{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":18,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":18,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"b93a9db1670c","filters":{"venue":"IoT"}},"results":[{"id":"W3126471047","doi":"10.3390/iot2010006","title":"Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy","year":2021,"lang":"en","type":"article","venue":"IoT","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":104,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; University of New Brunswick","funders":"","keywords":"Cloud computing; Computer science; Automation; Internet of Things; Fog computing; Big data; Process (computing); Data processing; Distributed computing; Data science; Database; World Wide Web; Data mining; Operating system; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04489601478269747,"gpt":0.2713725817888537,"spread":0.2264765670061562,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005830374,0.00009083172,0.0001399851,0.00007320516,0.00007865415,0.0002195817,0.0002664684,0.00005177459,0.000001860818],"category_scores_gemma":[0.00006576812,0.00009322017,0.0000145961,0.0004378448,0.000008602181,0.0001913218,0.0001297046,0.00009084756,0.00001631694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003489071,"about_ca_system_score_gemma":0.0001382058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007383616,"about_ca_topic_score_gemma":0.0004791286,"domain_scores_codex":[0.9989608,0.0001804274,0.0001957084,0.000331968,0.0001230282,0.0002080594],"domain_scores_gemma":[0.9994238,0.00008687769,0.00006143552,0.0002573167,0.0001050974,0.00006545965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001706083,0.0004292671,0.7071055,0.0005788159,0.00003218603,0.0002702942,0.009955381,0.001126433,0.001084064,0.001499804,0.004425518,0.2734756],"study_design_scores_gemma":[0.0004680146,0.00005684661,0.4154802,0.0001096794,0.00000224828,0.00005651225,0.00005698933,0.5772743,0.00158681,0.0004710172,0.00413121,0.0003062391],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97202,0.00009773851,0.02482655,0.0001393107,0.002246016,0.0001224763,4.427202e-7,0.0001047896,0.0004426312],"genre_scores_gemma":[0.994568,8.203095e-7,0.004802596,0.00007748054,0.0004910315,0.00001156627,0.000005288422,0.000005819832,0.00003740328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5761479,"threshold_uncertainty_score":0.3801408,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3092005458","doi":"10.3390/iot1020014","title":"Sentiment Analysis on Twitter Data of World Cup Soccer Tournament Using Machine Learning","year":2020,"lang":"en","type":"article","venue":"IoT","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Laurentian University","funders":"","keywords":"Artificial intelligence; Computer science; Sentiment analysis; Natural language processing; WordNet; Lexical analysis; Support vector machine; Naive Bayes classifier; Lexicon; Machine learning; Parsing; Stop words; Random forest; Preprocessor","retraction":null,"screen_n_in":null,"score":{"opus":0.1497165917975568,"gpt":0.3427472063976341,"spread":0.1930306146000772,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000300033,0.0001290361,0.0003050643,0.0002937372,0.00009139384,0.0001242771,0.0008571306,0.0000198022,0.0004433012],"category_scores_gemma":[0.00001804107,0.0001113253,0.0001647034,0.001424897,0.00001603606,0.0001354634,0.0006737954,0.0001471636,0.00003870624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003024538,"about_ca_system_score_gemma":0.00001868693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007651096,"about_ca_topic_score_gemma":0.00001031831,"domain_scores_codex":[0.9984462,0.00008942847,0.0003429197,0.0004803714,0.0004531855,0.0001878566],"domain_scores_gemma":[0.998939,0.00004981904,0.0002317076,0.0006448805,0.0000355811,0.00009901725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008249873,0.0006367834,0.6074892,0.00006965504,0.008029321,0.00009319435,0.008202652,0.307777,0.02433783,0.002011534,0.009787636,0.03148266],"study_design_scores_gemma":[0.0002093516,0.00003847906,0.001798479,0.00001785309,0.0002768619,3.439637e-7,0.00004839954,0.9875186,0.003707739,0.00001081209,0.006243801,0.0001292496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4751092,0.0005161462,0.5136535,0.008749796,0.0003378977,0.000182981,0.00001136247,0.000121159,0.001318002],"genre_scores_gemma":[0.9738867,0.00000706645,0.02426129,0.001263931,0.0001197168,7.179114e-7,0.00003212004,0.000008385278,0.0004200631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6797416,"threshold_uncertainty_score":0.4853837,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3185928824","doi":"10.3390/iot2030022","title":"Towards a Hybrid Deep Learning Model for Anomalous Activities Detection in Internet of Things