{"meta":{"query_hash":"96f42d4e9914","filters":{"venue":"Intelligent Decision Technologies"},"cohort_total":17,"direct_labels_cover":0,"predictions_cover":17,"exported":17,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/96f42d4e9914","api":"https://metacan.xera.ac/api/v1/cohort?venue=Intelligent+Decision+Technologies"},"results":[{"id":"W1481007432","doi":"10.3233/idt-130164","title":"Towards a formal analysis of dynamic reconfiguration in WS-BPEL","year":2013,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Control reconfiguration; Business Process Execution Language; Computer science; Software engineering; Formal methods; Programming language; Embedded system; Service-oriented architecture; Web service","score_opus":0.010263072284768079,"score_gpt":0.264092010550371,"score_spread":0.25382893826560293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481007432","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051603625,0.00037658564,0.9878258,0.0004718053,0.000089307316,0.000058508762,0.000046037847,0.000395261,0.005576246],"genre_scores_gemma":[0.31631806,0.0016866853,0.6719593,0.0005815754,0.00037538752,0.00035721055,0.0002827306,0.00037263712,0.008066386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971578,0.0007937061,0.00019509773,0.00027843614,0.0012880898,0.00028692145],"domain_scores_gemma":[0.99715257,0.001594589,0.0002227369,0.0003949219,0.00054660987,0.00008856195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003930386,0.0007744661,0.00060915254,0.0014470739,0.0010207872,0.0041550817,0.001986647,0.001292277,0.003044335],"category_scores_gemma":[0.0081479205,0.0007727757,0.0021031038,0.0014497911,0.00444446,0.0040788217,0.0024413373,0.0031555435,0.0008888236],"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":[0.000037391805,0.000086936976,0.00021802347,0.00014806258,0.000032098502,0.0003884984,0.0004778812,0.05949254,0.003652956,0.9151333,0.0010629005,0.019269465],"study_design_scores_gemma":[0.00003230645,0.000024758972,0.0001415649,0.000109111155,0.000036115594,0.0001235875,0.00010564851,0.31219414,0.004058489,0.66790235,0.0152392145,0.00003273912],"about_ca_topic_score_codex":0.0035885284,"about_ca_topic_score_gemma":0.0024130726,"teacher_disagreement_score":0.0041550817,"about_ca_system_score_codex":0.0018005917,"about_ca_system_score_gemma":0.0023720914,"threshold_uncertainty_score":0.020786166},"labels":[],"label_agreement":null},{"id":"W1550915148","doi":"10.3233/idt-2007-11-207","title":"Mobile agents in distributed meeting scheduling: A case study for distributed applications","year":2007,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Schedule; Distributed computing; Scheduling (production processes); Mobile agent; Matching (statistics); Software agent; Artificial intelligence; Engineering; Operating system; Operations management","score_opus":0.0470394693281963,"score_gpt":0.3442716425829301,"score_spread":0.2972321732547338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550915148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49538553,0.0029973695,0.47167736,0.0025506057,0.0001833888,0.00055395183,0.00011060529,0.0004019342,0.026139235],"genre_scores_gemma":[0.79585266,0.0011693026,0.19559002,0.00012998126,0.00010874114,0.00022768106,0.00007471681,0.00004781164,0.006799103],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853086,0.00088977953,0.000056796438,0.00012423834,0.00028269706,0.00011557536],"domain_scores_gemma":[0.99716645,0.0021148166,0.00015891723,0.00014678447,0.00018469458,0.00022832635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015199598,0.00050457084,0.0005265549,0.0003780644,0.0019589327,0.0015579201,0.00139251,0.0025604386,0.001827422],"category_scores_gemma":[0.0032958826,0.00028487542,0.00049799064,0.0010999275,0.0008590377,0.0014065224,0.00088704436,0.0010535347,0.00035000005],"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":[0.0013384884,0.0024225458,0.009124014,0.0014655439,0.00021180893,0.0151012195,0.006193817,0.52781504,0.025481135,0.17568992,0.008685474,0.22647095],"study_design_scores_gemma":[0.00042847943,0.0010496861,0.00263884,0.00011298175,0.00013095631,0.0043037515,0.004943481,0.8350966,0.020002259,0.031145366,0.10006308,0.000084559],"about_ca_topic_score_codex":0.0025367686,"about_ca_topic_score_gemma":0.0043466887,"teacher_disagreement_score":0.0025604386,"about_ca_system_score_codex":0.0006797075,"about_ca_system_score_gemma":0.00066458376,"threshold_uncertainty_score":0.008038402},"labels":[],"label_agreement":null},{"id":"W1565540967","doi":"10.3233/idt-140217","title":"Gini index-based digital image complementing in the study of medical images","year":2014,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Image (mathematics); Pixel; Artificial intelligence; Computer vision; Digital image; Computer science; Digital image analysis; Focus (optics); Index (typography); Transformation (genetics); Feature detection (computer vision); Line (geometry); Binary image; Function (biology); Pattern recognition (psychology); Image processing; Mathematics; Physics","score_opus":0.017549988421166403,"score_gpt":0.3086998902392936,"score_spread":0.2911499018181272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565540967","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07686927,0.0037606147,0.91320103,0.0006240842,0.00015161088,0.000096587806,0.00025700705,0.0003095367,0.0047302693],"genre_scores_gemma":[0.7286442,0.0024107066,0.26547787,0.00011490542,0.0003613486,0.00011083984,0.00044904932,0.00016697386,0.0022641644],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981192,0.00070837606,0.000110861445,0.00026796982,0.0007056039,0.000087964654],"domain_scores_gemma":[0.99578685,0.0026106883,0.00049076584,0.0003500105,0.000594059,0.00016765522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004288035,0.00051743793,0.0013098146,0.005250118,0.00056271476,0.0022477617,0.0008887283,0.00072109536,0.0009656804],"category_scores_gemma":[0.012276189,0.0001984126,0.00069489266,0.0054132915,0.0016135942,0.0021053485,0.0013589504,0.0012023603,0.00020112551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049744826,0.00010589122,0.015889384,0.0005916004,0.0003532331,0.00059003796,0.0005833587,0.1780417,0.018893521,0.27716908,0.0044549806,0.5028297],"study_design_scores_gemma":[0.000010838572,0.00015196156,0.008525548,0.00005707102,0.0000780026,0.00052077195,0.00011654319,0.8787065,0.0059964815,0.09878589,0.0069925417,0.000057819085],"about_ca_topic_score_codex":0.0026022964,"about_ca_topic_score_gemma":0.001643544,"teacher_disagreement_score":0.005250118,"about_ca_system_score_codex":0.0015060517,"about_ca_system_score_gemma":0.00083455694,"threshold_uncertainty_score":0.02267754},"labels":[],"label_agreement":null},{"id":"W1582609278","doi":"10.3233/idt-2011-0116","title":"A new adaptive sensor fusion localization method for passive acoustic arrays","year":2011,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Fusion; Sensor fusion; Acoustic sensor; Acoustics; Computer science; Materials science; Electronic engineering; Engineering; Artificial intelligence; Physics","score_opus":0.05499881298294278,"score_gpt":0.30574284055164286,"score_spread":0.25074402756870007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1582609278","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006684025,0.00009221826,0.99855524,0.000027169684,0.000050189436,0.0000087963435,0.000010804674,0.00023037851,0.00035681349],"genre_scores_gemma":[0.047555298,0.00033861163,0.945444,0.00009403525,0.00014090913,0.0001251386,0.00013878634,0.00009010756,0.006073092],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993932,0.00008108149,0.00002415272,0.00013195424,0.00034213156,0.000027404869],"domain_scores_gemma":[0.99969256,0.00007273757,0.000031988977,0.00003691349,0.00015149936,0.00001445717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004009123,0.0007592895,0.00063768885,0.00069262815,0.00033939074,0.0005464126,0.0010483025,0.00080183294,0.0019047427],"category_scores_gemma":[0.0009550342,0.0003748092,0.0005680927,0.0006322794,0.00039511028,0.001052393,0.0007603709,0.00095712516,0.0012098536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016035685,0.000057019788,0.00025781366,0.00015894698,0.00011171728,0.000082823935,0.00010096975,0.05804139,0.14787084,0.013880344,0.0050906367,0.7741872],"study_design_scores_gemma":[0.000025247575,0.0001413045,0.00039151468,0.000015929612,0.000049412654,0.0002766225,0.000014787565,0.93627214,0.039375328,0.003911919,0.019468319,0.000057379948],"about_ca_topic_score_codex":0.0010166963,"about_ca_topic_score_gemma":0.0014161478,"teacher_disagreement_score":0.0019047427,"about_ca_system_score_codex":0.0003272793,"about_ca_system_score_gemma":0.00044738347,"threshold_uncertainty_score":0.0063720345},"labels":[],"label_agreement":null},{"id":"W1600458433","doi":"10.3233/idt-130182","title":"ITIL-based IT service support process reengineering","year":2014,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Information Technology Governance and Strategy","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Information Technology Infrastructure Library; Financial management for IT services; Incident management; ITIL security management; Process management; IT service management; IT portfolio management; Business process reengineering; Service desk; Capacity management; Service (business); Knowledge management; Computer science; Business; Service design; Service provider; Engineering; Systems engineering; Information technology; Operations management; Information security; Computer security; Project management; Security service","score_opus":0.017739029957136433,"score_gpt":0.24798587087685706,"score_spread":0.2302468409197206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1600458433","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047730524,0.00045036542,0.84186983,0.0039119767,0.00021643685,0.0026475703,0.0008244672,0.0130332215,0.08931559],"genre_scores_gemma":[0.25555986,0.00044328903,0.73035324,0.0004822036,0.000051457424,0.0010561188,0.002144673,0.00080930075,0.009099821],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9712955,0.014073449,0.0028538064,0.0015243432,0.00850794,0.0017449709],"domain_scores_gemma":[0.9694574,0.007719449,0.0027604075,0.008306391,0.010541575,0.0012147819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.035090137,0.0009839466,0.0006221128,0.0074555357,0.002051835,0.011967439,0.002794766,0.0017922933,0.004746925],"category_scores_gemma":[0.040334955,0.0007330138,0.0013804934,0.0043613734,0.0019646438,0.0074918442,0.0045862687,0.0032093602,0.0032061234],"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":[0.000284514,0.0015510985,0.0074792975,0.0006787884,0.00013645223,0.00059175456,0.009671346,0.04673133,0.01210343,0.21278486,0.013729771,0.69425726],"study_design_scores_gemma":[0.0003052817,0.0013134942,0.008915944,0.0019708117,0.0002813048,0.0008974409,0.0062986813,0.40739822,0.06440201,0.10591715,0.40180814,0.00049163325],"about_ca_topic_score_codex":0.00981736,"about_ca_topic_score_gemma":0.00864006,"teacher_disagreement_score":0.035090137,"about_ca_system_score_codex":0.009521568,"about_ca_system_score_gemma":0.011521767,"threshold_uncertainty_score":0.18557656},"labels":[],"label_agreement":null},{"id":"W1943064151","doi":"10.3233/idt-2011-0101","title":"A multi-agent system for course timetabling","year":2011,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Negotiation; Computer science; Intelligent agent; Key (lock); Course (navigation); Partition (number theory); Multi-agent system; Intelligent decision support system; Order (exchange); Autonomous agent; Decision support system; Operations research; Artificial intelligence; Distributed computing; Engineering; Computer security","score_opus":0.3140246158563806,"score_gpt":0.4170870266593164,"score_spread":0.10306241080293582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1943064151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033756137,0.00063402177,0.9499564,0.00061898096,0.0002458563,0.00039101907,0.0001770502,0.002758744,0.011461868],"genre_scores_gemma":[0.4109581,0.00051128987,0.5760834,0.00017518693,0.00010015282,0.000495722,0.00036936707,0.0001045693,0.011202227],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995524,0.00014184962,0.000035847934,0.00009282458,0.00013600315,0.000041008283],"domain_scores_gemma":[0.999508,0.00015104601,0.00005913727,0.00006152124,0.0001320584,0.00008822947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006965127,0.00037012488,0.00048283313,0.00048466542,0.0012074957,0.0011898432,0.0011011809,0.0008639753,0.0048803687],"category_scores_gemma":[0.0013054152,0.00021521498,0.00040543673,0.00048108603,0.00031170575,0.0010070705,0.000743728,0.00080878544,0.001138218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007049543,0.0008174619,0.0038081552,0.0005827191,0.00020534602,0.00080601155,0.00087015383,0.3666344,0.05883128,0.07833408,0.015237597,0.47316784],"study_design_scores_gemma":[0.00012349877,0.00020127682,0.0007009588,0.00003694949,0.0000655493,0.00013714594,0.00007258574,0.93063664,0.010231257,0.0070702303,0.050676025,0.000047955615],"about_ca_topic_score_codex":0.0041216346,"about_ca_topic_score_gemma":0.0048392443,"teacher_disagreement_score":0.0048803687,"about_ca_system_score_codex":0.0007241726,"about_ca_system_score_gemma":0.0015623873,"threshold_uncertainty_score":0.016326487},"labels":[],"label_agreement":null},{"id":"W1956724972","doi":"10.3233/idt-2012-0120","title":"The entire range of Chaotic pattern recognition properties possessed by the Adachi neural network1","year":2011,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Chaotic; Range (aeronautics); Artificial neural network; Computer science; Materials science; Pattern recognition (psychology); Artificial intelligence; Composite