{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"a170a2a51cde","filters":{"venue":"Electronics Optics & Control"}},"results":[{"id":"W2347582950","doi":"","title":"Threat Level Assessment Based on Fuzzy Bayesian Networks","year":2014,"lang":"en","type":"article","venue":"Electronics Optics & Control","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Bayesian network; Azimuth; Fuzzy logic; Battlefield; Bayesian probability; Data mining; Software; Set (abstract data type); Computer science; Fuzzy set; Artificial intelligence; Machine learning; Mathematics","authors":[{"name":"Ding Da-l","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0105929591816875,"gpt":0.2801381035896611,"spread":0.2695451444079736,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003165487,0.0008871433,0.001006262,0.00298131,0.000923083,0.001915451,0.001370116,0.001182467,0.001891859],"category_scores_gemma":[0.01039994,0.0006427226,0.001161872,0.001486149,0.0008972696,0.003371536,0.001239112,0.001186573,0.0002856345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001880282,"about_ca_system_score_gemma":0.00182233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01416135,"about_ca_topic_score_gemma":0.008986278,"domain_scores_codex":[0.9975164,0.0008549782,0.0001480616,0.0004317489,0.0008784269,0.0001703789],"domain_scores_gemma":[0.9967578,0.002043884,0.000345812,0.00008280498,0.0006523311,0.0001173696],"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":[0.0001149711,0.0000482443,0.00261616,0.00009406941,0.00009313871,0.0001118827,0.000162014,0.8913996,0.001622485,0.02915885,0.0007968244,0.07378178],"study_design_scores_gemma":[0.000008899931,0.00001675388,0.0003701466,0.000014865,0.00002106583,0.00003018113,0.00001796951,0.9856051,0.0004288552,0.0130354,0.0004316132,0.00001925822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01288379,0.0002120508,0.9845847,0.000164746,0.00001872383,0.00005357117,0.00006931244,0.0001098844,0.001903116],"genre_scores_gemma":[0.7489758,0.0007651669,0.2468716,0.0001453128,0.00009972384,0.0002787736,0.0003014442,0.00003855285,0.002523528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01416135,"threshold_uncertainty_score":0.02815783,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2355356986","doi":"","title":"Radar Target Recognition by Using 2D Locality Sensitive Discriminant Analysis","year":2013,"lang":"en","type":"article","venue":"Electronics Optics & Control","topic":"Infrared Target Detection Methodologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Dimensionality reduction; Locality; Discriminant; Linear discriminant analysis; Radar; Principal component analysis; Computer science; Projection (relational algebra); Matrix (chemical analysis); Scatter matrix; Feature extraction; Class (philosophy); Mathematics; Feature (linguistics); Computer vision; Covariance matrix; Algorithm","authors":[{"name":"Yunlong Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0162373597427631,"gpt":0.2379873036180561,"spread":0.221749943875293,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003268624,0.0003786433,0.0005039484,0.001236009,0.0002108332,0.0004148315,0.0003029231,0.0002653406,0.0008035233],"category_scores_gemma":[0.0006446295,0.000202791,0.0004639456,0.0008493994,0.0002579865,0.0005667706,0.0004282354,0.0003202213,0.0005456364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001797284,"about_ca_system_score_gemma":0.000272117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001008669,"about_ca_topic_score_gemma":0.0008826139,"domain_scores_codex":[0.9996448,0.00007866095,0.00001346986,0.0000780238,0.0001461249,0.00003893086],"domain_scores_gemma":[0.9997404,0.00008132777,0.0000388869,0.0000353996,0.00008876099,0.00001520828],"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":[0.0002660965,0.000151127,0.003708152,0.0001497667,0.00007480065,0.0002181107,0.0001570488,0.06454878,0.2982144,0.006956463,0.003459306,0.6220959],"study_design_scores_gemma":[0.00001507241,0.00007960883,0.003248524,0.000004594231,0.0000201447,0.0002548367,0.00003800198,0.9626738,0.02922756,0.002677785,0.001726371,0.00003362804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06753279,0.0001621442,0.9298243,0.00008920005,0.0000309122,0.0000294731,0.00007885582,0.0007512927,0.001501061],"genre_scores_gemma":[0.647107,0.000276182,0.3499207,0.0000821914,0.0000517802,0.00007490045,0.0003049695,0.00008254465,0.002099717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001236009,"threshold_uncertainty_score":0.00268805,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}