Networks","year":2021,"lang":"en","type":"article","venue":"IoT","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; MQTT; Internet of Things; Botnet; Convolutional neural network; Anomaly detection; Intrusion detection system; Artificial intelligence; Computer network; Machine learning; Data mining; Computer security; The Internet; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.01210501563042712,"gpt":0.2246120079371497,"spread":0.2125069923067225,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002291439,0.00008384989,0.0001448342,0.00008458503,0.00005696632,0.00006417548,0.0001869886,0.00006206536,0.000007312684],"category_scores_gemma":[0.00004099127,0.00009158394,0.00006963591,0.0002275292,0.00001977806,0.0003160568,0.0001445729,0.0002189469,7.626257e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005159269,"about_ca_system_score_gemma":0.00003403071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007620156,"about_ca_topic_score_gemma":0.00008225548,"domain_scores_codex":[0.9992176,0.00006213397,0.0001858651,0.0002389107,0.0001138031,0.0001816743],"domain_scores_gemma":[0.9996098,0.00006878497,0.0000892547,0.0001415287,0.00006256224,0.00002808414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005607467,0.00005735169,0.00005249802,0.00003504043,0.00001434759,0.000009627557,0.002994089,0.1316385,0.002707648,0.001743747,0.00004963403,0.8606414],"study_design_scores_gemma":[0.0001988645,0.0001010441,0.00007583642,0.00003251535,0.000003162899,0.00002107777,0.00002628591,0.9455599,0.05045186,0.003168408,0.0002719669,0.00008911001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2378214,0.0001959306,0.7612295,0.00004319653,0.000344857,0.00006726812,1.275198e-7,0.00005247083,0.0002452309],"genre_scores_gemma":[0.9849699,0.00003599386,0.014591,0.0001138196,0.00006981051,0.00001854677,0.000001367409,0.000007473406,0.0001921569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8605523,"threshold_uncertainty_score":0.3734685,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390705384","doi":"10.3390/iot5010002","title":"Enhancing IoT Data Security: Using the Blockchain to Boost Data Integrity and Privacy","year":2024,"lang":"en","type":"article","venue":"IoT","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Blockchain; Computer science; Computer security; Encryption; Internet of Things; Cloud computing; Information privacy; Architecture; Big data","retraction":null,"screen_n_in":null,"score":{"opus":0.06610467806443142,"gpt":0.3324460676582977,"spread":0.2663413895938662,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001306028,0.0001474691,0.0001482905,0.0001112067,0.0003110578,0.0003616515,0.004908841,0.0001198933,0.000007290387],"category_scores_gemma":[0.0001887137,0.0001108302,0.00001575194,0.00071919,0.0001169772,0.0001202076,0.008737069,0.0006556969,0.00002448117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003206899,"about_ca_system_score_gemma":0.0001317773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003067894,"about_ca_topic_score_gemma":0.00035239,"domain_scores_codex":[0.9982926,0.00006387281,0.0002227936,0.0009526503,0.0001857485,0.000282311],"domain_scores_gemma":[0.9950418,0.0002172538,0.00003615455,0.004586713,0.00003536964,0.00008264372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009272012,0.0002265038,0.0004279012,0.0002200607,0.0001872806,0.0001085393,0.0133284,0.00003819327,0.01611861,0.6471769,0.02302985,0.2991285],"study_design_scores_gemma":[0.0000615908,0.00001948394,0.00007094687,0.00008321297,0.00002080713,0.0001034298,0.0001493429,0.8597755,0.002293959,0.02987789,0.1073404,0.0002034448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3894328,0.002695183,0.5642863,0.0418928,0.0003865301,0.0004625592,0.0001645223,0.0005844496,0.00009491541],"genre_scores_gemma":[0.951079,0.00002102664,0.04798721,0.0006972538,0.0001488384,0.00001121651,0.00001556388,0.00001179354,0.00002814983],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8597373,"threshold_uncertainty_score":0.9992801,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3007112902","doi":"10.3390/iot1010002","title":"Towards a Low-Cost Precision Viticulture System Using Internet of Things Devices","year":2020,"lang":"en","type":"article","venue":"IoT","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drone; Precision agriculture; Computer science; Wireless; Base station; Field (mathematics); Wireless sensor network; Soil moisture sensor; Internet of Things; Scale (ratio); Interconnection; Agriculture; Real-time computing; Agricultural engineering; Embedded system; Telecommunications; Engineering; Computer network; Water