material","score_opus":0.07228037437211568,"score_gpt":0.24950118709701632,"score_spread":0.17722081272490064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1956724972","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11319107,0.00870075,0.80939585,0.0030253967,0.00064993365,0.000099705016,0.0005151234,0.0006422331,0.06377988],"genre_scores_gemma":[0.907402,0.004185283,0.081328236,0.0002849384,0.00045435558,0.00010942516,0.0002599528,0.00009075696,0.0058851563],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999624,0.00009186528,0.000026158865,0.000067934976,0.000160224,0.000029656157],"domain_scores_gemma":[0.9983151,0.0009467611,0.00014648118,0.00030439554,0.0002420635,0.000045216017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080915156,0.0004776908,0.00076784095,0.00057263445,0.00076309516,0.0013345547,0.0005464593,0.0008280985,0.002070005],"category_scores_gemma":[0.0047416743,0.00035836696,0.00040019464,0.00077656645,0.0015242144,0.0020360355,0.00075324374,0.0010072178,0.00090656395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057673466,0.00007703612,0.007840802,0.0010015409,0.00012708755,0.0008196599,0.00064761733,0.20381162,0.044833284,0.3095701,0.007779375,0.42291504],"study_design_scores_gemma":[0.000035226025,0.00027455427,0.005269097,0.00013285532,0.000058681355,0.0012114105,0.00011743644,0.6116614,0.0113543095,0.35238624,0.017382216,0.000116569776],"about_ca_topic_score_codex":0.0012528748,"about_ca_topic_score_gemma":0.0010919211,"teacher_disagreement_score":0.002070005,"about_ca_system_score_codex":0.00044749436,"about_ca_system_score_gemma":0.0003763583,"threshold_uncertainty_score":0.0069248676},"labels":[],"label_agreement":null},{"id":"W2105694297","doi":"10.3233/idt-2012-0135","title":"Image retrieval based on high level concept detection and semantic labelling","year":2012,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Image retrieval; Visual Word; Artificial intelligence; Information retrieval; Thesaurus; Pattern recognition (psychology); Classifier (UML); Automatic image annotation; Euclidean distance; Visualization; Support vector machine; Content-based image retrieval; Image (mathematics)","score_opus":0.04045123221835276,"score_gpt":0.2896495118085935,"score_spread":0.24919827959024074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105694297","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024595488,0.00083990383,0.9692248,0.00013974028,0.00006555675,0.00029811656,0.0001656342,0.0019170765,0.0027536],"genre_scores_gemma":[0.1549096,0.0005343212,0.8399639,0.0001504368,0.00008994015,0.0002383878,0.000654881,0.00015166614,0.0033068424],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979546,0.000380883,0.00015424137,0.0004521873,0.00091963797,0.00013845094],"domain_scores_gemma":[0.99819475,0.00057955435,0.00021855303,0.00036133305,0.00058575295,0.00006001171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014884475,0.0006368191,0.0013296144,0.004476558,0.0006790707,0.0020011999,0.0017833352,0.0015303654,0.0026378953],"category_scores_gemma":[0.0040224437,0.00035384588,0.0013476324,0.0022945898,0.00109145,0.0042011407,0.0012846959,0.0009782461,0.0026149298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032252618,0.0003810739,0.00097436184,0.0005854967,0.000112775946,0.00018333085,0.0003519353,0.008573501,0.12006234,0.008424205,0.0045366753,0.85549176],"study_design_scores_gemma":[0.00012592759,0.0010421406,0.008324287,0.00019548013,0.00028139018,0.0019134278,0.00062976114,0.7110312,0.20984733,0.034657072,0.031727184,0.00022480621],"about_ca_topic_score_codex":0.0021693914,"about_ca_topic_score_gemma":0.0022508213,"teacher_disagreement_score":0.004476558,"about_ca_system_score_codex":0.00095691916,"about_ca_system_score_gemma":0.000952077,"threshold_uncertainty_score":0.0088246465},"labels":[],"label_agreement":null},{"id":"W2282249876","doi":"10.3233/idt-140227","title":"Granular fuzzy rule-based architectures: Pursuing analysis and design in the framework of granular computing","year":2015,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Granular computing; Granularity; Probabilistic logic; Computer science; Fuzzy logic; Exploit; Theoretical computer science; Fuzzy set; Granular material; Data mining; Artificial intelligence; Rough set; Engineering; Programming