673,0.0002198228,0.00009468594,0.038735766],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971247,0.00006450876,0.0010960405,0.00053389097,0.00067925215,0.00050166034],"domain_scores_gemma":[0.99557275,0.00036820208,0.00026292595,0.0031019326,0.00052773766,0.00016643877],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0021584292,0.00031009017,0.00030657434,0.0019049245,0.0006416037,0.0025335192,0.006682411,0.00018285404,0.000013691937],"category_scores_gemma":[0.00013297732,0.0003175061,0.000068565656,0.0021781651,0.001283395,0.012617327,0.005253973,0.00080348755,0.0011328342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.328373e-7,0.000014997164,0.0000010625668,0.00004648568,0.0000027147858,0.0000018440692,0.0024614965,0.00034776525,0.0000027166616,0.729669,0.00089040445,0.2665607],"study_design_scores_gemma":[0.000014155263,0.000048069272,0.000010387192,0.00028046587,0.0000039288807,0.00002494869,0.00010947441,0.5907298,0.00016836164,0.2587889,0.14950214,0.00031938148],"about_ca_topic_score_codex":0.000029054809,"about_ca_topic_score_gemma":0.00002787767,"teacher_disagreement_score":0.590382,"about_ca_system_score_codex":0.00051212986,"about_ca_system_score_gemma":0.0013381555,"threshold_uncertainty_score":0.9999277},"labels":[],"label_agreement":null},{"id":"W4400439180","doi":"10.1007/978-3-031-63800-8_11","title":"Investigating Calibrated Classification Scores Through the Lens of Interpretability","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interpretability; Computer science; Information retrieval; Optometry; Artificial intelligence; Natural language processing; Medicine","score_opus":0.2580863818663159,"score_gpt":0.41086528238041237,"score_spread":0.15277890051409648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400439180","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015477418,0.0007518003,0.13132598,0.011153433,0.00035350016,0.0012603627,0.00014310268,0.00020423596,0.85325986],"genre_scores_gemma":[0.934367,0.00081790437,0.061993897,0.00079379044,0.00003258211,0.00007808079,0.000056434103,0.000014505017,0.0018458036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972433,0.000056913203,0.0014417714,0.00031714447,0.000795695,0.00014516526],"domain_scores_gemma":[0.9944883,0.0012524822,0.0007239345,0.0027012965,0.000790971,0.00004302262],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00339744,0.00017161306,0.00025861277,0.00053619215,0.0004341166,0.0006481431,0.0033917956,0.000117041185,0.000022550877],"category_scores_gemma":[0.00064377795,0.000115052,0.00007208774,0.0011022193,0.0036038172,0.00342989,0.0020136142,0.00050602545,0.000058495334],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.5947287e-7,0.000006159748,0.00013122948,0.000015173867,0.0000027301708,1.2765905e-8,0.0022809985,0.00008437469,0.000015362131,0.95026904,0.0006189207,0.04657523],"study_design_scores_gemma":[0.000046029654,0.000027726706,0.0017787621,0.00029072686,0.000008884897,0.000005519367,0.00015423675,0.38538653,0.00003242571,0.4800195,0.13210195,0.00014771133],"about_ca_topic_score_codex":0.000064747044,"about_ca_topic_score_gemma":0.000035621146,"teacher_disagreement_score":0.93281925,"about_ca_system_score_codex":0.000081797094,"about_ca_system_score_gemma":0.00027175195,"threshold_uncertainty_score":0.9991078},"labels":[],"label_agreement":null},{"id":"W4400439200","doi":"10.1007/978-3-031-63800-8","title":"Explainable Artificial Intelligence","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Oak Ridge National Laboratory; Università degli Studi di Perugia; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Università degli Studi di Torino; Universidad de Granada; University of Illinois at Urbana-Champaign; Université de Bordeaux; Tallinna Tehnikaülikool; Universiteit Utrecht; Università degli Studi di Pavia; University of Waterloo; Kungliga Tekniska Högskolan; Universiteit Maastricht; Aristotle University of Thessaloniki; Universita degli Studi di Bari Aldo Moro; Dublin City University; Haute école Spécialisée de Suisse Occidentale; Technische Universität Berlin; University of Galway; Imperial College London; Università degli Studi di Napoli Federico II","keywords":"Computer science; Thesaurus; Information retrieval; Artificial intelligence","score_opus":0.06743547468698971,"score_gpt":0.327571071654115,"score_spread":0.2601355969671253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400439200","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012188337,0.0008039643,0.7595713,0.0020880685,0.0008431455,0.0004274172,0.0000075162916,0.00024668046,0.2359997],"genre_scores_gemma":[0.07866707,0.012172459,0.86268204,0.0062312535,0.0006473735,0.00054949673,0.0002198228,0.00009468594,0.038735766],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971247,0.00006450876,0.0010960405,0.00053389097,0.00067925215,0.00050166034],"domain_scores_gemma":[0.99557275,0.00036820208,0.00026292595,0.0031019326,0.00052773766,0.00016643877],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0021584292,0.00031009017,0.00030657434,0.0019049245,0.0006416037,0.0025335192,0.006682411,0.00018285404,0.000013691937],"category_scores_gemma":[0.00013297732,0.0003175061,0.000068565656,0.0021781651,0.001283395,0.012617327,0.005253973,0.00080348755,0.0011328342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.328373e-7,0.000014997164,0.0000010625668,0.00004648568,0.0000027147858,0.0000018440692,0.0024614965,0.00034776525,0.0000027166616,0.729669,0.00089040445,0.2665607],"study_design_scores_gemma":[0.000014155263,0.000048069272,0.000010387192,0.00028046587,0.0000039288807,0.00002494869,0.00010947441,0.5907298,0.00016836164,0.2587889,0.14950214,0.00031938148],"about_ca_topic_score_codex":0.000029054809,"about_ca_topic_score_gemma":0.00002787767,"teacher_disagreement_score":0.590382,"about_ca_system_score_codex":0.00051212986,"about_ca_system_score_gemma":0.0013381555,"threshold_uncertainty_score":0.9999277},"labels":[],"label_agreement":null},{"id":"W4400439306","doi":"10.1007/978-3-031-63787-2","title":"Explainable Artificial Intelligence","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Università degli Studi di Perugia; Haute école Spécialisée de Suisse Occidentale; Technological University Dublin; University of Illinois at Urbana-Champaign; Universidade do Minho; Università di Pisa; Università degli Studi di Salerno; Universität Paderborn; Università degli Studi di Torino; Universidad de Granada; Università di Bologna; Tallinna Tehnikaülikool; Universidade de Coimbra; Università degli Studi di Camerino; Universiteit Utrecht; Universita degli Studi di Bari Aldo Moro; University of Waterloo; Technische Universiteit Eindhoven; Universiteit Maastricht; Universität Bielefeld; University of Texas at San Antonio; Università degli Studi di Milano-Bicocca; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Universidad Complutense de Madrid; Dublin City University; Università degli Studi di Milano; Trinity College Dublin; Sapienza Università di Roma; Technische Universität Berlin; University of Galway; University College Dublin; Université de Bordeaux; Università degli Studi di Napoli Federico II; Oak Ridge National Laboratory; Imperial College London; Kungliga Tekniska Högskolan; Università degli Studi di Siena; Aristotle University of Thessaloniki; Università degli Studi di Pavia; Sveučilište u Zagrebu","keywords":"Computer science; Artificial intelligence; Thesaurus; Information retrieval","score_opus":0.06743547468698971,"score_gpt":0.327571071654115,"score_spread":0.2601355969671253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400439306","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012188337,0.0008039643,0.7595713,0.0020880685,0.0008431455,0.0004274172,0.0000075162916,0.00024668046,0.2359997],"genre_scores_gemma":[0.07866707,0.012172459,0.86268204,0.0062312535,0.0006473735,0.00054949673,0.0002198228,0.00009468594,0.038735766],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971247,0.00006450876,0.0010960405,0.00053389097,0.00067925215,0.00050166034],"domain_scores_gemma":[0.99557275,0.00036820208,0.00026292595,0.0031019326,0.00052773766,0.00016643877],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0021584292,0.00031009017,0.00030657434,0.0019049245,0.0006416037,0.0025335192,0.006682411,0.00018285404,0.000013691937],"category_scores_gemma":[0.00013297732,0.0003175061,0.000068565656,0.0021781651,0.001283395,0.012617327,0.005253973,0.00080348755,0.0011328342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.328373e-7,0.000014997164,0.0000010625668,0.00004648568,0.0000027147858,0.0000018440692,0.0024614965,0.00034776525,0.0000027166616,0.729669,0.00089040445,0.2665607],"study_design_scores_gemma":[0.000014155263,0.000048069272,0.000010387192,0.00028046587,0.0000039288807,0.00002494869,0.00010947441,0.5907298,0.00016836164,0.2587889,0.14950214,0.00031938148],"about_ca_topic_score_codex":0.000029054809,"about_ca_topic_score_gemma":0.00002787767,"teacher_disagreement_score":0.590382,"about_ca_system_score_codex":0.00051212986,"about_ca_system_score_gemma":0.0013381555,"threshold_uncertainty_score":0.9999277},"labels":[],"label_agreement":null},{"id":"W4400452414","doi":"10.1007/978-981-97-3948-6_19","title":"Optimal Deception Attacks on Remote State Estimation with Heterogeneous Vulnerabilities","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Deception; State (computer science); Computer science; Computer security; Estimation; Political science; Law; Algorithm; Engineering","score_opus":0.01772500418254807,"score_gpt":0.25957220219589106,"score_spread":0.24184719801334298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400452414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016112585,0.0015895613,0.66545546,0.0005580807,0.0012861473,0.0011735356,0.00010018179,0.00080812187,0.31291634],"genre_scores_gemma":[0.77713907,0.013375675,0.20407276,0.0006158148,0.0001323941,0.000057693265,0.00035502252,0.00008223496,0.0041693244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897933,0.000009253125,0.00037902515,0.00016212327,0.00030729675,0.00016295785],"domain_scores_gemma":[0.99886715,0.00010094691,0.00006532754,0.00078932184,0.00011547598,0.00006179824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032290016,0.00019355494,0.00015563778,0.0005892111,0.00023455768,0.0003403327,0.00058670406,0.00008434046,0.000008511459],"category_scores_gemma":[0.000009040482,0.0001710329,0.000025660054,0.00019619979,0.000657353,0.001744743,0.00023977658,0.00043638604,0.00010453199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005757943,0.0000042071647,0.0000024576125,0.00010333177,0.000007385245,7.1775787e-7,0.0024676078,0.8766617,0.0000022832128,0.015452716,0.00008784138,0.10520395],"study_design_scores_gemma":[0.0000941762,0.00007975453,0.000062363855,0.00042618427,0.000004669211,0.000039293685,0.000019254476,0.97722495,0.00003403959,0.0026244782,0.019175248,0.00021556934],"about_ca_topic_score_codex":0.000005380881,"about_ca_topic_score_gemma":0.000019316903,"teacher_disagreement_score":0.7610265,"about_ca_system_score_codex":0.00016340597,"about_ca_system_score_gemma":0.000061990206,"threshold_uncertainty_score":0.6974519},"labels":[],"label_agreement":null},{"id":"W4400725025","doi":"10.1007/978-3-031-64359-0_9","title":"Comparison of Tools and Methods for Technology-Assisted Review","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Information retrieval","score_opus":0.08852392516551118,"score_gpt":0.4451655094585418,"score_spread":0.3566415842930306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400725025","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000019988815,0.02769907,0.919766,0.003957247,0.0002030375,0.00050182396,0.000013492792,0.0001009654,0.04775633],"genre_scores_gemma":[0.0007624907,0.0136292735,0.98425764,0.00039597906,0.000011026698,0.000042964188,0.000026581069,0.000005619344,0.0008684237],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872553,0.00002726875,0.0007107756,0.00023239001,0.00017121441,0.00013283077],"domain_scores_gemma":[0.9975419,0.0004229719,0.00034660698,0.0013237975,0.00031687762,0.000047857582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017454769,0.00015402492,0.00039197615,0.00087229634,0.00021614999,0.0002902823,0.002002447,0.00010289483,0.00000165774],"category_scores_gemma":[0.00013773124,0.00013814896,0.000043270386,0.00055434037,0.00066600105,0.0018401005,0.0019887544,0.00039124445,0.0000055214737],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.0353778e-7,0.0000038062512,0.000007138859,0.0002628942,0.000002922923,1.7339504e-8,0.00018774215,0.0000052683135,0.0000018777864,0.41725832,0.00009756021,0.5821723],"study_design_scores_gemma":[0.00010209461,0.000070726055,0.000119339464,0.0019730036,0.000013788744,0.000017809434,0.000008609184,0.5701528,0.00001601395,0.022422759,0.40493557,0.00016749577],"about_ca_topic_score_codex":0.000001635351,"about_ca_topic_score_gemma":6.8082016e-7,"teacher_disagreement_score":0.5820047,"about_ca_system_score_codex":0.00003475029,"about_ca_system_score_gemma":0.00012207385,"threshold_uncertainty_score":0.5633551},"labels":[],"label_agreement":null},{"id":"W4400725186","doi":"10.1007/978-3-031-64359-0_24","title":"Limitations of the Utility of Categorization in eDiscovery Review Efforts","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Categorization; Computer science; Information retrieval; Data science; Artificial intelligence","score_opus":0.09306055483829982,"score_gpt":0.2995506511540169,"score_spread":0.20649009631571708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400725186","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017924234,0.019961203,0.3892952,0.0197903,0.0012145721,0.0023757394,0.000053858523,0.00021835252,0.5669116],"genre_scores_gemma":[0.8282842,0.13024639,0.038773406,0.0007854744,0.0000131908355,0.00008382103,0.000058098845,0.00001052325,0.0017448883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984414,0.000022709342,0.0008888861,0.00017906885,0.00036519126,0.000102773025],"domain_scores_gemma":[0.9969857,0.00022148051,0.00048805293,0.0020039147,0.00028193754,0.000018920522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088792644,0.0001228565,0.0002273564,0.00069359236,0.00009850112,0.00010293766,0.0027973363,0.00008260805,0.0000030137533],"category_scores_gemma":[0.00013247541,0.00009616417,0.000054650158,0.0010838946,0.0009095195,0.0031738414,0.0019728662,0.0002654388,0.0000065219865],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.934592e-7,0.0000087309845,0.00006594279,0.00019597831,0.0000018105701,2.609756e-8,0.00036900767,0.000016394073,0.0000021731457,0.9042227,0.00024604984,0.09487084],"study_design_scores_gemma":[0.00033629467,0.000073544754,0.015605899,0.007298551,0.00003195427,0.0000125387805,0.000077945224,0.3155322,0.0003359552,0.39680642,0.26336107,0.0005276088],"about_ca_topic_score_codex":0.000011196703,"about_ca_topic_score_gemma":0.000019062194,"teacher_disagreement_score":0.828105,"about_ca_system_score_codex":0.000067591325,"about_ca_system_score_gemma":0.00032674757,"threshold_uncertainty_score":0.5198193},"labels":[],"label_agreement":null},{"id":"W4400975784","doi":"10.1007/978-3-031-65996-6_11","title":"Exploring the Role of Generative AI in Medical Microbiology Education: Enhancing Bacterial Identification Skills in Laboratory Students","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Identification (biology); Microbiology; Computational biology; Medical education; Biology; Medicine; Botany","score_opus":0.0958132226086765,"score_gpt":0.4154875283729805,"score_spread":0.319674305764304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400975784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93930113,0.00451026,0.0015993181,0.015530342,0.0055639804,0.0031014816,0.000048278704,0.00006303478,0.030282186],"genre_scores_gemma":[0.992269,0.004955672,0.0009281894,0.001053813,0.0001658358,0.00014988602,0.00015061586,0.000008487091,0.00031851826],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998243,0.0000536834,0.001096145,0.00018250222,0.00028622002,0.00013849183],"domain_scores_gemma":[0.99840564,0.00021758095,0.00021258397,0.0006677556,0.00043673223,0.000059731563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017432069,0.00011853607,0.0002178805,0.0009375778,0.00011566937,0.000102495884,0.00068318774,0.00011842715,0.000019871388],"category_scores_gemma":[0.0001635162,0.00010148758,0.00002399681,0.00052332337,0.0005606798,0.0014009486,0.00038547098,0.0005504666,0.00003301962],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028647382,0.00027904662,0.004088473,0.00023830688,0.000015573649,8.232851e-7,0.04826699,0.00005333371,0.001751091,0.10939622,0.000107088,0.8357744],"study_design_scores_gemma":[0.0012448974,0.0008388405,0.22406295,0.025106555,0.000168122,0.00028130974,0.025367199,0.07673165,0.040095948,0.075003274,0.5287404,0.0023588515],"about_ca_topic_score_codex":0.00017061453,"about_ca_topic_score_gemma":0.00048050928,"teacher_disagreement_score":0.83341557,"about_ca_system_score_codex":0.00029865777,"about_ca_system_score_gemma":0.0015608943,"threshold_uncertainty_score":0.41385436},"labels":[],"label_agreement":null},{"id":"W4400977208","doi":"10.1007/978-3-031-65996-6_7","title":"Comparative Performance of GPT-4, RAG-Augmented GPT-4, and Students in MOOCs","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Computer science; Multimedia","score_opus":0.0499225043097927,"score_gpt":0.3260830684011841,"score_spread":0.27616056409139145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400977208","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13846852,0.008976626,0.26111072,0.0013127731,0.0028746866,0.0036191712,0.000049061793,0.0004058752,0.5831826],"genre_scores_gemma":[0.9746168,0.0026651633,0.016441336,0.00013834854,0.000024362998,0.000024482384,0.000011825316,0.00000823275,0.006069444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981999,0.00003231985,0.0007866866,0.0002789373,0.00050661777,0.00019557154],"domain_scores_gemma":[0.99826556,0.00014987585,0.00031299182,0.0009470869,0.00026360177,0.00006086121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011829565,0.00020620352,0.00035158527,0.0011069581,0.00019899613,0.0004423543,0.0021182266,0.00008657157,0.0000023823088],"category_scores_gemma":[0.000012046255,0.0001966524,0.000030474821,0.0004590048,0.0005012046,0.0033354077,0.002492186,0.00048750234,0.000028796821],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005127032,0.00002911892,0.0016340003,0.00017010694,0.000015931864,9.307601e-7,0.0135768065,0.001156996,0.000012997871,0.9416007,0.000029800423,0.04176751],"study_design_scores_gemma":[0.0004975852,0.00023469653,0.017554883,0.00285979,0.000009319368,0.000033182965,0.00021274884,0.8695188,0.00010495924,0.0026662487,0.1057635,0.0005442752],"about_ca_topic_score_codex":0.000027704464,"about_ca_topic_score_gemma":0.000009713153,"teacher_disagreement_score":0.93893445,"about_ca_system_score_codex":0.00013058793,"about_ca_system_score_gemma":0.00012564864,"threshold_uncertainty_score":0.8019252},"labels":[],"label_agreement":null},{"id":"W4401582011","doi":"10.1007/978-3-031-68165-3","title":"Cloud Computing and Services Science","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Magyar Tudományos Akadémia Számítástechnikai és Automatizálási Kutatóintézet; National Technical University of Athens; Politechnika Swietokrzyska w Kielcach; Universidade de Santiago de Compostela; Universidade de Pernambuco; Universidade Federal de Pernambuco; Università di Pisa; Universidade Federal de Santa Catarina; Universidade Estadual de Campinas; Thammasat University; Technological University Dublin; Universitetet i Oslo; Universidade Federal do Rio Grande do Sul; Universidad de Granada; National and Kapodistrian University of Athens; Szegedi Tudományegyetem; Universidad de Sevilla; Università degli Studi di Parma; Universidad de Murcia; Blekinge Tekniska Högskola; Ben-Gurion University of the Negev; Università degli Studi di Padova; Universität Wien; University of Surrey; Edinburgh Napier University; York University; University of Bristol; University of Macedonia; Università degli Studi di Messina; Newcastle University; Università degli Studi di Milano; Universitat de les Illes Balears; Università di Catania; Universität Ulm; Università Degli Studi di Modena e Reggio Emila; University of the West of England; Universitetet i Stavanger; Shandong University; Oklahoma State University; University of Balamand; National Institute of Advanced Industrial Science and Technology; University of New England","keywords":"Cloud computing; Computer science; World Wide Web; Data science; Information retrieval; Operating system","score_opus":0.05772896819241703,"score_gpt":0.3225381202354371,"score_spread":0.2648091520430201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401582011","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051169507,0.0034877183,0.020722972,0.0032725267,0.003787383,0.0009851186,0.00003588725,0.0004373842,0.96215403],"genre_scores_gemma":[0.9297113,0.007860861,0.032528695,0.019045664,0.0031981613,0.00005267711,0.000670187,0.00007912755,0.0068533765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998438,0.000004330976,0.00049017306,0.00032164305,0.0004816912,0.00026414712],"domain_scores_gemma":[0.9981178,0.000075466465,0.0002575179,0.0010176648,0.00050698686,0.000024562221],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0015954025,0.00019701419,0.00019140219,0.001688851,0.00085139676,0.0036358985,0.0025086985,0.00007853049,0.0000098585015],"category_scores_gemma":[0.00004139478,0.0001809977,0.000019292638,0.0018340792,0.0024722114,0.015947731,0.0059503256,0.00037373637,0.00021509611],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036450904,0.000018533647,0.00042237312,0.0010733187,0.0000046426426,6.057086e-7,0.0011281499,0.00008309594,0.000007028954,0.65736854,0.0035699853,0.3363201],"study_design_scores_gemma":[0.00007098678,0.0000049862724,0.001426938,0.0007212609,0.000011768255,0.000011351009,0.00007803213,0.4233033,0.000002718644,0.008018664,0.5660977,0.0002523145],"about_ca_topic_score_codex":0.00007155199,"about_ca_topic_score_gemma":0.00002930721,"teacher_disagreement_score":0.9553007,"about_ca_system_score_codex":0.00009305605,"about_ca_system_score_gemma":0.00029949515,"threshold_uncertainty_score":0.9978157},"labels":[],"label_agreement":null},{"id":"W4401762053","doi":"10.1007/978-3-031-66705-3_1","title":"Geometrical Realization for Time Series Forecasting","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Realization (probability); Series (stratigraphy); Computer science; Mathematics; Statistics; Geology; Paleontology","score_opus":0.04716604488706991,"score_gpt":0.27488184189272935,"score_spread":0.22771579700565944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401762053","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003966504,0.0006618015,0.78863734,0.00095320103,0.00023425417,0.00037024493,0.000033814777,0.00014113629,0.20896423],"genre_scores_gemma":[0.009080387,0.003524532,0.94468683,0.0009014063,0.00026543197,0.000121242636,0.00041800225,0.000049062146,0.04095311],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837434,0.000010068203,0.0007121468,0.00031645293,0.00034475632,0.00024225302],"domain_scores_gemma":[0.9976884,0.0002394817,0.0002954,0.0012245907,0.00046882618,0.000083312756],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011376615,0.00020246535,0.00026863595,0.0015178141,0.0005321212,0.0012628131,0.0020464133,0.000114110764,0.000010197811],"category_scores_gemma":[0.000099900404,0.00019399256,0.00008049533,0.0010291782,0.0004358671,0.007051372,0.0020985443,0.0002432029,0.000059323324],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012227397,0.000003156963,0.0000021169235,0.000034617577,0.00000614569,1.8790233e-7,0.00043006576,0.00025649756,8.8658044e-7,0.7476356,0.00024456394,0.25138494],"study_design_scores_gemma":[0.00007400976,0.000054131993,0.0000200167,0.00014394874,0.0000094382385,0.000024083776,0.0000057611596,0.77800524,0.0000032097646,0.03197074,0.18950062,0.00018877794],"about_ca_topic_score_codex":0.0000045730353,"about_ca_topic_score_gemma":0.000004213957,"teacher_disagreement_score":0.77774876,"about_ca_system_score_codex":0.00011437312,"about_ca_system_score_gemma":0.0001586707,"threshold_uncertainty_score":0.999774},"labels":[],"label_agreement":null},{"id":"W4401768173","doi":"10.1007/978-3-031-66705-3_14","title":"Investigating a Semantic Similarity Loss Function for the Parallel Training of Abstractive and Extractive Scientific Document Summarizers","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Information retrieval; Similarity (geometry); Function (biology); Natural language processing; Semantic similarity; Artificial intelligence; Biology; Genetics","score_opus":0.08608398480217001,"score_gpt":0.314668130721619,"score_spread":0.22858414591944898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401768173","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005213566,0.0007152858,0.9846686,0.0016708558,0.0005402336,0.0007376974,0.000013746413,0.000046964575,0.011085225],"genre_scores_gemma":[0.7227679,0.00074710685,0.2751643,0.00040065075,0.00004697046,0.00009728907,0.000027074351,0.000011386601,0.0007372989],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984826,0.000019508694,0.0006040672,0.00032985938,0.00038031102,0.00018369539],"domain_scores_gemma":[0.9972569,0.00079300127,0.00038185666,0.0011523967,0.00035290682,0.00006295186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021695292,0.00016583575,0.00019983944,0.00050656224,0.0007223385,0.0009816816,0.0014675908,0.0000840155,0.0000011230587],"category_scores_gemma":[0.00008322146,0.00013812346,0.00004635599,0.00030226892,0.0014200016,0.004430947,0.0013307283,0.00040792412,0.0000025158095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020991051,0.0000049154874,0.000016327524,0.00008153661,0.000015759351,8.8850435e-8,0.011522176,0.0023535192,0.000009600029,0.8266149,0.0000210274,0.15935801],"study_design_scores_gemma":[0.00016551858,0.00003498229,0.0005917086,0.0002873271,0.000019605155,0.000009635392,0.0002993872,0.85808665,0.0000074441377,0.13184969,0.008494596,0.0001534602],"about_ca_topic_score_codex":0.000020441488,"about_ca_topic_score_gemma":0.000024639665,"teacher_disagreement_score":0.8557331,"about_ca_system_score_codex":0.00009163424,"about_ca_system_score_gemma":0.00033177613,"threshold_uncertainty_score":0.9466379},"labels":[],"label_agreement":null},{"id":"W4401784090","doi":"10.1007/978-3-031-66694-0_17","title":"Citation Polarity Identification in Scientific Research Articles Using Deep Learning Methods","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Identification (biology); Polarity (international relations); Citation; Computer science; Information retrieval; Data science; Library science; Chemistry; Botany; Biology; Biochemistry","score_opus":0.1929742432770527,"score_gpt":0.4777759264100746,"score_spread":0.2848016831330219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401784090","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004179615,0.00097598677,0.9821496,0.0004039466,0.00019542938,0.00035792758,0.0000015299837,0.0001542763,0.015343343],"genre_scores_gemma":[0.19762936,0.0007312869,0.8005236,0.000053533025,0.000016775704,0.00003214596,0.000030821062,0.000011573336,0.00097090384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99709237,0.00024022936,0.0009774191,0.00053132,0.0008258338,0.00033284805],"domain_scores_gemma":[0.9961043,0.00051644765,0.000313244,0.0020024127,0.0009820524,0.0000815326],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.011648099,0.00018340388,0.00023710709,0.005754588,0.0009531417,0.00278921,0.0030663048,0.00014408138,0.000003318331],"category_scores_gemma":[0.00031445367,0.00019886765,0.000049476726,0.0035447942,0.0014919254,0.010863685,0.0031317188,0.001149344,0.000050876664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.301662e-7,0.00001039289,0.00005243911,0.000024076035,0.0000025841396,3.5648006e-7,0.0031619626,0.0010007323,0.00034338073,0.60838646,0.0000039352026,0.38701308],"study_design_scores_gemma":[0.0000525084,0.000013887526,0.00053038937,0.00017389705,0.0000038528283,0.0000063967855,0.00006812186,0.8091373,0.00018746722,0.18114965,0.008507537,0.0001690111],"about_ca_topic_score_codex":0.000039485803,"about_ca_topic_score_gemma":0.00005561398,"teacher_disagreement_score":0.8081365,"about_ca_system_score_codex":0.0005608727,"about_ca_system_score_gemma":0.00026508697,"threshold_uncertainty_score":0.998246},"labels":[],"label_agreement":null},{"id":"W4401871870","doi":"10.1007/978-3-031-66743-5_10","title":"Attention to Emotions: Body Emotion Recognition In-the-Wild Using Self-attention Transformer Network","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Transformer; Computer science; Psychology; Cognitive psychology; Speech recognition; Electrical engineering; Engineering","score_opus":0.05096040433179042,"score_gpt":0.2966581428812261,"score_spread":0.2456977385494357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401871870","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0044827363,0.00027961,0.866921,0.003709594,0.001551766,0.0019589332,0.00002944627,0.00033635573,0.120730564],"genre_scores_gemma":[0.653312,0.008730836,0.32338294,0.008982599,0.0010217967,0.00042980677,0.0012663014,0.00009066333,0.0027830151],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99755937,0.00008662838,0.0009781435,0.00042996238,0.00060360023,0.0003422951],"domain_scores_gemma":[0.9979686,0.00012585783,0.00027476056,0.0011570556,0.00037992597,0.00009379509],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0020366032,0.0002822584,0.00024169052,0.0017879336,0.00072112435,0.001308909,0.0016414347,0.00018165841,0.000012806287],"category_scores_gemma":[0.000017301752,0.00026809835,0.000100460384,0.0013606874,0.00020101116,0.008226683,0.0004395991,0.0006402186,0.0003751758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000777474,0.00013925534,0.000081123595,0.00019662076,0.00003008388,0.000003262294,0.006612676,0.0013041983,0.000057578665,0.44924003,0.00086464774,0.5414627],"study_design_scores_gemma":[0.0006459206,0.00021443338,0.007692201,0.0024826974,0.000071562325,0.00020678817,0.00019580337,0.8148406,0.00000919028,0.093638144,0.079046585,0.0009560805],"about_ca_topic_score_codex":0.000019248477,"about_ca_topic_score_gemma":0.000033461536,"teacher_disagreement_score":0.8135364,"about_ca_system_score_codex":0.00032753358,"about_ca_system_score_gemma":0.0001620501,"threshold_uncertainty_score":0.9999771},"labels":[],"label_agreement":null},{"id":"W4402259844","doi":"10.1007/978-3-031-66339-0","title":"Model-Driven Engineering and Software Development","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Télécom Paris; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; Taras Shevchenko National University of Kyiv; Mälardalens högskola; Universidad de Córdoba; Universitatea din București; Uppsala Universitet; Universidad Complutense de Madrid; University of Haifa; Università di Pisa; Universitetet i Oslo; Université Moulay Ismaïl; Ben-Gurion University of the Negev; Università degli Studi dell'Aquila; Technische Universiteit Eindhoven; Hebrew University of Jerusalem; North Dakota State University; Chang Gung University; Radboud Universiteit; Università degli Studi del Piemonte Orientale; Chang Gung Medical Foundation; Weizmann Institute of Science; Institut Polytechnique de Paris; Universitat Pompeu Fabra; Monash University; University Canada West; Université de Montpellier; Universidad de Sevilla","keywords":"Computer science; Software engineering; Software; Software development; Operating system","score_opus":0.027386184357301675,"score_gpt":0.2604998747353098,"score_spread":0.2331136903780081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402259844","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000030403506,0.00052718923,0.9957773,0.00017498746,0.00015124606,0.00025648982,0.0000059385925,0.000615401,0.0024610518],"genre_scores_gemma":[0.0011965133,0.0006950528,0.99714786,0.00016458951,0.000013822685,0.00006209616,0.000025397027,0.000011554197,0.0006831296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985179,0.000010791788,0.0005292089,0.00032535035,0.0003725754,0.00024423216],"domain_scores_gemma":[0.998005,0.00009027152,0.00010938618,0.0014936422,0.00018888975,0.00011286388],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006197628,0.00024598103,0.00022490422,0.0011419051,0.00021058714,0.00075441867,0.0026166365,0.00013272316,4.7270046e-7],"category_scores_gemma":[0.000013007444,0.00025688816,0.000025137657,0.0005309824,0.00025159016,0.004532867,0.0043904954,0.00050561124,0.000018476041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.2838363e-7,0.000007898515,0.000014057512,0.0001734998,0.0000073946803,7.4305666e-7,0.0041719107,0.02487451,0.0000025890308,0.5376662,0.0009786163,0.43210223],"study_design_scores_gemma":[0.000046306803,0.0000091135435,0.00007405785,0.00032040098,0.0000020935256,0.0000151890035,5.368838e-7,0.7666334,0.000006701833,0.001295258,0.23137715,0.0002197902],"about_ca_topic_score_codex":0.0000017301455,"about_ca_topic_score_gemma":0.000001871108,"teacher_disagreement_score":0.7417589,"about_ca_system_score_codex":0.0003114153,"about_ca_system_score_gemma":0.0006586775,"threshold_uncertainty_score":0.9999883},"labels":[],"label_agreement":null},{"id":"W4402343121","doi":"10.1007/978-3-031-70259-4","title":"Advances in Computational Collective Intelligence","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National University of Computer and Emerging Sciences; Universidad de Almería; Université de Technologie de Troyes; Université de Pau et des Pays de l'Adour; Universidade Federal do Rio Grande do Norte; Universidad de Granada; National Taiwan University of Science and Technology; Université de Tunis; Trakya Üniversitesi; University of Cape Town; National Taiwan University; University of Jordan; Yeungnam University; Universiti Teknologi Malaysia; Uniwersytet Rzeszowski; Uniwersytet Morski w Gdyni; Eötvös Loránd Tudományegyetem; Université Paris-Est Créteil Val-de-Marne; Universidad Complutense de Madrid; Silesian University of Technology; Bournemouth University; Politechnika Bialostocka; Politechnika Lódzka; Birmingham City University; Aristotle University of Thessaloniki; Virginia Commonwealth University; King Abdullah University of Science and Technology; Università di Bologna; Inha University; University of the West of England; University of Ulsan; Cardiff University; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Vrije Universiteit Amsterdam; Euskal Herriko Unibertsitatea; Uniwersytet Śląski w Katowicach; University of Carthage; Budapesti Műszaki és Gazdaságtudományi Egyetem; Inyuvesi Yakwazulu-Natali; Universidad Autónoma de Madrid; Slovenská technická univerzita v Bratislave; Nanyang Technological University; South Asian University; Malmö Högskola; Bharathiar University; Høgskulen på Vestlandet; Politechnika Wrocławska; University of Cyprus; Politechnika Koszalińska; Swinburne University of Technology; Université de Lorraine; University of Ottawa; Université Laval","keywords":"Collective intelligence; Computer science; Computational intelligence; Data science; Information retrieval; Artificial intelligence","score_opus":0.03066825145920012,"score_gpt":0.3219350801631798,"score_spread":0.2912668287039797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402343121","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008438555,0.0035559102,0.74368817,0.0006602159,0.0005058016,0.00032936878,0.0000073647693,0.0001137742,0.25113097],"genre_scores_gemma":[0.23500404,0.039970458,0.70661926,0.005031046,0.00038853122,0.00034480117,0.00034417718,0.00006382547,0.012233847],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978671,0.0000833354,0.00077636185,0.0004601057,0.0004915969,0.00032146298],"domain_scores_gemma":[0.9973293,0.00084409205,0.00022079602,0.001052471,0.00046238198,0.00009096105],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013838816,0.00025134004,0.00029170193,0.0019624203,0.00031836826,0.0008707831,0.003197643,0.00012399633,0.0000028457687],"category_scores_gemma":[0.00007776078,0.00026071706,0.000047298534,0.0025407663,0.0008662742,0.006593554,0.0033298936,0.00081834494,0.00009783088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001984847,0.000022075084,0.000034316843,0.00004489151,0.0000025041165,0.0000016302099,0.002820821,0.011317244,4.6041606e-8,0.31847033,0.0006787001,0.6666055],"study_design_scores_gemma":[0.00010269546,0.000039600636,0.00046508329,0.00061693235,0.0000021155124,0.000021037837,0.000020811072,0.8113595,9.707743e-7,0.1347086,0.05241283,0.00024977984],"about_ca_topic_score_codex":0.000004436865,"about_ca_topic_score_gemma":0.000024520961,"teacher_disagreement_score":0.80004233,"about_ca_system_score_codex":0.00059751456,"about_ca_system_score_gemma":0.0016168519,"threshold_uncertainty_score":0.9999845},"labels":[],"label_agreement":null},{"id":"W4402400605","doi":"10.1007/978-3-031-70245-7_19","title":"Goal Model Extraction from User Stories Using Large Language Models","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Extraction (chemistry); Natural language processing; Information retrieval; Information extraction; Artificial intelligence; Chromatography; Chemistry","score_opus":0.06199237035249826,"score_gpt":0.343000401956136,"score_spread":0.28100803160363774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402400605","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005428346,0.000998135,0.98049754,0.00016925702,0.00039176006,0.00020794901,0.00005068859,0.00022752715,0.01691433],"genre_scores_gemma":[0.22977062,0.0015517257,0.7636869,0.00036446683,0.00012104702,0.000036002522,0.00011933445,0.000034823654,0.004315091],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837095,0.000014001619,0.00044469812,0.0003127455,0.0005947857,0.00026280657],"domain_scores_gemma":[0.9972354,0.0003367252,0.00012217005,0.0019529721,0.0002562386,0.00009646293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007943198,0.0002018804,0.0001897287,0.0009573301,0.00031454995,0.0010177057,0.002622906,0.00013722018,0.0000046090922],"category_scores_gemma":[0.000050026327,0.00020912467,0.00004265104,0.00041860342,0.00028006543,0.010310755,0.0029490965,0.0006387445,0.0000500434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015009936,0.000013119569,0.000018561468,0.00003446131,0.000010073951,0.0000015616811,0.008521796,0.065568596,0.00002531151,0.899255,0.00015605397,0.026393961],"study_design_scores_gemma":[0.00009825768,0.000008779532,0.00006892993,0.0001592085,0.0000042362285,0.000008644254,0.000029816762,0.97204244,0.0000112858725,0.017493399,0.009865553,0.00020942077],"about_ca_topic_score_codex":0.000057444,"about_ca_topic_score_gemma":0.000015055961,"teacher_disagreement_score":0.9064739,"about_ca_system_score_codex":0.00031071657,"about_ca_system_score_gemma":0.00033245413,"threshold_uncertainty_score":0.98137593},"labels":[],"label_agreement":null},{"id":"W4402538968","doi":"10.1007/978-3-031-72260-8_1","title":"The Effect of News Dissemination on Infection Dynamics: An Evolutionary Epidemic Model in a Network Setting","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamics (music); Computer science; Evolutionary dynamics; Epidemic model; Demography; Psychology; Sociology","score_opus":0.01260301993496556,"score_gpt":0.3160415232490798,"score_spread":0.30343850331411426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402538968","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011826598,0.0010156863,0.4400195,0.001135887,0.0004304239,0.0022431621,0.000081979684,0.00021014364,0.54303664],"genre_scores_gemma":[0.9906038,0.0006674722,0.0076727294,0.000036641613,0.00008283474,0.000083149345,0.00032955312,0.000012093479,0.0005117166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987751,0.000063485204,0.00063344097,0.00016574925,0.00021133269,0.0001508692],"domain_scores_gemma":[0.99804103,0.00060910074,0.00032122506,0.0008834735,0.0001136948,0.000031452782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015576034,0.0001581183,0.00020770598,0.00050614617,0.0003341718,0.00014786329,0.0006562077,0.00005838949,0.0000026850278],"category_scores_gemma":[0.000015278238,0.00012860885,0.00006106742,0.0004096361,0.00035169022,0.0013240145,0.0005317637,0.00043978146,0.000004677516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005641491,0.000007307542,0.003508698,0.000018973782,0.0000076099122,1.8774346e-8,0.00025688505,0.06798655,5.179158e-7,0.61474526,0.00024465212,0.31321788],"study_design_scores_gemma":[0.0000547785,0.00005702469,0.0010823227,0.00044090388,0.0000110647625,4.675845e-7,0.000009579947,0.93265724,0.0000017613667,0.06416041,0.0014192702,0.000105189196],"about_ca_topic_score_codex":0.000086407,"about_ca_topic_score_gemma":0.00010261505,"teacher_disagreement_score":0.9787772,"about_ca_system_score_codex":0.00020231969,"about_ca_system_score_gemma":0.00006672914,"threshold_uncertainty_score":0.5244517},"labels":[],"label_agreement":null},{"id":"W4402543084","doi":"10.1007/978-3-031-69257-4_16","title":"Machine Learning-Based Per-Instance Algorithm Selection for High-Performance Subgraph Isomorphism Enumeration","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Tezpur University; Queen's University; Queen's University Belfast","keywords":"Enumeration; Isomorphism (crystallography); Selection (genetic algorithm); Computer science; Subgraph isomorphism problem; Induced subgraph isomorphism problem; Algorithm; Combinatorics; Artificial intelligence; Mathematics; Theoretical computer science; Chemistry; Crystallography; Graph","score_opus":0.015979033309971885,"score_gpt":0.24467727779749898,"score_spread":0.2286982444875271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402543084","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006918609,0.0006934289,0.9879916,0.00078162627,0.0006308887,0.0005842278,0.00004076591,0.00025330245,0.0089549795],"genre_scores_gemma":[0.22497092,0.0039789276,0.7637513,0.001365022,0.0001578128,0.00027307635,0.00052963936,0.000043516033,0.004929762],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981085,0.000037374954,0.00067959435,0.000437922,0.00043456577,0.00030202026],"domain_scores_gemma":[0.9977632,0.00022163468,0.00032881775,0.0010794124,0.0005129672,0.00009394323],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013634497,0.00031164527,0.00027921546,0.0013993393,0.0009989133,0.00084823335,0.0020666963,0.00016270397,0.0000073576493],"category_scores_gemma":[0.000021482752,0.00031442233,0.00007276443,0.0007472148,0.00061077427,0.005564493,0.00061683997,0.00066250126,0.00005577063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037514653,0.000015530404,0.000019179515,0.000057112295,0.000007701927,1.395094e-7,0.0005971307,0.0034237893,0.000006310704,0.68679446,0.00003541579,0.3090395],"study_design_scores_gemma":[0.0003214041,0.00017099942,0.00011531758,0.00018262633,0.000009694773,0.000014557931,0.0000042642487,0.90980536,0.00009055292,0.030338222,0.058616318,0.0003307101],"about_ca_topic_score_codex":0.000011532824,"about_ca_topic_score_gemma":0.0000079681895,"teacher_disagreement_score":0.90638155,"about_ca_system_score_codex":0.00015153048,"about_ca_system_score_gemma":0.0002692006,"threshold_uncertainty_score":0.9999308},"labels":[],"label_agreement":null},{"id":"W4403147465","doi":"10.1007/978-3-031-68435-7_8","title":"Discrete-Event Modeling of Human Behavior for Spread of Diseases on University Campuses","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mental Health Research Topics","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Event (particle physics); Computer science; Library science; History; Physics; Astrophysics","score_opus":0.1571573857333421,"score_gpt":0.4567160477852647,"score_spread":0.2995586620519226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403147465","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038312122,0.0024076868,0.09911592,0.0012545041,0.001405463,0.0059828963,0.002680338,0.00012404438,0.84871703],"genre_scores_gemma":[0.9911771,0.00056154974,0.0033818714,0.000064385415,0.000017905923,0.000025267644,0.00016366137,0.000007670611,0.004600585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991676,0.000018069646,0.00038246234,0.00011601201,0.00020761174,0.00010822136],"domain_scores_gemma":[0.9986897,0.00011969591,0.00016334387,0.0007900336,0.00017946473,0.000057778987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033945692,0.00008084547,0.00015220667,0.0005697499,0.00016698951,0.000022481307,0.00078210956,0.000057777197,0.000016556047],"category_scores_gemma":[0.000010480219,0.000080086356,0.00004203612,0.00011213815,0.0005564991,0.0004828875,0.0005234307,0.00017103396,0.0000066653097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016861988,0.000052903466,0.00013087428,0.00021437994,0.000006890269,2.0655371e-7,0.0016617941,0.0002689071,0.0000020210607,0.9579541,0.000087648055,0.039603423],"study_design_scores_gemma":[0.0028979732,0.0025748527,0.016361024,0.0051275725,0.00018720793,0.000013238781,0.002283614,0.8102933,0.0000669994,0.051615886,0.1074693,0.0011090371],"about_ca_topic_score_codex":0.0000751821,"about_ca_topic_score_gemma":0.00001519718,"teacher_disagreement_score":0.952865,"about_ca_system_score_codex":0.000098799814,"about_ca_system_score_gemma":0.00010492366,"threshold_uncertainty_score":0.3265827},"labels":[],"label_agreement":null},{"id":"W4403359445","doi":"10.1007/978-3-031-73180-8","title":"Agents and Robots for reliable Engineered Autonomy","year":2024,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office National d'études et de Recherches Aérospatiales; Technische Universität Clausthal; Universidade Federal de Santa Catarina; Universidade do Porto; Università degli Studi di Milano; University of Aberdeen; University of Oxford; Universidade Tecnológica Federal do Paraná; Imperial College London; Télécom Paris; Università degli Studi di Milano-Bicocca; McMaster University; Università Degli Studi di Modena e Reggio Emila; National and Kapodistrian University of Athens; Università degli Studi di Genova; TU Graz, Internationale Beziehungen und Mobilitätsprogramme","keywords":"Autonomy; Computer science; Robot; Artificial intelligence; Political science; Law","score_opus":0.08323593773114445,"score_gpt":0.39391256660869445,"score_spread":0.31067662887755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403359445","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009748741,0.0009994193,0.013577556,0.016089242,0.0009920615,0.0010265989,0.00004767313,0.00011855006,0.9670514],"genre_scores_gemma":[0.16371854,0.086387366,0.40074918,0.020888193,0.0015601041,0.00061996846,0.0008287092,0.00010649407,0.32514146],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990554,0.000024335684,0.0003135834,0.00013340433,0.00026690378,0.00020637053],"domain_scores_gemma":[0.9986182,0.0003286828,0.00010564775,0.00043746294,0.00039841677,0.000111598034],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0021565657,0.00010145381,0.00014863594,0.00038983615,0.0010096214,0.0011342461,0.00085989694,0.00016786395,0.0000041285425],"category_scores_gemma":[0.00022763223,0.00010625049,0.000028286971,0.0003266714,0.0012563766,0.0036827733,0.0005368567,0.00032804746,0.00001327379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.853056e-7,0.000007769636,0.000015065869,0.0000759887,0.0000062447475,6.4943926e-8,0.038091287,0.00010106928,2.1595413e-7,0.90235734,0.017857008,0.041486975],"study_design_scores_gemma":[0.000097794284,0.000018744619,0.00023829643,0.00017072128,0.0000071990326,4.6156666e-7,0.00023391712,0.03332649,3.387334e-7,0.04164361,0.9241266,0.0001358187],"about_ca_topic_score_codex":0.00010955613,"about_ca_topic_score_gemma":0.00008220525,"teacher_disagreement_score":0.9062696,"about_ca_system_score_codex":0.00029851976,"about_ca_system_score_gemma":0.001883997,"threshold_uncertainty_score":0.99990267},"labels":[],"label_agreement":null},{"id":"W4403359648","doi":"10.1007/978-3-031-73180-8_6","title":"Planning with Non-deterministic Actions in Jason","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science","score_opus":0.0483776318052908,"score_gpt":0.3072988658458596,"score_spread":0.25892123404056877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403359648","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021078247,0.0005864562,0.46777412,0.0012642021,0.00038070223,0.00038331974,0.000012153216,0.0001816823,0.5292066],"genre_scores_gemma":[0.68040186,0.00094721204,0.31075844,0.0013489159,0.00008700201,0.00008829567,0.00012379329,0.00003764665,0.0062068473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861896,0.000014964345,0.00049909885,0.00030040936,0.00032215175,0.0002444033],"domain_scores_gemma":[0.99796516,0.00025656197,0.00019230903,0.0013771523,0.0001252292,0.00008358615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075234304,0.00021114784,0.00021521593,0.0013706639,0.00038489042,0.00089631,0.0021618202,0.00010923425,0.0000033448086],"category_scores_gemma":[0.000015361078,0.00019493744,0.00002574582,0.0006138191,0.00042115472,0.00416964,0.00122629,0.0007019399,0.000067269015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006525677,0.000021697366,0.00039331158,0.00014742423,0.000011546338,0.000014897635,0.012213129,0.010397986,0.0000028388802,0.8146449,0.00038069295,0.16176508],"study_design_scores_gemma":[0.00021593989,0.000096784104,0.0011782395,0.0017206758,0.000006482255,0.00008292077,0.00004117998,0.91578454,0.0000028609566,0.008346972,0.07216209,0.00036133308],"about_ca_topic_score_codex":0.000019280149,"about_ca_topic_score_gemma":0.000013271864,"teacher_disagreement_score":0.90538657,"about_ca_system_score_codex":0.00014625699,"about_ca_system_score_gemma":0.000328897,"threshold_uncertainty_score":0.8643138},"labels":[],"label_agreement":null},{"id":"W4403523613","doi":"10.1007/978-3-031-75201-8_4","title":"Zoned Role-Based Approach to System Design, Implementation, and Access Control of Integrated Web Applications","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Computer science; World Wide Web; Control (management); Web application; Artificial intelligence","score_opus":0.038960575392436116,"score_gpt":0.3120512552609595,"score_spread":0.27309067986852337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403523613","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022684886,0.00040872517,0.95913863,0.00076999917,0.000059045957,0.0019000466,0.00011444237,0.00017158441,0.03741484],"genre_scores_gemma":[0.645122,0.00024724103,0.35190567,0.00090761436,0.000030402009,0.0013976947,0.00015807514,0.000021860244,0.00020946817],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976829,0.00006682026,0.0010631763,0.00046630192,0.0004997553,0.000220996],"domain_scores_gemma":[0.9960923,0.00037323817,0.00040606208,0.002120968,0.00085207896,0.00015534945],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0016675673,0.00027233895,0.0003708706,0.0016009281,0.00034951608,0.001092661,0.0036519933,0.00011783506,0.0000031937059],"category_scores_gemma":[0.000015095132,0.00026856162,0.000044285738,0.0010889928,0.00071087934,0.0034045898,0.0016167366,0.0003247266,0.000024732639],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000324916,0.00001806567,0.00002236115,0.00015428227,0.000009482817,3.3011922e-8,0.0010637405,0.0009710641,0.000019212972,0.95781916,0.00008642263,0.039832916],"study_design_scores_gemma":[0.0004630072,0.00005256626,0.00013913524,0.00018539079,0.000018541667,0.000011182557,0.00034408597,0.9177132,0.00009280561,0.0084307715,0.072216436,0.00033285323],"about_ca_topic_score_codex":0.000037468988,"about_ca_topic_score_gemma":0.000008758192,"teacher_disagreement_score":0.9493884,"about_ca_system_score_codex":0.0002518328,"about_ca_system_score_gemma":0.00074254134,"threshold_uncertainty_score":0.99997663},"labels":[],"label_agreement":null},{"id":"W4403529163","doi":"10.1007/978-3-031-75201-8_13","title":"A Case Study on AI to Automate Simulation Modelling","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Durham College; Ontario Tech University; Trent University","funders":"","keywords":"Computer science; Thesaurus; Information retrieval; Artificial intelligence","score_opus":0.27644236293651736,"score_gpt":0.4781235972173194,"score_spread":0.20168123428080204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403529163","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041836007,0.00005858972,0.8005058,0.0018832869,0.0002847701,0.0022049726,0.000056492638,0.000329759,0.19049273],"genre_scores_gemma":[0.98046577,0.00004138548,0.014393952,0.0012262539,0.000038236532,0.00008871266,0.000013484246,0.000014730495,0.003717494],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968239,0.000038413502,0.0013112002,0.00049697096,0.0011392969,0.00019018377],"domain_scores_gemma":[0.99499434,0.0009910414,0.00028299552,0.0027271006,0.00085381325,0.00015071758],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0030335253,0.00024192924,0.00029048277,0.0027411692,0.0006512678,0.0016016116,0.0018538266,0.00011312073,0.000026674392],"category_scores_gemma":[0.000117456,0.0002096586,0.000062667634,0.0012774499,0.00028998568,0.002719614,0.001487184,0.00045208467,0.00066507055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038671633,0.000042551204,0.00002731651,0.0000051687916,0.0000046693817,0.000008182165,0.0048421575,0.53541034,3.457072e-7,0.3273917,0.00035523993,0.1319084],"study_design_scores_gemma":[0.000098273435,0.000091207614,0.00004644567,0.00007074224,0.0000070576943,0.00005295721,0.000256983,0.86311877,0.000001067287,0.03340138,0.10265545,0.00019967546],"about_ca_topic_score_codex":0.00002757049,"about_ca_topic_score_gemma":0.0000122387055,"teacher_disagreement_score":0.9762822,"about_ca_system_score_codex":0.00016426726,"about_ca_system_score_gemma":0.00014175523,"threshold_uncertainty_score":0.9994348},"labels":[],"label_agreement":null},{"id":"W4403640394","doi":"10.1007/978-3-031-71975-2_6","title":": Mitigating Gender Bias in Neural Team Recommendation via Female-Advocate Loss Regularization","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Regularization (linguistics); Computer science; Gender bias; Medicine; Psychology; Artificial intelligence; Social psychology","score_opus":0.27622196476309835,"score_gpt":0.4254999534359285,"score_spread":0.14927798867283015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403640394","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03443637,0.0025925536,0.08117719,0.024449654,0.0040908335,0.004805365,0.00006533781,0.0004675681,0.8479151],"genre_scores_gemma":[0.9805918,0.0024307675,0.011782153,0.0019196161,0.00017067029,0.00006437858,0.0009157836,0.000024590105,0.002100288],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980835,0.000035259814,0.0010851636,0.00027124438,0.00029868734,0.00022616408],"domain_scores_gemma":[0.9981909,0.00019666879,0.00028948984,0.0007898958,0.0004262968,0.000106777086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001358522,0.00019195893,0.00024506563,0.0013062997,0.00027812054,0.00022659931,0.00039624106,0.0001836593,0.000034494475],"category_scores_gemma":[0.00011904085,0.00019472314,0.000043418237,0.0006097139,0.00050556654,0.0023649812,0.0003713296,0.000661417,0.000100108824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015190198,0.000041479067,0.0031193646,0.00033146972,0.00000828019,0.0000010338944,0.011337056,0.00040099848,0.000009165268,0.091346234,0.0001750792,0.89321464],"study_design_scores_gemma":[0.00013208813,0.00011216428,0.0043578735,0.0010773944,0.000028097156,0.00010489892,0.00062587234,0.9144891,0.000113141425,0.039427403,0.039154764,0.00037722223],"about_ca_topic_score_codex":0.00008774365,"about_ca_topic_score_gemma":0.000052166783,"teacher_disagreement_score":0.94615537,"about_ca_system_score_codex":0.00039191748,"about_ca_system_score_gemma":0.00038359506,"threshold_uncertainty_score":0.7940579},"labels":[],"label_agreement":null},{"id":"W4403640797","doi":"10.1007/978-3-031-71975-2_4","title":"Fairness Analysis of Machine Learning-Based Code Reviewer Recommendation","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Code (set theory); Information retrieval; Natural language processing; World Wide Web; Artificial intelligence; Programming language","score_opus":0.0855545768711964,"score_gpt":0.40162848990614214,"score_spread":0.31607391303494575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403640797","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000054826865,0.0012712906,0.019654285,0.013846074,0.00047969774,0.00046363915,0.00012729834,0.00008555593,0.96401733],"genre_scores_gemma":[0.82677215,0.114517614,0.022741394,0.006195832,0.00024437215,0.000060780916,0.0023822752,0.000049179533,0.027036406],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99858356,0.00008399573,0.00060061726,0.00014563817,0.00044230724,0.0001438795],"domain_scores_gemma":[0.9973162,0.00044300256,0.0003897177,0.00053363503,0.0012369468,0.00008049845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039206543,0.00011837233,0.00030665647,0.001361571,0.0006753273,0.00040740447,0.0009273075,0.00015964534,0.00009354462],"category_scores_gemma":[0.0004855021,0.000118426164,0.00009803001,0.001178324,0.0015263788,0.0022456923,0.00038182153,0.00053719804,0.00001873589],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020286561,0.000013400232,0.00015738913,0.00005936956,0.000049863196,6.078005e-8,0.010292144,0.00086799177,2.607342e-7,0.91349196,0.00018191535,0.07488358],"study_design_scores_gemma":[0.00007511991,0.000025337511,0.0003087606,0.0002223055,0.0001268866,8.727458e-8,0.0001563725,0.21718018,8.09431e-7,0.0102268355,0.7715113,0.00016598361],"about_ca_topic_score_codex":0.00038966033,"about_ca_topic_score_gemma":0.0014440261,"teacher_disagreement_score":0.9369809,"about_ca_system_score_codex":0.00016378032,"about_ca_system_score_gemma":0.00045768704,"threshold_uncertainty_score":0.56240064},"labels":[],"label_agreement":null},{"id":"W4403841929","doi":"10.1007/978-3-031-75431-9_4","title":"Region of Interest Features and Classification of MRI Brain Lesions","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Medicine; Artificial intelligence","score_opus":0.07063792325245556,"score_gpt":0.35021698212427776,"score_spread":0.2795790588718222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403841929","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012333973,0.007850922,0.08904596,0.06470171,0.0006981403,0.0015421357,0.000041644777,0.00012838075,0.82365716],"genre_scores_gemma":[0.95590705,0.010494141,0.027768748,0.00086270185,0.000043656957,0.000008983607,0.000108412394,0.000014504921,0.0047918214],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991858,0.000011770839,0.0004596004,0.000116835174,0.00015687312,0.000069141286],"domain_scores_gemma":[0.9987173,0.00018453263,0.00023073798,0.0006193467,0.0001883376,0.000059747497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054879684,0.000091603804,0.0002101826,0.00069427904,0.00007751942,0.000048300208,0.00032457692,0.00007969076,0.0000027713465],"category_scores_gemma":[0.00011714198,0.00007865221,0.000030411225,0.0001706596,0.001240219,0.00052511645,0.0004320866,0.00042537745,0.000002520489],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074192926,0.00001404315,0.0002182976,0.00028838753,0.000010564072,5.1255313e-7,0.0014868741,0.00001347308,0.00011326553,0.77458924,0.0015744979,0.2216834],"study_design_scores_gemma":[0.0011730541,0.00038039862,0.06556716,0.007892247,0.00012315404,0.0006447342,0.00031756688,0.55109096,0.0000754581,0.032801256,0.33949324,0.00044076072],"about_ca_topic_score_codex":0.00001020638,"about_ca_topic_score_gemma":0.000004109736,"teacher_disagreement_score":0.94357306,"about_ca_system_score_codex":0.000035451252,"about_ca_system_score_gemma":0.000116035786,"threshold_uncertainty_score":0.45696384},"labels":[],"label_agreement":null},{"id":"W4403842011","doi":"10.1007/978-3-031-75431-9_6","title":"Breast Thermographic Image Augmentation Using Generative Adversarial Networks (GANs)","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adversarial system; Generative adversarial network; Computer science; Generative grammar; Artificial intelligence; Image (mathematics); Computer vision","score_opus":0.026448028205291404,"score_gpt":0.30608707655937656,"score_spread":0.27963904835408515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403842011","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049141105,0.0043711946,0.23584029,0.0031004709,0.0029025765,0.0033640838,0.00020569586,0.00040641107,0.74489516],"genre_scores_gemma":[0.71164423,0.021005135,0.24907593,0.007875478,0.0022533808,0.0001650251,0.002595869,0.00019255145,0.0051923813],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841297,0.000023830098,0.0006538678,0.00023681913,0.0004608407,0.00021169386],"domain_scores_gemma":[0.99804854,0.000085982414,0.00024461307,0.0010616655,0.00044622732,0.000112964255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077182945,0.00024670016,0.00030342626,0.0014824118,0.00033824457,0.00021981112,0.00057335076,0.0001688436,0.000046765617],"category_scores_gemma":[0.000010930346,0.00022250313,0.000086250315,0.0006474815,0.0016676154,0.0020376525,0.0005084814,0.0006929669,0.000020748857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020858773,0.00011530911,0.00054950785,0.0004702235,0.0003306519,0.000019449426,0.01477522,0.003823394,0.00081760314,0.59881353,0.0010400977,0.37903643],"study_design_scores_gemma":[0.001098808,0.00012300194,0.0019058266,0.0013815755,0.00016751708,0.0004665848,0.00015158152,0.98310304,0.000015391748,0.004385399,0.006829269,0.00037200938],"about_ca_topic_score_codex":0.000017103615,"about_ca_topic_score_gemma":0.0000033913966,"teacher_disagreement_score":0.97927964,"about_ca_system_score_codex":0.00019002876,"about_ca_system_score_gemma":0.0002499888,"threshold_uncertainty_score":0.9073415},"labels":[],"label_agreement":null},{"id":"W4403886077","doi":"10.1007/978-981-97-8743-2_6","title":"SEBWatcher: Visual Analysis System for Subject, Environment and Behavior in Traffic Scenes","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Subject (documents); Computer science; Artificial intelligence; Information retrieval; Computer vision; World Wide Web","score_opus":0.035057437395595796,"score_gpt":0.31602534715595754,"score_spread":0.28096790976036173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403886077","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001951458,0.0015149588,0.9799173,0.0008661209,0.00037392558,0.0012636397,0.00013662215,0.00021862934,0.01375736],"genre_scores_gemma":[0.8503677,0.0084341755,0.13592818,0.00078007876,0.000073530784,0.00028344244,0.00076244934,0.000034560944,0.0033358636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984689,0.000020815873,0.00067143614,0.00034102245,0.0003129717,0.00018488799],"domain_scores_gemma":[0.9984524,0.00013153169,0.00019282423,0.0010347491,0.00010102851,0.000087422326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095173926,0.00019342874,0.00029524078,0.0018829101,0.00032218566,0.00071679836,0.0014325368,0.00010033357,0.0000024191586],"category_scores_gemma":[0.000009635188,0.00019126447,0.00006320466,0.0007694465,0.00039825478,0.0027112197,0.0017933684,0.00019491838,0.000015507054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027930619,0.000062285464,0.00036657677,0.00023449952,0.000044434888,0.000001485257,0.0037177585,0.0032419316,0.000002804841,0.8438189,0.00006156986,0.14844494],"study_design_scores_gemma":[0.00018354529,0.000039502735,0.0009949616,0.00011514612,0.00007355639,0.000007827853,0.00006561082,0.97125655,0.0000037206164,0.00031738478,0.026718514,0.00022366495],"about_ca_topic_score_codex":0.000009923879,"about_ca_topic_score_gemma":0.000027520739,"teacher_disagreement_score":0.96801466,"about_ca_system_score_codex":0.00017684561,"about_ca_system_score_gemma":0.00011243643,"threshold_uncertainty_score":0.77995384},"labels":[],"label_agreement":null},{"id":"W4403912171","doi":"10.1007/978-3-031-73494-6_23","title":"NPQuant: A Robust Quantum Inspired Computation Algorithms as an Efficient Solution to NP-Complete Problems","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computation; Computer science; Quantum computer; Quantum; Algorithm; Quantum algorithm; Physics; Quantum