content","retraction":null,"screen_n_in":null,"score":{"opus":0.02851027746820255,"gpt":0.2235600459502738,"spread":0.1950497684820712,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007843097,0.0001228621,0.0002021062,0.000004081905,0.00005634698,0.00005188993,0.0002468581,0.0001010298,0.0001113437],"category_scores_gemma":[0.00003317451,0.00003602772,0.0001020382,0.0002720063,0.00002143163,0.0001093439,0.00009048162,0.0000973665,0.00003275033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001916759,"about_ca_system_score_gemma":0.00000491887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003274131,"about_ca_topic_score_gemma":0.00004547805,"domain_scores_codex":[0.9991556,0.00003976572,0.0002099329,0.0002230236,0.000213233,0.0001584414],"domain_scores_gemma":[0.9996316,0.00004455334,0.0001080424,0.00002905818,0.00008413593,0.000102606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000617144,0.00006921515,0.004234194,0.000142982,0.0000348234,0.0000159711,0.00210503,0.00002076636,0.9527384,0.0004353421,0.006476904,0.03366467],"study_design_scores_gemma":[0.0008471658,0.001020769,0.17001,0.002073569,0.0002093155,0.0001061653,0.01160832,0.009719981,0.5471527,0.0000903649,0.2558178,0.001343858],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968538,0.0001500964,0.00003002909,0.00136034,0.0001323572,0.0001864825,0.00001572296,0.00007311279,0.001198072],"genre_scores_gemma":[0.9985371,0.000002604445,0.0002328962,0.0007113337,0.0004200692,0.000003509339,0.00002236054,7.099012e-7,0.00006944405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4055857,"threshold_uncertainty_score":0.1469168,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225120347","doi":"10.3390/iot3020017","title":"Evaluation and Selection Models for Ensemble Intrusion Detection Systems in IoT","year":2022,"lang":"en","type":"article","venue":"IoT","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Denial-of-service attack; Intrusion detection system; Scalability; Traffic classification; Internet of Things; Machine learning; Artificial intelligence; Classifier (UML); Data mining; Flexibility (engineering); Computer network; Computer security; The Internet; Quality of service","retraction":null,"screen_n_in":null,"score":{"opus":0.02982964560367175,"gpt":0.2606925953202721,"spread":0.2308629497166004,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001780911,0.00008096479,0.0001007487,0.0002195546,0.0004219269,0.00008889494,0.0001320078,0.00005308663,0.000009502193],"category_scores_gemma":[0.00003793632,0.00009072275,0.00002550582,0.0005213825,0.000008006818,0.0002126625,0.0001281467,0.0001608423,0.000001562375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003170436,"about_ca_system_score_gemma":0.00004917267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000292161,"about_ca_topic_score_gemma":0.0002755297,"domain_scores_codex":[0.9986258,0.0002857763,0.0001985737,0.0003197433,0.0004044308,0.000165723],"domain_scores_gemma":[0.9995767,0.00006432019,0.00008685906,0.0001167242,0.0001229973,0.00003237053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006143381,0.00005705391,0.00001745099,0.00002097258,0.00000698282,5.295408e-7,0.0007796147,0.4350581,0.02213264,0.007224713,0.00018191,0.5344585],"study_design_scores_gemma":[0.0004854646,0.0003094467,0.0001551419,0.000009264557,0.000007522573,0.00003523876,0.0000535264,0.9736081,0.002711781,0.01985141,0.002671762,0.0001012804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4488287,0.0004675798,0.5485365,0.0001267716,0.001041324,0.0007314641,0.000001159071,0.00009270317,0.0001737575],"genre_scores_gemma":[0.9982466,0.00001425177,0.00112062,0.00005590063,0.0001181554,0.00039698,0.000001676851,0.000007181049,0.00003868339],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5494179,"threshold_uncertainty_score":0.3699566,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309728390","doi":"10.3390/iot3040024","title":"Living in the Dark: MQTT-Based Exploitation of IoT Security Vulnerabilities in ZigBee Networks for Smart Lighting Control","year":2022,"lang":"en","type":"article","venue":"IoT","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"MQTT; Computer science; Home automation; Computer security; Computer network; Denial-of-service attack; The Internet; Internet of Things; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.008517261345961785,"gpt":0.2131317647065123,"spread":0.2046145033605505,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001174183,0.00009655347,0.00017262,0.000105145,0.0001148001,0.00001742406,0.0002010385,0.00004363518,0.00002032001],"category_scores_gemma":[0.0001838791,0.00008750665,0.00005755537,0.0002666782,0.00003490102,0.00004071943,0.00002309531,0.000309473,3.210509e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007530219,"about_ca_system_score_gemma":0.00002438265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001158945,"about_ca_topic_score_gemma":0.0005303115,"domain_scores_codex":[0.9989741,0.0001937951,0.0002881273,0.0001333895,0.000171179,0.0002394224],"domain_scores_gemma":[0.9981701,0.001596093,0.00004