{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":10,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":10,"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":"5b226f8dac2b","filters":{"venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)"}},"results":[{"id":"W4399663950","doi":"10.12928/telkomnika.v22i4.25847","title":"Multi objective hyperparameter tuning via random search on deep learning models","year":2024,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Flow Measurement and Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Universiti Teknologi MARA","keywords":"Hyperparameter; Random search; Computer science; Artificial intelligence; Machine learning; Hyperparameter optimization; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.01891612887932724,"gpt":0.2349294254175796,"spread":0.2160132965382523,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009843935,0.0002744669,0.0003680184,0.000269319,0.000365832,0.0002607068,0.0003065908,0.00009820553,0.00001163134],"category_scores_gemma":[0.00003406481,0.0002684062,0.0001496178,0.0003784458,0.00004200189,0.0001728903,0.00006161301,0.001048259,0.00002516467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001991448,"about_ca_system_score_gemma":0.0000319803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002839653,"about_ca_topic_score_gemma":0.00003382834,"domain_scores_codex":[0.9982883,0.0002404044,0.0003570424,0.0003387102,0.000256831,0.0005186675],"domain_scores_gemma":[0.9988167,0.0005739402,0.00003935524,0.0003883679,0.00009579123,0.00008587105],"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":[0.00004928186,0.00003881424,0.00006111455,0.00004117788,0.0004591323,0.000002253308,0.0007962158,0.7387106,0.01878356,0.0008491572,0.00003417326,0.2401745],"study_design_scores_gemma":[0.00131449,0.00009622611,0.00006660271,0.00008236137,0.00008314077,0.000007287337,0.0000620966,0.9947426,0.000883388,0.0003129236,0.002060652,0.0002882431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1349543,0.0345673,0.8272876,0.0003762222,0.0001201853,0.0003310252,0.000001389405,0.0009774657,0.001384569],"genre_scores_gemma":[0.9949315,0.002039453,0.002626788,0.0001675191,0.0000634931,0.00001946625,0.00002325045,0.00006887436,0.00005965443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8599772,"threshold_uncertainty_score":0.9999768,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3121978214","doi":"10.12928/telkomnika.v19i3.18768","title":"Design of compact microstrip bandpass filter using square DMS slots for Wi-Fi and bluetooth applications","year":2021,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec","funders":"","keywords":"Return loss; Miniaturization; Insertion loss; Microstrip; Band-pass filter; Resonator; Bluetooth; Computer science; Filter (signal processing); Microwave; Wireless; Electronic engineering; Acoustics; Electrical engineering; Materials science; Optoelectronics; Telecommunications; Physics; Engineering; Antenna (radio)","retraction":null,"screen_n_in":null,"score":{"opus":0.01644387065165689,"gpt":0.2380127097322021,"spread":0.2215688390805453,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003944473,0.0002188358,0.0003750371,0.00008626605,0.0002112334,0.00008990691,0.0002157585,0.0001049307,0.000003759216],"category_scores_gemma":[0.00003295498,0.0002441236,0.00006478923,0.0001921025,0.00005133996,0.00006450349,0.00004976923,0.000230811,5.38841e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007423422,"about_ca_system_score_gemma":0.00007239221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009613927,"about_ca_topic_score_gemma":0.000006051698,"domain_scores_codex":[0.9988245,0.00007436195,0.0004171428,0.0002345839,0.00008718461,0.0003622378],"domain_scores_gemma":[0.9986587,0.0005011262,0.0001096486,0.0004777308,0.0001789456,0.00007390822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004803554,0.0001024392,0.000223976,0.0004204744,0.0003694108,7.68832e-7,0.0004256742,0.3680741,0.5895033,0.003341024,0.0005345671,0.03695632],"study_design_scores_gemma":[0.001297322,0.00006991235,0.0002791716,0.00008039298,0.00008120306,0.00003953972,0.00004343497,0.9548646,0.03334397,0.0004452494,0.009164353,0.0002908159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07010362,0.02326426,0.9057115,0.0001310312,0.00004294829,0.0004974635,0.00003195154,0.0001548975,0.00006229572],"genre_scores_gemma":[0.9776089,0.001129746,0.02099406,0.00006322237,0.00005529351,0.00001879714,0.00006236387,0.00005034196,0.00001726771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9075053,"threshold_uncertainty_score":0.9955071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2945053206","doi":"10.12928/telkomnika.v17i5.10202","title":"Understanding