mechanics","score_opus":0.04508632951023637,"score_gpt":0.2905272982830646,"score_spread":0.24544096877282826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403912171","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008103547,0.00042252263,0.9676267,0.0033425465,0.0010027337,0.0010628033,0.000041176194,0.0005195214,0.02517165],"genre_scores_gemma":[0.15850644,0.0006579822,0.83502036,0.0036315639,0.00033076954,0.00015712123,0.00036404462,0.000086603664,0.0012451239],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962812,0.00007506163,0.0011936314,0.00088484876,0.0009943148,0.0005709603],"domain_scores_gemma":[0.9960987,0.00020746018,0.00041387693,0.0023070504,0.0006063327,0.0003666039],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015652297,0.00051020103,0.00046737873,0.0022957404,0.0010308761,0.0020213583,0.0040988866,0.00020892259,0.000003986512],"category_scores_gemma":[0.000043722448,0.0004996827,0.000102232836,0.0013591797,0.0006754886,0.00323372,0.0039523123,0.0008720598,0.00032169122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034492602,0.000048858376,0.0000012713202,0.000072298164,0.000010501783,0.000002407897,0.006865128,0.21519785,0.000014543727,0.5456491,0.00015299143,0.23198158],"study_design_scores_gemma":[0.0002441215,0.00034123994,0.00012182018,0.0005099205,0.000009297402,0.00011549286,0.000023287803,0.9338806,0.0000032832604,0.024957165,0.03922981,0.0005639259],"about_ca_topic_score_codex":0.00009855636,"about_ca_topic_score_gemma":0.000023825249,"teacher_disagreement_score":0.71868277,"about_ca_system_score_codex":0.00030014958,"about_ca_system_score_gemma":0.0004303044,"threshold_uncertainty_score":0.9997455},"labels":[],"label_agreement":null},{"id":"W4404160532","doi":"10.1007/978-981-97-9793-6_16","title":"Enhancing Classification Accuracy on Sparse Datasets Using a Modified Hybrid RBF-BP Network Classifier and the Sample Generation Method","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Classifier (UML); Pattern recognition (psychology); Computer science; Artificial intelligence; Artificial neural network; Sample (material); Chromatography; Chemistry","score_opus":0.1150028844650224,"score_gpt":0.35850867974738704,"score_spread":0.24350579528236466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404160532","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008069543,0.00045350142,0.97397,0.0024351224,0.0004602964,0.00045030433,0.000038202274,0.00009176058,0.022020092],"genre_scores_gemma":[0.12657987,0.0037114741,0.86220783,0.0051871585,0.0004802289,0.000094326286,0.0008028082,0.000035249068,0.0009010342],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979109,0.00016512831,0.0007492349,0.00044954833,0.0004598561,0.0002652962],"domain_scores_gemma":[0.9957686,0.0012787067,0.00044068575,0.0022469515,0.00017364732,0.00009140706],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0034986266,0.0002651547,0.0002829086,0.0005471861,0.0011072599,0.0017125973,0.0020482219,0.00010029326,0.000003877727],"category_scores_gemma":[0.00020271343,0.00020737153,0.00004943834,0.0004379286,0.0006201265,0.0035331969,0.0019985745,0.0006357226,0.000025892403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005317203,0.0000063699977,0.0000021799515,0.000019631496,0.0000078341145,2.402009e-7,0.000982318,0.009880559,0.000007771181,0.79436564,0.00051247753,0.19420967],"study_design_scores_gemma":[0.00028481203,0.00002118015,0.00006162191,0.00017606094,0.000014345272,0.000029027477,0.00001273559,0.9025833,0.00000922874,0.020252759,0.0763456,0.00020932377],"about_ca_topic_score_codex":0.000081996885,"about_ca_topic_score_gemma":0.000028418399,"teacher_disagreement_score":0.89270276,"about_ca_system_score_codex":0.000113123795,"about_ca_system_score_gemma":0.00021972723,"threshold_uncertainty_score":0.9993237},"labels":[],"label_agreement":null},{"id":"W4404420827","doi":"10.1007/978-981-97-9003-6_3","title":"DDPM-MoCo: Advancing Industrial Surface Defect Generation and Detection with Generative and Contrastive Learning","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Generative grammar; Computer science; Nanotechnology; Artificial intelligence; Materials science","score_opus":0.03255737050998604,"score_gpt":0.24917878970862428,"score_spread":0.21662141919863825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404420827","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16957891,0.0071702506,0.68224764,0.00023323542,0.0031471772,0.003681114,0.00007230591,0.00091274927,0.13295661],"genre_scores_gemma":[0.9955026,0.0016178626,0.002263437,0.000030043275,0.0001608066,0.00002166226,0.00002738462,0.000019042642,0.00035719326],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899566,0.000032903383,0.0004090051,0.00020114964,0.00020946741,0.00015182355],"domain_scores_gemma":[0.9992323,0.00013572737,0.000121791985,0.00027022464,0.00016552894,0.00007442551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073752826,0.00020821669,0.00022621811,0.00046747134,0.00044364927,0.0005253579,0.00013567296,0.00019562281,0.0000022758275],"category_scores_gemma":[0.000030476478,0.00018964424,0.000021058277,0.00024757587,0.00029575927,0.0020624143,0.00019435905,0.00068487047,0.000006355277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004584464,0.000008050475,0.0001758941,0.00016977376,0.000102094236,0.0000020931234,0.007131507,0.12459064,0.0025829955,0.025962781,0.00016514478,0.83906317],"study_design_scores_gemma":[0.0005254108,0.00019445935,0.00009901547,0.00035207983,0.00002695864,0.00006856162,0.00014525476,0.9689508,0.0004927949,0.00020607155,0.02862154,0.00031701938],"about_ca_topic_score_codex":0.000021991149,"about_ca_topic_score_gemma":0.00006445355,"teacher_disagreement_score":0.8443602,"about_ca_system_score_codex":0.00015803907,"about_ca_system_score_gemma":0.00006411083,"threshold_uncertainty_score":0.7733468},"labels":[],"label_agreement":null},{"id":"W4404645450","doi":"10.1007/978-3-031-75167-7_28","title":"Investigation of Satellite Data for Monitoring Air Quality Over Remote Sensing Technology","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"PricewaterhouseCoopers (Canada)","funders":"","keywords":"Remote sensing; Satellite; Computer science; Environmental science; Geography; Aerospace engineering; Engineering","score_opus":0.14251826092768594,"score_gpt":0.3565315773467187,"score_spread":0.21401331641903276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404645450","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051219832,0.004319014,0.5929569,0.007234336,0.004176868,0.0037659025,0.00060259405,0.00083430804,0.33489025],"genre_scores_gemma":[0.28961912,0.002513837,0.7053264,0.00017739032,0.00015666791,0.000004286664,0.00027302117,0.000029526476,0.0018997487],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985696,0.00001673478,0.0006950197,0.0002650952,0.00030076058,0.00015275867],"domain_scores_gemma":[0.99752545,0.00022991872,0.00034992388,0.0017729938,0.00007402579,0.000047656402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001890721,0.00013739498,0.00019225034,0.00038002938,0.00025560227,0.000083415245,0.0012840371,0.00013166302,0.0000025232719],"category_scores_gemma":[0.00010821747,0.00014161474,0.000024897565,0.00036754625,0.0013545793,0.0020653645,0.0028445954,0.000288372,0.000017307288],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037483705,0.0000020620773,0.0011738318,0.000132194,0.000006610547,8.7297806e-8,0.0016538562,0.00021697175,0.00014591342,0.027661916,0.000043113272,0.9689597],"study_design_scores_gemma":[0.00033672035,0.00007985288,0.011043411,0.0018123945,0.000036048667,0.000015109646,0.000251058,0.6957265,0.0006195765,0.098156095,0.1912787,0.0006445367],"about_ca_topic_score_codex":0.00007749103,"about_ca_topic_score_gemma":0.000010074887,"teacher_disagreement_score":0.9683152,"about_ca_system_score_codex":0.0001644779,"about_ca_system_score_gemma":0.000050500214,"threshold_uncertainty_score":0.5774881},"labels":[],"label_agreement":null},{"id":"W4405673732","doi":"10.1007/978-3-031-75236-0_2","title":"Towards a Closer Patient-Caregiver Relationship by Wearable and Ambient Assisted Living Design","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Agencia Nacional de Investigación y Desarrollo; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Agencia Nacional de Investigación e Innovación","keywords":"Wearable computer; Assisted living; Computer science; Psychology; Human–computer interaction; Medicine; Gerontology; Embedded system","score_opus":0.05154794339621102,"score_gpt":0.3011693634997548,"score_spread":0.2496214201035438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405673732","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025974044,0.009134238,0.05258608,0.011113956,0.0009580195,0.0022255527,0.000079496014,0.0007435736,0.9205617],"genre_scores_gemma":[0.9337285,0.010523129,0.04204847,0.00080390676,0.000041479707,0.0001028597,0.000039040842,0.000027071219,0.012685519],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99846894,0.00007891793,0.0004769056,0.00026363172,0.00046398412,0.00024763987],"domain_scores_gemma":[0.9981405,0.00045976674,0.00021172402,0.0008065593,0.00027370997,0.00010773858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013776012,0.00017332449,0.00018239315,0.0007598364,0.0010868998,0.0006006051,0.0010316249,0.00025433113,0.000016339864],"category_scores_gemma":[0.00022327201,0.00018061473,0.000030143046,0.00048268802,0.002189411,0.0030942766,0.0011422745,0.000552264,0.00006017206],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027751403,0.000024819956,0.0003379267,0.000038797712,0.000012816651,5.9760214e-7,0.046830114,0.000023883382,0.0000032460505,0.69111097,0.0035746451,0.2580394],"study_design_scores_gemma":[0.00031643445,0.00012843181,0.0067801764,0.0019077219,0.00004328375,0.000021619102,0.0020537379,0.025186557,0.000011216826,0.04683898,0.9159307,0.0007811603],"about_ca_topic_score_codex":0.00016722546,"about_ca_topic_score_gemma":0.00014872474,"teacher_disagreement_score":0.9311311,"about_ca_system_score_codex":0.00026888886,"about_ca_system_score_gemma":0.00037358154,"threshold_uncertainty_score":0.83596647},"labels":[],"label_agreement":null},{"id":"W4405675194","doi":"10.1007/978-3-031-76273-4_11","title":"Introducing Multidimensional Parallel Decoder to Reduce Cost of Implementation and Latency","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Latency (audio); Computer science; Parallel computing; Telecommunications","score_opus":0.044427901337953164,"score_gpt":0.3578496305056158,"score_spread":0.31342172916766264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405675194","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006244543,0.0005715898,0.9608774,0.0027502435,0.00047207123,0.0009814657,0.000017292978,0.00020588441,0.033499558],"genre_scores_gemma":[0.07260813,0.0009672547,0.9253593,0.00052115746,0.000024784613,0.000049910104,0.00002679353,0.000010460004,0.00043221426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847203,0.000020012572,0.00066951115,0.000323436,0.00034402625,0.00017100856],"domain_scores_gemma":[0.997829,0.00017548297,0.0002388946,0.0012829495,0.00038650987,0.00008712643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001115931,0.00017163726,0.00020632218,0.0010975209,0.00021493406,0.0002521544,0.001379237,0.00007253218,0.000004205798],"category_scores_gemma":[0.00003990787,0.00017375984,0.000026727996,0.00042721312,0.00032053993,0.0029819852,0.0029880935,0.00029543947,0.000017945322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019804943,0.000007165849,0.00005761932,0.00003748123,0.000005533636,2.3551732e-7,0.004169161,0.00039966073,0.000057495705,0.67262536,0.00036265203,0.32227564],"study_design_scores_gemma":[0.0004607016,0.00021614876,0.0029495105,0.0010800401,0.00002215592,0.000092433045,0.00015952466,0.88705754,0.0006134199,0.03883427,0.06774429,0.00076993636],"about_ca_topic_score_codex":0.000044177756,"about_ca_topic_score_gemma":0.000034891138,"teacher_disagreement_score":0.8866579,"about_ca_system_score_codex":0.000114336835,"about_ca_system_score_gemma":0.00019448885,"threshold_uncertainty_score":0.7085721},"labels":[],"label_agreement":null},{"id":"W4405675217","doi":"10.1007/978-3-031-76273-4_12","title":"Introducing Novel Parallel Computing Using Orbital Data","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Information retrieval","score_opus":0.0880867427648737,"score_gpt":0.3380531793774628,"score_spread":0.2499664366125891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405675217","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001042288,0.00070706604,0.9088895,0.00063582446,0.00046692186,0.00027563696,0.000021025995,0.00038622835,0.088607416],"genre_scores_gemma":[0.008218997,0.00062038633,0.9897397,0.00041136876,0.00010324879,0.0000030307274,0.00012300763,0.000016388556,0.0007638387],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974249,0.00001780686,0.001004574,0.0006882353,0.00052927097,0.0003352303],"domain_scores_gemma":[0.994247,0.00021312528,0.0004204991,0.004631407,0.00037256174,0.00011535824],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0020568394,0.00031772308,0.00034715468,0.0013801501,0.0006314922,0.0017203253,0.00788186,0.00015554497,0.0000024221956],"category_scores_gemma":[0.00007133881,0.00032840273,0.00004505186,0.00073803065,0.0006711764,0.008051746,0.014327395,0.000711153,0.00004283991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012301696,0.00001843986,0.000012304412,0.000054233507,0.000012761636,0.0000013065986,0.0012202123,0.025721809,0.000004797062,0.9055323,0.00038425857,0.06703635],"study_design_scores_gemma":[0.00013486999,0.00001989004,0.00004312915,0.00039064864,0.0000079809815,0.000094323,0.00000873335,0.9627303,0.000002606491,0.006423981,0.02979338,0.00035015083],"about_ca_topic_score_codex":0.000031279727,"about_ca_topic_score_gemma":0.0000040055334,"teacher_disagreement_score":0.9370085,"about_ca_system_score_codex":0.00019696925,"about_ca_system_score_gemma":0.00043476163,"threshold_uncertainty_score":0.9999168},"labels":[],"label_agreement":null},{"id":"W4405767988","doi":"10.1007/978-3-031-77426-3_10","title":"Enhancing K-Way Circuit Partitioning: A Deep Reinforcement Learning Methodology","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Reinforcement learning; Computer science; Artificial intelligence","score_opus":0.07926175215237737,"score_gpt":0.305504035482383,"score_spread":0.22624228333000562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405767988","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007830429,0.0006789461,0.64519495,0.000040103212,0.00015171882,0.00014795046,8.6147026e-7,0.00027263808,0.35350502],"genre_scores_gemma":[0.7342458,0.023720099,0.2311698,0.0007452456,0.0001921866,0.00025881123,0.00027516932,0.00008420693,0.009308688],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989206,0.000018843259,0.0005518742,0.00013163546,0.00019269579,0.00018434036],"domain_scores_gemma":[0.9989258,0.00017975552,0.00008930437,0.00063348276,0.00011490979,0.000056739445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010906775,0.00016621468,0.0001979474,0.00078572496,0.00023624208,0.00026720655,0.0006582656,0.00012849667,0.000029539928],"category_scores_gemma":[0.000032064025,0.00017742378,0.000036964673,0.00021553287,0.00032000893,0.0016566907,0.00047217132,0.00059178617,0.000091210786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.330393e-7,0.0000022035329,0.0000062832223,0.00015132061,0.000015385234,6.2644045e-7,0.0043149726,0.027994398,0.00011051043,0.8182899,0.00013010157,0.14898361],"study_design_scores_gemma":[0.0000789452,0.000044803404,0.000030496643,0.0004173633,0.000013402903,0.000024801353,0.000054596316,0.8132258,0.0003382125,0.026889233,0.15857361,0.00030874874],"about_ca_topic_score_codex":0.000004388528,"about_ca_topic_score_gemma":0.000008195116,"teacher_disagreement_score":0.7914006,"about_ca_system_score_codex":0.00016338132,"about_ca_system_score_gemma":0.000045253408,"threshold_uncertainty_score":0.7235132},"labels":[],"label_agreement":null},{"id":"W4405825130","doi":"10.1007/978-981-96-0313-8_15","title":"A Novel Embryo Morphology Evaluation Based on Improved YOLOv8 Object Detection Model","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Morphology (biology); Computer science; Object (grammar); Embryo; Artificial intelligence; Biology; Zoology; Cell biology","score_opus":0.056116333148899696,"score_gpt":0.3195289805804924,"score_spread":0.2634126474315927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405825130","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002383263,0.00013809737,0.9204116,0.0014468188,0.00034117515,0.0008915144,0.000019500445,0.00020985483,0.07651762],"genre_scores_gemma":[0.3530042,0.0007705316,0.6380774,0.00491945,0.00012172758,0.0007080165,0.00017839322,0.000047424797,0.0021729073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977067,0.000030449162,0.0007427512,0.0005866141,0.0006351226,0.00029834104],"domain_scores_gemma":[0.99574184,0.0002813071,0.00037387703,0.0029200108,0.0005718496,0.00011113471],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013398073,0.00031664685,0.00025803116,0.0014523704,0.0005286629,0.0005118454,0.002797091,0.00019891994,0.000004380255],"category_scores_gemma":[0.000057150606,0.00032028186,0.00007215358,0.0008700785,0.00060768565,0.0037852926,0.001498426,0.00073762663,0.000097307435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064545634,0.00003486049,4.748125e-7,0.00002382793,0.0000054962024,1.9266744e-7,0.0004327449,0.14891164,0.00054170896,0.5597464,0.00009686013,0.29019937],"study_design_scores_gemma":[0.00030898213,0.00007877762,0.000053853593,0.00010451154,0.000012458409,0.00001974187,0.0000034033828,0.9589551,0.00006887427,0.03364064,0.006458736,0.00029493272],"about_ca_topic_score_codex":0.000007071244,"about_ca_topic_score_gemma":0.0000159386,"teacher_disagreement_score":0.81004345,"about_ca_system_score_codex":0.00045456906,"about_ca_system_score_gemma":0.00048279663,"threshold_uncertainty_score":0.9999249},"labels":[],"label_agreement":null},{"id":"W4405872702","doi":"10.1007/978-3-031-78531-3_21","title":"Harmonizing AI and Human Values: The Ubuntu Approach to Super Alignment in OpenAI’s Initiatives","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Computer science; Artificial intelligence","score_opus":0.16598127670074536,"score_gpt":0.4078644745748675,"score_spread":0.24188319787412216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405872702","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005840114,0.0004505119,0.0012422877,0.01794164,0.0001399923,0.00062523474,0.000008790192,0.00002648037,0.9789811],"genre_scores_gemma":[0.97792476,0.0062047355,0.005226602,0.0076583684,0.000097997145,0.000059950005,0.000021338348,0.000011782912,0.0027944783],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986938,0.000076413766,0.0004015348,0.00017675663,0.00044390763,0.0002075696],"domain_scores_gemma":[0.99878544,0.00023769903,0.00009033117,0.00054002507,0.00024330878,0.000103189894],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003393065,0.00012934125,0.00016496875,0.00046661566,0.0015065328,0.0015171584,0.0012948778,0.0001212962,0.0000046978935],"category_scores_gemma":[0.00010559489,0.000106758795,0.000024566998,0.00035182395,0.0017626865,0.0040036114,0.0012665635,0.00058626954,0.000015696469],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.5076445e-7,0.00000794131,0.000042448966,0.000011604053,0.0000029051698,6.416971e-8,0.11701022,0.000017806953,7.3335485e-7,0.87628317,0.0001931502,0.0064295],"study_design_scores_gemma":[0.00035862727,0.00009642183,0.0063564284,0.00094396836,0.00002212995,0.000003352394,0.018778052,0.01297099,0.000004629662,0.31508043,0.6446631,0.0007218963],"about_ca_topic_score_codex":0.000579339,"about_ca_topic_score_gemma":0.00048523713,"teacher_disagreement_score":0.97734076,"about_ca_system_score_codex":0.00019050005,"about_ca_system_score_gemma":0.00029626786,"threshold_uncertainty_score":0.99979335},"labels":[],"label_agreement":null},{"id":"W4405888468","doi":"10.1007/978-3-031-77138-5_7","title":"Exploring and Learning Structure: Active Inference Approach in Navigational Agents","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas College","funders":"","keywords":"Inference; Computer science; Artificial intelligence; Thesaurus; Information retrieval; Machine learning","score_opus":0.11845452231403128,"score_gpt":0.30698584432763737,"score_spread":0.1885313220136061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405888468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010033533,0.0020360246,0.66815144,0.0017346558,0.0009516314,0.0011236238,0.000058658035,0.00043358354,0.31547686],"genre_scores_gemma":[0.8218529,0.0017880952,0.1752391,0.00031577976,0.000036659374,0.000045437802,0.00014111762,0.000012267945,0.0005686237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859685,0.000041101575,0.0004646152,0.00032912943,0.00036117874,0.00020711872],"domain_scores_gemma":[0.99855953,0.000337609,0.00018481653,0.0006978813,0.00014189274,0.00007825816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083309785,0.0001988729,0.00019277807,0.00095957075,0.0004250968,0.00075566146,0.0014581151,0.00009226898,0.0000028181282],"category_scores_gemma":[0.000046023164,0.00020212996,0.000020375099,0.0005114042,0.0003940724,0.0074054785,0.001955308,0.00088720024,0.000011314047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020539642,0.0000069252887,0.00038347073,0.000083459,0.0000063411053,9.551798e-7,0.015140235,0.008300818,0.0000024580893,0.69816977,0.00001557553,0.27788794],"study_design_scores_gemma":[0.00015686017,0.000030342413,0.0045555807,0.0005717247,0.0000032901007,0.000021788675,0.00008130445,0.96504796,0.0000047788794,0.016924057,0.012313673,0.00028865325],"about_ca_topic_score_codex":0.000023653509,"about_ca_topic_score_gemma":0.000004956708,"teacher_disagreement_score":0.9567471,"about_ca_system_score_codex":0.00012749895,"about_ca_system_score_gemma":0.00020300054,"threshold_uncertainty_score":0.824262},"labels":[],"label_agreement":null},{"id":"W4405888516","doi":"10.1007/978-3-031-77138-5_16","title":"Modeling Sustainable Resource Management Using Active Inference","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Embodied and Extended Cognition","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Inference; Computer science; Resource (disambiguation); Information retrieval; Artificial intelligence","score_opus":0.08681938137578155,"score_gpt":0.3313173032863854,"score_spread":0.24449792191060388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405888516","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000080920116,0.00011179132,0.024655951,0.00020559329,0.0001015755,0.00036866928,0.000012402005,0.000084876796,0.9743782],"genre_scores_gemma":[0.9559709,0.0058904164,0.019514149,0.002090497,0.000080342616,0.000062775136,0.00006762508,0.00003650528,0.01628683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985701,0.000020651709,0.00044111785,0.00030885104,0.00038889365,0.00027037165],"domain_scores_gemma":[0.99858993,0.00011529214,0.00012120757,0.0009222864,0.00018070264,0.00007058891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048075712,0.00018660676,0.00015498101,0.0011385415,0.0006349723,0.0005347512,0.0011355728,0.00008702736,0.000008298917],"category_scores_gemma":[0.00004876177,0.0001905594,0.000034510573,0.00043271494,0.0005836748,0.0041141915,0.0022124592,0.0004720006,0.00007170353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035538071,0.000006157107,1.795389e-7,0.00006967893,0.0000018261082,0.0000020052669,0.00090882945,0.006621776,0.0000050044814,0.9527415,0.000010446775,0.039629065],"study_design_scores_gemma":[0.00009466917,0.000014636825,0.0000010392986,0.00031782905,0.000010772026,0.000014027834,0.0002659003,0.73277414,0.00003362804,0.2349146,0.031368624,0.00019012816],"about_ca_topic_score_codex":0.000012541577,"about_ca_topic_score_gemma":0.00000184961,"teacher_disagreement_score":0.9580914,"about_ca_system_score_codex":0.00025240675,"about_ca_system_score_gemma":0.00012727328,"threshold_uncertainty_score":0.7770786},"labels":[],"label_agreement":null},{"id":"W4405888578","doi":"10.1007/978-3-031-77138-5_3","title":"Free Energy in a Circumplex Model of Emotion","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mental Health Research Topics","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Energy (signal processing); Computer science; Information retrieval; Physics; Quantum mechanics","score_opus":0.17585020445524505,"score_gpt":0.4252276478821954,"score_spread":0.24937744342695037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405888578","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00030319937,0.0008425672,0.028475503,0.0009085868,0.00027506906,0.0003099775,0.00008279116,0.000025373834,0.96877694],"genre_scores_gemma":[0.8681808,0.012735588,0.053640418,0.0028281366,0.00012644943,0.00025017228,0.00043809414,0.00005354061,0.061746806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871653,0.000025809268,0.0006323927,0.00015108087,0.0003034936,0.00017071799],"domain_scores_gemma":[0.99808866,0.000105965926,0.00015071775,0.0014589023,0.00013526251,0.000060504037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086916564,0.00010082569,0.00016356609,0.0012536548,0.000083478415,0.000059119964,0.0013320424,0.00011458134,0.000049879814],"category_scores_gemma":[0.000019589093,0.0001049215,0.000023443386,0.0002903416,0.0006176097,0.0010238825,0.0012016383,0.00036062938,0.000030821382],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027319845,0.000013472043,0.000018049786,0.00005980839,0.0000018511553,1.6600985e-7,0.002418394,0.00017163223,0.0000013061843,0.88294065,0.00028084876,0.11409107],"study_design_scores_gemma":[0.00036169877,0.000063927466,0.0009993449,0.00041516652,0.0000029606729,0.00000858351,0.00009106364,0.7809786,0.0000032154508,0.16612342,0.050791983,0.00016002211],"about_ca_topic_score_codex":0.00014916089,"about_ca_topic_score_gemma":0.000091997914,"teacher_disagreement_score":0.9070301,"about_ca_system_score_codex":0.0001753997,"about_ca_system_score_gemma":0.00020007954,"threshold_uncertainty_score":0.42785743},"labels":[],"label_agreement":null},{"id":"W4405888620","doi":"10.1007/978-3-031-77138-5_8","title":"Belief Sharing: A Blessing or a Curse","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Blessing; Curse; Computer science; Philosophy; Theology","score_opus":0.11440602630750413,"score_gpt":0.39438849145950583,"score_spread":0.2799824651520017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405888620","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005598538,0.00032841935,0.0027456612,0.002437577,0.00037372913,0.00032498702,0.000013023679,0.00012108859,0.99359953],"genre_scores_gemma":[0.18562376,0.07027049,0.069227844,0.013789978,0.0008505965,0.00006150217,0.0003377213,0.00009106159,0.65974706],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998362,0.000015763431,0.00060480036,0.00016793073,0.00058414484,0.00026533473],"domain_scores_gemma":[0.9982414,0.00013110555,0.00022911941,0.0009313989,0.00028918794,0.0001777679],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0018035924,0.00016216788,0.0001837945,0.0010561977,0.0010544641,0.0016062688,0.0016606753,0.00014769417,0.00013624215],"category_scores_gemma":[0.00012529948,0.00014355086,0.000039808194,0.00054980366,0.0016773805,0.007424342,0.0010984915,0.00042777034,0.00042945865],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021955382,0.000005062475,0.0000037877026,0.000023878018,0.0000028632762,2.6801158e-7,0.03566873,0.00002035832,1.4483702e-7,0.8374366,0.0009269694,0.12590912],"study_design_scores_gemma":[0.00012989668,0.000020451198,0.00007335679,0.00046686918,0.0000075699336,0.000007709423,0.000916403,0.038842935,6.1700064e-7,0.015000411,0.94431484,0.00021893592],"about_ca_topic_score_codex":0.000060956747,"about_ca_topic_score_gemma":0.00017345506,"teacher_disagreement_score":0.94338787,"about_ca_system_score_codex":0.00026026572,"about_ca_system_score_gemma":0.0008927794,"threshold_uncertainty_score":0.9994302},"labels":[],"label_agreement":null},{"id":"W4405930277","doi":"10.1007/978-3-031-74643-7_20","title":"Side-Channel Based Runtime Intrusion Detection for Network Equipment","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Intrusion detection system; Intrusion; Side channel attack; Computer network; Computer security; Geology; Cryptography","score_opus":0.037996771651272014,"score_gpt":0.30260627079954794,"score_spread":0.2646094991482759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405930277","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000020196914,0.00036503936,0.9649841,0.0012029815,0.000758504,0.00075769576,0.000023752944,0.00012954637,0.031758174],"genre_scores_gemma":[0.3080834,0.0030397936,0.6813955,0.0044096094,0.00037541258,0.00060698274,0.00047966,0.000049584192,0.001560114],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998252,0.000018455152,0.00071515044,0.00033702355,0.00038560576,0.000291774],"domain_scores_gemma":[0.99761146,0.00026072137,0.00025406116,0.0014219462,0.00036090656,0.00009089992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014370189,0.00022249408,0.00021252115,0.0010915757,0.00078959455,0.000950311,0.0018332454,0.00011492187,0.000006491012],"category_scores_gemma":[0.000019558483,0.00022326865,0.00008721413,0.0006688137,0.0003773159,0.003294885,0.001715666,0.00031064916,0.000028968045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030334184,0.00001134364,0.0000022940371,0.000049934726,0.0000065505433,1.573486e-7,0.0007619553,0.0010890611,0.0000036658123,0.80862814,0.00029133866,0.18915255],"study_design_scores_gemma":[0.00022601556,0.00007967917,0.00008476785,0.00015272856,0.000008400844,0.000005360631,0.000012099303,0.74855405,0.000013935362,0.09093507,0.15970862,0.00021928769],"about_ca_topic_score_codex":0.000014007624,"about_ca_topic_score_gemma":0.000051564475,"teacher_disagreement_score":0.74746495,"about_ca_system_score_codex":0.00016296662,"about_ca_system_score_gemma":0.00022005034,"threshold_uncertainty_score":0.91638714},"labels":[],"label_agreement":null},{"id":"W4405930398","doi":"10.1007/978-3-031-74640-6_28","title":"Synthesizing Diabetic Foot Ulcer Images with Diffusion Model","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto; University Health Network","funders":"","keywords":"Diabetic foot ulcer; Diffusion; Computer science; Diabetic foot; Foot (prosody); Medicine; Diabetes mellitus; Physics; Art; Endocrinology; Thermodynamics","score_opus":0.02892315282517945,"score_gpt":0.2936893062712524,"score_spread":0.26476615344607296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405930398","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005052428,0.0005097345,0.03645093,0.0025956323,0.00012073153,0.0006898447,0.000009683029,0.00009792712,0.95902026],"genre_scores_gemma":[0.7651077,0.008393878,0.15751134,0.002983781,0.000092035734,0.00016492105,0.00021596478,0.000064552936,0.06546581],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988243,0.0000056433896,0.00037900728,0.00020253906,0.00041377536,0.00017472231],"domain_scores_gemma":[0.99848527,0.00007038945,0.00011644588,0.0010687439,0.00017460462,0.0000845786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044118823,0.00018646843,0.0002373468,0.00081204664,0.00018781985,0.0003052348,0.0005329161,0.000063787455,0.000015627815],"category_scores_gemma":[0.0000098250985,0.00014721444,0.000035638215,0.00020285198,0.000659047,0.0013747861,0.0010343593,0.00031815708,0.00005140125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018981125,0.00007003322,0.0002098969,0.0005819893,0.000055181034,0.0000026616815,0.0017613319,0.0006917009,0.000022663351,0.68020177,0.001172172,0.3152116],"study_design_scores_gemma":[0.00061261695,0.00019950989,0.0020256212,0.0025306435,0.0001571712,0.000019308203,0.000084703,0.87092733,0.000028655757,0.009759148,0.11322977,0.00042551942],"about_ca_topic_score_codex":0.000003697158,"about_ca_topic_score_gemma":0.000003106358,"teacher_disagreement_score":0.89355445,"about_ca_system_score_codex":0.00012934618,"about_ca_system_score_gemma":0.00017281526,"threshold_uncertainty_score":0.600323},"labels":[],"label_agreement":null},{"id":"W4405930413","doi":"10.1007/978-3-031-74640-6_24","title":"Cross-Modal Video to Body-Joints Augmentation for Rehabilitation Exercise Quality Assessment","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Modal; Rehabilitation; Quality (philosophy); Computer science; Physical medicine and rehabilitation; Physical therapy; Multimedia; Medicine; Physics; Materials science; Composite material","score_opus":0.053517058590403295,"score_gpt":0.4233737998868136,"score_spread":0.36985674129641033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405930413","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031347405,0.0015495473,0.3401335,0.03102284,0.005260044,0.017562509,0.00072586583,0.00062239304,0.5717759],"genre_scores_gemma":[0.32070288,0.0022380168,0.6400749,0.0035122666,0.0002658926,0.0012536631,0.0013980472,0.00006741578,0.030486925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979304,0.000021675114,0.0010293652,0.00032414246,0.0005104261,0.00018397644],"domain_scores_gemma":[0.99695456,0.00071647513,0.00023529264,0.0010982883,0.0008387855,0.00015662146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018777587,0.00020212049,0.00035355033,0.0012403731,0.00029793102,0.00037552067,0.00042052616,0.00014128641,0.000032552798],"category_scores_gemma":[0.00024337687,0.00019194814,0.00013162634,0.00032487008,0.0006128193,0.0020908823,0.00042749886,0.00030065735,0.00008317994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016107249,0.00011921677,0.0020987254,0.0014808226,0.00003521071,2.6252397e-7,0.0058092433,0.0005520674,0.00011985547,0.72963893,0.0019314211,0.25805318],"study_design_scores_gemma":[0.0034461692,0.0014690444,0.27717754,0.0046846857,0.00014565673,0.000026322985,0.0006534455,0.15523006,0.00006628999,0.051366176,0.5047137,0.0010209073],"about_ca_topic_score_codex":0.000014397735,"about_ca_topic_score_gemma":0.0000059604445,"teacher_disagreement_score":0.6782727,"about_ca_system_score_codex":0.00054955925,"about_ca_system_score_gemma":0.0004367988,"threshold_uncertainty_score":0.78274184},"labels":[],"label_agreement":null},{"id":"W4405930431","doi":"10.1007/978-3-031-74640-6_25","title":"Multimodal Sensor Fusion for Daily Living Activity Recognition in Active Assisted Living for Older Adults","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; University of Toronto; University of Waterloo","funders":"","keywords":"Assisted living; Activity recognition; Sensor fusion; Computer science; Psychology; Physical medicine and rehabilitation; Medicine; Artificial intelligence; Gerontology","score_opus":0.05592006971486409,"score_gpt":0.3058842812513628,"score_spread":0.24996421153649873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405930431","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004261021,0.00020559384,0.96649516,0.00092622906,0.0011803922,0.0038680423,0.0002569105,0.00027946668,0.022527162],"genre_scores_gemma":[0.86510813,0.0005098675,0.13131441,0.0004448618,0.00014335207,0.00097208645,0.00015373259,0.00004108185,0.0013124815],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976249,0.00007875921,0.0008597011,0.0006400923,0.00042513682,0.00037142533],"domain_scores_gemma":[0.9939681,0.0031259307,0.00055659696,0.0013443372,0.0008935222,0.00011147005],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001991091,0.00034641018,0.00043953853,0.0017591708,0.00051950756,0.0009473883,0.0017078789,0.00026230334,0.0000061959427],"category_scores_gemma":[0.0003681264,0.00037459534,0.00013403693,0.0005907775,0.00030133952,0.009213889,0.0018181809,0.00053996785,0.000038218055],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018898909,0.00007121114,0.000021747492,0.00024133964,0.000011842561,2.9621117e-7,0.007291955,0.000021419137,0.000026168636,0.005479132,0.00006475047,0.98675126],"study_design_scores_gemma":[0.0007838808,0.00012485677,0.00980863,0.005912714,0.000016866792,0.000038098307,0.00025791916,0.97130364,0.00005458155,0.0020639275,0.008960387,0.00067451264],"about_ca_topic_score_codex":0.00006688756,"about_ca_topic_score_gemma":0.00018986956,"teacher_disagreement_score":0.9860767,"about_ca_system_score_codex":0.0004707449,"about_ca_system_score_gemma":0.00033950873,"threshold_uncertainty_score":0.9998706},"labels":[],"label_agreement":null},{"id":"W4405930443","doi":"10.1007/978-3-031-74640-6_18","title":"Learning When to Observe: A Frugal Reinforcement Learning Framework for a High-Cost World","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Innovation and Socioeconomic Development","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Ottawa; Vector Institute; National Research Council Canada","funders":"","keywords":"Reinforcement learning; Computer science; Reinforcement; Artificial intelligence; Psychology; Social psychology","score_opus":0.04815994935224382,"score_gpt":0.28807436717449164,"score_spread":0.23991441782224782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405930443","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00036016997,0.00007740205,0.3100467,0.010400601,0.0014723846,0.0018398741,0.0000051551224,0.00027499377,0.67552274],"genre_scores_gemma":[0.37445807,0.0005828213,0.36634794,0.05259482,0.0017297929,0.0011187791,0.0016637614,0.00013152177,0.20137247],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856323,0.000003926908,0.0007139324,0.00023071807,0.00025316444,0.00023500352],"domain_scores_gemma":[0.99856937,0.00012977891,0.0003404705,0.0004991711,0.00043711846,0.000024116156],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0012788987,0.0002031958,0.00022108924,0.0015698409,0.000711075,0.0014358748,0.00091650826,0.000097195465,0.00010034019],"category_scores_gemma":[0.000116303985,0.00021521797,0.000042680775,0.0004412408,0.00018428368,0.003463827,0.0014766187,0.00062126113,0.0005296815],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004432717,0.0000032212477,0.00009577378,0.000078945865,0.000007938863,8.212543e-8,0.0012290062,0.0032099294,2.3152576e-7,0.9429556,0.0013393386,0.051075473],"study_design_scores_gemma":[0.00015636047,0.000010487721,0.00037923298,0.00037351553,0.000008232911,4.600788e-7,0.00010134446,0.104389526,6.0683055e-7,0.046495877,0.84782994,0.00025444114],"about_ca_topic_score_codex":0.00002765144,"about_ca_topic_score_gemma":0.000025727033,"teacher_disagreement_score":0.89645976,"about_ca_system_score_codex":0.00023761256,"about_ca_system_score_gemma":0.000117066455,"threshold_uncertainty_score":0.9996007},"labels":[],"label_agreement":null},{"id":"W4405930571","doi":"10.1007/978-3-031-74640-6_27","title":"Assessing Frailty Using Behavioral and Physical Health Data in Everyday Living Settings","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Frailty in Older Adults","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Computer science; Physical health; Psychology; Gerontology; Data science; Medicine; Psychiatry; Mental health","score_opus":0.17740655290220134,"score_gpt":0.4380779692855144,"score_spread":0.26067141638331304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405930571","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40642253,0.019636879,0.09319086,0.049663346,0.0036166785,0.009611177,0.0009336223,0.001185423,0.41573948],"genre_scores_gemma":[0.8775083,0.0018649474,0.117152564,0.0019025957,0.00013221524,0.000011420728,0.00041485517,0.000032924454,0.0009801951],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998512,0.00002423412,0.0005869891,0.00029949154,0.00036826212,0.00020896562],"domain_scores_gemma":[0.9976715,0.0002267899,0.00021217055,0.0016582685,0.0001224342,0.0001088715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012337805,0.00017682256,0.0003218237,0.0007599846,0.00025127464,0.0005342698,0.0008240954,0.00008550016,0.0000034102509],"category_scores_gemma":[0.00007172356,0.00017598903,0.00002020304,0.00031454812,0.0007268702,0.0057039023,0.0030448898,0.0007227652,0.0000086772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005950797,0.00015986584,0.003343286,0.0010559799,0.000018453848,0.000005525235,0.033318527,0.00012388371,0.000039176102,0.028166497,0.0006357212,0.9331271],"study_design_scores_gemma":[0.00033211484,0.000081062586,0.014899615,0.006307417,0.00003110787,0.00015421418,0.00037594864,0.95025396,0.0000020430393,0.0010501258,0.026209267,0.00030313004],"about_ca_topic_score_codex":0.000120830315,"about_ca_topic_score_gemma":0.00004233953,"teacher_disagreement_score":0.95013005,"about_ca_system_score_codex":0.00027522878,"about_ca_system_score_gemma":0.0005414182,"threshold_uncertainty_score":0.71766245},"labels":[],"label_agreement":null},{"id":"W4406457429","doi":"10.1007/978-3-031-80419-9","title":"Emerging Information Security and Applications","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Information and Cyber Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Surrey; University of Waterloo; Jiangsu University; Universiteit van Amsterdam; Norges Teknisk-Naturvitenskapelige Universitet; Università degli Studi di Padova; Jiangsu University of Technology; University of Wollongong","keywords":"Computer science; Information security; Information retrieval; Computer security","score_opus":0.012526226786358093,"score_gpt":0.27712177577200625,"score_spread":0.26459554898564813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406457429","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008525566,0.00035109647,0.5378996,0.0016108048,0.0002245556,0.0006923183,0.000027449907,0.00016705615,0.45901856],"genre_scores_gemma":[0.113035776,0.05664188,0.741859,0.063065186,0.0006613444,0.003072354,0.0039767316,0.000067154455,0.017620573],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99795306,0.000048763566,0.00097406877,0.00023857463,0.0004925025,0.00029306285],"domain_scores_gemma":[0.9965987,0.00018255565,0.00044769456,0.0020148456,0.00062069437,0.00013545985],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001297296,0.00025553262,0.00026995258,0.0017939283,0.00084326975,0.0015142895,0.0030658427,0.00017899534,0.0000041086128],"category_scores_gemma":[0.00005525263,0.00027373506,0.000041802105,0.001333915,0.0006802674,0.024832178,0.0035944218,0.00058241066,0.00006163457],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.257358e-7,0.0000085689035,0.000014331454,0.00008429639,0.000003250154,3.6531915e-8,0.0043328004,0.000024465882,7.0992506e-8,0.7116757,0.001580024,0.28227574],"study_design_scores_gemma":[0.00025457478,0.000014809565,0.00043050537,0.00011712214,0.0000048133074,0.000012777164,0.00008220168,0.2438885,0.0000028869363,0.019179128,0.7357459,0.0002667798],"about_ca_topic_score_codex":0.000016559974,"about_ca_topic_score_gemma":0.000009815603,"teacher_disagreement_score":0.73416585,"about_ca_system_score_codex":0.00024036759,"about_ca_system_score_gemma":0.00094548124,"threshold_uncertainty_score":0.9999715},"labels":[],"label_agreement":null},{"id":"W4406771321","doi":"10.1007/978-981-96-1024-2_8","title":"Evaluation of Retrieval-Augmented Generation: A Survey","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":104,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Information retrieval; Computer science; Thesaurus; Natural language processing","score_opus":0.17110464924601465,"score_gpt":0.3563433662537061,"score_spread":0.18523871700769146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406771321","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018516606,0.0007269014,0.8396555,0.0004626238,0.00045752912,0.00054561254,0.000018365094,0.00004438149,0.1579039],"genre_scores_gemma":[0.469556,0.0053093713,0.5185835,0.0016377412,0.0001239328,0.00006736978,0.00048317993,0.000018416535,0.004220487],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99746394,0.0001518403,0.00083349855,0.00027161205,0.0011405181,0.00013857232],"domain_scores_gemma":[0.9944987,0.0002106215,0.00040619564,0.0023999275,0.0024355496,0.000048964295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008081684,0.00015238451,0.00022398915,0.001017277,0.00023787202,0.00027908877,0.0025967192,0.00011067437,0.0000084792255],"category_scores_gemma":[0.00030555076,0.0001606611,0.00003318388,0.00063545647,0.00035812883,0.0037973248,0.0018449321,0.00024110594,0.000007952628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016329664,0.000014181253,0.000053066142,0.000021602154,0.0000105187155,4.052156e-8,0.0007842046,0.0020744773,0.000009586058,0.5188041,0.0003039443,0.47792268],"study_design_scores_gemma":[0.00026545746,0.000019009738,0.0010916939,0.00013094109,0.000011405131,0.0000022452377,0.0000032188223,0.98858017,0.000036058853,0.004298251,0.0054217307,0.00013981017],"about_ca_topic_score_codex":0.00002927326,"about_ca_topic_score_gemma":0.000037122998,"teacher_disagreement_score":0.9865057,"about_ca_system_score_codex":0.00023886941,"about_ca_system_score_gemma":0.0011804871,"threshold_uncertainty_score":0.65515697},"labels":[],"label_agreement":null},{"id":"W4406819681","doi":"10.1007/978-3-031-81455-6_18","title":"On Solving the Physicians Scheduling Problem at an Emergency Department: A Case Study from Canada","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Emergency department; Scheduling (production processes); Operations research; Computer science; Medical emergency; Operations management; Medicine; Engineering; Nursing","score_opus":0.09052007791210864,"score_gpt":0.36514774189895516,"score_spread":0.2746276639868465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406819681","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41500217,0.0024386467,0.1028645,0.008706226,0.005130942,0.0058262423,0.0009282837,0.0003342613,0.45876873],"genre_scores_gemma":[0.98176885,0.00019503044,0.014570042,0.0008426239,0.00005075553,0.00005493649,0.000064138236,0.000007949693,0.0024456934],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99688536,0.00014402633,0.0011076666,0.00042562708,0.0011746174,0.00026269344],"domain_scores_gemma":[0.99420625,0.0014749283,0.0005328431,0.0030117347,0.00067530863,0.000098915705],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0029322626,0.00023113466,0.00028662934,0.0006473222,0.0026200137,0.00065271574,0.0029735328,0.00006947589,0.000043892614],"category_scores_gemma":[0.00040446548,0.0001728192,0.00005536187,0.00084729766,0.0004075417,0.0020631417,0.001703077,0.0004923476,0.00003545474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026873093,0.00038504874,0.003634329,0.000016728056,0.00011348443,0.000032734948,0.029445715,0.04951646,0.000003217191,0.22719409,0.006397283,0.68323404],"study_design_scores_gemma":[0.00061548763,0.00016587999,0.0032077434,0.0002743033,0.00007331192,0.00007322963,0.004289007,0.8935389,0.000004272369,0.03614394,0.060939755,0.0006741795],"about_ca_topic_score_codex":0.040346526,"about_ca_topic_score_gemma":0.25370196,"teacher_disagreement_score":0.84402245,"about_ca_system_score_codex":0.00032783503,"about_ca_system_score_gemma":0.00090541324,"threshold_uncertainty_score":0.99867845},"labels":[],"label_agreement":null},{"id":"W4406828381","doi":"10.1007/978-3-031-77941-1_20","title":"Nature-Inspired Techniques for Combinatorial Reverse Auctions in Electricity Consumption","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Common value auction; Computer science; Consumption (sociology); Electricity; Combinatorial auction; Operations research; Microeconomics; Engineering; Economics; Electrical engineering; Art","score_opus":0.0667212499314264,"score_gpt":0.3925477525379666,"score_spread":0.32582650260654017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406828381","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004744681,0.0007990467,0.55891126,0.0065906374,0.0023111973,0.004556415,0.00033336206,0.00033401814,0.4256896],"genre_scores_gemma":[0.5717225,0.021074427,0.33900654,0.011448358,0.0007801552,0.0029738247,0.0011952108,0.00008240699,0.051716592],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974164,0.0000813096,0.0012788996,0.0004058115,0.00059901836,0.00021861056],"domain_scores_gemma":[0.99508125,0.0015066974,0.00058254297,0.0017987322,0.00095537223,0.00007542938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043028477,0.00020933826,0.00034818306,0.0021139807,0.000789111,0.00045466473,0.0022793922,0.00035738313,0.000028389268],"category_scores_gemma":[0.00088918186,0.00020545852,0.000086339256,0.0012059758,0.0010563501,0.0033186767,0.00076580665,0.0007657255,0.00004512511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013252328,0.00002589313,0.00008690603,0.000010680872,0.000002626944,4.1115474e-8,0.00017094015,0.000029781906,0.000005410684,0.89554065,0.0034709868,0.10064281],"study_design_scores_gemma":[0.00039170618,0.00004043258,0.0007803523,0.00012867634,0.000008864191,0.000005794474,0.000034024713,0.027345303,0.000082012324,0.32251278,0.6484281,0.00024198266],"about_ca_topic_score_codex":0.000010550597,"about_ca_topic_score_gemma":0.000027469883,"teacher_disagreement_score":0.6449571,"about_ca_system_score_codex":0.0002860474,"about_ca_system_score_gemma":0.00042301955,"threshold_uncertainty_score":0.8378355},"labels":[],"label_agreement":null},{"id":"W4406828593","doi":"10.1007/978-3-031-77941-1_17","title":"Biologically-Inspired Algorithms for Adaptive Non-Player Character Behavior in Video Games","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Character (mathematics); Video game; Artificial intelligence; Algorithm; Multimedia; Mathematics","score_opus":0.08307458231393706,"score_gpt":0.33970571898676777,"score_spread":0.2566311366728307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406828593","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001743456,0.00020207702,0.94754755,0.0012667574,0.00059728645,0.0014664592,0.000045167446,0.00009968228,0.04860064],"genre_scores_gemma":[0.10497382,0.0029881122,0.88311875,0.0041943425,0.00011306111,0.0010274361,0.00013567232,0.000019709574,0.0034290662],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784523,0.000033438617,0.0010110926,0.00045443588,0.0003143771,0.00034144885],"domain_scores_gemma":[0.99660236,0.00057538814,0.00037139896,0.0018078625,0.0005576367,0.000085379776],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011547144,0.00028294307,0.00037200373,0.0013632689,0.00033924857,0.0005210543,0.004172246,0.00022793138,0.000006882454],"category_scores_gemma":[0.00010537058,0.0002677624,0.00008158898,0.0005558824,0.0008940516,0.0049247216,0.0023752016,0.0004540745,0.00003923128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000073587935,0.000039649745,0.00014934782,0.000015218988,0.000004457967,6.735887e-7,0.0013813825,0.00008584179,0.000011456491,0.36293548,0.0002512919,0.6351178],"study_design_scores_gemma":[0.0002604391,0.00018170262,0.0058453823,0.00038748066,0.000008906252,0.000008388942,0.000048727543,0.88419974,0.00016278225,0.014623917,0.09372404,0.0005484966],"about_ca_topic_score_codex":0.00003381474,"about_ca_topic_score_gemma":0.000034256336,"teacher_disagreement_score":0.8841139,"about_ca_system_score_codex":0.00020918598,"about_ca_system_score_gemma":0.00038087755,"threshold_uncertainty_score":0.99997747},"labels":[],"label_agreement":null},{"id":"W4406986776","doi":"10.1007/978-3-031-77493-5_7","title":"Exploring the Impact of AI-Driven Gamification on Visitor Engagement in Museums: A Critical Review","year":2025,"lang":"en","type":"review","venue":"Communications in computer and information science","topic":"Educational Games and Gamification","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Visitor pattern; Computer science; World Wide Web; Library science","score_opus":0.2969062676543609,"score_gpt":0.505234548046232,"score_spread":0.20832828039187112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406986776","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000055173336,0.9886144,0.0028732903,0.0020945347,0.00050718687,0.0015186111,0.00003268145,0.000020726762,0.004283409],"genre_scores_gemma":[0.0055589764,0.9920167,0.0010681365,0.00036917705,0.00002759818,0.00085898454,0.00008790727,0.0000045390243,0.0000080139735],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99770683,0.00051336724,0.0011107739,0.00022798203,0.00025218326,0.00018884717],"domain_scores_gemma":[0.9958637,0.0016407035,0.00033492598,0.0018326471,0.00028345655,0.00004460662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002141321,0.00018372583,0.00047999172,0.0009889641,0.0001901086,0.000102258266,0.0016303904,0.000058459143,0.00001857513],"category_scores_gemma":[0.0004687552,0.00013000863,0.0001257531,0.0022892326,0.00045075858,0.0014612213,0.0003843344,0.0005627388,0.000037497663],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015608631,0.00011867351,0.000040477928,0.0022306982,0.000009048828,3.815672e-8,0.002373581,0.000038753136,4.231339e-8,0.066131,0.00040884144,0.9286473],"study_design_scores_gemma":[0.0002450698,0.0001432728,0.032662004,0.055800483,0.00008751867,0.0000112123635,0.00040935696,0.0046965606,2.4115775e-7,0.00025542648,0.9053163,0.00037254192],"about_ca_topic_score_codex":0.00007046806,"about_ca_topic_score_gemma":0.0000031026916,"teacher_disagreement_score":0.92827475,"about_ca_system_score_codex":0.00027189692,"about_ca_system_score_gemma":0.0005462983,"threshold_uncertainty_score":0.5301598},"labels":[],"label_agreement":null},{"id":"W4407237133","doi":"10.1007/978-3-031-74630-7_11","title":"Mitigating Discrimination in Insurance with Wasserstein Barycenters","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Computer science; Business","score_opus":0.03575423890153752,"score_gpt":0.23933381675284537,"score_spread":0.20357957785130787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407237133","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060321162,0.00064465444,0.0065864003,0.00063647726,0.00032164258,0.0004558315,0.000064321575,0.00002565535,0.9852329],"genre_scores_gemma":[0.99231905,0.0017133116,0.0042371317,0.0003970718,0.000022779806,0.000030446285,0.00007278915,0.000007901498,0.0011995006],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99851733,0.000009418852,0.0009902553,0.00024739842,0.000058264595,0.00017734579],"domain_scores_gemma":[0.9985034,0.00007719292,0.00053286727,0.00075894373,0.00008108098,0.00004652416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008966388,0.00013643988,0.00034119558,0.001031493,0.00021465453,0.00026754747,0.0008387873,0.000097560864,0.000008978462],"category_scores_gemma":[0.00003439596,0.00017782454,0.00003183126,0.00027041193,0.00052879454,0.003199843,0.00029730922,0.00025532252,0.000036505466],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044736444,0.00001002422,0.009769222,0.00005201702,0.000004765001,1.5376273e-7,0.0017750632,0.00014187563,1.9644298e-7,0.9731666,0.000030368252,0.015045228],"study_design_scores_gemma":[0.0035966956,0.00024045291,0.21830195,0.004596253,0.000012829661,0.00001906254,0.0010374596,0.31480366,0.00001893177,0.32827997,0.12700228,0.0020904317],"about_ca_topic_score_codex":0.00017569939,"about_ca_topic_score_gemma":0.00044844294,"teacher_disagreement_score":0.98628694,"about_ca_system_score_codex":0.00030287643,"about_ca_system_score_gemma":0.00009124781,"threshold_uncertainty_score":0.7251474},"labels":[],"label_agreement":null},{"id":"W4407269550","doi":"10.1007/978-3-031-79103-1_2","title":"Optimized Brain Tumor Segmentation for Resource Constrained Settings: VGG-Infused U-Net Approach","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; University of British Columbia; Artificial Intelligence in Medicine (Canada); Lawson Health Research Institute","funders":"","keywords":"Segmentation; Computer science; Resource (disambiguation); Net (polyhedron); Artificial intelligence; Mathematics","score_opus":0.04709910892347795,"score_gpt":0.29741353647198154,"score_spread":0.2503144275485036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407269550","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006265275,0.0000692776,0.38096812,0.005844635,0.00034051473,0.0028206785,0.00019689335,0.00028834495,0.60940886],"genre_scores_gemma":[0.07281446,0.0012697913,0.8063346,0.06332209,0.0002764618,0.0019447635,0.0019394857,0.000111632726,0.051986706],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978379,0.00009814316,0.0009058463,0.00046797332,0.00041993475,0.0002702103],"domain_scores_gemma":[0.99659157,0.0011545102,0.000619416,0.0012701639,0.00026303978,0.00010127422],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014573713,0.00027311165,0.0003060782,0.0010961277,0.0008703855,0.0005614249,0.0014534103,0.0001321103,0.00001246333],"category_scores_gemma":[0.0006668127,0.00028836066,0.00007954944,0.0005605733,0.0013406698,0.0022324838,0.00054270105,0.00042497838,0.000015555313],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000087816756,0.00008293966,0.000003941426,0.00027032106,0.0000106138295,3.465065e-7,0.003049358,0.001189236,0.0014915046,0.745958,0.011999745,0.23585619],"study_design_scores_gemma":[0.0017333257,0.000079134574,0.000051904095,0.00021835492,0.000016927517,0.000038992675,0.00028862446,0.6447673,0.0012402555,0.0026957493,0.34841374,0.00045570417],"about_ca_topic_score_codex":0.0000029175403,"about_ca_topic_score_gemma":0.000001187946,"teacher_disagreement_score":0.74326223,"about_ca_system_score_codex":0.00021823627,"about_ca_system_score_gemma":0.00037247626,"threshold_uncertainty_score":0.99995685},"labels":[],"label_agreement":null},{"id":"W4407269637","doi":"10.1007/978-3-031-79103-1_12","title":"Generative Style Transfer for MR Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan Africa","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; University of British Columbia; Artificial Intelligence in Medicine (Canada); Lawson Health Research Institute","funders":"","keywords":"Segmentation; Style (visual arts); Generative grammar; Artificial intelligence; Computer science; Image segmentation; Computer vision; Pattern recognition (psychology); Natural language processing; Geography","score_opus":0.03798201701427577,"score_gpt":0.32664313038377163,"score_spread":0.28866111336949585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407269637","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000112586924,0.0004254009,0.9849281,0.0004953567,0.0001301105,0.001449079,0.00008236002,0.000066065935,0.012310942],"genre_scores_gemma":[0.008308042,0.0024315955,0.98763967,0.0005834667,0.000019765013,0.00040357577,0.00019508443,0.000010554264,0.00040825427],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977857,0.00007834611,0.0011593372,0.00034611323,0.00040349123,0.00022703236],"domain_scores_gemma":[0.9974192,0.00042046458,0.00029900047,0.0011529698,0.0006211912,0.000087198314],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013093977,0.00024075333,0.00033757766,0.0017418001,0.00027335453,0.00034578115,0.0016198212,0.00012644204,0.000010549334],"category_scores_gemma":[0.00006715701,0.00025345187,0.00006614233,0.0008430114,0.000736421,0.0060388953,0.0006578147,0.00027225266,0.000004808536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020679761,0.00011864943,0.000006022464,0.0003324115,0.000024611223,0.000013834979,0.012842689,0.00009645889,0.004400645,0.16139653,0.002795102,0.81795233],"study_design_scores_gemma":[0.0038670981,0.0004999797,0.00010543568,0.0012666526,0.000048996397,0.00024446743,0.0004287915,0.8973111,0.07163632,0.013133251,0.010294521,0.0011634133],"about_ca_topic_score_codex":0.00002244455,"about_ca_topic_score_gemma":0.000036280388,"teacher_disagreement_score":0.8972146,"about_ca_system_score_codex":0.00023272696,"about_ca_system_score_gemma":0.0003868504,"threshold_uncertainty_score":0.9999918},"labels":[],"label_agreement":null},{"id":"W4407363760","doi":"10.1007/978-3-031-81342-9_24","title":"Digital Twin for Diabetes Management Using System Dynamics Simulation - The Case of India","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"General Dynamics (Canada)","funders":"","keywords":"Computer science; Dynamics (music); System dynamics; Artificial intelligence; Psychology","score_opus":0.02753392698624944,"score_gpt":0.268691666675662,"score_spread":0.2411577396894126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407363760","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00053722283,0.000074437114,0.40227845,0.000033560704,0.00025248373,0.00078591635,0.00029265694,0.00008032828,0.5956649],"genre_scores_gemma":[0.98929226,0.000073130854,0.010084341,0.00004127906,0.000012292382,0.0000342068,0.00015365375,0.000009270327,0.00029956168],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991112,0.0000045494376,0.0005742959,0.000071958675,0.00012635147,0.0001116806],"domain_scores_gemma":[0.9987654,0.0002466501,0.00013111917,0.0006577593,0.0001743842,0.000024676297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032416556,0.0001255662,0.00014065638,0.0005400953,0.00019901649,0.00032213502,0.00063507917,0.0000825416,6.592568e-7],"category_scores_gemma":[0.000009254037,0.00011585309,0.000035407134,0.00025119857,0.00030959252,0.0031664965,0.0002680205,0.00015460247,0.0000017026435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.689987e-7,0.00000414717,0.000023241537,0.0006771976,0.000021346435,2.7114194e-7,0.00040219442,0.27077612,9.1467236e-8,0.46757057,0.000040243718,0.2604836],"study_design_scores_gemma":[0.00011548199,0.0000068272752,0.000027824057,0.00040744932,0.000012629841,0.000008475038,0.00019743702,0.9907215,0.0000022636702,0.0005279934,0.00786564,0.00010647136],"about_ca_topic_score_codex":7.3410445e-7,"about_ca_topic_score_gemma":0.000001188498,"teacher_disagreement_score":0.98875505,"about_ca_system_score_codex":0.00022951653,"about_ca_system_score_gemma":0.000038981812,"threshold_uncertainty_score":0.47243518},"labels":[],"label_agreement":null},{"id":"W4407364688","doi":"10.1007/978-3-031-80760-2_8","title":"An Inventory Management Support Tool Through Indirect Q-Value Estimation: A Combined Optimization and Forecasting Approach","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Cégep Saint-Jean-sur-Richelieu","funders":"","keywords":"Estimation; Inventory management; Computer science; Value (mathematics); Operations research; Operations management; Mathematics; Systems engineering; Engineering; Machine learning","score_opus":0.1366351247358329,"score_gpt":0.3714684271611959,"score_spread":0.234833302425363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407364688","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000719024,0.000058019155,0.677464,0.0003288506,0.000078613724,0.00076809747,0.000023556457,0.00010481264,0.32110217],"genre_scores_gemma":[0.029242203,0.0007096547,0.96633685,0.0008081192,0.000019596062,0.00014866222,0.00030574255,0.000011684956,0.0024175015],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969816,0.000072093215,0.0013537639,0.0004978127,0.00087205664,0.000222623],"domain_scores_gemma":[0.9961203,0.00036621792,0.00069095846,0.0022015334,0.0005344106,0.00008660445],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003633934,0.00025787638,0.00036197246,0.0012800157,0.0008866815,0.001137371,0.002329485,0.0001530269,0.0000199318],"category_scores_gemma":[0.00019362198,0.00024332914,0.00005009284,0.0009596797,0.0009917297,0.0053039435,0.0017986579,0.00033539147,0.000010056718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004901729,0.00003245087,0.000084037216,0.00004157632,0.0000068784357,1.818996e-7,0.000982697,0.023054548,2.2551164e-7,0.7205736,0.0008733478,0.25434557],"study_design_scores_gemma":[0.00023537072,0.00006034752,0.00025829973,0.00013635392,0.000013397647,0.000013451539,0.00007529046,0.931909,0.0000023166456,0.04276478,0.024286633,0.00024475908],"about_ca_topic_score_codex":0.000009394817,"about_ca_topic_score_gemma":0.000002389105,"teacher_disagreement_score":0.9088544,"about_ca_system_score_codex":0.0001329234,"about_ca_system_score_gemma":0.00019739804,"threshold_uncertainty_score":0.99989957},"labels":[],"label_agreement":null},{"id":"W4407364934","doi":"10.1007/978-3-031-80760-2_6","title":"Machine Learning Tool for Yield Maximization in Cream Cheese Production","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Polytechnique Montréal; École Nationale d'Administration Publique","funders":"","keywords":"Maximization; Production (economics); Yield (engineering); Computer science; Food science; Mathematics; Chemistry; Mathematical optimization; Materials