language","score_opus":0.043530571560043224,"score_gpt":0.29356324935612976,"score_spread":0.2500326777960865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2282249876","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011997464,0.00060553703,0.9825638,0.00044268207,0.000048757927,0.00010010633,0.00005569286,0.00024181262,0.003944243],"genre_scores_gemma":[0.42638898,0.0011492997,0.56953806,0.00019887701,0.000076559714,0.00028444178,0.00013361791,0.000053319152,0.0021768492],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99873394,0.0003223211,0.00012896564,0.00019945425,0.0005174358,0.000097899996],"domain_scores_gemma":[0.99837816,0.0006914124,0.0001822039,0.00034727977,0.00030122595,0.0000997354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022521429,0.0004942168,0.00093425554,0.000904218,0.00050351094,0.0033180318,0.0015917153,0.0010999988,0.0020625265],"category_scores_gemma":[0.0051021366,0.000477417,0.0009525216,0.0011034581,0.0017245009,0.0029576062,0.0010192591,0.0014960692,0.0004790426],"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":[0.00012586833,0.00009336308,0.0008567826,0.0003202578,0.000108636166,0.00029285534,0.00037143062,0.41423345,0.0059113097,0.4685235,0.0015811392,0.10758139],"study_design_scores_gemma":[0.0000185343,0.00006733854,0.00016988278,0.000068688154,0.00004651717,0.00008683634,0.000062393716,0.8139919,0.0017863002,0.17877303,0.004904885,0.000023735409],"about_ca_topic_score_codex":0.0020145243,"about_ca_topic_score_gemma":0.0015556478,"teacher_disagreement_score":0.0033180318,"about_ca_system_score_codex":0.0009476276,"about_ca_system_score_gemma":0.0010391308,"threshold_uncertainty_score":0.011910617},"labels":[],"label_agreement":null},{"id":"W2315211922","doi":"10.3233/idt-150246","title":"Measuring the nearness of layered flow graphs: Application to Content Based Image Retrieval","year":2016,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Disjoint sets; Set (abstract data type); Flow (mathematics); Computer science; Perception; Simplicity; Rough set; Image (mathematics); Pattern recognition (psychology); Artificial intelligence; Data mining; Theoretical computer science; Mathematics; Combinatorics","score_opus":0.05888102174665606,"score_gpt":0.2676988700315519,"score_spread":0.20881784828489586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315211922","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3522801,0.0009648876,0.6427499,0.00025339628,0.00005393997,0.00021920736,0.00047922772,0.0011813464,0.0018180633],"genre_scores_gemma":[0.82087046,0.0002915469,0.17794146,0.00003382033,0.00002308166,0.000048353493,0.00044026464,0.000039914863,0.00031110892],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915004,0.00024241525,0.00006600577,0.00012186917,0.00036266082,0.000057031022],"domain_scores_gemma":[0.9970855,0.0016537143,0.00039555834,0.0002640055,0.00048338203,0.0001178404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001782192,0.00050394214,0.0006695317,0.005960707,0.0005067492,0.0011168901,0.00044433973,0.00076943514,0.00054012815],"category_scores_gemma":[0.00807092,0.0001757191,0.000608346,0.0029383432,0.00052072917,0.0014958049,0.0006404174,0.0004457645,0.0001201351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008437973,0.0003916214,0.014013756,0.0003432826,0.00021055358,0.00036947065,0.0005368816,0.40429685,0.033496413,0.016124174,0.0021274711,0.5272457],"study_design_scores_gemma":[0.000020268211,0.00021518693,0.0077586668,0.000021081876,0.000054146894,0.00023415507,0.00018223465,0.9637534,0.011218417,0.01543263,0.0010655934,0.000044298056],"about_ca_topic_score_codex":0.004549859,"about_ca_topic_score_gemma":0.0029828106,"teacher_disagreement_score":0.005960707,"about_ca_system_score_codex":0.00089506956,"about_ca_system_score_gemma":0.00048665437,"threshold_uncertainty_score":0.0094252825},"labels":[],"label_agreement":null},{"id":"W2591663134","doi":"10.3233/idt-170284","title":"Planning for the next software release using adaptive network-based fuzzy inference system","year":2017,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adaptive neuro fuzzy inference system; Inference; Process (computing); Computer science; Software release life cycle; Fuzzy logic; Data mining; Software; Inference engine; Machine learning; Reliability (semiconductor); Fuzzy inference system; Perspective (graphical); Artificial intelligence; Fuzzy control system; Software quality; Software development","score_opus":0.14157031471738002,"score_gpt":0.3592322270332248,"score_spread":0.2176619123158448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2591663134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047942735,0.00030904703,0.9466157,0.00019922771,0.000041474083,0.00013661142,0.00008746201,0.0006492927,0.004018472],"genre_scores_gemma":[0.8696508,0.00029577158,0.12739357,0.00006694182,0.00002555537,0.0002707018,0.00018963024,0.000026090338,0.0020808869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994746,0.00011242248,0.000053781303,0.00015690431,0.00014085067,0.000061585226],"domain_scores_gemma":[0.9991954,0.000490964,0.00011691872,0.00001910354,0.00015327941,0.000024281022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010055447,0.00075033185,0.0007242903,0.0007217818,0.00064365,0.0010414416,0.0009