user intention in image retrieval: generalization selection using multiple concept hierarchies","year":2019,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":4,"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","funders":"","keywords":"Computer science; Generalization; Hierarchy; Selection (genetic algorithm); Set (abstract data type); Information retrieval; Context (archaeology); Focus (optics); Task (project management); Abstraction; Artificial intelligence; Theoretical computer science; Data mining; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.03376756610720483,"gpt":0.2698657800103234,"spread":0.2360982139031185,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000896165,0.0002298579,0.0003139923,0.0003550498,0.0003285456,0.0003548403,0.0006407145,0.00013847,0.000008216572],"category_scores_gemma":[0.0001235363,0.0002445453,0.00007535543,0.0009716951,0.000076501,0.0007655855,0.0002075418,0.0004458782,0.000005514944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005980708,"about_ca_system_score_gemma":0.0001278343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008708524,"about_ca_topic_score_gemma":0.00004106237,"domain_scores_codex":[0.9978438,0.0003921126,0.0005597739,0.0004856082,0.0002626564,0.0004560367],"domain_scores_gemma":[0.9984123,0.0003600247,0.0003623848,0.0005839171,0.0002183905,0.00006294772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001893544,0.0003048675,0.0183104,0.00008417097,0.0001089119,0.000001591004,0.001444376,0.002608253,0.5797163,0.3690789,0.00007028178,0.02808259],"study_design_scores_gemma":[0.001428266,0.0001427938,0.002430123,0.00006123544,0.00001212156,0.00001935616,0.00008220463,0.9668467,0.02292243,0.005022998,0.0007214777,0.0003103058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1007511,0.0009115618,0.8966436,0.0006412477,0.0001067356,0.0005031032,0.000001197065,0.0003249037,0.0001165928],"genre_scores_gemma":[0.9655936,0.0004551353,0.03361367,0.000199919,0.00003016367,0.00000579827,0.00002311584,0.00002486275,0.00005366939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9642384,"threshold_uncertainty_score":0.9972268,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1716099252","doi":"10.12928/telkomnika.v9i1.679","title":"Hybrid De-embedding Technique for Microwave Absorber Characterization","year":2011,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Advanced Antenna and Metasurface Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Institut Teknologi Bandung; Queen's University; Queen's University Belfast; Health Resources in Action","keywords":"Test fixture; Microwave; Fixture; Scattering parameters; Embedding; Characterization (materials science); Experimental data; Computer science; Process (computing); Test data; Ideal (ethics); Algorithm; Electronic engineering; Optics; Mechanical engineering; Mathematics; Physics; Engineering; Artificial intelligence; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.01297133180877277,"gpt":0.2333409372028099,"spread":0.2203696053940371,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003751738,0.0001887846,0.0002435385,0.00009748796,0.0001884607,0.00003281447,0.0003060808,0.00009763532,0.000003302686],"category_scores_gemma":[0.00004429894,0.0002015559,0.00006029524,0.00009495408,0.00004914371,0.0001157676,0.00005240318,0.0002745923,0.000002055053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009371514,"about_ca_system_score_gemma":0.00002545505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003479838,"about_ca_topic_score_gemma":0.00000374981,"domain_scores_codex":[0.9990107,0.00003412999,0.000284586,0.0001836014,0.00005189844,0.0004350912],"domain_scores_gemma":[0.9992755,0.0001067707,0.0001032808,0.0003877712,0.00008203227,0.00004463411],"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":[0.00002381013,0.0000276464,0.00009330926,0.00003896323,0.00005989703,4.722124e-7,0.000184422,0.0004412926,0.9075378,0.006600412,0.00002644982,0.08496555],"study_design_scores_gemma":[0.001253461,0.0001893548,0.00109417,0.00007811966,0.00007426884,0.00006701355,0.00007582796,0.3957812,0.5713044,0.01586891,0.01361027,0.0006030526],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1637962,0.001917501,0.8327586,0.00007281595,0.00004449159,0.0004674848,0.000007605461,0.0006663583,0.0002689368],"genre_scores_gemma":[0.9378073,0.00145989,0.06041227,0.000093676,0.00002506775,0.00009725321,0.00003839802,0.00004698567,0.00001921518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7740111,"threshold_uncertainty_score":0.8219213,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3004508189","doi":"10.12928/telkomnika.v18i4.13073","title":"SVC