science; Economics; Microeconomics","score_opus":0.035344790678278046,"score_gpt":0.303104705498744,"score_spread":0.26775991482046596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407364934","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014399376,0.0022099628,0.08193006,0.0018241905,0.00027767633,0.00079771836,0.000060015474,0.00018271897,0.9112777],"genre_scores_gemma":[0.67363733,0.040487304,0.12785994,0.0014724577,0.0003180737,0.00048862107,0.00260141,0.00005858863,0.15307629],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989662,0.0000055363876,0.0005090409,0.00019903695,0.00017732357,0.00014281795],"domain_scores_gemma":[0.99864906,0.00015486046,0.00023674224,0.0006986195,0.00023460951,0.000026122802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050803914,0.00014532516,0.00020479177,0.000996931,0.0002857704,0.00015806775,0.0006858213,0.00013187801,0.000056932702],"category_scores_gemma":[0.00041815577,0.00015415587,0.00003673901,0.00053139176,0.00025023083,0.0015673973,0.00040445846,0.0004026834,0.0000040089626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009865877,0.00030378232,0.007043201,0.001427724,0.00007810294,4.5161275e-7,0.004147827,0.010014451,0.0011334107,0.31587052,0.0016521548,0.6582297],"study_design_scores_gemma":[0.000793072,0.0000735765,0.0009312824,0.00081372674,0.000074196956,0.000011325811,0.00013535483,0.7604422,0.0020381524,0.0065784394,0.22739333,0.00071535335],"about_ca_topic_score_codex":0.00001968629,"about_ca_topic_score_gemma":0.000017651142,"teacher_disagreement_score":0.7582014,"about_ca_system_score_codex":0.00018715345,"about_ca_system_score_gemma":0.00014626163,"threshold_uncertainty_score":0.62862945},"labels":[],"label_agreement":null},{"id":"W4407506113","doi":"10.1007/978-3-031-80775-6_6","title":"Towards the Automation of the Product Definition Process for Design-to-Order Manufacturing Systems","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Automation; Computer science; Manufacturing engineering; Product (mathematics); Order (exchange); Process (computing); Process automation system; Process engineering; Engineering; Mathematics; Business; Mechanical engineering; Programming language","score_opus":0.05224939196629803,"score_gpt":0.26863116464394,"score_spread":0.21638177267764197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407506113","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007902762,0.00023564439,0.95511645,0.00041707244,0.00039342433,0.0014980424,0.000022879307,0.00006763037,0.042169802],"genre_scores_gemma":[0.78821224,0.002309309,0.20611185,0.00056819204,0.00011161102,0.0009315256,0.0001577429,0.000039339775,0.0015581768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991167,0.000013681257,0.0004398503,0.000103842955,0.00021846584,0.00010745431],"domain_scores_gemma":[0.99863666,0.00010670022,0.00015985436,0.0007414234,0.000334962,0.000020415644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006027143,0.00012934231,0.00013546526,0.00032157276,0.00032344233,0.00017887514,0.0009848034,0.00005767679,0.0000015907543],"category_scores_gemma":[0.00005202741,0.00008988039,0.000023583694,0.00022402279,0.00016434312,0.0009830075,0.00024482695,0.00015663753,0.0000018539293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003042791,0.000004153207,0.000002674342,0.0005487247,0.000008145213,4.489078e-9,0.0015150354,0.870176,0.0000017439158,0.041745003,0.00019995715,0.085795514],"study_design_scores_gemma":[0.0001127168,0.000012673004,0.00037936826,0.0004981366,0.000013309573,0.0000019770055,0.000027785347,0.9848395,0.00083855103,0.0022838193,0.010851905,0.0001402491],"about_ca_topic_score_codex":0.0000040345376,"about_ca_topic_score_gemma":0.0000020586333,"teacher_disagreement_score":0.7881332,"about_ca_system_score_codex":0.000076782526,"about_ca_system_score_gemma":0.00012362686,"threshold_uncertainty_score":0.36652163},"labels":[],"label_agreement":null},{"id":"W4407719212","doi":"10.1007/978-981-96-2292-4_7","title":"Joint Multi-modal Modeling for Speech-to-Text Translation as Multilingual Neural Machine Translation","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Machine translation; Translation (biology); Natural language processing; Joint (building); Modal; Artificial intelligence; Speech recognition; Engineering; Biology; Chemistry; Messenger RNA; Structural engineering","score_opus":0.07970553934307349,"score_gpt":0.3535581530429059,"score_spread":0.2738526136998324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407719212","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000030170142,0.0022857182,0.9880189,0.0018606104,0.00023083723,0.0011186999,0.00002993535,0.0002789557,0.0061461944],"genre_scores_gemma":[0.052330453,0.00029726082,0.94590753,0.00097558845,0.000025914745,0.0000563039,0.000105107145,0.000010318755,0.00029154393],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979461,0.000031229352,0.00088620227,0.00043050657,0.0004287476,0.00027724044],"domain_scores_gemma":[0.9974494,0.00021435734,0.00025150276,0.0013837633,0.0005924523,0.00010853956],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011319184,0.0002971817,0.00030982654,0.001510116,0.0005440264,0.0006851512,0.0026093216,0.00019282084,0.0000021061066],"category_scores_gemma":[0.000098774704,0.0003022836,0.00008775361,0.0005247748,0.00022296152,0.005209189,0.00081802433,0.00048789303,0.000008378641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007736252,0.000014655854,0.0000011654531,0.000056901645,0.0000036188112,2.2922102e-7,0.0022820344,0.0025211263,0.000037456117,0.06478842,0.000015852074,0.9302708],"study_design_scores_gemma":[0.000413658,0.00005765809,0.0000054795855,0.0002728245,0.000007806328,0.000012798193,0.000009014903,0.9843426,0.00015381894,0.009104039,0.0053115445,0.00030876647],"about_ca_topic_score_codex":0.000046658453,"about_ca_topic_score_gemma":0.00004462449,"teacher_disagreement_score":0.9818215,"about_ca_system_score_codex":0.00014920362,"about_ca_system_score_gemma":0.00032381556,"threshold_uncertainty_score":0.9999429},"labels":[],"label_agreement":null},{"id":"W4407745814","doi":"10.1007/978-3-031-80475-5_7","title":"A Literature Review and Taxonomy of In-VR Questionnaire User Interfaces","year":2025,"lang":"en","type":"review","venue":"Communications in computer and information science","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Taxonomy (biology); Computer science; Information retrieval; Thesaurus; World Wide Web; Human–computer interaction; Natural language processing; Biology; Botany","score_opus":0.06056850846383494,"score_gpt":0.3675262344836709,"score_spread":0.30695772601983595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407745814","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000001022664,0.9200476,0.0774286,0.0004780685,0.00004623109,0.0008577777,0.0000129705695,0.000020662741,0.001107061],"genre_scores_gemma":[0.00024070947,0.9687636,0.030321658,0.0004258243,0.0000034815885,0.00021544503,0.000020039113,0.000001872922,0.000007358285],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983281,0.00014707046,0.0009422443,0.0002458314,0.00017098743,0.00016575199],"domain_scores_gemma":[0.9973257,0.00024997693,0.00039315168,0.0017114442,0.00025132913,0.00006837991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012434268,0.00018903484,0.0006490536,0.0011626024,0.00014253757,0.00041291615,0.0026573848,0.00009576698,5.7258075e-7],"category_scores_gemma":[0.00020324218,0.00015946222,0.000044650344,0.0039901435,0.00044191538,0.0055743307,0.0022106047,0.00034571116,0.0000032618245],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2793105e-7,0.00001854673,0.000009310402,0.008316609,0.0000023915659,5.715964e-8,0.0003399402,0.0000020661432,1.809503e-8,0.04520607,0.00008519195,0.94601965],"study_design_scores_gemma":[0.00010297076,0.0000287075,0.00033122575,0.09047959,0.000024092078,0.000029593715,0.0000095680525,0.005963891,4.7711575e-7,0.00029767258,0.9025209,0.00021129286],"about_ca_topic_score_codex":0.000017796609,"about_ca_topic_score_gemma":0.000010480465,"teacher_disagreement_score":0.94580835,"about_ca_system_score_codex":0.00008627192,"about_ca_system_score_gemma":0.00051637465,"threshold_uncertainty_score":0.650268},"labels":[],"label_agreement":null},{"id":"W4407746066","doi":"10.1007/978-3-031-80475-5_20","title":"Exploring the Inclusive Design and Use of Social Multi-platform Virtual Reality for a Post-secondary Gender Diversity Workshop","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Algonquin College","funders":"","keywords":"Diversity (politics); Virtual reality; Computer science; Data science; World Wide Web; Sociology; Human–computer interaction; Anthropology","score_opus":0.29666188728666854,"score_gpt":0.35031150817993634,"score_spread":0.0536496208932678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407746066","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021417336,0.00006127173,0.99358416,0.0015340619,0.000094723626,0.0008213976,0.00008354988,0.000031390617,0.0035752745],"genre_scores_gemma":[0.34936836,0.004898466,0.6399035,0.00410071,0.00006116985,0.00029189637,0.00019384235,0.000017435079,0.0011646296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869406,0.000043788983,0.0005377687,0.00024028434,0.00029585874,0.00018821182],"domain_scores_gemma":[0.9965666,0.0011544444,0.00034619265,0.001224089,0.0006378917,0.00007080467],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0014434395,0.00017449034,0.00023618655,0.00049818074,0.001727492,0.00045408748,0.0022450588,0.00009162442,0.0000010331088],"category_scores_gemma":[0.00016904261,0.0001499103,0.000053862357,0.00037272146,0.0009875341,0.008198236,0.0070605697,0.00032777444,0.000001273456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008625866,0.000015968839,0.0000033659546,0.000026833937,0.000010648284,3.306743e-8,0.0108858645,0.00021031169,0.0000023973132,0.6570302,0.00021292767,0.3315928],"study_design_scores_gemma":[0.00084527413,0.00013363942,0.011011895,0.00017138993,0.000032410633,0.000009075129,0.0005329789,0.9036599,0.000027030499,0.016448447,0.06665197,0.00047603063],"about_ca_topic_score_codex":0.000053790583,"about_ca_topic_score_gemma":0.000023709856,"teacher_disagreement_score":0.90344954,"about_ca_system_score_codex":0.00012748754,"about_ca_system_score_gemma":0.0004550545,"threshold_uncertainty_score":0.9995721},"labels":[],"label_agreement":null},{"id":"W4407898024","doi":"10.1007/978-981-96-1907-8_2","title":"Single Cell RNA-Seq Analysis Reveals Similarities Between Colorectal, Liver and Lung T Cells’ Populations","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"RNA-Seq; Computational biology; Biology; Genetics; Transcriptome; Gene; Gene expression","score_opus":0.03933999975027412,"score_gpt":0.27127189496964477,"score_spread":0.23193189521937063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407898024","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.110761344,0.011552312,0.32641014,0.0010665235,0.00093881175,0.0021294095,0.0010311026,0.00013303822,0.5459773],"genre_scores_gemma":[0.9614273,0.005584173,0.02791378,0.0005003755,0.00005710117,0.000013931479,0.0009068625,0.000010111096,0.003586374],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989955,0.00002858827,0.00045572882,0.0002216573,0.00015325313,0.00014526998],"domain_scores_gemma":[0.99875885,0.00006319918,0.00017674276,0.00071193866,0.00022310167,0.000066135704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003322888,0.00017074792,0.00023683441,0.00057708274,0.00038338342,0.00022608052,0.00062251865,0.00018320145,0.000005366755],"category_scores_gemma":[0.000017526127,0.00018418918,0.0000673306,0.00027942978,0.00058132526,0.00012284689,0.00062508235,0.00019260673,0.0000016561137],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020414288,0.0008291032,0.10414662,0.002585545,0.001791332,0.000004511594,0.017808119,0.009938585,0.06393134,0.2234961,0.021225924,0.5540387],"study_design_scores_gemma":[0.0033794984,0.0010667639,0.07372074,0.0011056986,0.002432645,0.000019082532,0.0003554156,0.45675266,0.023622628,0.006734606,0.42636213,0.0044481466],"about_ca_topic_score_codex":0.00003934724,"about_ca_topic_score_gemma":0.00006980188,"teacher_disagreement_score":0.8506659,"about_ca_system_score_codex":0.000043516702,"about_ca_system_score_gemma":0.00010476963,"threshold_uncertainty_score":0.7511017},"labels":[],"label_agreement":null},{"id":"W4407984248","doi":"10.1007/978-3-031-82931-4_16","title":"Comprehensive Evaluation of GAN Architectures for Acute Lymphoblastic Leukemia Classification","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Lymphoblastic Leukemia; Computer science; Computational biology; Medicine; Leukemia; Internal medicine; Biology","score_opus":0.05889502724736643,"score_gpt":0.34001388487513085,"score_spread":0.2811188576277644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407984248","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009820613,0.001085811,0.69212043,0.00086366263,0.00054304965,0.0021555265,0.00019803301,0.00016905626,0.3018824],"genre_scores_gemma":[0.7236299,0.0007952584,0.27216908,0.0013935763,0.00004763143,0.00032475404,0.0004318432,0.000021829299,0.001186114],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980184,0.000038776077,0.00073228555,0.00031414808,0.0007037245,0.00019268664],"domain_scores_gemma":[0.9952335,0.0004635282,0.0004959152,0.0019361082,0.001793256,0.00007770946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077669905,0.0002175126,0.00028542356,0.0012798081,0.00026124422,0.0004323976,0.0028263123,0.00008518999,0.0000016543925],"category_scores_gemma":[0.0001410982,0.00022494426,0.00007899718,0.00046373717,0.0008956698,0.002299915,0.0010901174,0.00015389212,0.0000061973233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006202884,0.000022351365,0.000017979984,0.00008792834,0.000028915296,5.273256e-8,0.0005390529,0.00279991,0.000016409205,0.47934827,0.0003533508,0.51677954],"study_design_scores_gemma":[0.0005585413,0.00005260636,0.0022438266,0.00029492236,0.00007153758,0.0000069513703,0.000013473877,0.94469446,0.0000713167,0.039685443,0.012084065,0.00022283135],"about_ca_topic_score_codex":0.000006298043,"about_ca_topic_score_gemma":0.000002901983,"teacher_disagreement_score":0.9418946,"about_ca_system_score_codex":0.00034166384,"about_ca_system_score_gemma":0.001546622,"threshold_uncertainty_score":0.91729605},"labels":[],"label_agreement":null},{"id":"W4408044374","doi":"10.1007/978-981-96-2186-6_17","title":"Research on Transformer Tracking with Temporal Context and Bounding Box Refinement Module","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital","funders":"","keywords":"Computer science; Minimum bounding box; Transformer; Tracking (education); Artificial intelligence; Electrical engineering; Engineering; Psychology","score_opus":0.12628902368661016,"score_gpt":0.3782878819514316,"score_spread":0.25199885826482143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408044374","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033337157,0.000685746,0.46946,0.00022335646,0.00017986473,0.00045777162,0.00000778039,0.00009408879,0.528558],"genre_scores_gemma":[0.804127,0.006848398,0.18525176,0.00045187463,0.000057834997,0.00010149701,0.000046439065,0.00002690317,0.0030882896],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989816,0.000022770348,0.0003317194,0.00013334943,0.00036316874,0.0001674031],"domain_scores_gemma":[0.99897426,0.00015806133,0.000048298803,0.0005335837,0.00023248253,0.000053316486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014512354,0.00013507273,0.00015340609,0.0009723177,0.0004650942,0.00023175415,0.000369364,0.0000681237,0.0000045451684],"category_scores_gemma":[0.000015125836,0.00012339231,0.000014341085,0.00030260943,0.00047262726,0.001577956,0.000098601675,0.0005146494,0.0000037908092],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015319474,0.0000073927026,0.000038701397,0.00011023983,0.000010085489,1.3885264e-7,0.0012429457,0.0031632036,0.000026360056,0.13637258,0.00021410386,0.8587989],"study_design_scores_gemma":[0.0010938299,0.00027182515,0.00071588566,0.0018211916,0.000013895335,0.000012169428,0.00049119984,0.24964198,0.0006635649,0.004936584,0.7397629,0.00057495775],"about_ca_topic_score_codex":0.0000052557043,"about_ca_topic_score_gemma":0.000031417658,"teacher_disagreement_score":0.858224,"about_ca_system_score_codex":0.00016015647,"about_ca_system_score_gemma":0.00007248344,"threshold_uncertainty_score":0.50317925},"labels":[],"label_agreement":null},{"id":"W4408044438","doi":"10.1007/978-981-96-2186-6_16","title":"Lightweight and Efficient Top-Down Human Pose Estimation Algorithm Research","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital","funders":"","keywords":"Computer science; Estimation; Algorithm; Artificial intelligence; Engineering; Systems engineering","score_opus":0.05412926551910804,"score_gpt":0.35699060348591943,"score_spread":0.3028613379668114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408044438","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016180727,0.00044404314,0.601436,0.0012180106,0.0003824331,0.0006582946,0.000017034075,0.0001416704,0.3955407],"genre_scores_gemma":[0.104241066,0.0064679063,0.8691391,0.0026538207,0.00026710294,0.00021526344,0.0004545015,0.000032459095,0.01652883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980211,0.0000728138,0.0006373147,0.00037346387,0.000623814,0.0002714968],"domain_scores_gemma":[0.99714446,0.00028244805,0.00021325887,0.0015248336,0.000718527,0.000116462936],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0019311382,0.0001985579,0.00021722728,0.0022530952,0.0014105298,0.0012057509,0.0019037027,0.00014882938,0.000013369096],"category_scores_gemma":[0.000045213925,0.00019952685,0.000034415436,0.0006784257,0.0009072626,0.0038186307,0.0025025948,0.00063889794,0.0000644233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.9490603e-7,0.000016370808,0.000002486203,0.000022151893,0.0000028892841,3.4200343e-7,0.00081120315,0.000048190588,0.0000031229317,0.5022303,0.0004893993,0.49637303],"study_design_scores_gemma":[0.00028457012,0.00006846417,0.00049830414,0.00039244376,0.0000053821136,0.000021100612,0.000024289218,0.88381976,0.000056624984,0.030003458,0.08454967,0.0002759529],"about_ca_topic_score_codex":0.000016387043,"about_ca_topic_score_gemma":0.0000041241005,"teacher_disagreement_score":0.88377154,"about_ca_system_score_codex":0.00017366634,"about_ca_system_score_gemma":0.00027101612,"threshold_uncertainty_score":0.9998895},"labels":[],"label_agreement":null},{"id":"W4408074826","doi":"10.1007/978-3-031-82150-9","title":"Intelligent Systems and Pattern Recognition","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ajman University; National Technical University of Athens; Technical University of Sofia; Université Cadi Ayyad; Macau University of Science and Technology; Università degli Studi di Perugia; National Institute of Development Administration; University of Technology - Iraq; Zayed University; Universidad Simón Bolívar; Universidad de Las Palmas de Gran Canaria; National and Kapodistrian University of Athens; National University of Sciences and Technology; Qatar University; Università degli Studi di Salerno; Lakehead University; Indian Institute of Technology Roorkee; Université du Québec à Montréal; Lviv Polytechnic National University; United Arab Emirates University; Queen's University; Ain Shams University; Université de Sfax; Amrita Vishwa Vidyapeetham University; Galgotias University; Universidad de Oviedo; Asia University; Southern Federal University; Netaji Subhas University of Technology; University of Gabès; Université de Technologie de Compiègne; Chaoyang University of Technology; Bahria University; Universitatea 'Dunărea de Jos' Galați; University of Lethbridge; McGill University; Université Mohammed V de Rabat; Arkansas Tech University; Ball State University; Università degli Studi di Milano-Bicocca; Middle Tennessee State University; Taibah University; University of Dayton","keywords":"Computer science; Thesaurus; Information retrieval; Artificial intelligence; Natural language processing","score_opus":0.04969903879415186,"score_gpt":0.2953616755603279,"score_spread":0.24566263676617603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408074826","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000033182754,0.0010620465,0.90541416,0.0013865508,0.00038964604,0.00057170214,0.000020220094,0.00009715191,0.091025345],"genre_scores_gemma":[0.17263432,0.1518725,0.59797204,0.02458129,0.00092626206,0.0022422273,0.002034379,0.00008313917,0.047653828],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987101,0.00004311062,0.00054375734,0.0002759131,0.00024295725,0.0001841662],"domain_scores_gemma":[0.99770105,0.00024207559,0.00022766054,0.0014702815,0.00027505364,0.000083879415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062073546,0.00016276022,0.00019157943,0.0006624983,0.0004175861,0.0010344106,0.0020978348,0.0000956403,0.0000012557736],"category_scores_gemma":[0.000017434792,0.00016008096,0.0000229548,0.0006803635,0.00043937555,0.0036746585,0.0023377293,0.000336955,0.000025499548],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.88466e-7,0.00001013679,0.000018093167,0.00004573674,0.0000025603301,1.1265695e-7,0.00038462598,0.000103912935,3.3597246e-7,0.07902118,0.002732593,0.91768044],"study_design_scores_gemma":[0.000101708305,0.000021305097,0.0003274167,0.00035096574,0.000004149348,0.000016286955,0.00001154816,0.7822425,0.000002247225,0.0052017276,0.2115213,0.00019887682],"about_ca_topic_score_codex":0.000021848944,"about_ca_topic_score_gemma":0.000006685132,"teacher_disagreement_score":0.91748154,"about_ca_system_score_codex":0.0001187113,"about_ca_system_score_gemma":0.00029519963,"threshold_uncertainty_score":0.9974845},"labels":[],"label_agreement":null},{"id":"W4408132766","doi":"10.1007/978-3-031-82156-1_12","title":"An RNN-LSTM Approach for Algerian Accent Identification","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Stress (linguistics); Identification (biology); Computer science; Natural language processing; Artificial intelligence; Speech recognition; Botany; Biology","score_opus":0.05676930210946809,"score_gpt":0.31504300315739775,"score_spread":0.2582737010479297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408132766","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005437626,0.00009115043,0.82625145,0.0005524912,0.00025470785,0.00061976333,0.000028392758,0.00010684646,0.17208974],"genre_scores_gemma":[0.009291877,0.001337587,0.98415023,0.0016206366,0.000054372107,0.00021740464,0.00038040525,0.000010273277,0.002937224],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981923,0.00003997755,0.0007683118,0.00040660953,0.00036783985,0.00022495934],"domain_scores_gemma":[0.99610984,0.00020475575,0.00035720613,0.002594831,0.0006164469,0.00011692015],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014621245,0.00021444946,0.00024559803,0.0012517798,0.0006135345,0.0013318599,0.0042487774,0.0001495881,0.000007377265],"category_scores_gemma":[0.000069809816,0.00022346676,0.000066522734,0.00045356402,0.0004413423,0.007472365,0.0009776579,0.0002329778,0.000021481963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015233544,0.000024486575,0.0000034243712,0.00002565701,0.0000037109342,3.441914e-8,0.0003710719,0.000027572289,0.0000063036173,0.46457833,0.00031859477,0.5346393],"study_design_scores_gemma":[0.0002457681,0.00003564609,0.0004230183,0.000084495776,0.0000085408,0.000008525396,0.000028725153,0.8788283,0.000084982654,0.010379687,0.109568164,0.0003041335],"about_ca_topic_score_codex":0.000005626891,"about_ca_topic_score_gemma":0.0000036006081,"teacher_disagreement_score":0.87880075,"about_ca_system_score_codex":0.0001478424,"about_ca_system_score_gemma":0.00033648568,"threshold_uncertainty_score":0.99970484},"labels":[],"label_agreement":null},{"id":"W4408134649","doi":"10.1007/978-3-031-83435-6_20","title":"Femoral Head Surface Segmentation Using Ultrasound Images as Input Source: A Local Phase and Rigid Filtering Approach","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer vision; Segmentation; Head (geology); Computer science; Ultrasound; Artificial intelligence; Phase (matter); Biomedical engineering; Geology; Radiology; Medicine; Physics; Geomorphology","score_opus":0.04772927622272023,"score_gpt":0.3633861243831824,"score_spread":0.3156568481604622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408134649","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010414972,0.0004421003,0.7228358,0.00043300114,0.00015715329,0.0011051181,0.000023178542,0.000074027324,0.26451465],"genre_scores_gemma":[0.46763673,0.0033568798,0.5165761,0.0020827155,0.000054400138,0.000036765694,0.00074858114,0.000023991495,0.009483819],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882877,0.000019777104,0.00045727007,0.00021227336,0.0003136301,0.00016830969],"domain_scores_gemma":[0.99878854,0.000091566486,0.00017648516,0.000694239,0.00016422532,0.000084923944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056401984,0.00018621888,0.0002538857,0.0005269054,0.00031581448,0.00035486792,0.00036866276,0.00007174389,0.000012544866],"category_scores_gemma":[0.000017822547,0.00018612048,0.000030169655,0.00022299882,0.00081921334,0.0017184931,0.0007854258,0.00025926513,0.0000050810763],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008384882,0.00031189583,0.0013957781,0.0011693246,0.00011642418,0.000002105501,0.006030568,0.0035699944,0.0004900966,0.064548016,0.0013214862,0.9209605],"study_design_scores_gemma":[0.0043185176,0.00038840325,0.0024058926,0.001448474,0.00019217383,0.00012495898,0.0009799483,0.90592223,0.00022559971,0.0012283392,0.082081445,0.00068403524],"about_ca_topic_score_codex":0.000041212417,"about_ca_topic_score_gemma":0.0000023054108,"teacher_disagreement_score":0.9202764,"about_ca_system_score_codex":0.00017481079,"about_ca_system_score_gemma":0.00020633404,"threshold_uncertainty_score":0.7589773},"labels":[],"label_agreement":null},{"id":"W4408135470","doi":"10.1007/978-3-031-82153-0_26","title":"BA-GAN: A Boundary-Aware Generative Adversarial Network for Document Restoration","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Generative grammar; Generative adversarial network; Boundary (topology); Adversarial system; Computer science; Information retrieval; Artificial intelligence; Mathematics; Deep learning","score_opus":0.02240356776309566,"score_gpt":0.28829711874120983,"score_spread":0.2658935509781142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408135470","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000029241105,0.00040438824,0.935117,0.0015182705,0.0012599463,0.00051703333,0.0000147868805,0.000084869906,0.061080754],"genre_scores_gemma":[0.004275653,0.0013600996,0.986863,0.0016027121,0.00029980534,0.00013504492,0.00022726406,0.000009607959,0.0052267984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984299,0.000037453727,0.0006504067,0.00032599407,0.00031628562,0.00023995808],"domain_scores_gemma":[0.9974073,0.00019099249,0.00039770367,0.0012422374,0.0006952745,0.00006648658],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001065689,0.00021363648,0.00023889648,0.00063582056,0.0012399192,0.0013932984,0.0018582201,0.00014608642,0.000002962259],"category_scores_gemma":[0.000045623176,0.00021825673,0.0000555133,0.0004257279,0.00064115634,0.007301844,0.00091267715,0.00031670212,0.0000098670425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000059981103,0.0000056707436,0.0000051269085,0.000037732556,0.000006942901,8.9063406e-8,0.00092031626,0.0010113943,8.5216215e-7,0.51509255,0.0029217193,0.47999159],"study_design_scores_gemma":[0.00039293585,0.000058317168,0.000033985536,0.00026926934,0.0000089417845,0.000011593768,0.000014717445,0.6162765,0.0000164473,0.0466112,0.3360523,0.00025381084],"about_ca_topic_score_codex":0.000008555681,"about_ca_topic_score_gemma":0.000020301906,"teacher_disagreement_score":0.6152651,"about_ca_system_score_codex":0.00024074002,"about_ca_system_score_gemma":0.0012166017,"threshold_uncertainty_score":0.9996433},"labels":[],"label_agreement":null},{"id":"W4408230751","doi":"10.1007/978-3-031-84263-4_10","title":"Comparing Ensemble Learning and Deep Neural Networks for Malware Detection","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Malware; Computer science; Artificial intelligence; Artificial neural network; Deep learning; Ensemble learning; Machine learning; Computer security","score_opus":0.028043908682875318,"score_gpt":0.29359646417935537,"score_spread":0.26555255549648005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408230751","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000152138855,0.0005238474,0.9803794,0.00016926423,0.00023219296,0.00048468527,0.0000013190682,0.00027498827,0.017919095],"genre_scores_gemma":[0.4041286,0.0031441008,0.5907378,0.00060870673,0.000053023006,0.00016890993,0.000034060125,0.000015727679,0.0011090535],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987024,0.00002878515,0.000522662,0.00032039479,0.00019547084,0.00023028055],"domain_scores_gemma":[0.99798197,0.0003457895,0.00030982652,0.0009004044,0.00039001604,0.00007197553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006757385,0.00020957382,0.00025160107,0.00091057864,0.0008489089,0.00058846537,0.0013525574,0.00013926766,7.0732665e-7],"category_scores_gemma":[0.00007747924,0.00023376802,0.000040397274,0.00037657778,0.00039374118,0.0046018134,0.0020823833,0.0005337057,0.0000012852665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035826442,0.0000032909916,0.00003409616,0.00003386187,0.0000030018932,9.19647e-8,0.00023219288,0.0030358892,0.0000042536863,0.114146374,0.000012320717,0.88249105],"study_design_scores_gemma":[0.00017559032,0.000066601824,0.00017782956,0.000094718715,0.000004346971,0.000019579003,0.000012526003,0.9441906,0.00003943332,0.004600898,0.05040388,0.0002139819],"about_ca_topic_score_codex":0.0000062401746,"about_ca_topic_score_gemma":0.00002900796,"teacher_disagreement_score":0.9411547,"about_ca_system_score_codex":0.0001384709,"about_ca_system_score_gemma":0.00005522388,"threshold_uncertainty_score":0.95327836},"labels":[],"label_agreement":null},{"id":"W4408295990","doi":"10.1007/978-3-031-83790-6_22","title":"Software Defects Prediction Using Generative Adversarial Network Based Data Balancing","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Adversarial system; Generative grammar; Generative adversarial network; Software; Data mining; Artificial intelligence; Programming language; Deep learning","score_opus":0.0589607147818736,"score_gpt":0.3099992995879466,"score_spread":0.251038584806073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408295990","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002234964,0.0003281582,0.9923533,0.0001527932,0.00083225325,0.00037528234,0.00005655161,0.00019939707,0.0056798668],"genre_scores_gemma":[0.006035625,0.00035670164,0.99228346,0.00056272425,0.00015737249,0.000017100781,0.00034079351,0.000010242629,0.00023598268],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980606,0.00005240361,0.0005481456,0.00043536743,0.0005908264,0.0003126943],"domain_scores_gemma":[0.994289,0.00103379,0.00020503819,0.003944843,0.00042876235,0.00009858429],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0017260732,0.00021857595,0.00023341732,0.00091703,0.00064960273,0.00071852945,0.0055143284,0.00014703997,0.0000037784228],"category_scores_gemma":[0.00048505925,0.00023762023,0.000031826035,0.00082076906,0.0004002632,0.0068645943,0.0063606715,0.0005565608,0.000009202578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000125579745,0.000041845877,0.0032391336,0.0002488202,0.0000481655,0.0000032861378,0.0015093716,0.345014,0.000009466409,0.28056043,0.007386652,0.36192626],"study_design_scores_gemma":[0.00022919037,0.00002152268,0.0010458885,0.00036904594,0.000006418873,0.0000055766354,0.0000019176603,0.97173584,0.000003914486,0.0009053568,0.025485164,0.00019015963],"about_ca_topic_score_codex":0.000016984786,"about_ca_topic_score_gemma":0.000007989553,"teacher_disagreement_score":0.62672186,"about_ca_system_score_codex":0.00032902378,"about_ca_system_score_gemma":0.0012071022,"threshold_uncertainty_score":0.9998663},"labels":[],"label_agreement":null},{"id":"W4408316627","doi":"10.1007/978-3-031-84148-4_11","title":"AI and Leadership in Startup Innovation and Disruption: The Case of Mobility as a Service (MaaS)","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Canada West","funders":"","keywords":"Service (business); Business; Chemistry; Computer science; Knowledge management; Marketing","score_opus":0.11149745638896474,"score_gpt":0.3009018287691848,"score_spread":0.18940437238022007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408316627","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18375358,0.0026365903,0.030351296,0.05281902,0.00065411796,0.0041091116,0.00008530103,0.00020306089,0.72538793],"genre_scores_gemma":[0.99278617,0.00021392411,0.0009313804,0.005618556,0.000019273928,0.000020395655,0.000038597387,0.000004129359,0.00036757448],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990593,0.000006650759,0.0005306447,0.00015754186,0.0001308639,0.00011498802],"domain_scores_gemma":[0.9984899,0.00012844431,0.00031287738,0.0006054939,0.0004568126,0.000006472814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010426737,0.00012727373,0.00015499111,0.00090732664,0.00025686718,0.0004818316,0.0004934394,0.00007145421,0.0000041253816],"category_scores_gemma":[0.00011998853,0.00011304112,0.000010804594,0.001098216,0.0007468559,0.0063266773,0.0011986649,0.00027737298,0.0000052410373],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000053871986,0.000010239994,0.0006380343,0.00031634563,0.0000017019346,6.357016e-7,0.0004953501,0.00002052423,0.0000011554049,0.90779203,0.000094735784,0.09062383],"study_design_scores_gemma":[0.0011904698,0.00005319591,0.037836254,0.0027507853,0.00003342028,0.00015261928,0.0016125382,0.6261108,0.000010778008,0.17579919,0.15366408,0.0007858907],"about_ca_topic_score_codex":0.00030121702,"about_ca_topic_score_gemma":0.00050817843,"teacher_disagreement_score":0.8090326,"about_ca_system_score_codex":0.000045397053,"about_ca_system_score_gemma":0.00008771559,"threshold_uncertainty_score":0.46463135},"labels":[],"label_agreement":null},{"id":"W4408363720","doi":"10.1007/978-3-031-84391-4_10","title":"Exploring Recursion Pedagogies: Innovative Strategies and Their Effects on Engineering Students","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Recursion (computer science); Computer science; Mathematics education; Engineering ethics; Engineering; Psychology; Programming language","score_opus":0.16799386744935627,"score_gpt":0.4189063498814988,"score_spread":0.2509124824321425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408363720","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03846025,0.00081543316,0.23611863,0.00067584903,0.0019699896,0.0009856337,0.0000161326,0.00028937135,0.72066873],"genre_scores_gemma":[0.9309499,0.0020964656,0.059803754,0.0012831381,0.00013879189,0.00020375158,0.00008982825,0.00003169304,0.005402659],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989317,0.00011128874,0.0003936709,0.00021136798,0.00018724245,0.00016473456],"domain_scores_gemma":[0.9977725,0.00094587856,0.00019546668,0.00080076675,0.00025605955,0.000029333603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020260282,0.00020724956,0.00022597729,0.0012620284,0.00035767,0.00036531533,0.00086130825,0.00008972028,0.0000042185047],"category_scores_gemma":[0.0001491024,0.00018451446,0.000016587534,0.0004946216,0.00033202342,0.0022508102,0.0007943983,0.0008502566,0.00000984168],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066544494,0.000009860094,0.000090233094,0.000050357416,0.000013345171,1.8167934e-7,0.02117289,0.00006966411,0.0000053568847,0.51285213,0.000049856975,0.46567947],"study_design_scores_gemma":[0.002652852,0.0012089727,0.18817511,0.008896284,0.00002829336,0.000031866548,0.011184171,0.032010633,0.0001615307,0.011314503,0.7422816,0.0020541877],"about_ca_topic_score_codex":0.000011057585,"about_ca_topic_score_gemma":5.98565e-7,"teacher_disagreement_score":0.8924897,"about_ca_system_score_codex":0.00008908789,"about_ca_system_score_gemma":0.0000941863,"threshold_uncertainty_score":0.7524281},"labels":[],"label_agreement":null},{"id":"W4408364611","doi":"10.1007/978-3-031-84391-4_11","title":"Enhancing and Analyzing Log Generation for Collaborative Problem-Solving Activities: Video Analysis and OCR  Techniques","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Information retrieval; Multimedia; Thesaurus; Natural language processing","score_opus":0.052707299843801236,"score_gpt":0.38898793118894,"score_spread":0.33628063134513875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408364611","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008279431,0.00054052135,0.9113258,0.0003337622,0.00009296239,0.0005408326,0.000025924202,0.000060123853,0.08625212],"genre_scores_gemma":[0.09361217,0.0012361824,0.90053535,0.0005876107,0.000067846006,0.0001465305,0.00017077183,0.000011658733,0.0036318817],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987028,0.0001776165,0.00055037363,0.00028368464,0.00012572968,0.00015979196],"domain_scores_gemma":[0.99768454,0.0008121047,0.0004120863,0.00062944216,0.0004269678,0.000034890014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036190106,0.00017946002,0.00032426836,0.0019366627,0.0008314071,0.00038342059,0.00036403752,0.00014129945,0.000006290411],"category_scores_gemma":[0.00014403756,0.0001802617,0.00003166516,0.00083082414,0.00062510587,0.0014947039,0.0004188665,0.0004181837,5.1917544e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011527197,0.000013248513,0.0007267954,0.00008233817,0.00014496346,9.289309e-8,0.024911214,0.000045890778,0.0002943621,0.3571189,0.00021926763,0.6164314],"study_design_scores_gemma":[0.0022412809,0.0009294658,0.022690898,0.0026499047,0.0011330051,0.000037543632,0.005911224,0.5145606,0.0016420984,0.023478488,0.42169964,0.0030258528],"about_ca_topic_score_codex":0.000036452602,"about_ca_topic_score_gemma":0.00006142947,"teacher_disagreement_score":0.6134055,"about_ca_system_score_codex":0.00009446325,"about_ca_system_score_gemma":0.00013949502,"threshold_uncertainty_score":0.7350859},"labels":[],"label_agreement":null},{"id":"W4408365403","doi":"10.1007/978-3-031-84397-6_11","title":"Validation of a Chronic Kidney Disease Prediction System Using Machine Learning Techniques","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Kidney disease; Artificial intelligence; Machine learning; Medicine; Internal medicine","score_opus":0.12936651129847596,"score_gpt":0.4429384271498686,"score_spread":0.31357191585139266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408365403","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035979026,0.003684831,0.5173918,0.0033154453,0.003762781,0.010299944,0.0012980138,0.0012765911,0.4553727],"genre_scores_gemma":[0.8906098,0.0137480395,0.08381381,0.0016302391,0.0005910562,0.0005438293,0.0022947472,0.000068045,0.0067004347],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784017,0.00017192848,0.0012730157,0.00018077691,0.00033271444,0.00020142498],"domain_scores_gemma":[0.99687886,0.00033165098,0.00077341386,0.0009979586,0.0008842807,0.00013382979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016332547,0.0001529533,0.00025076454,0.0010209508,0.0012243806,0.000040573057,0.00075499597,0.00018557296,0.000019663412],"category_scores_gemma":[0.00027234963,0.00015737048,0.00003657739,0.00036089486,0.0005020605,0.0018332511,0.00096364605,0.0008223488,0.0000149996695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052361956,0.000043947766,0.022078998,0.006881875,0.000022320974,5.176658e-7,0.008751321,0.0022746064,0.00010168467,0.78617835,0.00036356456,0.17325045],"study_design_scores_gemma":[0.000078867546,0.000044756078,0.00022016087,0.0059872745,0.00001947021,0.000001242458,0.00019257558,0.9415681,0.0001041537,0.000856794,0.05078745,0.00013920691],"about_ca_topic_score_codex":0.00033354864,"about_ca_topic_score_gemma":0.000030513096,"teacher_disagreement_score":0.93929344,"about_ca_system_score_codex":0.0009915399,"about_ca_system_score_gemma":0.0020851276,"threshold_uncertainty_score":0.9417069},"labels":[],"label_agreement":null},{"id":"W4408977518","doi":"10.1007/978-3-031-84059-3_19","title":"Implementing an NFT by Developing a Smart Contract in OpenSea Marketplace","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saskatchewan Polytechnic","funders":"","keywords":"Business; Smart contract; Computer science; World Wide Web; Database","score_opus":0.023913002328785876,"score_gpt":0.3002801340699521,"score_spread":0.2763671317411662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408977518","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046755277,0.00070368184,0.80835843,0.006122611,0.00016390001,0.001029294,0.000032659605,0.00022566828,0.18289621],"genre_scores_gemma":[0.27517125,0.007297771,0.7087396,0.0058856616,0.000025462075,0.0003295874,0.0002970233,0.000020726608,0.0022329423],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980781,0.000051101946,0.00082595344,0.0003964576,0.0002689393,0.00037944186],"domain_scores_gemma":[0.99684167,0.0002639977,0.00031253143,0.0022387528,0.00027363806,0.00006938583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025509514,0.0002188553,0.00027663028,0.0011750115,0.0006414599,0.00056790205,0.0045305057,0.00019451343,0.0000059726176],"category_scores_gemma":[0.0000486947,0.00024171194,0.000027591967,0.0007787003,0.00052945793,0.0045430725,0.0039224452,0.00060031685,0.000010492532],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010500314,0.000015085023,0.00017921817,0.000018905355,0.0000027047906,2.2895011e-7,0.000555564,0.0000060750413,0.0000021435665,0.7865085,0.00033692655,0.21237357],"study_design_scores_gemma":[0.00044050245,0.000030077159,0.0017560407,0.0003165126,0.0000034712818,0.000015540336,0.000039153845,0.53170365,0.000025433335,0.019232063,0.44600707,0.0004304653],"about_ca_topic_score_codex":0.00007864842,"about_ca_topic_score_gemma":0.00021932223,"teacher_disagreement_score":0.76727647,"about_ca_system_score_codex":0.00021365132,"about_ca_system_score_gemma":0.0004940846,"threshold_uncertainty_score":0.9856727},"labels":[],"label_agreement":null},{"id":"W4409013456","doi":"10.1007/978-3-031-85628-0_1","title":"High-Precision Method to Reduce Overfitting in ANNs Using Highly Uniform Chaotic Sequences","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Overfitting; Chaotic; Computer science; Pattern recognition (psychology); Artificial intelligence; Biological system; Algorithm; Artificial neural network; Biology","score_opus":0.05721733729900588,"score_gpt":0.35056691635209053,"score_spread":0.2933495790530847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409013456","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035832523,0.00017644267,0.94431424,0.0028841994,0.00033121262,0.0007473536,0.00001490892,0.000092767725,0.051080573],"genre_scores_gemma":[0.023709504,0.00055264914,0.97310185,0.0013102385,0.000045576337,0.000039494083,0.0000219806,0.000007394302,0.0012113068],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978326,0.000057201913,0.0009191183,0.000445752,0.00042674653,0.00031859166],"domain_scores_gemma":[0.99673605,0.00046990335,0.0003385191,0.0020110328,0.0003203308,0.00012414386],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016660733,0.00024975854,0.00032656488,0.0015578426,0.0005449953,0.0007002779,0.0039403057,0.00013065923,0.0000049390824],"category_scores_gemma":[0.000049637758,0.0002496019,0.000043057353,0.0016705148,0.0002802007,0.0047534397,0.0034676737,0.0004929384,0.000027930459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013718577,0.000009783284,0.000007272026,0.000013714507,0.0000018994218,3.396476e-7,0.00045704065,0.015292048,0.000024452766,0.5444052,0.00013161493,0.4396552],"study_design_scores_gemma":[0.00018034321,0.00003364273,0.00036652325,0.00062144676,0.0000043838304,0.000013626692,0.000013547422,0.93210506,0.00006277545,0.017678522,0.04860191,0.0003182087],"about_ca_topic_score_codex":0.00013518812,"about_ca_topic_score_gemma":0.000026969476,"teacher_disagreement_score":0.916813,"about_ca_system_score_codex":0.00028996423,"about_ca_system_score_gemma":0.00040151746,"threshold_uncertainty_score":0.99999565},"labels":[],"label_agreement":null},{"id":"W4409013497","doi":"10.1007/978-3-031-85628-0_22","title":"XAI-Based Assessment of Software Vulnerability Contributing Factors in Transformer Models","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Vulnerability (computing); Computer science; Software; Vulnerability assessment; Transformer; Engineering; Computer security; Medicine; Electrical engineering; Operating system","score_opus":0.048527713681525905,"score_gpt":0.3397813336764742,"score_spread":0.29125361999494825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409013497","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00064803363,0.000111199945,0.9859098,0.00024481144,0.00012728249,0.00045750622,0.000029366416,0.00007875121,0.012393254],"genre_scores_gemma":[0.7322651,0.00022317831,0.26718476,0.00012705363,0.00000464939,0.000035076133,0.000052086278,0.000005747185,0.00010233987],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979062,0.000049525926,0.0008587502,0.00028015798,0.0006020754,0.000303277],"domain_scores_gemma":[0.9954953,0.0018496795,0.00020062177,0.0018500505,0.0005294211,0.000074882715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023262477,0.00020144718,0.0003441328,0.0015216995,0.00021394985,0.00022783053,0.0031211835,0.00013377084,0.000003399288],"category_scores_gemma":[0.00030211013,0.00020136955,0.00005750489,0.00080218783,0.00052402366,0.003962502,0.000979892,0.00064294116,0.0000010029732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003865092,0.000087398956,0.02304401,0.000374811,0.000012781152,5.1462024e-7,0.0022974096,0.080343395,0.0000058565142,0.6994614,0.00003920909,0.19432935],"study_design_scores_gemma":[0.00034917804,0.000034034798,0.026917249,0.00039479233,0.0000021886551,7.621811e-7,0.000008099245,0.9662234,0.00004186903,0.0045947917,0.0012301236,0.00020348247],"about_ca_topic_score_codex":0.00004258592,"about_ca_topic_score_gemma":0.000016280317,"teacher_disagreement_score":0.88588005,"about_ca_system_score_codex":0.00037690517,"about_ca_system_score_gemma":0.0010637537,"threshold_uncertainty_score":0.82116115},"labels":[],"label_agreement":null},{"id":"W4409013944","doi":"10.1007/978-3-031-85628-0_7","title":"Revisiting the Nexus Between Handwriting and Personality: Graphology","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Writing and Handwriting Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Handwriting; Nexus (standard); Personality; Computer science; Thesaurus; Natural language processing; Psychology; Information retrieval; Artificial intelligence; Social psychology","score_opus":0.0625851478329788,"score_gpt":0.36130652101279154,"score_spread":0.29872137317981273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409013944","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001247953,0.0013243383,0.0029895322,0.02007463,0.00018400345,0.00035363715,0.000017508455,0.00007115534,0.97373724],"genre_scores_gemma":[0.96483934,0.009845574,0.012475026,0.0029168234,0.0009783894,0.000045422817,0.00010903947,0.0000128868205,0.008777509],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99880826,0.0001095123,0.00042863443,0.00017090506,0.00027796938,0.0002047048],"domain_scores_gemma":[0.997831,0.0010206739,0.00023888847,0.0005377154,0.00030822112,0.00006349268],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003718636,0.000113097,0.00017495849,0.0004285607,0.0028958037,0.0006512206,0.00089746976,0.00011657538,0.0000071379077],"category_scores_gemma":[0.00035930466,0.000104748404,0.000028813185,0.000312312,0.002270738,0.0013566703,0.0005882275,0.00042940848,0.0000048804395],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.1616138e-7,0.0000012524075,0.0010602023,0.000024806586,0.0000030650883,4.197846e-8,0.011112408,9.382937e-7,2.1034083e-7,0.69199324,0.000111084664,0.29569232],"study_design_scores_gemma":[0.0003375122,0.0000239586,0.0257262,0.0017385664,0.000049902545,0.000011582693,0.009265384,0.0048917225,0.000001237327,0.050081942,0.9073774,0.00049455505],"about_ca_topic_score_codex":0.0002596242,"about_ca_topic_score_gemma":0.00006965901,"teacher_disagreement_score":0.96495974,"about_ca_system_score_codex":0.000088016146,"about_ca_system_score_gemma":0.0003720973,"threshold_uncertainty_score":0.9984023},"labels":[],"label_agreement":null},{"id":"W4409186439","doi":"10.1007/978-3-031-86069-0_13","title":"Innovative Integration of Machine Learning Predictive Models Within Blockchain Frameworks for Supply Chain Fault Tolerance","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Blockchain; Computer science; Supply chain; Fault tolerance; Distributed computing; Business; Computer security","score_opus":0.019368858530280055,"score_gpt":0.27324728352353367,"score_spread":0.25387842499325364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409186439","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000121213685,0.00046345685,0.97743934,0.0014524407,0.00014318248,0.0009887066,0.00007766173,0.0001484737,0.01916554],"genre_scores_gemma":[0.44704956,0.0012069425,0.5493862,0.0007784046,0.000023281997,0.0003558306,0.0001777718,0.0000115805005,0.0010104399],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796873,0.000043262564,0.0010360647,0.00040035052,0.00032837226,0.0002231895],"domain_scores_gemma":[0.9954101,0.0004790452,0.00077858864,0.0017109638,0.0015703076,0.000050988132],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015544442,0.00026925848,0.00040029694,0.0014398043,0.0005463745,0.00017666588,0.0030686804,0.00047529995,0.000001395601],"category_scores_gemma":[0.00017151554,0.00027258805,0.00005482064,0.0013095208,0.0010878703,0.0019044746,0.0016715091,0.0013521137,0.0000014109484],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006701124,0.000022413546,0.000012313978,0.00003195099,0.000009049261,3.9978588e-8,0.0034781399,0.013362028,0.000007586095,0.87489384,0.000061033305,0.10811493],"study_design_scores_gemma":[0.000260113,0.000096261225,0.000040165578,0.0003444648,0.0000051867924,0.0000032760202,0.000055144985,0.87350434,0.00013696884,0.12114307,0.004212902,0.00019808425],"about_ca_topic_score_codex":0.000023830546,"about_ca_topic_score_gemma":0.000023996008,"teacher_disagreement_score":0.86014235,"about_ca_system_score_codex":0.00013572103,"about_ca_system_score_gemma":0.00038889205,"threshold_uncertainty_score":0.99997264},"labels":[],"label_agreement":null},{"id":"W4409186723","doi":"10.1007/978-3-031-86069-0_11","title":"Quantum-Resistant Digital Rights Management (DRM) for Protecting Intellectual Property in ARVR Metaverse Content","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Rights Management and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Intellectual property; Digital rights management; Internet privacy; Computer science; Digital rights; Digital content; World Wide Web; Business; Computer security; Operating system","score_opus":0.06507138188575434,"score_gpt":0.26783273685233583,"score_spread":0.2027613549665815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409186723","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006678861,0.00009037842,0.394328,0.00047925464,0.00025177418,0.0020113988,0.00001841242,0.000095920936,0.6026581],"genre_scores_gemma":[0.5309066,0.002610634,0.30441216,0.0024964774,0.00010903557,0.0013534939,0.00045578,0.000050552495,0.15760528],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99801105,0.000024998051,0.0008426166,0.00040238144,0.0004179007,0.00030103175],"domain_scores_gemma":[0.9975703,0.0003263333,0.0002679463,0.0014729679,0.00029178418,0.000070714814],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011116882,0.0002642051,0.00030680042,0.0014658318,0.0005121724,0.0017177723,0.0032009333,0.00007874018,0.0000027050567],"category_scores_gemma":[0.00008931208,0.00019438432,0.0000774649,0.0005538597,0.00046444032,0.008484819,0.0031164628,0.00033688318,0.000024968473],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011124973,0.00003645923,0.0000019375773,0.000085257736,0.000012722236,8.8835645e-7,0.0013126717,0.00003203504,2.852311e-7,0.8523995,0.00034632502,0.14576076],"study_design_scores_gemma":[0.00052271254,0.000089731555,0.00006883134,0.00048490558,0.000007708995,0.0000022444074,0.00006158187,0.34997216,0.000006211803,0.06563869,0.5828089,0.0003363198],"about_ca_topic_score_codex":0.00002403768,"about_ca_topic_score_gemma":0.000043953343,"teacher_disagreement_score":0.78676087,"about_ca_system_score_codex":0.00022211717,"about_ca_system_score_gemma":0.000130679,"threshold_uncertainty_score":0.99931854},"labels":[],"label_agreement":null},{"id":"W4409382829","doi":"10.1007/978-3-031-85923-6_5","title":"Improving Critical Controls Using IoT and Computer Vision","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Internet of Things; Computer science; Thesaurus; Artificial intelligence; Information retrieval; Computer vision; World Wide Web","score_opus":0.020092250394009283,"score_gpt":0.28454666845266235,"score_spread":0.26445441805865305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409382829","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00071063585,0.0014109886,0.9144563,0.00021917274,0.0012221928,0.0006302992,0.00003947069,0.00021535336,0.08109558],"genre_scores_gemma":[0.66167504,0.0013342075,0.33467916,0.0012244995,0.00032222486,0.000041299212,0.00009230464,0.00005172107,0.00057953683],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987851,0.000021897205,0.00059607695,0.00016395134,0.00023243086,0.00020056432],"domain_scores_gemma":[0.99842083,0.00034117454,0.00008509092,0.000853622,0.00021850955,0.00008078649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066383363,0.00019811664,0.0002739827,0.00079501315,0.00034325704,0.0004695906,0.0006506777,0.00014235018,0.0000033760166],"category_scores_gemma":[0.000034557506,0.0002084579,0.000029574836,0.00018401915,0.0006642619,0.0018006946,0.0007815277,0.0003814426,0.000008979072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000069271678,0.0000159081,0.00008765386,0.0008073035,0.00002200075,0.000001345879,0.0014066033,0.010121146,0.0001421905,0.4197355,0.0006716481,0.5669818],"study_design_scores_gemma":[0.00020869463,0.000025577427,0.0001818107,0.00047592967,0.000007931994,0.000017847204,0.000008657709,0.9748566,0.000006464428,0.00032639664,0.023682743,0.0002013384],"about_ca_topic_score_codex":0.000014546287,"about_ca_topic_score_gemma":0.0000054826587,"teacher_disagreement_score":0.96473545,"about_ca_system_score_codex":0.00015950818,"about_ca_system_score_gemma":0.000109377004,"threshold_uncertainty_score":0.85006666},"labels":[],"label_agreement":null},{"id":"W4409386943","doi":"10.1007/978-3-031-85923-6_16","title":"Autonomous Driving Prototype with Raspberry Pi by Using Image Processing Technology","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Earl Haig Secondary School; Lions Gate Hospital","funders":"","keywords":"Raspberry pi; Computer science; Pi; Computer vision; Computer graphics (images); World Wide Web; Biology; Internet of Things","score_opus":0.015907444676836104,"score_gpt":0.2547837438040405,"score_spread":0.2388762991272044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409386943","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002286731,0.0009573821,0.68658787,0.00053291017,0.0001374164,0.0010798645,0.000025783143,0.0018579988,0.30653402],"genre_scores_gemma":[0.53973955,0.0011823126,0.45777994,0.00011495585,0.000020275591,0.00011619739,0.0000621657,0.000034339886,0.000950243],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992201,0.0000044815133,0.00031840373,0.00014868328,0.00012900359,0.00017933726],"domain_scores_gemma":[0.998886,0.000045432935,0.00012010263,0.0007731174,0.0001520825,0.000023260993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021704118,0.00018248422,0.00018159082,0.00096974877,0.00033305495,0.00023456945,0.0010305101,0.00014673726,0.000003026657],"category_scores_gemma":[0.000025325528,0.00017456645,0.000013420488,0.0003195956,0.00096528535,0.0015781086,0.00084347435,0.00052169984,0.0000049470623],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017754099,0.0000068405793,0.00006717762,0.00018731014,0.000011341079,4.5900637e-7,0.00035582238,0.0014391092,0.000053372958,0.018264735,0.0002628178,0.97934926],"study_design_scores_gemma":[0.00024879214,0.00005758544,0.0002061696,0.0017609487,0.000016020751,0.000033516648,0.00008292786,0.87227225,0.0016973661,0.0036391409,0.11938805,0.00059720414],"about_ca_topic_score_codex":0.0000026783173,"about_ca_topic_score_gemma":0.0000022623892,"teacher_disagreement_score":0.978752,"about_ca_system_score_codex":0.00015159676,"about_ca_system_score_gemma":0.00013146708,"threshold_uncertainty_score":0.7118613},"labels":[],"label_agreement":null},{"id":"W4409388561","doi":"10.1007/978-3-031-85923-6_22","title":"Soft Actor Critic Based End-to-End QoS Path Selection in Multi-Domain SDN Environments","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"End-to-end principle; Computer science; Quality of service; Path (computing); End user; Computer network; Selection (genetic algorithm); Domain (mathematical analysis); Distributed computing; World Wide Web; Artificial intelligence; Mathematics","score_opus":0.031022810793478555,"score_gpt":0.2769603177058599,"score_spread":0.24593750691238134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409388561","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006009473,0.00024245527,0.98692715,0.000957399,0.00036169888,0.0005455978,0.000018100536,0.00008755964,0.0107999705],"genre_scores_gemma":[0.114382714,0.001215199,0.8751265,0.0064076986,0.0000810856,0.00020565884,0.00011660812,0.00002391888,0.0024406204],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978783,0.000068703666,0.0007696864,0.00043312286,0.0004912617,0.00035893518],"domain_scores_gemma":[0.99771446,0.00047336976,0.0002187003,0.0013261539,0.00012557741,0.00014173075],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010737072,0.00028500054,0.00029744476,0.0015065772,0.0004463143,0.0005405536,0.002735522,0.0001706321,0.000015161926],"category_scores_gemma":[0.00008581593,0.000303987,0.000054672877,0.0008958331,0.00039298018,0.003469901,0.0017909218,0.0005411405,0.000054609434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013862176,0.0002015194,0.0013940557,0.000113857284,0.000014705266,0.0000025692286,0.003389412,0.008426646,0.000030438328,0.22253864,0.001978708,0.7618956],"study_design_scores_gemma":[0.00056738296,0.0000653188,0.007618394,0.0004466649,0.000004297736,0.0000059413346,0.000012105121,0.8276359,0.000010448263,0.0014700452,0.16177751,0.00038599822],"about_ca_topic_score_codex":0.000026290696,"about_ca_topic_score_gemma":0.00003786661,"teacher_disagreement_score":0.8192093,"about_ca_system_score_codex":0.00036546934,"about_ca_system_score_gemma":0.0004630439,"threshold_uncertainty_score":0.99994123},"labels":[],"label_agreement":null},{"id":"W4409468107","doi":"10.1007/978-3-031-86644-9_17","title":"Using Survey to Investigate the Integration of Artificial Intelligence in e-Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Artificial intelligence; Data science; Information retrieval","score_opus":0.13910495510628745,"score_gpt":0.3736360754504002,"score_spread":0.23453112034411272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409468107","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00050594885,0.00007271518,0.9836774,0.0017766596,0.00014723024,0.00022436249,0.0000045887773,0.000025992633,0.013565124],"genre_scores_gemma":[0.43675378,0.0008309344,0.5603181,0.0009853238,0.00003120476,0.000010899207,0.00004853253,0.000008582363,0.0010126483],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851197,0.00011642853,0.00074508716,0.00018813742,0.00029183686,0.00014653176],"domain_scores_gemma":[0.99770194,0.00047281166,0.00029638413,0.0010703038,0.00041106722,0.000047509962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002718048,0.00013290042,0.00019906992,0.0011842106,0.00026070172,0.0003354666,0.002504006,0.00007357587,0.0000010886928],"category_scores_gemma":[0.00044603867,0.00011314001,0.000026339361,0.0013145156,0.0005012511,0.0016876732,0.0017138142,0.0005725317,0.0000069278503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014712864,0.000007908751,0.0002034564,0.000011457083,0.0000017936999,7.85266e-8,0.0024421697,0.025892168,0.000010780624,0.6518551,0.00001104128,0.31956255],"study_design_scores_gemma":[0.000021497015,0.000025675028,0.0012833677,0.00033544804,0.0000019520633,0.0000015867374,0.00005092279,0.9830197,0.000026461226,0.013398554,0.0017216027,0.00011321777],"about_ca_topic_score_codex":0.00014671651,"about_ca_topic_score_gemma":0.00017930644,"teacher_disagreement_score":0.9571276,"about_ca_system_score_codex":0.00009339391,"about_ca_system_score_gemma":0.00040762694,"threshold_uncertainty_score":0.46531075},"labels":[],"label_agreement":null},{"id":"W4409507688","doi":"10.1007/978-3-031-85856-7_13","title":"AuthAttLyzer-V2: Unveiling Code Authorship Attribution Using Enhanced Ensemble Learning Models and Generating Benchmark Dataset","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Benchmark (surveying); Computer science; Attribution; Code (set theory); Artificial intelligence; Authorship attribution; Natural language processing; Ensemble learning; Information retrieval; Machine learning; Programming language; Psychology; Cartography; Geography","score_opus":0.12797304388066152,"score_gpt":0.34642177946470937,"score_spread":0.21844873558404784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409507688","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034935513,0.00071463437,0.9858465,0.0004310867,0.00029912754,0.00035981828,0.00011159402,0.00012147906,0.011766375],"genre_scores_gemma":[0.32808173,0.002620517,0.6648543,0.001144061,0.000083857085,0.0000330039,0.001993512,0.00001895266,0.0011701218],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747115,0.00016399316,0.0009456593,0.00053082075,0.00048416128,0.00040419705],"domain_scores_gemma":[0.9969438,0.0004057197,0.00054104475,0.0014871462,0.0004501531,0.00017215089],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0033199794,0.00032613453,0.00036624516,0.000997854,0.0016675164,0.0011535657,0.0020124922,0.00027160524,0.0000047228355],"category_scores_gemma":[0.00014892264,0.00035979453,0.00004475309,0.00067924854,0.00055381586,0.00789563,0.003383712,0.0010028082,0.000008677358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037324846,0.000009838951,0.00003561195,0.00007806916,0.000009552877,4.847579e-7,0.0024364926,0.020256203,0.00013666275,0.82629174,0.000095826654,0.15064578],"study_design_scores_gemma":[0.00021043928,0.00002585046,0.00004136709,0.00039629004,0.000010760693,0.000016117347,0.00003031592,0.9728543,0.00016542955,0.011851952,0.014041753,0.00035540346],"about_ca_topic_score_codex":0.000021691609,"about_ca_topic_score_gemma":0.000012333134,"teacher_disagreement_score":0.9525981,"about_ca_system_score_codex":0.00025697306,"about_ca_system_score_gemma":0.00053601695,"threshold_uncertainty_score":0.9998854},"labels":[],"label_agreement":null},{"id":"W4409529026","doi":"10.1007/978-3-031-85933-5_8","title":"A Review of Multi-modal and Multi-view Applications in Hand-Drawn Sketch Images","year":2025,"lang":"en","type":"review","venue":"Communications in computer and information science","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Sketch; Modal; Computer science; Information retrieval; Artificial intelligence; Algorithm; Materials