164368,0.0001542539,0.00002026514,0.00001760187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002923109,0.00006150214,0.01210017,0.0001128985,0.000005711268,0.000002746953,0.009402905,0.9769171,0.0003412523,0.0004659831,0.0002277406,0.0003327826],"study_design_scores_gemma":[0.0006326315,0.00009300889,0.01048495,0.00008154522,0.000006630145,0.00000169663,0.005439989,0.9816022,0.0003149372,0.0006151664,0.0005896747,0.0001375569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944302,0.0005834229,0.003637171,0.0001497949,0.0004277623,0.0004255888,0.00001511319,0.00004488782,0.000286039],"genre_scores_gemma":[0.9993967,0.000004226778,0.0001143046,0.0001069431,0.00008908553,0.0002667604,0.000004392725,0.00001333231,0.000004299309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004966435,"threshold_uncertainty_score":0.3568418,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3175101188","doi":"10.3390/iot2030019","title":"A Client/Server Malware Detection Model Based on Machine Learning for Android Devices","year":2021,"lang":"en","type":"article","venue":"IoT","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Android (operating system); Malware; Computer science; Mobile malware; Naive Bayes classifier; Mobile device; Mobile phone; Random forest; Machine learning; Computation; Artificial intelligence; Operating system; Support vector machine; Data mining; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.01755294246414554,"gpt":0.2684432642241041,"spread":0.2508903217599586,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001579863,0.0001296731,0.0001272426,0.0001095056,0.0001999712,0.00008779984,0.0002464702,0.0000715251,0.00001243272],"category_scores_gemma":[0.0001141848,0.000133222,0.00008868222,0.0002630423,0.00001182734,0.0002023908,0.00008998682,0.0001825019,0.000012036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007688825,"about_ca_system_score_gemma":0.0000490928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008674851,"about_ca_topic_score_gemma":0.00008290362,"domain_scores_codex":[0.9989573,0.00005022999,0.0001602279,0.0004302977,0.0001939137,0.0002079935],"domain_scores_gemma":[0.9992196,0.0001023581,0.00008755726,0.0003745765,0.0001590533,0.00005686315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000153615,0.0002361273,0.0006930227,0.0001690614,0.0000241742,0.00004354491,0.0002174581,0.5268207,0.03070059,0.003794652,0.0002173566,0.4369297],"study_design_scores_gemma":[0.0002641005,0.0001677078,0.0001079191,0.00002095396,0.000003469804,0.000007730982,0.00000464923,0.7821257,0.2097179,0.00205779,0.005393393,0.0001286283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009827107,0.00006448758,0.9884688,0.0003618477,0.0001506397,0.0001753001,0.000004222003,0.000684227,0.0002634081],"genre_scores_gemma":[0.8250691,0.00000373165,0.1736365,0.0007297919,0.00003373248,0.00007702405,0.00000563595,0.00001611857,0.0004283703],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8152421,"threshold_uncertainty_score":0.5432637,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4366771731","doi":"10.3390/iot4020007","title":"Secure Adaptive Context-Aware ABE for Smart Environments","year":2023,"lang":"en","type":"article","venue":"IoT","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure","funders":"","keywords":"Computer science; Computer security; Context (archaeology); Cloud computing; Orchestration; Encryption; Access control; Enforcement; Context awareness","retraction":null,"screen_n_in":null,"score":{"opus":0.04962705467817242,"gpt":0.2767575015414634,"spread":0.227130446863291,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0002093033,0.0001224545,0.0001277645,0.00008550541,0.0001148681,0.00005509562,0.01272843,0.000109723,0.00001235176],"category_scores_gemma":[0.002010175,0.0001188256,0.00004974621,0.0002979468,0.00007379224,0.0001991561,0.03044818,0.0001378996,0.0004299336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006117176,"about_ca_system_score_gemma":0.00002323215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001482641,"about_ca_topic_score_gemma":0.00001086455,"domain_scores_codex":[0.9988381,0.00002314647,0.0001348342,0.0004480533,0.0002054816,0.0003503786],"domain_scores_gemma":[0.9958364,0.0001945115,0.00005839789,0.003850725,0.00001396752,0.00004604303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009327339,0.00003188947,0.0003943535,0.00001262978,0.00003796647,0.00002739685,0.000135826,0.00001358978,0.0006584424,0.007538906,0.9386146,0.05252507],"study_design_scores_gemma":[0.0008879176,0.0002620851,0.005359896,0.0000728554,0.000009172566,0.000008154293,0.0002039635,0.3458694,0.01229264,0.3888209,0.2457326,0.0004804107],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02015336,0.0001667067,0.930846,0.04316093,0.001038554,0.0008349201,0.0003043794,0.002781891,0.0007132875],"genre_scores_gemma":[0.8817176,0.00003336924,0.1161474,0.0007057122,0.00007293915,0.0001899886,0.00004981859,0.00002803182,0.001055167],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8615642,"threshold_uncertainty_score":0.9926132,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403870071","doi":"10.3390/iot5040030","title":"A