device optimal location for voltage stability enhancement based on a combined particle swarm optimization-continuation power flow technique","year":2020,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":4,"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":"Static VAR compensator; Particle swarm optimization; Control theory (sociology); AC power; Computer science; Voltage; Electric power system; Power (physics); Stability (learning theory); Mathematical optimization; Engineering; Mathematics; Electrical engineering; Algorithm; Control (management)","retraction":null,"screen_n_in":null,"score":{"opus":0.01127063258727467,"gpt":0.2229751542872774,"spread":0.2117045217000027,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009899919,0.0002857871,0.0003811255,0.00005822041,0.0003005653,0.0001296465,0.0003229644,0.0001313944,0.00003981428],"category_scores_gemma":[0.0002649451,0.0003143118,0.00008495391,0.0003958229,0.00004475107,0.0001561393,0.00004175062,0.0002745561,0.000004487315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002458761,"about_ca_system_score_gemma":0.0001149828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000481416,"about_ca_topic_score_gemma":0.0000105462,"domain_scores_codex":[0.9980759,0.0001952703,0.0006860485,0.0004044381,0.0002198255,0.0004185087],"domain_scores_gemma":[0.9981926,0.0004486436,0.0001891998,0.0006038167,0.0004146645,0.0001510879],"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":[0.0002148174,0.0001472638,0.0001287394,0.0000999294,0.00004329394,9.284832e-8,0.0004290706,0.9912987,0.00373425,0.0009699293,0.00007996385,0.002853983],"study_design_scores_gemma":[0.00222628,0.0004675328,0.0001257512,0.0000343894,0.00003279352,5.361647e-7,0.00005811677,0.9808806,0.01416639,0.00002856524,0.001677944,0.0003011475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01535382,0.0005438795,0.9799031,0.001431184,0.00007048724,0.001901177,0.00001659951,0.0004971717,0.0002825677],"genre_scores_gemma":[0.9628828,0.00004599024,0.03579274,0.0007518948,0.00002289851,0.0003035075,0.0001478016,0.00004712143,0.000005307469],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9475289,"threshold_uncertainty_score":0.9999309,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2476717803","doi":"10.12928/telkomnika.v14i2a.4375","title":"O2O E-Commerce Data Mining in Big Data Era","year":2016,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Air Canada","funders":"","keywords":"Big data; Computer science; Data mining; Data science","retraction":null,"screen_n_in":null,"score":{"opus":0.05821511814293429,"gpt":0.2733290228157315,"spread":0.2151139046727972,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001676277,0.0002628873,0.0003695809,0.0004544258,0.0004375234,0.0002223613,0.003351053,0.0001628105,0.00002157773],"category_scores_gemma":[0.000449745,0.0002237467,0.00002768942,0.0008663451,0.0001868588,0.001078787,0.002727706,0.0005018149,0.00004836305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006004087,"about_ca_system_score_gemma":0.0000852694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004351696,"about_ca_topic_score_gemma":0.002046277,"domain_scores_codex":[0.9978439,0.00005845609,0.0006427792,0.0006682189,0.0001798343,0.0006068756],"domain_scores_gemma":[0.9951858,0.0005304237,0.0004072181,0.003709512,0.000150127,0.00001690883],"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":[0.00003793215,0.0001738441,0.02696268,0.0000269833,0.00008167482,0.000002271765,0.00003171171,0.000007396396,0.001753344,0.06436915,0.004980555,0.9015725],"study_design_scores_gemma":[0.009303632,0.00008442919,0.05568531,0.0005258897,0.0002025648,0.00003474153,0.0004666272,0.2080575,0.00009488145,0.01369309,0.7103707,0.00148066],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7870817,0.006285785,0.05034595,0.1448731,0.0004475808,0.001063041,0.00007123571,0.001092121,0.008739557],"genre_scores_gemma":[0.9928713,0.0004574088,0.001650175,0.004052049,0.0004104256,0.00001154538,0.0004478606,0.00004157402,0.0000576654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9000918,"threshold_uncertainty_score":0.9124125,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405794961","doi":"10.12928/telkomnika.v23i1.26155","title":"PV