science","score_opus":0.04784014137262523,"score_gpt":0.3799446016412361,"score_spread":0.3321044602686109,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409529026","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.6625931e-7,0.6236844,0.37539345,0.00010178291,0.000060723727,0.0005635082,0.00000838007,0.000021694557,0.00016571366],"genre_scores_gemma":[0.000023109129,0.75287735,0.24672776,0.00015789724,0.0000040951522,0.00017729068,0.000023169758,0.0000024942208,0.000006844673],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979095,0.00017603459,0.0011861257,0.00032959858,0.00019064883,0.00020813571],"domain_scores_gemma":[0.99723333,0.00033403793,0.00054647535,0.0014621996,0.00036020606,0.00006372148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001534702,0.00023128687,0.0007534799,0.0012569721,0.00046795743,0.0005932981,0.002452749,0.00009802535,6.756805e-7],"category_scores_gemma":[0.00016001848,0.0001999555,0.00007070765,0.0033527904,0.0012608576,0.0042042723,0.0017964536,0.0003742495,0.0000037439709],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.737536e-8,0.00003627655,0.000018243956,0.024190636,0.0000023921891,4.015886e-8,0.00033213283,0.0000018948085,1.0497835e-7,0.0016285464,0.000016756601,0.9737729],"study_design_scores_gemma":[0.00053817633,0.000024267692,0.0003516716,0.15880184,0.000053591302,0.000088363886,0.000041368447,0.15098739,0.000005635383,0.00020647477,0.68835884,0.00054240826],"about_ca_topic_score_codex":0.00002687282,"about_ca_topic_score_gemma":0.000010898266,"teacher_disagreement_score":0.9732305,"about_ca_system_score_codex":0.00007903532,"about_ca_system_score_gemma":0.0011701598,"threshold_uncertainty_score":0.8153949},"labels":[],"label_agreement":null},{"id":"W4409529050","doi":"10.1007/978-3-031-85933-5_13","title":"Mobility Anomaly Detection with Intelligent Video Surveillance","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Anomaly detection; Computer science; Anomaly (physics); Remote sensing; Artificial intelligence; Geography; Physics","score_opus":0.020313341529396838,"score_gpt":0.271366712868013,"score_spread":0.25105337133861616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409529050","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005961529,0.00015603857,0.87663263,0.00048647844,0.00009674488,0.0005088129,0.000008770892,0.00022042831,0.121830486],"genre_scores_gemma":[0.614913,0.0041962177,0.3726701,0.0016283002,0.000054205288,0.0003876512,0.000051702966,0.000019606094,0.006079227],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99837387,0.000029833585,0.000633272,0.0004106542,0.00034303433,0.00020935944],"domain_scores_gemma":[0.9961934,0.00017460895,0.00033271348,0.00266306,0.0005479987,0.00008821221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009069294,0.00023381034,0.00024489372,0.0009146928,0.00057642313,0.0005238628,0.0026316703,0.00013310232,0.0000055654855],"category_scores_gemma":[0.0000256438,0.00021931894,0.0000473143,0.00085517124,0.00076340896,0.003604638,0.0016554493,0.0003813379,0.000019990475],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036273377,0.000021258626,0.00007048937,0.000026069967,0.0000054872735,1.4942117e-7,0.00021923015,0.00009838735,0.000006348357,0.43543783,0.00009651445,0.5640146],"study_design_scores_gemma":[0.0002858049,0.00021464375,0.0042833537,0.0002536446,0.0000069969947,0.00006129562,0.000019896912,0.4848846,0.00048485142,0.015639564,0.4931848,0.0006805477],"about_ca_topic_score_codex":0.000038312315,"about_ca_topic_score_gemma":0.00010707743,"teacher_disagreement_score":0.6148534,"about_ca_system_score_codex":0.00024191808,"about_ca_system_score_gemma":0.00030966167,"threshold_uncertainty_score":0.89435667},"labels":[],"label_agreement":null},{"id":"W4409537179","doi":"10.1007/978-3-031-85933-5_2","title":"Analysis of Driver Attention to Objects While Driving","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Thesaurus; Information retrieval; Artificial intelligence","score_opus":0.025922107292989893,"score_gpt":0.2870758553090325,"score_spread":0.26115374801604263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409537179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006798183,0.00007923414,0.8379336,0.0008760478,0.00018260998,0.00023600887,0.000010890393,0.00010906295,0.15989274],"genre_scores_gemma":[0.82036793,0.0004135715,0.176864,0.00056820386,0.000007663815,0.000018776427,0.000041791725,0.0000038520325,0.0017142],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871135,0.000021046893,0.0005538954,0.0002588394,0.0002961252,0.00015873244],"domain_scores_gemma":[0.99710363,0.00017129915,0.0002897686,0.0019167108,0.00046379428,0.00005480049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066549436,0.00014238142,0.0003101412,0.0038902047,0.00023269375,0.00020135615,0.0029076596,0.00010246238,0.0000037793745],"category_scores_gemma":[0.000053161915,0.00014847239,0.00007290267,0.0020774999,0.00043738115,0.002082394,0.0025678289,0.00024078965,0.000014251971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.1233254e-7,0.000015638841,0.0015465728,0.000015849993,0.000046192683,1.5559937e-7,0.00088913704,0.0005747352,0.000017227121,0.7550105,0.00015669895,0.24172673],"study_design_scores_gemma":[0.00022911193,0.00008652374,0.14698529,0.0005342586,0.00011493635,0.0000034804389,0.000035931673,0.8114349,0.000042146505,0.004209449,0.035876352,0.00044760184],"about_ca_topic_score_codex":0.000012526012,"about_ca_topic_score_gemma":0.000037352755,"teacher_disagreement_score":0.81968814,"about_ca_system_score_codex":0.00010059754,"about_ca_system_score_gemma":0.0001640119,"threshold_uncertainty_score":0.60545284},"labels":[],"label_agreement":null},{"id":"W4409603440","doi":"10.1007/978-3-031-88226-5_16","title":"Functional Sparse Data Clustering Using Conditional Expectation PACE Method","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Cluster analysis; Pace; Data mining; Pattern recognition (psychology); Artificial intelligence; Physics","score_opus":0.15505149710650282,"score_gpt":0.3661923080572737,"score_spread":0.2111408109507709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409603440","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011116579,0.0001424837,0.94881713,0.0007186422,0.00041408357,0.00025088608,0.000057682337,0.00007676468,0.049511224],"genre_scores_gemma":[0.0042142393,0.0007537553,0.9909421,0.0013383464,0.00006636215,0.00002290013,0.0011732822,0.000007562931,0.0014814313],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981559,0.00005748564,0.0006354882,0.00043009376,0.00052227156,0.00019878677],"domain_scores_gemma":[0.9963654,0.00033324005,0.0003464793,0.0024326912,0.00043909473,0.000083066705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011306228,0.0002094332,0.00021768134,0.0011206483,0.00064683275,0.00063402567,0.0030084385,0.00013481203,0.000026650254],"category_scores_gemma":[0.000068656795,0.00022175234,0.00003518291,0.00044038295,0.000349158,0.010998484,0.0049934597,0.0003731551,0.00004345087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010621462,0.00004468789,0.00003949046,0.00009865306,0.000025865766,0.0000011855313,0.0017505533,0.009766191,0.00007393063,0.53870165,0.0070054214,0.44248173],"study_design_scores_gemma":[0.0002421861,0.000012404496,0.0003222452,0.00026693998,0.00000796781,0.000029411012,0.000034698747,0.9487345,0.000019657902,0.0074591637,0.042642422,0.00022837176],"about_ca_topic_score_codex":0.000018204333,"about_ca_topic_score_gemma":0.000010262695,"teacher_disagreement_score":0.93896836,"about_ca_system_score_codex":0.0001513817,"about_ca_system_score_gemma":0.0005181942,"threshold_uncertainty_score":0.9042798},"labels":[],"label_agreement":null},{"id":"W4409618148","doi":"10.1007/978-3-031-86302-8_2","title":"Comparative Analysis of Improved K-Means Clustering for Human Freedom Index","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Index (typography); Cluster analysis; Computer science; Information retrieval; Artificial intelligence; World Wide Web","score_opus":0.051644602779820775,"score_gpt":0.3331275381133378,"score_spread":0.281482935333517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409618148","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005063447,0.00007545593,0.91746587,0.00019662967,0.00013759619,0.0004229362,0.000051616677,0.00003855374,0.08156071],"genre_scores_gemma":[0.34297186,0.000935957,0.6507296,0.0010796518,0.0000416988,0.00019453019,0.0006381112,0.000009851548,0.0033987276],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858385,0.000021957258,0.0007432508,0.00024849415,0.00024250538,0.00015993275],"domain_scores_gemma":[0.99710125,0.0002818986,0.00045904453,0.0014725198,0.00062973076,0.000055579734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006572948,0.0001707325,0.00043121292,0.0022758706,0.0003998469,0.00028475642,0.0023727103,0.000112341724,0.0000048532347],"category_scores_gemma":[0.00002151146,0.00017054478,0.0001069208,0.0009226734,0.0005032786,0.0031180622,0.0017224178,0.00021423383,0.000002333152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001262116,0.000061144885,0.00012619514,0.00015591712,0.0002223752,8.236869e-8,0.007145742,0.01150435,0.00013824069,0.81136304,0.00073800224,0.16853227],"study_design_scores_gemma":[0.00026775035,0.00004303587,0.00072591606,0.00017750583,0.000045934266,4.8516955e-7,0.00003533238,0.9817673,0.000033695585,0.002992812,0.013739924,0.00017033174],"about_ca_topic_score_codex":0.000036755424,"about_ca_topic_score_gemma":0.00011778203,"teacher_disagreement_score":0.97026294,"about_ca_system_score_codex":0.000073226016,"about_ca_system_score_gemma":0.00017032269,"threshold_uncertainty_score":0.69546145},"labels":[],"label_agreement":null},{"id":"W4409625226","doi":"10.1007/978-3-031-85908-3_42","title":"A Health Records Kiosk, Using an Ontology-Based Information Architecture","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Interactive kiosk; Ontology; Computer science; Information retrieval; Architecture; World Wide Web; Geography; Archaeology; Philosophy","score_opus":0.20991404066395322,"score_gpt":0.44267862084468507,"score_spread":0.23276458018073184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409625226","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000045024997,0.00011694564,0.82333624,0.007127773,0.00048739434,0.0006573702,0.0001683913,0.00006538668,0.16799547],"genre_scores_gemma":[0.02510276,0.0017123221,0.89576185,0.069308035,0.00012189359,0.00008253146,0.0024113138,0.000020767015,0.0054785097],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996582,0.00018625139,0.0016172483,0.0002942034,0.0010554834,0.00026484954],"domain_scores_gemma":[0.99466884,0.0005509837,0.00094348495,0.0030431582,0.00064718595,0.00014636396],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007096228,0.0002205254,0.0004006984,0.002934378,0.0008171302,0.001328859,0.0037888412,0.00013534086,0.000031142397],"category_scores_gemma":[0.00045678075,0.00019829544,0.000058408983,0.00086640706,0.00091755646,0.010884624,0.001897122,0.00048147197,0.00006312657],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000065380273,0.000016750615,0.000023344717,0.000033767672,0.0000030331157,6.172881e-8,0.001543832,0.0023145063,7.6425664e-8,0.25482407,0.0019453426,0.7392887],"study_design_scores_gemma":[0.00023940497,0.00006745365,0.000538086,0.00017828569,0.0000044685544,0.0000042612414,0.00013426365,0.31658638,4.985969e-7,0.025026845,0.6570288,0.0001912665],"about_ca_topic_score_codex":0.00019054828,"about_ca_topic_score_gemma":0.00040873655,"teacher_disagreement_score":0.7390974,"about_ca_system_score_codex":0.00025453037,"about_ca_system_score_gemma":0.0011589965,"threshold_uncertainty_score":0.9997079},"labels":[],"label_agreement":null},{"id":"W4409625236","doi":"10.1007/978-3-031-85908-3_27","title":"Challenges and Opportunities in a Big Data Pipeline for Resilience and Wellness Development: A Case Study for Police Training","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Resilience and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Ontario Tech University","funders":"","keywords":"Resilience (materials science); Pipeline (software); Training (meteorology); Big data; Computer science; Data science; Data mining; Geography; Operating system","score_opus":0.466900602743254,"score_gpt":0.46886546021826636,"score_spread":0.0019648574750123493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409625236","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06341596,0.035643056,0.18072158,0.008958588,0.0026058112,0.022113077,0.00093701895,0.00022002071,0.68538487],"genre_scores_gemma":[0.94755405,0.024285702,0.02183235,0.0013965584,0.00007078404,0.00064140256,0.000236368,0.000015441965,0.0039673247],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99875593,0.000034842255,0.00058220926,0.00030753217,0.00011697709,0.00020252433],"domain_scores_gemma":[0.9980636,0.0005582057,0.00017545263,0.001031121,0.00010230215,0.000069273796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001899992,0.00014446095,0.00022997199,0.0007551431,0.00043419123,0.00010529487,0.0008537493,0.000074050615,6.698313e-7],"category_scores_gemma":[0.00003049356,0.00014374117,0.000007847592,0.00010111279,0.0005267596,0.0013448815,0.0010237194,0.00015515673,4.882525e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013112992,0.000028143013,0.00001954438,0.00010469255,0.0000028322766,0.0000011444708,0.07108977,9.873233e-7,4.4807756e-8,0.036131334,0.00004329698,0.8925651],"study_design_scores_gemma":[0.0051294775,0.0006514783,0.004718431,0.0019146611,0.000046615158,0.00097609474,0.23121439,0.117591,0.000002147067,0.003453407,0.6332386,0.0010637118],"about_ca_topic_score_codex":0.00014574459,"about_ca_topic_score_gemma":0.0021533906,"teacher_disagreement_score":0.89150137,"about_ca_system_score_codex":0.000044851935,"about_ca_system_score_gemma":0.00037548618,"threshold_uncertainty_score":0.58615947},"labels":[],"label_agreement":null},{"id":"W4409625260","doi":"10.1007/978-3-031-85908-3_14","title":"Comparing Models for Sentiment Analysis of Tweets in Response to Public Health Announcements During the Pandemic","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Western University","funders":"","keywords":"Sentiment analysis; Pandemic; Coronavirus disease 2019 (COVID-19); Computer science; Natural language processing; Information retrieval; Medicine; Internal medicine","score_opus":0.12101108950349247,"score_gpt":0.35711193597439644,"score_spread":0.23610084647090396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409625260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004886638,0.00038566557,0.982465,0.0039151115,0.00015566673,0.00091859256,0.000029963416,0.00003525092,0.0072080805],"genre_scores_gemma":[0.92086416,0.0012039681,0.074947,0.0015497135,0.000011354965,0.00010510612,0.000110748064,0.0000062067415,0.0012017292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99787295,0.00008952205,0.001050647,0.0002818045,0.00044606216,0.0002590294],"domain_scores_gemma":[0.9971016,0.00038034233,0.00048382676,0.001631194,0.00032378297,0.000079239035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004266653,0.00015542164,0.00042994437,0.003604199,0.00042115396,0.00040293494,0.002737971,0.000047373906,0.0000017103451],"category_scores_gemma":[0.000042440777,0.00013742076,0.00009680981,0.002196045,0.00019215375,0.0024259912,0.002139687,0.00017430382,0.0000015326277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006994723,0.00014828314,0.020277888,0.00016768911,0.00048267856,1.9764015e-7,0.03708915,0.17377894,0.000033213488,0.6042626,0.0003690412,0.1633204],"study_design_scores_gemma":[0.00027667708,0.000025937901,0.01605298,0.00016082826,0.000016549317,4.1479186e-7,0.00006751206,0.97290856,0.0000016534535,0.0004890005,0.009871734,0.00012814472],"about_ca_topic_score_codex":0.000029441322,"about_ca_topic_score_gemma":0.000075763484,"teacher_disagreement_score":0.91597754,"about_ca_system_score_codex":0.00032559555,"about_ca_system_score_gemma":0.00038129115,"threshold_uncertainty_score":0.56038564},"labels":[],"label_agreement":null},{"id":"W4409625267","doi":"10.1007/978-3-031-85908-3_4","title":"MobiVitalsConnect: A Comprehensive Mobile Healthcare System for Real-Time Patient Monitoring and Data Visualization","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Sheridan College","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Health care; World Wide Web; Real-time computing; Data mining; Political science","score_opus":0.07314189646189875,"score_gpt":0.35175466855362125,"score_spread":0.2786127720917225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409625267","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000985623,0.002883097,0.9511167,0.000948666,0.0017109454,0.0058030263,0.00069389556,0.00064488867,0.035213158],"genre_scores_gemma":[0.7688877,0.010320158,0.21524312,0.00079953606,0.00023796064,0.0012832346,0.0017204129,0.000061917046,0.0014459775],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977916,0.000085511594,0.0009026648,0.0005680843,0.00040499732,0.000247147],"domain_scores_gemma":[0.9943485,0.0008654489,0.00057301624,0.0030507562,0.0010421516,0.00012010367],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00089253346,0.00026889952,0.0004285986,0.0009844283,0.0006739395,0.0008801494,0.0027498077,0.00014961997,7.676976e-7],"category_scores_gemma":[0.000054430464,0.00029301873,0.00003713426,0.0004401872,0.00032981506,0.0072087566,0.0047489577,0.00021647013,0.000012415148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007841995,0.000026956484,0.00005891845,0.0006821363,0.000024493045,5.0213714e-7,0.0038248047,0.00007208913,0.00003232932,0.20685709,0.00040613962,0.7880067],"study_design_scores_gemma":[0.00062577816,0.00021511209,0.0002786891,0.0024989136,0.000018976809,0.00005678143,0.00041007542,0.90657556,0.0000628267,0.0009103052,0.087759934,0.0005870386],"about_ca_topic_score_codex":0.00007264644,"about_ca_topic_score_gemma":0.000008988935,"teacher_disagreement_score":0.9065035,"about_ca_system_score_codex":0.00027668473,"about_ca_system_score_gemma":0.00040759187,"threshold_uncertainty_score":0.9999522},"labels":[],"label_agreement":null},{"id":"W4409625268","doi":"10.1007/978-3-031-85908-3_9","title":"Advancing Fall Detection and Prevention: Integrating Wearable Devices and a Camera-Based Analysis","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lions Gate Hospital; Health PEI; Burnaby Hospital; University of British Columbia","funders":"","keywords":"Wearable computer; Computer science; Embedded system","score_opus":0.025289057585671442,"score_gpt":0.29353605347943007,"score_spread":0.2682469958937586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409625268","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003826456,0.00084031676,0.97117555,0.0006762585,0.0001189594,0.0003692827,0.000006376009,0.00008439155,0.026346225],"genre_scores_gemma":[0.81160456,0.0014399085,0.1845645,0.0009528835,0.000025059644,0.000077927194,0.000027389538,0.000007693295,0.0013000995],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984604,0.0000777874,0.0006260752,0.00035811093,0.00029888802,0.00017874912],"domain_scores_gemma":[0.997529,0.0004788315,0.00042273485,0.0010532662,0.00042808696,0.00008812024],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013191577,0.00020445272,0.00033432955,0.0018544539,0.000622959,0.0010608017,0.00097926,0.00010615025,0.000002430735],"category_scores_gemma":[0.000077378376,0.00021219357,0.00005473665,0.0010288638,0.0003766422,0.0062064887,0.0011957315,0.00034371487,0.0000037368566],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002095511,0.000008973671,0.00052937673,0.00007637032,0.000033994926,1.8842725e-7,0.0009816358,0.00013439641,0.0000062024333,0.015267874,0.000014880519,0.982944],"study_design_scores_gemma":[0.00025887863,0.000053083517,0.0024998372,0.0006059783,0.00004802561,0.000014296954,0.0000808252,0.9733027,0.000017420354,0.0017091688,0.021140419,0.00026933305],"about_ca_topic_score_codex":0.00012613347,"about_ca_topic_score_gemma":0.0012788125,"teacher_disagreement_score":0.98267466,"about_ca_system_score_codex":0.00012887538,"about_ca_system_score_gemma":0.00026617793,"threshold_uncertainty_score":0.9999762},"labels":[],"label_agreement":null},{"id":"W4409625346","doi":"10.1007/978-3-031-85908-3_25","title":"Predictive Modelling for Length of Stay with the MIMIC-III Critical Care Database","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Database; Information retrieval","score_opus":0.04909115341487293,"score_gpt":0.34221945180764124,"score_spread":0.2931282983927683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409625346","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00030657646,0.0007129556,0.93852776,0.0008864481,0.00010215638,0.0006846091,0.00013720214,0.000021150792,0.058621123],"genre_scores_gemma":[0.77151924,0.003772822,0.22205132,0.0006685491,0.00008277597,0.00010944214,0.00041379945,0.000013839135,0.0013682293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992762,0.0000104976625,0.00028746712,0.000111365334,0.00021548527,0.00009896715],"domain_scores_gemma":[0.997848,0.0003929328,0.000096620635,0.0009680541,0.00065469916,0.00003970653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039200648,0.00009934667,0.0001744102,0.00026612615,0.0002560569,0.000044051154,0.00048123897,0.000054377982,0.0000011723181],"category_scores_gemma":[0.000023653014,0.000068742374,0.000025982607,0.000116470386,0.00081849814,0.0006386826,0.00023255945,0.0002475025,4.4469215e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023590155,0.000056784247,0.000111296584,0.0008694599,0.00006574376,3.1993906e-7,0.017873865,0.005004471,0.0000072837975,0.79319227,0.0003093206,0.1822733],"study_design_scores_gemma":[0.00066146144,0.00019120271,0.00005112914,0.00096266874,0.00004743128,0.0000059272884,0.00052443193,0.9457823,0.000030695857,0.00059808773,0.05103873,0.00010594931],"about_ca_topic_score_codex":0.00001321375,"about_ca_topic_score_gemma":0.0000033824874,"teacher_disagreement_score":0.94077784,"about_ca_system_score_codex":0.00005745402,"about_ca_system_score_gemma":0.00035328287,"threshold_uncertainty_score":0.30157906},"labels":[],"label_agreement":null},{"id":"W4409651922","doi":"10.1007/978-3-031-86305-9_7","title":"An Ensemble Method for Insider Threat Detection Based on User Activities Analysis Using Bi-LSTM and GA Optimization","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Insider threat; Insider; Computer science; Artificial intelligence; Data mining; Political science; Law","score_opus":0.03871672347815553,"score_gpt":0.32098500664887886,"score_spread":0.28226828317072333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409651922","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009599478,0.00007249727,0.99246514,0.00017037577,0.00022783899,0.00044336298,0.000010952633,0.00008242871,0.0064314147],"genre_scores_gemma":[0.0497494,0.00061446097,0.9482609,0.0010629734,0.00003679416,0.000044491426,0.00005464357,0.0000083530995,0.00016797773],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998488,0.00009365771,0.000512805,0.000393538,0.00032138638,0.00019060074],"domain_scores_gemma":[0.997269,0.00047435865,0.00033175052,0.0014728261,0.0003721178,0.00007999167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011936559,0.00022838012,0.00030325286,0.002480887,0.00094120944,0.0008727366,0.0010040703,0.00018673467,0.0000040534383],"category_scores_gemma":[0.000038922677,0.0002355875,0.00007400034,0.0011281772,0.00027247937,0.0061198603,0.00052987994,0.00027868417,7.296005e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019934794,0.000029841054,0.00001581747,0.000039647508,0.000028955204,8.830275e-8,0.00083084934,0.4728284,0.00004079766,0.11440226,0.000025503903,0.41173792],"study_design_scores_gemma":[0.00024137949,0.000121418285,0.00008703892,0.00009573084,0.00005209695,0.0000036745455,0.00001451272,0.9908667,0.00017608219,0.0021666873,0.0059403074,0.00023437472],"about_ca_topic_score_codex":0.000032847,"about_ca_topic_score_gemma":0.00007804842,"teacher_disagreement_score":0.51803833,"about_ca_system_score_codex":0.00017035424,"about_ca_system_score_gemma":0.00018525189,"threshold_uncertainty_score":0.96069795},"labels":[],"label_agreement":null},{"id":"W4409665822","doi":"10.1007/978-3-031-85930-4_3","title":"A Novel Simple Data Structure for Selecting, Inserting, and Deleting in Square Root Time","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Earl Haig Secondary School","funders":"","keywords":"Square root; Simple (philosophy); Root (linguistics); Computer science; Square (algebra); Algorithm; Mathematics; Geometry; Philosophy","score_opus":0.041574504631492266,"score_gpt":0.3129840639268332,"score_spread":0.27140955929534094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409665822","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002087122,0.00044523974,0.9881424,0.0005759953,0.00012634127,0.000627454,0.00024237034,0.00007129967,0.009560192],"genre_scores_gemma":[0.016648827,0.00044155665,0.98030794,0.0009369429,0.00005529834,0.000028138405,0.0010585036,0.000012122857,0.00051070174],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984033,0.00001980932,0.0006409942,0.00043907354,0.00025768613,0.00023911626],"domain_scores_gemma":[0.9964882,0.00039963395,0.00033164932,0.0024509497,0.0002640909,0.00006545038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010650891,0.00020183843,0.00025167427,0.000760095,0.00053097506,0.0007358107,0.0041974364,0.00012543339,0.0000026894916],"category_scores_gemma":[0.00017699113,0.00019776278,0.00001741501,0.00044139568,0.0002448129,0.006078351,0.007819748,0.00038303694,0.00000201442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005738931,0.000025397476,0.00032981893,0.00014117076,0.0000062101844,2.1390032e-7,0.0018679994,0.0003818875,0.000040118386,0.16712905,0.0015710554,0.82850134],"study_design_scores_gemma":[0.00031856063,0.000025939657,0.0009836009,0.00031049192,0.0000030227393,0.0000115339035,0.00000870562,0.88509685,0.0000052178084,0.0035777944,0.109454885,0.00020337026],"about_ca_topic_score_codex":0.00005408095,"about_ca_topic_score_gemma":0.00011246572,"teacher_disagreement_score":0.88471496,"about_ca_system_score_codex":0.00007760672,"about_ca_system_score_gemma":0.00032108466,"threshold_uncertainty_score":0.9746756},"labels":[],"label_agreement":null},{"id":"W4409800425","doi":"10.1007/978-981-96-5881-7_8","title":"A Comparative Analysis of Tabular Generative Models on Gene-Expression Data","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Expression (computer science); Computational biology; Computer science; Biology; Programming language","score_opus":0.09387070961513544,"score_gpt":0.3569603669825378,"score_spread":0.26308965736740236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409800425","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014199689,0.0023157252,0.48366052,0.00050312316,0.00026299572,0.00088206836,0.00080264575,0.00002400993,0.5101289],"genre_scores_gemma":[0.8694382,0.016387984,0.09442758,0.0018504139,0.00008251759,0.00008736723,0.010763196,0.000014381334,0.006948384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882925,0.00003132498,0.0004705125,0.00032114543,0.00025242177,0.00009537479],"domain_scores_gemma":[0.99657184,0.000037897033,0.00033344564,0.0026653402,0.00034536349,0.000046090274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004222789,0.00015152142,0.0002715713,0.0009383919,0.00017644945,0.00006638439,0.0016352807,0.00012425726,0.0000057283673],"category_scores_gemma":[0.000019470666,0.00014156959,0.00004688819,0.00044372623,0.0004497365,0.00014644233,0.0015848433,0.00015034473,0.0000018311092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027340674,0.00036114926,0.00031046913,0.00015591318,0.001027797,3.6120178e-7,0.006086942,0.13130459,0.04109422,0.6150186,0.03221845,0.17214808],"study_design_scores_gemma":[0.00041570264,0.000116767354,0.00067672925,0.00022503758,0.00014136429,7.073583e-7,0.000092066264,0.8287085,0.014071214,0.0010790188,0.15410672,0.00036616132],"about_ca_topic_score_codex":0.000004339575,"about_ca_topic_score_gemma":0.000013256313,"teacher_disagreement_score":0.8680182,"about_ca_system_score_codex":0.0000325701,"about_ca_system_score_gemma":0.00026742145,"threshold_uncertainty_score":0.57730407},"labels":[],"label_agreement":null},{"id":"W4409806752","doi":"10.1007/978-981-96-4285-4_24","title":"A Low-Cost EEG-Based System for Measuring and Forecasting Levels of Alertness with Long Short-Term Memory","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Coquitlam College","funders":"","keywords":"Alertness; Term (time); Electroencephalography; Computer science; Audiology; Psychology; Neuroscience; Medicine; Psychiatry; Physics","score_opus":0.10412223678773767,"score_gpt":0.32076336211078355,"score_spread":0.21664112532304586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409806752","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005137944,0.00078992755,0.729519,0.00015160089,0.0005333184,0.0021117143,0.00012782287,0.000094122304,0.26153454],"genre_scores_gemma":[0.9883221,0.000039589617,0.011173973,0.000091619535,0.000012653824,0.00010230988,0.000049006467,0.00000937362,0.00019941054],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986958,0.000029557108,0.00066996115,0.00020811365,0.00021423599,0.0001823419],"domain_scores_gemma":[0.99772644,0.0005092986,0.0003206272,0.0009457982,0.00044042137,0.000057426954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009229857,0.00018179498,0.00029323107,0.0007266266,0.0003452095,0.000116645184,0.0007781529,0.00014859767,0.0000043639366],"category_scores_gemma":[0.000025600619,0.00016748339,0.000036184058,0.0002478312,0.00064719876,0.000864555,0.00031447326,0.0002643951,0.0000015584317],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044514356,0.000024552626,0.0016178036,0.00034259396,0.000046889858,6.712932e-7,0.0028118335,0.00080178864,0.0000029994821,0.081946306,0.000027374146,0.91233265],"study_design_scores_gemma":[0.014295812,0.0007884777,0.103650875,0.074684255,0.00058242644,0.00019898907,0.002998352,0.79325646,0.0010774963,0.00047380725,0.0040239,0.003969178],"about_ca_topic_score_codex":0.000010002339,"about_ca_topic_score_gemma":0.00002237863,"teacher_disagreement_score":0.9831841,"about_ca_system_score_codex":0.0000818933,"about_ca_system_score_gemma":0.00016551226,"threshold_uncertainty_score":0.68297744},"labels":[],"label_agreement":null},{"id":"W4410033730","doi":"10.1007/978-3-031-88854-0_7","title":"Recognizing Overarching Themes and Actors in Peacebuilding: A Longitudinal Analysis of Press Content in Latin America","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sport and Mega-Event Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Latin Americans; Peacebuilding; Political science; Content analysis; Content (measure theory); Library science; Sociology; Social science; Computer science; Public administration; Law; Mathematics","score_opus":0.157747395266926,"score_gpt":0.37237104539904553,"score_spread":0.21462365013211954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410033730","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24569738,0.0030991775,0.0062092897,0.0017316758,0.00032271384,0.0014497915,0.000053179127,0.000058178626,0.7413786],"genre_scores_gemma":[0.9854786,0.007908077,0.0057415734,0.0001332672,0.0000082369,0.0000099655,0.000029619596,0.000002578273,0.00068812387],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99882185,0.00004787744,0.00054868014,0.0001407724,0.00027451408,0.00016631582],"domain_scores_gemma":[0.9986973,0.00038739882,0.00031303504,0.00039482675,0.00015230481,0.00005518054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012081289,0.000104220075,0.00030053643,0.0017509056,0.00020907697,0.00015344226,0.0006377675,0.00006694729,0.000006731322],"category_scores_gemma":[0.0002124337,0.00010443939,0.00003564522,0.0010232165,0.0007387163,0.0015622069,0.0005185135,0.00025172645,2.8791334e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017656886,0.00005341918,0.063059025,0.000057942885,0.000060298175,5.822578e-7,0.0899003,0.0008043861,0.0000052080204,0.4128429,0.000060455473,0.43313783],"study_design_scores_gemma":[0.0011261879,0.000085085034,0.4854746,0.0024482678,0.00017421275,0.0000013538876,0.004085498,0.1770813,0.0000128395195,0.0035809905,0.32513067,0.0007990084],"about_ca_topic_score_codex":0.0024001626,"about_ca_topic_score_gemma":0.0022665577,"teacher_disagreement_score":0.74069047,"about_ca_system_score_codex":0.00012737558,"about_ca_system_score_gemma":0.0002484863,"threshold_uncertainty_score":0.42589146},"labels":[],"label_agreement":null},{"id":"W4410034677","doi":"10.1007/978-3-031-88854-0_10","title":"Using Machine and Deep Transfer Learning for Classification of EEG Signals from Embodied and Non-embodied Priming in a Motor Imagery Training in Virtual Reality","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Embodied cognition; Priming (agriculture); Computer science; Motor imagery; Electroencephalography; Psychology; Virtual reality; Brain–computer interface; Artificial intelligence; Cognitive psychology; Neuroscience; Biology","score_opus":0.11933785731562116,"score_gpt":0.3423302021051162,"score_spread":0.22299234478949506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410034677","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22835562,0.0006932601,0.73310626,0.00070487766,0.00028703568,0.0023138442,0.00018157733,0.00007205531,0.0342855],"genre_scores_gemma":[0.9858444,0.0006965336,0.013143526,0.00019890259,0.000009406073,0.000023536535,0.000031609336,0.0000068276145,0.00004527694],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982497,0.00009343774,0.0009006042,0.0003527946,0.00020904627,0.00019442142],"domain_scores_gemma":[0.9978834,0.0012533105,0.00025375155,0.00045094406,0.00010766199,0.000050943425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001194606,0.00019967965,0.00038915154,0.0010403823,0.00026249117,0.00022133472,0.00063092646,0.00012474372,0.0000016947143],"category_scores_gemma":[0.00019463302,0.00020793767,0.000032738302,0.00026928989,0.0007350908,0.0019695882,0.00046561542,0.00042617702,2.3493352e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019735732,0.000105235275,0.0019498977,0.00051644264,0.000017420492,0.0000013929404,0.07491066,0.0088821165,0.045931462,0.13743292,0.0000067928177,0.7300483],"study_design_scores_gemma":[0.00063839986,0.00006441727,0.004251799,0.0006848401,0.000008055447,0.0000034385241,0.0003154561,0.99038094,0.0005879254,0.002401446,0.00045882797,0.00020443257],"about_ca_topic_score_codex":0.00008752158,"about_ca_topic_score_gemma":0.00010387742,"teacher_disagreement_score":0.98149884,"about_ca_system_score_codex":0.00008415908,"about_ca_system_score_gemma":0.00017308623,"threshold_uncertainty_score":0.8479452},"labels":[],"label_agreement":null},{"id":"W4410041388","doi":"10.1007/978-3-031-86623-4_17","title":"Harnessing Pre-trained Language Models for Efficient Move Recognition in Biomedical Abstracts","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Information retrieval","score_opus":0.04928139306695458,"score_gpt":0.3130020145758459,"score_spread":0.26372062150889136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410041388","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003524589,0.00019380295,0.94393826,0.0007181237,0.0002573296,0.00056247413,0.000021915665,0.00006946201,0.053886198],"genre_scores_gemma":[0.23524635,0.0004176463,0.762072,0.0010967555,0.00005122723,0.00011643241,0.00019569272,0.000009884465,0.00079396286],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982411,0.000022930246,0.000819107,0.0003195916,0.0003539463,0.0002432842],"domain_scores_gemma":[0.99780434,0.00032128213,0.00026993215,0.0012813136,0.0002475213,0.00007563283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001456216,0.00017458061,0.00022479129,0.0012866866,0.00024574078,0.000450808,0.0020691515,0.00015008848,0.0000016009864],"category_scores_gemma":[0.000092681476,0.00018079816,0.000042385494,0.00040823573,0.00033494344,0.003170086,0.0012164976,0.0003398986,0.000005415652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033435617,0.000029927753,0.000001463627,0.00007441959,0.000002674896,4.7378552e-7,0.0053230566,0.015163195,0.000006375981,0.19824584,0.000038035545,0.7811112],"study_design_scores_gemma":[0.00035576485,0.000016621058,0.00012699947,0.00049861363,0.0000026931139,0.0000061467167,0.000033716708,0.9789911,0.000010764273,0.017290091,0.0024839947,0.00018352414],"about_ca_topic_score_codex":0.000027863245,"about_ca_topic_score_gemma":0.000010359046,"teacher_disagreement_score":0.96382785,"about_ca_system_score_codex":0.00018942768,"about_ca_system_score_gemma":0.00040981683,"threshold_uncertainty_score":0.7372735},"labels":[],"label_agreement":null},{"id":"W4410041753","doi":"10.1007/978-3-031-87569-4_7","title":"Mechanical Fault Prediction Based on Event Knowledge Graph and Deep Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Computer science; Artificial intelligence; Graph; Fault (geology); Deep learning; Event (particle physics); Knowledge graph; Natural language processing; Seismology; Theoretical computer science; Geology; Physics","score_opus":0.025151007975024415,"score_gpt":0.3208601102046934,"score_spread":0.295709102229669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410041753","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000060438456,0.00027991782,0.92028874,0.0003926907,0.00019512391,0.0003172514,0.0000046754094,0.00024258839,0.07827299],"genre_scores_gemma":[0.12546445,0.004075442,0.8681497,0.0011967268,0.00003303472,0.00008189907,0.000048224287,0.00001396336,0.0009365502],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825674,0.000063847285,0.00064735836,0.00038998734,0.00044585724,0.00019621797],"domain_scores_gemma":[0.99668986,0.00070686574,0.00028704308,0.0018315619,0.00039274333,0.00009194739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001295627,0.00022913842,0.00024058882,0.001597591,0.0006293906,0.00043548242,0.0023729154,0.00016579742,0.000002328006],"category_scores_gemma":[0.00019815358,0.00022668765,0.000048134243,0.00059421203,0.00045704786,0.0031775562,0.0026033637,0.00068311446,0.000011308422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002212552,0.000013779513,0.000007660421,0.000012498733,0.0000016215349,1.8177765e-7,0.00024852535,0.001135991,0.0000010903545,0.4631111,0.00007259691,0.53539276],"study_design_scores_gemma":[0.0001734362,0.000111339425,0.00023724447,0.00047269656,0.0000034971847,0.0000067929095,0.000005246009,0.8828638,0.000011628042,0.040994745,0.074938074,0.00018146398],"about_ca_topic_score_codex":0.0000019104518,"about_ca_topic_score_gemma":0.0000037833975,"teacher_disagreement_score":0.8817279,"about_ca_system_score_codex":0.00017793983,"about_ca_system_score_gemma":0.00019430387,"threshold_uncertainty_score":0.9244054},"labels":[],"label_agreement":null},{"id":"W4410462350","doi":"10.1007/978-3-031-88042-1_6","title":"Traffic Crash Severity Prediction Using eXplainable AI","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Crash; Computer science; Artificial intelligence; Operating system","score_opus":0.04871422867016001,"score_gpt":0.30994382602247306,"score_spread":0.26122959735231305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410462350","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022579225,0.00024178729,0.8547525,0.0011510085,0.00063012575,0.00053510675,0.000018272609,0.00020974567,0.1422357],"genre_scores_gemma":[0.21907538,0.007244972,0.7497322,0.008559199,0.00023970929,0.00015911668,0.0001930624,0.000045325512,0.014751056],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978498,0.000048150283,0.0008504817,0.00039846302,0.00050637807,0.0003466879],"domain_scores_gemma":[0.9962758,0.00019313696,0.00029713873,0.0024356763,0.00068465207,0.00011360704],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0013355829,0.0002569746,0.0002752978,0.0014064724,0.0009894116,0.0010775593,0.0037587837,0.00018172686,0.000010329616],"category_scores_gemma":[0.00007734248,0.00028547723,0.000057635163,0.00092479936,0.0007800149,0.013105939,0.0028216639,0.00057524524,0.000046020825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020496482,0.000026833663,0.000035865392,0.00005307792,0.000006439378,8.781449e-7,0.001990971,0.008420208,0.000006585501,0.7167402,0.0006420813,0.27207482],"study_design_scores_gemma":[0.00008340806,0.000030462435,0.00014583502,0.00022808556,0.0000053821345,0.00001766474,0.000038076694,0.9027919,0.000041565338,0.009873782,0.08650575,0.00023805273],"about_ca_topic_score_codex":0.00003677665,"about_ca_topic_score_gemma":0.000023588782,"teacher_disagreement_score":0.89437175,"about_ca_system_score_codex":0.0004198651,"about_ca_system_score_gemma":0.0007697685,"threshold_uncertainty_score":0.99995977},"labels":[],"label_agreement":null},{"id":"W4410494267","doi":"10.1007/978-3-031-90341-0_26","title":"Next Generation Imminent Fracture Risk Assessment Using AI","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Osteoporosis Canada; University of Guelph","funders":"Osteoporosis Canada","keywords":"Computer science; Fracture (geology); Risk analysis (engineering); Medicine; Engineering; Geotechnical engineering","score_opus":0.041862508260192346,"score_gpt":0.3197675467234106,"score_spread":0.2779050384632183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410494267","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001863754,0.00073223474,0.90736157,0.00072134106,0.00030399597,0.00015791623,0.000016530641,0.00008515064,0.09043491],"genre_scores_gemma":[0.48742825,0.040161822,0.46027333,0.0073503694,0.00042940705,0.000050677365,0.0010149013,0.00004001702,0.0032512231],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906796,0.000015551088,0.00043263414,0.00011048673,0.00025768747,0.000115663526],"domain_scores_gemma":[0.9988157,0.000060929306,0.000104545885,0.00077979115,0.00017954608,0.000059462833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048253266,0.00013772812,0.00016915929,0.00060979294,0.00029175245,0.00038722283,0.00058754184,0.00008711126,0.000019605479],"category_scores_gemma":[0.000022189817,0.00013308579,0.000036350786,0.00022679525,0.00023893618,0.0021938786,0.00029870315,0.0005088641,0.000008099198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.5857269e-7,0.00001896648,0.00035820884,0.00013080605,0.00005708659,4.1186544e-7,0.0011617178,0.1646159,0.00008055103,0.043496653,0.0073746783,0.7827046],"study_design_scores_gemma":[0.00006855797,0.000002771511,0.00014985538,0.00011530435,0.000018543278,0.0000017672741,0.000007769768,0.89151394,0.0000051632455,0.0003675351,0.107633345,0.00011545584],"about_ca_topic_score_codex":0.00002067963,"about_ca_topic_score_gemma":0.000003938067,"teacher_disagreement_score":0.78258914,"about_ca_system_score_codex":0.00016637037,"about_ca_system_score_gemma":0.00013196286,"threshold_uncertainty_score":0.54270816},"labels":[],"label_agreement":null},{"id":"W4410494511","doi":"10.1007/978-3-031-90341-0_13","title":"Assisting Personal Support Worker’s e-Training with AI Prediction","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Training (meteorology); Computer science; Artificial intelligence; Geography","score_opus":0.20920061779631988,"score_gpt":0.4618421721298551,"score_spread":0.25264155433353525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410494511","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029015073,0.0001595901,0.05307962,0.0046605524,0.0008962262,0.0012396658,0.00009651882,0.00017698194,0.9394007],"genre_scores_gemma":[0.76759464,0.0049281023,0.1262619,0.031100852,0.0009707935,0.0008604019,0.0014742163,0.00008843524,0.066720635],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978302,0.00008220545,0.0010455287,0.0002441513,0.00044435362,0.00035353928],"domain_scores_gemma":[0.99682385,0.0006893112,0.00046258478,0.00092546776,0.0009809036,0.0001178586],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0018572983,0.00019000396,0.00026056872,0.0008143956,0.0021736005,0.000107177424,0.0009003142,0.00024109826,0.00009544025],"category_scores_gemma":[0.0001703095,0.00017637537,0.00002809502,0.00039935432,0.0008992239,0.0026082995,0.0008802897,0.0015001267,0.000090091155],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026268073,0.00001353374,0.012786188,0.0002923599,0.000014017025,9.0793526e-7,0.04741348,0.0001530033,6.455607e-7,0.30007553,0.003584826,0.63563925],"study_design_scores_gemma":[0.00029768175,0.00016198152,0.008572954,0.0051571433,0.00002555228,0.0000151437225,0.0047974912,0.4903095,0.0000013140548,0.0049830377,0.4852105,0.00046769183],"about_ca_topic_score_codex":0.000087973196,"about_ca_topic_score_gemma":0.00027691407,"teacher_disagreement_score":0.87268007,"about_ca_system_score_codex":0.0004220625,"about_ca_system_score_gemma":0.0023387466,"threshold_uncertainty_score":0.9991254},"labels":[],"label_agreement":null},{"id":"W4410568955","doi":"10.1007/978-3-031-88762-8_17","title":"An Efficient Framework for Multi-level Lung Cancer Prediction Using Support Vector Machine Classifier","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Workplace Health, Safety and Compensation Commission","funders":"","keywords":"Support vector machine; Lung cancer; Classifier (UML); Computer science; Artificial intelligence; Machine learning; Oncology; Medicine","score_opus":0.3569091041819048,"score_gpt":0.5422085270092531,"score_spread":0.18529942282734835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410568955","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033529027,0.0004267819,0.984059,0.00091605994,0.0021328893,0.0025462527,0.0009909617,0.00010256817,0.008490206],"genre_scores_gemma":[0.10938503,0.003975916,0.8725523,0.006307063,0.0005947923,0.0012242765,0.0010645139,0.0000643245,0.0048318263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99757415,0.00010146159,0.0012821777,0.00031221297,0.00033880078,0.0003912221],"domain_scores_gemma":[0.99593693,0.0007077137,0.0005791161,0.0014560721,0.0011660603,0.00015412744],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0016113146,0.00022636293,0.00030439056,0.0007884545,0.0022378212,0.00009580805,0.001212158,0.00041999127,0.000079244346],"category_scores_gemma":[0.00022121251,0.00022598593,0.000049517777,0.0003393302,0.00056651,0.0014747523,0.0007106542,0.0011103428,0.000014646261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004576944,0.00007760755,0.007865355,0.0009368332,0.00002183145,1.788367e-7,0.017507073,0.007334737,0.0000090182275,0.7996489,0.0008404048,0.16571233],"study_design_scores_gemma":[0.00014164601,0.000037664664,0.0022236495,0.0012601169,0.000018552766,7.5305184e-7,0.00023055829,0.97254086,0.0000037457987,0.0011969223,0.02216046,0.00018508252],"about_ca_topic_score_codex":0.0003215181,"about_ca_topic_score_gemma":0.00038671447,"teacher_disagreement_score":0.9652061,"about_ca_system_score_codex":0.00084994343,"about_ca_system_score_gemma":0.0018470571,"threshold_uncertainty_score":0.9990611},"labels":[],"label_agreement":null},{"id":"W4410755212","doi":"10.1007/978-981-96-6403-0_13","title":"Credit Card Fraud Detection with Deep Multilayer Perceptrons","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Credit card fraud; Computer science; Perceptron; Artificial intelligence; Pattern recognition (psychology); Credit card; World Wide Web; Artificial neural network","score_opus":0.024203241766438035,"score_gpt":0.2779501540965774,"score_spread":0.2537469123301394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410755212","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008837164,0.00011144688,0.8507563,0.0005403141,0.00018549895,0.00042209102,0.000020714911,0.00026259827,0.14769223],"genre_scores_gemma":[0.09023021,0.0027784968,0.90117776,0.0017573115,0.00006387948,0.00019543705,0.00018339897,0.000018993196,0.0035944849],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981448,0.000036389756,0.00062270113,0.00041781107,0.00051854295,0.0002597569],"domain_scores_gemma":[0.99531,0.00018366694,0.0003541103,0.0034167103,0.00063914165,0.00009637507],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00071262376,0.0002707146,0.00026825172,0.0013924416,0.0005962783,0.00072320347,0.0040301937,0.00017707008,0.000006526879],"category_scores_gemma":[0.000050088976,0.00025546964,0.000041644118,0.0006741353,0.0008979049,0.007711813,0.002175189,0.00058502436,0.00004445492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038673866,0.000016911918,0.000031982792,0.000030690342,0.000008288445,3.418348e-7,0.0011368444,0.00011891975,0.000024390314,0.34962407,0.0005277798,0.64847594],"study_design_scores_gemma":[0.00032563327,0.000098007644,0.002070275,0.00026793854,0.000011266339,0.000029706063,0.000032933473,0.65899354,0.00019551718,0.0032683597,0.33421108,0.000495754],"about_ca_topic_score_codex":0.000023853474,"about_ca_topic_score_gemma":0.000057006986,"teacher_disagreement_score":0.6588746,"about_ca_system_score_codex":0.0002987038,"about_ca_system_score_gemma":0.00037170536,"threshold_uncertainty_score":0.99998975},"labels":[],"label_agreement":null},{"id":"W4410756277","doi":"10.1007/978-981-96-6403-0_7","title":"Federated Learning for Privacy-Preserving: Current Status and Future Directions","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Current (fluid); Computer science; Internet privacy; Electrical engineering; Engineering","score_opus":0.044961175579933475,"score_gpt":0.3191798376890676,"score_spread":0.27421866210913415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410756277","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004686389,0.0084124515,0.896807,0.02438019,0.00128275,0.0012174948,0.000060419537,0.00078600505,0.06700679],"genre_scores_gemma":[0.0037227822,0.120118864,0.8736363,0.000572658,0.00012498339,0.00022205073,0.00035230405,0.000021070504,0.0012289913],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99816936,0.000041471983,0.0006300858,0.00046633946,0.0003278748,0.00036485266],"domain_scores_gemma":[0.99275804,0.00048999494,0.00034409112,0.0057709734,0.00053382886,0.000103074875],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0009283905,0.00026829823,0.00028501116,0.0012894742,0.0012798929,0.0013554278,0.016670005,0.00018472702,0.0000030681515],"category_scores_gemma":[0.002476635,0.00027639818,0.000041547428,0.0007183928,0.00067468634,0.006322677,0.096656874,0.00083791296,0.000005000005],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020001055,0.00001137142,0.00007016623,0.00007298188,0.000007193235,6.499731e-8,0.00036079844,0.000009615946,8.0477514e-7,0.16654354,0.007300224,0.82562125],"study_design_scores_gemma":[0.00016084885,0.000024843677,0.00036265087,0.0001486043,0.0000040690707,0.000003213748,0.000014096062,0.40143946,0.0000033981632,0.03695085,0.5607129,0.00017507678],"about_ca_topic_score_codex":0.000012068733,"about_ca_topic_score_gemma":0.000011023158,"teacher_disagreement_score":0.8254461,"about_ca_system_score_codex":0.00019867434,"about_ca_system_score_gemma":0.0004357423,"threshold_uncertainty_score":0.9999688},"labels":[],"label_agreement":null},{"id":"W4410756393","doi":"10.1007/978-981-96-6403-0","title":"Machine Learning and Soft Computing","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universidad de Almería; Université Paris-Est Créteil Val-de-Marne; Jimei University; Nanjing University; Universiti Malaysia Kelantan; University of Surrey; Università degli Studi di Salerno; Jiangsu University; Simon Fraser University; Hunan University; University of Hong Kong; Jiangsu University of Science and Technology; Norges Teknisk-Naturvitenskapelige Universitet; Universiti Sains Malaysia; Universidad de Málaga; Universiti Tunku Abdul Rahman; Chongqing University of Technology; Chongqing University; Arkansas Tech University; Turun Yliopisto; City University of Hong Kong; Sun Yat-sen University; Iowa State University; Auburn University; Thammasat University; Mississippi State University","keywords":"Soft computing; Computer science; Artificial intelligence; Information retrieval; Artificial neural network","score_opus":0.021143988971010472,"score_gpt":0.29328640869955075,"score_spread":0.27214241972854025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410756393","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017897384,0.0016227659,0.819054,0.0019063421,0.00017561395,0.00034482087,0.0000061053292,0.00016124368,0.17671119],"genre_scores_gemma":[0.066566475,0.027964404,0.8594725,0.00785304,0.0002273798,0.00011387287,0.0003630589,0.00003083326,0.037408397],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866176,0.000048055885,0.0005106909,0.00030013185,0.00025049536,0.00022884173],"domain_scores_gemma":[0.9979408,0.0004153088,0.00024962056,0.0011008134,0.00020513691,0.00008833029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000791269,0.00018257227,0.000220502,0.00064721523,0.00088137516,0.0008637825,0.0023485024,0.000090137204,0.0000015185293],"category_scores_gemma":[0.000038910657,0.00018291257,0.000027177628,0.00087959575,0.00058503967,0.0031877093,0.0043485584,0.00061919034,0.000010304122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.0134083e-7,0.000008315857,0.00011095765,0.000028963334,0.0000025415698,1.3615814e-7,0.00052121986,0.00043200623,8.2683385e-7,0.35786816,0.0007357438,0.64029074],"study_design_scores_gemma":[0.000103868624,0.000013896583,0.00028246146,0.00012184317,0.0000022586592,0.0000100432035,0.000004156457,0.70129585,8.9797345e-7,0.0038073102,0.2942201,0.00013729709],"about_ca_topic_score_codex":0.000011495471,"about_ca_topic_score_gemma":0.0000057407274,"teacher_disagreement_score":0.70086384,"about_ca_system_score_codex":0.00008943518,"about_ca_system_score_gemma":0.00033794311,"threshold_uncertainty_score":0.83294743},"labels":[],"label_agreement":null},{"id":"W4410838966","doi":"10.1007/978-3-031-91328-0_12","title":"Exploring the Feasibility of Virtual Reality in Post-Stroke Rehabilitation: Medical Perspectives on Motion Health VR","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Virtual reality; Rehabilitation; Motion (physics); Physical medicine and rehabilitation; Stroke (engine); Human–computer interaction; Computer science; Medicine; Psychology; Physical therapy; Engineering; Artificial intelligence; Mechanical engineering","score_opus":0.10518270882350869,"score_gpt":0.3740958411309117,"score_spread":0.268913132307403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410838966","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17131425,0.0029597725,0.03382647,0.17584191,0.002534709,0.00935243,0.00045437264,0.00025033238,0.60346574],"genre_scores_gemma":[0.9843917,0.006526546,0.0064034746,0.0016287696,0.00004809581,0.00007358857,0.000088670706,0.000007137828,0.0008320173],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99787194,0.00014067866,0.0009430633,0.00023015593,0.0006762983,0.00013786383],"domain_scores_gemma":[0.99616337,0.0016017231,0.00028368822,0.0012792217,0.00058189343,0.00009011902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032520033,0.0001410788,0.00034672493,0.0010710562,0.00021138618,0.000040116214,0.0005495401,0.00009145226,0.000016227774],"category_scores_gemma":[0.0015207076,0.00010876896,0.00009249687,0.00038580952,0.0015447331,0.0012327866,0.00035934892,0.00060605723,0.0000044136173],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010229484,0.00020766664,0.0027561046,0.0002575475,0.000013798647,1.6525013e-7,0.02589068,0.00016326577,0.000002872137,0.38877192,0.00012259456,0.5817111],"study_design_scores_gemma":[0.0028553035,0.0028335592,0.8938049,0.005108222,0.000026319092,0.000027150003,0.016782006,0.05339857,0.000011198546,0.0028284257,0.021860715,0.00046360193],"about_ca_topic_score_codex":0.00007378794,"about_ca_topic_score_gemma":0.000063688945,"teacher_disagreement_score":0.89104885,"about_ca_system_score_codex":0.0005282687,"about_ca_system_score_gemma":0.0010409015,"threshold_uncertainty_score":0.5691633},"labels":[],"label_agreement":null},{"id":"W4410930579","doi":"10.1007/978-3-031-94263-1_24","title":"Intelligent Vehicle Detection System","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science","score_opus":0.02265439359405384,"score_gpt":0.2415711221528082,"score_spread":0.21891672855875438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410930579","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005224402,0.0004725981,0.33873835,0.000071216265,0.00063424563,0.00042092268,0.000021284075,0.0004063673,0.65871257],"genre_scores_gemma":[0.974487,0.004752163,0.019557329,0.00018621977,0.00005941443,0.000054200722,0.000100926394,0.000019203213,0.0007835369],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918824,0.00000897068,0.00041874105,0.000098028104,0.00016697113,0.00011905459],"domain_scores_gemma":[0.9989753,0.00008134451,0.000072744384,0.0006595261,0.00016768494,0.000043416607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034152213,0.00012817579,0.00013634513,0.00075196574,0.00023010325,0.00024311626,0.0005385329,0.000110247514,0.000003761722],"category_scores_gemma":[0.000009037191,0.00014464252,0.000024022169,0.00023983433,0.00023534539,0.0018002732,0.00032114825,0.0003095023,0.00007004364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014135734,0.000003046779,0.0000048767006,0.00019443937,0.00000780575,1.5773387e-7,0.00046123535,0.003374531,0.000027510776,0.069997296,0.00006190867,0.92586577],"study_design_scores_gemma":[0.00008234672,0.000009611805,0.00010472474,0.00038230538,0.0000063963307,0.000010520061,0.000029684172,0.9465513,0.00023959848,0.0003571561,0.052078206,0.00014814272],"about_ca_topic_score_codex":0.000005737298,"about_ca_topic_score_gemma":0.00001226317,"teacher_disagreement_score":0.9739646,"about_ca_system_score_codex":0.00030955995,"about_ca_system_score_gemma":0.000057681926,"threshold_uncertainty_score":0.58983505},"labels":[],"label_agreement":null},{"id":"W4410930600","doi":"10.1007/978-3-031-94263-1_14","title":"A Multi-modal Data-Driven Dashboard for Enhanced Public Health Surveillance and Awareness","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; University of Windsor","funders":"","keywords":"Dashboard; Modal; Computer science; Health surveillance; Data science; World Wide Web; Environmental health; Medicine; Chemistry","score_opus":0.19498318016887187,"score_gpt":0.4068680692607934,"score_spread":0.21188488909192152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410930600","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027161262,0.0011282051,0.9463596,0.0062658833,0.0005768976,0.0022626086,0.0003056892,0.00025403334,0.040131003],"genre_scores_gemma":[0.39579445,0.0039136093,0.5812789,0.015882313,0.00011866416,0.0001620781,0.0014361925,0.00002963333,0.0013841414],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873793,0.000025351394,0.0005648095,0.00027489103,0.00020076663,0.00019625039],"domain_scores_gemma":[0.99727714,0.00032704772,0.00029228374,0.0015597102,0.00046406823,0.00007972361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011960223,0.00015459,0.00031796767,0.00066603336,0.0005053392,0.00022561672,0.00082656025,0.00008567204,0.0000013308643],"category_scores_gemma":[0.00031915007,0.00015272704,0.000024384348,0.00027698188,0.0005383632,0.0016598091,0.0012193588,0.00026937784,0.0000033410408],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002438738,0.00006989527,0.0010337522,0.00061321876,0.00003571569,2.408531e-7,0.0024608762,0.00002661933,0.00020995374,0.025851822,0.00066879205,0.96900475],"study_design_scores_gemma":[0.0011999817,0.00008692031,0.0027420595,0.00044301848,0.000006948482,0.00002522569,0.00004290778,0.75165033,0.00005248542,0.00013739301,0.24340616,0.00020656426],"about_ca_topic_score_codex":0.000029146833,"about_ca_topic_score_gemma":0.00010299953,"teacher_disagreement_score":0.96879816,"about_ca_system_score_codex":0.00012242665,"about_ca_system_score_gemma":0.0009198421,"threshold_uncertainty_score":0.6228028},"labels":[],"label_agreement":null},{"id":"W4411025202","doi":"10.1007/978-981-96-6459-7_27","title":"Machine Learning for Dynamic Spectrum Allocation in 6G Non-Terrestrial Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Computer science; Spectrum (functional analysis); Artificial intelligence; Physics","score_opus":0.013304028183902732,"score_gpt":0.2594240746086023,"score_spread":0.24612004642469956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411025202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008469975,0.0005089683,0.967278,0.00009803227,0.00041441646,0.00067063514,0.000007602468,0.00007874654,0.030935127],"genre_scores_gemma":[0.8317917,0.020794071,0.1411862,0.00022954457,0.00015518593,0.00034571474,0.0020207982,0.00006374998,0.0034130309],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989411,0.000012563339,0.0006205263,0.00014248707,0.00010889843,0.00017438183],"domain_scores_gemma":[0.9989754,0.0001662472,0.00015062212,0.0005988895,0.00007526744,0.00003359898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005105906,0.00017026819,0.00021333488,0.0008880282,0.00017930612,0.0001424578,0.0006467001,0.0001340206,0.000001914287],"category_scores_gemma":[0.000030584535,0.00019885521,0.000027696247,0.00032186636,0.00014954747,0.0019252644,0.00026698833,0.0004103896,0.0000036967704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003587071,0.0000028358838,0.000019159479,0.000042584943,0.0000029820671,4.0882213e-8,0.0002617402,0.9380246,7.746454e-7,0.00981787,0.000028808714,0.051795006],"study_design_scores_gemma":[0.0003819913,0.000017492652,0.0000907573,0.00029496002,0.000003838163,0.0000018963993,0.000008422398,0.983833,0.0000014300782,0.0007237153,0.014473244,0.0001692416],"about_ca_topic_score_codex":0.000011778814,"about_ca_topic_score_gemma":0.000100825804,"teacher_disagreement_score":0.83178324,"about_ca_system_score_codex":0.00030988947,"about_ca_system_score_gemma":0.00007899461,"threshold_uncertainty_score":0.810908},"labels":[],"label_agreement":null},{"id":"W4411026514","doi":"10.1007/978-981-96-6459-7_3","title":"Interference Study of 5G Network Deployment on Meteorological Satellite System in 1800 MHz Band","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Software deployment; Satellite; Interference (communication); Telecommunications; Computer science; Remote sensing; Meteorology; Environmental science; Astronomy; Physics; Geography","score_opus":0.03994362441390055,"score_gpt":0.26858604880384657,"score_spread":0.22864242438994603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411026514","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045871325,0.0045148456,0.03218384,0.00031330835,0.0008249252,0.0030471089,0.00004345636,0.0012744991,0.9119267],"genre_scores_gemma":[0.9860191,0.002957973,0.010855732,0.000032268097,0.0000058332184,0.000048118127,0.00001254414,0.0000054723787,0.00006297873],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868596,0.000035397417,0.000785053,0.000147811,0.00017718106,0.00016858033],"domain_scores_gemma":[0.99773383,0.00031829343,0.0001582115,0.0016465292,0.00011713618,0.00002597827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072249316,0.00018041083,0.00030938495,0.00086292217,0.00014580504,0.00009733895,0.0018517672,0.0001257989,0.0000018302222],"category_scores_gemma":[0.000032711687,0.0001678426,0.000023837463,0.00048740467,0.00034875434,0.0005598749,0.00079721364,0.00051533966,0.000005375062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016530972,0.00014505882,0.0014351129,0.00023475123,0.000035443827,7.1971544e-7,0.003099281,0.06100524,0.000006936607,0.25920305,0.00018370524,0.67463416],"study_design_scores_gemma":[0.0015083445,0.0010157119,0.035458397,0.004880595,0.00004431683,0.000017184366,0.0014786473,0.88727474,0.00006682514,0.0037780944,0.0634258,0.0010513221],"about_ca_topic_score_codex":0.000015562739,"about_ca_topic_score_gemma":0.000068310284,"teacher_disagreement_score":0.94014776,"about_ca_system_score_codex":0.00018657502,"about_ca_system_score_gemma":0.00004421504,"threshold_uncertainty_score":0.6844423},"labels":[],"label_agreement":null},{"id":"W4411026794","doi":"10.1007/978-981-96-6459-7_1","title":"An Energy-Efficient WSN Routing Protocol Using Genetic Algorithms and Predictive Coding","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; École de Technologie Supérieure","funders":"","keywords":"Computer science; Coding (social sciences); Routing algorithm; Algorithm; Routing protocol; Routing (electronic design automation); Computer