639384,0.0009345916,0.001701286],"category_scores_gemma":[0.0019773515,0.00036023837,0.00065665285,0.00048440055,0.00036764666,0.0007200204,0.0004973021,0.00079106103,0.00019644563],"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":[0.00010529173,0.00005412799,0.000901462,0.00008342338,0.000037067544,0.00012936328,0.00011211977,0.94936746,0.0023224212,0.0013762084,0.00040700487,0.04510415],"study_design_scores_gemma":[0.000006189734,0.000017748835,0.000121883095,0.000006220915,0.000009635675,0.0000074874224,0.000009092022,0.99890316,0.00036246196,0.0004291302,0.00012267233,0.00000423731],"about_ca_topic_score_codex":0.01926824,"about_ca_topic_score_gemma":0.01833879,"teacher_disagreement_score":0.01926824,"about_ca_system_score_codex":0.0011025234,"about_ca_system_score_gemma":0.0012669216,"threshold_uncertainty_score":0.038312197},"labels":[],"label_agreement":null},{"id":"W3110716649","doi":"10.3233/idt-190114","title":"A new approach based on graph matching and evolutionary approach for sport scheduling problem","year":2020,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Crossover; Tournament; Tournament selection; Mathematical optimization; Computer science; Schedule; Genetic algorithm; Scheduling (production processes); Constructive; Job shop scheduling; Operator (biology); Graph; Evolutionary algorithm; Operations research; Heuristic; Artificial intelligence; Theoretical computer science; Machine learning; Mathematics","score_opus":0.1264925375277027,"score_gpt":0.35193642735680675,"score_spread":0.22544388982910404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110716649","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008126924,0.00039203383,0.9854176,0.00025575073,0.00013152708,0.00014449666,0.00007491464,0.00022855816,0.0052281055],"genre_scores_gemma":[0.118343264,0.0009680307,0.8726706,0.00026727334,0.00015376609,0.00036924155,0.00049110496,0.00012938849,0.0066072536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927455,0.00016235361,0.000039876413,0.00017881086,0.00026316752,0.00008128615],"domain_scores_gemma":[0.9997217,0.000091217895,0.000038647453,0.00003515915,0.000083412204,0.000029814237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059808674,0.0009895948,0.0008174774,0.0022765235,0.00073557254,0.0008819658,0.0017534022,0.0011412166,0.0036136364],"category_scores_gemma":[0.0013019844,0.0003838004,0.0014383455,0.0026273122,0.0003812463,0.0013641553,0.0009136538,0.0010419481,0.00050892873],"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":[0.00008920976,0.0003222269,0.0014789227,0.00037034473,0.00014968019,0.00029156465,0.0001236117,0.4672286,0.009585218,0.05955688,0.0094168885,0.45138693],"study_design_scores_gemma":[0.000029238205,0.00011683153,0.00038822734,0.00002547207,0.000051142528,0.00025715257,0.000044702145,0.969415,0.0017037165,0.015313283,0.0126381405,0.000017008902],"about_ca_topic_score_codex":0.0040492504,"about_ca_topic_score_gemma":0.0036647427,"teacher_disagreement_score":0.0040492504,"about_ca_system_score_codex":0.00075917924,"about_ca_system_score_gemma":0.0016574189,"threshold_uncertainty_score":0.012088895},"labels":[],"label_agreement":null},{"id":"W4220881492","doi":"10.3233/idt-200220","title":"Fuzzy expert systems for prediction of ICU admission in patients with COVID-19","year":2022,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Adaptive neuro fuzzy inference system; Fuzzy logic; Computer science; Artificial intelligence; Machine learning; Expert system; Decision tree; Data mining; Task (project management); Naive Bayes classifier; Coronavirus disease 2019 (COVID-19); Fuzzy control system; Engineering; Disease; Medicine; Support vector machine","score_opus":0.05198430275873314,"score_gpt":0.34088875083766224,"score_spread":0.2889044480789291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220881492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51256394,0.0018221642,0.47597688,0.0011571228,0.00020563943,0.00025258816,0.00075582083,0.00089996756,0.0063659064],"genre_scores_gemma":[0.9620662,0.00031924868,0.036451437,0.000057565052,0.00002862203,0.00005708408,0.00021245019,0.000005098724,0.00080221647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997094,0.00009694116,0.000034836405,0.00005322262,0.000077140074,0.000028430502],"domain_scores_gemma":[0.99898225,0.0007103357,0.00007422983,0.000020889936,0.00017820639,0.000034146877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009600373,0.00036983017,0.00048755933,0.00073545193,0.00035335182,0.00063281954,0.00041338446,0.0007697564,0.0014913725],"category_scores_gemma":[0.0038471129,0.00013254683,0.0004311138,0.0003272793,0.0001274613,0.00042176346,0.00024332215,0