Survey of Artificial Intelligence Applications in Nuclear Power Plants","year":2024,"lang":"en","type":"article","venue":"IoT","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Algoma University; Ontario Tech University","funders":"","keywords":"Nuclear power; Environmental science; Computer science; Engineering; Biology; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.02059174668992974,"gpt":0.2568573817028993,"spread":0.2362656350129695,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001003295,0.00003722466,0.00006444271,0.00006467631,0.000006673323,0.0000143464,0.0000469702,0.00003052554,0.00005175085],"category_scores_gemma":[0.000007765751,0.00003608886,0.00001498816,0.000171488,0.000007496607,0.00001318896,0.000004027145,0.00006028452,0.0001576588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001640288,"about_ca_system_score_gemma":0.000004693093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002170694,"about_ca_topic_score_gemma":0.0004403866,"domain_scores_codex":[0.9996901,0.00001225558,0.0001319311,0.00005992132,0.00004541673,0.00006037761],"domain_scores_gemma":[0.9998585,0.00004225319,0.000004871868,0.00007229576,0.000006714517,0.00001534531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001105303,0.0002678794,0.00381574,0.0008337694,0.000291917,0.00004694493,0.009067795,0.07085551,0.174783,0.04625133,0.00432659,0.689349],"study_design_scores_gemma":[0.00004582947,0.0000321819,0.02212811,0.00009939713,0.00000368131,0.000005132628,0.0004638731,0.9372577,0.004057834,0.0004405722,0.03526921,0.0001964666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750822,0.0012041,0.01492961,0.00002793282,0.0008805905,0.0002837358,0.00007327726,0.0003967066,0.007121864],"genre_scores_gemma":[0.9999186,0.000005193416,0.00001059249,0.000003106565,0.00001637168,0.00001070123,0.000001823631,0.000009518185,0.00002408511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8664022,"threshold_uncertainty_score":0.2026438,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404064052","doi":"10.3390/iot5040033","title":"An Innovative Honeypot Architecture for Detecting and Mitigating Hardware Trojans in IoT Devices","year":2024,"lang":"en","type":"article","venue":"IoT","topic":"Physical Unclonable Functions (PUFs) and Hardware Security","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Honeypot; Internet of Things; Embedded system; Architecture; Computer science; Computer hardware; Operating system; Computer security; Art","retraction":null,"screen_n_in":null,"score":{"opus":0.01500267832119552,"gpt":0.2728957039927088,"spread":0.2578930256715133,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002698289,0.0001634278,0.0001942546,0.0002063197,0.000197366,0.0003525743,0.0003150617,0.00006573368,0.000004687564],"category_scores_gemma":[0.0001195865,0.0001461303,0.00004631434,0.001114095,0.00004723959,0.000270603,0.0001137035,0.0003338562,0.000006247722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004671566,"about_ca_system_score_gemma":0.00007914966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007398249,"about_ca_topic_score_gemma":0.0003771294,"domain_scores_codex":[0.9987339,0.00005889659,0.000205099,0.0005329862,0.0001492304,0.0003198601],"domain_scores_gemma":[0.9992002,0.0003312718,0.00004147495,0.000246124,0.00009935968,0.0000815295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003709649,0.0001712402,0.001666511,0.0006327527,0.00008178237,0.00006514931,0.02240947,0.001100739,0.03636992,0.07280645,0.0003143807,0.8643445],"study_design_scores_gemma":[0.001827089,0.001563125,0.02341272,0.001704042,0.00004695905,0.0001026075,0.001742035,0.6869729,0.05240038,0.1654635,0.06299791,0.001766658],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7242505,0.0003863389,0.2727875,0.001085452,0.0003950044,0.0003051744,0.00003185944,0.0002884395,0.0004697843],"genre_scores_gemma":[0.9719987,0.000001468368,0.0273005,0.0003046377,0.0002779746,0.00005508049,0.000005696625,0.00001387804,0.00004205911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8625779,"threshold_uncertainty_score":0.5959021,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409607258","doi":"10.3390/iot6020023","title":"A Lightweight Encryption Method for IoT-Based Healthcare Applications: A Review and Future Prospects","year":2025,"lang":"en","type":"review","venue":"IoT","topic":"Internet of Things and AI","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"St. Clair College","funders":"National Institute of Standards and