network; Mathematics; Statistics","score_opus":0.024148088330016537,"score_gpt":0.2907780321442811,"score_spread":0.2666299438142646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411026794","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014191924,0.00007326852,0.96833956,0.000006926387,0.000103054765,0.004617065,0.000017263059,0.00009573295,0.026732951],"genre_scores_gemma":[0.09444424,0.00077259913,0.89889824,0.00016316235,0.00010531737,0.005162538,0.00012726853,0.00004480924,0.00028180494],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897265,0.000018005681,0.0005261885,0.00016535245,0.00016460981,0.00015317815],"domain_scores_gemma":[0.99878913,0.00006514567,0.0001550642,0.00071568554,0.00021225179,0.00006274598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003249046,0.00017393696,0.00017377659,0.0006142051,0.00035187093,0.00023945095,0.00052788033,0.00009721385,0.0000014040862],"category_scores_gemma":[0.000012613736,0.00019189843,0.000014122289,0.00024363917,0.00030200023,0.0017982785,0.00042120516,0.00019981443,7.4272407e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001329791,0.0000048081138,0.00001558457,0.00007158439,0.000004324549,1.0811353e-7,0.00096539286,0.8874468,0.000010966121,0.023608455,0.000006875001,0.087863766],"study_design_scores_gemma":[0.00017201519,0.000018593428,0.000081814265,0.00041360216,0.000005412199,0.00000956949,0.00003647741,0.99611056,0.000015881107,0.00023768908,0.0027248708,0.00017351679],"about_ca_topic_score_codex":0.000007377925,"about_ca_topic_score_gemma":0.0000021747965,"teacher_disagreement_score":0.10866375,"about_ca_system_score_codex":0.00021830139,"about_ca_system_score_gemma":0.000091985996,"threshold_uncertainty_score":0.7825391},"labels":[],"label_agreement":null},{"id":"W4411075542","doi":"10.1007/978-3-031-94150-4_28","title":"A Mixed Methods Evaluation of Telehealth Care for Rural Oncology Patients in New Brunswick, Canada","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Horizon Health Network; Dr. Everett Chalmers Regional Hospital","funders":"","keywords":"Telehealth; Medicine; Oncology; Internal medicine; Family medicine; Telemedicine; Political science; Health care","score_opus":0.09433940555135693,"score_gpt":0.4543808859393998,"score_spread":0.36004148038804284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411075542","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.075142376,0.011198252,0.27319267,0.03139059,0.007180194,0.038892183,0.0005732638,0.00016703586,0.5622634],"genre_scores_gemma":[0.37936652,0.0044013206,0.60318,0.0074600624,0.00011463043,0.0001644072,0.0041966233,0.000025428428,0.0010910032],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980987,0.00008381567,0.0010282913,0.00013170151,0.00047998235,0.00017753242],"domain_scores_gemma":[0.99704283,0.00040651343,0.00047289292,0.0006075057,0.0013689568,0.00010131384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019203166,0.00012857479,0.00037477957,0.000882329,0.00013144687,0.000015520494,0.00036021761,0.000097680146,0.000009012028],"category_scores_gemma":[0.00029463173,0.00012707322,0.000026434713,0.00033041943,0.00017800856,0.0005605114,0.00022358303,0.00024128896,3.7266875e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021648682,0.000015104559,0.002949488,0.00024396516,0.0000051483116,2.655977e-8,0.0020975207,0.000023136938,4.183469e-7,0.022147182,0.0013699405,0.97112644],"study_design_scores_gemma":[0.009356226,0.0008983198,0.36171415,0.0013452291,0.00015226833,0.000006405169,0.0021316656,0.08425287,0.000033727938,0.0017801041,0.53801554,0.0003134842],"about_ca_topic_score_codex":0.08668657,"about_ca_topic_score_gemma":0.40710366,"teacher_disagreement_score":0.9708129,"about_ca_system_score_codex":0.0012650372,"about_ca_system_score_gemma":0.02725672,"threshold_uncertainty_score":0.97825783},"labels":[],"label_agreement":null},{"id":"W4411075654","doi":"10.1007/978-3-031-94150-4_39","title":"Fitness-Based Recommender Systems for Reducing Sedentary Behaviour","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Recommender system; Computer science; Information retrieval","score_opus":0.10665176706398412,"score_gpt":0.44775660204459217,"score_spread":0.34110483498060806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411075654","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000083907,0.0032750096,0.35745984,0.01601399,0.004231026,0.018863225,0.00090524787,0.0003565379,0.5988112],"genre_scores_gemma":[0.0799617,0.08848693,0.45745862,0.10729227,0.0020286562,0.102975525,0.015425458,0.0002712275,0.14609961],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973623,0.00009100085,0.0015097816,0.0003108719,0.00027347472,0.00045253916],"domain_scores_gemma":[0.9951927,0.0012618654,0.0007092768,0.0017991298,0.0008230861,0.00021393641],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002365026,0.00022477677,0.0003723502,0.0010580285,0.0023891488,0.000088385714,0.0012406991,0.00030215585,0.0000324804],"category_scores_gemma":[0.000097701326,0.00023283734,0.000051843544,0.00032415582,0.00038658723,0.0011805652,0.00063886034,0.0008668913,0.00004251066],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029240251,0.000051206433,0.00089158973,0.002206273,0.000008953756,7.469264e-8,0.0013291191,0.00076244987,4.2255922e-7,0.7314981,0.0625561,0.20066646],"study_design_scores_gemma":[0.00068091607,0.000038595706,0.00082004425,0.001327738,0.000016374928,9.66938e-7,0.0001255367,0.1429477,3.4388108e-7,0.0011420031,0.85270256,0.00019725416],"about_ca_topic_score_codex":0.0002115514,"about_ca_topic_score_gemma":0.000040886523,"teacher_disagreement_score":0.7901464,"about_ca_system_score_codex":0.0005513579,"about_ca_system_score_gemma":0.002562029,"threshold_uncertainty_score":0.9989096},"labels":[],"label_agreement":null},{"id":"W4411103953","doi":"10.1007/978-3-031-94159-7_33","title":"The Interplay of Trust in Automation, Attentional Capacity, and Situation Awareness in the Age of Vehicle Automation","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Automation; Computer science; Psychology; Data science; Engineering; Mechanical engineering","score_opus":0.047264152759178585,"score_gpt":0.37300403963561674,"score_spread":0.3257398868764382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411103953","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19089964,0.00075957755,0.08237076,0.00830686,0.0019570268,0.0032592858,0.00014495518,0.00013100092,0.7121709],"genre_scores_gemma":[0.9970849,0.0003384414,0.0013831065,0.00028606885,0.000011238794,0.00006156818,0.00011835741,0.000003797143,0.000712498],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9981041,0.00016828188,0.0011359927,0.00014708226,0.00032833102,0.00011623472],"domain_scores_gemma":[0.997573,0.00077626115,0.0005303909,0.0007867425,0.0003161545,0.000017433937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021409092,0.00012750817,0.0002051049,0.0009701193,0.00027387048,0.00013308246,0.0008943929,0.000112605434,0.00003415279],"category_scores_gemma":[0.00010789736,0.000099977704,0.000036401965,0.00045194925,0.0008639684,0.0013748377,0.00029655156,0.00032507477,0.00000813673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015623596,0.000062646235,0.0034320178,0.00006907,0.000010784189,1.7183247e-7,0.02514375,0.00026997988,0.000012986354,0.901457,0.0003314075,0.06919453],"study_design_scores_gemma":[0.0009031588,0.000055686232,0.67423725,0.00065377593,0.0000115360845,0.000014506719,0.0015340738,0.28858575,0.0000101709675,0.011187874,0.022605848,0.00020034295],"about_ca_topic_score_codex":0.000113718845,"about_ca_topic_score_gemma":0.00038259014,"teacher_disagreement_score":0.89026916,"about_ca_system_score_codex":0.00010247367,"about_ca_system_score_gemma":0.00013601859,"threshold_uncertainty_score":0.40769726},"labels":[],"label_agreement":null},{"id":"W4411104928","doi":"10.1007/978-3-031-94159-7_41","title":"Enhancing Driver Takeover Performance in Conditionally Automated Vehicles: Effects of Warning Presentation Within the Vehicle Interface","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Presentation (obstetrics); Interface (matter); Computer science; Warning system; Telecommunications; Operating system; Medicine","score_opus":0.020861871207579357,"score_gpt":0.3454411338123311,"score_spread":0.32457926260475173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411104928","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13812183,0.00074847596,0.046035085,0.0018375994,0.0033610684,0.0029667884,0.000055004377,0.00050321117,0.8063709],"genre_scores_gemma":[0.994162,0.00016587423,0.0016602544,0.000463413,0.000014591873,0.0000560853,0.000055053075,0.0000062625722,0.0034164202],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983516,0.000105502266,0.0009207772,0.000180227,0.00030053122,0.00014140952],"domain_scores_gemma":[0.99755543,0.00073821616,0.0005678082,0.0007833178,0.00032243374,0.000032772823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008700602,0.00015785878,0.00021173667,0.00080717565,0.00029669073,0.00011626499,0.0008790949,0.00011794246,0.000074705196],"category_scores_gemma":[0.000091338705,0.0001404646,0.00003647959,0.00036593148,0.00063373265,0.0021068836,0.00042362267,0.00050442707,0.000070557086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009156809,0.00017380186,0.0036037022,0.0006571456,0.00009937738,0.0000013804822,0.10508923,0.012135821,0.00038921623,0.80159724,0.0026871122,0.0734744],"study_design_scores_gemma":[0.0013022451,0.00010318074,0.18282022,0.002026085,0.000020448566,0.000013210043,0.00073056115,0.7910587,0.0005376503,0.0008073156,0.020235144,0.00034523875],"about_ca_topic_score_codex":0.000029189301,"about_ca_topic_score_gemma":0.00003601983,"teacher_disagreement_score":0.85604024,"about_ca_system_score_codex":0.00015313379,"about_ca_system_score_gemma":0.00018420546,"threshold_uncertainty_score":0.572798},"labels":[],"label_agreement":null},{"id":"W4411105431","doi":"10.1007/978-3-031-94159-7_24","title":"Helpful but Terrifying: Older Adults’ Perspectives of AI in Remote Healthcare Technology","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Research and Productivity Council; Carleton University","funders":"","keywords":"Health care; Computer science; Medicine; Psychology; Political science","score_opus":0.02274721390515398,"score_gpt":0.3323836813246205,"score_spread":0.3096364674194665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411105431","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0108797755,0.010575319,0.031492386,0.16225365,0.0010003825,0.004494851,0.000116424635,0.0008668752,0.7783203],"genre_scores_gemma":[0.9470504,0.01187145,0.037574224,0.0010079037,0.00002764333,0.000030534546,0.000025340609,0.000010499935,0.0024020283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983265,0.00005553885,0.0007139401,0.00027559165,0.00034966928,0.0002787681],"domain_scores_gemma":[0.9974141,0.00014229998,0.00033243504,0.001326594,0.0007298845,0.00005467215],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009793126,0.00016881163,0.00031698745,0.003111035,0.00046295158,0.000081732986,0.0023481539,0.00042497256,0.0000071329064],"category_scores_gemma":[0.00026943078,0.00018784041,0.000037710754,0.0011717085,0.003823883,0.0018132619,0.0012462663,0.00088321173,0.0000073489364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038969433,0.000017728422,0.00064175646,0.000057871646,0.000003305591,2.8475765e-7,0.034181178,0.0000031840261,6.417264e-7,0.67169595,0.000069354035,0.29332486],"study_design_scores_gemma":[0.004868419,0.00041955878,0.045223776,0.019060934,0.000048470993,0.000042073905,0.124953866,0.07026995,0.00012936567,0.20820455,0.5241506,0.002628409],"about_ca_topic_score_codex":0.0010458031,"about_ca_topic_score_gemma":0.002321034,"teacher_disagreement_score":0.9361706,"about_ca_system_score_codex":0.0003520849,"about_ca_system_score_gemma":0.0009515594,"threshold_uncertainty_score":0.9988871},"labels":[],"label_agreement":null},{"id":"W4411113979","doi":"10.1007/978-3-031-94153-5_4","title":"A Comparison of Pilot Situation Awareness in Virtual Reality Flight Simulation and an Online Cognitive Health Screening Tool","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Virtual reality; Cognition; Computer science; Human–computer interaction; Psychology; Psychiatry","score_opus":0.2568864280036301,"score_gpt":0.5086262141737519,"score_spread":0.25173978617012177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411113979","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021193735,0.00035712673,0.8919252,0.0014944925,0.00059638143,0.0016559106,0.00033934898,0.00012845635,0.08230933],"genre_scores_gemma":[0.99476916,0.00017019636,0.0032524986,0.0005523197,0.000021187901,0.000019509785,0.00079475465,0.0000053183608,0.00041504356],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978642,0.0001778292,0.0012868296,0.00024607996,0.00027921118,0.00014585508],"domain_scores_gemma":[0.99744207,0.0006164348,0.0007135907,0.00067731546,0.0004887463,0.00006185142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012869562,0.00016908198,0.00037030887,0.0012311782,0.00032987588,0.00011211045,0.0004431051,0.00011139093,0.000046845027],"category_scores_gemma":[0.00009512667,0.00018616664,0.000023691351,0.00033914807,0.00047778798,0.002407554,0.00033998716,0.00039698876,0.000005807172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000112607166,0.00028371005,0.003280821,0.000077929944,0.000017105005,1.2102872e-7,0.028328462,0.011642074,0.0000015780714,0.2346529,0.00011952572,0.7214832],"study_design_scores_gemma":[0.00081667455,0.00025773857,0.11554538,0.0006003998,0.0000073934502,0.0000020926554,0.0010266388,0.8758594,0.0000014998974,0.000523944,0.005171476,0.00018741592],"about_ca_topic_score_codex":0.0001796844,"about_ca_topic_score_gemma":0.0004286885,"teacher_disagreement_score":0.9735754,"about_ca_system_score_codex":0.00012322358,"about_ca_system_score_gemma":0.00024184118,"threshold_uncertainty_score":0.7591655},"labels":[],"label_agreement":null},{"id":"W4411214024","doi":"10.1007/978-981-96-6468-9_11","title":"Dynamic Load Balancing with Agent-Based Algorithm in Cloud Computing via OpenStack","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Cloud computing; Parallel computing; Load balancing (electrical power); Distributed computing; Operating system; Mathematics","score_opus":0.014418837061744374,"score_gpt":0.25093299774780276,"score_spread":0.23651416068605838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411214024","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034712083,0.0013077931,0.9044277,0.00035073693,0.00021860487,0.0005178535,0.000023474275,0.00046990937,0.092336774],"genre_scores_gemma":[0.19860817,0.0026380068,0.7980215,0.0002632057,0.00001010418,0.000030059908,0.0001304614,0.000021341357,0.0002771686],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987334,0.000016105452,0.0006020228,0.00017191013,0.00023954976,0.00023703692],"domain_scores_gemma":[0.99777925,0.00020455512,0.00014628646,0.0016215418,0.00021154454,0.000036793892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063513726,0.00022598772,0.0002664711,0.0010227741,0.0002781001,0.0002392917,0.0018820268,0.00013785527,0.0000032399969],"category_scores_gemma":[0.000022830303,0.00022720799,0.000025163854,0.0006375543,0.0005703016,0.0011495927,0.0010189757,0.00066578673,0.000010884181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014503613,0.000011059138,0.00006371602,0.000067892266,0.0000063319703,5.923465e-7,0.0003826393,0.026134066,0.0000025972756,0.006194837,0.00010223933,0.96703255],"study_design_scores_gemma":[0.00028351822,0.000021299098,0.0005058173,0.0007147146,0.000004540357,0.000008004095,0.00003813694,0.97452074,0.000006735515,0.00037921872,0.023271326,0.00024594378],"about_ca_topic_score_codex":0.000029083885,"about_ca_topic_score_gemma":0.000112489564,"teacher_disagreement_score":0.9667866,"about_ca_system_score_codex":0.00050539785,"about_ca_system_score_gemma":0.00024410406,"threshold_uncertainty_score":0.92652726},"labels":[],"label_agreement":null},{"id":"W4411215333","doi":"10.1007/978-981-96-6468-9_25","title":"Optimizing Remote Medical Services with AloT: Integration of Large Language Models and 6G Edge Computing","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Data and IoT Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; York University","funders":"","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Artificial intelligence","score_opus":0.018780148097281516,"score_gpt":0.2868294432917256,"score_spread":0.2680492951944441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411215333","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00063861057,0.0013569051,0.9463303,0.00009691774,0.00005472524,0.00016156302,0.00002891866,0.00014927148,0.05118276],"genre_scores_gemma":[0.4098306,0.012529314,0.57688725,0.00031018717,0.000018322238,0.000004278035,0.00027623633,0.000013881813,0.00012990535],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922055,0.000005867895,0.00035700458,0.00010396431,0.0002001867,0.00011240655],"domain_scores_gemma":[0.99901307,0.00009428047,0.00010355683,0.0006435517,0.00011305936,0.000032511096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033831835,0.00012621078,0.00018287,0.00047311655,0.00013660765,0.00007727075,0.00074881327,0.000111918605,0.0000014960798],"category_scores_gemma":[0.000015553756,0.00011117072,0.00001100415,0.00019511189,0.0003729572,0.0022685113,0.00084895035,0.00031582927,8.0519413e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027722922,0.000005238369,0.0000075492862,0.00027461658,0.000010226482,3.7899613e-7,0.0052083847,0.009939187,0.000014269572,0.19017515,0.00003784225,0.7943244],"study_design_scores_gemma":[0.0001551862,0.000014725195,0.000037103615,0.00096710265,0.000004460786,0.0000064485107,0.00029237173,0.99407774,0.00004292726,0.001131392,0.0031582443,0.00011229354],"about_ca_topic_score_codex":0.000010177369,"about_ca_topic_score_gemma":0.00003831777,"teacher_disagreement_score":0.98413855,"about_ca_system_score_codex":0.00003655165,"about_ca_system_score_gemma":0.00004855047,"threshold_uncertainty_score":0.45334104},"labels":[],"label_agreement":null},{"id":"W4411215599","doi":"10.1007/978-981-96-6468-9_24","title":"Network Coding Techniques for Efficient Wireless Multimedia Delivery","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Multimedia; Computer science; Coding (social sciences); Wireless; Wireless network; Computer network; Telecommunications; Mathematics","score_opus":0.04550527261447342,"score_gpt":0.3026959437784698,"score_spread":0.2571906711639964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411215599","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007490321,0.0010139011,0.8828248,0.001350012,0.00036244895,0.0008806781,0.0000117199,0.00019946518,0.11334951],"genre_scores_gemma":[0.03284025,0.022217497,0.9368595,0.0042573735,0.00014918322,0.00031924885,0.0001407919,0.000019825913,0.0031963259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981508,0.00005360973,0.00079193816,0.00035573443,0.0003194544,0.00032846394],"domain_scores_gemma":[0.9954054,0.0007877215,0.0003557838,0.002509838,0.0008451404,0.00009614452],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016913204,0.00027036358,0.00033242532,0.00086637394,0.0010721404,0.00068100065,0.004623916,0.00015398284,0.0000036166944],"category_scores_gemma":[0.00006569663,0.00028288877,0.000070433896,0.0006707864,0.00066735543,0.0023447631,0.0043958584,0.0004566887,0.000010912151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017694153,0.000008396678,0.000004346822,0.000018438026,0.0000036189213,6.078739e-8,0.00040869313,0.00025235632,0.0000029438158,0.539113,0.0011115267,0.45907485],"study_design_scores_gemma":[0.00019224634,0.00002828668,0.0000655204,0.0004903066,0.000005277537,0.0000032253147,0.000005899502,0.80093884,0.000021302712,0.0026421924,0.19534086,0.000266047],"about_ca_topic_score_codex":0.0000026745106,"about_ca_topic_score_gemma":0.00001057927,"teacher_disagreement_score":0.8006865,"about_ca_system_score_codex":0.00022714915,"about_ca_system_score_gemma":0.00044303408,"threshold_uncertainty_score":0.99996233},"labels":[],"label_agreement":null},{"id":"W4411215803","doi":"10.1007/978-981-96-6468-9_17","title":"Spectrum Sharing Techniques for Wireless Multimedia Services","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Wireless; Computer science; Spectrum (functional analysis); Multimedia; World Wide Web; Telecommunications; Physics","score_opus":0.03567583280132052,"score_gpt":0.32469991496783807,"score_spread":0.28902408216651754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411215803","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000013238906,0.00060331414,0.8061232,0.0033023402,0.00023289712,0.001208367,0.000021823991,0.00030453995,0.18819027],"genre_scores_gemma":[0.025947876,0.013944684,0.9501483,0.0019816547,0.00011711494,0.0005050205,0.00024592507,0.000028415001,0.007081011],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782884,0.00003305233,0.00082341465,0.00044046176,0.0004987171,0.00037548982],"domain_scores_gemma":[0.99379563,0.00060549896,0.00036761974,0.004513318,0.00059972156,0.00011822526],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001712838,0.00027182235,0.00033313013,0.0016338176,0.00075423624,0.0012396419,0.011259423,0.00019759517,0.000003967951],"category_scores_gemma":[0.000029845214,0.00028736168,0.000068834546,0.000706752,0.00075608096,0.0064740353,0.0090515325,0.0006213007,0.000018166978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020418624,0.000011379047,0.000028267983,0.00008240341,0.000005411693,8.7559165e-8,0.0005864664,0.000041649582,0.0000021723522,0.6028405,0.00019559468,0.39620405],"study_design_scores_gemma":[0.00018368261,0.000028770106,0.00015779036,0.000496966,0.0000032161595,0.0000042441966,0.000010106941,0.8447127,0.000050871753,0.015988166,0.13810365,0.00025984625],"about_ca_topic_score_codex":0.000023192453,"about_ca_topic_score_gemma":0.000054926484,"teacher_disagreement_score":0.8446711,"about_ca_system_score_codex":0.00024108571,"about_ca_system_score_gemma":0.0004022134,"threshold_uncertainty_score":0.99995786},"labels":[],"label_agreement":null},{"id":"W4411617655","doi":"10.1007/978-981-96-6954-7_9","title":"An Innovative Approach to Detection of Steep Changes in Images","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence; Information retrieval; Remote sensing; Geology","score_opus":0.029235818374849603,"score_gpt":0.29909874477732046,"score_spread":0.26986292640247084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411617655","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006980056,0.000048953945,0.85670054,0.00036262302,0.000051710223,0.0005175125,0.000011934992,0.00007652679,0.14216039],"genre_scores_gemma":[0.4784038,0.0008691462,0.51862967,0.00094706967,0.00002080482,0.00026285578,0.000035428413,0.000008328909,0.00082289445],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987163,0.000029298462,0.00056486006,0.00029020628,0.00024821135,0.00015115121],"domain_scores_gemma":[0.99732715,0.00007804625,0.0002791516,0.0017421866,0.00051584194,0.00005760442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008243514,0.00015965958,0.00022693966,0.0022739966,0.00020170468,0.00021160053,0.0024966844,0.00011063971,9.851334e-7],"category_scores_gemma":[0.000023855106,0.0001690122,0.000019789288,0.0019328496,0.0003682675,0.002988494,0.0012752522,0.00030118495,0.0000035943567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017626184,0.00003497341,0.000017886307,0.000025113863,0.0000018713392,2.7843592e-8,0.0013708434,0.00015294275,0.00017325288,0.49889913,0.000027912361,0.49929428],"study_design_scores_gemma":[0.00054977584,0.00049283233,0.008967113,0.00055292214,0.000008052449,0.000018570141,0.00020490542,0.8348709,0.007631438,0.01754314,0.12818775,0.00097260193],"about_ca_topic_score_codex":0.00003745024,"about_ca_topic_score_gemma":0.000034566565,"teacher_disagreement_score":0.8347179,"about_ca_system_score_codex":0.00013133166,"about_ca_system_score_gemma":0.00017159349,"threshold_uncertainty_score":0.6892117},"labels":[],"label_agreement":null},{"id":"W4411653785","doi":"10.1007/978-3-031-92178-0_13","title":"Comparative Analysis of Machine Learning Classifiers for Yellow Fever Diagnosis Using Causative Data: Evaluating Naïve Bayes, KNN, RIPPER, and PART","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Royal University","funders":"","keywords":"Naive Bayes classifier; Artificial intelligence; Bayes' theorem; Computer science; Machine learning; Natural language processing; Support vector machine; Bayesian probability","score_opus":0.1741703264378278,"score_gpt":0.40548663044278616,"score_spread":0.23131630400495837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411653785","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021646282,0.00054017716,0.9875008,0.0002839173,0.00007648255,0.00070847676,0.00019559494,0.00006375214,0.010414359],"genre_scores_gemma":[0.13345912,0.0062064705,0.8577514,0.0004790959,0.000029557603,0.00024388416,0.0006749506,0.000010496087,0.0011449864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982214,0.00006630707,0.0007960021,0.0004324037,0.00030883704,0.00017506316],"domain_scores_gemma":[0.9960522,0.0008018469,0.0006906478,0.0017687819,0.0006177968,0.00006873293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015122986,0.00020997913,0.00048066612,0.0014249937,0.0007751106,0.00031060178,0.0020614418,0.00011140928,0.0000050406306],"category_scores_gemma":[0.000096294156,0.00021397845,0.00006883806,0.001259647,0.0007887841,0.0032566395,0.0026275807,0.00033762679,8.3309584e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001165968,0.00006191009,0.0014163285,0.0001162938,0.00037252912,1.14802035e-7,0.0057673757,0.005970528,0.00002407857,0.58771574,0.0006110482,0.3979324],"study_design_scores_gemma":[0.00015375981,0.0000614968,0.000562798,0.00013273938,0.00013690707,0.0000015422531,0.00006688279,0.9544766,0.00003225941,0.0013164626,0.04286266,0.00019592402],"about_ca_topic_score_codex":0.00007343607,"about_ca_topic_score_gemma":0.000058073187,"teacher_disagreement_score":0.94850606,"about_ca_system_score_codex":0.00012749065,"about_ca_system_score_gemma":0.00027336142,"threshold_uncertainty_score":0.8725788},"labels":[],"label_agreement":null},{"id":"W4412394752","doi":"10.1007/978-981-96-9949-0_38","title":"MCT-Net: Multiscale Convolution-Transformer Network for Defect Image Generation Using Segmentation Maps","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Convolution (computer science); Transformer; Artificial intelligence; Segmentation; Computer vision; Pattern recognition (psychology); Electrical engineering; Engineering; Artificial neural network; Voltage","score_opus":0.045916379604135846,"score_gpt":0.2915973830434393,"score_spread":0.24568100343930344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412394752","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003310632,0.0005333848,0.9571772,0.000038853344,0.0013227784,0.0012431344,0.00011081451,0.00011498048,0.039127793],"genre_scores_gemma":[0.24614942,0.0070821573,0.7342677,0.0009783568,0.0020479807,0.0007200911,0.00353834,0.0001310753,0.005084889],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998712,0.000022670496,0.00069002475,0.00016355583,0.00020992172,0.0002018214],"domain_scores_gemma":[0.9988172,0.00012809149,0.00015305757,0.0005463008,0.00030538262,0.00004994493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008025643,0.00019750607,0.00022818244,0.00056161877,0.00056606863,0.0003112689,0.0003487731,0.00020105277,0.0000067223564],"category_scores_gemma":[0.000019538593,0.0002125745,0.00007930564,0.0002902532,0.00019978837,0.0025097239,0.000092907634,0.00025094443,0.0000115187995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003326055,0.000024543611,0.00007822419,0.0005325526,0.00009746492,2.575978e-7,0.002312406,0.23752578,0.0025372829,0.095679455,0.016956728,0.6442221],"study_design_scores_gemma":[0.000450067,0.000030146419,0.000042936208,0.00021741382,0.000021723565,0.000005709413,0.00001902317,0.9108215,0.00021410058,0.0004975278,0.08744852,0.00023134226],"about_ca_topic_score_codex":0.00002307352,"about_ca_topic_score_gemma":0.000031506475,"teacher_disagreement_score":0.67329574,"about_ca_system_score_codex":0.00029593534,"about_ca_system_score_gemma":0.00011766404,"threshold_uncertainty_score":0.86685365},"labels":[],"label_agreement":null},{"id":"W4412423181","doi":"10.1007/978-3-031-93598-5_5","title":"Enhancing Structural Minority Visibility in Link Recommendations","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Visibility; Link (geometry); Computer science; Information retrieval; World Wide Web; Geography; Computer network","score_opus":0.024182970118411556,"score_gpt":0.3265813826908089,"score_spread":0.3023984125723973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412423181","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009139173,0.00020564678,0.160237,0.001875941,0.00022796592,0.00075011875,0.00007272456,0.0000893273,0.8356274],"genre_scores_gemma":[0.8479773,0.0004930648,0.14720923,0.0004435775,0.00014681232,0.0000683452,0.0007154151,0.000008710486,0.0029375346],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986769,0.000035871853,0.00075000565,0.00021038162,0.00016460002,0.00016225828],"domain_scores_gemma":[0.99798524,0.00021724336,0.00025070828,0.0012737591,0.0002297227,0.0000432971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008026962,0.00016350434,0.00025007775,0.0008317317,0.0003204607,0.00022737593,0.0010968244,0.000060563165,0.00008100581],"category_scores_gemma":[0.000014054451,0.00017600859,0.000053990116,0.00046099318,0.00036827163,0.0019562,0.0012600105,0.0004908579,0.000007201696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011699118,0.000008411411,0.0030092176,0.000014445711,0.00000643423,2.279885e-8,0.0004863758,0.00006459428,0.0000013171792,0.52631533,0.00023020405,0.46986246],"study_design_scores_gemma":[0.0005180066,0.00003560123,0.022264719,0.00079468056,0.000033679426,0.0000014203974,0.000108268956,0.56850773,0.000050858514,0.2273034,0.17959128,0.00079033774],"about_ca_topic_score_codex":0.00017618563,"about_ca_topic_score_gemma":0.00019913906,"teacher_disagreement_score":0.84706336,"about_ca_system_score_codex":0.00015179215,"about_ca_system_score_gemma":0.0002109382,"threshold_uncertainty_score":0.7177422},"labels":[],"label_agreement":null},{"id":"W4412496830","doi":"10.1007/978-981-96-6957-8_18","title":"Top-Down Backpropagation in Deep Feedforward Neural Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Backpropagation; Feed forward; Feedforward neural network; Artificial neural network; Computer science; Artificial intelligence; Control engineering; Engineering","score_opus":0.02107952939137216,"score_gpt":0.283759156999145,"score_spread":0.26267962760777286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412496830","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000027330894,0.0002536639,0.8148027,0.0017271211,0.00019970421,0.0004497965,0.0000022098757,0.00014532763,0.18239217],"genre_scores_gemma":[0.37960598,0.0065179197,0.59757847,0.011518288,0.00009413214,0.00021481483,0.0002527341,0.000027249067,0.004190398],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980888,0.000070243375,0.0008652367,0.00033557485,0.00038750458,0.00025267614],"domain_scores_gemma":[0.99702096,0.00022713338,0.00033519146,0.0019834598,0.00035883603,0.000074394724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015378292,0.00023398225,0.00027262344,0.0017734492,0.0002861444,0.0008715229,0.003383313,0.00019513597,0.000005538523],"category_scores_gemma":[0.00005277892,0.00024652088,0.000048286805,0.00094593794,0.00046903608,0.0077558835,0.0024385497,0.0006853858,0.000013878134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001519743,0.000010236746,0.00007695034,0.000012045063,0.0000017013491,2.5274878e-7,0.0010361784,0.0039803963,3.8748297e-7,0.6731558,0.00017142994,0.32155314],"study_design_scores_gemma":[0.00018860612,0.000030988445,0.0011189212,0.00013411573,0.000002025633,0.0000071095455,0.000010190107,0.96259564,0.0000063525054,0.00923323,0.026437646,0.00023519801],"about_ca_topic_score_codex":0.000020620419,"about_ca_topic_score_gemma":0.000055348923,"teacher_disagreement_score":0.95861524,"about_ca_system_score_codex":0.00020895147,"about_ca_system_score_gemma":0.000261882,"threshold_uncertainty_score":0.9999987},"labels":[],"label_agreement":null},{"id":"W4412509088","doi":"10.1007/978-981-96-6462-7_19","title":"Application of Ultra-Scale Antenna Technology in 6G Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Antenna (radio); Scale (ratio); Computer science; Telecommunications; Electrical engineering; Engineering; Geography; Cartography","score_opus":0.010746989691737858,"score_gpt":0.2352500001411051,"score_spread":0.22450301044936724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412509088","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004103517,0.000818962,0.93261504,0.00018425455,0.000049120306,0.00018198851,0.000006709144,0.00006209512,0.0660408],"genre_scores_gemma":[0.97318643,0.010392816,0.015788855,0.00011639914,0.000010488707,0.000031787058,0.000061827835,0.0000069726652,0.00040443038],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991685,0.0000059732834,0.0005081233,0.00009791577,0.00010690978,0.00011253501],"domain_scores_gemma":[0.9988865,0.000057959292,0.00010347554,0.0007964056,0.00013350316,0.000022106007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313815,0.00010973055,0.00021003115,0.0014923912,0.00006692838,0.000036754504,0.00085707003,0.00013816816,0.0000021732585],"category_scores_gemma":[0.000008504129,0.00011673904,0.000026616886,0.0007972465,0.00048336422,0.00076980673,0.00019753577,0.00029218942,0.000004766336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004185121,0.000030086125,0.0021275345,0.00019454115,0.000023709928,2.3351016e-7,0.0010485816,0.018684404,0.00047926698,0.43947777,0.00014284489,0.53778684],"study_design_scores_gemma":[0.00008642135,0.0000063295006,0.00055503513,0.00017351641,0.000004972186,0.0000015907971,0.000027280847,0.9921998,0.000010690495,0.0018741036,0.004957458,0.000102829355],"about_ca_topic_score_codex":0.000008250617,"about_ca_topic_score_gemma":0.00001830604,"teacher_disagreement_score":0.9735154,"about_ca_system_score_codex":0.00006558329,"about_ca_system_score_gemma":0.000038832823,"threshold_uncertainty_score":0.476048},"labels":[],"label_agreement":null},{"id":"W4412509094","doi":"10.1007/978-981-96-6462-7_18","title":"Edge Computing in Wireless Multimedia Communications: Empowering Low-Latency and High-Quality Services","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Computer science; Wireless; Latency (audio); Multimedia; Low latency (capital markets); Computer network; Enhanced Data Rates for GSM Evolution; Telecommunications","score_opus":0.031665164851405796,"score_gpt":0.32140268824205626,"score_spread":0.28973752339065045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412509094","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019733753,0.005877385,0.67354393,0.005767534,0.009118541,0.0030651572,0.0000290863,0.0009718242,0.28189278],"genre_scores_gemma":[0.48055798,0.01029982,0.50518686,0.0026133694,0.0003125866,0.0000511312,0.0002410636,0.000034870078,0.00070234964],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99699163,0.00012483749,0.0014645377,0.0005286963,0.00045145277,0.0004388241],"domain_scores_gemma":[0.99430925,0.00090893684,0.0006075931,0.0035954115,0.0004422703,0.00013652265],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0024699438,0.00037993674,0.0005320966,0.0015520825,0.0009000002,0.0010121699,0.0062570907,0.00022708927,8.385453e-7],"category_scores_gemma":[0.000055140157,0.00041552875,0.00005227785,0.0009439317,0.0010396949,0.005491436,0.011126687,0.00091332046,0.000018131437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037018522,0.00005221442,0.0015026066,0.00033465817,0.000011237255,0.0000010230409,0.0082258005,0.00008420737,0.000011833792,0.24158286,0.00008857045,0.7481013],"study_design_scores_gemma":[0.0005829936,0.000025157402,0.01950958,0.001757182,0.000005848279,0.000012270843,0.00006211177,0.95897573,0.000012541366,0.00522712,0.013265,0.0005644885],"about_ca_topic_score_codex":0.00020435426,"about_ca_topic_score_gemma":0.000051758117,"teacher_disagreement_score":0.9588915,"about_ca_system_score_codex":0.00022107986,"about_ca_system_score_gemma":0.0003467359,"threshold_uncertainty_score":0.99982965},"labels":[],"label_agreement":null},{"id":"W4412509357","doi":"10.1007/978-981-96-6462-7_15","title":"Integration Challenges for 5G and Beyond Wireless Communications","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Wireless; Computer science; Telecommunications","score_opus":0.04916633683968127,"score_gpt":0.28360931293932573,"score_spread":0.23444297609964446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412509357","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016982997,0.023638356,0.113505125,0.007692134,0.00037458717,0.001628291,0.00014875284,0.0009950682,0.8518478],"genre_scores_gemma":[0.2532003,0.34499115,0.39924082,0.00041182048,0.000033934095,0.00046055345,0.0004533865,0.00003754061,0.0011705362],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897355,0.000015038521,0.0005519402,0.00016193022,0.00012696855,0.00017054492],"domain_scores_gemma":[0.9964077,0.00048292213,0.00013657597,0.002634244,0.0002965112,0.000042051928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057928433,0.00021200854,0.0002465981,0.00094330974,0.0005215531,0.00024611704,0.00221499,0.00019387786,0.0000013621554],"category_scores_gemma":[0.00006532524,0.00022373039,0.000033273074,0.00023500904,0.0011636105,0.0017151048,0.001031572,0.00045816434,0.0000037438724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.111388e-7,0.0000053265044,0.000002592419,0.00006007798,0.0000057894895,9.3355e-9,0.0004970396,0.000045071414,0.0000068690797,0.4279976,0.0002339431,0.571145],"study_design_scores_gemma":[0.0002654153,0.00004257288,0.00032405302,0.00047427873,0.000017817325,0.0000081835415,0.00021694886,0.66265035,0.000042873733,0.0228557,0.31273907,0.00036274182],"about_ca_topic_score_codex":0.000004598912,"about_ca_topic_score_gemma":0.00005399198,"teacher_disagreement_score":0.8506773,"about_ca_system_score_codex":0.00011696903,"about_ca_system_score_gemma":0.0000823691,"threshold_uncertainty_score":0.912346},"labels":[],"label_agreement":null},{"id":"W4412509469","doi":"10.1007/978-981-96-6462-7_34","title":"Latency Reduction Techniques in Real-Time Wireless Multimedia Transmission","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Latency (audio); Computer science; Reduction (mathematics); Wireless; Transmission (telecommunications); Wireless transmission; Multimedia; Computer network; Telecommunications","score_opus":0.022541936409677662,"score_gpt":0.3070973407954576,"score_spread":0.2845554043857799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412509469","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022110738,0.00020227957,0.82884955,0.00082958274,0.00015175129,0.00077843387,0.000012955149,0.0005380395,0.16861527],"genre_scores_gemma":[0.0021782534,0.016447948,0.97866255,0.00020072862,0.000021373993,0.00009229607,0.00011579893,0.000010752553,0.0022703244],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978262,0.000059324557,0.00095833157,0.0004472023,0.00044496646,0.00026393047],"domain_scores_gemma":[0.9964539,0.00018866172,0.0003625767,0.0025711718,0.00032784924,0.000095830845],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010626363,0.0002810686,0.0003478241,0.0021614495,0.00030832808,0.0003174921,0.0041396716,0.0002338661,0.000008653543],"category_scores_gemma":[0.00002824369,0.0002826002,0.000044493558,0.0008314226,0.000631253,0.008866118,0.0025874523,0.0006100498,0.000019996305],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029548119,0.000020835982,0.0000048902807,0.000028159619,0.0000013507289,5.1426287e-7,0.0007149554,0.000015201188,0.00024497893,0.11909957,0.00056572835,0.87930083],"study_design_scores_gemma":[0.00040287763,0.00008926536,0.00045895242,0.0024044074,0.000005823796,0.00003321077,0.00001506375,0.8101474,0.0023355675,0.038683828,0.14465751,0.0007660923],"about_ca_topic_score_codex":0.00003707427,"about_ca_topic_score_gemma":0.0000025498825,"teacher_disagreement_score":0.8785348,"about_ca_system_score_codex":0.00025663266,"about_ca_system_score_gemma":0.00035712656,"threshold_uncertainty_score":0.9999626},"labels":[],"label_agreement":null},{"id":"W4412510611","doi":"10.1007/978-981-96-7008-6_31","title":"Role-Playing Based on Large Language Models via Style Extraction","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Style (visual arts); Extraction (chemistry); Computer science; Natural language processing; Artificial intelligence; Information retrieval; Art; Chromatography; Literature; Chemistry","score_opus":0.031609915465871566,"score_gpt":0.2982491380845073,"score_spread":0.26663922261863576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412510611","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015100075,0.00013150547,0.7418583,0.00040290193,0.0001608513,0.00021034473,0.000007632835,0.000092026465,0.25712132],"genre_scores_gemma":[0.41752583,0.00049921,0.5750164,0.0043310984,0.00005898451,0.000055056666,0.000095522526,0.000013275842,0.002404666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998398,0.000034447818,0.00054120756,0.0003195694,0.00047003277,0.00023670678],"domain_scores_gemma":[0.99674046,0.0002345901,0.00025166036,0.0024804259,0.00021929333,0.00007354879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010711574,0.00020006577,0.00019683872,0.0011732988,0.00053363986,0.0005254523,0.0026887287,0.00013106714,0.0000063423304],"category_scores_gemma":[0.00002719469,0.00020932459,0.00004629129,0.00035358808,0.00015995919,0.0058276616,0.0013743866,0.00050262857,0.000027697255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019019105,0.000020398445,0.0000066164744,0.000022239072,0.0000023897885,3.5546958e-7,0.0016312544,0.012469557,0.000008107784,0.63915056,0.000061925,0.34662467],"study_design_scores_gemma":[0.00021181654,0.000019587318,0.00006973133,0.00019944615,0.0000027653355,0.0000038195535,0.000021957783,0.9812562,0.000008524809,0.0058873785,0.01212669,0.00019210296],"about_ca_topic_score_codex":0.000019921012,"about_ca_topic_score_gemma":0.000011373392,"teacher_disagreement_score":0.9687866,"about_ca_system_score_codex":0.00018509495,"about_ca_system_score_gemma":0.00026920348,"threshold_uncertainty_score":0.85360086},"labels":[],"label_agreement":null},{"id":"W4412512470","doi":"10.1007/978-981-96-6688-1_28","title":"A Simultaneous Hierarchical Count Data Clustering and Feature Selection Based on Multinomial Nested Dirichlet Mixture Using the Minorization-Maximization Framework","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Multinomial distribution; Feature selection; Latent Dirichlet allocation; Selection (genetic algorithm); Hierarchical Dirichlet process; Dirichlet distribution; Cluster analysis; Maximization; Hierarchical clustering; Count data; Data mining; Artificial intelligence; Statistics; Topic model; Mathematics; Mathematical optimization","score_opus":0.034810372676734196,"score_gpt":0.3026684632058938,"score_spread":0.2678580905291596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412512470","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000036518904,0.00015306186,0.99032813,0.004952701,0.0002508422,0.0005408319,0.000028352888,0.00017910691,0.0035304765],"genre_scores_gemma":[0.17536975,0.0012202451,0.81903327,0.003120481,0.00008878454,0.000038818023,0.00038425127,0.000016589145,0.0007278294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983697,0.00006312006,0.00047977985,0.0004527055,0.0004361421,0.00019856151],"domain_scores_gemma":[0.995524,0.001103335,0.0003654629,0.0026188293,0.00033482863,0.00005353286],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006655192,0.00024853906,0.00021044184,0.0008408862,0.0009953588,0.0011686073,0.0035973217,0.00028266845,0.0000022422494],"category_scores_gemma":[0.00044932854,0.00020607376,0.000023375034,0.0008814079,0.0006822341,0.0030125794,0.0026944408,0.0007538609,0.0000024379842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022076392,0.000046338428,0.00025728624,0.00008161707,0.000013884483,6.972933e-7,0.0013770903,0.047149744,0.000012215977,0.48574382,0.0006323277,0.4646629],"study_design_scores_gemma":[0.00018512899,0.000031661137,0.0002831016,0.0002461017,0.000009719346,0.0000089515315,0.000018368508,0.9649313,0.000004723033,0.0021108834,0.031966936,0.00020312681],"about_ca_topic_score_codex":0.000009885718,"about_ca_topic_score_gemma":0.000015603497,"teacher_disagreement_score":0.91778153,"about_ca_system_score_codex":0.00017225041,"about_ca_system_score_gemma":0.00034777107,"threshold_uncertainty_score":0.9998683},"labels":[],"label_agreement":null},{"id":"W4412582368","doi":"10.1007/978-3-031-99261-2_33","title":"Designing an Ethical Framework for the Integration of Generative AI in Higher Education: Balancing Stakeholder Interests and Enhancing Learning Outcomes","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Stakeholder; Generative grammar; Computer science; Knowledge management; Engineering ethics; Artificial intelligence; Political science; Engineering; Public relations","score_opus":0.19710700576751186,"score_gpt":0.4500034332734173,"score_spread":0.25289642750590546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412582368","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019942964,0.0013706784,0.7548587,0.104956165,0.0015708583,0.0021462082,0.000014460277,0.00007324064,0.13301544],"genre_scores_gemma":[0.8623226,0.0027709845,0.12395304,0.008183791,0.000119465854,0.000063747924,0.000029571625,0.000009044304,0.002547729],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998782,0.000147423,0.0004965904,0.00014207786,0.00028265652,0.0001492704],"domain_scores_gemma":[0.99624455,0.0023382718,0.00027259026,0.00036853264,0.00072124694,0.000054790067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034807306,0.0001172958,0.00020760956,0.0003844523,0.001070165,0.0005386434,0.00067656656,0.0003080078,0.000006780245],"category_scores_gemma":[0.0011183817,0.00009903341,0.000027502438,0.0002546422,0.0011843749,0.0023978925,0.00028832606,0.0011687169,3.6855624e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022610936,0.0000075810667,0.00024229885,0.000016493426,0.0000039039423,1.1026264e-8,0.04019279,0.00006743485,0.0000065762115,0.88829774,0.000026165908,0.07113676],"study_design_scores_gemma":[0.0008073109,0.00029804735,0.038609415,0.0053415988,0.00007065067,0.0000014183605,0.030552926,0.07225137,0.00009952621,0.7452114,0.10570902,0.0010473082],"about_ca_topic_score_codex":0.0002873451,"about_ca_topic_score_gemma":0.0013281832,"teacher_disagreement_score":0.8603283,"about_ca_system_score_codex":0.00014902587,"about_ca_system_score_gemma":0.00095540046,"threshold_uncertainty_score":0.8230952},"labels":[],"label_agreement":null},{"id":"W4412585222","doi":"10.1007/978-3-031-99264-3_26","title":"Design and Validation of the Psychometric Properties of a Questionnaire Measuring AI Literacy Among University Students: Preliminary Results","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital literacy in education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Literacy; Psychology; Computer science; Natural language processing; Mathematics education; Pedagogy","score_opus":0.0419806301224227,"score_gpt":0.28592642818059627,"score_spread":0.24394579805817357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412585222","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020096084,0.0018102209,0.9323327,0.0019007986,0.00096777617,0.0024049194,0.000032857835,0.0001105274,0.040344134],"genre_scores_gemma":[0.9721537,0.00047292435,0.026466684,0.00006217943,0.00000416054,0.0000054163884,0.000007021911,0.0000025807935,0.0008253183],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857736,0.000091881426,0.0006175887,0.0002010305,0.00041608483,0.00009603108],"domain_scores_gemma":[0.996869,0.00017387305,0.0005648083,0.0014304933,0.0009305279,0.000031246676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011877212,0.00012902191,0.0001711429,0.0012409232,0.00024378717,0.00039827137,0.0028079362,0.00006542629,1.9600147e-7],"category_scores_gemma":[0.0001962422,0.00011135053,0.000029414816,0.0010912535,0.0007504907,0.00992499,0.0020690232,0.00020084587,7.3838356e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010230435,0.00027810354,0.0066995565,0.00075830106,0.000046657045,1.634708e-7,0.03968288,0.0038574948,0.00003147042,0.29456043,0.00029764493,0.653685],"study_design_scores_gemma":[0.002710443,0.0006731955,0.2289224,0.021471735,0.000094636955,0.000034977416,0.0002844024,0.7114831,0.0031178708,0.014779774,0.01518407,0.0012433586],"about_ca_topic_score_codex":0.000016218442,"about_ca_topic_score_gemma":6.763733e-7,"teacher_disagreement_score":0.9520576,"about_ca_system_score_codex":0.00011541749,"about_ca_system_score_gemma":0.00030622992,"threshold_uncertainty_score":0.71953785},"labels":[],"label_agreement":null},{"id":"W4412585364","doi":"10.1007/978-3-031-99264-3_8","title":"SSRLBot: Designing and Developing a Large Language Model-Based Agent Using Socially Shared Regulated Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; World Wide Web","score_opus":0.06230411736592756,"score_gpt":0.3164787178625257,"score_spread":0.2541746004965981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412585364","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00031378458,0.0003764747,0.989567,0.00032366175,0.00011976042,0.00036853534,0.0000069101857,0.00010364935,0.008820262],"genre_scores_gemma":[0.14283001,0.00047329426,0.8545922,0.0008929903,0.000024734441,0.000021263495,0.00009222635,0.000012159362,0.0010611269],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837387,0.00006765077,0.0006395695,0.00030641266,0.00035843562,0.00025408715],"domain_scores_gemma":[0.998165,0.000153358,0.0004273175,0.00086641015,0.0003166843,0.000071197326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014119754,0.00021335909,0.0002562261,0.00092495984,0.0009610863,0.0007763853,0.0013302559,0.00014332151,0.0000020542495],"category_scores_gemma":[0.000061346655,0.00022853292,0.000038026727,0.00042444057,0.00019338755,0.0035521134,0.0014979268,0.00034734642,0.0000042541315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052721884,0.000023935621,0.00026256603,0.00027121985,0.00002365441,0.0000015507987,0.020143934,0.037797462,0.00018814637,0.77572197,0.00011838291,0.16544192],"study_design_scores_gemma":[0.00031546567,0.000011079145,0.00037734403,0.0005985552,0.0000060691473,0.000003847305,0.00004371542,0.99462193,0.00002561013,0.0007569515,0.0029971586,0.00024229466],"about_ca_topic_score_codex":0.000023687096,"about_ca_topic_score_gemma":0.000018207416,"teacher_disagreement_score":0.9568244,"about_ca_system_score_codex":0.00028735626,"about_ca_system_score_gemma":0.00094623404,"threshold_uncertainty_score":0.93193024},"labels":[],"label_agreement":null},{"id":"W4412591596","doi":"10.1007/978-3-031-99267-4_11","title":"An Augmented Intelligence System for Automated Quality Control and Feedback Generation of Multiple Choice Test Items","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Test (biology); Multiple choice; Computer science; Control (management); Quality (philosophy); Artificial intelligence; Biology; Statistics; Mathematics; Botany","score_opus":0.07028701809007214,"score_gpt":0.3364495307656157,"score_spread":0.26616251267554353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412591596","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025904967,0.00024553217,0.99288446,0.00013234578,0.0003965481,0.00081382366,0.000053016865,0.00019350678,0.0050216927],"genre_scores_gemma":[0.89698,0.0002497045,0.101238824,0.00018352004,0.000067462555,0.00007644485,0.00008484754,0.000008982226,0.0011102164],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802387,0.00007737936,0.0010669404,0.00032964486,0.00031128814,0.00019090933],"domain_scores_gemma":[0.99554956,0.0014416325,0.0006692691,0.0013235329,0.00093649584,0.00007953779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018479428,0.00021013997,0.00035748948,0.0006437522,0.00047797363,0.00050251663,0.0017022195,0.00012707575,4.62927e-7],"category_scores_gemma":[0.0003393903,0.00020897567,0.000043332773,0.00029495306,0.00034896625,0.0033998948,0.0005348188,0.00021664207,0.0000026590003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004611033,0.000031499592,0.0007144258,0.0003116316,0.000014042937,7.530774e-8,0.001430939,0.0032706365,0.0003269087,0.90294063,0.000054950087,0.09089967],"study_design_scores_gemma":[0.0002818728,0.000096419935,0.0018122985,0.00054949714,0.000006372946,0.0000038841285,0.000059130383,0.9822528,0.00014874792,0.00012096464,0.014466769,0.00020129152],"about_ca_topic_score_codex":0.00010404106,"about_ca_topic_score_gemma":0.0000260256,"teacher_disagreement_score":0.9789821,"about_ca_system_score_codex":0.00015815503,"about_ca_system_score_gemma":0.00021199026,"threshold_uncertainty_score":0.8521781},"labels":[],"label_agreement":null},{"id":"W4412591686","doi":"10.1007/978-3-031-99267-4_5","title":"Knowledge, Uses and Perceptions of ChatGPT in Higher Education","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Cegep de Saint Jerome","funders":"","keywords":"Perception; Computer science; Thesaurus; Information retrieval; World Wide Web; Psychology; Natural language processing; Neuroscience","score_opus":0.03638066633100999,"score_gpt":0.3406353201368291,"score_spread":0.3042546538058191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412591686","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010558254,0.003581405,0.05742451,0.011970905,0.0008982567,0.0005764406,0.00001878195,0.000119758944,0.92435414],"genre_scores_gemma":[0.65896744,0.016196955,0.27067238,0.0016102028,0.00010346989,0.00004471157,0.00009769581,0.000014638626,0.0522925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990063,0.000028924514,0.0004992244,0.00018583707,0.00016333953,0.00011639279],"domain_scores_gemma":[0.99823636,0.0001656069,0.0001973471,0.0010496682,0.00030224014,0.000048792397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005005196,0.00012843877,0.00019945504,0.0014366659,0.00016786152,0.00020735178,0.001381345,0.000092311224,0.0000068256527],"category_scores_gemma":[0.000029862398,0.00013186356,0.000024620425,0.00057364546,0.0005408422,0.0024739767,0.0013660725,0.0003119869,0.000008571422],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.4802534e-7,0.000028876453,0.0004583405,0.000041528932,0.0000016466003,2.4402524e-8,0.0011808986,0.000044717868,0.0000010582268,0.7903497,0.00015831627,0.20773456],"study_design_scores_gemma":[0.000491553,0.00009298624,0.06786712,0.0019149156,0.00001625079,0.000012616927,0.00013702431,0.55514956,0.0000040939035,0.057488043,0.31625533,0.00057048106],"about_ca_topic_score_codex":0.000016974014,"about_ca_topic_score_gemma":0.00001749794,"teacher_disagreement_score":0.8720616,"about_ca_system_score_codex":0.00007192607,"about_ca_system_score_gemma":0.00055568287,"threshold_uncertainty_score":0.537724},"labels":[],"label_agreement":null},{"id":"W4412593129","doi":"10.1007/978-3-031-94039-2_13","title":"GDAdaP: A Domain Adaptation Framework for Gene Dependency Prediction in Lung Cancer","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Dependency (UML); Adaptation (eye); Domain adaptation; Lung cancer; Domain (mathematical analysis); Computer science; Computational biology; Biology; Internal medicine; Artificial intelligence; Medicine; Mathematics; Neuroscience","score_opus":0.01902068210711665,"score_gpt":0.2939066544018691,"score_spread":0.2748859722947524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412593129","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037720404,0.0021452445,0.96873885,0.0003729367,0.0003549761,0.00080535637,0.0001494891,0.0000117576665,0.027044155],"genre_scores_gemma":[0.11145864,0.029098283,0.84852016,0.0027526761,0.00038141414,0.00067591073,0.0024627117,0.00003301742,0.004617178],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989591,0.000012744283,0.0005483648,0.00017639334,0.00013776855,0.0001656194],"domain_scores_gemma":[0.99876624,0.000053989355,0.00022282754,0.0007167491,0.00019800068,0.000042195134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005809943,0.00014758497,0.00015012754,0.00036706214,0.00020079185,0.00011364388,0.00064700923,0.00025177444,0.0000039066163],"category_scores_gemma":[0.000030675063,0.00015821835,0.00003969758,0.00015167068,0.00021789019,0.00012880907,0.0004954183,0.00023719325,0.0000014263526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007026061,0.000039110946,0.00070752954,0.00028399695,0.00004624436,1.4677279e-7,0.0031854294,0.010474307,0.00010202615,0.5723091,0.0017120811,0.4110698],"study_design_scores_gemma":[0.00078600476,0.00009434096,0.0013432612,0.00063490774,0.000019589681,0.000005596791,0.00009646083,0.8304789,0.000050554074,0.043543804,0.12255786,0.000388719],"about_ca_topic_score_codex":0.000016510641,"about_ca_topic_score_gemma":0.000098708435,"teacher_disagreement_score":0.8200046,"about_ca_system_score_codex":0.00009773505,"about_ca_system_score_gemma":0.00036747524,"threshold_uncertainty_score":0.64519566},"labels":[],"label_agreement":null},{"id":"W4412593175","doi":"10.1007/978-3-031-94039-2_11","title":"Prediction and Analysis of Postpartum Depression with Chronic Diseases as Risk Factors","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Maternal Mental Health During Pregnancy and Postpartum","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Depression (economics); Postpartum depression; Medicine; Biology; Pregnancy","score_opus":0.021838606849750357,"score_gpt":0.3020212901616945,"score_spread":0.2801826833119441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412593175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.62826777,0.02660526,0.02478797,0.0015212046,0.0010426971,0.0053873537,0.002800373,0.00032572838,0.30926162],"genre_scores_gemma":[0.9798095,0.017293483,0.0014358034,0.00013268743,0.000010263341,0.000014970085,0.0003856575,0.000003928993,0.00091367395],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991261,0.000017486109,0.0003912957,0.00013515636,0.00023527995,0.00009469576],"domain_scores_gemma":[0.9987049,0.00012627422,0.00027612352,0.00065549026,0.00014711135,0.00009011092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017991656,0.00011601612,0.0002630447,0.0009468762,0.0002135776,0.00004138803,0.00022254942,0.0000626723,0.000011140165],"category_scores_gemma":[0.000020675945,0.000089552785,0.000031666194,0.00030284785,0.00046131425,0.00081461546,0.00032117413,0.00019983658,0.0000011522218],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024551305,0.00008773544,0.8846803,0.0027961535,0.00030344308,9.4830443e-7,0.0026143969,0.000411362,0.0000023425027,0.028938124,0.00003963012,0.079880066],"study_design_scores_gemma":[0.00046926813,0.00030443404,0.915965,0.005172174,0.0005607883,0.000009303739,0.000020578664,0.07366397,0.000037164307,0.00023075279,0.003442891,0.00012366513],"about_ca_topic_score_codex":0.00007121228,"about_ca_topic_score_gemma":0.000015457217,"teacher_disagreement_score":0.35154176,"about_ca_system_score_codex":0.000084692314,"about_ca_system_score_gemma":0.0002189947,"threshold_uncertainty_score":0.36518565},"labels":[],"label_agreement":null},{"id":"W4412615167","doi":"10.1007/978-3-031-99267-4_30","title":"Human-AI Collaboration and Culture For Equity and Inclusion (Half-Day Workshop)","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Equity (law); Inclusion (mineral); Computer science; Library science; World Wide Web; Political science; Sociology; Social science","score_opus":0.18463283742216227,"score_gpt":0.477613671212504,"score_spread":0.2929808337903417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412615167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033803302,0.0070027555,0.5980731,0.010234065,0.0010040746,0.0025852125,0.00016320722,0.000108116736,0.38049138],"genre_scores_gemma":[0.808267,0.003068665,0.11982335,0.008555593,0.0002641998,0.00017871194,0.00015711182,0.000029923225,0.05965547],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968592,0.00007753823,0.0012743304,0.00044147315,0.0011368318,0.00021062302],"domain_scores_gemma":[0.9948821,0.0013587235,0.00059462234,0.0015213045,0.0015277772,0.0001154789],"candidate_categories":["sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.007106578,0.00023027616,0.00041733644,0.001346724,0.0037299604,0.0022679346,0.002103836,0.00020385739,0.000011664561],"category_scores_gemma":[0.0008970375,0.00018799072,0.0000464547,0.00076023786,0.00082926574,0.0042615817,0.028460406,0.0003219564,0.0000053367185],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005093094,0.000006661551,0.000031722728,0.000022718463,0.0000028797563,8.599884e-8,0.0054140813,0.000052369633,0.000007389276,0.64307815,0.009964169,0.34141466],"study_design_scores_gemma":[0.00032283977,0.00003807967,0.000403262,0.0002675664,0.000006359523,0.000005967398,0.00019803435,0.11919821,0.0000014342221,0.32358906,0.55577624,0.00019297592],"about_ca_topic_score_codex":0.000011405307,"about_ca_topic_score_gemma":0.00016486821,"teacher_disagreement_score":0.8079289,"about_ca_system_score_codex":0.000109040506,"about_ca_system_score_gemma":0.00025100744,"threshold_uncertainty_score":0.9987678},"labels":[],"label_agreement":null},{"id":"W4412615198","doi":"10.1007/978-3-031-99267-4_33","title":"Workshop on Advancements in AI-Supported Exploratory Learning (AI4EL)","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Data science","score_opus":0.047689542934834565,"score_gpt":0.3134181660957129,"score_spread":0.2657286231608783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412615198","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008307192,0.0004046808,0.6596688,0.0009475606,0.0007546866,0.00051246246,0.000002689395,0.00014434649,0.3374817],"genre_scores_gemma":[0.4697972,0.021227611,0.23345791,0.015167819,0.00036847906,0.00049784436,0.00030647908,0.0000956479,0.259081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99808633,0.00007028073,0.00076058955,0.00034707444,0.00045588074,0.00027983284],"domain_scores_gemma":[0.9975971,0.00027544072,0.00032980248,0.001426414,0.00030179025,0.00006943869],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013160047,0.00023632172,0.00027278005,0.0016677474,0.00042976398,0.0005213617,0.002486367,0.00012217417,0.0000064406026],"category_scores_gemma":[0.00009896181,0.0002472946,0.000040986895,0.00063273846,0.00024789976,0.005008464,0.0018269316,0.0010251155,0.00007088049],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023230082,0.000013929505,0.00014265192,0.000021783704,0.000003430737,0.0000010059687,0.0020422349,0.004032935,0.0000015180522,0.7664383,0.00010248026,0.22719738],"study_design_scores_gemma":[0.0002752693,0.0000576487,0.00054271985,0.0016633167,0.0000020120915,0.00000336982,0.000109717905,0.28187922,0.000011498417,0.002141276,0.712969,0.00034495656],"about_ca_topic_score_codex":0.000008598494,"about_ca_topic_score_gemma":0.000009379859,"teacher_disagreement_score":0.76429707,"about_ca_system_score_codex":0.00028930776,"about_ca_system_score_gemma":0.0003126045,"threshold_uncertainty_score":0.9999979},"labels":[],"label_agreement":null},{"id":"W4412615213","doi":"10.1007/978-3-031-99267-4_4","title":"Deep Reinforcement Learning for Engagement-Aware Question Selection in Adaptive Assessment Systems","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Reinforcement learning; Selection (genetic algorithm); Computer science; Artificial intelligence; Information retrieval","score_opus":0.0473602519164681,"score_gpt":0.3236650112478875,"score_spread":0.2763047593314194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412615213","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005147651,0.000176451,0.9397113,0.00013741569,0.00042658197,0.00091627176,8.085548e-7,0.00008084847,0.05854522],"genre_scores_gemma":[0.70494103,0.0024991964,0.25041434,0.00046516422,0.00018787727,0.0008405902,0.0001683579,0.00003028419,0.040453143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979787,0.00012515638,0.000865594,0.00034060667,0.00041364963,0.00027633412],"domain_scores_gemma":[0.9978723,0.0003528415,0.0004886036,0.0006214056,0.0006104649,0.000054411536],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002771214,0.00023178561,0.0002866503,0.0014134864,0.00070159097,0.00070068176,0.0014253226,0.00013236474,0.0000019126048],"category_scores_gemma":[0.000062314,0.00024736708,0.000048323036,0.00044331484,0.00013754638,0.0038958497,0.0010560184,0.0007096626,0.000007640641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022080387,0.000006855399,0.00009573658,0.00005636653,0.000006122411,1.1689345e-7,0.0008048918,0.18038198,0.0000012904678,0.7796541,0.000025695594,0.03896467],"study_design_scores_gemma":[0.00022027385,0.00011382842,0.000365911,0.0007965378,0.000004106542,0.0000040552654,0.00010102961,0.9051432,0.0000023885523,0.0007225484,0.09231095,0.00021516095],"about_ca_topic_score_codex":0.00008239361,"about_ca_topic_score_gemma":0.000020306166,"teacher_disagreement_score":0.7789315,"about_ca_system_score_codex":0.0007889074,"about_ca_system_score_gemma":0.00040355217,"threshold_uncertainty_score":0.99999785},"labels":[],"label_agreement":null},{"id":"W4412636726","doi":"10.1007/978-3-031-99264-3_36","title":"Making