.0005146798,0.00021109248],"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":[0.00068011065,0.00030481865,0.01968647,0.00021575132,0.000121516714,0.0005357265,0.00030085543,0.8151163,0.005163785,0.0026023004,0.002282907,0.15298945],"study_design_scores_gemma":[0.0000093066,0.000049007253,0.0015353974,0.000014753186,0.000016439373,0.000031748637,0.0000397128,0.99699545,0.0005623405,0.0005406645,0.00019780986,0.0000073044575],"about_ca_topic_score_codex":0.013746665,"about_ca_topic_score_gemma":0.011141366,"teacher_disagreement_score":0.013746665,"about_ca_system_score_codex":0.0006340889,"about_ca_system_score_gemma":0.00073152286,"threshold_uncertainty_score":0.02733332},"labels":[],"label_agreement":null},{"id":"W4324138366","doi":"10.3233/idt-220214","title":"Tolerance-based granular methods: Foundations and applications in natural language processing","year":2023,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Artificial intelligence; Natural language processing; Sentiment analysis; Automatic summarization; Machine translation; Named-entity recognition; Information extraction; Information retrieval; Machine learning; Task (project management)","score_opus":0.033149764929434215,"score_gpt":0.35883289576392546,"score_spread":0.32568313083449124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324138366","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040303078,0.0038937742,0.9870411,0.00082174264,0.00010350929,0.000072149574,0.000089060464,0.00018366253,0.0037647046],"genre_scores_gemma":[0.2364106,0.008244508,0.7514257,0.0004077855,0.0005497764,0.0003569305,0.00023757908,0.00012586698,0.0022413118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997124,0.0008037837,0.00032571843,0.00041350705,0.0011944526,0.00013855382],"domain_scores_gemma":[0.9941314,0.0035570425,0.0007119739,0.00074074423,0.0006941885,0.00016452375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004181932,0.00078934454,0.0014801283,0.0038910247,0.00094996847,0.0049874946,0.0016310208,0.0013403983,0.0016779884],"category_scores_gemma":[0.012052338,0.0006057385,0.0016721046,0.0044376715,0.003397045,0.005312775,0.0025657988,0.003034221,0.00044917155],"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":[0.00006449949,0.000046958932,0.0011389875,0.00061542174,0.00009741853,0.00014913232,0.00044903,0.071676746,0.0017883219,0.7749172,0.0019031833,0.14715317],"study_design_scores_gemma":[0.000014182076,0.000045340592,0.00067689683,0.0002242448,0.000032490352,0.000104873936,0.00019784627,0.2326415,0.0011358538,0.7535153,0.011355946,0.00005543185],"about_ca_topic_score_codex":0.0025359315,"about_ca_topic_score_gemma":0.0012564713,"teacher_disagreement_score":0.0049874946,"about_ca_system_score_codex":0.0020653747,"about_ca_system_score_gemma":0.0011344439,"threshold_uncertainty_score":0.022116482},"labels":[],"label_agreement":null},{"id":"W4386768836","doi":"10.3233/idt-220295","title":"HT-WSO: A hybrid meta-heuristic approach-aided multi-objective constraints for energy efficient routing in WBANs","year":2023,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Routing protocol; Swarm behaviour; Heuristic; Routing (electronic design automation); Network packet; Data transmission; Efficient energy use; Computer network; Distributed computing; Engineering","score_opus":0.04768766210099982,"score_gpt":0.2725254041363565,"score_spread":0.2248377420353567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386768836","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033024326,0.0013438626,0.9575762,0.00030279602,0.00013012021,0.00022957477,0.00017029629,0.00035353444,0.006869306],"genre_scores_gemma":[0.6547522,0.0012743538,0.33675817,0.00031312037,0.00008226729,0.0009783248,0.00048447176,0.00013873626,0.0052183466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953127,0.00016684679,0.000037221806,0.00007279049,0.000116400995,0.00007555988],"domain_scores_gemma":[0.9992823,0.00047774348,0.00007706904,0.000027051818,0.00010319372,0.000032640804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009210768,0.001541118,0.0013410265,0.0012938892,0.00051342545,0.0012416051,0.0015186889,0.0013846073,0.0017646024],"category_scores_gemma":[0.0016300807,0.00070154434,0.0015252038,0.001147928,0.00052600104,0.00082328764,0.0010129812,0.0010833623,0.00020370996],"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":[0.000018080897,0.00002483249,0.00025623458,0.00006116502,0.000046676734,0.000051385217,0.00002157007,0.988734,0.00043389888,0.0018163768,0.0002895234,0.008246264],"study_design_scores_gemma":[0.000007950102,0.000022532175,0.000048876627,0.000009513612,0.000009760131,0.000007570452,0.000011351888,0.9986545,0.0001564998,0.000729305,0.00033877668,0.000003386226],"about_ca_topic_score_codex":0.009410541,"about_ca_topic_score_gemma":0.0072715837,"teacher_disagreement_score":0.009410541,"about_ca_system_score_codex":0.0008114823,"about_ca_system_score_gemma":0.001758874,"threshold_uncertainty_score":0.018711507},"labels":[],"label_agreement":null},{"id":"W4392949175","doi":"10.3233/idt-230629","title":"SExpSMA-based