Technology","keywords":"Internet of Things; Computer science; Encryption; Health care; Computer security; Embedded system; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.02261670005952168,"gpt":0.374788136632298,"spread":0.3521714365727764,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005447944,0.0003210655,0.001163095,0.0001519332,0.000134658,0.000140416,0.0008523705,0.0002337627,0.000005701613],"category_scores_gemma":[0.00003556068,0.000239711,0.000345563,0.0004798987,0.00001348591,0.00004891257,0.0001495643,0.0002806679,0.00001335669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001025174,"about_ca_system_score_gemma":0.0005341868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009585927,"about_ca_topic_score_gemma":0.000004354391,"domain_scores_codex":[0.9982485,0.0001398753,0.0004827475,0.000724029,0.00015946,0.0002453439],"domain_scores_gemma":[0.9984761,0.0002066785,0.0003828844,0.0006869193,0.000159917,0.00008744623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.94504e-7,0.00001361363,2.309559e-8,0.1377773,0.00001755844,7.109109e-7,0.00001074112,1.782385e-8,4.598497e-8,0.08745238,0.003522273,0.7712049],"study_design_scores_gemma":[0.00007610855,0.0000538517,1.263335e-7,0.03947826,0.0002582396,0.00001357041,5.010907e-7,0.0001763755,0.00000186622,0.00222298,0.9574936,0.0002245324],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[6.348472e-10,0.7320576,0.2568187,0.007590985,0.000219363,0.003029112,0.00002828354,0.00008528667,0.0001707405],"genre_scores_gemma":[8.2731e-9,0.7483844,0.2458316,0.002496196,0.0003848819,0.002279979,0.00003093829,0.00001304038,0.0005789612],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9539713,"threshold_uncertainty_score":0.9775131,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3158281120","doi":"10.3390/iot2020014","title":"A Greedy Scheduling Approach for Peripheral Mobile Intelligent Systems","year":2021,"lang":"en","type":"article","venue":"IoT","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Distributed computing; Cloudlet; Load balancing (electrical power); Scheduling (production processes); Wireless network; Greedy algorithm; Heuristics; Mobile computing; Wireless; Mobile device; Computer network; Algorithm; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.03511785922869599,"gpt":0.2679766479064904,"spread":0.2328587886777944,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002659944,0.0001143328,0.0001675407,0.0000393296,0.0001655439,0.0003144946,0.0004385041,0.00005614576,0.000001598997],"category_scores_gemma":[0.00003021001,0.0001099295,0.00009574802,0.0002472932,0.00001564714,0.00008908004,0.0002346045,0.0001043462,0.00001453688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006049167,"about_ca_system_score_gemma":0.0000977931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001794698,"about_ca_topic_score_gemma":3.584561e-7,"domain_scores_codex":[0.9988929,0.00004021499,0.0002067357,0.0003805015,0.0001550278,0.0003246027],"domain_scores_gemma":[0.999309,0.00005941369,0.00005145629,0.0003699892,0.0001338206,0.00007630205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004689092,0.001308889,0.003026217,0.001750424,0.000389624,0.0002037268,0.02346923,0.3207005,0.01185702,0.06727739,0.02265384,0.5473163],"study_design_scores_gemma":[0.0001569468,0.00005162429,0.00002714257,0.00003097128,0.000004278274,0.00005026893,0.0001841239,0.9659681,0.001940493,0.0001578084,0.03126267,0.0001656218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03062383,0.001404743,0.9587334,0.00005286812,0.007174779,0.0002501315,2.513971e-7,0.0001437613,0.001616177],"genre_scores_gemma":[0.5504459,0.000005635762,0.4433728,0.0002007211,0.004286194,0.0001425195,0.00001256291,0.00002439943,0.001509262],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6452675,"threshold_uncertainty_score":0.4482796,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404063776","doi":"10.3390/iot5040032","title":"Review of IoT Systems for Air Quality Measurements Based on LTE/4G and LoRa Communications","year":2024,"lang":"en","type":"article","venue":"IoT","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Canada Research Chairs; York University; University of Toronto","funders":"University of Toronto; University of Johannesburg; National Research Foundation; Natural Sciences and Engineering Research Council of Canada; International Development Research Centre","keywords":"Internet of Things; Computer science; Computer network; Telecommunications; Embedded