Generative AI Hallucinations Useful by Reassessing the Troublemaker Agent Strategy","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Generative grammar; Computer science; Artificial intelligence","score_opus":0.08497441642269019,"score_gpt":0.349361195893825,"score_spread":0.26438677947113487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412636726","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000133654885,0.0006379459,0.8549386,0.0073352614,0.0003915965,0.0005844588,0.00002360822,0.000121013756,0.13595414],"genre_scores_gemma":[0.21084018,0.0039498834,0.75351477,0.019781621,0.00023756095,0.00032884596,0.00030843043,0.000044975302,0.010993761],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973182,0.00013879153,0.0009822156,0.0005171792,0.00068739936,0.00035620268],"domain_scores_gemma":[0.99481845,0.00057529635,0.00046451495,0.0032165197,0.00083602016,0.00008918312],"candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0017878439,0.00034800323,0.0003321867,0.00078544253,0.0014869869,0.0025786548,0.0053246254,0.00015709856,0.000010857986],"category_scores_gemma":[0.00007936717,0.00029089075,0.00008355748,0.00092092727,0.0011570613,0.0068689836,0.004500379,0.0008103724,0.000021626269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.074893e-7,0.00002846618,0.000029612473,0.000019527706,0.0000109848215,4.7942797e-7,0.001422025,0.001368557,0.0000021371238,0.7120825,0.002282887,0.28275192],"study_design_scores_gemma":[0.00021718898,0.000041815405,0.0010654373,0.00021198788,0.000010522435,0.000021930713,0.000038317157,0.83718365,0.000008027785,0.041385695,0.11945854,0.00035689247],"about_ca_topic_score_codex":0.00002144053,"about_ca_topic_score_gemma":0.000043068972,"teacher_disagreement_score":0.8358151,"about_ca_system_score_codex":0.00041716965,"about_ca_system_score_gemma":0.0008272964,"threshold_uncertainty_score":0.99995434},"labels":[],"label_agreement":null},{"id":"W4412840669","doi":"10.1007/978-3-031-94956-2_7","title":"A Study on the Importance of Features in Detecting Advanced Persistent Threats Using Machine Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick; University of Windsor","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Data science","score_opus":0.04989291317624531,"score_gpt":0.30848388759010115,"score_spread":0.2585909744138558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412840669","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19318695,0.011014631,0.22140424,0.005654559,0.0025415155,0.008448731,0.000027398373,0.00051489606,0.55720705],"genre_scores_gemma":[0.977644,0.0012087674,0.020196607,0.00048187724,0.00001483887,0.000025168541,0.0000043584873,0.000005591794,0.00041873535],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985868,0.000085247804,0.0005813771,0.00023614494,0.00035508221,0.00015535475],"domain_scores_gemma":[0.99772465,0.00039443118,0.0004015874,0.0012576929,0.0001927894,0.00002884836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001441509,0.00016144481,0.00021859084,0.0007696914,0.0005448356,0.00021154944,0.0018851017,0.00007013358,0.00000235746],"category_scores_gemma":[0.00009216238,0.0001318674,0.000051808238,0.00067651574,0.00027645845,0.0015650783,0.0016379931,0.0007222903,0.0000014739952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026832808,0.000126603,0.0032370705,0.00005624211,0.00002338929,0.0000016096259,0.019798312,0.02310804,0.000024396944,0.41993186,0.000018388195,0.53364724],"study_design_scores_gemma":[0.00042482343,0.00029918805,0.0029424075,0.0007134819,0.000008191679,0.000016503056,0.00045283316,0.9884251,0.00004608001,0.0034593043,0.002952893,0.00025921568],"about_ca_topic_score_codex":0.000029090475,"about_ca_topic_score_gemma":0.00015839963,"teacher_disagreement_score":0.965317,"about_ca_system_score_codex":0.00014641647,"about_ca_system_score_gemma":0.000127846,"threshold_uncertainty_score":0.5377397},"labels":[],"label_agreement":null},{"id":"W4412840708","doi":"10.1007/978-3-031-94956-2_6","title":"Dynamic Malware Detection Using LSTM Based GANs and Linux System Calls","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Malware; Computer science; Operating system","score_opus":0.020196504043576573,"score_gpt":0.2882167951715297,"score_spread":0.2680202911279531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412840708","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005285736,0.00023910875,0.9837333,0.00020925935,0.0002728014,0.00046926262,0.000015069339,0.00038907467,0.014619284],"genre_scores_gemma":[0.14984857,0.0006992927,0.8483175,0.0005771407,0.0000146490665,0.00004990555,0.000019746965,0.000012977291,0.00046024032],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983285,0.00004346386,0.0006738006,0.00038046128,0.0003510357,0.00022270426],"domain_scores_gemma":[0.9969413,0.00020328842,0.00038330784,0.001894988,0.0004844987,0.00009260527],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00074137887,0.0002586468,0.0002760816,0.0016317201,0.00068909436,0.0005646881,0.0019107184,0.00018924016,0.000001190157],"category_scores_gemma":[0.000044127006,0.0002812912,0.000043543187,0.000631808,0.00057137635,0.0049142595,0.0018397993,0.00046783692,0.0000054072657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050737294,0.000013102398,0.000017557475,0.00027731125,0.0000078729645,0.0000012511288,0.00054594345,0.0016708869,0.00006241486,0.2751094,0.000017777322,0.7222714],"study_design_scores_gemma":[0.00016571101,0.000043081087,0.00017615185,0.0005547102,0.0000071187083,0.00004489944,0.000018848374,0.9831083,0.00013557189,0.0018259897,0.013644168,0.00027545926],"about_ca_topic_score_codex":0.000024163688,"about_ca_topic_score_gemma":0.00003387359,"teacher_disagreement_score":0.9814374,"about_ca_system_score_codex":0.0005279348,"about_ca_system_score_gemma":0.00039479687,"threshold_uncertainty_score":0.99996394},"labels":[],"label_agreement":null},{"id":"W4412840713","doi":"10.1007/978-3-031-94956-2_21","title":"Analysis of Neighborhood Map-Based Wireless Medium Access Control","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Wireless; Telecommunications","score_opus":0.0276293367829751,"score_gpt":0.3115170996323273,"score_spread":0.28388776284935224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412840713","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000050932495,0.00015780967,0.92927843,0.0013899566,0.00019553024,0.0014211365,0.00004038307,0.000056054985,0.067455575],"genre_scores_gemma":[0.881551,0.001874676,0.10380631,0.008976229,0.00011074714,0.0015001394,0.00039822617,0.00002591669,0.0017567032],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99790674,0.000056678477,0.0009581206,0.00030720187,0.0005405322,0.00023073367],"domain_scores_gemma":[0.99525857,0.00057880895,0.00064462464,0.0027546773,0.0006677245,0.000095616],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0011986063,0.00023130243,0.00055523915,0.0025211,0.00029033382,0.0006912279,0.0066159638,0.00015850549,0.000012784753],"category_scores_gemma":[0.000022780452,0.00022295803,0.00012588351,0.0018790823,0.0007127595,0.0044951434,0.0021194373,0.00036321857,0.0000048961024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000067799024,0.000031060918,0.0010847509,0.000086380845,0.000091915936,2.9163468e-7,0.00032377974,0.009412407,8.276341e-7,0.78175676,0.00033464897,0.20687042],"study_design_scores_gemma":[0.0004002631,0.00003212593,0.003042949,0.00026192883,0.000060922135,4.6558512e-7,0.0000020468565,0.9706872,0.000008207402,0.0023284086,0.022961743,0.00021374042],"about_ca_topic_score_codex":0.000017778837,"about_ca_topic_score_gemma":0.000020959082,"teacher_disagreement_score":0.9612748,"about_ca_system_score_codex":0.000090348716,"about_ca_system_score_gemma":0.00074365304,"threshold_uncertainty_score":0.99875873},"labels":[],"label_agreement":null},{"id":"W4412902185","doi":"10.1007/978-3-031-99332-9_1","title":"Multiuser HAP Architecture Using Symbol Wavelengths","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Satellite Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Symbol (formal); Architecture; Computer science; Wavelength; Computer architecture; Physics; Optoelectronics; History; Archaeology; Programming language","score_opus":0.036605128611656094,"score_gpt":0.280168750567724,"score_spread":0.2435636219560679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412902185","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023471827,0.006007479,0.16968139,0.00028591062,0.0008564294,0.0010521176,0.00006572603,0.0004774107,0.82133883],"genre_scores_gemma":[0.38007784,0.06442575,0.5415264,0.0022217806,0.0002841184,0.00019525406,0.0006182439,0.00015776358,0.010492883],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985373,0.000029299177,0.0007631106,0.00016465381,0.00029566378,0.00020994549],"domain_scores_gemma":[0.99672717,0.00026028257,0.00015003725,0.0025354933,0.0002503273,0.00007669772],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00060251576,0.00025359678,0.00028375405,0.0012500037,0.0003153781,0.0003008163,0.0021509884,0.00018136931,0.000011903342],"category_scores_gemma":[0.000032669614,0.000271481,0.000047967686,0.0004050232,0.00055505394,0.0018402505,0.0011562897,0.0006245285,0.0000383928],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033382485,0.000014785376,0.00008625201,0.00037044086,0.000039872382,3.8877963e-7,0.0063665668,0.018804576,0.000054360342,0.14645936,0.00045631587,0.82734376],"study_design_scores_gemma":[0.00015930705,0.0000054038746,0.00015350082,0.0005066639,0.0000071475356,0.000013929637,0.00003837414,0.6232504,0.000017260392,0.00074638426,0.3748258,0.0002757999],"about_ca_topic_score_codex":0.000010950284,"about_ca_topic_score_gemma":0.000010814882,"teacher_disagreement_score":0.827068,"about_ca_system_score_codex":0.00025322454,"about_ca_system_score_gemma":0.00015513942,"threshold_uncertainty_score":0.9999737},"labels":[],"label_agreement":null},{"id":"W4412962459","doi":"10.1007/978-3-031-93691-3","title":"Computer Vision and Image Processing","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute for Materials Science; University at Albany; University of Texas MD Anderson Cancer Center; University of California, Santa Barbara; Samsung; International Institute of Information Technology, Hyderabad; Dr B R Ambedkar National Institute of Technology Jalandhar; Malaviya National Institute of Technology, Jaipur; Motilal Nehru National Institute of Technology Allahabad; University of Mysore; National Institute of Technology, Patna; Universitat Autònoma de Barcelona; National Institute of Technology Rourkela; Indian Institute of Technology Delhi; College of Engineering, Michigan State University; National Taipei University of Technology; Southeast University; Indian Institute of Technology, Patna; Birla Institute of Technology and Science, Pilani; Indian Institute of Technology Jodhpur; South China University of Technology; Indian Institute of Technology Roorkee; Zhejiang University; Università degli Studi di Pavia; Akademie Věd České Republiky; National Institute of Technology Hamirpur; Indian Institute of Technology Indore; Khalifa University of Science, Technology and Research; Indian Institute of Technology Madras; Visvesvaraya National Institute of Technology; Rijksuniversiteit Groningen; Westfälische Wilhelms-Universität Münster; Amity University; Indian Institute of Technology Kanpur; Indian Institute of Technology Tirupati; Vellore Institute of Technology, Chennai; Universitetet i Tromsø; University of Alberta; Florida Atlantic University; Indian Institute of Technology Palakkad; University of Pittsburgh; Jawaharlal Nehru University; Indian Institute of Technology Gandhinagar; National Institute of Technology Warangal; King Mongkut's Institute of Technology Ladkrabang; Universidad del Atlántico; Indian Space Research Organisation; National Institute of Technology Sikkim; Concordia University; Trinity College Dublin; Indian National Science Academy; Jadavpur University; National Institute of Technology Calicut; Università degli Studi di Milano; University of Salford Manchester; Case Western Reserve University; University of Windsor; Indian Institute of Technology (BHU) Varanasi; Indian Institute of Technology Bombay; University of South Florida; National Institute of Technology, Raipur; Michigan State University; National Institute of Technology Delhi; Indian Institute of Technology Kharagpur; Indian Institute of Science; University at Buffalo; University of Rochester; Universidade do Porto; University of Central Florida; Maulana Azad National Institute of Technology; Indian Institute of Technology Guwahati; Johns Hopkins University; Lehigh University; Netaji Subhas University of Technology; Cleveland State University","keywords":"Computer science; Computer vision; Image processing; Artificial intelligence; Information retrieval; Computer graphics (images); Image (mathematics)","score_opus":0.019486899296515748,"score_gpt":0.28422884439111173,"score_spread":0.264741945094596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412962459","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006269541,0.0015675382,0.5510581,0.00020231468,0.0013145208,0.0008585232,0.000024634133,0.00038449504,0.4439629],"genre_scores_gemma":[0.5410645,0.018975396,0.4145321,0.0028569216,0.0016130861,0.000319441,0.0006593624,0.00013688649,0.019842355],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990322,0.00002249962,0.00047384342,0.00013406195,0.00019921469,0.00013819066],"domain_scores_gemma":[0.9990008,0.000092411865,0.0000949179,0.000571905,0.00018852553,0.000051466934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006414636,0.0001546347,0.00020347374,0.00081353646,0.00032829694,0.000624777,0.00046741118,0.0001482958,0.0000020439945],"category_scores_gemma":[0.000013214985,0.00014675206,0.000020841127,0.00046045796,0.00033173602,0.003222004,0.0005495667,0.00036748557,0.000012240962],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021276894,0.000004802781,0.0000073112733,0.00021471526,0.0000033026347,1.8139934e-7,0.000750127,0.0007958103,0.000012201257,0.0025127027,0.006351873,0.98934484],"study_design_scores_gemma":[0.00020743479,0.000030980165,0.0003989804,0.0006145119,0.0000041296116,0.000014164951,0.000014688361,0.77922773,0.000010678459,0.00025735263,0.21905103,0.0001683352],"about_ca_topic_score_codex":0.0000047450494,"about_ca_topic_score_gemma":0.0000026430669,"teacher_disagreement_score":0.9891765,"about_ca_system_score_codex":0.00014662305,"about_ca_system_score_gemma":0.00016675548,"threshold_uncertainty_score":0.6024739},"labels":[],"label_agreement":null},{"id":"W4412964784","doi":"10.1007/978-3-031-93688-3_14","title":"A Transfer Learning Approach for Emotion Recognition Integrated with Cognitive Evaluation in Virtual Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Transfer of learning; Computer science; Cognition; Artificial intelligence; Human–computer interaction; Cognitive science; Information retrieval; Psychology; Neuroscience","score_opus":0.0897589473525127,"score_gpt":0.34573571690946586,"score_spread":0.25597676955695314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412964784","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003232384,0.00015435343,0.62310416,0.0001303057,0.00019824422,0.001950829,0.00003924848,0.00008303387,0.37110746],"genre_scores_gemma":[0.96614355,0.0009908567,0.015699638,0.0006525864,0.000049217666,0.000939336,0.008263522,0.00003093157,0.0072303456],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982557,0.00021505129,0.00064447307,0.00033889717,0.00033110043,0.00021474047],"domain_scores_gemma":[0.9979654,0.00034314347,0.00021144691,0.0003222141,0.0011137926,0.000043988228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022494716,0.00022635722,0.00025830723,0.0017149606,0.00039308588,0.00017384996,0.00034823237,0.00024107749,0.0000676406],"category_scores_gemma":[0.00015001599,0.00022425021,0.0000460994,0.0005534254,0.00045813702,0.0022944363,0.000109448694,0.00086494227,0.000023867724],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010543685,0.000065909284,0.00004741769,0.00004366026,0.000019218985,1.0892e-7,0.0061098086,0.0022024594,0.0000028284653,0.025807437,0.000026696513,0.965569],"study_design_scores_gemma":[0.0057803807,0.00087856763,0.0019315424,0.0021662521,0.000134271,0.0000321845,0.0055220965,0.95966643,0.000019938665,0.001838617,0.021292906,0.0007367837],"about_ca_topic_score_codex":0.000022799295,"about_ca_topic_score_gemma":0.000023871451,"teacher_disagreement_score":0.96483225,"about_ca_system_score_codex":0.00021029773,"about_ca_system_score_gemma":0.00028763537,"threshold_uncertainty_score":0.91446584},"labels":[],"label_agreement":null},{"id":"W4412991222","doi":"10.1007/978-3-031-93601-2_8","title":"A New Hybrid Algorithm to Diagnose MS Using MRI Image Processing","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Image processing; Algorithm; Artificial intelligence; Pattern recognition (psychology); Computer vision; Image (mathematics)","score_opus":0.025165923313505596,"score_gpt":0.30507933174684315,"score_spread":0.27991340843333756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412991222","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008302267,0.00042941034,0.8580879,0.0010698297,0.00020160555,0.00036065758,0.00002528224,0.0001393691,0.13967764],"genre_scores_gemma":[0.0008146803,0.0002718417,0.9950636,0.0019235293,0.000035704896,0.000015197156,0.000029172556,0.000008538666,0.0018377398],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981659,0.000015996498,0.0006260716,0.0003861711,0.0005014526,0.00030441929],"domain_scores_gemma":[0.99678934,0.00013021701,0.00024880492,0.0020874883,0.00048117782,0.0002629471],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00045455174,0.0002645587,0.00025975073,0.0014421309,0.000451557,0.0028464582,0.004425208,0.00004919976,0.0000045469087],"category_scores_gemma":[0.000077924284,0.00028521346,0.000055677665,0.0008126676,0.00043642687,0.015074134,0.005059174,0.0002658236,0.000045541306],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.5923535e-7,0.000016266056,0.000007704673,0.000027189099,0.0000032444375,0.0000013002274,0.00048716526,0.00015778688,0.0000014869084,0.062596455,0.0022048,0.9344959],"study_design_scores_gemma":[0.00022624353,0.000029401257,0.00010935741,0.0007437549,0.000010330153,0.00003578641,0.000007699244,0.8455689,0.00004902485,0.011463688,0.14134383,0.00041195174],"about_ca_topic_score_codex":0.000049284823,"about_ca_topic_score_gemma":0.000003839875,"teacher_disagreement_score":0.934084,"about_ca_system_score_codex":0.00018920584,"about_ca_system_score_gemma":0.0012360085,"threshold_uncertainty_score":0.99996},"labels":[],"label_agreement":null},{"id":"W4413056540","doi":"10.1007/978-981-96-7036-9_27","title":"StreetSyn: A Full Radiance Field Solution for Street and Vehicle Free-View Synthesis","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Radiance; Computer science; Field (mathematics); Remote sensing; Computer graphics (images); Geography; Mathematics","score_opus":0.03408940658566386,"score_gpt":0.30826306628656563,"score_spread":0.2741736597009018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413056540","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010943671,0.0009372813,0.9803234,0.0025613322,0.0001648605,0.00054916,0.000035132896,0.00013254816,0.015285357],"genre_scores_gemma":[0.048313618,0.0303578,0.91237736,0.0069942963,0.00010930732,0.00046302445,0.000097090124,0.000026139183,0.0012613673],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853563,0.000030105677,0.0006035112,0.00035173545,0.00026246192,0.0002165388],"domain_scores_gemma":[0.9965825,0.00068897667,0.00028004058,0.0019609174,0.00039758428,0.00009000058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008533166,0.00021799996,0.00027685074,0.00097599765,0.00053259765,0.0006560711,0.002889081,0.00014994094,0.0000020595528],"category_scores_gemma":[0.0001299906,0.00023265113,0.000055974655,0.00045308573,0.00038420316,0.0033756988,0.0026724036,0.00023269316,0.0000015144186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013616176,0.0000070943015,0.000020499021,0.00005244276,0.0000036055167,5.7010975e-8,0.00017223084,0.0000024497435,8.113276e-7,0.64968747,0.0012980516,0.34875393],"study_design_scores_gemma":[0.00019700454,0.000094509654,0.00019626433,0.0004932362,0.000007985756,0.000003783606,0.0000040990753,0.8393849,0.000042798405,0.02779449,0.13151689,0.0002640303],"about_ca_topic_score_codex":0.000025833706,"about_ca_topic_score_gemma":0.0000617468,"teacher_disagreement_score":0.83938247,"about_ca_system_score_codex":0.000069328555,"about_ca_system_score_gemma":0.0002381633,"threshold_uncertainty_score":0.9487238},"labels":[],"label_agreement":null},{"id":"W4413056564","doi":"10.1007/978-981-96-7036-9_13","title":"Behavior-Driven Data Augmentation for Non-Intrusive Load Monitoring","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science","score_opus":0.05354484732171682,"score_gpt":0.3133949376341959,"score_spread":0.2598500903124791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413056564","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019282779,0.00034508327,0.68696296,0.00022557152,0.002384202,0.0014392318,0.00017207397,0.00022527078,0.30805275],"genre_scores_gemma":[0.15759382,0.022654448,0.805006,0.0007151882,0.000676064,0.0012063005,0.004113811,0.000089325215,0.007945006],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905896,0.0000041323374,0.00040928167,0.00015932492,0.000231269,0.00013702534],"domain_scores_gemma":[0.9978399,0.000097504155,0.00008970511,0.0017304192,0.00020489628,0.00003753958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037124453,0.00014601703,0.0001414502,0.0004945755,0.00021778602,0.00022467866,0.0018114416,0.000068881694,0.0000032016737],"category_scores_gemma":[0.000018307886,0.00016999326,0.000019224131,0.0001660631,0.0001810029,0.0029810057,0.0015643575,0.00017120241,0.000011225465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055822006,0.000021237718,0.00032971113,0.00031946014,0.000051725787,3.8085506e-7,0.0020199814,0.09796257,0.000022354256,0.0994348,0.008385386,0.7914468],"study_design_scores_gemma":[0.00023075071,0.000010905499,0.0012032515,0.00020675476,0.000021190965,8.994163e-7,0.000026857922,0.82833326,0.00002206643,0.0002100184,0.16955683,0.00017723833],"about_ca_topic_score_codex":0.000008081727,"about_ca_topic_score_gemma":0.00000994565,"teacher_disagreement_score":0.79126954,"about_ca_system_score_codex":0.00031803735,"about_ca_system_score_gemma":0.00010762091,"threshold_uncertainty_score":0.6932124},"labels":[],"label_agreement":null},{"id":"W4413060070","doi":"10.1007/978-981-96-6465-8_13","title":"Compatibility Assessment of 5G Macro Stations with GSM-R Systems in High-Speed Railway","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Transportation Systems and Safety","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; École de Technologie Supérieure","funders":"","keywords":"Compatibility (geochemistry); Macro; GSM; Computer science; Reliability engineering; Telecommunications; Engineering; Chemical engineering","score_opus":0.027371938744460672,"score_gpt":0.29914979954520127,"score_spread":0.2717778608007406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413060070","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00075258454,0.00022934539,0.83766526,0.0005402938,0.0003657135,0.0011263298,0.000118335825,0.00007509533,0.15912701],"genre_scores_gemma":[0.88651097,0.00045676794,0.112053566,0.00015610237,0.000009033812,0.00003859943,0.00012717399,0.0000060342322,0.0006417694],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973431,0.00008069777,0.0013992811,0.00033658626,0.0006336206,0.00020670026],"domain_scores_gemma":[0.9959873,0.0003572613,0.0006475547,0.0021559172,0.0007731479,0.000078847304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016102287,0.00022763682,0.00047798938,0.0012932401,0.00024983077,0.00033114443,0.0023153655,0.00010911083,0.000003610829],"category_scores_gemma":[0.000014724817,0.00020688373,0.000039050465,0.0009275483,0.00063499034,0.0039248397,0.00043453608,0.00038437243,0.000003571828],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002972523,0.00003351551,0.002553726,0.00012820757,0.000008186546,4.121751e-7,0.0015600427,0.0073420433,0.000002203777,0.9747223,0.00003406504,0.013612317],"study_design_scores_gemma":[0.0011498891,0.00010882405,0.257615,0.0011707903,0.0000102579925,0.000008476963,0.00010787603,0.72024196,0.000004055968,0.0034512824,0.015697533,0.0004340673],"about_ca_topic_score_codex":0.00036418895,"about_ca_topic_score_gemma":0.00026718044,"teacher_disagreement_score":0.97127104,"about_ca_system_score_codex":0.00022368037,"about_ca_system_score_gemma":0.00093352806,"threshold_uncertainty_score":0.8436474},"labels":[],"label_agreement":null},{"id":"W4413060109","doi":"10.1007/978-981-96-6465-8_1","title":"Inter-system Interference and Optimal Utilisation of Resources in 1800 MHz Band 5G Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Telecommunications and Broadcasting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Interference (communication); Computer science; Telecommunications","score_opus":0.02461925703582301,"score_gpt":0.24542093311152946,"score_spread":0.22080167607570644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413060109","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026052501,0.0075035943,0.45743272,0.0005624505,0.0005395769,0.0012175147,0.00006708514,0.00080906175,0.5058155],"genre_scores_gemma":[0.9731854,0.00387368,0.0227786,0.000017292798,0.0000056601516,0.000018438994,0.00002234053,0.0000053349577,0.000093244606],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989765,0.000018998495,0.00065118127,0.00012297736,0.00010168708,0.00012862058],"domain_scores_gemma":[0.99840325,0.000217993,0.00015745277,0.0010666285,0.00012998134,0.000024679292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054575637,0.00015142576,0.0002354604,0.001039275,0.00012417098,0.00014279912,0.0012186556,0.00014368503,0.0000019008389],"category_scores_gemma":[0.00003934978,0.00015664917,0.000019011351,0.00034803225,0.0007148133,0.001116405,0.0008099763,0.00043073753,0.0000011169353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008438023,0.000016763146,0.000932034,0.0003554174,0.00001543067,1.8330778e-7,0.0040306523,0.024278069,0.000014055413,0.12395218,0.00019374948,0.846203],"study_design_scores_gemma":[0.00016231758,0.000030553507,0.002308742,0.0012916481,0.0000052681876,0.0000070657093,0.0002920796,0.98034406,0.00002142016,0.00031692913,0.015048573,0.0001713663],"about_ca_topic_score_codex":0.000022139131,"about_ca_topic_score_gemma":0.00003899255,"teacher_disagreement_score":0.95606595,"about_ca_system_score_codex":0.000113879665,"about_ca_system_score_gemma":0.000039054725,"threshold_uncertainty_score":0.6387968},"labels":[],"label_agreement":null},{"id":"W4413060220","doi":"10.1007/978-981-96-6465-8_31","title":"Leveraging Artificial Neural Networks for Accurate Short-Term Traffic Prediction in Centralized SDN Architecture","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; École de Technologie Supérieure","funders":"","keywords":"Term (time); Computer science; Artificial neural network; Architecture; Artificial intelligence; Computer architecture; History","score_opus":0.04391758709610501,"score_gpt":0.28837959649620404,"score_spread":0.24446200940009905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413060220","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037511394,0.00055436225,0.9914772,0.00089926686,0.0008573015,0.0008437076,0.000020259144,0.00015799185,0.0048148176],"genre_scores_gemma":[0.7705241,0.0038066027,0.21996585,0.0029126983,0.00044703225,0.00039742285,0.00070511654,0.000042406977,0.0011987785],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796975,0.000044945395,0.0009057401,0.0003933649,0.0002889462,0.0003972844],"domain_scores_gemma":[0.9976392,0.0004439111,0.00022417065,0.0013858315,0.00021624292,0.00009068984],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009008936,0.00027398297,0.00032185437,0.0010311175,0.00048883166,0.0008015429,0.0024945133,0.00018869647,0.0000025611926],"category_scores_gemma":[0.0000414612,0.00027743485,0.00008083003,0.0006721438,0.00035775,0.0030151738,0.0011700862,0.0006239658,0.0000019792815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012214126,0.000018574869,0.00010738647,0.000035952624,0.000005682549,4.5627013e-7,0.001241729,0.19120938,5.0823525e-7,0.06503504,0.00036429067,0.7419688],"study_design_scores_gemma":[0.00029668608,0.00003724767,0.0014075284,0.00027660656,0.000006186767,0.000009678069,0.0000072904877,0.98209345,9.679561e-7,0.0023739198,0.013252671,0.00023773378],"about_ca_topic_score_codex":0.000004794909,"about_ca_topic_score_gemma":0.000023199587,"teacher_disagreement_score":0.79088414,"about_ca_system_score_codex":0.0001572089,"about_ca_system_score_gemma":0.00024333573,"threshold_uncertainty_score":0.99996775},"labels":[],"label_agreement":null},{"id":"W4413060228","doi":"10.1007/978-981-96-6465-8_17","title":"Enhancing Rail Network Efficiency with Advanced 5G Connectivity Solutions","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Network Time Synchronization Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Concordia University","funders":"","keywords":"Computer science; Computer network","score_opus":0.015350207955295842,"score_gpt":0.24754484493018616,"score_spread":0.23219463697489032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413060228","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012247017,0.0010274106,0.8318395,0.00091264624,0.00024557262,0.0004574326,0.00000464901,0.00036163194,0.16513889],"genre_scores_gemma":[0.14915982,0.0053560566,0.8395626,0.0015528959,0.0000629042,0.00015458855,0.00006844427,0.000023319293,0.0040594097],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979092,0.000043002543,0.000687395,0.000444735,0.00045824307,0.00045745278],"domain_scores_gemma":[0.995519,0.0004710652,0.00044767663,0.002890497,0.00060631393,0.00006544083],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012400423,0.00029522716,0.0003369445,0.0009732777,0.0012300259,0.0005983254,0.0041527823,0.0001683996,0.0000069042153],"category_scores_gemma":[0.00010672303,0.00028369666,0.000041001167,0.001628985,0.0013755119,0.0061874967,0.003291501,0.0005909797,0.000031723324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015381759,0.000010957351,0.000015352853,0.0000183053,0.0000053237154,2.5926536e-7,0.00028337512,0.007462528,0.0000015054471,0.7286764,0.00023785509,0.2632866],"study_design_scores_gemma":[0.00058579893,0.00015988637,0.00047097352,0.0009973985,0.000012676185,0.000029906218,0.000029773695,0.8379414,0.00005621452,0.027066365,0.13192888,0.0007207185],"about_ca_topic_score_codex":0.0000063006432,"about_ca_topic_score_gemma":0.000040584466,"teacher_disagreement_score":0.8304789,"about_ca_system_score_codex":0.0002878271,"about_ca_system_score_gemma":0.0008145974,"threshold_uncertainty_score":0.9999615},"labels":[],"label_agreement":null},{"id":"W4413065313","doi":"10.1007/978-981-96-6294-4_20","title":"Word Embedding Bias in Large Language Models","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Word (group theory); Word embedding; Computer science; Natural language processing; Embedding; Linguistics; Artificial intelligence; Philosophy","score_opus":0.0730375053919994,"score_gpt":0.33158081651414867,"score_spread":0.2585433111221493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413065313","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009455665,0.0004598268,0.76343036,0.0005500591,0.00018947004,0.00022769863,0.000006378019,0.00007176496,0.23496987],"genre_scores_gemma":[0.26188263,0.0030513343,0.72589904,0.0030880133,0.00005051066,0.000056351128,0.00005976254,0.00001316941,0.005899203],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99834603,0.00003359534,0.00069168286,0.00029925184,0.0003579338,0.00027147977],"domain_scores_gemma":[0.9970648,0.00021274353,0.00020899957,0.0022848186,0.00016563355,0.00006297153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015100653,0.000183253,0.00023941562,0.0015638978,0.00025295187,0.00053091376,0.0036592945,0.00011929945,0.000004048716],"category_scores_gemma":[0.000050711453,0.00019306941,0.00003724145,0.0005832104,0.00020374132,0.0070076236,0.0037697959,0.0004987004,0.0000169573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.8077226e-7,0.000007750841,0.00002479954,0.000018715367,0.0000014051965,5.2880915e-7,0.0040122382,0.0037449447,3.550023e-7,0.7850717,0.000056103847,0.20706098],"study_design_scores_gemma":[0.00020081426,0.000006100621,0.000111404166,0.000319138,0.0000013110675,0.000004332381,0.000047478137,0.9689337,0.0000018342262,0.016062783,0.014128646,0.0001824532],"about_ca_topic_score_codex":0.000028682383,"about_ca_topic_score_gemma":0.000050169107,"teacher_disagreement_score":0.96518874,"about_ca_system_score_codex":0.00017858669,"about_ca_system_score_gemma":0.00031977816,"threshold_uncertainty_score":0.78731424},"labels":[],"label_agreement":null},{"id":"W4413159051","doi":"10.1007/978-3-031-94937-1_4","title":"Domestic Abuse Survivor Assistance Through Forecasting and Engagement with Artificial Intelligence Solutions","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Operations research; Data science; Engineering","score_opus":0.126449363245237,"score_gpt":0.2824650616626889,"score_spread":0.15601569841745191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413159051","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002942,0.0016642475,0.657954,0.0005017183,0.00024792724,0.0004754978,0.000072877556,0.000031746076,0.3387578],"genre_scores_gemma":[0.7637841,0.04016324,0.19027315,0.0016103043,0.0000927038,0.00017533683,0.0001213597,0.00002621954,0.0037535613],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986271,0.000009723045,0.0007772355,0.00027253377,0.000087783395,0.00022557998],"domain_scores_gemma":[0.9984493,0.0001549089,0.0004092677,0.00081041554,0.00013938303,0.000036682257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011959381,0.00017211084,0.0002754357,0.00059356197,0.000729857,0.00034409112,0.00068763446,0.00007243912,0.000009114763],"category_scores_gemma":[0.000051690615,0.00018578244,0.00002743828,0.0003805145,0.0007488741,0.0023392844,0.00058977597,0.00031670753,0.00003050764],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000039499455,0.000011890524,0.0002140079,0.0000397885,0.0000063572256,3.366189e-7,0.001543721,0.0002797291,2.6029596e-8,0.9325251,0.00003910177,0.065336],"study_design_scores_gemma":[0.00025787414,0.00012838678,0.005149589,0.0007829999,0.000018055285,0.000009998947,0.00025578434,0.29424226,0.0000015104932,0.33137223,0.36704352,0.0007377864],"about_ca_topic_score_codex":0.00006307701,"about_ca_topic_score_gemma":0.00012443874,"teacher_disagreement_score":0.7634899,"about_ca_system_score_codex":0.00013197844,"about_ca_system_score_gemma":0.00007711281,"threshold_uncertainty_score":0.7575988},"labels":[],"label_agreement":null},{"id":"W4413159459","doi":"10.1007/978-3-031-94937-1_7","title":"Advanced Forecasting of CCPP Output Power Using Regression and Neural Network Models","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Artificial neural network; Regression; Computer science; Econometrics; Statistics; Artificial intelligence; Mathematics","score_opus":0.052464129468286484,"score_gpt":0.26830660703749637,"score_spread":0.21584247756920988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413159459","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013099133,0.0061033685,0.23696613,0.00008196496,0.0012250966,0.0005332631,0.000036884085,0.0001946581,0.7417595],"genre_scores_gemma":[0.8488423,0.0026326792,0.14792514,0.0001198661,0.000032562944,0.0000059233334,0.00003608516,0.000015369798,0.00039007413],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990794,0.000009173523,0.00049295626,0.0001070973,0.00015230419,0.0001590407],"domain_scores_gemma":[0.99899364,0.00013565384,0.00015965327,0.00053159555,0.00013526529,0.000044180353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034010308,0.00015677254,0.00021131727,0.00038728243,0.00022878888,0.000087370565,0.00047099846,0.0000891955,0.0000013747201],"category_scores_gemma":[0.000015519963,0.00015309168,0.000025012014,0.00021165986,0.00030024862,0.0022546523,0.0006514228,0.00026365998,2.2793799e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020758812,0.0000016319606,0.000024559431,0.0000694603,0.00000429038,1.101956e-7,0.00080108165,0.76790535,0.0000046124073,0.043947667,0.000039172846,0.18719997],"study_design_scores_gemma":[0.000118062715,0.000011759847,0.00002851911,0.0010603301,0.0000048288503,0.000008366569,0.000014995537,0.99254155,0.000008627301,0.0016933357,0.004373295,0.00013630102],"about_ca_topic_score_codex":0.0000039659626,"about_ca_topic_score_gemma":0.000003414501,"teacher_disagreement_score":0.8357432,"about_ca_system_score_codex":0.000046253,"about_ca_system_score_gemma":0.000048447524,"threshold_uncertainty_score":0.62428975},"labels":[],"label_agreement":null},{"id":"W4413188043","doi":"10.1007/978-3-031-95133-6_7","title":"Enhancing IoT Security with EAP-PWD: A Resource-Efficient Authentication Solution for Manufacturer Usage Description (MUD)-Based Environments","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Internet of Things; Authentication (law); Computer science; Computer security; Resource (disambiguation); Computer network","score_opus":0.0249136248174997,"score_gpt":0.25572912853796964,"score_spread":0.23081550372046994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413188043","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045951898,0.00014698085,0.9863331,0.0014103011,0.00023257606,0.0013759438,0.000031487867,0.00010619486,0.009903915],"genre_scores_gemma":[0.85355496,0.00014505527,0.14065287,0.0016865156,0.000055900684,0.00035032813,0.00040570815,0.000024184674,0.0031244769],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747217,0.00008039793,0.0009031478,0.0005246087,0.00067855336,0.00034113237],"domain_scores_gemma":[0.99644434,0.00026323443,0.0005811646,0.0023206603,0.00026105708,0.00012952705],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016781566,0.00032015482,0.0003147872,0.0012217937,0.00082583714,0.00080950203,0.002363183,0.00019498113,0.0000053160084],"category_scores_gemma":[0.00005018574,0.00030856338,0.000078274745,0.00042617047,0.00059279747,0.0019285706,0.0008391069,0.00036720702,0.000026215057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069002795,0.0004129191,0.000102883154,0.0006732823,0.000064204396,7.7639714e-7,0.060494773,0.0016268386,0.00034290127,0.815493,0.0009725854,0.11974687],"study_design_scores_gemma":[0.00055089867,0.00007736813,0.0003967575,0.00041916585,0.000019812349,0.0000055304436,0.000032134343,0.8777645,0.00023549295,0.0026110387,0.117559314,0.00032797127],"about_ca_topic_score_codex":0.000013601524,"about_ca_topic_score_gemma":0.000034385626,"teacher_disagreement_score":0.8761377,"about_ca_system_score_codex":0.0004198113,"about_ca_system_score_gemma":0.0003705639,"threshold_uncertainty_score":0.99993664},"labels":[],"label_agreement":null},{"id":"W4413198398","doi":"10.1007/978-981-95-0568-5_6","title":"Transforming Digital Reminder Systems for Dementia Care into Behavioral Anomaly Detectors: A Proof-of-Concept Using LSTM Autoencoders","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Anomaly detection; Dementia; Anomaly (physics); Detector; Proof of concept; Artificial intelligence; Medicine; Internal medicine; Operating system; Telecommunications; Physics","score_opus":0.057610786490878335,"score_gpt":0.3154515934599823,"score_spread":0.25784080696910394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413198398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003195292,0.0015072026,0.98592216,0.00006282675,0.0005078309,0.0014582077,0.00006746898,0.00007240554,0.010082383],"genre_scores_gemma":[0.90529615,0.00006269654,0.094124265,0.00006705947,0.000030147823,0.00012325298,0.0000962647,0.000012739023,0.00018742082],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977877,0.000032108477,0.0010868333,0.00036988017,0.00045973723,0.0002637452],"domain_scores_gemma":[0.9965651,0.00026941946,0.0005943055,0.0014479975,0.0010347799,0.000088412686],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005715599,0.00027982506,0.00042387962,0.0012108507,0.0005114594,0.001010351,0.002457624,0.00017953562,0.0000011950502],"category_scores_gemma":[0.000034003904,0.00030141673,0.00011646483,0.0004945903,0.0005915698,0.00979695,0.001051127,0.00027469336,0.0000012845296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007436594,0.0000441963,0.00014849074,0.00050004607,0.00004404165,4.0582856e-7,0.021427883,0.0012985384,0.000016419299,0.04470452,0.000052664098,0.93175536],"study_design_scores_gemma":[0.0006923757,0.00017403251,0.0000350567,0.0016608634,0.00005073955,0.000031553398,0.00070010213,0.9545847,0.00038905116,0.000812797,0.040272463,0.00059627666],"about_ca_topic_score_codex":0.00009108982,"about_ca_topic_score_gemma":0.00003491122,"teacher_disagreement_score":0.9532862,"about_ca_system_score_codex":0.00033009492,"about_ca_system_score_gemma":0.00085657684,"threshold_uncertainty_score":0.9999438},"labels":[],"label_agreement":null},{"id":"W4413211177","doi":"10.1007/978-3-031-94962-3_3","title":"Comparative Analysis of YOLOv8 and RT-DETR for Real-Time Object Detection in Advanced Driver Assistance Systems","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Object (grammar); Real-time computing; Information retrieval; Artificial intelligence","score_opus":0.029157463257096772,"score_gpt":0.3149333548097675,"score_spread":0.2857758915526707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413211177","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001234081,0.0005576819,0.9588219,0.00016461914,0.000127751,0.0013306154,0.0000635106,0.0000765796,0.03762324],"genre_scores_gemma":[0.69404143,0.0062335473,0.29736206,0.00019664348,0.000020193782,0.00042905172,0.00014382275,0.000010537691,0.001562709],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818724,0.000047075704,0.00089434214,0.00039607182,0.0002695601,0.00020571258],"domain_scores_gemma":[0.99638176,0.00084262213,0.0006315985,0.0015797119,0.00050235627,0.00006194053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067693024,0.00021672172,0.0005759054,0.0020279118,0.00030820663,0.00019867628,0.0016360016,0.00011131078,7.687566e-7],"category_scores_gemma":[0.00003596902,0.00022898133,0.00006349696,0.002073302,0.00061400747,0.0032999215,0.0009657829,0.00024173019,0.000002157146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025251786,0.000044015243,0.00017759834,0.00011867213,0.000093741815,1.7787917e-7,0.002533044,0.03807695,0.00024236497,0.7431683,0.00007992936,0.21543996],"study_design_scores_gemma":[0.00029551686,0.000051870127,0.0061082644,0.00017627036,0.000038956692,0.0000019022374,0.00002882861,0.98356485,0.000051651445,0.0022055914,0.0072535593,0.00022273486],"about_ca_topic_score_codex":0.000025150752,"about_ca_topic_score_gemma":0.00009588787,"teacher_disagreement_score":0.9454879,"about_ca_system_score_codex":0.00020316271,"about_ca_system_score_gemma":0.00015188666,"threshold_uncertainty_score":0.93375874},"labels":[],"label_agreement":null},{"id":"W4413211245","doi":"10.1007/978-3-031-94962-3_2","title":"Leveraging Bayer Pattern Analysis for Authenticity Detection of Real and Fake Images","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Information retrieval; Artificial intelligence","score_opus":0.02760109058008395,"score_gpt":0.2741720442620276,"score_spread":0.24657095368194368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413211245","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004693716,0.000069725254,0.9720224,0.00017410105,0.00025218964,0.00030363697,0.000019138362,0.000047122907,0.026642326],"genre_scores_gemma":[0.94870615,0.0007549422,0.04969152,0.00016818603,0.000016765245,0.00003299806,0.000030361296,0.0000046072832,0.0005944807],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875414,0.00001770063,0.0005607956,0.00025019288,0.0002724325,0.0001447279],"domain_scores_gemma":[0.9977538,0.0002913648,0.00034225796,0.0011335682,0.00042492512,0.00005405883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074461143,0.00014994903,0.00026864794,0.0016480249,0.00023524844,0.00039654845,0.0011229268,0.00006883773,7.4604225e-7],"category_scores_gemma":[0.00006257559,0.00015432772,0.00006774684,0.0006645695,0.00052758044,0.0037251506,0.0012395241,0.00016443105,0.0000013065008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019501397,0.00000785814,0.00017985787,0.00005625405,0.00003071078,6.0704934e-8,0.0010327188,0.000095405696,0.000014593844,0.032021374,0.000017724456,0.96654147],"study_design_scores_gemma":[0.00030926598,0.00007904429,0.011065739,0.0001728828,0.000070058,0.000006804411,0.000031091604,0.9705879,0.00048445252,0.009935526,0.006985696,0.00027153295],"about_ca_topic_score_codex":0.000052086623,"about_ca_topic_score_gemma":0.000043738768,"teacher_disagreement_score":0.9704925,"about_ca_system_score_codex":0.000081577724,"about_ca_system_score_gemma":0.00010428466,"threshold_uncertainty_score":0.62933016},"labels":[],"label_agreement":null},{"id":"W4413211394","doi":"10.1007/978-3-031-94962-3_7","title":"A Novel Image Enhancement Method for Dimmed Displays Based on JND and Human Frequency Sensitivity","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sensitivity (control systems); Just-noticeable difference; Computer science; Computer vision; Image (mathematics); Artificial intelligence; Electronic engineering; Engineering","score_opus":0.027998442114876253,"score_gpt":0.32426277051125846,"score_spread":0.2962643283963822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413211394","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000023573572,0.000048839713,0.9459814,0.00029694234,0.000061135586,0.0003732931,0.000043045377,0.0001301534,0.053041648],"genre_scores_gemma":[0.021872597,0.00019540142,0.9774461,0.00024938572,0.0000057278307,0.00005790961,0.000056547393,0.0000070025376,0.00010932257],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924874,0.0000070694855,0.00031867804,0.00015049687,0.0001292395,0.00014577556],"domain_scores_gemma":[0.99843353,0.00045497293,0.00007223352,0.00087104924,0.0001351411,0.000033060034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005008525,0.00016131665,0.00018196397,0.00048713817,0.00025108224,0.00014125777,0.00045154322,0.00007787505,0.0000011049268],"category_scores_gemma":[0.00008660211,0.00016462496,0.000022313176,0.00013687095,0.0005425809,0.0011620129,0.00043655405,0.0002788185,0.0000016761825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000317704,0.000025021278,0.000011886459,0.0002272021,0.000009672755,2.0010721e-7,0.00030157162,0.0032516657,0.0022606547,0.7399019,0.00015077298,0.25385627],"study_design_scores_gemma":[0.00026515758,0.00003185706,0.00025640364,0.00027769365,0.0000074193995,0.0000017726034,0.000008686398,0.98761034,0.0004021547,0.007642866,0.0032998996,0.00019575475],"about_ca_topic_score_codex":0.0000031535112,"about_ca_topic_score_gemma":0.0000062607955,"teacher_disagreement_score":0.98435867,"about_ca_system_score_codex":0.00012418082,"about_ca_system_score_gemma":0.00003619336,"threshold_uncertainty_score":0.6713211},"labels":[],"label_agreement":null},{"id":"W4413223202","doi":"10.1007/978-981-95-0568-5_5","title":"Rehabilitation Exercise Quality Assessment and Feedback Generation Using Large Language Models with Prompt Engineering","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Rehabilitation; Computer science; Quality (philosophy); Physical medicine and rehabilitation; Medicine; Physical therapy; Physics","score_opus":0.047663207456738056,"score_gpt":0.351483552390553,"score_spread":0.30382034493381493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223202","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.111885704,0.0026749496,0.78842354,0.0026003125,0.00052471575,0.0045413966,0.00011863195,0.00022091705,0.089009844],"genre_scores_gemma":[0.3653417,0.001684474,0.63116336,0.00038091952,0.000046581223,0.00006299357,0.00026683998,0.000014346058,0.0010387995],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886346,0.000022684904,0.00049669214,0.0001922818,0.00030048535,0.00012440833],"domain_scores_gemma":[0.9984843,0.00021416305,0.00017330915,0.0007050159,0.00035517628,0.00006804256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089097413,0.00015015839,0.0002656136,0.00072450744,0.000208405,0.00014299534,0.00017852841,0.00009569338,0.0000047879676],"category_scores_gemma":[0.00004926639,0.00013228563,0.00003260897,0.00021596049,0.00028271688,0.0019844025,0.00026211335,0.00026040792,0.0000011086905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077487035,0.000193151,0.0044992254,0.002148323,0.00006220431,8.9578987e-7,0.01783066,0.013817915,0.00039434314,0.69724333,0.00025207424,0.26348042],"study_design_scores_gemma":[0.0007265844,0.000094939765,0.015783917,0.0011956994,0.000029314935,0.000010109157,0.00026037192,0.9791251,0.000007607599,0.0002998091,0.002287487,0.00017908927],"about_ca_topic_score_codex":0.000014880826,"about_ca_topic_score_gemma":0.000007410173,"teacher_disagreement_score":0.9653072,"about_ca_system_score_codex":0.0002376583,"about_ca_system_score_gemma":0.00035958012,"threshold_uncertainty_score":0.5394451},"labels":[],"label_agreement":null},{"id":"W4413223212","doi":"10.1007/978-981-95-0568-5_1","title":"Early Prediction of Agitation in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning: Benchmarking of State-of-the-Art Techniques","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Benchmarking; Computer science; Artificial intelligence; State (computer science); Dementia; Medicine; Programming language; Management","score_opus":0.03678208380870259,"score_gpt":0.28086754598412345,"score_spread":0.24408546217542085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223212","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8657948,0.00021750834,0.11918238,0.00014312837,0.00015927032,0.0010486332,0.0000833584,0.00004750052,0.013323473],"genre_scores_gemma":[0.97348857,0.00042745372,0.025968399,0.00004144897,0.0000027335514,0.000004047019,0.000012346994,0.0000043048462,0.000050714567],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986577,0.00015281735,0.00068081357,0.00012839162,0.00027758855,0.00010268641],"domain_scores_gemma":[0.99803615,0.0004964763,0.0006205379,0.0005432727,0.00028315416,0.00002041151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009008017,0.00012906095,0.00022723766,0.00076108554,0.00029073108,0.00007205138,0.00071929675,0.00005463243,9.3445504e-7],"category_scores_gemma":[0.00008609884,0.00011104234,0.000024449195,0.00044495234,0.00083139737,0.0013947829,0.00079698465,0.0004943369,1.1573255e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002010905,0.00046275498,0.13547373,0.0028818592,0.00008591998,6.7548905e-7,0.13221003,0.14921266,0.024256403,0.043696772,0.000043996097,0.51147413],"study_design_scores_gemma":[0.0003389416,0.00021931443,0.017630182,0.002106167,0.000017833185,0.000009638814,0.00011604812,0.9646819,0.01339996,0.0006850881,0.0006371848,0.00015772932],"about_ca_topic_score_codex":0.00017965343,"about_ca_topic_score_gemma":0.000077199125,"teacher_disagreement_score":0.81546926,"about_ca_system_score_codex":0.000039507642,"about_ca_system_score_gemma":0.000096407006,"threshold_uncertainty_score":0.45281753},"labels":[],"label_agreement":null},{"id":"W4413223247","doi":"10.1007/978-981-95-0568-5_9","title":"Enhancing Diabetic Foot Ulcer Assessment Through Fine-Tuned Vision-Language Models","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto; University Health Network","funders":"","keywords":"Diabetic foot ulcer; Computer science; Diabetic foot; Foot (prosody); Artificial intelligence; Information retrieval; Natural language processing; Medicine; Optometry; Linguistics; Diabetes mellitus; Philosophy","score_opus":0.028883229673980337,"score_gpt":0.3476273183096471,"score_spread":0.3187440886356668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223247","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019743867,0.00040232742,0.18456605,0.0021322574,0.00028026392,0.0008736114,0.000011437804,0.00007415384,0.81146246],"genre_scores_gemma":[0.4172651,0.006862032,0.5164391,0.00814965,0.0001342975,0.00027361626,0.00082061865,0.000045918554,0.050009724],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981132,0.000023050612,0.0007614094,0.0002789363,0.00056676817,0.00025663475],"domain_scores_gemma":[0.9974743,0.00017481516,0.00024456673,0.001718681,0.0003003198,0.000087276436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008255914,0.00025096152,0.0003901112,0.000797246,0.000308104,0.00029892736,0.00087415916,0.00011196925,0.00005454633],"category_scores_gemma":[0.000024459576,0.0002360881,0.00007065773,0.00034306524,0.0005306238,0.0027565253,0.0016899606,0.00043592195,0.00002365715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010484244,0.000112867005,0.000057292007,0.0004313067,0.000061380604,0.000001704061,0.0032034589,0.00025745647,0.00003428349,0.7114571,0.002504968,0.28186774],"study_design_scores_gemma":[0.0035982083,0.000638963,0.005584419,0.0057154326,0.00032949288,0.000016401527,0.0006095542,0.6092044,0.00022551796,0.037202835,0.33558086,0.001293886],"about_ca_topic_score_codex":0.000017714554,"about_ca_topic_score_gemma":0.000021460417,"teacher_disagreement_score":0.76145273,"about_ca_system_score_codex":0.00027060162,"about_ca_system_score_gemma":0.00046944263,"threshold_uncertainty_score":0.96273935},"labels":[],"label_agreement":null},{"id":"W4413223345","doi":"10.1007/978-981-95-0568-5_3","title":"Dynamics of Affective States During Takeover Requests in Conditionally Automated Driving Among Older Adults with and Without Cognitive Impairment","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Tornado Spectral Systems (Canada); Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Dynamics (music); Cognition; Cognitive impairment; Psychology; Cognitive psychology; Audiology; Medicine; Neuroscience","score_opus":0.01380009176860977,"score_gpt":0.3417879132393388,"score_spread":0.3279878214707291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92944777,0.0002403818,0.005403933,0.000759645,0.00020069882,0.00430917,0.00031407317,0.0002578258,0.05906648],"genre_scores_gemma":[0.9955316,0.0011012099,0.0024693706,0.00013402989,0.000006618765,0.0001269967,0.00017796824,0.000008962231,0.0004432232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983728,0.000097974626,0.0007543137,0.00023575588,0.00029770244,0.00024148017],"domain_scores_gemma":[0.99730563,0.00077701785,0.0005763893,0.00047669763,0.0008087527,0.000055500856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064845494,0.00021581621,0.00035826254,0.0009252067,0.00062140875,0.000047140107,0.0003920201,0.00012427042,0.0000063843954],"category_scores_gemma":[0.00010458053,0.00019481676,0.000016170114,0.00033131396,0.0012752239,0.0019746048,0.0010922201,0.0005900785,0.0000023534196],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046778146,0.00008220344,0.9156297,0.0014246275,0.00007321008,9.804769e-7,0.05567276,0.00021575928,6.880779e-7,0.019477759,0.00009491621,0.007280644],"study_design_scores_gemma":[0.0013957944,0.000053284326,0.8582538,0.015086332,0.000014061946,0.0000022471447,0.0015517796,0.123090185,0.000001956302,0.00035120398,0.000015497628,0.00018386397],"about_ca_topic_score_codex":0.00014079272,"about_ca_topic_score_gemma":0.0035216573,"teacher_disagreement_score":0.122874424,"about_ca_system_score_codex":0.00038289852,"about_ca_system_score_gemma":0.00038705967,"threshold_uncertainty_score":0.7944397},"labels":[],"label_agreement":null},{"id":"W4413223372","doi":"10.1007/978-981-95-0568-5_8","title":"Scene Invariant Cross Camera Anomaly Detection of Behaviours of Risk in People with Dementia","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Invariant (physics); Anomaly detection; Dementia; Artificial intelligence; Computer science; Computer vision; Medicine; Mathematics; Internal medicine; Mathematical physics","score_opus":0.013818849608069441,"score_gpt":0.26842925449570754,"score_spread":0.2546104048876381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223372","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006545308,0.00021343768,0.97237694,0.000093075425,0.00006065016,0.0004738133,0.000036826703,0.000052278363,0.020147644],"genre_scores_gemma":[0.8757336,0.0011753356,0.122858204,0.00005528678,0.000004431113,0.000043758995,0.000015648477,0.000004413324,0.00010928892],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984808,0.00003137117,0.0008143303,0.00023835561,0.00029081863,0.00014430727],"domain_scores_gemma":[0.9970767,0.000134313,0.0006879172,0.0015756271,0.0004817749,0.00004366001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007958165,0.00015733534,0.00027070014,0.0012682787,0.00023287196,0.00014746911,0.0018598745,0.00010855218,0.0000028463523],"category_scores_gemma":[0.000022965773,0.00015516022,0.000041030547,0.0010452966,0.0006387622,0.0024315037,0.0010911127,0.000321015,0.0000014155132],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016468537,0.00013981208,0.017590467,0.0000916465,0.000021426093,2.5481765e-7,0.002491577,0.0009851307,0.00007342409,0.55491734,0.000016792319,0.42365566],"study_design_scores_gemma":[0.0012347293,0.00047300162,0.42189977,0.00096083235,0.000059648683,0.000032534033,0.000073041556,0.5560933,0.0037316082,0.008704422,0.0059583923,0.0007787658],"about_ca_topic_score_codex":0.00054405595,"about_ca_topic_score_gemma":0.0006650031,"teacher_disagreement_score":0.8691883,"about_ca_system_score_codex":0.00009346053,"about_ca_system_score_gemma":0.00029709018,"threshold_uncertainty_score":0.632725},"labels":[],"label_agreement":null},{"id":"W4413240238","doi":"10.1007/978-3-031-95127-5_9","title":"Simulating Data Patterns Produced by Dynamic IoT Environments","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"","keywords":"Internet of Things; Computer science; Data science; Information retrieval; World Wide Web","score_opus":0.04348137422350147,"score_gpt":0.3204672347094972,"score_spread":0.2769858604859957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413240238","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005070356,0.00023822537,0.95667416,0.0009936093,0.00019195754,0.00053557794,0.00035780188,0.00020759838,0.040750377],"genre_scores_gemma":[0.054396942,0.0037868724,0.933918,0.001822428,0.000024991628,0.000050994266,0.002399451,0.000020692218,0.0035796417],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806005,0.000032949607,0.00067909295,0.00053860137,0.0004545484,0.00023474549],"domain_scores_gemma":[0.99185514,0.00021959624,0.00037026915,0.0074038734,0.000081159786,0.00006994468],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0010992324,0.0002377663,0.00022964196,0.0006815928,0.00038536286,0.0006997163,0.011306487,0.00011003811,0.0000037762952],"category_scores_gemma":[0.0000872711,0.00025327137,0.000020168367,0.00029503804,0.00044755772,0.0066179074,0.015778959,0.00041541617,0.000021336045],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.575253e-7,0.000029564375,0.0001083576,0.000042900523,0.000009425806,3.6872328e-7,0.00056907494,0.000053248652,0.000025218653,0.09238105,0.0028127749,0.9039671],"study_design_scores_gemma":[0.00012787143,0.000025695123,0.00025899883,0.00031250456,0.000004925464,0.000004016142,0.000004579969,0.8216519,0.000032261927,0.0014255128,0.17587048,0.0002813091],"about_ca_topic_score_codex":0.00001681895,"about_ca_topic_score_gemma":0.0000052972223,"teacher_disagreement_score":0.90368575,"about_ca_system_score_codex":0.00017276568,"about_ca_system_score_gemma":0.00019800209,"threshold_uncertainty_score":0.99999195},"labels":[],"label_agreement":null},{"id":"W4413245579","doi":"10.1007/978-3-031-94953-1_11","title":"Analyzing the Complexity of Yen-Dollar Exchange Rates: Recurrence Quantification, Orthogonal Matching Pursuit, and Anomaly Detection","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Liberian dollar; Matching (statistics); Anomaly (physics); Matching pursuit; Anomaly detection; Computer science; Us dollar; Internal medicine; Pattern recognition (psychology); Mathematics; Artificial intelligence; Statistics; Exchange rate; Medicine; Physics; Economics; Monetary economics; Finance","score_opus":0.09108874182184812,"score_gpt":0.280178855830502,"score_spread":0.1890901140086539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413245579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050376896,0.02113836,0.7172413,0.0033669944,0.00077920663,0.0013958926,0.0005567907,0.00007180321,0.25041196],"genre_scores_gemma":[0.9810465,0.00854798,0.00856185,0.00015206405,0.000037989415,0.000030802996,0.0001012009,0.000008925829,0.001512662],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984057,0.00002663712,0.0010805683,0.00025389346,0.000092328235,0.00014089527],"domain_scores_gemma":[0.99754393,0.0001605157,0.00089934235,0.001098682,0.00025610576,0.000041449348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018299529,0.00015993559,0.0003817666,0.0008755136,0.0006271195,0.00035894,0.000996773,0.00007792894,0.000034291228],"category_scores_gemma":[0.000061482955,0.00015505888,0.00006571242,0.000610412,0.0012232107,0.0015186243,0.00079876947,0.00020391167,0.000013128894],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033750898,0.000008983608,0.0012521535,0.000100056925,0.00002275176,3.175139e-8,0.0010885093,0.00006710857,0.0000025290049,0.948745,0.0000695404,0.048639946],"study_design_scores_gemma":[0.0004853093,0.000086744345,0.07167603,0.0006354561,0.000045055458,0.000016521195,0.0003627893,0.5236038,0.000015860178,0.14603975,0.25630304,0.00072963216],"about_ca_topic_score_codex":0.00030222742,"about_ca_topic_score_gemma":0.00031545074,"teacher_disagreement_score":0.97600883,"about_ca_system_score_codex":0.000075451935,"about_ca_system_score_gemma":0.00006379982,"threshold_uncertainty_score":0.63231176},"labels":[],"label_agreement":null},{"id":"W4413305426","doi":"10.1007/978-981-95-1525-7_15","title":"Can Information Technology Bridge Cultural Differences? Design and Effectiveness Analysis of COIL Based on Intercultural Communication","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"International Student and Expatriate Challenges","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Roads University","funders":"","keywords":"Bridge (graph theory); Electromagnetic coil; Computer science; Engineering; Electrical engineering; Medicine; Internal medicine","score_opus":0.050391234321261316,"score_gpt":0.34595545605238565,"score_spread":0.29556422173112434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413305426","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10389925,0.0022861925,0.17307985,0.026518136,0.001187789,0.006157379,0.00047904652,0.0004708405,0.68592155],"genre_scores_gemma":[0.9918227,0.004282696,0.0033625367,0.00020090769,0.0000068077024,0.000026438709,0.00017687045,0.0000019841748,0.00011906657],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986059,0.0001501536,0.00052962673,0.0001355662,0.0004362449,0.00014250349],"domain_scores_gemma":[0.99742234,0.00068928674,0.00041755155,0.00058659224,0.00083853997,0.00004569333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014807994,0.00015979624,0.00032022176,0.0021437672,0.00066102244,0.00028578736,0.0012824757,0.0001747107,0.000007635542],"category_scores_gemma":[0.000177314,0.00014526134,0.00005651861,0.00087251,0.001636997,0.0021485481,0.0005397366,0.00029052116,0.0000027729566],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037801645,0.000030425648,0.0013523002,0.000056009976,0.0001028131,6.369723e-8,0.043017924,0.0012103494,0.0000016582567,0.86681867,0.000054911692,0.087317094],"study_design_scores_gemma":[0.0022006005,0.00042555624,0.1434395,0.0027128253,0.00053613243,0.000002163859,0.013542663,0.77670395,0.00005232939,0.020724392,0.038323753,0.0013361234],"about_ca_topic_score_codex":0.0005226812,"about_ca_topic_score_gemma":0.00037807808,"teacher_disagreement_score":0.8879234,"about_ca_system_score_codex":0.00026595703,"about_ca_system_score_gemma":0.0002092468,"threshold_uncertainty_score":0.60315835},"labels":[],"label_agreement":null},{"id":"W4413367346","doi":"10.1007/978-3-032-04228-6_12","title":"Human