solar anomaly detection using low-cost data logger and ANN algorithm","year":2024,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Data logger; Anomaly detection; Computer science; Anomaly (physics); Algorithm; Data mining; Physics; Operating system","retraction":null,"screen_n_in":null,"score":{"opus":0.02135306883225684,"gpt":0.2761771474573779,"spread":0.2548240786251211,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001227531,0.0002496305,0.0002743654,0.0002111811,0.000603323,0.0009557332,0.001173078,0.0001400453,0.000003725753],"category_scores_gemma":[0.00006131289,0.0002593694,0.00005015754,0.0005386091,0.00007362491,0.0007717421,0.0006664671,0.0005839058,0.000008809208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001238892,"about_ca_system_score_gemma":0.0002051086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001276277,"about_ca_topic_score_gemma":0.00007588417,"domain_scores_codex":[0.9979528,0.0002543973,0.0004155409,0.0006858276,0.000218333,0.0004731533],"domain_scores_gemma":[0.9977048,0.0004301641,0.0001509126,0.001466268,0.0001145396,0.0001333394],"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":[0.000009417864,0.00005212479,0.0002080665,0.00003582375,0.0001020022,0.000004673203,0.00036451,0.0003851554,0.004886894,0.003998541,0.00008208197,0.9898707],"study_design_scores_gemma":[0.000538819,0.0000554551,0.0008052722,0.00003937478,0.00003725732,0.0001273634,0.00001626913,0.9685541,0.0008630331,0.00114666,0.02753302,0.0002834173],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03724842,0.01829629,0.9426072,0.0007212312,0.0002668707,0.0003704717,0.0000156832,0.000400598,0.00007329809],"genre_scores_gemma":[0.9722251,0.001517579,0.02541384,0.0005970414,0.0001390335,0.000007648861,0.00004906308,0.00003051939,0.00002013898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9895873,"threshold_uncertainty_score":0.9999859,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405794967","doi":"10.12928/telkomnika.v23i1.25857","title":"Swarm intelligence for intrusion detection systems in internet of things environments","year":2024,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Universitas Islam Riau","keywords":"Internet of Things; Intrusion detection system; Computer science; Swarm intelligence; Swarm behaviour; The Internet; Intrusion; Computer security; Artificial intelligence; World Wide Web; Machine learning; Particle swarm optimization; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.009726242668192943,"gpt":0.2364912110619449,"spread":0.226764968393752,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001272846,0.0001728424,0.0002703839,0.0002663325,0.0001366942,0.000218203,0.0006760222,0.0001282916,0.000001647113],"category_scores_gemma":[0.00005026541,0.0001737241,0.0000745739,0.0004184833,0.00005093617,0.0004290705,0.0002491819,0.0004117783,0.000003821359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001739676,"about_ca_system_score_gemma":0.00004756871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001714062,"about_ca_topic_score_gemma":0.00004617477,"domain_scores_codex":[0.9983113,0.0001848261,0.0006016291,0.0004043192,0.0001768536,0.0003211131],"domain_scores_gemma":[0.9986711,0.0005495577,0.0001953603,0.0004856104,0.00005044482,0.00004799263],"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":[0.00005750113,0.0000831315,0.00002438445,0.0001075596,0.00004732821,7.554416e-7,0.001332393,0.003189823,0.01116581,0.1032913,0.00002281453,0.8806772],"study_design_scores_gemma":[0.0003053625,0.0003165576,0.00009483857,0.0001615536,0.00001176086,0.00001962081,0.00002532416,0.9666242,0.01223101,0.006982105,0.01306527,0.0001624056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06181975,0.01306306,0.9237496,0.0003189804,0.0003700569,0.0004764413,6.231795e-7,0.0001261151,0.00007534867],"genre_scores_gemma":[0.9941337,0.001975222,0.003647365,0.000107873,0.00004818662,0.00003815514,0.000005348871,0.00001592547,0.000028199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9634343,"threshold_uncertainty_score":0.7084261,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3041073179","doi":"10.12928/telkomnika.v18i5.5632","title":"Accurate