T5: Serial exponential-slime mould algorithm based T5 model for question answer and distractor generation","year":2024,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Context (archaeology); Range (aeronautics); Exponential function; Algorithm; Artificial intelligence; Process (computing); Natural language processing; Machine learning; Arithmetic; Mathematics; Engineering; Programming language","score_opus":0.05118028656545992,"score_gpt":0.31051808802110653,"score_spread":0.2593378014556466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392949175","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033266045,0.00067156483,0.9589318,0.00041967374,0.00015001751,0.0002514466,0.00032035707,0.0036842066,0.0023048492],"genre_scores_gemma":[0.45660612,0.0004528271,0.5297109,0.00057840464,0.00013175116,0.00071758404,0.001579944,0.0003613885,0.009861057],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989586,0.0002501478,0.000094530966,0.0003819788,0.00021149483,0.000103256745],"domain_scores_gemma":[0.998252,0.0008965197,0.000102733226,0.00013570281,0.00052995497,0.00008321073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015424071,0.0010983731,0.00092685095,0.0013195937,0.0008504336,0.0012879138,0.0023854293,0.001897944,0.005572202],"category_scores_gemma":[0.0056475345,0.00048439103,0.0018147894,0.0009802819,0.0006336995,0.0019179262,0.0011557735,0.0021701904,0.002047713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073913514,0.0003304085,0.007472928,0.00028623667,0.0001998719,0.00030012912,0.00046642195,0.32810658,0.01511818,0.013455629,0.009297474,0.62422705],"study_design_scores_gemma":[0.000022205011,0.00009222717,0.0003742532,0.000009680772,0.000022080043,0.00006416201,0.000025128218,0.9907432,0.0033316002,0.0033744907,0.0019282807,0.000012669795],"about_ca_topic_score_codex":0.016265478,"about_ca_topic_score_gemma":0.01765173,"teacher_disagreement_score":0.016265478,"about_ca_system_score_codex":0.0014043722,"about_ca_system_score_gemma":0.0021822688,"threshold_uncertainty_score":0.0323416},"labels":[],"label_agreement":null},{"id":"W4415621754","doi":"10.1177/18724981251381581","title":"Deep neural network-based imaging system for efficient pancreatic tumor identification","year":2025,"lang":"en","type":"article","venue":"Intelligent Decision Technologies","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wycliffe College","funders":"","keywords":"Segmentation; Identification (biology); Pattern recognition (psychology); Artificial neural network; Image segmentation; Deep neural networks; Deep learning; Medical imaging","score_opus":0.027873572552899024,"score_gpt":0.2935930293055754,"score_spread":0.2657194567526764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415621754","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057552993,0.0022668028,0.9242022,0.00074371044,0.0002597326,0.00012473603,0.001049382,0.006371416,0.0074290233],"genre_scores_gemma":[0.71030635,0.0019221491,0.267842,0.0007492351,0.00013781192,0.0002528807,0.002135373,0.00018290941,0.016471254],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988675,0.000014359237,0.000009092482,0.000032285894,0.000036808404,0.000020720552],"domain_scores_gemma":[0.99990356,0.000018719022,0.000012953657,0.000011362662,0.000043391698,0.000009937295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025342757,0.0004336137,0.00046860403,0.0006159877,0.00021546755,0.0006212039,0.0007040744,0.0006900708,0.0036506287],"category_scores_gemma":[0.0005054667,0.00021744428,0.00038954816,0.0005491758,0.00013348313,0.0007028617,0.00065398536,0.00073209376,0.0014753395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004967723,0.00032109776,0.0042976583,0.0002466821,0.000120013276,0.0004139439,0.00007540877,0.08387523,0.053295393,0.0030860137,0.015843237,0.83792853],"study_design_scores_gemma":[0.000015256559,0.00009724615,0.001534155,0.000028211023,0.00003740919,0.0002232128,0.00002097829,0.9737182,0.017443582,0.0022772916,0.0045793676,0.00002497702],"about_ca_topic_score_codex":0.003239971,"about_ca_topic_score_gemma":0.004787282,"teacher_disagreement_score":0.0036506287,"about_ca_system_score_codex":0.00043541344,"about_ca_system_score_gemma":0.0005892891,"threshold_uncertainty_score":0.0122125745},"labels":[],"label_agreement":null}]}