{"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"},"query_hash":"29e8ddea9a6b","filters":{"venue":"Computers in Cardiology Conference"}},"results":[{"id":"W1548451947","doi":"","title":"Acute hypotension episode prediction using information divergence for feature selection, and non-parametric methods for classification","year":2009,"lang":"en","type":"article","venue":"Computers in Cardiology Conference","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carré Technologies (Canada)","funders":"","keywords":"Discriminative model; Divergence (linguistics); Event (particle physics); Pattern recognition (psychology); Artificial intelligence; Computer science; Feature selection; Parametric statistics; Kullback–Leibler divergence; Training set; Nonparametric statistics; Set (abstract data type); Data set; Feature (linguistics); Test set; Feature extraction; Data mining; Statistics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.04459204395439844,"gpt":0.3644855153392511,"spread":0.3198934713848526,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004089932,0.0001169787,0.0003178882,0.0002496532,0.0001058989,0.00001973092,0.00005708802,0.0002113365,2.089574e-7],"category_scores_gemma":[0.0001263795,0.0001104056,0.00005901228,0.00023848,0.00003453455,0.000157997,0.00001229315,0.000150523,2.681766e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100637,"about_ca_system_score_gemma":0.00006555469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006297614,"about_ca_topic_score_gemma":3.181009e-7,"domain_scores_codex":[0.9992514,0.00006786051,0.0002206369,0.0002240708,0.00005626145,0.0001797538],"domain_scores_gemma":[0.9992197,0.0001979318,0.00009778661,0.0001311598,0.0003000124,0.00005338073],"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":[0.0007636044,0.00003998229,0.06289337,0.0001105909,0.000196798,0.000002008258,0.0003899509,0.003773618,0.06573798,0.001000678,0.0006537287,0.8644377],"study_design_scores_gemma":[0.00111964,0.0004268119,0.2244891,0.00005221239,0.00007182533,0.00008228955,0.00001760304,0.7708468,0.0008342862,0.001375234,0.0005973681,0.00008678723],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2442629,0.00005305013,0.7541068,0.0003004716,0.0006219099,0.0005882463,0.00001110224,0.00003576147,0.00001971256],"genre_scores_gemma":[0.6812941,0.0001117942,0.3182476,0.000114246,0.0001270818,0.0000266336,0.00007016493,0.00000364123,0.000004809248],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8643509,"threshold_uncertainty_score":0.4502209,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2162358136","doi":"","title":"Comparative analysis of infrasonic cardiac signals","year":2009,"lang":"en","type":"article","venue":"Computers in Cardiology Conference","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Infrasound; Acoustics; Physics; Computer science; Cardiology; Geology; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.02783130147412537,"gpt":0.2601975190030509,"spread":0.2323662175289255,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003205026,0.0001246982,0.0008879316,0.0005315806,0.00004111361,0.00001886195,0.0002276961,0.0000866538,0.0003417152],"category_scores_gemma":[0.00001776719,0.0001123784,0.0002964087,0.001301294,0.0001315618,0.00007354326,0.000008527606,0.000153292,0.00002817259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004679011,"about_ca_system_score_gemma":0.00004581419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001906941,"about_ca_topic_score_gemma":0.0003802049,"domain_scores_codex":[0.9987453,0.0003196724,0.0003072719,0.0002821551,0.0001309504,0.0002146298],"domain_scores_gemma":[0.9992367,0.0002810566,0.0001098751,0.0002229299,0.0000825531,0.00006685641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002053649,0.000008158192,0.7736788,0.000002188267,0.0008081081,0.00001202213,0.0003476138,0.1918586,0.0001282639,0.0002785978,0.0001467863,0.03271028],"study_design_scores_gemma":[0.0001058993,0.0001128612,0.9047731,0.00000732986,0.0002096374,0.000001258167,0.0001198587,0.09382971,0.00007405956,0.0004018423,0.0002501757,0.0001142327],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701879,0.0005110481,0.01397054,0.0001008641,0.0002388891,0.00008624172,0.0000464007,0.00002799412,0.01483013],"genre_scores_gemma":[0.9989607,0.0001005808,0.000659358,0.0001558114,0.00003303655,4.25867e-7,0.00007166769,5.389183e-7,0.00001791066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1310943,"threshold_uncertainty_score":0.4582658,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}