harmonic source identification using S-transform","year":2020,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Infineon Technologies (Canada)","funders":"","keywords":"Harmonic; MATLAB; Computer science; Electrical impedance; Identification (biology); Harmonic analysis; Power (physics); S transform; Electronic engineering; Acoustics; Physics; Engineering; Artificial intelligence; Electrical engineering; Wavelet transform","retraction":null,"screen_n_in":null,"score":{"opus":0.02633344104584415,"gpt":0.2508089269642004,"spread":0.2244754859183563,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005035912,0.0002490553,0.0003226429,0.00006713758,0.000359407,0.0001916585,0.000502767,0.0001252049,0.00001176519],"category_scores_gemma":[0.00004035718,0.0002871312,0.00009045247,0.0003042718,0.00005683494,0.0002278475,0.00006814472,0.0005850593,0.00002139798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001278759,"about_ca_system_score_gemma":0.00006671857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001587411,"about_ca_topic_score_gemma":0.00001270444,"domain_scores_codex":[0.9983672,0.0001146946,0.0005778925,0.0002782307,0.0001747261,0.0004872088],"domain_scores_gemma":[0.9990103,0.0001596208,0.0001409937,0.000447305,0.00008343324,0.000158306],"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":[0.0001982125,0.000182531,0.0002198364,0.0004986015,0.000827443,0.000003443751,0.007944168,0.2978997,0.2650813,0.02009413,0.0009044926,0.4061461],"study_design_scores_gemma":[0.0008933381,0.00005155601,0.0002590588,0.00001884976,0.00006380289,0.0000104872,0.00008652106,0.967216,0.005584747,0.0005110073,0.0249797,0.0003249923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2906646,0.01300922,0.6916851,0.002942728,0.00009774947,0.0003954837,0.000009740206,0.0008060657,0.0003891998],"genre_scores_gemma":[0.9958336,0.002098817,0.001056858,0.0008107622,0.00009269469,0.000007818686,0.00003229401,0.00005533247,0.00001182322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.705169,"threshold_uncertainty_score":0.9999581,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4405795043","doi":"10.12928/telkomnika.v23i1.26377","title":"Enhanced sentiment analysis and emotion detection in movie reviews using support vector machine algorithm","year":2024,"lang":"en","type":"article","venue":"TELKOMNIKA (Telecommunication Computing Electronics and Control)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Support vector machine; Emotion detection; Computer science; Artificial intelligence; Algorithm; Pattern recognition (psychology); Emotion recognition","retraction":null,"screen_n_in":null,"score":{"opus":0.0130035643032562,"gpt":0.2798707231855362,"spread":0.26686715888228,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00157785,0.0002324285,0.0005001,0.0006309376,0.0002701936,0.0004542958,0.0003728375,0.00008075394,0.00001282985],"category_scores_gemma":[0.00002265934,0.0002254738,0.0001625192,0.001603098,0.00003151854,0.0003309643,0.0002105987,0.0003395722,0.000005494101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001765004,"about_ca_system_score_gemma":0.00005589147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001229235,"about_ca_topic_score_gemma":0.0001432787,"domain_scores_codex":[0.9978414,0.0003434802,0.0006642591,0.0005710566,0.0002030499,0.000376723],"domain_scores_gemma":[0.998868,0.0001839017,0.000229954,0.00057699,0.0000631757,0.00007794074],"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":[0.000005757026,0.00005804724,0.0002932959,0.00002925438,0.0003459675,0.000001855106,0.0005540884,0.0008133049,0.01305055,0.001816983,0.000006339264,0.9830245],"study_design_scores_gemma":[0.0004411656,0.00008000908,0.00180737,0.00005502226,0.0002258777,0.00001158447,0.00001752148,0.9923094,0.002878347,0.0002557593,0.001691219,0.0002267542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06389933,0.02339981,0.9117516,0.0004042112,0.0001042861,0.0002757779,0.000001374446,0.0001187895,0.00004480438],"genre_scores_gemma":[0.9755435,0.003964668,0.02021424,0.0001482852,0.00004879558,0.0000113045,0.00002410265,0.00001391186,0.00003118924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9914961,"threshold_uncertainty_score":0.9194555,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}