system","retraction":null,"screen_n_in":null,"score":{"opus":0.2184633640435791,"gpt":0.3926466590560009,"spread":0.1741832950124219,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001519654,0.00006823782,0.0001364795,0.00001452842,0.00008897242,0.00001272039,0.000162432,0.00002760776,0.00001956582],"category_scores_gemma":[0.0001751089,0.000058546,0.00004378679,0.0001068472,0.00008934572,0.00001648933,0.0000626914,0.00006780062,0.00002372862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008318732,"about_ca_system_score_gemma":0.000009453105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002992906,"about_ca_topic_score_gemma":0.000006888675,"domain_scores_codex":[0.9991611,0.0001365226,0.0002488709,0.0001512432,0.0002033698,0.00009891748],"domain_scores_gemma":[0.9992328,0.0002558603,0.00006534607,0.0003921524,0.00001237688,0.00004143556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002316004,0.002057087,0.1534002,0.1605575,0.0004052091,0.000005557806,0.00476003,0.01967103,0.02553705,0.008350272,0.1134309,0.5115935],"study_design_scores_gemma":[0.001414307,0.0009506073,0.04060971,0.08302773,0.000321653,0.000007879148,0.0005727875,0.2763657,0.004554933,0.0007764192,0.5901391,0.001259172],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5234652,0.3500026,0.02288263,0.02757888,0.004555183,0.007971406,0.0007389323,0.0009520274,0.06185318],"genre_scores_gemma":[0.9977164,0.0003397464,0.001405351,0.0002753639,0.00003962421,0.00004901255,0.000006717438,0.000009634703,0.0001581401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5103343,"threshold_uncertainty_score":0.2387436,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3196413096","doi":"10.3390/iot2030027","title":"A Pervasive Collaborative Architectural Model at the Network’s Periphery","year":2021,"lang":"en","type":"article","venue":"IoT","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Ubiquitous computing; Wireless network; Mobile device; The Internet; Mobile computing; Distributed computing; Wireless; Computer network; Telecommunications; World Wide Web; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.01298816519891615,"gpt":0.2287267192558534,"spread":0.2157385540569373,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001546523,0.0001215241,0.0001284619,0.00001062106,0.0004487479,0.0001842637,0.0004893022,0.00003804028,0.000009224984],"category_scores_gemma":[0.00003176857,0.00008549579,0.00007219725,0.0004844599,0.00005934384,0.00006817748,0.0007276087,0.0001630435,0.00005736512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006689647,"about_ca_system_score_gemma":0.0002576806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007929547,"about_ca_topic_score_gemma":0.0000387956,"domain_scores_codex":[0.9989003,0.0001056904,0.0001311227,0.0003148622,0.0001948509,0.0003531626],"domain_scores_gemma":[0.9991344,0.0001518359,0.00005153268,0.0004455636,0.000157062,0.00005959419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004508324,0.00009393309,0.001927755,0.00003405316,0.0002155173,0.0004067152,0.05491388,0.4972426,0.003720893,0.01420318,0.2340255,0.1931708],"study_design_scores_gemma":[0.0002024417,0.00002914161,0.001211772,0.00002489987,0.000008385184,0.0001104169,0.00009502201,0.9671242,0.001436542,0.004008494,0.02553417,0.0002145529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6674975,0.003191318,0.2830889,0.01186648,0.009542666,0.0002748993,0.000001446009,0.0002621388,0.02427465],"genre_scores_gemma":[0.8987157,0.00001873452,0.07693531,0.0054142,0.005675419,0.00003057145,0.000007856115,0.00003076192,0.01317145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4698815,"threshold_uncertainty_score":0.3486417,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4361005410","doi":"10.3390/iot4020005","title":"Evaluating Consumer Behavior, Decision Making, Risks, and Challenges for Buying an IoT Product","year":2023,"lang":"en","type":"article","venue":"IoT","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"Mitacs","keywords":"Product (mathematics); Warranty; Software; Preference; Business; Smart device; Computer science; Internet privacy; Internet of Things; Willingness to pay; Marketing; Advertising; Human–computer interaction","retraction":null,"screen_n_in":null,"score":{"opus":0.6590241673501064,"gpt":0.5620289818321567,"spread":0.09699518551794972,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004317834,0.0001631538,0.000259634,0.000485722,0.0003876423,0.0001564758,0.0004914487,0.0001599247,0.0001119781],"category_scores_gemma":[0.003739026,0.0001315511,0.00006701542,0.000494912,0.0001344203,0.0001235853,0.0002108689,0.0001846016,0.0002025991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002080028,"about_ca_system_score_gemma":0.00004314196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001001378,"about_ca_topic_score_gemma":0.00008083392,"domain_scores_codex":[0.9974769,0.0001322257,0.0004781039,0.0008157307,0.0007567176,0.0003403003],"domain_scores_gemma":[0.9977457,0.0009440347,0.0001944263,0.0007360554,0.0002926965,0.00008709195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003169369,0.00005229896,0.07020571,0.000005050913,0.000004392704,0.000008645885,0.0004