Papillomavirus Detection Using Novel Machine Learning Algorithm Based on Cytology Images","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Human papillomavirus; Computer science; Cytology; Artificial intelligence; Pattern recognition (psychology); Medicine; Pathology; Internal medicine","score_opus":0.03893539171720457,"score_gpt":0.30820964479284635,"score_spread":0.2692742530756418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413367346","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000014176843,0.00013007341,0.9419307,0.00026077346,0.0004384496,0.00029378565,0.000015918558,0.00016409498,0.056752026],"genre_scores_gemma":[0.09194801,0.0006815399,0.90322256,0.0021017215,0.000101195736,0.000063057516,0.000073763906,0.000026088159,0.0017820331],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815845,0.000061388884,0.00065881835,0.00041150284,0.00045151365,0.00025835086],"domain_scores_gemma":[0.9971327,0.00021268943,0.00046380653,0.0017502797,0.00036723175,0.00007327258],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010064238,0.00027672717,0.00029371644,0.0018839389,0.0012162824,0.00052995357,0.0023254745,0.00019093273,0.000006460655],"category_scores_gemma":[0.000045654957,0.00030050622,0.000060126018,0.0006812252,0.0006557153,0.0036013988,0.0015820648,0.0008691809,0.000013335748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000036928543,0.000028888111,0.000028057824,0.00003583068,0.000007672307,4.901335e-7,0.00028987636,0.010539293,0.00017406854,0.0703664,0.000024789817,0.91850096],"study_design_scores_gemma":[0.0003402711,0.00011737967,0.0002613588,0.00019173659,0.0000068751247,0.000018404151,0.000004021143,0.9632659,0.00019651631,0.0014835303,0.03384208,0.00027192966],"about_ca_topic_score_codex":0.000087942804,"about_ca_topic_score_gemma":0.000021956048,"teacher_disagreement_score":0.9527266,"about_ca_system_score_codex":0.0005127321,"about_ca_system_score_gemma":0.00029811496,"threshold_uncertainty_score":0.9999447},"labels":[],"label_agreement":null},{"id":"W4413459428","doi":"10.1007/978-3-031-95540-2_4","title":"Improving the Performance of a Quarter Vehicle Model with a Complex Lead Compensator","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Lead (geology); Lead–lag compensator; Computer science; Control theory (sociology); Control engineering; History; Engineering; Artificial intelligence; Biology; Control (management)","score_opus":0.016276534838707724,"score_gpt":0.2189054440151869,"score_spread":0.2026289091764792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413459428","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04570489,0.0008567912,0.4065476,0.0008984958,0.00031652665,0.001955492,0.00012696246,0.0002573542,0.54333586],"genre_scores_gemma":[0.9945358,0.00023216348,0.0048426646,0.000121547724,0.000006712326,0.000018523859,0.000011684319,0.000005137098,0.00022574898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920076,0.000007216136,0.0004017232,0.00008059885,0.00019243849,0.00011723417],"domain_scores_gemma":[0.9987356,0.00006482346,0.00012530595,0.0008679882,0.00018236625,0.000023900922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032876828,0.00012304632,0.0001823252,0.00024316921,0.00019325386,0.000115852694,0.000848069,0.000049229686,0.0000012436041],"category_scores_gemma":[0.0000023846428,0.00009269467,0.000022057162,0.0001525201,0.00041950098,0.0009632959,0.00021588661,0.00023205558,0.0000030522367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020753836,0.000017333034,0.00073143985,0.00063377095,0.000050256265,1.4722458e-7,0.0042665442,0.384226,0.00029985368,0.2795564,0.0003750771,0.32982242],"study_design_scores_gemma":[0.00019567159,0.000025313566,0.0008729448,0.00017112824,0.000005810765,0.0000025924703,0.000025329638,0.9970369,0.000003238651,0.000052425425,0.001502995,0.00010569671],"about_ca_topic_score_codex":0.000015208058,"about_ca_topic_score_gemma":0.000027066979,"teacher_disagreement_score":0.9488309,"about_ca_system_score_codex":0.000059042122,"about_ca_system_score_gemma":0.000099186305,"threshold_uncertainty_score":0.37799788},"labels":[],"label_agreement":null},{"id":"W4413776343","doi":"10.1007/978-3-031-94950-0_2","title":"Places365-CNNs for 4-Way Classification of Alzheimer’s Disease Using MRI Images","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology)","score_opus":0.12639230754211936,"score_gpt":0.348171675659202,"score_spread":0.22177936811708263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413776343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006581836,0.0009815817,0.56574816,0.004979297,0.0013664545,0.0040590987,0.0007377495,0.00026928718,0.4212002],"genre_scores_gemma":[0.9085635,0.0054154964,0.07658707,0.00251215,0.00011809279,0.0003147522,0.00027884578,0.000045593504,0.0061645242],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982957,0.000050044197,0.0007967588,0.00032845468,0.00035288153,0.00017615782],"domain_scores_gemma":[0.9970482,0.0004535409,0.0006409878,0.0013648241,0.00039384497,0.00009861145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072224677,0.00019347575,0.00023417265,0.0010590629,0.0005349779,0.00021010895,0.0011810003,0.00010035255,0.000008843954],"category_scores_gemma":[0.00029571672,0.00020400871,0.00007373845,0.00044911646,0.0012958416,0.0024457714,0.00047923593,0.00024632167,0.000008639548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037924347,0.000051628303,0.00003731496,0.0001425013,0.000006622567,1.16744665e-7,0.00051614374,0.00049678277,0.003434399,0.8583608,0.0009763928,0.13593933],"study_design_scores_gemma":[0.0005420911,0.000048038357,0.0030320215,0.00039346883,0.000057391484,0.000007298469,0.000058358186,0.89218515,0.004192493,0.008121382,0.090964444,0.00039787474],"about_ca_topic_score_codex":0.000004246411,"about_ca_topic_score_gemma":0.0000022669205,"teacher_disagreement_score":0.9079053,"about_ca_system_score_codex":0.00012365443,"about_ca_system_score_gemma":0.00042105664,"threshold_uncertainty_score":0.8319234},"labels":[],"label_agreement":null},{"id":"W4413776357","doi":"10.1007/978-3-031-94950-0_7","title":"Brain Tumor Classification Through Transfer Learning Models","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Transfer of learning; Computer science; Artificial intelligence; Neuroscience; Psychology","score_opus":0.12088567266545669,"score_gpt":0.31274318047862915,"score_spread":0.19185750781317246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413776357","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013790488,0.0000994588,0.18494293,0.0040633734,0.0002973067,0.0005925676,0.000020165466,0.00020447634,0.80964184],"genre_scores_gemma":[0.93162143,0.0060109994,0.013441753,0.015612792,0.00009309196,0.00022275055,0.00014603756,0.00004367526,0.032807447],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792594,0.00010579038,0.00078988954,0.00044197036,0.00049187575,0.00024453635],"domain_scores_gemma":[0.99757457,0.0005531925,0.00024260335,0.0013079264,0.00024545062,0.00007625684],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008209829,0.00025317012,0.0002466248,0.0008701491,0.0008988806,0.0004651571,0.0015146303,0.00014067083,0.000023567045],"category_scores_gemma":[0.0002467333,0.0002683272,0.00006453099,0.00067210355,0.0012320051,0.0059721638,0.00047373588,0.0008311463,0.000075618074],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064185233,0.000015181717,0.0000029629327,0.000029869918,0.0000014473841,1.9655643e-7,0.00119027,0.0005082745,0.00039321283,0.9144963,0.00042522748,0.08293064],"study_design_scores_gemma":[0.0003622395,0.000044886703,0.000179794,0.00020837442,0.00000797151,0.000026088286,0.00009285329,0.606737,0.0005686243,0.025616037,0.36580226,0.0003538558],"about_ca_topic_score_codex":0.0000077262475,"about_ca_topic_score_gemma":0.000006221946,"teacher_disagreement_score":0.93148357,"about_ca_system_score_codex":0.00022248327,"about_ca_system_score_gemma":0.00033613914,"threshold_uncertainty_score":0.9999769},"labels":[],"label_agreement":null},{"id":"W4413838753","doi":"10.1007/978-3-032-04291-0_7","title":"User-Aligned Privacy Framework in the Era of Generative Artificial Intelligence","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Generative grammar; Computer science; Artificial intelligence","score_opus":0.0699563205003495,"score_gpt":0.33645473057852765,"score_spread":0.26649841007817815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413838753","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000058670823,0.00031785798,0.9493279,0.023653911,0.0002310835,0.000484346,0.000019324581,0.000079567646,0.025827337],"genre_scores_gemma":[0.039281085,0.0025752007,0.9567519,0.0012491997,0.000017355762,0.000043717075,0.000028435348,0.0000042007455,0.000048920116],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978081,0.00008874721,0.0010014226,0.00033447062,0.0005306734,0.00023659847],"domain_scores_gemma":[0.9859984,0.0010669801,0.00043203062,0.012150357,0.00032112276,0.000031133954],"candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0020352341,0.00021452188,0.0002830757,0.0009586491,0.00031468406,0.000533715,0.049837958,0.00020699596,0.000003979493],"category_scores_gemma":[0.0035485388,0.00018146104,0.000042706728,0.0014032891,0.0014201851,0.004409162,0.065173104,0.00085050624,0.000011766041],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011727491,0.000016412814,0.000016310385,0.000014729642,0.000002541428,2.7047727e-7,0.0015197353,0.000059436315,0.0000015888965,0.7584257,0.00087738596,0.2390647],"study_design_scores_gemma":[0.00003410311,0.00003370466,0.00023394133,0.00039085757,0.0000024704154,0.0000043158984,0.00005754615,0.3478507,0.00012117831,0.64287245,0.008230354,0.00016834972],"about_ca_topic_score_codex":0.000022720375,"about_ca_topic_score_gemma":0.000016681208,"teacher_disagreement_score":0.34779128,"about_ca_system_score_codex":0.00012470032,"about_ca_system_score_gemma":0.00041305504,"threshold_uncertainty_score":0.9553029},"labels":[],"label_agreement":null},{"id":"W4413867021","doi":"10.1007/978-3-031-99353-4_10","title":"“Juiciness” and Interactive Infographics: An Ethnographic Perspective","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Infographic; Perspective (graphical); Ethnography; Computer science; Information retrieval; Geography; Artificial intelligence; Archaeology; Data mining","score_opus":0.037851345453888616,"score_gpt":0.36074372195979637,"score_spread":0.32289237650590774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413867021","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001951758,0.0005643439,0.001809359,0.0016892332,0.00018575958,0.00033504475,0.000015304719,0.000050423543,0.99515533],"genre_scores_gemma":[0.62996167,0.15053356,0.049991954,0.012720505,0.00046954319,0.00020747438,0.00032918106,0.000050071143,0.15573607],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989705,0.00003743495,0.0003261262,0.00018677088,0.00030746896,0.00017171876],"domain_scores_gemma":[0.9981076,0.00025883282,0.0001788545,0.00064446643,0.0006790982,0.00013116309],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0009046892,0.00013932207,0.00018165639,0.0012971042,0.0004420284,0.0005934508,0.00095839676,0.00012297275,0.0000072514554],"category_scores_gemma":[0.00015064278,0.0001405316,0.000032114443,0.0005500971,0.003586369,0.006564975,0.00069113984,0.0003807401,0.000004072839],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021263495,0.000007611139,0.00009339881,0.0000067769242,0.0000038456847,7.404446e-8,0.027569812,0.0000015156965,7.8495134e-8,0.69020325,0.000056959445,0.2820545],"study_design_scores_gemma":[0.00018278648,0.000055563993,0.0016259153,0.00029818114,0.00001086807,0.0000019598435,0.007945084,0.0033587567,3.1120445e-7,0.016604017,0.96969056,0.00022601469],"about_ca_topic_score_codex":0.00021862287,"about_ca_topic_score_gemma":0.0007700609,"teacher_disagreement_score":0.9696336,"about_ca_system_score_codex":0.00010630091,"about_ca_system_score_gemma":0.00043035284,"threshold_uncertainty_score":0.9991253},"labels":[],"label_agreement":null},{"id":"W4414158670","doi":"10.1007/978-3-031-94940-1_22","title":"Genetic Algorithm Visualization","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Knapsack problem; Attractor; Crossover; Visualization; Set (abstract data type); Genetic algorithm; Mutation","score_opus":0.02142362223658602,"score_gpt":0.29258255861860377,"score_spread":0.27115893638201777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414158670","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000013628269,0.00046768706,0.83315575,0.00078118447,0.00018516768,0.00030402697,0.000014442392,0.00010427427,0.16498612],"genre_scores_gemma":[0.00079936476,0.0051215696,0.98672974,0.0012158504,0.00005317916,0.00007346983,0.000085829204,0.000007489015,0.005913521],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839,0.000022631793,0.0006517952,0.00033258155,0.00039419183,0.00020878727],"domain_scores_gemma":[0.9969371,0.00014110841,0.00025740478,0.0020971538,0.00047694388,0.00009031716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000496706,0.000205169,0.00019955657,0.0011196731,0.0006148792,0.0005228225,0.003198403,0.00012810229,0.00000785912],"category_scores_gemma":[0.00002132061,0.00022160365,0.000042655494,0.0007737025,0.0006031079,0.004567386,0.0024416626,0.00028528585,0.0000627244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.2610981e-7,0.000009285619,0.0000056025815,0.0000075240564,0.000002054431,1.0897174e-7,0.0001669997,0.00008264974,2.8692398e-7,0.6085924,0.0004434788,0.39068946],"study_design_scores_gemma":[0.0001250689,0.000017759323,0.0010167294,0.000091150665,0.0000037365862,0.000012489297,0.0000042638994,0.7335948,0.0000018950136,0.025130887,0.23980443,0.0001968322],"about_ca_topic_score_codex":0.000011477952,"about_ca_topic_score_gemma":0.0000024977637,"teacher_disagreement_score":0.7335121,"about_ca_system_score_codex":0.00016222065,"about_ca_system_score_gemma":0.00047846243,"threshold_uncertainty_score":0.90367347},"labels":[],"label_agreement":null},{"id":"W4414158748","doi":"10.1007/978-981-95-0988-1_1","title":"Evaluating the Behavior of Small Language Models in Answering Binary Questions","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Security token; Binary number; Natural language; Language model; Binary classification; Natural (archaeology)","score_opus":0.11777774152110751,"score_gpt":0.3699668967910038,"score_spread":0.25218915526989627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414158748","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022926512,0.0009393343,0.90743506,0.0006805739,0.00023186342,0.0007633555,0.000008524815,0.000060638722,0.087588005],"genre_scores_gemma":[0.2736231,0.001280291,0.72323513,0.0005335609,0.000020692969,0.00017748235,0.000020469268,0.0000074897184,0.001101767],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986287,0.000048107973,0.0006759714,0.00020056032,0.00029555612,0.00015111442],"domain_scores_gemma":[0.99719554,0.0002682541,0.00024498344,0.0020321587,0.00022805348,0.000031001106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016221947,0.00013036816,0.00017798904,0.00083716144,0.00024112334,0.00019957956,0.0031955254,0.00007515846,0.0000013576228],"category_scores_gemma":[0.000052638887,0.00011552589,0.000032888973,0.0004675116,0.0003636232,0.0028016798,0.0025813198,0.000385751,0.0000017933664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.0650166e-7,0.00001097006,0.000032734326,0.000021936132,0.0000013351439,2.2070442e-7,0.003847156,0.023159135,0.000014795315,0.60389155,0.0000034652371,0.36901608],"study_design_scores_gemma":[0.000113387985,0.000024410081,0.0005760434,0.00033838625,0.000004024061,0.000004429651,0.00004600398,0.9929265,0.000005831434,0.005359339,0.00049302564,0.000108647204],"about_ca_topic_score_codex":0.00009710401,"about_ca_topic_score_gemma":0.000048957925,"teacher_disagreement_score":0.96976733,"about_ca_system_score_codex":0.00010351836,"about_ca_system_score_gemma":0.00036264036,"threshold_uncertainty_score":0.5938134},"labels":[],"label_agreement":null},{"id":"W4414537602","doi":"10.1007/978-3-032-06136-2_21","title":"Mass Migration of Records: LRM-Factory, a Solution to Facilitate the Transition to Linked Data for Bibliographic Agencies","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advantage Forensics (Canada)","funders":"","keywords":"Metadata; Linked data; Semantic Web; Process (computing); Transition (genetics); Controlled vocabulary","score_opus":0.14528104663983815,"score_gpt":0.3031877780855065,"score_spread":0.15790673144566836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414537602","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010825088,0.00011366423,0.9665628,0.008017907,0.00045972937,0.0014686716,0.00026407323,0.00006427275,0.022940628],"genre_scores_gemma":[0.18531159,0.005624292,0.7806288,0.01948869,0.00018765684,0.0006713129,0.0016963608,0.000024910374,0.0063664056],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976427,0.000054801123,0.0011114721,0.00035822674,0.00058349955,0.00024931828],"domain_scores_gemma":[0.9949233,0.00035631092,0.00039419258,0.0035039058,0.0007084658,0.00011385763],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0026538235,0.00020952652,0.00027328447,0.004165769,0.00061226485,0.00089607754,0.0070294747,0.00010711947,0.0000024246458],"category_scores_gemma":[0.000102093065,0.00017171536,0.000067334535,0.003303138,0.0004200238,0.018912902,0.0018444298,0.0001975907,0.000023800627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040437997,0.000038619037,0.00009200447,0.00043440086,0.000040751092,1.2141682e-7,0.071990825,0.0035850771,0.00026172452,0.4078349,0.05636151,0.45931962],"study_design_scores_gemma":[0.00017313626,0.00013719096,0.00056053995,0.00030276173,0.0000048127517,0.0000024316455,0.00027396,0.6288554,0.00003117448,0.0037161016,0.36569664,0.0002458222],"about_ca_topic_score_codex":0.00008210452,"about_ca_topic_score_gemma":0.000066596454,"teacher_disagreement_score":0.62527037,"about_ca_system_score_codex":0.00008229961,"about_ca_system_score_gemma":0.0005192368,"threshold_uncertainty_score":0.998343},"labels":[],"label_agreement":null},{"id":"W4414537698","doi":"10.1007/978-3-032-06136-2_33","title":"Ecolink: Towards a Knowledge Graph Schema for Complex Environmental Systems","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Waterloo; McMaster University; University of Toronto; Carleton University","funders":"","keywords":"Schema (genetic algorithms); Knowledge graph; Publishing; Graph; Field (mathematics); Knowledge extraction; Data access; Knowledge engineering","score_opus":0.06192827477882113,"score_gpt":0.3094722729528911,"score_spread":0.24754399817406997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414537698","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024148107,0.0015974496,0.7552123,0.0007199938,0.00063908496,0.0008583215,0.000047892772,0.00012349352,0.2407773],"genre_scores_gemma":[0.18159333,0.009362732,0.79461473,0.0021636926,0.00015901175,0.0004721763,0.00038720222,0.000025516887,0.011221605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984352,0.00002638844,0.00068181515,0.00032078644,0.00027124883,0.00026455382],"domain_scores_gemma":[0.9972129,0.0003095959,0.0002712396,0.0019470962,0.00017924448,0.0000799392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008808154,0.00023816027,0.0003338425,0.0009829556,0.0005655024,0.00067994953,0.003904889,0.00014905742,0.0000031346115],"category_scores_gemma":[0.000038944985,0.00023179203,0.00007755422,0.00028583154,0.00084177795,0.0031121692,0.0027881905,0.00024636966,0.00002774026],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016233386,0.000021280042,0.000027159796,0.0000762033,0.00000878778,1.2451652e-7,0.0008512703,0.00005413784,0.0000028048653,0.813221,0.0013117929,0.18442385],"study_design_scores_gemma":[0.00036430094,0.000052034822,0.0011774137,0.00020639194,0.000008000081,0.000014454307,0.00005096719,0.63149804,0.000006026677,0.007601313,0.35873058,0.00029046962],"about_ca_topic_score_codex":0.000010800679,"about_ca_topic_score_gemma":0.000007278595,"teacher_disagreement_score":0.80561966,"about_ca_system_score_codex":0.0001689701,"about_ca_system_score_gemma":0.00037494831,"threshold_uncertainty_score":0.9452205},"labels":[],"label_agreement":null},{"id":"W4414551658","doi":"10.1007/978-3-031-91141-5_10","title":"A Preliminary Geospatial Analysis of Out-of-Hospital Cardiac Arrests in Lombardy","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Geospatial analysis; Population; Geographic information system; Socioeconomic status; Distribution (mathematics)","score_opus":0.022028088092169135,"score_gpt":0.3152009432397789,"score_spread":0.2931728551476097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414551658","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02144624,0.014231785,0.0167108,0.0023032366,0.0037047358,0.0026260018,0.000548928,0.00007021367,0.93835807],"genre_scores_gemma":[0.9559003,0.028045189,0.014192805,0.00023679501,0.000044167366,0.00004322039,0.00046772786,0.0000076104357,0.0010621818],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998786,0.000015590616,0.0007155504,0.00012493046,0.00026056092,0.00009737618],"domain_scores_gemma":[0.9982092,0.0001362857,0.00026444954,0.0008889859,0.00047032422,0.000030769745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043471786,0.00011829316,0.00049191236,0.0014965724,0.00007190722,0.000012260273,0.00047201058,0.00007973972,0.0000061267547],"category_scores_gemma":[0.00006985074,0.00011283409,0.00011350358,0.0007068036,0.00065753586,0.0006033003,0.00074700546,0.00021357219,0.0000013857705],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014587864,0.00041254383,0.061355453,0.0012318298,0.0016171271,0.0000025963782,0.062850796,0.0013743471,0.000015323641,0.22539853,0.0044850926,0.6411105],"study_design_scores_gemma":[0.0021035702,0.0015969737,0.60425895,0.00542406,0.0026332114,0.0000021647122,0.0015553666,0.25465906,0.00009485548,0.0023519038,0.12414642,0.0011734718],"about_ca_topic_score_codex":0.000042981697,"about_ca_topic_score_gemma":0.000038129707,"teacher_disagreement_score":0.93729585,"about_ca_system_score_codex":0.000054383112,"about_ca_system_score_gemma":0.00021110888,"threshold_uncertainty_score":0.46012405},"labels":[],"label_agreement":null},{"id":"W4414638520","doi":"10.1007/978-981-95-0129-8_19","title":"Concept-Aware Deep Representation Learning for Co-evolving Sequences","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Interpretability; Representation (politics); Constraint (computer-aided design); Identification (biology); Mechanism (biology); Series (stratigraphy); Deep learning; Time series","score_opus":0.04461701813251495,"score_gpt":0.32077809026512627,"score_spread":0.2761610721326113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414638520","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000062988356,0.00041644144,0.8726019,0.00060070684,0.00015311282,0.00031648204,0.0000067847677,0.00008284491,0.1258154],"genre_scores_gemma":[0.17273308,0.0047377837,0.80110663,0.002120037,0.00018766697,0.00019278281,0.000772785,0.000028368375,0.018120851],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983724,0.000034496705,0.0006934374,0.00033301077,0.00033525287,0.00023142036],"domain_scores_gemma":[0.9971476,0.00048102633,0.00047828228,0.0011921261,0.00063415023,0.000066820416],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00090837665,0.00019119876,0.00028026244,0.00082771276,0.0010239179,0.0010438259,0.0024149825,0.000107103275,0.000011477738],"category_scores_gemma":[0.00013706861,0.00019495415,0.000080413185,0.000524524,0.0006137624,0.006729351,0.0013253825,0.00033891527,0.000009499016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015153482,0.000005107749,0.000078460755,0.000032496202,0.000011751787,2.1346807e-7,0.0021977997,0.0041919425,0.000002016895,0.46592036,0.00029980188,0.5272585],"study_design_scores_gemma":[0.00015196422,0.00003907805,0.00017542118,0.00016599297,0.000008153152,0.0000063075995,0.00009774404,0.9307365,0.000013784365,0.004160049,0.06424017,0.0002048778],"about_ca_topic_score_codex":0.000019775667,"about_ca_topic_score_gemma":0.000011354983,"teacher_disagreement_score":0.9265445,"about_ca_system_score_codex":0.00012488809,"about_ca_system_score_gemma":0.00025749768,"threshold_uncertainty_score":0.9999932},"labels":[],"label_agreement":null},{"id":"W4414681828","doi":"10.1007/978-3-032-00986-9_7","title":"Robot Vision System for Retail Shelf Monitoring","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Robot; Mobile robot; Object (grammar); Machine vision; Off the shelf; Object detection","score_opus":0.042969259975963715,"score_gpt":0.28625693338982633,"score_spread":0.24328767341386262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414681828","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017928485,0.0011854717,0.5194548,0.000096468415,0.004378717,0.0014248604,0.000048123296,0.0005116427,0.47272065],"genre_scores_gemma":[0.90860265,0.0044817855,0.0743183,0.00011430675,0.0007490872,0.00036587735,0.00016172537,0.00006516719,0.011141074],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889195,0.000010864483,0.0006055834,0.00013134131,0.00021479435,0.00014549044],"domain_scores_gemma":[0.9985567,0.00015531744,0.00012096211,0.0008529851,0.00026550944,0.00004857721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008019672,0.00015900322,0.00022500091,0.0007867679,0.00036747995,0.0003213229,0.0006268665,0.00018815404,0.0000017597221],"category_scores_gemma":[0.000023403432,0.00016171433,0.000049330763,0.00023968189,0.00012666028,0.0018272828,0.00029987367,0.0002816536,0.00001645085],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007792664,0.0000042308043,0.000017202488,0.0004822481,0.000014385398,1.2900406e-7,0.0006389319,0.009197307,0.000056581706,0.0716219,0.0008584573,0.91710085],"study_design_scores_gemma":[0.0003956506,0.00005180984,0.0001657555,0.0016774349,0.000011901548,0.000008762512,0.00007430727,0.59931535,0.00019542743,0.00018796293,0.39763087,0.0002847791],"about_ca_topic_score_codex":0.000005666075,"about_ca_topic_score_gemma":0.0000015271434,"teacher_disagreement_score":0.91681606,"about_ca_system_score_codex":0.00028304008,"about_ca_system_score_gemma":0.00007507141,"threshold_uncertainty_score":0.6594519},"labels":[],"label_agreement":null},{"id":"W4414772328","doi":"10.1007/978-3-032-00986-9_28","title":"NAUTICAL: Navigation Aid Using U-Net and $$Theta^*$$ with Integrated Collision Avoidance and Landmarking","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Obstacle avoidance; Motion planning; Trajectory; Path (computing); Skeletonization; Obstacle; Path length; Artificial neural network","score_opus":0.01790949291802905,"score_gpt":0.25727408375450567,"score_spread":0.23936459083647663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414772328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024331843,0.0034075356,0.49277392,0.00076894835,0.00047836365,0.0017278799,0.00015975884,0.00050374644,0.475848],"genre_scores_gemma":[0.73239046,0.013981325,0.2502474,0.0007851395,0.00005184584,0.000039701892,0.0006459853,0.000041904106,0.0018162325],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917185,0.00001709367,0.00037626617,0.00013791637,0.00017916548,0.00011769713],"domain_scores_gemma":[0.9991034,0.00013761676,0.00008590641,0.00043199048,0.00017880119,0.000062259955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004529243,0.00016062043,0.00018378983,0.00038353092,0.00030174805,0.00027418174,0.0002882558,0.00010514237,0.0000038978965],"category_scores_gemma":[0.000016564532,0.00014741346,0.000010543555,0.00027217576,0.00052479724,0.0015805244,0.00030702678,0.00035128213,0.0000016025432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003937237,0.000020516125,0.00091241155,0.0007540608,0.000042072727,0.0000015405252,0.0054109576,0.016316501,0.00005610466,0.3380853,0.00024518828,0.63811594],"study_design_scores_gemma":[0.0003069313,0.000018104247,0.0006760943,0.00095981965,0.000009860568,0.000024216599,0.000042584612,0.95312965,0.000014055115,0.0008155058,0.043817114,0.00018607137],"about_ca_topic_score_codex":0.000011514058,"about_ca_topic_score_gemma":0.000011519058,"teacher_disagreement_score":0.9368131,"about_ca_system_score_codex":0.00009108194,"about_ca_system_score_gemma":0.00008123711,"threshold_uncertainty_score":0.60113466},"labels":[],"label_agreement":null},{"id":"W4414772366","doi":"10.1007/978-3-032-00986-9_14","title":"Online Collaborative UAV Path Planning for Mapping and Spraying Missions","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Planner; Motion planning; Plan (archaeology); Path (computing); Autonomy; Swarm behaviour","score_opus":0.06272485010864773,"score_gpt":0.33314161328541086,"score_spread":0.2704167631767631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414772366","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001971302,0.0009479545,0.9600156,0.0015715256,0.0002913238,0.00054872554,0.00006327727,0.00009354067,0.036448356],"genre_scores_gemma":[0.0010352051,0.0008231571,0.9959983,0.00085783936,0.000029297964,0.00003361725,0.00009119285,0.0000057264415,0.001125624],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984747,0.000029882525,0.00063127343,0.00033422478,0.00028273588,0.00024718675],"domain_scores_gemma":[0.99707997,0.0006998278,0.00035106088,0.0012537244,0.0005043381,0.000111085756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095479895,0.00022401166,0.00029066365,0.001062838,0.00086001714,0.00063951715,0.0020678572,0.00012595775,5.328149e-7],"category_scores_gemma":[0.00017021282,0.00022646043,0.000028992084,0.0005858812,0.00047853272,0.0035964053,0.0021634302,0.00037510667,0.0000024483777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030711349,0.000029885681,0.00013919808,0.00012244386,0.000017770803,0.0000013659985,0.010765111,0.0021370193,0.000005964983,0.57166564,0.0016360483,0.4134765],"study_design_scores_gemma":[0.00029593124,0.00004116347,0.0008985798,0.001034108,0.0000053114823,0.000013685124,0.00013863562,0.8990102,0.0000023574391,0.004982063,0.09331692,0.0002610749],"about_ca_topic_score_codex":0.0000040525774,"about_ca_topic_score_gemma":6.091666e-7,"teacher_disagreement_score":0.8968732,"about_ca_system_score_codex":0.00010518173,"about_ca_system_score_gemma":0.0005457676,"threshold_uncertainty_score":0.92347884},"labels":[],"label_agreement":null},{"id":"W4414772568","doi":"10.1007/978-3-032-00986-9_30","title":"Objects Detection on the Water Surface Using Satellite Imagery, Drones and Vessel-Based Imaging Applied for Logistics","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cégep de Chicoutimi; Université du Québec à Chicoutimi","funders":"","keywords":"Drone; Satellite; Automation; Process (computing); Motion planning; Point (geometry); Transit (satellite)","score_opus":0.026358085253840546,"score_gpt":0.2576496096585378,"score_spread":0.23129152440469725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414772568","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036614467,0.00014150066,0.76389784,0.0023240836,0.00058015954,0.0019709822,0.0000323661,0.000121997815,0.22726962],"genre_scores_gemma":[0.97591674,0.0004947651,0.02091348,0.0018943544,0.000019266026,0.000034541295,0.000043324977,0.000010402684,0.0006731366],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991009,0.000021188676,0.00032039228,0.00019741952,0.00020063482,0.00015946617],"domain_scores_gemma":[0.9989279,0.00024663887,0.00013780968,0.0005875446,0.00006005084,0.00004008109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077158137,0.00015250115,0.00011893979,0.00019668101,0.0008080471,0.00028219074,0.0004255085,0.000062972555,0.000012071204],"category_scores_gemma":[0.000030843916,0.00010498681,0.000024906103,0.00015050269,0.0010239659,0.0008355143,0.0004402994,0.00019657677,0.00001908486],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003127228,0.000025401709,0.00019151102,0.00009319653,0.000007104425,1.3636041e-7,0.0015887546,0.018328948,0.0030989682,0.031858806,0.00016380446,0.9446121],"study_design_scores_gemma":[0.0003354753,0.000035486944,0.00092318637,0.0001301453,0.00001775763,0.0000045291986,0.00006835952,0.907641,0.0056970045,0.0060159266,0.078835264,0.00029588642],"about_ca_topic_score_codex":0.000023312818,"about_ca_topic_score_gemma":0.00001733729,"teacher_disagreement_score":0.9722553,"about_ca_system_score_codex":0.00018208646,"about_ca_system_score_gemma":0.000035278892,"threshold_uncertainty_score":0.6214926},"labels":[],"label_agreement":null},{"id":"W4415060225","doi":"10.1007/978-3-032-08049-3_2","title":"Selecting the Most Specific Plan in AgentSpeak Programs","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Plan (archaeology); Function (biology); Selection (genetic algorithm); Order (exchange); Context (archaeology)","score_opus":0.06563825177963067,"score_gpt":0.28946071788140604,"score_spread":0.22382246610177536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415060225","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027334556,0.001104786,0.52230626,0.002672714,0.0011108845,0.001905995,0.000013120368,0.00017849423,0.4704344],"genre_scores_gemma":[0.63523626,0.016796382,0.32177815,0.006138787,0.00040142954,0.00050111726,0.000574267,0.000052257517,0.018521376],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982676,0.000056465313,0.00075884967,0.00027424286,0.0004072729,0.00023558496],"domain_scores_gemma":[0.9974028,0.00020810413,0.00034125266,0.001779685,0.0002180139,0.000050151124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015663408,0.00018565037,0.00019813875,0.0008554187,0.0005341312,0.0009159088,0.0034252387,0.00009943384,0.000003432862],"category_scores_gemma":[0.00002828019,0.00015277545,0.00003336888,0.00093211414,0.0003210846,0.0035928604,0.0017210796,0.00046297532,0.000030305002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010518372,0.000018187538,0.0003650398,0.00002685296,0.0000034646678,3.4565477e-7,0.003355728,0.00016984312,0.000001927636,0.5359993,0.0005766898,0.45948154],"study_design_scores_gemma":[0.00030933804,0.000028641212,0.005006036,0.0005105448,0.0000023143066,0.000014310831,0.000061214356,0.56013346,0.000005765164,0.0022037001,0.4314465,0.0002781609],"about_ca_topic_score_codex":0.000044164703,"about_ca_topic_score_gemma":0.00010078969,"teacher_disagreement_score":0.6349629,"about_ca_system_score_codex":0.0001840306,"about_ca_system_score_gemma":0.00023305452,"threshold_uncertainty_score":0.8832129},"labels":[],"label_agreement":null},{"id":"W4415062055","doi":"10.1007/978-3-032-06075-4","title":"Smart Business Technologies","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Digital Innovation in Industries","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Soochow University; Università di Bologna; Università degli Studi del Piemonte Orientale; University of Tehran; Helwan University; University of Akron; University of Reading; McMaster University; University of South Africa; Università di Pisa; University of Southern California","keywords":"Scope (computer science); Variety (cybernetics); Informatics; Relevance (law); Dissemination; Work (physics); Information and Communications Technology; Focus (optics)","score_opus":0.041462060851000626,"score_gpt":0.2695124994402205,"score_spread":0.22805043858921986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415062055","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000043284646,0.00015150357,0.007530795,0.004130968,0.00050443975,0.00029239367,0.000008183395,0.00030154473,0.9870369],"genre_scores_gemma":[0.275046,0.012168227,0.1431586,0.08876882,0.002494487,0.0017348662,0.008057507,0.00020588037,0.46836564],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988144,0.000002815309,0.0005582189,0.00016703272,0.00028469827,0.00017283444],"domain_scores_gemma":[0.9972105,0.0000971456,0.00034979446,0.001197642,0.0011401507,0.000004756752],"candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00057502027,0.00016671907,0.00018328286,0.0025005604,0.0004075357,0.0017953026,0.0021227978,0.00014967826,0.000007718132],"category_scores_gemma":[0.00031916663,0.00016743499,0.000018205117,0.0031515912,0.0013428003,0.016132195,0.003318413,0.00034710884,0.00011335721],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000011592931,0.000010776663,0.00033857633,0.00012523624,0.0000026342948,9.32927e-8,0.000034895736,0.00003645466,1.6770777e-7,0.7662771,0.03189035,0.2012826],"study_design_scores_gemma":[0.000114874616,0.0000018723335,0.0018932486,0.0003684088,0.000004569959,0.0000012736151,0.000058510323,0.009192045,0.0000012830691,0.019554112,0.9686241,0.00018567097],"about_ca_topic_score_codex":0.000019041247,"about_ca_topic_score_gemma":0.00000853391,"teacher_disagreement_score":0.9367338,"about_ca_system_score_codex":0.00012544279,"about_ca_system_score_gemma":0.00043163865,"threshold_uncertainty_score":0.99924093},"labels":[],"label_agreement":null},{"id":"W4415092883","doi":"10.1007/978-3-032-08649-5_4","title":"Pairwise Clustering on Numerical Datasets by Translation","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Pairwise comparison; Cluster analysis; Partition (number theory); Categorical variable; Parameterized complexity; Constrained clustering; Set (abstract data type); Computation; Similarity (geometry)","score_opus":0.05057951670700949,"score_gpt":0.3428955448297427,"score_spread":0.2923160281227332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415092883","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000011069467,0.0002460418,0.9072669,0.0014870906,0.00017887643,0.00032686314,0.000085315856,0.00010313449,0.09030468],"genre_scores_gemma":[0.00838107,0.004857659,0.977915,0.0033122564,0.00006096394,0.000109672736,0.00091412134,0.000025682479,0.004423602],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980643,0.000043697604,0.00058964686,0.0003908842,0.00062339555,0.00028812332],"domain_scores_gemma":[0.9966418,0.00039395664,0.00018548204,0.0024829158,0.00017601188,0.00011980167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081254204,0.00023195818,0.00023387566,0.0009571788,0.00046778008,0.0006101686,0.0039063427,0.00011959448,0.000005023132],"category_scores_gemma":[0.000050048486,0.000241691,0.000036618112,0.000552618,0.00046919502,0.005529328,0.0027462845,0.0006007783,0.00004658934],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037334366,0.000016625225,0.0000016340186,0.000030178277,0.0000036439276,4.907487e-7,0.0003907122,0.0012397927,0.0000029010241,0.07181577,0.0014699097,0.9250246],"study_design_scores_gemma":[0.00020249106,0.000048636408,0.000028749273,0.00017755783,0.0000015148261,0.0000062210966,0.0000031646912,0.75433886,0.000009889047,0.0013447324,0.24364546,0.00019274467],"about_ca_topic_score_codex":0.000009700084,"about_ca_topic_score_gemma":0.0000032150379,"teacher_disagreement_score":0.92483187,"about_ca_system_score_codex":0.00022938744,"about_ca_system_score_gemma":0.00023225206,"threshold_uncertainty_score":0.9855873},"labels":[],"label_agreement":null},{"id":"W4415155604","doi":"10.1007/978-981-95-3358-9_33","title":"Integrating Information Retrieval and LLMs: A Document Retrieval Chatbot in Education Settings","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Chatbot; Relevance (law); Pipeline (software); Search engine indexing; Context (archaeology); Document retrieval; Question answering; Natural language; Automatic indexing","score_opus":0.018849564393143906,"score_gpt":0.2897360571952305,"score_spread":0.2708864928020866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415155604","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011633721,0.0014194623,0.75747555,0.0071235076,0.0012003003,0.0015895683,0.000013827018,0.00020476835,0.22980963],"genre_scores_gemma":[0.12827905,0.009290551,0.8505112,0.008910807,0.00012579943,0.00007096605,0.00024164062,0.000018882678,0.0025511144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977065,0.000048156675,0.0011635099,0.0003154211,0.00050957256,0.00025684456],"domain_scores_gemma":[0.99711454,0.00023864827,0.00050139043,0.0015701595,0.00048120282,0.00009406119],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0021274353,0.0002506465,0.0002812176,0.0019365428,0.00037066333,0.0012144531,0.0021477109,0.00017691814,0.0000030033905],"category_scores_gemma":[0.00025473564,0.00026310634,0.000032839347,0.0008119048,0.00037003023,0.014613837,0.0026011593,0.0006519709,0.000012329626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005465824,0.000008481593,0.000043676744,0.00007088234,0.0000023601217,9.032816e-8,0.0047620563,0.000079953425,0.0000019977433,0.5802877,0.000113630274,0.4146237],"study_design_scores_gemma":[0.00053427153,0.00006472122,0.001058459,0.0015244201,0.0000071594636,0.000028298864,0.00032242207,0.85615134,0.000024288627,0.029369973,0.11041113,0.00050350477],"about_ca_topic_score_codex":0.000046299607,"about_ca_topic_score_gemma":0.0000140358225,"teacher_disagreement_score":0.8560714,"about_ca_system_score_codex":0.00041984717,"about_ca_system_score_gemma":0.0010128355,"threshold_uncertainty_score":0.9999821},"labels":[],"label_agreement":null},{"id":"W4415204140","doi":"10.1007/978-3-032-08203-9_20","title":"Learning Structured Spatiotemporal Tasks with xLSTM Under Uncertainty: A Multi-task Approach","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Weighting; Benchmark (surveying); Task (project management); Scalability; Categorical variable; Bounding overwatch; Robotics; Variance (accounting); Reinforcement learning","score_opus":0.03748338588721219,"score_gpt":0.28239905072413085,"score_spread":0.24491566483691868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415204140","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002956256,0.00017067982,0.8695334,0.00054559996,0.00013398589,0.0004050854,0.0000057004554,0.00015994512,0.12901604],"genre_scores_gemma":[0.16669181,0.0006642912,0.8226186,0.0018777403,0.00003135084,0.00005156684,0.0002455469,0.00001785818,0.007801244],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978726,0.00008661402,0.0006749293,0.00045461455,0.0005989747,0.00031225092],"domain_scores_gemma":[0.9969468,0.00021169134,0.00049724255,0.001718314,0.00049348996,0.00013247758],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009877705,0.0003233975,0.00033313053,0.0012331152,0.00085606985,0.0010693527,0.0029151011,0.00017195879,0.000006562539],"category_scores_gemma":[0.000055728924,0.0002950212,0.0000513652,0.0007949494,0.00088362047,0.0045710406,0.0017459141,0.0009716658,0.00001806187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007360926,0.000022990487,0.00010977949,0.000046086643,0.00001832161,5.642516e-7,0.0045521446,0.056813546,0.000002374271,0.6493255,0.00010369834,0.28899765],"study_design_scores_gemma":[0.00058007456,0.00006563205,0.0012383622,0.00017110449,0.0000071862005,0.00001832741,0.00015853127,0.9195891,0.0000012886863,0.0016793947,0.07613575,0.00035523967],"about_ca_topic_score_codex":0.000036038837,"about_ca_topic_score_gemma":0.000026455535,"teacher_disagreement_score":0.86277556,"about_ca_system_score_codex":0.00020721984,"about_ca_system_score_gemma":0.0006912405,"threshold_uncertainty_score":0.99996763},"labels":[],"label_agreement":null},{"id":"W4415363525","doi":"10.1007/978-3-032-07370-9_26","title":"A Quantitative Assessment of Barriers to Economic Aid Access: DURANA Economic Area Case","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Taxation and Compliance Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Sustainable development; Economic risk; Quantitative assessment; Higher education; Economic impact analysis; Quantitative analysis (chemistry); Economic data","score_opus":0.09499830480304224,"score_gpt":0.35033738174620066,"score_spread":0.25533907694315844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415363525","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015159354,0.00060234446,0.055834975,0.0017845109,0.0005760409,0.00064573635,0.0006935312,0.000030080164,0.9383168],"genre_scores_gemma":[0.9218438,0.006629832,0.06547982,0.0021733167,0.000035354984,0.000154325,0.000100488825,0.00001843654,0.0035646218],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846435,0.000009248376,0.0010705868,0.0002625404,0.00004296073,0.00015032382],"domain_scores_gemma":[0.9978956,0.0001464326,0.0007551911,0.000993316,0.00010285557,0.00010658517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006860382,0.00017232055,0.0004271116,0.0013286042,0.00036027704,0.00026141378,0.001195488,0.000066696346,0.00014091571],"category_scores_gemma":[0.00006120801,0.0002086564,0.00006193399,0.00016438414,0.0004988661,0.0024661876,0.0011881121,0.00018460517,0.00009118765],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034104094,0.0000046102937,0.0016194774,0.000027120173,0.000019649095,3.464436e-7,0.0008770172,0.0021715115,6.794483e-8,0.99007595,0.0008903811,0.0043104854],"study_design_scores_gemma":[0.00092181884,0.00017529119,0.012337216,0.00038487057,0.00001499094,0.000034370285,0.0006260587,0.5018201,0.000003525551,0.046554137,0.43630514,0.0008225334],"about_ca_topic_score_codex":0.00016982236,"about_ca_topic_score_gemma":0.00021652126,"teacher_disagreement_score":0.9435218,"about_ca_system_score_codex":0.00043550273,"about_ca_system_score_gemma":0.00038007123,"threshold_uncertainty_score":0.85087615},"labels":[],"label_agreement":null},{"id":"W4415515862","doi":"10.1007/978-3-032-07373-0_35","title":"AI-Driven Evolution: Bridging 5G and 6G for a Hyper-connected Future","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Bridging (networking); Key (lock); Transformative learning; Implementation; Automation; Wireless","score_opus":0.016934256962361838,"score_gpt":0.269169888135471,"score_spread":0.25223563117310915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415515862","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003154303,0.0008202335,0.95376325,0.007013667,0.00024718457,0.0006750419,0.000037363818,0.00014971009,0.037261996],"genre_scores_gemma":[0.130779,0.0058673276,0.844859,0.008716953,0.00041549955,0.0005694183,0.0005638459,0.00003454277,0.008194396],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986421,0.00001813379,0.00052838476,0.00034962647,0.00024228376,0.000219462],"domain_scores_gemma":[0.99723494,0.00020533006,0.00022238662,0.001807872,0.00043714355,0.00009231514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048288255,0.00020742165,0.00023840331,0.0008077157,0.0008274129,0.0007095442,0.0023035125,0.00013370493,0.0000023421267],"category_scores_gemma":[0.000028921097,0.00021763702,0.000050685696,0.00052599976,0.00050745695,0.0038028455,0.0015566028,0.00031329974,0.000010680834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.647203e-7,0.0000073071033,0.000016792425,0.00003243691,0.0000038459566,5.6017626e-8,0.00043394166,0.000037331673,0.000007198323,0.8223638,0.0009105418,0.1761859],"study_design_scores_gemma":[0.00025483832,0.000020777512,0.00067281927,0.00012730595,0.000007809188,0.000019224814,0.000014679847,0.69267577,0.000007677847,0.009900332,0.29608467,0.00021408343],"about_ca_topic_score_codex":0.000008394528,"about_ca_topic_score_gemma":0.000012478403,"teacher_disagreement_score":0.81246346,"about_ca_system_score_codex":0.00012898985,"about_ca_system_score_gemma":0.00038839714,"threshold_uncertainty_score":0.887498},"labels":[],"label_agreement":null},{"id":"W4415515869","doi":"10.1007/978-3-032-07373-0_3","title":"Facial Spoof Detection Using Deep Learning Techniques for Enhanced Biometric Security","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Liveness; Spoofing attack; Biometrics; Convolutional neural network; Deep learning; Authentication (law); Vulnerability (computing); Facial recognition system","score_opus":0.03878836484766509,"score_gpt":0.3157351913628646,"score_spread":0.27694682651519953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415515869","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007987694,0.00030175172,0.9648908,0.00012875372,0.00039913086,0.0006189316,0.000012951932,0.00017147519,0.03339634],"genre_scores_gemma":[0.3813896,0.0038411848,0.6119665,0.00063307944,0.00009919145,0.00013057436,0.00013772727,0.000016007893,0.0017861215],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818635,0.0000444017,0.0007429847,0.00037110917,0.00041099064,0.00024414406],"domain_scores_gemma":[0.9970273,0.00029493685,0.0004711791,0.0012846937,0.00084165565,0.00008025278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015819478,0.00021572303,0.00026775533,0.005493619,0.0009822585,0.00087712577,0.0025102461,0.00022492651,0.0000034785264],"category_scores_gemma":[0.00022765066,0.00023903142,0.00007851557,0.003027764,0.0004939041,0.0045722476,0.0015575826,0.0004539081,0.000008108674],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026549285,0.000015858783,0.000005582349,0.000054016426,0.000005302145,4.4354913e-8,0.0010745154,0.000021056841,0.00008982729,0.14647391,0.00001307698,0.85224414],"study_design_scores_gemma":[0.00022998729,0.00005705961,0.00016681901,0.000106615,0.000009314985,0.000006553966,0.000023404149,0.7585339,0.0015892821,0.008413796,0.23052341,0.00033985797],"about_ca_topic_score_codex":0.000024362593,"about_ca_topic_score_gemma":0.000014243575,"teacher_disagreement_score":0.8519043,"about_ca_system_score_codex":0.00032582722,"about_ca_system_score_gemma":0.00026682968,"threshold_uncertainty_score":0.9747418},"labels":[],"label_agreement":null},{"id":"W4415515884","doi":"10.1007/978-3-032-07373-0_11","title":"Computer-Aided Diagnosis in Uterus Imaging","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Feature (linguistics); MATLAB; Pattern recognition (psychology); Process (computing); Principal component analysis; Image (mathematics); Interface (matter); Artificial neural network","score_opus":0.026755272656608018,"score_gpt":0.2908461129273004,"score_spread":0.26409084027069235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415515884","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000043667,0.00080422347,0.8423016,0.0028546865,0.0011674622,0.0005982499,0.000011723069,0.00019333638,0.15202503],"genre_scores_gemma":[0.088755734,0.017682297,0.8820423,0.008387722,0.00022830702,0.00043599625,0.00008510703,0.000036154484,0.002346387],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99762964,0.000056125038,0.0009820835,0.00049257383,0.00049546803,0.00034411516],"domain_scores_gemma":[0.9960685,0.0004227245,0.00037997088,0.0026944513,0.0003382096,0.00009619179],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012279894,0.00030288476,0.00035096137,0.0024779479,0.00040171936,0.00091660034,0.0046009496,0.00013339656,0.000007140994],"category_scores_gemma":[0.000038606326,0.0003399743,0.000061534556,0.0010821582,0.00068766956,0.008796072,0.0045235553,0.00066732476,0.000039699724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000014516079,0.000015444783,0.00044916203,0.000034486435,0.0000032511218,0.0000011707237,0.00091628655,0.00042302354,5.150424e-7,0.24753787,0.00075165374,0.7498657],"study_design_scores_gemma":[0.00039660127,0.000036479534,0.003689404,0.0006534969,0.0000041028043,0.000022598655,0.000009565166,0.829448,0.000016119599,0.012065911,0.15325545,0.00040229023],"about_ca_topic_score_codex":0.00007548726,"about_ca_topic_score_gemma":0.00005652922,"teacher_disagreement_score":0.829025,"about_ca_system_score_codex":0.000582249,"about_ca_system_score_gemma":0.00047696315,"threshold_uncertainty_score":0.9999052},"labels":[],"label_agreement":null},{"id":"W4415516344","doi":"10.1007/978-3-032-07373-0_9","title":"Defeating CAPTCHAs with CNN-Based Image Recognition: Methods and Mitigation Strategies","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"CAPTCHA; Turing test; Convolutional neural network; Deep learning; Image (mathematics); Compromise; Training set","score_opus":0.04220966204467223,"score_gpt":0.33378958429945726,"score_spread":0.291579922254785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415516344","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010879469,0.00026856991,0.8856446,0.001416344,0.00011640219,0.00043619872,0.000010941621,0.000112257556,0.11188589],"genre_scores_gemma":[0.05025574,0.00040495527,0.9475555,0.0009705596,0.000021146292,0.0000682677,0.00010758798,0.000008557956,0.0006077036],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984399,0.00009746074,0.0006174972,0.0003251616,0.00033837155,0.00018162608],"domain_scores_gemma":[0.99713284,0.0004045818,0.00036239196,0.0013832389,0.0006248079,0.000092144954],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0014150108,0.00021951238,0.00024899366,0.0009315076,0.0005524892,0.0016168102,0.0014660204,0.00011025724,0.000005406187],"category_scores_gemma":[0.000049139042,0.00020758563,0.000029759054,0.0004981603,0.0008567494,0.006423502,0.0007260013,0.00032827826,0.000013953143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033412982,0.0000173208,0.000038737704,0.00016068523,0.000011025222,4.327073e-7,0.013190224,0.000024224075,0.000017871713,0.67634875,0.00007104723,0.31011635],"study_design_scores_gemma":[0.00054031203,0.00008111235,0.0005910553,0.00085230975,0.000017385648,0.000027772581,0.00025660027,0.9373526,0.00010821232,0.035080917,0.024621138,0.00047060405],"about_ca_topic_score_codex":0.000022209635,"about_ca_topic_score_gemma":0.000026655583,"teacher_disagreement_score":0.93732834,"about_ca_system_score_codex":0.00008445217,"about_ca_system_score_gemma":0.00057916186,"threshold_uncertainty_score":0.9994196},"labels":[],"label_agreement":null},{"id":"W4415536294","doi":"10.1007/978-3-032-07742-4","title":"Artificial Intelligence of Things","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National University of Computer and Emerging Sciences; Mälardalens högskola; Università Politecnica delle Marche; Zhejiang Shuren University; Universiti Kebangsaan Malaysia; University of Technology Sydney; York University; Prince Sattam bin Abdulaziz University; University of Central Punjab; Hamad Bin Khalifa University; Multimedia University; Université de Lille; University of Hail; SRM Institute of Science and Technology; University of Derby; Iqra University; New York University Abu Dhabi; Khalifa University of Science, Technology and Research; Glasgow Caledonian University; Yeditepe Üniversitesi; Norges Teknisk-Naturvitenskapelige Universitet; Southern Connecticut State University","keywords":"Scope (computer science); Variety (cybernetics); Relevance (law); Informatics; Dissemination; Selection (genetic algorithm); Focus (optics)","score_opus":0.0497464842694762,"score_gpt":0.3152909001273997,"score_spread":0.2655444158579235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415536294","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012061075,0.00024572553,0.86941695,0.0008836044,0.00045074066,0.00034721327,0.000006037145,0.000086410786,0.12855127],"genre_scores_gemma":[0.01618232,0.0011752252,0.9795799,0.0013568334,0.000049855866,0.000041170748,0.000043535707,0.000007101855,0.0015640574],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747217,0.00008137433,0.001218012,0.00037336588,0.0005884236,0.00026664106],"domain_scores_gemma":[0.994857,0.0006846037,0.00047707724,0.0031527975,0.00074533094,0.00008318007],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0020839027,0.00022761067,0.00036954042,0.0014872983,0.00032399292,0.00050971296,0.0073843435,0.0001487415,0.0000043364385],"category_scores_gemma":[0.00018646765,0.00023232315,0.00006904393,0.0017989585,0.0014483973,0.0072393254,0.0067872866,0.0005253609,0.000020625977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.444468e-7,0.00002464958,0.000007961768,0.000043893917,0.0000023917626,1.2548715e-7,0.0015593072,0.00027070363,9.134471e-7,0.49332902,0.0001513459,0.5046089],"study_design_scores_gemma":[0.000036390047,0.000050107432,0.00023005733,0.00021225004,0.0000038652593,0.0000072126118,0.000023068913,0.82223195,0.00006382918,0.16129862,0.015614895,0.00022775878],"about_ca_topic_score_codex":0.000024516574,"about_ca_topic_score_gemma":0.0000055777405,"teacher_disagreement_score":0.8219612,"about_ca_system_score_codex":0.00025802015,"about_ca_system_score_gemma":0.0014612286,"threshold_uncertainty_score":0.9979862},"labels":[],"label_agreement":null},{"id":"W4415536403","doi":"10.1007/978-3-032-07742-4_4","title":"SmartSync: Revolutionizing Remote Work with AIoT Virtual Office Interactivity","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Interactivity; Work (physics); Control (management); Coronavirus disease 2019 (COVID-19); On demand; Virtual machine; Virtual reality","score_opus":0.02833660766669386,"score_gpt":0.2526477801238171,"score_spread":0.22431117245712326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415536403","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006096598,0.00034051327,0.4698181,0.002496199,0.00029942312,0.00029139608,0.00000460735,0.00016029982,0.5259798],"genre_scores_gemma":[0.9319301,0.0017179175,0.048118982,0.006264081,0.00042567097,0.000021598422,0.00033196848,0.000032831424,0.011156821],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876165,0.0000064258957,0.00047909346,0.00024512204,0.000331138,0.00017658026],"domain_scores_gemma":[0.9976425,0.0001049799,0.00043247125,0.0010069337,0.00079798483,0.000015126135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072282035,0.00020929027,0.00025775752,0.0013378996,0.00067938113,0.0009192165,0.0011066776,0.000090092384,0.0000126697],"category_scores_gemma":[0.00008036116,0.00019189398,0.00004104193,0.0010606827,0.00052579073,0.008285231,0.0012930022,0.00042558418,0.000056249464],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003246493,0.000024852827,0.0004554701,0.00017257452,0.000022627699,4.6945888e-7,0.00020725741,0.0041124024,6.5697253e-7,0.23345768,0.00076371495,0.7607498],"study_design_scores_gemma":[0.0002665681,0.000008099838,0.0011168806,0.0016591778,0.00005527026,0.0000031648606,0.000038731054,0.73513097,4.5648667e-7,0.0021217014,0.25920844,0.00039054622],"about_ca_topic_score_codex":0.00019359989,"about_ca_topic_score_gemma":0.000077737954,"teacher_disagreement_score":0.9313205,"about_ca_system_score_codex":0.00010151234,"about_ca_system_score_gemma":0.00016300922,"threshold_uncertainty_score":0.8864026},"labels":[],"label_agreement":null},{"id":"W4415560381","doi":"10.1007/978-981-95-1581-3_11","title":"Performance Analysis of Microservice Systems in Cloud-Edge Collaborative Environments: An Empirical Study","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Cloud computing; Microservices; Edge computing; Software deployment; Quality of service; Enhanced Data Rates for GSM Evolution; Server; Empirical research","score_opus":0.02625433542347819,"score_gpt":0.3151935627080368,"score_spread":0.28893922728455856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415560381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39514935,0.0038104388,0.378319,0.0014372973,0.003980771,0.010852417,0.00035428224,0.00042760943,0.20566885],"genre_scores_gemma":[0.9880079,0.0013509351,0.009585086,0.0002480395,0.000018000444,0.000089869245,0.00008814467,0.000005866325,0.0006061656],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972727,0.00013701356,0.0013059761,0.00041799655,0.00064513483,0.00022118833],"domain_scores_gemma":[0.99564725,0.00024425163,0.00052560755,0.0030000338,0.00050386117,0.00007900793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026319404,0.00024560618,0.0006064333,0.0024503395,0.00028537694,0.00030542442,0.0036093246,0.00015408453,0.0000020904865],"category_scores_gemma":[0.00003285019,0.00022825703,0.00005242649,0.0029821885,0.0005588113,0.005670368,0.0019852426,0.000370742,0.000008648753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006880629,0.0016656319,0.51516217,0.00084126025,0.000551086,0.000002707507,0.111373715,0.07586367,0.000016198359,0.069348164,0.00038712798,0.22471945],"study_design_scores_gemma":[0.00040272667,0.00018080664,0.14243136,0.0002009171,0.000048567363,0.00000172609,0.00035321157,0.843556,0.0000034132304,0.000059236452,0.012494999,0.0002670166],"about_ca_topic_score_codex":0.00009266154,"about_ca_topic_score_gemma":0.00008240443,"teacher_disagreement_score":0.7676923,"about_ca_system_score_codex":0.00029118202,"about_ca_system_score_gemma":0.00044379424,"threshold_uncertainty_score":0.93080515},"labels":[],"label_agreement":null},{"id":"W4415681780","doi":"10.1007/978-981-95-4142-3_9","title":"BFCSR: A Blockchain-Based Federated Learning Framework with Client Selection and Round-Based Training Scheme","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Federated learning; Scheme (mathematics); Selection (genetic algorithm); Training (meteorology); Training set; Feature selection","score_opus":0.041497626029193366,"score_gpt":0.2917048710542572,"score_spread":0.2502072450250638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415681780","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043960102,0.00021799498,0.97810954,0.0064476873,0.00010818152,0.00040841402,0.0000071379704,0.0005067543,0.013754661],"genre_scores_gemma":[0.094203785,0.00019392416,0.90438735,0.000992188,0.000011366976,0.00004540382,0.000040326093,0.00000912188,0.00011654689],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980109,0.00006317917,0.0005918266,0.00049535587,0.0005047343,0.00033400182],"domain_scores_gemma":[0.99417245,0.0006861929,0.0004134635,0.0041817105,0.00045825014,0.00008794849],"candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0013047637,0.0003010202,0.00030550722,0.0014052682,0.0011762126,0.0012990772,0.010651977,0.00026020643,0.0000032968567],"category_scores_gemma":[0.0017645397,0.00029493266,0.000029674155,0.0011683146,0.0009017663,0.0016984898,0.017552441,0.0012338628,0.000004788099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002570759,0.000047508838,0.0006340148,0.0001680526,0.000031510885,0.000001862565,0.0011880388,0.010833447,0.000011325632,0.35954085,0.0010937522,0.62642395],"study_design_scores_gemma":[0.00036085816,0.00011806634,0.00020323337,0.000801683,0.0000056987847,0.0000108079485,0.000024436315,0.9670966,0.000027616667,0.014517367,0.01652003,0.0003135648],"about_ca_topic_score_codex":0.000016505635,"about_ca_topic_score_gemma":0.000021746404,"teacher_disagreement_score":0.9562632,"about_ca_system_score_codex":0.00024983627,"about_ca_system_score_gemma":0.00088524853,"threshold_uncertainty_score":0.9999503},"labels":[],"label_agreement":null},{"id":"W4415688799","doi":"10.1007/978-3-032-04339-9_15","title":"Enhancing Off-Policy Method SAC with KAN for Continuous Reinforcement Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Reinforcement learning; Embedding; Architecture; Reinforcement; Artificial neural network","score_opus":0.02445174135414655,"score_gpt":0.3154284189345152,"score_spread":0.2909766775803686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415688799","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000011933678,0.000111990965,0.8438277,0.00076281815,0.00015000999,0.00068826193,0.0000017946514,0.000120403034,0.15433578],"genre_scores_gemma":[0.004356877,0.0013471133,0.97230244,0.0015038586,0.000058410835,0.000100257515,0.00007869597,0.000014887399,0.020237476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99763435,0.000049501148,0.00097165164,0.0003775605,0.00056388613,0.0004030497],"domain_scores_gemma":[0.9957124,0.0007092893,0.000690995,0.0020223316,0.0007533414,0.00011161428],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019747883,0.00032174808,0.00041823144,0.0016462527,0.0008701669,0.00095491234,0.0034296117,0.00014324328,0.0000038648104],"category_scores_gemma":[0.00022765217,0.00030660557,0.00006701078,0.00069346325,0.0004835515,0.004485288,0.0024796834,0.00063104625,0.000014658189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000045103516,0.0000037373104,0.000012706351,0.00006122538,0.000013423278,1.5460172e-7,0.0013805656,0.21618104,0.0000023986606,0.62596166,0.000106206644,0.1562724],"study_design_scores_gemma":[0.00039843132,0.0001701078,0.000033396744,0.00041245727,0.000009894019,0.000009753071,0.000028684697,0.76690054,0.00003111582,0.000995073,0.23072338,0.00028716843],"about_ca_topic_score_codex":0.000021545275,"about_ca_topic_score_gemma":0.000008748911,"teacher_disagreement_score":0.62496656,"about_ca_system_score_codex":0.0003296437,"about_ca_system_score_gemma":0.0010120324,"threshold_uncertainty_score":0.9999386},"labels":[],"label_agreement":null},{"id":"W4415688800","doi":"10.1007/978-3-032-04339-9_17","title":"Investigating