223684,0.00002987746,0.001028303,0.0005137505,0.0006901525,0.9270077],"study_design_scores_gemma":[0.0007913889,0.0002594446,0.9604132,0.00005817012,0.00005460251,0.00003814264,0.001775557,0.004476536,0.0004742291,0.01574204,0.01562367,0.0002930179],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952791,0.001649507,0.0003825391,0.001121958,0.0005655233,0.0005385626,0.00002513953,0.0003820347,0.00005568719],"genre_scores_gemma":[0.9828693,0.0001945775,0.01634474,0.00006566546,0.00007645522,0.0001303812,0.000003447748,0.0000240209,0.0002914151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9267147,"threshold_uncertainty_score":0.5364497,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4392916160","doi":"10.3390/iot5010009","title":"Integration of Smart Cane with Social Media: Design of a New Step Counter Algorithm for Cane","year":2024,"lang":"en","type":"article","venue":"IoT","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cane; Computer science; Social media; Algorithm; Agricultural engineering; Engineering; World Wide Web; Biology; Food science","retraction":null,"screen_n_in":null,"score":{"opus":0.02001352608807617,"gpt":0.2311688651333334,"spread":0.2111553390452572,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001691129,0.0001116429,0.0002228532,0.0000985385,0.00001402814,0.00001452408,0.00006628808,0.00007609758,0.0000218787],"category_scores_gemma":[0.00001414582,0.00009270673,0.00004382084,0.0001675711,0.00002609149,0.00004204785,0.000004553986,0.00008156915,0.000004948016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001051718,"about_ca_system_score_gemma":0.0001448453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005434077,"about_ca_topic_score_gemma":0.001359924,"domain_scores_codex":[0.999344,0.00001691944,0.0002207383,0.000103985,0.0001722304,0.0001421335],"domain_scores_gemma":[0.9996442,0.0001332115,0.00002920043,0.00008750363,0.00007041181,0.00003551723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003990816,0.0001120083,0.0001266033,0.004174784,0.001456613,0.00007964676,0.03948369,0.01843534,0.1605982,0.001916468,0.2973204,0.4758972],"study_design_scores_gemma":[0.001918265,0.0006362365,0.0003104784,0.0009690512,0.0002212601,0.00002846545,0.001216212,0.8572639,0.1158008,0.0001496749,0.02096407,0.0005215438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01995522,0.0005173908,0.9772363,0.00006414828,0.001294703,0.000456642,0.0001473001,0.0001365748,0.0001917414],"genre_scores_gemma":[0.9768351,0.000004496513,0.02189147,0.000008715216,0.0007044374,0.00005509128,0.00003308347,0.00006625408,0.0004013449],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9568799,"threshold_uncertainty_score":0.3780471,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3043656308","doi":"10.3390/iot2020012","title":"ThriftyNets: Convolutional Neural Networks with Tiny Parameter Budget","year":2021,"lang":"en","type":"preprint","venue":"IoT","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Convolutional neural network; Normalization (sociology); Computer science; Computation; Upsampling; Complement (music); Factorization; Algorithm; Artificial intelligence; Image (mathematics)","retraction":null,"screen_n_in":null,"score":{"opus":0.01874690361588241,"gpt":0.2574461907209802,"spread":0.2386992871050978,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009977922,0.000376607,0.000372455,0.00006192353,0.0001663451,0.000320063,0.001439541,0.0002441142,0.00003770868],"category_scores_gemma":[0.00002313409,0.0003362446,0.0001350885,0.0003636809,0.0001471954,0.0001612449,0.001738167,0.001074838,0.00002547693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007617491,"about_ca_system_score_gemma":0.0001349926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001569547,"about_ca_topic_score_gemma":0.00002405688,"domain_scores_codex":[0.9975464,0.0001014443,0.0003409405,0.001116273,0.0003929915,0.0005020009],"domain_scores_gemma":[0.9974791,0.0003274833,0.0002638933,0.001588032,0.0001764664,0.0001650537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001359319,0.00008847733,0.0008061918,0.00002289559,0.00007382853,0.00007910854,0.000100742,0.9681058,0.00002692176,0.01221263,0.003109561,0.01536024],"study_design_scores_gemma":[0.0002308513,0.00004802122,0.002665078,0.00007522274,0.00002046357,0.00009586308,0.000006230978,0.9876479,0.00005942922,0.003545184,0.005097864,0.0005078964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01433769,0.001249047,0.9799097,0.002160938,0.0008518537,0.0004671474,0.0000110145,0.000386024,0.0006266267],"genre_scores_gemma":[0.7860474,0.0000621296,0.2108556,0.001764357,0.0005523121,0.0002992875,0.000129478,0.00004026519,0.0002491071],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7717097,"threshold_uncertainty_score":0.999909,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}