Zero-Shot Diagnostic Pathology in Vision-Language Models with Efficient Prompt Design","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Université de Montréal; Concordia University","funders":"","keywords":"Context (archaeology); Domain (mathematical analysis); Task (project management); Digital pathology; Computational model; Clinical Practice; Computational Science and Engineering","score_opus":0.0419747694207174,"score_gpt":0.29572737156089596,"score_spread":0.2537526021401786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415688800","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020985412,0.000421865,0.9568287,0.00057025685,0.0001973035,0.00079861336,0.0000049192245,0.000101460755,0.040867038],"genre_scores_gemma":[0.25611684,0.0010051607,0.7408213,0.0013413619,0.000022069487,0.00022098754,0.000026481284,0.000015417729,0.00043038683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99788904,0.00010162205,0.0007575027,0.00045266168,0.0004937037,0.0003054636],"domain_scores_gemma":[0.99612844,0.001009909,0.00037955574,0.0020870683,0.00030283313,0.000092202004],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016464918,0.00026756772,0.0003013634,0.0015465062,0.000394001,0.00048594334,0.0029167605,0.00015183748,0.0000018168842],"category_scores_gemma":[0.00015336067,0.00025253685,0.000026962729,0.0010211833,0.00096319773,0.004018753,0.002224984,0.00062678044,0.000011314223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050178173,0.000042224237,0.00005313288,0.00008281743,0.0000058625697,0.000004685829,0.0111105535,0.22262067,0.000012578492,0.45170328,0.00015575804,0.3142034],"study_design_scores_gemma":[0.00033772393,0.00011787738,0.00041652756,0.00080717896,0.0000041543467,0.00003726765,0.000028625851,0.9848402,0.000028763208,0.012313134,0.0007894443,0.0002790634],"about_ca_topic_score_codex":0.000028328017,"about_ca_topic_score_gemma":0.000024784962,"teacher_disagreement_score":0.76221955,"about_ca_system_score_codex":0.00036502082,"about_ca_system_score_gemma":0.0007191742,"threshold_uncertainty_score":0.99999267},"labels":[],"label_agreement":null},{"id":"W4415688834","doi":"10.1007/978-3-032-04339-9","title":"Deep Learning Theory and Applications","year":2025,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universidade Federal de Pernambuco; Akademia Górniczo-Hutnicza im. Stanislawa Staszica; Universitat Rovira i Virgili; Universitatea Politehnica Timisoara; Kungliga Tekniska Högskolan; Inha University; Université de Sherbrooke; Sungkyunkwan University; U.S. National Library of Medicine; Washington University in St. Louis; Intel Corporation; University of Regina; Florida State University; TU Graz, Internationale Beziehungen und Mobilitätsprogramme; King Mongkut's University of Technology North Bangkok; Trakya Üniversitesi","keywords":"Scope (computer science); Relevance (law); Informatics; Variety (cybernetics); Dissemination; Focus (optics); Selection (genetic algorithm)","score_opus":0.015268337802681388,"score_gpt":0.28982550628515896,"score_spread":0.2745571684824776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415688834","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000001505824,0.0010196724,0.74174523,0.00043274695,0.00006732939,0.0003641487,0.000003031889,0.00008653743,0.25627977],"genre_scores_gemma":[0.024520587,0.03437302,0.85316646,0.011257061,0.0004255945,0.0020830613,0.0009869741,0.00005412443,0.07313313],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985494,0.00009185907,0.0005089814,0.0003494599,0.00030267774,0.00019759874],"domain_scores_gemma":[0.99676925,0.000965878,0.0002591031,0.00151741,0.00038871003,0.000099626115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012667676,0.00019326535,0.00020856048,0.00088329933,0.00054966426,0.00054229255,0.0024938493,0.000094119016,0.0000038259814],"category_scores_gemma":[0.000048507172,0.00020894491,0.000034730067,0.0008341072,0.0007399138,0.0034887134,0.003038326,0.00050494075,0.000030230405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.798727e-7,0.00000881005,0.000008079319,0.000018504197,0.0000028964168,2.72372e-8,0.00047021508,0.00035879234,2.6925125e-7,0.6623811,0.00027246893,0.33647832],"study_design_scores_gemma":[0.0001018345,0.000010989346,0.0005320125,0.000049869497,0.0000042918587,0.0000053835356,0.000012081974,0.35516623,4.5475298e-7,0.16825458,0.47570202,0.00016024266],"about_ca_topic_score_codex":0.0000045773804,"about_ca_topic_score_gemma":0.0000028598968,"teacher_disagreement_score":0.49412656,"about_ca_system_score_codex":0.00022983308,"about_ca_system_score_gemma":0.00078554236,"threshold_uncertainty_score":0.8520526},"labels":[],"label_agreement":null},{"id":"W4415721238","doi":"10.1007/978-3-032-05855-3_3","title":"An Effective LSTM – Autoencoder Approach with Acoustic Features in Indian Classical Music Raga Recognition","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Deep learning; Autoencoder; Convolutional neural network; Melody; Context (archaeology); Music information retrieval; Classical music; Expansive","score_opus":0.02437012310604605,"score_gpt":0.2695947727221223,"score_spread":0.24522464961607623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415721238","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018715486,0.00015088734,0.8380142,0.0005057588,0.00014461516,0.0006372559,0.000008942733,0.00010087322,0.16025035],"genre_scores_gemma":[0.33166245,0.00049507804,0.661273,0.0049170237,0.00008801932,0.0002331945,0.00025833814,0.000019159776,0.0010537625],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983143,0.00007426159,0.00048779574,0.00043281683,0.00041833863,0.00027248988],"domain_scores_gemma":[0.9976242,0.00022472671,0.0002806273,0.0014623244,0.00030323464,0.00010487086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000932485,0.00026091083,0.0002974323,0.0014392666,0.00046268935,0.0008958679,0.002453222,0.0001839708,0.0000032632972],"category_scores_gemma":[0.00003659357,0.000230185,0.00002951539,0.00090449856,0.00080278976,0.0073581394,0.0009811383,0.000767194,0.000008750472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075331764,0.00005891416,0.000038476945,0.00010625913,0.000005893352,0.0000016739697,0.006336323,0.0019132859,0.0000031541845,0.058404602,0.00029855338,0.9328253],"study_design_scores_gemma":[0.000657085,0.0001412,0.006553561,0.0009906342,0.0000112298,0.00006410001,0.00009774994,0.9776513,0.000012382883,0.008102294,0.005185584,0.0005328675],"about_ca_topic_score_codex":0.000015533944,"about_ca_topic_score_gemma":0.000061052866,"teacher_disagreement_score":0.97573805,"about_ca_system_score_codex":0.0001978541,"about_ca_system_score_gemma":0.000491569,"threshold_uncertainty_score":0.9386672},"labels":[],"label_agreement":null},{"id":"W4416052776","doi":"10.1007/978-981-95-2566-9_33","title":"Research on Industrial Big Data Display Systems Based on Grafana and ECharts","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Big data; Data transformation; Data quality; Message queue; Reliability (semiconductor); Visualization; Data processing; Quality (philosophy); Data visualization","score_opus":0.36353078946716916,"score_gpt":0.3788026441360725,"score_spread":0.01527185466890335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416052776","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024385656,0.00028086753,0.16060492,0.0027714167,0.0012839581,0.0008916432,0.0003732842,0.000090210946,0.8336793],"genre_scores_gemma":[0.88468486,0.009041855,0.06688193,0.015381144,0.0011447419,0.00037994783,0.005750845,0.00007025349,0.016664434],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99807906,0.00007223253,0.00054220296,0.00048778253,0.00056700787,0.0002516865],"domain_scores_gemma":[0.9934551,0.0008705511,0.00017927734,0.0051176306,0.00024704068,0.00013037269],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0026252454,0.00019072813,0.00022784733,0.0018363834,0.00061025197,0.0021151744,0.0060461713,0.00016341104,0.0000012744189],"category_scores_gemma":[0.00010505487,0.00017737085,0.000017160375,0.00060841045,0.00084359065,0.005628795,0.0061503844,0.0007241654,0.000042675183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035242238,0.000015029977,0.000011397896,0.000018944791,0.0000021665785,3.3874866e-7,0.00007113061,0.00015374534,4.3253173e-8,0.6677449,0.004135543,0.32784328],"study_design_scores_gemma":[0.00025087947,0.00007699694,0.000099665274,0.0004772143,0.000001545477,0.0000028817772,0.000009047108,0.59800875,7.873618e-7,0.0013787921,0.3995409,0.00015254045],"about_ca_topic_score_codex":0.000033507084,"about_ca_topic_score_gemma":0.000010511893,"teacher_disagreement_score":0.8846605,"about_ca_system_score_codex":0.000117786716,"about_ca_system_score_gemma":0.00064588874,"threshold_uncertainty_score":0.9993316},"labels":[],"label_agreement":null},{"id":"W4416142091","doi":"10.1007/978-981-95-4409-7_19","title":"Task-Specific Knowledge Distillation for Scalable Sentiment Classification in Low-Resource Settings","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Scalability; Sentiment analysis; Limiting; Distillation; Software deployment; Enhanced Data Rates for GSM Evolution","score_opus":0.03929592685276493,"score_gpt":0.3017272538036325,"score_spread":0.26243132695086757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416142091","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006863883,0.000939798,0.80824757,0.0017729389,0.0003329455,0.0008726462,0.000016830918,0.00008187901,0.18766677],"genre_scores_gemma":[0.17780207,0.009908703,0.7720573,0.0028067152,0.00033059478,0.0006005267,0.0022814083,0.00005976194,0.034152918],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979604,0.00004055048,0.0009686413,0.0004330039,0.0003383899,0.00025899723],"domain_scores_gemma":[0.99718386,0.00032529698,0.00044890147,0.0015958184,0.00037536415,0.00007076716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015861277,0.00022552477,0.00029613686,0.0017211947,0.0004665403,0.00077076495,0.0021326647,0.00013053152,0.000005593392],"category_scores_gemma":[0.00003621789,0.00023974793,0.00007648345,0.00089652877,0.00032279067,0.0033421095,0.0013415933,0.00026377887,0.000029657474],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030833603,0.000035231093,0.00009630109,0.000052811774,0.0000068157437,6.1850635e-8,0.001602363,0.00047161203,0.000008437996,0.7218515,0.002669915,0.27320185],"study_design_scores_gemma":[0.0002622483,0.00001341377,0.0009043868,0.00036574333,0.000003940998,8.5652624e-7,0.00003147641,0.65833586,0.000012065557,0.0012383955,0.33865258,0.00017901066],"about_ca_topic_score_codex":0.000003088478,"about_ca_topic_score_gemma":0.000006677068,"teacher_disagreement_score":0.7206131,"about_ca_system_score_codex":0.00030133646,"about_ca_system_score_gemma":0.00022424526,"threshold_uncertainty_score":0.97766364},"labels":[],"label_agreement":null},{"id":"W4416230884","doi":"10.1007/978-3-032-09598-5_1","title":"Securing Automatic Identification System Based on Certificateless Cryptography","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Cryptography; Authentication (law); Scheme (mathematics); Identification (biology); State (computer science); Public-key cryptography","score_opus":0.017354794187825595,"score_gpt":0.24533580215148462,"score_spread":0.22798100796365903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416230884","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009187994,0.00016151168,0.22433206,0.00025568242,0.00051729055,0.0005834654,0.00004848723,0.00054604147,0.77346355],"genre_scores_gemma":[0.97567827,0.00074722135,0.022009173,0.00042295625,0.000034774745,0.00011198019,0.0003871048,0.000023439732,0.000585104],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998602,0.000021048209,0.00073909754,0.00016171642,0.00032739033,0.00014876825],"domain_scores_gemma":[0.9981094,0.000160715,0.00014839426,0.0013138034,0.00020392255,0.000063776024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067333184,0.00018994037,0.00020353906,0.0013969388,0.00031357195,0.00034655182,0.0009856124,0.00012636122,0.000015914386],"category_scores_gemma":[0.000015771495,0.00020815783,0.000048808906,0.00047143293,0.00029200118,0.0012554487,0.00019367269,0.0003495426,0.0000548715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023928617,0.0000136159315,0.000028724839,0.0007504677,0.000010329703,2.4501165e-7,0.0005187262,0.020571059,0.000007522851,0.6399035,0.0005426103,0.3376508],"study_design_scores_gemma":[0.00014851966,0.0000070476763,0.000799944,0.0007107358,0.0000068765207,0.0000016403274,0.000019255414,0.9726826,0.000029190182,0.00047175508,0.024934957,0.00018749428],"about_ca_topic_score_codex":0.0000026057794,"about_ca_topic_score_gemma":0.000001889391,"teacher_disagreement_score":0.97558635,"about_ca_system_score_codex":0.00022604008,"about_ca_system_score_gemma":0.000090028974,"threshold_uncertainty_score":0.848843},"labels":[],"label_agreement":null},{"id":"W4416260937","doi":"10.1007/978-981-95-4109-6_33","title":"Semantic Consistency Guided Backdoor Trigger Inversion and InitDistillNet for Backdoor Detection","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Novelis (Canada)","funders":"","keywords":"Backdoor; Inversion (geology); Outlier; Anomaly detection; Consistency (knowledge bases)","score_opus":0.034931989835471036,"score_gpt":0.3011699993093499,"score_spread":0.2662380094738789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416260937","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006253844,0.0002843459,0.9353829,0.0013355997,0.0005685054,0.0007460214,0.00001255245,0.0001075724,0.061499983],"genre_scores_gemma":[0.1990201,0.0043137115,0.7842386,0.0036933415,0.0001452767,0.00016502338,0.00017704541,0.000034970642,0.008211942],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981569,0.00005640664,0.000782818,0.00041309907,0.00033772405,0.00025307084],"domain_scores_gemma":[0.99668866,0.00067543896,0.00043753744,0.0015652921,0.000531796,0.00010125287],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001359845,0.00026921928,0.00034082323,0.001176502,0.000930713,0.0005983271,0.002096683,0.00018970351,0.0000054734737],"category_scores_gemma":[0.00029808754,0.00027663968,0.000059414466,0.00044038158,0.0008503413,0.0046454277,0.002755253,0.00045942608,0.000016153299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009002159,0.000012520507,0.000046022156,0.00015995525,0.000012354688,3.1405241e-7,0.0011089691,0.00050992385,0.000008568012,0.54358625,0.00080046727,0.45374566],"study_design_scores_gemma":[0.000612379,0.00006162205,0.0003478712,0.00026504335,0.000016595024,0.00001839238,0.000023190449,0.8723811,0.000017130496,0.010034648,0.11590804,0.0003139873],"about_ca_topic_score_codex":0.000021301217,"about_ca_topic_score_gemma":0.000016413678,"teacher_disagreement_score":0.8718712,"about_ca_system_score_codex":0.00017089906,"about_ca_system_score_gemma":0.0003607253,"threshold_uncertainty_score":0.9999686},"labels":[],"label_agreement":null},{"id":"W4416340285","doi":"10.1007/978-3-032-07083-8_7","title":"Reverberation Time as an Acoustic Biomarker for Speech Impairment in Parkinson Disease","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Reverberation; Random forest; Decision tree; Disease; Classifier (UML); Intelligibility (philosophy)","score_opus":0.02856977296647215,"score_gpt":0.326797927876852,"score_spread":0.29822815491037985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416340285","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016283141,0.0025771898,0.15501457,0.023638416,0.0009393132,0.013892458,0.00034414686,0.00036793106,0.78694284],"genre_scores_gemma":[0.5343832,0.023567451,0.32538053,0.029640278,0.00026790344,0.0010049914,0.008188865,0.00009459181,0.07747219],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887866,0.000017762291,0.0004989863,0.00019601805,0.0002530945,0.00015549286],"domain_scores_gemma":[0.99839216,0.00011002782,0.00013359239,0.0009959075,0.00025397987,0.00011433264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007253561,0.00014938992,0.00020906543,0.00090196804,0.00019532499,0.00013970456,0.0004582311,0.000093684015,0.000023856419],"category_scores_gemma":[0.00009217358,0.0001476296,0.000042149284,0.00025152718,0.00027963103,0.0018760065,0.00027058535,0.00018692254,0.000030869393],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040838082,0.0004546437,0.0022320296,0.0007994872,0.00003679913,0.00000472985,0.0031212517,0.00043979115,0.00010913235,0.050015688,0.0075852666,0.9347928],"study_design_scores_gemma":[0.0016903932,0.00026523546,0.01997179,0.0011202735,0.000056967423,0.00001445389,0.00006457084,0.6787214,0.000010956386,0.006121682,0.29161167,0.00035057243],"about_ca_topic_score_codex":0.000017906541,"about_ca_topic_score_gemma":0.000032486514,"teacher_disagreement_score":0.9344422,"about_ca_system_score_codex":0.00018929699,"about_ca_system_score_gemma":0.0005733258,"threshold_uncertainty_score":0.60201603},"labels":[],"label_agreement":null},{"id":"W4416633744","doi":"10.1007/978-981-95-4499-8_9","title":"Scaffolding Computer Programming Learning for Novice Learners Using LLM as a Conversational Resource","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Education and Digital Technologies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of the Fraser Valley; Douglas College","funders":"","keywords":"WebQuest; Syntax; Scaffold; Resource (disambiguation); Java Programming Language; Coding (social sciences); Computer programming; Authentic learning","score_opus":0.07439356962728579,"score_gpt":0.37108053859529133,"score_spread":0.29668696896800556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416633744","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009943986,0.00039003557,0.1515945,0.005521207,0.0005485859,0.0016103854,0.000013190597,0.00044642997,0.83888125],"genre_scores_gemma":[0.28205833,0.003786452,0.6797192,0.0054308544,0.00045616165,0.0002143657,0.0005125161,0.000046337173,0.027775785],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998592,0.000039463062,0.00047770384,0.00023356517,0.0003910083,0.00026621294],"domain_scores_gemma":[0.99798715,0.0006043454,0.00033146745,0.00050867617,0.0004893666,0.000078996345],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0014569699,0.00015844604,0.00019019171,0.00097444956,0.0016841844,0.0008816192,0.0012116435,0.0001808717,0.000010826514],"category_scores_gemma":[0.00036430827,0.0001801068,0.000055835048,0.0005061258,0.0017302989,0.0029600835,0.0007608415,0.00033889848,0.000013016834],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029444604,0.000011777681,0.000109255365,0.000028316426,0.000005366187,4.6202043e-8,0.005826318,0.0005906783,5.0739317e-7,0.7388024,0.0002612363,0.25436115],"study_design_scores_gemma":[0.00019959,0.00004168724,0.00005025315,0.00030676217,0.00000895299,0.0000020494313,0.003348874,0.07903337,0.000002167141,0.0055950065,0.91117465,0.00023661897],"about_ca_topic_score_codex":0.00010378349,"about_ca_topic_score_gemma":0.000036816607,"teacher_disagreement_score":0.9109134,"about_ca_system_score_codex":0.00034892448,"about_ca_system_score_gemma":0.0010473998,"threshold_uncertainty_score":0.9996155},"labels":[],"label_agreement":null},{"id":"W4416773353","doi":"10.1007/978-3-032-11733-5_16","title":"Identification of Social Media Users that Perpetuate Xenophobic Attitudes and Hate Speech Narratives in South Africa","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Narrative; Social media; Politics; Identification (biology); Hatred; Focus (optics); Racism","score_opus":0.03433457820265787,"score_gpt":0.2740530658754147,"score_spread":0.23971848767275686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416773353","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049382087,0.0046281675,0.6127919,0.0053430954,0.002974339,0.0038783166,0.0001856741,0.00062473444,0.32019168],"genre_scores_gemma":[0.9717327,0.0012574086,0.026063118,0.00009335073,0.000016801045,0.000025129953,0.00002411064,0.000006226749,0.0007811667],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99834526,0.00005614657,0.00069872534,0.00029954012,0.0004047737,0.00019557426],"domain_scores_gemma":[0.9981296,0.00017527978,0.00045504753,0.0009168599,0.00026897996,0.000054199245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011912185,0.00019290854,0.00027756643,0.0014009401,0.0003795381,0.00044552982,0.0016744591,0.00013320253,0.0000031775703],"category_scores_gemma":[0.000053655822,0.00019962966,0.000037647595,0.0006412008,0.0008250588,0.003749807,0.0012257976,0.0003429158,0.000009080487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012692981,0.00004635182,0.00031092117,0.00019890114,0.000018293069,0.000001094003,0.15490122,0.000080618825,0.00019460672,0.5546969,0.00009159668,0.28944677],"study_design_scores_gemma":[0.004592122,0.0003975282,0.1266498,0.0038618469,0.00007327533,0.00008560814,0.007070205,0.67068803,0.0034507564,0.09518168,0.08411218,0.0038369785],"about_ca_topic_score_codex":0.0000058719093,"about_ca_topic_score_gemma":0.000031390427,"teacher_disagreement_score":0.9223506,"about_ca_system_score_codex":0.000099344456,"about_ca_system_score_gemma":0.00019741397,"threshold_uncertainty_score":0.8140662},"labels":[],"label_agreement":null},{"id":"W4416773420","doi":"10.1007/978-3-032-11733-5_27","title":"Exploring Postgraduate Students’ Use and Perceptions of Generative AI as a Research Support Tool: A South African Case","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Perception; Higher education; Generative grammar; Quarter (Canadian coin); Cognition; SPARK (programming language); Balance (ability)","score_opus":0.5845891398578039,"score_gpt":0.5189589951397475,"score_spread":0.0656301447180564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416773420","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89874315,0.00033428104,0.011837095,0.011681355,0.00057872356,0.0033522143,0.00012749818,0.00008691131,0.07325879],"genre_scores_gemma":[0.9851319,0.003969701,0.008352349,0.0007425006,0.00003552907,0.00007955429,0.00006396867,0.0000059136764,0.001618588],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984202,0.00005791596,0.0006911466,0.00019451707,0.00045420564,0.00018204893],"domain_scores_gemma":[0.9968745,0.00037558886,0.00014984698,0.00091462274,0.0015759423,0.00010946591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014956422,0.00012194824,0.0002240518,0.0013829964,0.00058942614,0.00025859743,0.00038370525,0.00007654834,0.000015370228],"category_scores_gemma":[0.00030849755,0.00011869995,0.000029972076,0.00047825326,0.0011944774,0.002685581,0.00075146765,0.0005467279,0.000016897111],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007075413,0.0001455837,0.010893054,0.00034949885,0.000039542138,0.000015017684,0.20557809,0.000031774838,0.00002397822,0.20811518,0.00064418797,0.57409334],"study_design_scores_gemma":[0.0025440645,0.008148103,0.22059937,0.015603202,0.00069495,0.006530807,0.21372797,0.20397033,0.0014684725,0.056400463,0.26598126,0.0043310123],"about_ca_topic_score_codex":0.0005519004,"about_ca_topic_score_gemma":0.0000878939,"teacher_disagreement_score":0.56976235,"about_ca_system_score_codex":0.00016589153,"about_ca_system_score_gemma":0.00083288556,"threshold_uncertainty_score":0.48404434},"labels":[],"label_agreement":null},{"id":"W4416840971","doi":"10.1007/978-3-032-12229-2_18","title":"An ENA-Informed Approach to Integrating Diverse Expert Knowledge in Cognitive Work Analysis","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Toronto","funders":"","keywords":"Workload; Expert system; Situation awareness; Table (database); Cognition; Interpretation (philosophy); Situational ethics; Intelligence analysis; Situation analysis; Subject-matter expert","score_opus":0.09323968762220966,"score_gpt":0.4323475293224361,"score_spread":0.33910784170022645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416840971","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029199338,0.000103291444,0.107311346,0.00018822278,0.00034025472,0.0005497425,0.00002388825,0.00006871155,0.8911225],"genre_scores_gemma":[0.89163065,0.00071523886,0.062083233,0.005046671,0.000110967136,0.00062559464,0.0012319298,0.000022545377,0.03853317],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981344,0.000098106946,0.0010024494,0.0003059254,0.00023946376,0.0002197035],"domain_scores_gemma":[0.99739355,0.00049463887,0.00030445986,0.0011881855,0.00049559784,0.00012357008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010414076,0.00023068115,0.00041535273,0.004019214,0.00037284306,0.00033118873,0.0013045822,0.00016559973,0.00023874748],"category_scores_gemma":[0.00009739405,0.0002251176,0.000091599926,0.0017616333,0.00041408255,0.002568419,0.0006502586,0.0005289901,0.00015907588],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059907674,0.00018990411,0.0007164571,0.000022445485,0.000118501994,3.3032458e-7,0.13550207,0.0004247354,3.726867e-7,0.36459565,0.0029292267,0.4954404],"study_design_scores_gemma":[0.002689642,0.00018227978,0.065288424,0.0016854566,0.00017092806,0.000012375668,0.0277724,0.47444868,0.000003487886,0.0007312546,0.42545626,0.0015588076],"about_ca_topic_score_codex":0.000070260634,"about_ca_topic_score_gemma":0.00022352357,"teacher_disagreement_score":0.89133865,"about_ca_system_score_codex":0.00028025958,"about_ca_system_score_gemma":0.00025568574,"threshold_uncertainty_score":0.91800296},"labels":[],"label_agreement":null},{"id":"W54847556","doi":"10.1007/978-3-642-32129-0_43","title":"Financial Option Pricing on APU","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Scalability; Valuation of options; Vectorization (mathematics); Computational finance; Computation; Domain (mathematical analysis); Finance; Supercomputer; Scope (computer science); Parallel computing; Algorithm; Operating system; Business; Programming language","score_opus":0.055586516907070664,"score_gpt":0.25850858889444805,"score_spread":0.20292207198737738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W54847556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006519123,0.0010624531,0.6590377,0.0005363875,0.00021899871,0.00032136147,0.000066238725,0.000034694716,0.33865696],"genre_scores_gemma":[0.8458709,0.011437103,0.13200283,0.0054788394,0.0007091469,0.00034636815,0.00040074118,0.000061623985,0.0036924335],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988396,0.0000016361282,0.0006781375,0.00020547572,0.00007860358,0.00019650381],"domain_scores_gemma":[0.9984207,0.00007344275,0.00044761907,0.0008916896,0.0001079375,0.00005857145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006290473,0.00015203997,0.0002360582,0.00074255135,0.00039136055,0.00015536627,0.0008436032,0.00013030512,0.00001692864],"category_scores_gemma":[0.000073690644,0.00017861385,0.00003814069,0.0002756898,0.0003832875,0.0019340725,0.00045355954,0.00031496226,0.0005496594],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015463253,0.0000130345525,0.00002897141,0.000012313322,0.0000011031462,2.014245e-8,0.00038590733,0.000033176188,1.9730197e-7,0.93563527,0.000042289277,0.06384614],"study_design_scores_gemma":[0.00023587147,0.000054176133,0.0060420283,0.00016093887,0.0000032510027,0.0000053814465,0.0000073286606,0.026360588,0.0000019406195,0.57255626,0.39420742,0.0003648198],"about_ca_topic_score_codex":0.000015572234,"about_ca_topic_score_gemma":0.0000034107945,"teacher_disagreement_score":0.8458057,"about_ca_system_score_codex":0.0001553542,"about_ca_system_score_gemma":0.00008054589,"threshold_uncertainty_score":0.72836614},"labels":[],"label_agreement":null},{"id":"W55195068","doi":"10.1007/978-3-642-15810-0","title":"Trends in Intelligent Robotics","year":2010,"lang":"en","type":"book","venue":"Communications in computer and information science","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Robotics; Robot; Artificial intelligence; Volume (thermodynamics); Computer science; Physics","score_opus":0.029755364912407593,"score_gpt":0.2781855377589628,"score_spread":0.24843017284655522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W55195068","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022269516,0.00089112524,0.13656817,0.000292493,0.0017282863,0.00036730064,0.000019502444,0.00027912937,0.8596313],"genre_scores_gemma":[0.6456352,0.020527273,0.31317616,0.0009797871,0.0003708061,0.00016185326,0.0012919188,0.000121208854,0.0177358],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990289,0.00001101293,0.0005376707,0.00008583546,0.00017817323,0.00015841593],"domain_scores_gemma":[0.99884534,0.00005716027,0.00007434176,0.0008957191,0.00007772524,0.00004973465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049513404,0.00012874293,0.00017403072,0.0013930096,0.000088144596,0.00023513027,0.0010348976,0.00013967084,0.0000054774814],"category_scores_gemma":[0.000008360614,0.00013225607,0.00002128625,0.00062828657,0.00026345783,0.0013361224,0.0003633938,0.00054099725,0.00003145783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7100815e-7,0.000017956632,0.00009492292,0.00009078864,0.000005126939,4.462425e-7,0.002866044,0.4271889,0.000009260481,0.046975873,0.0031366518,0.51961356],"study_design_scores_gemma":[0.00006923113,0.000006323532,0.0007712596,0.00013008139,0.0000013232526,0.0000053566673,0.0000120498,0.90817696,0.0000045944435,0.0003433679,0.09033838,0.00014108045],"about_ca_topic_score_codex":0.000005855681,"about_ca_topic_score_gemma":0.00004047202,"teacher_disagreement_score":0.8418955,"about_ca_system_score_codex":0.00016034149,"about_ca_system_score_gemma":0.000085605076,"threshold_uncertainty_score":0.53932464},"labels":[],"label_agreement":null},{"id":"W58067616","doi":"10.1007/978-3-642-35267-6_13","title":"Regression Testing of Object-Oriented Software: A Technique Based on Use Cases and Associated Tool","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Regression testing; Computer science; Software; Information retrieval; Data mining; Software engineering; Programming language; Software development; Software construction","score_opus":0.07075414036268389,"score_gpt":0.30479052641519233,"score_spread":0.23403638605250843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W58067616","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006628236,0.00023626286,0.991084,0.00015713667,0.00014208397,0.00074775727,0.00002999126,0.0019534195,0.0049865306],"genre_scores_gemma":[0.19756155,0.00017602378,0.80170625,0.00039859634,0.0000093031185,0.000043598935,0.000028573608,0.000009730142,0.000066398636],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983953,0.00006237098,0.00062348164,0.0002557231,0.00044383528,0.00021927021],"domain_scores_gemma":[0.9930639,0.0039278036,0.0006022664,0.001726502,0.00059926056,0.0000802216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015817754,0.0002314728,0.00027979733,0.0010401718,0.00039199283,0.00028724887,0.0013282077,0.00016519964,0.0000010384949],"category_scores_gemma":[0.003527172,0.0002113917,0.00003235163,0.00063811685,0.00064359646,0.0035544108,0.0014839816,0.00039875388,0.0000020522275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000094162815,0.000111876376,0.013178564,0.00011037507,0.000007644113,0.0000022267632,0.0010774953,0.000107053056,0.000022031718,0.084834024,0.00072653464,0.89981276],"study_design_scores_gemma":[0.00087272277,0.0008376012,0.040697325,0.008559584,0.00003204221,0.00019524306,0.000005224579,0.9074894,0.00043305193,0.019994687,0.01943944,0.0014436517],"about_ca_topic_score_codex":0.000042166932,"about_ca_topic_score_gemma":0.0000017104122,"teacher_disagreement_score":0.90738237,"about_ca_system_score_codex":0.000121934245,"about_ca_system_score_gemma":0.0002480789,"threshold_uncertainty_score":0.8620303},"labels":[],"label_agreement":null},{"id":"W602747969","doi":"10.1007/978-3-662-47386-3_6","title":"Interrogating Interactive and Responsive Architecture: The Quest of a Technological Solution Looking for an Architectural Problem","year":2015,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Architecture and Computational Design","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Architecture; Context (archaeology); Computer science; Architectural engineering; Engineering; History; Art; Visual arts","score_opus":0.04154967384901452,"score_gpt":0.2963814282483316,"score_spread":0.25483175439931705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W602747969","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021259678,0.0006762309,0.96372646,0.00059624354,0.00008159729,0.0010258479,0.00003429019,0.00012958131,0.031603802],"genre_scores_gemma":[0.88459533,0.00008292541,0.11505974,0.00009493808,0.000021162003,0.000057057707,0.000045526685,0.000009874138,0.00003345561],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912137,0.00003654042,0.000403026,0.00012962766,0.00018151212,0.00012793268],"domain_scores_gemma":[0.998606,0.0004980927,0.00015931812,0.0004381241,0.00025543783,0.000043016273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008207298,0.00015082797,0.00017159905,0.00047858796,0.00021326396,0.000096743,0.0006796591,0.00008117024,6.731936e-7],"category_scores_gemma":[0.00007478507,0.000114793766,0.000026004675,0.00014293568,0.0010397544,0.0008107834,0.00047926218,0.0004180009,7.9341396e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029276947,0.000006622799,0.0000042220086,0.000065084714,0.000015094794,8.5946404e-8,0.01054262,0.031823523,0.00006220795,0.15374672,0.000031743468,0.8036728],"study_design_scores_gemma":[0.00026316373,0.0002277054,0.00022242093,0.0003789134,0.000013265968,0.000099275094,0.00024069866,0.87439424,0.000055270888,0.113134354,0.010731542,0.0002391363],"about_ca_topic_score_codex":0.0000038365915,"about_ca_topic_score_gemma":0.000034632776,"teacher_disagreement_score":0.88246936,"about_ca_system_score_codex":0.00007194748,"about_ca_system_score_gemma":0.00007887755,"threshold_uncertainty_score":0.4681154},"labels":[],"label_agreement":null},{"id":"W620062935","doi":"10.1007/978-3-642-54525-2_43","title":"Preserving Database Privacy in Cloud Computing","year":2014,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; École de Technologie Supérieure; Concordia University","funders":"","keywords":"Cloud computing; Outsourcing; Computer science; Computer security; The Internet; Service provider; Service (business); Utility computing; Cloud computing security; Database; World Wide Web; Internet privacy; Business; Operating system","score_opus":0.06103164693779986,"score_gpt":0.3135499349705244,"score_spread":0.2525182880327246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W620062935","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013111466,0.00039502163,0.9013705,0.007305631,0.00048389536,0.0005011545,0.000020486468,0.0003685628,0.08942358],"genre_scores_gemma":[0.046709634,0.002269922,0.94939584,0.0011269151,0.000064269734,0.000021750177,0.00013355947,0.000017685574,0.00026040475],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99714494,0.000074951546,0.0010978244,0.0005831397,0.0006383574,0.00046081038],"domain_scores_gemma":[0.9795101,0.0006280081,0.0005280738,0.018956847,0.00027107223,0.00010585108],"candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0030922391,0.00032181226,0.00038713042,0.0018813153,0.00044109317,0.00093889463,0.061208177,0.00020969262,0.0000063806515],"category_scores_gemma":[0.0034318143,0.0003452276,0.0000409576,0.00093674695,0.001016974,0.008916096,0.23227929,0.0010535799,0.00006246047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021868145,0.00002424118,0.000304709,0.00010203619,0.000005556144,0.0000019837971,0.0010060997,0.00025903928,0.0000054605425,0.66516685,0.010203164,0.32291865],"study_design_scores_gemma":[0.0002720593,0.000024904433,0.00065632164,0.0005626411,0.0000020340747,0.000019842788,0.000008909833,0.8387942,0.000011073353,0.06274812,0.096543096,0.00035684524],"about_ca_topic_score_codex":0.000044462846,"about_ca_topic_score_gemma":0.0000245075,"teacher_disagreement_score":0.83853513,"about_ca_system_score_codex":0.00027318727,"about_ca_system_score_gemma":0.00029334993,"threshold_uncertainty_score":0.9999},"labels":[],"label_agreement":null},{"id":"W64050937","doi":"10.1007/978-3-642-30439-2_5","title":"Gained Experience by Making Intervention to Improve Software Process in Very Small Organizations","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Intervention (counseling); Process (computing); Process management; Software; Psychological intervention; Computer science; Software engineering; Knowledge management; Engineering management; Business; Engineering; Medicine; Operating system; Nursing","score_opus":0.026742593397098145,"score_gpt":0.30996389846166117,"score_spread":0.283221305064563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W64050937","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040715563,0.0004016441,0.99457854,0.00034963587,0.0002675563,0.00043684934,0.000009853386,0.00024479095,0.0033039479],"genre_scores_gemma":[0.30665898,0.0010148634,0.69058543,0.0010582025,0.000043078413,0.00019591683,0.000069939255,0.000024592187,0.00034901348],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850947,0.000026728785,0.00062218943,0.00028649173,0.0002900377,0.00026510126],"domain_scores_gemma":[0.99760526,0.00022648467,0.0002867596,0.0014049405,0.0003791126,0.00009743169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008900623,0.00021019272,0.0001983611,0.00092012895,0.00023856222,0.0005880442,0.0029311683,0.000121504374,0.000008490319],"category_scores_gemma":[0.00028857574,0.00022901494,0.000025963187,0.0009841493,0.00017829335,0.007640597,0.0019378427,0.000382986,0.000022453933],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006646669,0.000096461175,0.00116527,0.00016474552,0.000006662136,8.298978e-7,0.023121178,0.0012384513,0.00003111435,0.13852271,0.00033006075,0.8353159],"study_design_scores_gemma":[0.0014804578,0.00048765063,0.008552655,0.003965453,0.000028446415,0.000112265145,0.00042730384,0.57878464,0.0007786742,0.01666037,0.38537422,0.0033478264],"about_ca_topic_score_codex":0.000020529995,"about_ca_topic_score_gemma":0.000011147843,"teacher_disagreement_score":0.831968,"about_ca_system_score_codex":0.00018787997,"about_ca_system_score_gemma":0.00013048436,"threshold_uncertainty_score":0.9338958},"labels":[],"label_agreement":null},{"id":"W68234713","doi":"10.1007/978-3-642-39473-7_35","title":"Insights from Eye Movement into Dynamic Decision-Making Research and Usability Testing","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Eye movement; Usability; Eye tracking; Computer science; Cognition; Dynamic decision-making; Process (computing); Movement (music); Event (particle physics); Cognitive load; Information processing; Artificial intelligence; Human–computer interaction; Cognitive psychology; Psychology","score_opus":0.10491027194573736,"score_gpt":0.4469250034481521,"score_spread":0.34201473150241474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W68234713","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034840543,0.00075799535,0.052127168,0.000904938,0.0009931439,0.0011492552,0.000027219177,0.0001429406,0.9090568],"genre_scores_gemma":[0.9314768,0.00027945382,0.06601205,0.00076189096,0.000037329573,0.00008138239,0.000052803727,0.00001147158,0.0012868238],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979887,0.000094273375,0.0008930378,0.00033707736,0.0004964668,0.0001904315],"domain_scores_gemma":[0.9951412,0.0019693065,0.00029935702,0.0016151781,0.00087639707,0.000098549644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010251414,0.0001773114,0.00021954934,0.0010681018,0.00094491016,0.0005483114,0.001134418,0.00015445196,0.0004165422],"category_scores_gemma":[0.00025149088,0.00017035672,0.000024275336,0.0003568901,0.0013729152,0.0027677002,0.0015435976,0.00071143854,0.00047771243],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010454975,0.000039179064,0.00031773778,0.000015770971,0.000010717799,2.830418e-7,0.010861048,0.000042609066,0.000008377047,0.32343677,0.00033843447,0.6649186],"study_design_scores_gemma":[0.00055072526,0.00017260456,0.13943914,0.001012938,0.000007184154,0.000006039946,0.0010194158,0.4127616,0.0000014428241,0.34827983,0.096249945,0.0004991406],"about_ca_topic_score_codex":0.00017166778,"about_ca_topic_score_gemma":0.000106609994,"teacher_disagreement_score":0.90777,"about_ca_system_score_codex":0.00030142313,"about_ca_system_score_gemma":0.00012033583,"threshold_uncertainty_score":0.72675806},"labels":[],"label_agreement":null},{"id":"W7083427451","doi":"10.1007/978-3-031-91141-5_9","title":"Mapping the Threat: Using a Geospatial Lens on Malakand Division, Pakistan, to Gain Early Insights into Antimicrobial Resistance (AMR)","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Eastern European Communism and Reforms","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Rural Health Research Society; University of Saskatchewan; University of Calgary","funders":"","keywords":"Foothills; Geospatial analysis; Amoxicillin; Population; Geographic information system; Functional illiteracy; Psychological intervention; Spatial analysis; Spatial epidemiology","score_opus":0.050459773326999344,"score_gpt":0.31499318782321495,"score_spread":0.2645334144962156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7083427451","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008558516,0.00064232026,0.06956348,0.0057354453,0.00084573374,0.0014340638,0.00003235046,0.00010898433,0.9130791],"genre_scores_gemma":[0.9341087,0.0071858233,0.027029514,0.00681274,0.00024366743,0.000026122669,0.00006737304,0.000031656473,0.02449444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998144,0.00014805108,0.0006474597,0.00024291888,0.0005369756,0.0002806113],"domain_scores_gemma":[0.99734056,0.00027365773,0.0002892348,0.0016176283,0.00038408686,0.000094816525],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015064942,0.00021968383,0.00023334679,0.0007821591,0.0032887738,0.0007812114,0.0028736475,0.00012170169,0.00000574054],"category_scores_gemma":[0.00007100812,0.00016286572,0.00005591981,0.0006411576,0.0015596136,0.0022667039,0.0019750234,0.0005249611,0.00004159048],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025089272,0.000037399153,0.00023141735,0.00007429344,0.000016907845,0.0000013457219,0.17219982,0.0005874095,0.000014543061,0.7236951,0.00089793076,0.102218755],"study_design_scores_gemma":[0.0004412791,0.000060152757,0.0043009324,0.0026757543,0.000012048427,0.0000016592907,0.001467617,0.009446455,0.000009683608,0.0072223865,0.9737439,0.00061812636],"about_ca_topic_score_codex":0.00037796868,"about_ca_topic_score_gemma":0.0018000803,"teacher_disagreement_score":0.972846,"about_ca_system_score_codex":0.0002604283,"about_ca_system_score_gemma":0.00043314393,"threshold_uncertainty_score":0.9980088},"labels":[],"label_agreement":null},{"id":"W7083467577","doi":"10.1007/978-3-031-91141-5_26","title":"A Novel Spatial Unit to Improve Representation in Crime Mapping: The Toronto, Canada Example","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Religious Education and Schools","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Crime analysis; Transparency (behavior); Spatial analysis; Unit (ring theory); Representation (politics); Visualization; Population; Spatial planning","score_opus":0.09130690609608247,"score_gpt":0.3534624992635602,"score_spread":0.2621555931674777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7083467577","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017318984,0.00021791016,0.020868547,0.007055601,0.0007547592,0.0009610104,0.000020541775,0.000024347633,0.9699241],"genre_scores_gemma":[0.76321834,0.011865508,0.051090486,0.027603291,0.0006598516,0.0006768547,0.00040740453,0.0000376202,0.14444065],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99854445,0.000060314684,0.000536175,0.00018694054,0.00046672096,0.00020538931],"domain_scores_gemma":[0.9979269,0.00036681848,0.00018887673,0.0010228418,0.00039249004,0.00010207086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013368253,0.000118266704,0.00015078754,0.00033339614,0.0007803636,0.00041933174,0.0016437742,0.0000787073,0.000031033553],"category_scores_gemma":[0.00025407193,0.00010956335,0.000021820613,0.00047173756,0.0004206844,0.0009823636,0.0005756337,0.00026257327,0.0000088300285],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000039730576,0.00001171668,0.00034103452,0.0000124505805,0.0000047439353,9.750518e-8,0.030335292,0.00012718882,0.000004310722,0.72443146,0.018299365,0.22642839],"study_design_scores_gemma":[0.00022149111,0.000012422881,0.017233364,0.00015970392,0.0000039625934,9.958454e-7,0.0025909038,0.00795594,0.0000027297363,0.0040380196,0.9675484,0.00023210411],"about_ca_topic_score_codex":0.71102375,"about_ca_topic_score_gemma":0.7375813,"teacher_disagreement_score":0.94924897,"about_ca_system_score_codex":0.0007412963,"about_ca_system_score_gemma":0.0037510248,"threshold_uncertainty_score":0.6654157},"labels":[],"label_agreement":null},{"id":"W7106672325","doi":"10.1007/978-981-95-4721-0_12","title":"On Online Self-Organizing Linear Search","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Online algorithm; Bounded function; Quality (philosophy); Online search","score_opus":0.04907550252332892,"score_gpt":0.32425391086749494,"score_spread":0.275178408344166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106672325","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000016957281,0.00013701916,0.6359824,0.0033382168,0.00026603087,0.0005019214,0.000021798227,0.00025873617,0.35947695],"genre_scores_gemma":[0.0056645796,0.0066467565,0.97335607,0.00588159,0.00005117969,0.00001869486,0.00018362408,0.000014889108,0.008182605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823564,0.00004547923,0.00058520975,0.0003073791,0.0005701016,0.00025616548],"domain_scores_gemma":[0.99680823,0.00032358797,0.00015413134,0.002112925,0.00048202538,0.000119100434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010511222,0.00019916399,0.00021342449,0.0015472737,0.00055413146,0.00061032467,0.0038471096,0.00012440802,0.000011888987],"category_scores_gemma":[0.00006142976,0.00019745587,0.00003745497,0.00082689815,0.00039294263,0.0039367676,0.0032731819,0.00066420244,0.000078199635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.319555e-7,0.000031498777,0.0000049158834,0.000025225701,0.0000042130227,2.6742347e-7,0.0010887819,0.0016981834,5.2368745e-7,0.887059,0.00043381212,0.10965269],"study_design_scores_gemma":[0.00022815117,0.00006007985,0.00009915217,0.00022468995,0.0000020301638,0.000005025864,0.000010051059,0.8968538,0.0000056426215,0.0045724316,0.09773357,0.00020535804],"about_ca_topic_score_codex":0.0000068757417,"about_ca_topic_score_gemma":0.000004435575,"teacher_disagreement_score":0.8951556,"about_ca_system_score_codex":0.00018044762,"about_ca_system_score_gemma":0.0005781797,"threshold_uncertainty_score":0.80520165},"labels":[],"label_agreement":null},{"id":"W7115571114","doi":"10.1007/978-3-032-14583-3_9","title":"VedicViz: Towards Visualizing Vedic Principles in Mental Arithmetic","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visualization; Competence (human resources); Set (abstract data type); Multiplication (music); Mental arithmetic; Mental model; Mental image","score_opus":0.08723794328427674,"score_gpt":0.3681215102443886,"score_spread":0.28088356696011185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115571114","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008962673,0.00032829956,0.016407978,0.001011409,0.00022032906,0.0007858404,0.00002693298,0.00007305627,0.9802499],"genre_scores_gemma":[0.22984593,0.014922584,0.7244948,0.00493478,0.00015417679,0.0002976531,0.0004177659,0.00007098494,0.024861304],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983102,0.000023422104,0.0008256649,0.0001953234,0.00043850913,0.00020687365],"domain_scores_gemma":[0.99836755,0.0005068688,0.00021125669,0.0006652197,0.00017830227,0.00007083234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001160461,0.00020432757,0.00031491468,0.0009680868,0.00022826652,0.00019795109,0.0009980387,0.0001045349,0.000034874884],"category_scores_gemma":[0.00032522102,0.00019400602,0.000040783438,0.00033583617,0.0006404821,0.0015143323,0.0018962448,0.00037386167,0.000033758482],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000030177944,0.00005078262,0.000044516004,0.00013926208,0.000006797625,7.776883e-7,0.0024851572,0.0000011808818,0.0000010649313,0.8278135,0.00029445405,0.16915947],"study_design_scores_gemma":[0.0015525856,0.00011937467,0.0044759572,0.006573481,0.000034677087,0.00004323511,0.00047468996,0.07988304,0.000089058754,0.7174592,0.18821786,0.0010768035],"about_ca_topic_score_codex":0.000009411046,"about_ca_topic_score_gemma":0.000027620239,"teacher_disagreement_score":0.9553886,"about_ca_system_score_codex":0.00026169253,"about_ca_system_score_gemma":0.00030173967,"threshold_uncertainty_score":0.7911336},"labels":[],"label_agreement":null},{"id":"W74666794","doi":"10.1007/978-3-642-22185-9_31","title":"User Centric Homogeneity-Based Clustering Approach for Intelligence Computation","year":2011,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cluster analysis; Homogeneity (statistics); Computer science; Computation; Data mining; Hierarchical clustering; Software; Information retrieval; Artificial intelligence; Machine learning; Algorithm","score_opus":0.0925614050617813,"score_gpt":0.3398276076177767,"score_spread":0.2472662025559954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W74666794","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000029462603,0.00019517756,0.9651475,0.0001671038,0.00020011622,0.00086365273,0.00001635219,0.00012784389,0.03327934],"genre_scores_gemma":[0.008624857,0.00053416874,0.989777,0.00034280604,0.00003039136,0.00010836754,0.000090817135,0.00001628665,0.0004752769],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977035,0.000041709376,0.00078600313,0.0004951518,0.0005535593,0.00042010625],"domain_scores_gemma":[0.9963941,0.00034443915,0.00038107732,0.001955191,0.0007658927,0.00015930804],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013353452,0.0002942867,0.00030437208,0.0015156331,0.0006279026,0.0006390794,0.0044099814,0.0001553399,0.0000028114441],"category_scores_gemma":[0.00006480646,0.00031228628,0.000071677416,0.0006979719,0.0007925227,0.005087262,0.003033511,0.00045520594,0.000020850466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074195023,0.00003681749,0.000011118629,0.00012874675,0.0000066655616,3.3049577e-7,0.0008985738,0.03765314,0.0000021336693,0.1721678,0.00004025831,0.789047],"study_design_scores_gemma":[0.00023395206,0.00007626058,0.00009188455,0.00010305776,0.0000038010207,0.000013492327,0.0000097806615,0.9802963,0.00003777504,0.005945737,0.012856521,0.00033144516],"about_ca_topic_score_codex":0.00001188164,"about_ca_topic_score_gemma":0.000004025743,"teacher_disagreement_score":0.94264317,"about_ca_system_score_codex":0.00028343528,"about_ca_system_score_gemma":0.0003977023,"threshold_uncertainty_score":0.99993294},"labels":[],"label_agreement":null},{"id":"W78060492","doi":"10.1007/978-3-642-30507-8_38","title":"An Efficient Algorithm for Enumerating Minimal PathSets in Communication Networks","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Algorithm","score_opus":0.028162785309590432,"score_gpt":0.2845177376795149,"score_spread":0.25635495236992445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W78060492","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006719558,0.0035808529,0.98852277,0.00027369394,0.00029805268,0.00068719144,0.000011952446,0.00010620992,0.006452098],"genre_scores_gemma":[0.09413075,0.0040634307,0.9004956,0.00074385526,0.00010437367,0.00016043718,0.0001876131,0.000019814814,0.000094124414],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978552,0.00007670047,0.00093257026,0.0003458874,0.0003504143,0.00043923262],"domain_scores_gemma":[0.9956859,0.0005765895,0.0004536085,0.0027695636,0.0003598957,0.00015446126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024498033,0.00027895096,0.00032377135,0.0008143413,0.000646872,0.00073757605,0.0038829343,0.00021370957,0.0000028027334],"category_scores_gemma":[0.00003432923,0.00029290872,0.00005612196,0.00052037317,0.0004993281,0.005148069,0.0017396837,0.00054756313,0.000009743371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000016740996,0.000039625666,0.000055860248,0.00001280818,0.0000024747337,1.14843225e-7,0.0017092685,0.01039823,3.0390427e-7,0.18042415,0.0000557866,0.80729973],"study_design_scores_gemma":[0.00035861714,0.000062688436,0.0011989024,0.0002487508,0.000004163927,0.000010634419,0.000020608308,0.9780306,0.000001350876,0.0015206522,0.018222546,0.00032048053],"about_ca_topic_score_codex":0.000017434879,"about_ca_topic_score_gemma":0.00001415729,"teacher_disagreement_score":0.96763235,"about_ca_system_score_codex":0.00018143826,"about_ca_system_score_gemma":0.00021835012,"threshold_uncertainty_score":0.9999523},"labels":[],"label_agreement":null},{"id":"W79607642","doi":"10.1007/978-3-642-31718-7_20","title":"Assimilation of Information in RDF-Based Knowledge Base","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; RDF; Information retrieval; Relevance (law); RDF Schema; World Wide Web; Subject (documents); Semantic Web; SPARQL","score_opus":0.0582025072886846,"score_gpt":0.3034896741607876,"score_spread":0.245287166872103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W79607642","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027282425,0.00076959527,0.7656767,0.0008955302,0.00044158017,0.0005449583,0.000013617965,0.00009839527,0.23128681],"genre_scores_gemma":[0.7398367,0.0014085302,0.25762847,0.0007912518,0.00003015832,0.000039521365,0.00011463145,0.000007556506,0.00014316035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982591,0.000042778807,0.00094603,0.00014703817,0.0003597325,0.0002452713],"domain_scores_gemma":[0.9970795,0.000333026,0.00051270495,0.0015893084,0.0004094588,0.000075989534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016969698,0.00018548853,0.00027106222,0.0019059423,0.00015905696,0.00024304655,0.002319629,0.00015238073,0.000006955185],"category_scores_gemma":[0.000103287384,0.00018310551,0.000042682612,0.000615677,0.0005656564,0.012618535,0.0011698204,0.0003037597,0.000046243695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031215804,0.000036107504,0.00089464424,0.00008816521,0.000002514006,7.8033686e-8,0.003936305,0.0008495944,0.0000027580347,0.59120846,0.00011513658,0.40286314],"study_design_scores_gemma":[0.00054976356,0.000051435716,0.02575956,0.00036098872,0.000005259452,0.0000056761746,0.00003888696,0.9217715,0.000071775474,0.0050725555,0.04598831,0.00032424682],"about_ca_topic_score_codex":0.000019865476,"about_ca_topic_score_gemma":0.00003019466,"teacher_disagreement_score":0.9209219,"about_ca_system_score_codex":0.00016289801,"about_ca_system_score_gemma":0.00047981032,"threshold_uncertainty_score":0.91481334},"labels":[],"label_agreement":null},{"id":"W79611872","doi":"10.1007/978-3-540-89985-3_7","title":"Optimizing Fixpoint Evaluation of Logic Programs with Uncertainty","year":2008,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Multiset; Computer science; Backtracking; Set (abstract data type); Fixed point; Lattice (music); Context (archaeology); Algorithm; Theoretical computer science; Programming language; Mathematics; Discrete mathematics","score_opus":0.1423135322840594,"score_gpt":0.35092938189508566,"score_spread":0.20861584961102625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W79611872","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015915035,0.00062145735,0.84455925,0.00021147034,0.00017338751,0.00097405043,0.00000419723,0.00009201758,0.153205],"genre_scores_gemma":[0.031856865,0.0015924119,0.96613604,0.0001647095,0.000013427901,0.00006840381,0.000043934124,0.000007232611,0.00011695768],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99738806,0.00010364913,0.00081898394,0.00031046325,0.0011598967,0.00021892088],"domain_scores_gemma":[0.99492913,0.000117399366,0.00074889726,0.002488569,0.0016367212,0.00007926201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034229783,0.00022410929,0.00028735716,0.00087967544,0.0003405332,0.00024424936,0.0030102844,0.0001246719,0.0000043282243],"category_scores_gemma":[0.000087630775,0.0001969059,0.000042070853,0.0006739643,0.001425455,0.006058845,0.0013113332,0.00036406046,0.00001121569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046147056,0.00002709427,0.000020617841,0.00003098618,0.0000071327754,1.5643683e-7,0.003621177,0.008975064,0.0000023955356,0.4565215,0.000027832024,0.5307614],"study_design_scores_gemma":[0.00038839455,0.00016330519,0.0005497811,0.0002922154,0.000012623067,0.000046356792,0.000030374329,0.9813941,0.000030843526,0.0049272957,0.011894957,0.00026976925],"about_ca_topic_score_codex":0.000014686118,"about_ca_topic_score_gemma":0.000007955031,"teacher_disagreement_score":0.972419,"about_ca_system_score_codex":0.00027985344,"about_ca_system_score_gemma":0.00068855355,"threshold_uncertainty_score":0.80295897},"labels":[],"label_agreement":null},{"id":"W87896560","doi":"10.1007/978-3-642-40576-1_18","title":"Slide Attacks against Iterated Hill Ciphers","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Allison University","funders":"","keywords":"Iterated function; Computer science; Cryptanalysis; Cipher; Block cipher; Stream cipher; Boomerang attack; Differential cryptanalysis; Theoretical computer science; Computer security; Cryptography; Mathematics; Encryption","score_opus":0.037023911784221875,"score_gpt":0.3001247951444379,"score_spread":0.26310088336021603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W87896560","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045853903,0.0003730554,0.4368121,0.002324838,0.00053545553,0.00088732684,0.000034285236,0.00021708,0.5583573],"genre_scores_gemma":[0.31275836,0.014198064,0.6531893,0.014185559,0.00015021898,0.00026499585,0.0008370864,0.00005051992,0.0043658568],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979887,0.00004802857,0.00086956617,0.00032607853,0.00046500177,0.00030263275],"domain_scores_gemma":[0.99643594,0.0001868755,0.0003814491,0.0022722345,0.0005690908,0.00015440195],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010989672,0.00025354992,0.00024833195,0.0012328761,0.00064059236,0.0013817707,0.0034074974,0.00012656196,0.00004524918],"category_scores_gemma":[0.000031104002,0.00025328982,0.00006357138,0.00073894626,0.0007365493,0.008938312,0.0022557615,0.0004629217,0.00014745176],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.037783e-7,0.000011664785,0.00003457509,0.000012519999,0.0000058786786,3.0020607e-7,0.0020577332,0.00006631045,0.0000033416266,0.743621,0.0013113826,0.25287482],"study_design_scores_gemma":[0.00041191807,0.00004876531,0.0011943659,0.00015267197,0.0000051061693,0.000015703225,0.00006853145,0.525577,0.0000071657373,0.012768808,0.4592475,0.0005024586],"about_ca_topic_score_codex":0.00002658199,"about_ca_topic_score_gemma":0.00001939414,"teacher_disagreement_score":0.7308522,"about_ca_system_score_codex":0.00013065281,"about_ca_system_score_gemma":0.00025658513,"threshold_uncertainty_score":0.99999195},"labels":[],"label_agreement":null},{"id":"W89327733","doi":"10.1007/978-3-642-16419-4_42","title":"Moderated Regression: Effects of IT Infrastructure Integration and Supply Chain Process Integration on the Relationships between RFID Adoption Attributes and System Deployment Outcomes","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Software deployment; Supply chain; Radio-frequency identification; System deployment; Process (computing); Identification (biology); Process management; Business; Regression analysis; Knowledge management; System integration; Computer science; Marketing; Database; Computer security; Software engineering","score_opus":0.09341589340913548,"score_gpt":0.35267938922582925,"score_spread":0.2592634958166938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W89327733","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78177005,0.0005859554,0.1832732,0.021146953,0.00090196414,0.004154497,0.00020823383,0.00034238075,0.007616754],"genre_scores_gemma":[0.9940947,0.0003501498,0.005058161,0.00018078108,0.000014953982,0.00005005894,0.00007621408,0.000007982952,0.00016695715],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9973827,0.00014935684,0.0011394905,0.00034442314,0.0008294883,0.00015451608],"domain_scores_gemma":[0.9949862,0.0017965195,0.0009260101,0.0013148646,0.00088850164,0.0000879492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003023295,0.0002824318,0.00041440563,0.0012633591,0.0009541346,0.00048734306,0.0011956377,0.00042100245,0.000006026406],"category_scores_gemma":[0.0010704093,0.00017508278,0.000041590047,0.0005704187,0.0012991689,0.002358714,0.00059381657,0.001197714,0.0000075026383],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027599264,0.00003525269,0.05868463,0.00009777911,0.000020680012,3.833687e-7,0.009620731,0.00014721058,0.000117600706,0.68981713,0.0003170046,0.24111399],"study_design_scores_gemma":[0.0010332695,0.00026850277,0.8229909,0.0022735184,0.00007395564,0.000040312912,0.0030754884,0.120969385,0.0010320182,0.04484105,0.0027671398,0.0006344544],"about_ca_topic_score_codex":0.0000067586084,"about_ca_topic_score_gemma":0.000030225889,"teacher_disagreement_score":0.7643063,"about_ca_system_score_codex":0.000093856186,"about_ca_system_score_gemma":0.0001281186,"threshold_uncertainty_score":0.73385286},"labels":[],"label_agreement":null},{"id":"W89938556","doi":"10.1007/978-3-642-29752-6_5","title":"Movement Disorder Assessment and Attenuation Techniques for Removal of Tremor","year":2013,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Essential tremor; Computer science; Coherence (philosophical gambling strategy); Kalman filter; Computer vision; Filter (signal processing); Artificial intelligence; Mathematics; Physical medicine and rehabilitation; Medicine","score_opus":0.044069281384553814,"score_gpt":0.3762758681331901,"score_spread":0.3322065867486363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W89938556","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024305804,0.0002620161,0.87469316,0.001992624,0.000021698992,0.0020516138,0.00003369914,0.00005768029,0.12064448],"genre_scores_gemma":[0.00999711,0.0046004863,0.9827874,0.0006396792,0.000018833336,0.0002863654,0.00016610687,0.000009238038,0.0014948361],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999112,0.0000046399905,0.0004801162,0.00013555157,0.00017751251,0.00009018437],"domain_scores_gemma":[0.998445,0.00008031194,0.0002799186,0.00073843263,0.0004091459,0.000047216123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036068447,0.00011415577,0.0002052792,0.00036445406,0.00015610889,0.00004430666,0.0002645156,0.00007539765,0.000008227789],"category_scores_gemma":[0.000013181551,0.00010452418,0.000028932789,0.0001070005,0.0005058154,0.0009133834,0.0003358919,0.00014371047,0.0000012220592],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000029371456,0.000021318247,0.000039372808,0.00005450282,0.0000024069266,3.011411e-8,0.00013171164,0.000007760195,0.00006279047,0.39212406,0.00014698236,0.60740614],"study_design_scores_gemma":[0.0009465895,0.00046594784,0.0070133912,0.00086666876,0.000057665522,0.000053593536,0.000108131586,0.2523197,0.00034728812,0.06444613,0.6729586,0.00041629045],"about_ca_topic_score_codex":0.000009416627,"about_ca_topic_score_gemma":0.0000022471588,"teacher_disagreement_score":0.6728116,"about_ca_system_score_codex":0.000089784895,"about_ca_system_score_gemma":0.000120011886,"threshold_uncertainty_score":0.42623726},"labels":[],"label_agreement":null}]}